CN110672028A - Device and method for monitoring deformation of high-steep rock mass body - Google Patents
Device and method for monitoring deformation of high-steep rock mass body Download PDFInfo
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Abstract
The invention discloses a monitoring device for deformation of a high and steep rock mass body, which comprises a data acquisition unit, a data processing control unit, a data monitoring unit and a neural network prediction unit, wherein the data acquisition unit, the data processing control unit, the data monitoring unit and the neural network prediction unit are sequentially connected; the invention also provides a method for monitoring the deformation of the high-steep-risk rock mass block, which is used for monitoring the whole or local block of the high-steep-risk rock mass block in real time by combining the advanced optical fiber sensor technology, the data processing control technology and the intelligent neural network algorithm technology. The device has the advantages of small volume, high precision and low power consumption, can realize 24-hour uninterrupted automatic real-time monitoring, can operate the device on site, is simple and practical, has a friendly human-computer interaction interface, and can help site monitoring personnel to know the dangerous rock embodying field deformation condition in the first time.
Description
Technical Field
The invention relates to the field of dangerous rock mass deformation monitoring, in particular to a device and a method for monitoring deformation of a high-steep dangerous rock mass body.
Background
At present, China is accelerating the development of hydraulic and hydroelectric engineering, but in the development process and the operation period of the hydraulic and hydroelectric engineering, collapse, landslide and debris flow geological disasters are inevitable, and high and steep slopes and dangerous rock body collapse in the hydraulic and hydroelectric engineering field are important geological disasters in the hydroelectric engineering field. Serious casualties and serious economic losses are caused by the fact that serious disaster events caused by the instability of dangerous rock masses are also in endless.
Deformation monitoring of dangerous rock masses on high and steep slopes is always important research content in the field of water conservancy and hydropower engineering, and the main technical method for monitoring the dangerous rock masses mainly comprises macroscopic monitoring and microscopic monitoring. The macroscopic monitoring mainly utilizes video monitoring equipment to observe whether the dangerous rock mass changes on a large scale or not, and on one hand, the microscopic monitoring can utilize three-dimensional laser scanning and oblique photography to regularly scan the dangerous rock mass, so that the dangerous rock mass can be regularly scanned, and the deformation monitoring of the dangerous rock mass is realized through later software processing; on the other hand, the microscopic monitoring is mainly realized by monitoring the specific deformation of the dangerous rock mass, such as crack displacement monitoring and dangerous rock mass comparative deformation monitoring, and combining anchor cable and anchor rod stress monitoring after the dangerous rock mass is subjected to a supporting structure, and the specific deformation condition of the dangerous rock mass can also be directly monitored.
A novel monitoring technology developed in recent years by a three-dimensional laser scanning technology belongs to non-contact measurement, and the method mainly utilizes a laser ranging principle to quickly and accurately acquire dangerous rock mass point cloud data in different periods, then establishes a high-accuracy three-dimensional model through some post-processing methods, and comprehensively masters the dynamic change process and deformation characteristics of dangerous rock masses.
Oblique photography platform passes through the different angles of high-definition camera lens shooting danger rock mass, acquire the earth's surface information of danger rock mass, oblique photography platform generally carries on unmanned aerial vehicle, set for through carrying out the airline to the unmanned aerial vehicle platform, the fixed point is exposed, set for different shooting angles and realize forward, oblique photography, can carry out corresponding data processing with the photo after accomplishing the shooting, form the real three-dimensional model of dangerous rock mass, image data such as digital model, after scanning through the unscheduled, can compare the analysis to several period data, and then calculate the concrete deformation change of danger rock mass.
The utility model discloses a patent is granted and is announced No. CN204496658U and discloses a dangerous rock collapse monitoring and early warning device relates to dangerous rock monitoring technology field, mainly includes proruption supervisory equipment and slow deformation numerical value change supervisory equipment, can realize the whole situation of change monitoring that dangerous rock mass collapses. The method has the main defects that the accuracy of the dangerous rock is to be improved through image acquisition and analysis and remote judgment, the deformation value can be only estimated, and the analysis and early warning of the collapse dangerous rock trend are not realized.
Utility model patent grant publication No. CN205561791U discloses a device based on displacement and pressure sensor detect dangerous rock mass and collapse, mainly detects the mechanics change monitoring and the motion trend monitoring of dangerous rock mass. The method has the main defects that the method aims at monitoring the deformation of the high and steep dangerous rocks, the arrangement difficulty is high, the construction condition is inconvenient, each block cannot be monitored, the monitoring precision of a displacement sensor and a pressure sensor is not described, and the monitoring effect of the dangerous rocks is seriously influenced due to large precision deviation.
The invention discloses an early warning system for dangerous rock collapse monitoring, which mainly comprises a moving device, a conducting device and a displacement monitoring device. The device has the main defects that the device has the basic function of monitoring and alarming the dangerous rock collapse, has higher requirements on the dangerous rock collapse body during installation, can monitor the dangerous rock collapse body only by a proper construction surface, and cannot monitor and calculate the deformation of the dangerous rock collapse body.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a device and a method for monitoring the deformation of a high-steep dangerous rock mass body, which mainly apply an advanced optical fiber arrangement technology to effectively monitor the high-steep dangerous rock mass body, and provide a reasonable and effective arrangement method after the high-steep dangerous rock mass body is investigated and identified in advance.
In order to achieve the above object, the present invention adopts the following technical solutions.
The monitoring device for the deformation of the high and steep dangerous rock mass body comprises a data acquisition unit, a data processing control unit, a data monitoring unit and a neural network prediction unit, wherein the data acquisition unit comprises a broadband light source, an optical fiber grating sensor and a data acquisition module, the data processing control unit comprises a data processing module, a synchronous control unit, an optical pulse transmitting module, a laser, an optical path coupler, an optical splitter, an optical filter and a light source receiving module, the data monitoring unit comprises a data transmission module and a data monitoring center, the data processing control unit transmits specific deformation monitoring data to the data monitoring center through the data transmission module, the neural network prediction unit comprises a monitoring data preprocessing module and a BP neural network prediction module, and the data acquisition unit, the data processing control unit, the neural network prediction unit and the data processing control unit are connected in series and parallel, The data monitoring unit and the neural network prediction unit are sequentially connected.
Further, the data acquisition unit comprises a plurality of fiber grating sensors which are sequentially connected through the optical fibers, and the optical fibers and the fiber grating sensors are directly fixed on the high-steep dangerous rock mass body.
Furthermore, one end of the data acquisition unit is provided with a plurality of broadband light sources, the broadband light sources are uniformly arranged at the bottom edge of the mountain body, the other end of the data acquisition unit is connected with the data acquisition module through the optical fiber, and the data acquisition module is arranged at the top of the mountain body.
Further, the data processing control unit analyzes the data acquired by the data acquisition unit and judges which distance and block are deformed.
Further, the monitoring data preprocessing module carries out simple data preprocessing on the temperature data and the strain data acquired on site, and then sends the data to the BP neural network prediction model for data analysis and processing, and the movement trend of the high-steep rock mass is calculated.
A method for monitoring deformation of a high-steep rock mass body comprises the following steps:
s1, surveying and identifying the high-steep-risk rock mass body in advance, sequentially connecting a plurality of fiber grating sensors through optical fibers, directly fixing the optical fibers and the fiber grating sensors to the high-steep-risk rock mass body, connecting the input end of the optical fibers with the broadband light source, connecting the output end of the optical fibers with the data acquisition module, and acquiring deformation monitoring data of the high-steep-risk rock mass body by the data acquisition module;
s2, the data processing module drives the light pulse emitting module in real time through the synchronous control unit to drive a light pulse signal with larger power to the laser, the laser is input into a tail fiber of the measuring optical fiber, the optical pulse passing through the tail fiber needs to directly enter a measured light line through the optical path coupler, the scattered light carrying deformation monitoring data returns to the optical splitter through the optical path coupler, the optical splitter mainly comprises optical filters with different central wavelengths, the scattered light with different resolution is transmitted to the light source receiving module, the light source receiving module simply processes the light source data and then transmits the processed data to the data processing module, the data processing module can analyze the light source data at the first time and judge which distance and which block are deformed;
s3, the data processing module may further transmit the specific deformation monitoring data to the background data monitoring center through the data transmission module, and the data monitoring center performs depth analysis and processing on the detected optical fiber monitoring data according to a strong calculation capability;
s4, adding a neural network algorithm into data analysis by the data monitoring center, performing simple data preprocessing on the temperature data and the strain data acquired on site according to the requirement of the neural network algorithm to form two-dimensional input discrete variables, sending the discrete variables into the BP neural network prediction model, performing data fitting and trend analysis by the BP neural network prediction model according to the received processed data, and calculating the motion trend of the high-steep rock mass.
Furthermore, the data processing module can also realize real-time monitoring data query in a dangerous rock embodying field, the data processing module starts the laser to input light pulses into the optical fiber to be tested by sending the light pulse signals to the synchronous control unit, then returns to the data processing module again through conversion of a series of light signals and electric signals, and directly measures the dangerous rock body deformation data in the current mode through field real-time analysis and pre-judgment.
The invention has the following beneficial effects: the device is combined with an advanced optical fiber sensor technology, a data processing control technology and an intelligent neural network algorithm technology to monitor the whole or local block of the high and steep dangerous rock mass in real time, has the characteristics of small size, high precision, low power consumption and the like, can realize 24-hour uninterrupted automatic real-time monitoring, can operate the device on site, is simple and practical, has a friendly human-computer interaction interface, and can help site monitoring personnel to know the dangerous rock mass field deformation condition in the first time. In addition, the invention can effectively improve the measurement precision of dangerous rock mass deformation monitoring through the neural network algorithm of the data monitoring center.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings used in the description of the embodiments will be briefly described below.
FIG. 1 is a structural block diagram of a deformation monitoring device for a high-steep dangerous rock mass body according to the invention;
FIG. 2 is a schematic view of optical fiber monitoring deployment of the high-steep-risk rock mass body of the invention;
FIG. 3 is a block diagram of the data acquisition unit of the present invention;
FIG. 4 is a block diagram of a neural network prediction unit according to the present invention;
in the drawings, the names represented by the respective reference numerals are as follows:
1-a data acquisition module; 2-fiber grating sensor; 3-high-steep rock mass; 4-an optical fiber; 5-broadband light source.
Detailed Description
The technical solutions of the present invention are further illustrated by the following specific examples, which are only used for explaining the present invention and are not used for limiting the scope of the present invention.
Example 1
A monitoring device and a method for high and steep rock mass deformation comprise a data acquisition unit, a data processing control unit, a data monitoring unit and a neural network prediction unit, wherein the data acquisition unit, the data processing control unit, the data monitoring unit and the neural network prediction unit are sequentially connected.
The data acquisition unit comprises a broadband light source, an optical fiber grating sensor and a data acquisition module. Through surveying in advance and discerning high steep dangerous rock mass body, connect gradually a plurality of fiber grating sensor through optic fibre, optic fibre and fiber grating sensor direct fixation are to high steep dangerous rock mass body on, connect broadband light source at the input of optic fibre, and broadband light source evenly sets up in the bottom edge of massif, and data acquisition module is connected to the output of optic fibre, and data acquisition module sets up in the top of massif. The data acquisition module acquires deformation monitoring data of the high-steep rock mass body.
The data processing control unit comprises a data processing module, a synchronous control unit, an optical pulse transmitting module, a laser, an optical path coupler, an optical splitter, an optical filter and a light source receiving module. The data processing module drives the light pulse transmitting module in real time through the synchronous control unit to drive a light pulse signal with larger power for the laser, the light pulse which passes through the tail fiber is input into a tail fiber of the measuring optical fiber through the laser, the light pulse directly enters a measured light through the light path coupler, namely, in each monitoring block of the rock mass block with high and steep danger, the light pulse which passes through the light path coupler can generate light scattering in the measuring light, the specific deformation quantity of the block is directly embodied according to the size of the scattering intensity, the scattered light carrying deformation monitoring data returns to the light splitter through the light path coupler, the light splitter mainly comprises optical filters with different central wavelengths, the light splitter can resolve at least two kinds of light scattering, the light is transmitted to the light source receiving module through resolving different scattered light, and the light source receiving module simply processes the light source data and then delivers the light source data to the data processing module, the data processing module can analyze the light source data at the first time, and then judges which section of distance and which block have been deformed.
The data monitoring unit comprises a data transmission module and a data monitoring center. The data processing module can transmit specific deformation monitoring data to the background data monitoring center through the data transmission module when judging where the detected optical fiber is subjected to specific deformation, the background data monitoring center performs deep analysis and processing on the detected optical fiber monitoring data according to strong computing power, data sharing and real-time monitoring and early warning can be realized with the field data processing module, discrimination and analysis on the overall motion trend of the detected dangerous rock body can be realized, and the deformation monitoring precision of the dangerous rock body can be effectively improved after the data is processed and analyzed by utilizing a neural network algorithm through certain data accumulation.
The neural network prediction unit comprises a monitoring data preprocessing module and a BP neural network prediction module. The data monitoring center can add a neural network algorithm in data analysis, the neural network algorithm mainly inputs laser wavelength input into the measured optical fiber and field real-time monitoring temperature, the output value is the specific deformation of the measured optical fiber, and the reliability and stability of the specific deformation of the measured optical fiber are improved through the learning precision and speed of the neural network. The method comprises the steps of establishing a dangerous rock mass deformation trend data model based on a neural network, carrying out simple data preprocessing on temperature data and strain data acquired on site according to the requirement of a neural network algorithm to form two-dimensional input discrete variables, sending the discrete variables into a BP neural network to carry out data analysis and processing, carrying out data fitting and trend analysis on the BP neural network according to the received processed data, establishing a mathematical model for responding to input data and output data, and further calculating the movement trend of the high and steep dangerous rock mass, so that accurate judgment is carried out on the next deformation state of the dangerous rock mass.
The data processing control unit can also realize real-time monitoring data query in a high and steep dangerous rock embodiment field, a friendly man-machine interaction interface can be provided for monitoring personnel, on-site real-time monitoring can be realized through keys, the data processing module sends pulse signals to the synchronous control unit, the laser is started to input light pulses into the optical fiber to be detected, then the optical signals and the electric signals are converted and returned to the data processing module, on-site real-time analysis and pre-judgment are carried out, dangerous rock body deformation data in the current mode are directly measured, and good data support is provided for line detection personnel.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the technical scope of the present invention, so that any minor modifications, equivalent changes and modifications made to the above embodiment according to the technical spirit of the present invention are within the technical scope of the present invention.
Claims (7)
1. The utility model provides a monitoring devices of high steep dangerous rock mass body deformation which characterized in that: comprises a data acquisition unit, a data processing control unit, a data monitoring unit and a neural network prediction unit, the data acquisition unit comprises a broadband light source, an optical fiber grating sensor and a data acquisition module, the data processing control unit comprises a data processing module, a synchronous control unit, an optical pulse transmitting module, a laser, an optical path coupler, an optical splitter, an optical filter and a light source receiving module, the data monitoring unit comprises a data transmission module and a data monitoring center, the data processing control unit transmits specific deformation monitoring data to the data monitoring center through the data transmission module, the neural network prediction unit comprises a monitoring data preprocessing module and a BP neural network prediction module, the data acquisition unit, the data processing control unit, the data monitoring unit and the neural network prediction unit are connected in sequence.
2. The device for monitoring the deformation of the rock mass with the high and steep crisis as claimed in claim 1, wherein: the data acquisition unit comprises a plurality of fiber grating sensors which are sequentially connected through the optical fibers, and the optical fibers and the fiber grating sensors are directly fixed on the high-steep rock mass body.
3. The device for monitoring the deformation of the rock mass with the high and steep crisis as claimed in claim 2, wherein: one end of the data acquisition unit is provided with a plurality of broadband light sources, the broadband light sources are uniformly arranged at the bottom edge of the mountain body, the other end of the data acquisition unit is connected with the data acquisition module through the optical fiber, and the data acquisition module is arranged at the top of the mountain body.
4. The device for monitoring the deformation of the rock mass with the high and steep crisis as claimed in claim 1, wherein: the data processing control unit analyzes the data acquired by the data acquisition unit and judges which block is deformed according to which distance.
5. The device for monitoring the deformation of the rock mass with the high and steep crisis as claimed in claim 1, wherein: and the monitoring data preprocessing module is used for simply preprocessing temperature data and strain data acquired on site, sending the data into the BP neural network prediction model for data analysis and processing, and calculating the motion trend of the high-steep rock mass.
6. A monitoring method for deformation of a high and steep rock mass body is characterized by comprising the following steps:
s1, surveying and identifying the high-steep-risk rock mass body in advance, sequentially connecting a plurality of fiber grating sensors through optical fibers, directly fixing the optical fibers and the fiber grating sensors to the high-steep-risk rock mass body, connecting the input end of the optical fibers with the broadband light source, connecting the output end of the optical fibers with the data acquisition module, and acquiring deformation monitoring data of the high-steep-risk rock mass body by the data acquisition module;
s2, the data processing module drives the light pulse emitting module in real time through the synchronous control unit to drive a light pulse signal with larger power to the laser, the laser is input into a tail fiber of the measuring optical fiber, the optical pulse passing through the tail fiber needs to directly enter a measured light line through the optical path coupler, the scattered light carrying deformation monitoring data returns to the optical splitter through the optical path coupler, the optical splitter mainly comprises optical filters with different central wavelengths, the scattered light with different resolution is transmitted to the light source receiving module, the light source receiving module simply processes the light source data and then transmits the processed data to the data processing module, the data processing module can analyze the light source data at the first time and judge which distance and which block are deformed;
s3, the data processing module may further transmit the specific deformation monitoring data to the background data monitoring center through the data transmission module, and the data monitoring center performs depth analysis and processing on the detected optical fiber monitoring data according to a strong calculation capability;
s4, adding a neural network algorithm into data analysis by the data monitoring center, performing simple data preprocessing on the temperature data and the strain data acquired on site according to the requirement of the neural network algorithm to form two-dimensional input discrete variables, sending the discrete variables into the BP neural network prediction model, performing data fitting and trend analysis by the BP neural network prediction model according to the received processed data, and calculating the motion trend of the high-steep rock mass.
7. The method for monitoring the deformation of the high-steep rock mass body according to claim 6, wherein the method comprises the following steps: the data processing module can also realize real-time monitoring data query in a dangerous rock embodying field, the data processing module starts the laser to input light pulses into an optical fiber to be tested by sending the light pulse signals to the synchronous control unit, then returns to the data processing module again through conversion of a series of light signals and electric signals, and directly measures dangerous rock body deformation data in the current mode through field real-time analysis and pre-judgment.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112833808A (en) * | 2021-01-05 | 2021-05-25 | 厦门银江智慧城市技术股份有限公司 | Equipment deformation detection method and device based on convolutional neural network algorithm |
| CN115217045A (en) * | 2022-07-11 | 2022-10-21 | 华北水利水电大学 | Active protection, dynamic monitoring and treatment method for high-speed rail high-slope dangerous stone |
| CN116543018A (en) * | 2023-05-08 | 2023-08-04 | 重庆市二零八地质环境研究院有限公司 | High-steep dangerous rock collapse movement analysis method based on video feature point dynamic tracking |
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2019
- 2019-11-25 CN CN201911165245.9A patent/CN110672028A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112833808A (en) * | 2021-01-05 | 2021-05-25 | 厦门银江智慧城市技术股份有限公司 | Equipment deformation detection method and device based on convolutional neural network algorithm |
| CN115217045A (en) * | 2022-07-11 | 2022-10-21 | 华北水利水电大学 | Active protection, dynamic monitoring and treatment method for high-speed rail high-slope dangerous stone |
| CN116543018A (en) * | 2023-05-08 | 2023-08-04 | 重庆市二零八地质环境研究院有限公司 | High-steep dangerous rock collapse movement analysis method based on video feature point dynamic tracking |
| CN116543018B (en) * | 2023-05-08 | 2023-12-19 | 重庆市二零八地质环境研究院有限公司 | High-steep dangerous rock collapse movement analysis method based on video feature point dynamic tracking |
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