CN113916186A - Deformation monitoring system and method based on GNSS and MEMS - Google Patents

Deformation monitoring system and method based on GNSS and MEMS Download PDF

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CN113916186A
CN113916186A CN202111526711.9A CN202111526711A CN113916186A CN 113916186 A CN113916186 A CN 113916186A CN 202111526711 A CN202111526711 A CN 202111526711A CN 113916186 A CN113916186 A CN 113916186A
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gnss
monitoring station
communication network
data
station
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CN113916186B (en
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黄坤
张永利
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Guangzhou Geoelectron Co ltd
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Guangzhou Geoelectron Co ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
    • G01B21/32—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring the deformation in a solid
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C9/00—Measuring inclination, e.g. by clinometers, by levels
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/02—Alarms for ensuring the safety of persons
    • G08B21/10—Alarms for ensuring the safety of persons responsive to calamitous events, e.g. tornados or earthquakes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/08—Testing, supervising or monitoring using real traffic

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  • Business, Economics & Management (AREA)
  • Emergency Management (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Life Sciences & Earth Sciences (AREA)
  • Environmental & Geological Engineering (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Alarm Systems (AREA)
  • Emergency Alarm Devices (AREA)

Abstract

The embodiment of the application discloses a deformation monitoring system and method based on a GNSS and an MEMS, which can accurately determine the danger degree of deformation of a GNSS monitoring station. The method comprises the following steps: when the cloud server detects that the first long-distance communication network is successfully connected and the second long-distance communication network is successfully connected, determining a first danger degree of deformation of a landslide area around the GNSS monitoring station; when the GNSS reference station detects that the second long-distance communication network fails to connect and the regional communication network succeeds to connect or when the GNSS monitoring station detects that the first long-distance communication network fails to connect and the regional communication network succeeds to connect, the GNSS reference station determines a second danger degree of deformation of a landslide region around the GNSS monitoring station; and when the GNSS monitoring station detects that the first long-distance communication network fails to connect and the regional communication network fails to connect, determining a third risk degree of deformation of a landslide region around the GNSS monitoring station.

Description

Deformation monitoring system and method based on GNSS and MEMS
Technical Field
The application relates to the technical field of safety monitoring, in particular to a deformation monitoring system and method based on GNSS and MEMS.
Background
Over time, monitoring points such as various reservoir dams, tailing reservoirs, mountain slopes, highway and railway bridges, high-voltage towers, communication iron towers, high-rise buildings and the like can deform to a greater or lesser extent. Therefore, deformation monitoring can be carried out on the monitoring stations arranged on the monitoring points, and therefore monitoring of the monitoring points is achieved.
In the correlation technique, if the monitoring station meets bad weather, then, can lead to can't accurate monitoring to the dangerous degree that this monitoring station takes place the deformation, lead to this monitoring station paralysis even to can't provide the safety guarantee for people's life and property, also can bring great economic loss for the country simultaneously.
Therefore, how to effectively determine the risk degree of deformation of the monitoring station becomes an urgent problem to be solved.
Disclosure of Invention
The embodiment of the application provides a deformation monitoring system and method based on a GNSS and an MEMS, which can more flexibly and accurately determine the danger degree of deformation of a GNSS monitoring station.
The first aspect of the embodiment of the application provides a deformation monitoring method based on a GNSS and an MEMS, which is applied to a deformation monitoring system, wherein the deformation monitoring system comprises a GNSS monitoring station of a global navigation satellite system, a GNSS reference station and a cloud server; the GNSS monitoring station is connected with the GNSS reference station through a regional communication network, the GNSS monitoring station is connected with the cloud server through a first long-distance communication network, and the GNSS reference station is connected with the cloud server through a second long-distance communication network; the method can comprise the following steps:
when the cloud server detects that the first long-distance communication network is successfully connected and the second long-distance communication network is successfully connected, the cloud server determines a first danger degree of deformation of a landslide area around the GNSS monitoring station;
when the GNSS reference station detects that the second long-distance communication network is failed to connect and the regional communication network is successfully connected, or when the GNSS monitoring station detects that the first long-distance communication network is failed to connect and the regional communication network is successfully connected, the GNSS reference station determines a second risk degree of deformation of a landslide area around the GNSS monitoring station;
when the GNSS monitoring station detects that the first long-distance communication network fails to connect and the area communication network fails to connect, the GNSS monitoring station determines a third risk degree of deformation of a landslide area around the GNSS monitoring station.
A second aspect of the embodiments of the present application provides a deformation monitoring system, which may include: the system comprises a global navigation satellite system GNSS monitoring station, a GNSS reference station and a cloud server; the GNSS monitoring station is connected with the GNSS reference station through a regional communication network, the GNSS monitoring station is connected with the cloud server through a first long-distance communication network, and the GNSS reference station is connected with the cloud server through a second long-distance communication network;
the cloud server is used for determining a first danger degree of deformation of a landslide area around the GNSS monitoring station when the first long-distance communication network is successfully connected and the second long-distance communication network is successfully connected;
the GNSS reference station is used for determining a second danger degree of deformation of a landslide area around the GNSS monitoring station when detecting that the second long-distance communication network fails to connect and the area communication network succeeds in connecting or when detecting that the first long-distance communication network fails to connect and the area communication network succeeds in connecting;
the GNSS monitoring station is used for determining a third danger degree of deformation of a landslide area around the GNSS monitoring station when the first long-distance communication network connection failure and the area communication network connection failure are detected.
A third aspect of embodiments of the present application provides a computer-readable storage medium, on which executable program code is stored, and when the executable program code is executed by a processor, the method according to the first aspect of embodiments of the present application is implemented.
A fourth aspect of the embodiments of the present application discloses a computer program product, which, when running on a computer, causes the computer to execute any one of the methods disclosed in the first aspect of the embodiments of the present application.
A fifth aspect of the embodiments of the present application discloses an application publishing platform, where the application publishing platform is configured to publish a computer program product, where when the computer program product runs on a computer, the computer is caused to execute any one of the methods disclosed in the first aspect of the embodiments of the present application.
According to the technical scheme, the embodiment of the application has the following advantages:
the deformation monitoring system is applied to the deformation monitoring system, and the deformation monitoring system comprises a global navigation satellite system GNSS monitoring station, a GNSS reference station and a cloud server; the GNSS monitoring station is connected with the GNSS reference station through a regional communication network, the GNSS monitoring station is connected with the cloud server through a first long-distance communication network, and the GNSS reference station is connected with the cloud server through a second long-distance communication network; the method comprises the following steps: when the cloud server detects that the first long-distance communication network is successfully connected and the second long-distance communication network is successfully connected, the cloud server determines a first danger degree of deformation of a landslide area around the GNSS monitoring station; when the GNSS reference station detects that the second long-distance communication network is failed to connect and the regional communication network is successfully connected, or when the GNSS monitoring station detects that the first long-distance communication network is failed to connect and the regional communication network is successfully connected, the GNSS reference station determines a second risk degree of deformation of a landslide area around the GNSS monitoring station; and when the GNSS monitoring station detects that the first long-distance communication network fails to connect and the regional communication network fails to connect, the GNSS monitoring station determines a third risk degree of deformation of a landslide region around the GNSS monitoring station. The GNSS monitoring station, the GNSS reference station and the cloud server respectively monitor the deformation condition of the GNSS monitoring station based on different communication network connection states, and the danger degree of deformation of the GNSS monitoring station can be determined more flexibly and accurately.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the embodiments and the drawings used in the description of the prior art, and obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained according to the drawings.
FIG. 1 is a schematic diagram of an embodiment of a deformation monitoring system in an embodiment of the present application;
FIG. 2 is a schematic diagram of an embodiment of a GNSS and MEMS based deformation monitoring method in the embodiment of the present application;
FIG. 3 is a schematic diagram of another exemplary GNSS and MEMS based deformation monitoring method in the embodiment of the present application;
FIG. 4 is a schematic diagram of another exemplary GNSS and MEMS based deformation monitoring method according to the embodiment of the present application;
FIG. 5 is a schematic diagram of another exemplary GNSS and MEMS based deformation monitoring method according to the embodiment of the present application;
fig. 6 is a schematic diagram of another embodiment of a deformation monitoring system in an embodiment of the present application.
Detailed Description
The embodiment of the application provides a deformation monitoring system and method based on a GNSS and an MEMS, which can more flexibly and accurately determine the danger degree of deformation of a GNSS monitoring station.
For a person skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, and not all embodiments. The embodiments in the present application shall fall within the protection scope of the present application.
It should be noted that the deformation monitoring System according to the embodiment of the present application may include, but is not limited to, a Global Navigation Satellite System (GNSS) monitoring station, a GNSS reference station, and a cloud server; the GNSS monitoring station and the GNSS reference station can be connected through a regional communication network, the GNSS monitoring station and the cloud server can be connected through a first long-distance communication network, and the GNSS reference station and the cloud server can be connected through a second long-distance communication network.
Exemplarily, as shown in fig. 1, a schematic diagram of an embodiment of a deformation monitoring system in an embodiment of the present application is shown. In fig. 1, the deformation monitoring system may include: the GNSS monitoring station 101, the GNSS reference station 102 and the cloud server 103. The GNSS monitoring station 101 is a communication tower, the GNSS monitoring station 101 and the GNSS reference station 102 can be connected through a local communication network, the GNSS monitoring station 101 and the cloud server 103 can be connected through a first long-distance communication network, and the GNSS reference station 102 and the cloud server 103 can be connected through a second long-distance communication network.
Wherein the monitoring points may include, but are not limited to, at least one of: reservoir dam, tailing pond, mountain slope, highway and railway bridge, high-voltage power tower, communication iron tower, high-rise building and the like. The GNSS monitoring station 101 may be set at each of the monitoring points, and the monitoring of the monitoring points may be implemented by monitoring the GNSS monitoring station 101.
Optionally, the GNSS monitoring station 101 may include a Micro Electro Mechanical System (MEMS), and the MEMS may include an attitude sensor, and the attitude sensor may be disposed inside the GNSS monitoring station 101. The attitude sensor may be configured to obtain attitude data of the GNSS monitoring station 101, where the attitude data may include tilt angle data of the GNSS monitoring station 101.
The attitude sensors may include, but are not limited to: an accelerometer and/or an inclinometer. Wherein, the accelerometer may also be called as an acceleration sensor, and the accelerometer may be used to acquire acceleration data of the GNSS monitoring station 101; the inclinometer, which may also be referred to as a tilt sensor, may be used to acquire tilt angle data for the GNSS monitoring station 101.
Optionally, the GNSS monitoring station 101 may further be provided with a weather sensor, and the weather sensor may be disposed outside the GNSS monitoring station 101. The weather sensor may be configured to acquire weather data around the GNSS monitoring station 101.
The weather sensor may include, but is not limited to, at least one of: rain gauges, crack gauges, moisture content monitors, water infiltration gauges, anemometers, thermometers, and hygrometers, to name a few. Wherein, the rain gauge can be used for acquireing the peripheral rainfall value of this GNSS monitoring station 101, the crack gauge can be used for acquireing the peripheral crack degree of this GNSS monitoring station 101, the water content monitoring meter can be used for acquireing the peripheral water level value of this GNSS monitoring station 101, the infiltration gauge can be used for acquireing the peripheral infiltration degree of this GNSS monitoring station 101, the anemograph can be used for acquireing the peripheral wind velocity value of this GNSS monitoring station 101, the thermometer can be used for acquireing the peripheral temperature value of this GNSS monitoring station 101, and the hygrometer can be used for acquireing the peripheral humidity value of this GNSS monitoring station 101.
It is to be understood that the weather data may include, but is not limited to, at least one of: rain amount value, crack degree, water level value, water seepage degree, wind speed value, humidity value and the like.
Optionally, the attitude sensor and the weather sensor may be connected to the GNSS monitoring station 101 through a regional communication network. Namely, the attitude sensor can send attitude data to the GNSS monitor through the regional communication network; the weather sensor may send weather data to the GNSS monitoring station 101 via the regional communication network.
Optionally, the GNSS monitoring station 101 may further include a GNSS antenna, and the GNSS antenna may be used to acquire GNSS observation data of the GNSS monitoring station 101. Wherein, the number of the GNSS antennas is not limited.
Optionally, the GNSS monitoring station 101 is further provided with an alarm, the alarm is connected to the GNSS monitoring station 101 through a regional communication network process, and the alarm may be configured to perform an early warning on the GNSS monitoring station 101 according to the early warning information. The alarm may be built in the GNSS monitoring station 101, or may be externally mounted on the GNSS monitoring station 101, which is not specifically limited herein.
Optionally, the alarm may include, but is not limited to, a voice alarm and/or a beep alarm.
Optionally, the GNSS monitoring station 101 may further include an Advanced RISC Machines (ARM) module of a first Reduced Instruction Set Computer (RISC).
Optionally, the first ARM module may be an embedded Linux operating system. The first ARM module may be configured to analyze data collected by the MEMS, analyze data collected by the weather sensor, analyze GNSS observation data, and upload the data or an analysis result obtained based on the data to the GNSS reference station 102 and/or the cloud server 103.
The GNSS reference station 102 may also include a second ARM module and/or an alarm. The second ARM module may be configured to analyze GNSS observation data and analyze data sent by the GNSS monitoring station 101; and upload these data or the analysis results obtained based on these data to the cloud server 103, and/or the second ARM module may be configured to issue the analysis results obtained from these data to the GNSS monitoring station 101.
The cloud server 103 may analyze data sent by the GNSS monitoring station 101, or may analyze data sent by the GNSS reference station 102, and issue an analysis result obtained based on the data to the GNSS monitoring station 101 and/or the GNSS reference station 102.
The local area network refers to a local area network. Optionally, the local communication network may include, but is not limited to, one of the following: radio communication networks, Long Range Radio (LoRa), and Wireless Fidelity (WiFi).
Long-range communication networks refer to non-local area networks. Optionally, the first long-range communication network may include, but is not limited to, one of the following: second Generation mobile communication technology (The 2nd Generation, 2G), third Generation mobile communication technology (The 3 rd Generation, 3G), fourth Generation mobile communication technology (The 4th Generation, 4G), fifth Generation mobile communication technology (The 5th Generation, 5G), beidou short message and The like.
Optionally, the second long-distance communication network may be the same as or different from the first long-distance communication network, and is not limited specifically herein.
In the following, the technical solution of the present application is further described by way of an embodiment, as shown in fig. 2, which is a schematic view of an embodiment of a deformation monitoring method based on GNSS and MEMS in the embodiment of the present application, and is applied to a deformation monitoring system, where the method may include:
201. when the cloud server detects that the first long-distance communication network is successfully connected and the second long-distance communication network is successfully connected, the cloud server determines a first danger degree of deformation of a landslide area around the GNSS monitoring station.
It should be noted that the first risk degree of deformation of the landslide region around the GNSS monitoring station refers to a first risk probability of deformation of the landslide region around the GNSS monitoring station.
Optionally, the deformation of the landslide area may include, but is not limited to, at least one of: landslide, horizontal displacement, settlement, inclination, crack, deflection, swing, vibration, and the like occur in a landslide area.
Optionally, when the cloud server detects that the first long-distance communication network is successfully connected and the second long-distance communication network is successfully connected, the cloud server determines a first risk degree of deformation of a landslide area around the GNSS monitoring station, which may include: when the cloud server detects that the first long-distance communication network is successfully connected and the second long-distance communication network is successfully connected, the cloud server receives first GNSS observation data, attitude data and weather data sent by the GNSS monitoring station and receives second GNSS observation data and a reference station state sent by the GNSS reference station; the cloud server determines a first danger degree of deformation of a landslide area around the GNSS monitoring station according to the first GNSS observation data, the attitude data, the weather data, the second GNSS observation data and the state of the reference station.
It can be understood that the cloud server may receive the first GNSS observation data, the attitude data, and the weather data sent by the GNSS monitoring station through the first long-distance communication network, and receive the second GNSS observation data and the reference station state sent by the GNSS reference station through the second long-distance communication network.
Optionally, the first GNSS observation data may include, but is not limited to, at least one of: a first pseudorange observation, a first carrier observation, and a first doppler observation.
Wherein the first pseudorange observation is an estimated distance between the satellite and the ground receiving station.
Pseudoranges may be measured by Time of Flight (TOF) techniques: the propagation time of the signal can be obtained according to the transmission time of the satellite transmission signal and the receiving time of the receiver receiving the signal, and the satellite-to-ground distance can be obtained by multiplying the propagation time by the propagation speed. However, clock error exists between the satellite clock and the receiver clock, and the signal is also influenced by factors such as atmospheric refraction during propagation, so the distance directly measured by the method can be the estimated distance between the satellite and the receiver.
The first carrier wave observation is the frequency of the electrical wave generated by the oscillator and transmitted over the communication channel, and the carrier wave is modulated to convey voice or other information.
The first doppler observation can be used to calculate a rate of motion of the receiver; when relative motion exists between the satellite and the receiver, the frequency of a signal received by the receiver is different from the frequency of a signal transmitted by the satellite, and the first doppler observation value is a difference value between the frequency of the signal received by the receiver and the frequency of the signal transmitted by the satellite, which can also be called doppler frequency shift; since the doppler shift is related to the rate of change of the distance between the satellite and the receiver, the first doppler observation can be used to calculate the velocity of the receiver.
Wherein, the receiver is the GNSS monitoring station.
In some embodiments, the GNSS monitoring station may periodically acquire first GNSS observation data, attitude data, and weather data using a GNSS antenna. The acquisition period may be set before the GNSS monitoring station leaves the factory, or may be customized by the user according to an empirical value, which is not specifically limited herein.
Optionally, the second GNSS observation data may include, but is not limited to, at least one of: a second pseudorange observation, a second carrier observation, and a second doppler observation.
Wherein the second pseudorange observation is an estimated distance from the satellite to the ground receiving station.
The second carrier wave observation is the frequency of the electrical wave generated by the oscillator and transmitted over the communication channel, and the carrier wave is modulated to convey voice or other information.
The second doppler observation can be used to calculate a rate of motion of the receiver.
Wherein the receiver is a GNSS reference station.
In some embodiments, after receiving second GNSS observation data transmitted by a satellite, a GNSS reference station sends the second GNSS observation data to a cloud server, and the cloud server receives the second GNSS observation data sent by the GNSS reference station.
It is appreciated that, because the GNSS monitoring station and the GNSS reference station are located at different locations, the first GNSS observation data collected by the GNSS monitoring station and the second GNSS observation data collected by the GNSS reference station are also different.
Optionally, the reference station status may include, but is not limited to: and the running state corresponding to the current time of the GNSS reference station.
Optionally, the cloud server determines, according to the first GNSS observation data, the attitude data, the weather data, the second GNSS observation data, and the reference station state, a first risk degree of deformation occurring in a landslide area around the GNSS monitoring station, and may include: the cloud server determines first GNSS displacement data of the GNSS monitoring station according to the first GNSS observation data and the second GNSS observation data; the cloud server determines a first danger degree of deformation of a landslide area around the GNSS monitoring station according to the first GNSS displacement data, the attitude data, the weather data and the state of the reference station.
It can be understood that, when the first GNSS displacement data indicates that the GNSS monitoring station is displaced, the cloud server determines a displacement variation corresponding to the GNSS monitoring station according to the first GNSS observation data and the second GNSS observation data.
In some embodiments, the cloud server determining, according to the first GNSS displacement data, the attitude data, the weather data, and the reference station state, a first risk level of deformation of a landslide area around the GNSS monitoring station may include: the cloud server obtains a first score according to the first GNSS displacement data and the attitude data based on the state of the reference station and the weather data; and the cloud server determines a first risk degree of deformation of a landslide area around the GNSS monitoring station according to the first score.
Optionally, the first score may be a value obtained by summing the first GNSS displacement data and the attitude data according to a certain ratio.
It will be appreciated that different reference station states and different weather data correspond to different first scores. The first score has a relationship with the first risk level. Optionally, the first score may correspond to different intervals, and each interval corresponds to one first risk degree, that is, different first scores correspond to different first risk degrees.
Exemplarily, (0, 2) is a first interval, and the first interval corresponds to a first risk degree of 0 to 5%; and [2, 4 ] is a second interval, the first danger degree corresponding to the second interval is 6% -10%, and the rest can be done in the same way.
Optionally, the cloud server determines, according to the first GNSS observation data, the attitude data, the weather data, the second GNSS observation data, and the reference station state, a first risk degree of deformation occurring in a landslide area around the GNSS monitoring station, and may include: the cloud server determines GNSS displacement data of the GNSS monitoring station according to the first GNSS observation data and the second GNSS observation data; the cloud server determines a first danger degree of deformation of a landslide area around the GNSS monitoring station according to the GNSS displacement data, the attitude data, the weather data and the state of the reference station by using a landslide deformation early warning model.
The landslide deformation early warning model is obtained by training based on a historical data set, the historical data set comprises a plurality of historical data and historical danger degrees corresponding to the historical data, and each historical data comprises at least one of GNSS displacement data, historical attitude data, historical weather data and historical reference station states.
It should be noted that, for the security monitoring of the GNSS monitoring station, the cloud server monitors the GNSS monitoring station by using data sent by the GNSS monitoring station on the one hand and by using data sent by the GNSS reference station on the other hand. On the premise that the collapse and slide deformation early warning model is obtained by the cloud server based on historical data set training. The cloud server utilizes the collapse and slide deformation early warning model to prejudge in advance under the condition that deformation occurs in the GNSS monitoring station, early warning can be carried out on the GNSS monitoring station in advance, and therefore the loss rate of the GNSS monitoring station is reduced.
The GNSS monitoring station monitoring system has the advantages that the safety performance of the GNSS monitoring station can be monitored even the connection state of the area communication network between the GNSS monitoring station and the GNSS reference station is uncertain when the cloud server detects that the first long-distance communication network is successfully connected and the second long-distance communication network is successfully connected, and accordingly the monitoring function of the deformation monitoring system on the GNSS monitoring station is perfected.
202. When the GNSS reference station detects that the second long-distance communication network is failed to connect and the regional communication network is successfully connected, or when the GNSS monitoring station detects that the first long-distance communication network is failed to connect and the regional communication network is successfully connected, the GNSS reference station determines a second danger degree of deformation of a landslide region around the GNSS monitoring station.
It should be noted that the second risk degree of deformation of the landslide region around the GNSS monitoring station refers to a second risk probability of deformation of the landslide region around the GNSS monitoring station.
Optionally, the determining, by the GNSS reference station, a second risk degree of deformation of a landslide area around the GNSS monitoring station may include: the GNSS reference station acquires a second GNSS observation number and receives first GNSS observation data, attitude data and weather data sent by the GNSS monitoring station through the regional communication network; and the GNSS reference station determines a second danger degree of deformation of a landslide area around the GNSS monitoring station according to the second GNSS observation number, the first GNSS observation data, the attitude data and the weather data.
It can be understood that, since the GNSS reference station is provided with the embedded Linux operating system, the GNSS reference station may determine the second GNSS displacement data of the GNSS monitoring station according to the second GNSS observation data and the first GNSS observation data by using the embedded Linux operating system; and the GNSS reference station determines a second danger degree of deformation of a landslide area around the GNSS monitoring station according to the second GNSS displacement data, the attitude data and the weather data. And when the second GNSS displacement data indicate that the GNSS monitoring station displaces, the GNSS reference station determines the displacement variation corresponding to the GNSS monitoring station according to the first GNSS observation data and the second GNSS observation data.
Optionally, the GNSS reference station obtains second GNSS displacement data according to the first GNSS observation data and the second GNSS observation data; the GNSS reference station obtains a second score according to the second GNSS displacement data and the attitude data based on the weather data; and the GNSS reference station determines a second risk degree of deformation of a landslide area around the GNSS monitoring station according to the second score.
Optionally, different weather data corresponds to different second scores. The second score may be a value obtained by summing the second GNSS displacement data and the attitude data according to a certain ratio.
It is understood that the second score has a relationship with the second risk level. Optionally, the second score may correspond to different intervals, and each interval corresponds to one second risk degree, that is, different second scores correspond to different second risk degrees.
It can be understood that, when detecting that the second long distance communication network connection fails and the regional communication network connection succeeds, the GNSS reference station can monitor the safety performance of the GNSS monitoring station even if the state of the first long distance communication network connection between the GNSS monitoring station and the cloud server is uncertain, or, when detecting that the first long distance communication network connection fails and the regional communication network connection succeeds, the safety performance of the GNSS monitoring station can be monitored even if the state of the second long distance communication network connection between the GNSS reference station and the cloud server is uncertain, thereby perfecting the monitoring function of the deformation monitoring system on the GNSS monitoring station.
203. When the GNSS monitoring station detects that the first long-distance communication network fails to connect and the area communication network fails to connect, the GNSS monitoring station determines a third risk degree of deformation of a landslide area around the GNSS monitoring station.
It should be noted that the third risk degree of deformation of the landslide region around the GNSS monitoring station refers to a third risk probability of deformation of the landslide region around the GNSS monitoring station.
Optionally, the determining, by the GNSS monitoring station, a third risk degree of deformation of a landslide area around the GNSS monitoring station may include: the GNSS monitoring station acquires weather data around the GNSS monitoring station acquired by the weather sensor and acquires attitude data of the GNSS monitoring station acquired by the attitude sensor; and the GNSS monitoring station determines a third risk degree of deformation of a landslide area around the GNSS monitoring station according to the weather data and the attitude data.
It is understood that the attitude data corresponding to different weather data is different, and the third risk level corresponding to different attitude data is also different. Because the weather data comprises at least one of a rain value, a crack degree, a water level value, a water seepage degree, a wind speed value and a humidity value, and the attitude data comprises at least one of a roll angle, a pitch angle and a course angle, the GNSS monitoring station can obtain a third score from the weather data and the attitude data; and the GNSS monitoring station determines a third risk degree of deformation of a landslide area around the GNSS monitoring station according to the third fraction.
Optionally, the third score may be a numerical value obtained by directly summing the weather data and the attitude data, may be a numerical value obtained by summing the weather data and the attitude data according to a certain proportion, or may be a numerical value obtained by averaging the weather data and the attitude data, which is not specifically limited herein.
It is understood that the third score has a relationship with the third risk level. Optionally, the third scores may correspond to different intervals, and each interval corresponds to one third risk degree, that is, different third scores correspond to different third risk degrees.
Optionally, the obtaining, by the GNSS monitoring station, the attitude data of the GNSS monitoring station acquired by using the attitude sensor may include: a GNSS monitoring station acquires tilt angle data of the GNSS monitoring station acquired by an accelerometer and/or an inclinometer.
Optionally, the acquiring, by the GNSS monitoring station, the inclination angle data of the GNSS monitoring station acquired by using the accelerometer may include: the method comprises the steps that a GNSS monitoring station acquires acceleration data of the GNSS monitoring station acquired by an accelerometer; and the GNSS monitoring station determines the inclination angle data of the GNSS monitoring station according to the acceleration data.
It is understood that the accelerometer may be a capacitive accelerometer or a variable gap accelerometer, and is not limited herein. If the GNSS monitoring station needs to acquire the inclination angle data by using the accelerometer, the GNSS monitoring station needs to acquire the acceleration data based on the accelerometer, and indirectly determine the inclination angle data of the GNSS monitoring station by using the inclination angle measurement principle.
Specifically, the inclination angle data is obtained by accelerometer sensitive gravity acceleration data, an accelerometer sensitive axis has a fixed direction relative to the GNSS monitoring station, and outputs acceleration data sensed in the fixed direction, that is, the accelerometer is affected by the gravity acceleration data when in a measurement balance state, and when the accelerometer output is inspected, a relationship needs to be established with the gravity acceleration data in size and direction, so as to measure the inclination angle data.
In some embodiments, a GNSS monitoring station acquires tilt angle data for the GNSS monitoring station acquired with an inclinometer.
The inclinometer can be an electronic inclinometer or a measuring instrument consisting of two communicated cylinders filled with liquid. The inclinometer can directly acquire inclination angle data of the GNSS monitoring station.
It should be noted that the GNSS monitoring station may indirectly acquire the tilt angle data according to the acceleration data acquired by the accelerometer, may directly acquire the tilt angle data according to the inclinometer, or may acquire the tilt angle data according to the accelerometer and the inclinometer at the same time, and then selects one of the acquired tilt angle data for use. No matter which way the GNSS monitoring station acquires the inclination angle data, the subsequent use of the GNSS monitoring station may be facilitated, and is not specifically limited herein.
Optionally, the attitude data may include, but is not limited to, at least one of a heading angle, a roll angle, and a pitch angle of the GNSS monitoring station relative to horizontal.
Optionally, the GNSS monitoring station determines, according to the weather data and the attitude data, a third risk level of deformation of a landslide area around the GNSS monitoring station, and may include but is not limited to at least one of the following implementation manners:
implementation mode 1: the GNSS monitoring station determines the roll angle and/or the pitch angle of the GNSS monitoring station according to the inclination angle data; and the GNSS monitoring station determines a third risk degree of deformation of a landslide area around the GNSS monitoring station according to the roll angle and/or the pitch angle and weather data.
It will be appreciated that the GNSS monitoring station may determine whether the tilt angle is roll or pitch based on the magnitude of the tilt value and the direction of the tilt in the tilt data.
Implementation mode 2: and the GNSS monitoring station determines the course angle of the GNSS monitoring station according to the first GNSS observation data.
It is to be appreciated that the GNSS monitoring station may determine a heading angle of the GNSS monitoring station based on at least one of the first pseudorange observations, the first carrier observations, and the first doppler observations in the first GNSS observation.
In step 203, since the GNSS monitoring station detects that the first long-distance communication network connection fails, the GNSS monitoring station and the cloud server perform data transmission, which can reduce transmission of network data, thereby reducing resource consumption pressure of the cloud server.
In addition, the above steps 201 and 203 may be performed simultaneously, or may be started in a hierarchical manner according to the state of the communication network, which is not limited herein.
Optionally, when the steps 201 and 203 are performed simultaneously, one of the following implementation manners may be further included:
implementation mode 1: the cloud server receives the third risk degree sent by the GNSS monitoring station and receives the second risk degree sent by the GNSS reference station; the cloud server determines the target risk degree of deformation of the landslide area around the GNSS monitoring station according to the first risk degree, the second risk degree and the third risk degree.
It can be understood that the cloud server may obtain a fourth score from the first risk level, the second risk level, and the third risk level; and the cloud server determines the target risk degree of deformation of a landslide area around the GNSS monitoring station according to the fourth fraction.
Optionally, the fourth score may be a numerical value obtained by directly summing the first risk degree, the second risk degree and the third risk degree by the cloud server, may be a numerical value obtained by summing the first risk degree, the second risk degree and the third risk degree according to a certain proportion, or may be a numerical value obtained by averaging the first risk degree, the second risk degree and the third risk degree, which is not specifically limited herein.
Wherein the fourth score has a relationship with the fourth risk level. Optionally, the fourth scores may correspond to different intervals, and each interval corresponds to a fourth risk degree, that is, different fourth scores correspond to different target risk degrees.
Implementation mode 2: the GNSS reference station receives the first risk degree sent by the cloud server and receives the third risk degree sent by the GNSS monitoring station; and the GNSS reference station determines the target risk degree of deformation of the landslide area around the GNSS monitoring station according to the first risk degree, the second risk degree and the third risk degree.
Implementation mode 3: the GNSS monitoring station receives the first risk degree sent by the cloud server and receives the second risk degree sent by the GNSS reference station; and the GNSS monitoring station determines the target risk degree of deformation of the landslide area around the GNSS monitoring station according to the first risk degree, the second risk degree and the third risk degree.
Implementation 2 is similar to implementation 1, and implementation 3 is similar to implementation 1, and is not specifically limited herein.
In any of the above-mentioned mode implementation manners 1 to 3, the GNSS monitoring station, the GNSS reference station and the cloud server are all configured to monitor the GNSS monitoring station at the same time, so that the safety performance of the GNSS monitoring station can be further ensured by improving the utilization rate of the deformation monitoring system.
In the embodiment of the application, the GNSS monitoring station, the GNSS reference station and the cloud server respectively monitor the deformation condition of the GNSS monitoring station based on different communication network connection states, so that the danger degree of deformation of the GNSS monitoring station can be determined more flexibly and accurately.
As shown in fig. 3, which is a schematic diagram of another embodiment of a GNSS and MEMS based deformation monitoring method in an embodiment of the present application, applied to a deformation monitoring system, the method may include:
301. when the cloud server detects that the first long-distance communication network is successfully connected and the second long-distance communication network is successfully connected, the cloud server determines a first danger degree of deformation of a landslide area around the GNSS monitoring station.
It should be noted that step 301 is similar to step 201 shown in fig. 2 in this embodiment, and is not described again here.
302. When the first danger degree is larger than a first preset danger degree threshold value, the cloud server carries out early warning on the GNSS monitoring station and sends first early warning information to the GNSS reference station and the GNSS monitoring station.
It should be noted that the first preset risk threshold may be set before the cloud server leaves a factory, or may be customized on the cloud server by the user according to the actual situation of the GNSS monitoring station, and is not specifically limited here.
In some embodiments, the cloud server is connected to the GNSS monitoring station through a first long-distance communication network, the cloud server is connected to the GNSS reference station through a second long-distance communication network, and the cloud server detects that a first risk degree of deformation of a landslide region around the GNSS monitoring station is high, so that the cloud server can generate first early warning information to the GNSS reference station through the first long-distance communication network and send the first early warning information to the GNSS monitoring station through the second long-distance communication network while early warning the GNSS monitoring station.
The method comprises the steps that a cloud server sends first early warning information to a GNSS reference station and then sends the first early warning information to a GNSS monitoring station; the first early warning information can be sent to the GNSS monitoring station firstly, and then the first early warning information can be sent to the GNSS reference station; the first warning information may also be sent to the GNSS reference station and the GNSS monitoring station at the same time, which is not specifically limited herein.
303. The GNSS reference station receives first early warning information sent by the cloud server, and early warning is carried out on the GNSS monitoring station according to the first early warning information.
It can be understood that, when the alarm is arranged on the GNSS reference station, the GNSS reference station can receive the first early warning information sent by the cloud server through the second long-distance communication network, and then utilize the alarm according to the first early warning information to perform early warning on the GNSS monitoring station. Therefore, the GNSS reference station can perform early warning on the GNSS monitoring station with the cloud server, and the safety performance of the GNSS monitoring station is improved.
304. The GNSS monitoring station receives first early warning information sent by the cloud server and carries out early warning on the GNSS monitoring station according to the first early warning information.
Optionally, the GNSS monitoring station performs the early warning on the GNSS monitoring station according to the first early warning information, which may include but is not limited to at least one of the following implementation manners:
implementation mode 1: and the GNSS monitoring station performs early warning on the GNSS monitoring station by using an alarm according to the first early warning information.
Implementation mode 2: the GNSS monitoring station sends first early warning information to electronic equipment related to the GNSS monitoring station, so that the electronic equipment can perform early warning on the GNSS monitoring station according to the first early warning information.
Optionally, the electronic device may be a terminal device or a wearable device, and is not limited in this respect.
The GNSS monitoring station can receive first early warning information sent by the cloud server through the first long-distance communication network, and then utilizes the alarm to perform early warning on the GNSS monitoring station according to the first early warning information, and/or utilizes electronic equipment related to the GNSS monitoring station to perform early warning on the GNSS monitoring station. Therefore, the GNSS monitoring station can perform early warning on the GNSS monitoring station with the cloud server, and the safety performance of the GNSS monitoring station is improved.
It should be noted that steps 303 and 304 are not limited in timing.
It can be understood that, when step 303 and step 304 are executed simultaneously, the GNSS monitoring station, the GNSS reference station, and the cloud server may perform early warning on the GNSS monitoring station simultaneously, so that the security performance of the GNSS monitoring station may be ensured to a great extent.
In the embodiment of the application, in the whole deformation monitoring system, the priority of the cloud server is higher than that of the GNSS reference station and the GNSS monitoring station, so that the cloud server can send first early warning messages to the GNSS monitoring station and the GNSS reference station when early warning is carried out on the GNSS monitoring station, so that the GNSS monitoring station and the GNSS reference station can carry out early warning on the GNSS monitoring station simultaneously, the loss rate of the GNSS monitoring station can be reduced, and meanwhile, the safety performance of the GNSS monitoring station is strengthened and ensured.
As shown in fig. 4, which is a schematic diagram of another embodiment of a GNSS and MEMS based deformation monitoring method in an embodiment of the present application, applied to a deformation monitoring system, the method may include:
401. when the GNSS reference station detects that the second long-distance communication network is failed to connect and the regional communication network is successfully connected, or when the GNSS monitoring station detects that the first long-distance communication network is failed to connect and the regional communication network is successfully connected, the GNSS reference station determines a second danger degree of deformation of a landslide region around the GNSS monitoring station.
It should be noted that step 401 is similar to step 202 shown in fig. 2 in this embodiment, and is not described here again.
402. And when the second danger degree is greater than a second preset danger degree threshold value, the GNSS reference station gives an early warning to the GNSS monitoring station and sends second early warning information to the GNSS monitoring station.
It should be noted that the second preset risk threshold may be set before the GNSS reference station leaves the factory, or may be customized on the GNSS reference station by the user according to the actual situation of the GNSS monitoring station, and the second preset risk threshold may be the same as or different from the first preset risk threshold, and is not specifically limited herein.
In some embodiments, the GNSS reference station is connected to the GNSS monitoring station through a regional communication network, and the GNSS reference station detects that a second risk degree of deformation of a landslide region around the GNSS monitoring station is high, so that the GNSS reference station can send second warning information to the GNSS monitoring station through the regional communication network while warning the GNSS monitoring station.
403. And the GNSS monitoring station receives second early warning information sent by the GNSS reference station and carries out early warning on the GNSS monitoring station according to the second early warning information.
Optionally, the GNSS monitoring station performs the early warning on the GNSS monitoring station according to the second early warning information, which may include but is not limited to at least one of the following implementation manners:
implementation mode 1: and the GNSS monitoring station performs early warning on the GNSS monitoring station by using the alarm according to the second early warning information.
Implementation mode 2: and the GNSS monitoring station sends second early warning information to the electronic equipment related to the GNSS monitoring station, so that the electronic equipment can perform early warning on the GNSS monitoring station according to the second early warning information.
It can be understood that the GNSS monitoring station may receive the second warning information sent by the GNSS reference station through the regional communication network, and then perform warning on the GNSS monitoring station by using the alarm according to the second warning information, and/or perform warning on the GNSS monitoring station by using the electronic device related to the GNSS monitoring station. Therefore, the GNSS monitoring station and the GNSS reference station can perform early warning on the GNSS monitoring station at the same time, and the safety performance of the GNSS monitoring station is improved.
In this application embodiment, because the high in the clouds server can't carry out the early warning to this GNSS monitoring station, so, in whole deformation monitoring system, the priority of GNSS reference station is higher than the GNSS monitoring station, so, when the GNSS reference station carries out the early warning to the GNSS monitoring station, can send second early warning message to this GNSS monitoring station to make this GNSS monitoring station carry out the early warning to this GNSS monitoring station simultaneously, can reduce the loss rate of this GNSS monitoring station like this, and simultaneously, strengthen the security performance who ensures this GNSS monitoring station.
As shown in fig. 5, which is a schematic diagram of another embodiment of a GNSS and MEMS based deformation monitoring method in an embodiment of the present application, applied to a deformation monitoring system, the method may include:
501. when the GNSS monitoring station detects that the first long-distance communication network fails to connect and the area communication network fails to connect, the GNSS monitoring station determines a third risk degree of deformation of a landslide area around the GNSS monitoring station.
It should be noted that step 501 is similar to step 203 shown in fig. 2 in this embodiment, and is not described here again.
502. And when the third danger degree is greater than a third preset danger degree threshold value, the GNSS monitoring station utilizes the alarm to perform early warning on the GNSS monitoring station.
It should be noted that the third preset risk degree threshold may be set before the GNSS monitoring station leaves the factory, or may be customized by the user on the GNSS monitoring station according to the actual situation of the GNSS monitoring station, and the third preset risk degree threshold may be the same as or different from the second preset risk degree threshold, and is not specifically limited herein.
Optionally, the GNSS monitoring station performs early warning on the GNSS monitoring station, and may further include: and the GNSS monitoring station sends third early warning information to the electronic equipment related to the GNSS monitoring station.
It can be understood that the GNSS monitoring station can separately guarantee the safety performance of the GNSS monitoring station.
In the embodiment of the application, the cloud server and the GNSS reference station cannot perform early warning on the GNSS monitoring station, so that the deformation condition of the GBSS monitoring station can be only early warned by the GNSS monitoring station in the whole deformation monitoring system, the loss rate of the GNSS monitoring station is reduced, and meanwhile, the safety performance of the GNSS monitoring station is guaranteed.
As shown in fig. 6, which is a schematic diagram of another embodiment of a deformation monitoring system in an embodiment of the present application, the deformation monitoring system may include a global navigation satellite system GNSS monitoring station 101, a GNSS reference station 102, and a cloud server 103; the GNSS monitoring station 101 is connected with the GNSS reference station 102 through a regional communication network, the GNSS monitoring station 101 is connected with the cloud server 103 through a first long-distance communication network, and the GNSS reference station 102 is connected with the cloud server 103 through a second long-distance communication network;
the cloud server 103 is configured to determine a first risk degree of deformation of a landslide area around the GNSS monitoring station 101 when it is detected that the first long-distance communication network is successfully connected and the second long-distance communication network is successfully connected;
the GNSS reference station 102 is configured to determine a second risk degree of deformation of a landslide area around the GNSS monitoring station 101 when it is detected that the second long-distance communication network fails to connect and the area communication network succeeds to connect, or when the GNSS monitoring station 101 detects that the first long-distance communication network fails to connect and the area communication network succeeds to connect;
the GNSS monitoring station 101 is configured to determine a third risk degree of deformation of a landslide area around the GNSS monitoring station 101 when it is detected that the first long-distance communication network connection fails and the area communication network connection fails.
Alternatively, in some embodiments of the present application,
the cloud server 103 is specifically configured to receive first GNSS observation data, attitude data and weather data sent by the GNSS monitoring station 101, and receive second GNSS observation data and a reference station state sent by the GNSS reference station 102 when it is detected that the first long-distance communication network is successfully connected and the second long-distance communication network is successfully connected; and determining a first danger degree of deformation of a landslide area around the GNSS monitoring station 101 according to the first GNSS observation data, the attitude data, the weather data, the second GNSS observation data and the state of the reference station.
Alternatively, in some embodiments of the present application,
the cloud server 103 is specifically configured to determine GNSS displacement data of the GNSS monitoring station 101 according to the first GNSS observation data and the second GNSS observation data; determining a first risk degree of deformation of a landslide area around the GNSS monitoring station 101 according to the GNSS displacement data, the attitude data, the weather data and the state of the reference station by using a landslide deformation early warning model; the landslide deformation early warning model is obtained by training based on a historical data set, the historical data set comprises a plurality of historical data and historical danger degrees corresponding to the historical data, and each historical data comprises at least one of GNSS displacement data, historical attitude data, historical weather data and historical reference station states.
Alternatively, in some embodiments of the present application,
the cloud server 103 is further configured to perform early warning on the GNSS monitoring station 101 when the first risk degree is greater than a first preset risk degree threshold value, and send first early warning information to the GNSS reference station 102 and the GNSS monitoring station 101;
the GNSS reference station 102 is further configured to receive first early warning information sent by the cloud server 103, and perform early warning on the GNSS monitoring station 101 according to the first early warning information;
the GNSS monitoring station 101 is further configured to receive first warning information sent by the cloud server 103, and perform warning on the GNSS monitoring station 101 according to the first warning information.
Alternatively, in some embodiments of the present application,
the GNSS reference station 102 is specifically configured to obtain a second GNSS observation number, and receive first GNSS observation data, attitude data, and weather data sent by the GNSS monitoring station 101 through the local communication network; and determining a second danger degree of deformation of a landslide area around the GNSS monitoring station 101 according to the second GNSS observation number, the first GNSS observation data, the attitude data and the weather data.
Alternatively, in some embodiments of the present application,
the GNSS reference station 102 is further configured to perform early warning on the GNSS monitoring station 101 when the second risk degree is greater than a second preset risk degree threshold, and send second early warning information to the GNSS monitoring station 101;
the GNSS monitoring station 101 is further configured to receive second warning information sent by the GNSS reference station 102, and perform warning on the GNSS monitoring station 101 according to the second warning information.
Alternatively, in some embodiments of the present application,
the GNSS monitoring station 101 comprises a micro-electro-mechanical system (MEMS) comprising an attitude sensor for acquiring attitude data of the GNSS monitoring station 101; the GNSS monitoring station 101 is also provided with a weather sensor, and the weather sensor is used for acquiring weather data around the GNSS monitoring station 101;
the GNSS monitoring station 101 is specifically configured to acquire weather data around the GNSS monitoring station 101 acquired by using the weather sensor, and acquire attitude data of the GNSS monitoring station 101 acquired by using the attitude sensor; and determining a third risk degree of deformation of the landslide area around the GNSS monitoring station 101 according to the weather data and the attitude data.
Alternatively, in some embodiments of the present application,
the GNSS monitoring station 101 is also provided with an alarm,
the GNSS monitoring station 101 is further configured to, when the third risk level is greater than a third preset risk level threshold, perform early warning on the GNSS monitoring station 101 by using the alarm.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product.
The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can store or a data storage device, such as a server, a data center, etc., that is integrated with one or more available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.

Claims (10)

1. A deformation monitoring method based on GNSS and MEMS is characterized in that the deformation monitoring method is applied to a deformation monitoring system, wherein the deformation monitoring system comprises a global navigation satellite system GNSS monitoring station, a GNSS reference station and a cloud server; the GNSS monitoring station is connected with the GNSS reference station through a regional communication network, the GNSS monitoring station is connected with the cloud server through a first long-distance communication network, and the GNSS reference station is connected with the cloud server through a second long-distance communication network; the method comprises the following steps:
when the cloud server detects that the first long-distance communication network is successfully connected and the second long-distance communication network is successfully connected, the cloud server determines a first danger degree of deformation of a landslide area around the GNSS monitoring station;
when the GNSS reference station detects that the second long-distance communication network is failed to connect and the regional communication network is successfully connected, or when the GNSS monitoring station detects that the first long-distance communication network is failed to connect and the regional communication network is successfully connected, the GNSS reference station determines a second risk degree of deformation of a landslide area around the GNSS monitoring station;
and when the GNSS monitoring station detects that the first long-distance communication network fails to connect and the regional communication network fails to connect, the GNSS monitoring station determines a third risk degree of deformation of a landslide region around the GNSS monitoring station.
2. The method of claim 1, wherein the determining, by the cloud server, the first risk level of deformation of the landslide area around the GNSS monitoring station when the cloud server detects that the first long-range communication network connection is successful and the second long-range communication network connection is successful comprises:
when the cloud server detects that the first long-distance communication network is successfully connected and the second long-distance communication network is successfully connected, the cloud server receives first GNSS observation data, attitude data and weather data sent by the GNSS monitoring station and receives second GNSS observation data and a reference station state sent by the GNSS reference station;
and the cloud server determines a first danger degree of deformation of a landslide area around the GNSS monitoring station according to the first GNSS observation data, the attitude data, the weather data, the second GNSS observation data and the state of the reference station.
3. The method of claim 2, wherein the cloud server determining a first risk level of deformation of a landslide area around the GNSS monitoring station based on the first GNSS observation data, the attitude data, the weather data, the second GNSS observation data, and the reference station status comprises:
the cloud server determines GNSS displacement data of the GNSS monitoring station according to the first GNSS observation data and the second GNSS observation data;
the cloud server determines a first risk degree of deformation of a landslide area around the GNSS monitoring station according to the GNSS displacement data, the attitude data, the weather data and the state of the reference station by using a landslide deformation early warning model;
the landslide deformation early warning model is obtained by training based on a historical data set, the historical data set comprises a plurality of historical data and historical danger degrees corresponding to the historical data, and each historical data comprises at least one of GNSS displacement data, historical attitude data, historical weather data and historical reference station states.
4. The method of claim 3, further comprising:
when the first danger degree is larger than a first preset danger degree threshold value, the cloud server carries out early warning on the GNSS monitoring station and sends first early warning information to the GNSS reference station and the GNSS monitoring station;
the GNSS reference station receives first early warning information sent by the cloud server and carries out early warning on the GNSS monitoring station according to the first early warning information;
the GNSS monitoring station receives first early warning information sent by the cloud server and carries out early warning on the GNSS monitoring station according to the first early warning information.
5. The method of claim 1, wherein the GNSS reference station determining a second risk level of deformation of a landslide area surrounding the GNSS monitoring station comprises:
the GNSS reference station acquires a second GNSS observation number and receives first GNSS observation data, attitude data and weather data sent by the GNSS monitoring station through the regional communication network;
and the GNSS reference station determines a second danger degree of deformation of a landslide area around the GNSS monitoring station according to the second GNSS observation number, the first GNSS observation data, the attitude data and the weather data.
6. The method of claim 5, further comprising:
when the second danger degree is larger than a second preset danger degree threshold value, the GNSS reference station gives an early warning to the GNSS monitoring station and sends second early warning information to the GNSS monitoring station;
and the GNSS monitoring station receives second early warning information sent by the GNSS reference station and carries out early warning on the GNSS monitoring station according to the second early warning information.
7. The method of claim 1, wherein the GNSS monitoring station comprises a micro-electro-mechanical system (MEMS) comprising an attitude sensor for acquiring attitude data of the GNSS monitoring station; the GNSS monitoring station is also provided with a weather sensor, and the weather sensor is used for acquiring weather data around the GNSS monitoring station;
the GNSS monitoring station determines a third risk degree of deformation of a landslide area around the GNSS monitoring station, and the third risk degree comprises the following steps:
the GNSS monitoring station acquires weather data around the GNSS monitoring station acquired by the weather sensor and acquires attitude data of the GNSS monitoring station acquired by the attitude sensor;
and the GNSS monitoring station determines a third risk degree of deformation of a landslide area around the GNSS monitoring station according to the weather data and the attitude data.
8. The method of claim 7, wherein the GNSS monitoring station is further provided with an alarm, the method further comprising:
and when the third danger degree is greater than a third preset danger degree threshold value, the GNSS monitoring station utilizes the alarm to perform early warning on the GNSS monitoring station.
9. A deformation monitoring system is characterized by comprising a Global Navigation Satellite System (GNSS) monitoring station, a GNSS reference station and a cloud server; the GNSS monitoring station is connected with the GNSS reference station through a regional communication network, the GNSS monitoring station is connected with the cloud server through a first long-distance communication network, and the GNSS reference station is connected with the cloud server through a second long-distance communication network;
the cloud server is used for determining a first danger degree of deformation of a landslide area around the GNSS monitoring station when the first long-distance communication network is successfully connected and the second long-distance communication network is successfully connected;
the GNSS reference station is used for determining a second risk degree of deformation of a landslide area around the GNSS monitoring station when the second long-distance communication network connection failure and the area communication network connection success are detected, or when the GNSS monitoring station detects the first long-distance communication network connection failure and the area communication network connection success are detected;
and the GNSS monitoring station is used for determining a third danger degree of deformation of a landslide area around the GNSS monitoring station when the first long-distance communication network connection fails and the area communication network connection fails.
10. A computer-readable storage medium having executable program code stored thereon, wherein the executable program code, when executed by a processor, implements the method of any of claims 1-8.
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20150309161A1 (en) * 2014-04-24 2015-10-29 Eni S.P.A. Method and system for the remote monitoring of the two/three-dimensional field of displacements and vibrations of objects/structures
CN106767661A (en) * 2016-11-09 2017-05-31 广州中海达定位技术有限公司 A kind of base station of the deformation monitoring based on GNSS technologies, monitoring station and system
CN107192328A (en) * 2017-05-17 2017-09-22 千寻位置网络有限公司 Deformation monitoring terminal device and implementation method based on dual communication module
CN109443188A (en) * 2018-09-29 2019-03-08 桂林电子科技大学 A kind of double-layer multi-dimensional landslide monitoring method
CN110017765A (en) * 2019-05-29 2019-07-16 中国地质环境监测院 A kind of mixed positioning landslide deformation monitoring system
CN112903008A (en) * 2021-01-15 2021-06-04 泉州师范学院 Mountain landslide early warning method based on multi-sensing data fusion technology

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20150309161A1 (en) * 2014-04-24 2015-10-29 Eni S.P.A. Method and system for the remote monitoring of the two/three-dimensional field of displacements and vibrations of objects/structures
CN106767661A (en) * 2016-11-09 2017-05-31 广州中海达定位技术有限公司 A kind of base station of the deformation monitoring based on GNSS technologies, monitoring station and system
CN107192328A (en) * 2017-05-17 2017-09-22 千寻位置网络有限公司 Deformation monitoring terminal device and implementation method based on dual communication module
CN109443188A (en) * 2018-09-29 2019-03-08 桂林电子科技大学 A kind of double-layer multi-dimensional landslide monitoring method
CN110017765A (en) * 2019-05-29 2019-07-16 中国地质环境监测院 A kind of mixed positioning landslide deformation monitoring system
CN112903008A (en) * 2021-01-15 2021-06-04 泉州师范学院 Mountain landslide early warning method based on multi-sensing data fusion technology

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