CN110921446B - Equipment attribute acquisition system - Google Patents
Equipment attribute acquisition system Download PDFInfo
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- CN110921446B CN110921446B CN201911259891.1A CN201911259891A CN110921446B CN 110921446 B CN110921446 B CN 110921446B CN 201911259891 A CN201911259891 A CN 201911259891A CN 110921446 B CN110921446 B CN 110921446B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
- B66B1/3492—Position or motion detectors or driving means for the detector
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/0006—Monitoring devices or performance analysers
- B66B5/0018—Devices monitoring the operating condition of the elevator system
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Abstract
The invention discloses an equipment attribute computing system, which comprises an acceleration acquisition module and an equipment attribute acquisition module; the acceleration acquisition module is used for acquiring acceleration data of the set direction of the equipment; the device attribute acquisition module is used for acquiring at least one of the motion mode type, the maximum acceleration, the maximum deceleration, the maximum speed, the running distance and the running time of the device according to the acceleration data of the set direction of the device acquired by the acceleration acquisition module; if the equipment has at least two stations and runs regularly, the equipment attribute data acquired by the equipment attribute acquisition module further comprises the relative distance between the equipment stations and the number of equipment running stations according to the acceleration data in the set direction of the equipment. The equipment attribute acquisition system provided by the invention can acquire more attributes of equipment; meanwhile, the accelerometer is arranged on the equipment door, so that the door opening and closing information of the equipment door can be obtained.
Description
Technical Field
The invention belongs to the technical field of elevator equipment, relates to an attribute acquisition system, and particularly relates to an equipment attribute acquisition system.
Background
At present, no uniform elevator monitoring system exists except that an elevator manufacturer and an elevator main board can directly obtain basic conditions and attributes of an elevator. The desire to obtain attributes of an elevator is to add additional equipment in addition to obtaining master board privileges from the elevator manufacturer.
In the prior art with an acceleration sensor, the available information is limited, and most of them can only detect the running speed and distance of the elevator by means of calculus. However, the elevator has different operation modes and different rated speeds and accelerations, and the traditional method is difficult to remove abnormal data and carry out a large amount of statistics. In addition, the traditional acceleration sensor additionally arranged in the elevator can only calculate the up-and-down movement of the elevator between floors, and other attributes of the elevator cannot be obtained.
In view of the above, there is an urgent need to design an equipment attribute obtaining method to overcome the above-mentioned defects of the existing elevator monitoring method.
Disclosure of Invention
The invention provides a device attribute acquisition system which can acquire more attributes of devices.
In order to solve the technical problem, according to one aspect of the present invention, the following technical solutions are adopted:
a device attribute acquisition system, the system comprising:
the acceleration acquisition module is used for acquiring acceleration data of the set direction of the equipment;
the device attribute acquisition module is used for acquiring at least one of the motion mode type, the maximum acceleration, the maximum deceleration, the maximum speed, the running distance and the running time of the device according to the acceleration data of the set direction of the device acquired by the acceleration acquisition module; if the equipment has at least two stations and runs regularly, the equipment attribute data acquired by the equipment attribute acquisition module further comprises the relative distance between the equipment stations and the number of equipment running stations according to the acceleration data in the set direction of the equipment.
As an embodiment of the present invention, the device attribute acquisition module includes at least one of a device motion pattern type acquisition unit, a maximum acceleration acquisition unit, a maximum deceleration acquisition unit, a maximum velocity acquisition unit, a travel distance acquisition unit, an inter-device station relative distance acquisition unit, and a device travel station number acquisition unit.
As an embodiment of the present invention, the maximum speed acquiring unit is configured to acquire a maximum speed; the equipment has different speed modes, and the maximum value of the speed curve of each time of complete operation of the equipment is taken to obtain M maximum operation speeds; performing density-based clustering DBSCAN on the M data with the maximum operating speed; obtaining A different maximum operation speed sets after clustering, wherein the A different maximum operation speed sets correspond to A classes of maximum operation speeds; finding out one complete motion corresponding to various devices; summing and averaging the maximum running speeds of the various types respectively to obtain the maximum running speeds of the A types of motion modes;
the maximum acceleration acquisition unit is used for acquiring maximum acceleration; taking the maximum value of the absolute value of the first acceleration non-0 section of each type of acceleration curve, and averaging according to the type to obtain the maximum acceleration of each type of motion of the equipment;
the maximum deceleration obtaining unit is used for obtaining the maximum deceleration; and taking the maximum value of the absolute value of the second acceleration non-0 section of the acceleration curve, and averaging according to classes to obtain the maximum deceleration of various types of motion of the equipment.
As an embodiment of the invention, the apparatus is an elevator; the running distance acquisition unit is used for integrating the vertical inter-floor motion of the elevator with one complete inter-floor motion direction of the elevator, calculating the distance curve of single running of all the elevators, and taking the maximum value of the distance curve as the single running distance of the elevator;
the device operation station number acquisition unit is used for accumulating the single operation distance, and after each accumulation, the accumulated distance is used as a result which is counted as dis [ i ], wherein i represents the ith result; when data of a long time is collected, the number of dis is enough, then clustering DBSCAN based on density is carried out on all dis to obtain several types of data which basically represent the number of floors of the building;
the relative distance acquisition unit between the equipment stations is used for averaging all similar internal distances to obtain the relative distance of each floor of the building; arranging all the average values from small to large, wherein the relative distance between the floor and the bottommost layer is obtained by subtracting the minimum average value from all the average values; the heights of all floors are obtained.
As an embodiment of the invention, the apparatus is an elevator; the system also comprises an elevator door data acquisition module, a data acquisition module and a data acquisition module, wherein the elevator door data acquisition module is used for processing acceleration data of the elevator car door in the door opening and closing direction to obtain curves of door movement distance, door speed and door acceleration, and the door width is the maximum door movement distance of one-time door opening or door closing movement; the one-time complete door opening/closing is divided into four processes of slow acceleration, deceleration and slow deceleration, and certain noise influence is generated when people go up and down after the door is opened; when a single door opening or closing curve is intercepted, an upper threshold and a lower threshold are set and divided into a data section continuously larger than the upper threshold and a data section continuously smaller than the lower threshold; the middle constant speed section in the acceleration and deceleration process of the opening and closing of the elevator door is smaller than a set threshold value, and if the difference time of the acceleration and deceleration data sections of the opening and closing door is smaller than a set value, a one-time door opening or closing curve is obtained.
As an embodiment of the invention, the apparatus is an elevator; the system also comprises a standby position acquisition module which is used for collecting data within set time, detecting the time period within the set time after the elevator stops when the vertical movement of the x axis between floors of the elevator is detected each time, and detecting whether the door is opened or closed or not by the y axis; if the open and close door cannot be detected, the standby position of the elevator of the building is represented; the standby position is calculated at several floors by calculating the relative floor height of the floor.
As an embodiment of the present invention, the apparatus includes a door; the system further comprises a door data acquisition module used for acquiring at least one of the time for opening the door, the time for closing the door, the door width and the standby position of the equipment according to the acceleration data of the set direction of the equipment.
As an embodiment of the invention, the apparatus is an elevator; the acceleration acquisition module is used for acquiring triaxial acceleration data of the equipment;
the system comprises an orientation determining module, a three-axis acceleration sensor and a three-axis direction determining module, wherein the orientation determining module is used for determining three orientations in an actual space represented by three axes according to information returned by the three-axis acceleration sensor; the x-axis represents the direction of movement between elevator floors, the y-axis represents the direction of opening and closing of the car doors, and the z-axis represents the direction perpendicular to the x-and y-axes.
As an embodiment of the invention, the apparatus is an elevator; the system comprises: the elevator inter-floor motion data acquisition module is used for converting unit LSB/g of x-axis data returned by a sensor of the elevator inter-floor motion, namely the motion of an x axis, into m/s2Specifically, the conversion mode is that a is (k-b) × 9.8/b, wherein a is the converted acceleration value with the unit of meter per second square and 98 is the value of the gravitational acceleration g, b is the value of the x-axis when the elevator is in a stationary period, k is the value of the sensor at a certain moment.
As an embodiment of the invention, the apparatus is an elevator; assuming a complete acceleration of the vertical movement between the elevator floors starting from 0 and ending at T, the speed of the elevator at time T is the integral of the acceleration over time from 0 to time T, i.e. the acceleration is measured as a function of the time
Wherein T is more than or equal to 0 and less than or equal to T and VtIs the velocity at time t, and a (t) is the acceleration at time t; after the speed at all the moments is calculated by the method, the data of the change of the speed of the complete elevator floor vertical motion along with the time is obtained, and the distance of the complete elevator floor vertical motion is the integral of the speed on the time;
at the moment, three pieces of data of the complete motion of all the elevators are obtained, namely data of the change of the acceleration relative to time, data of the change of the speed relative to time and data of the change of the motion distance of the elevator relative to time under the complete motion of one elevator; assuming that the elevator has moved N times in total, 3N pieces of data are obtained.
The invention has the beneficial effects that: the equipment attribute acquisition system provided by the invention can acquire more attributes of the equipment. In a use scene of the invention, the invention takes the single elevator interlayer vertical motion of the elevator as a motion unit, calculates elevator attributes including maximum acceleration and the like for the single motion unit, collects a large amount of single motions, namely collects each attribute under the single motion, and then calculates, thereby having statistical significance. After theoretical study and study are carried out on the speed regulation modes of the elevators, the fact that one elevator operation mode can be multiple (the elevator with a lower floor number can only have one speed regulation mode) is found, different motion modes of the elevators are firstly classified before the statistical significance processing is carried out on the attributes of each elevator, and therefore the attributes under different elevator operation modes are obtained. Besides, with the aid of machine learning, the device can statistically acquire the maximum acceleration, the maximum deceleration, the maximum speed, the relative distance between the running stations and the number of stations of the device in various motion modes.
Drawings
FIG. 1 is a block diagram of a device attribute calculation system according to an embodiment of the present invention.
Fig. 2 is a one-dimensional data smoothing graph of acceleration and speed of vertical movement between elevator floors in an ideal state along with time.
Fig. 3 is a graph of acceleration and velocity of an elevator car door switch over time in an ideal state.
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
For a further understanding of the invention, reference will now be made to the preferred embodiments of the invention by way of example, and it is to be understood that the description is intended to further illustrate features and advantages of the invention, and not to limit the scope of the claims.
The description in this section is for several exemplary embodiments only, and the present invention is not limited only to the scope of the embodiments described. It is within the scope of the present disclosure and protection that the same or similar prior art means and some features of the embodiments may be interchanged.
The invention discloses an equipment attribute acquisition system, and FIG. 1 is a schematic diagram of an equipment attribute calculation system according to an embodiment of the invention; referring to fig. 1, the system includes an acceleration acquisition module 1 and a device attribute acquisition module 2. The acceleration acquisition module is used for acquiring acceleration data of the set direction of the equipment; the device attribute acquisition module is used for acquiring at least one of the motion mode type, the maximum acceleration, the maximum deceleration, the maximum speed, the running distance and the running time of the device according to the acceleration data of the set direction of the device acquired by the acceleration acquisition module; if the equipment has at least two stations and runs regularly, the equipment attribute data acquired by the equipment attribute acquisition module further comprises the relative distance between the equipment stations and the number of equipment running stations according to the acceleration data in the set direction of the equipment.
In an embodiment of the present invention, the device attribute obtaining module includes at least one of a device motion pattern type obtaining unit, a maximum acceleration obtaining unit, a maximum deceleration obtaining unit, a maximum speed obtaining unit, a travel distance obtaining unit, an inter-device-station relative distance obtaining unit, and a device travel station number obtaining unit.
FIG. 2 is a one-dimensional data smoothing graph of acceleration and speed of vertical movement between elevator floors over time in an ideal state; fig. 3 is a graph of acceleration and velocity of an elevator car door switch over time in an ideal state. Referring to fig. 2 and 3, in an embodiment, the operation curve of the elevator can be described with reference to fig. 2 and 3.
In one embodiment, the maximum speed obtaining unit is used for obtaining a maximum speed; the equipment has different speed modes, and the maximum value of the speed curve of each time of complete operation of the equipment is taken to obtain M maximum operation speeds; performing density-based clustering DBSCAN on the M data with the maximum operating speed; obtaining A different maximum operation speed sets after clustering, wherein the A different maximum operation speed sets correspond to A classes of maximum operation speeds; finding out one complete motion corresponding to various devices; and summing and averaging the maximum running speeds of the various types respectively to obtain the maximum running speeds of the A types of motion modes. The maximum acceleration acquisition unit is used for acquiring maximum acceleration; and taking the maximum value of the absolute value of the first acceleration non-0 section of each type of acceleration curve, and averaging according to the type to obtain the maximum acceleration of each type of motion of the equipment. The maximum deceleration obtaining unit is used for obtaining the maximum deceleration; and taking the maximum value of the absolute value of the second acceleration non-0 section of the acceleration curve, and averaging according to classes to obtain the maximum deceleration of various types of motion of the equipment.
In one embodiment, the apparatus is an elevator; the running distance obtaining unit is used for integrating the vertical inter-floor motion of the elevator with complete inter-floor motion direction once, calculating and obtaining the distance curve of single running of all the elevators, and the maximum value of the distance curve is the single running distance of the elevator.
The device operation station number acquisition unit is used for accumulating the single operation distance, and after each accumulation, the accumulated distance is used as a result which is counted as dis [ i ], wherein i represents the ith result; after collecting data for a long time, the number of dis is enough, and then clustering DBSCAN based on density is carried out on all dis to obtain several types of data which basically represent how many floors the building has.
The relative distance acquisition unit between the equipment stations is used for averaging all similar internal distances to obtain the relative distance of each floor of the building; arranging all the average values from small to large, wherein the relative distance between the floor and the bottommost layer is obtained by subtracting the minimum average value from all the average values; the heights of all floors are obtained.
In one embodiment of the invention, the apparatus is an elevator. The system also comprises an elevator door data acquisition module, a data acquisition module and a data acquisition module, wherein the elevator door data acquisition module is used for processing acceleration data of the elevator car door in the door opening and closing direction to obtain curves of door movement distance, door speed and door acceleration, and the door width is the maximum door movement distance of one-time door opening or door closing movement; the one-time complete door opening/closing is divided into four processes of slow acceleration, deceleration and slow deceleration, and certain noise influence is generated when people go up and down after the door is opened; when a single door opening or closing curve is intercepted, an upper threshold and a lower threshold are set and divided into a data section continuously larger than the upper threshold and a data section continuously smaller than the lower threshold; the middle constant speed section in the acceleration and deceleration process of the opening and closing of the elevator door is smaller than a set threshold value, and if the difference time of the acceleration and deceleration data sections of the opening and closing door is smaller than a set value, a one-time door opening or closing curve is obtained.
In an embodiment of the invention, the system further comprises a standby position acquisition module for collecting data within a set time, and detecting a time period within the set time after the elevator stops when the elevator is detected to perform x-axis vertical motion between floors each time, wherein whether the y-axis can detect the opening and closing of the door or not; if the open and close door cannot be detected, the standby position of the elevator of the building is represented; the standby position is calculated at several floors by calculating the relative floor height of the floor.
In one embodiment of the invention, the apparatus comprises a door; the system further comprises a door data acquisition module used for acquiring at least one of the time for opening the door, the time for closing the door, the door width and the standby position of the equipment according to the acceleration data of the set direction of the equipment.
In an embodiment of the present invention, the acceleration obtaining module is configured to obtain three-axis acceleration data of a device; the system comprises an orientation determining module, a three-axis acceleration sensor and a three-axis direction determining module, wherein the orientation determining module is used for determining three orientations in an actual space represented by three axes according to information returned by the three-axis acceleration sensor; the x-axis represents the direction of movement between elevator floors, the y-axis represents the direction of opening and closing of the car doors, and the z-axis represents the direction perpendicular to the x-and y-axes.
In one embodiment of the invention, the system comprises an elevator inter-floor motion data acquisition module used for converting unit LSB/g of x-axis data returned by a sensor of the elevator inter-floor motion, namely the motion of an x-axis, into m/s2Specifically, the conversion mode is that a is (k-b) × 9.8/b, wherein a is the converted acceleration value in meters per second, 9.8 is the value of the gravity acceleration g, b is the value of the x axis when the elevator is in a stationary period, and k is the value of the sensor at a certain moment.
In one embodiment of the invention, assuming a complete acceleration of the vertical movement between the elevator floors, the time of which starts at 0 and ends at T, the speed of the elevator at time T is the integral of the acceleration over time from 0 to time T, i.e. the integral of the acceleration over time
Wherein T is more than or equal to 0 and less than or equal to T and VtIs the velocity at time t, and a (t) is the acceleration at time t; after the speed at all the moments is calculated by the method, the data of the change of the speed of the complete elevator floor vertical movement along with the time is obtained, and the distance of the complete elevator floor vertical movement is the integral of the speed on the time. At the moment, three pieces of data of the complete motion of all the elevators are obtained, namely data of the change of the acceleration relative to time, data of the change of the speed relative to time and data of the change of the motion distance of the elevator relative to time under the complete motion of one elevator; assuming that the elevator has moved N times in total, 3N pieces of data are obtained.
In summary, the device attribute acquiring system provided by the invention can acquire more attributes of the device. In a use scene of the invention, the invention takes the single elevator interlayer vertical motion of the elevator as a motion unit, calculates elevator attributes including maximum acceleration and the like for the single motion unit, collects a large amount of single motions, namely collects each attribute under the single motion, and then calculates, thereby having statistical significance. After theoretical study and study are carried out on the speed regulation modes of the elevators, the fact that one elevator operation mode can be multiple (the elevator with a lower floor number can only have one speed regulation mode) is found, different motion modes of the elevators are firstly classified before the statistical significance processing is carried out on the attributes of each elevator, and therefore the attributes under different elevator operation modes are obtained. Besides, with the aid of machine learning, the device can statistically acquire the maximum acceleration, the maximum deceleration, the maximum speed, the relative distance between the running stations and the number of stations of the device in various motion modes.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The description and applications of the invention herein are illustrative and are not intended to limit the scope of the invention to the embodiments described above. Variations and modifications of the embodiments disclosed herein are possible, and alternative and equivalent various components of the embodiments will be apparent to those skilled in the art. It will be clear to those skilled in the art that the present invention may be embodied in other forms, structures, arrangements, proportions, and with other components, materials, and parts, without departing from the spirit or essential characteristics thereof. Other variations and modifications of the embodiments disclosed herein may be made without departing from the scope and spirit of the invention.
Claims (7)
1. A device attribute acquisition system, the system comprising:
the acceleration acquisition module is used for acquiring acceleration data of the set direction of the equipment;
the device attribute acquisition module is used for acquiring at least one of the motion mode type, the maximum acceleration, the maximum deceleration, the maximum speed, the running distance and the running time of the device according to the acceleration data of the set direction of the device acquired by the acceleration acquisition module; if the equipment has at least two stations and runs regularly, the equipment attribute data acquired by the equipment attribute acquisition module further comprises the relative distance between the equipment stations and the number of equipment running stations according to the acceleration data in the set direction of the equipment;
the equipment is an elevator; the system also comprises a standby position acquisition module which is used for collecting data within set time, detecting the time period within the set time after the elevator stops when the vertical movement of the x axis between floors of the elevator is detected each time, and detecting whether the door is opened or closed or not by the y axis; if the open and close door cannot be detected, the standby position of the elevator of the building is represented; the standby position is calculated by calculating the relative bottom height of the floor at several floors;
the equipment attribute acquisition module comprises at least one of an equipment motion mode type acquisition unit, a maximum acceleration acquisition unit, a maximum deceleration acquisition unit, a maximum speed acquisition unit, a running distance acquisition unit, an equipment inter-station relative distance acquisition unit and an equipment running station number acquisition unit;
the maximum speed obtaining unit is used for obtaining a maximum speed; the equipment has different speed modes, and the maximum value of the speed curve of each time of complete operation of the equipment is taken to obtain M maximum operation speeds; performing density-based clustering DBSCAN on the M data with the maximum operating speed; obtaining A different maximum operation speed sets after clustering, wherein the A different maximum operation speed sets correspond to A classes of maximum operation speeds; finding out one complete motion corresponding to various devices; summing and averaging the maximum running speeds of the various types respectively to obtain the maximum running speeds of the A types of motion modes;
the maximum acceleration acquisition unit is used for acquiring maximum acceleration; taking the maximum value of the absolute value of the first acceleration non-0 section of each type of acceleration curve, and averaging according to the type to obtain the maximum acceleration of each type of motion of the equipment;
the maximum deceleration obtaining unit is used for obtaining the maximum deceleration; taking the maximum value of the absolute value of the second acceleration non-0 section of the acceleration curve, and averaging according to classes to obtain the maximum deceleration of various types of motion of the equipment;
the running distance acquisition unit is used for integrating the vertical inter-floor motion of the elevator with one complete inter-floor motion direction of the elevator, calculating the distance curve of single running of all the elevators, and taking the maximum value of the distance curve as the single running distance of the elevator;
the device operation station number acquisition unit is used for accumulating the single operation distance, and after each accumulation, the accumulated distance is used as a result which is counted as dis [ i ], wherein i represents the ith result; when data of a long time is collected, the number of dis is enough, then clustering DBSCAN based on density is carried out on all dis to obtain several types of data which basically represent the number of floors of the building;
the relative distance acquisition unit between the equipment stations is used for averaging all similar internal distances to obtain the relative distance of each floor of the building; arranging all the average values from small to large, wherein the relative distance between the floor and the bottommost layer is obtained by subtracting the minimum average value from all the average values; the heights of all floors are obtained.
2. The device-attribute acquiring system according to claim 1, wherein: the equipment attribute acquisition module comprises at least one of an equipment motion mode type acquisition unit, a maximum acceleration acquisition unit, a maximum deceleration acquisition unit, a maximum speed acquisition unit, a running distance acquisition unit, an inter-equipment station relative distance acquisition unit and an equipment running station number acquisition unit.
3. The device-attribute acquiring system according to claim 1, wherein: the system also comprises an elevator door data acquisition module, a data acquisition module and a data acquisition module, wherein the elevator door data acquisition module is used for processing acceleration data of the elevator car door in the door opening and closing direction to obtain curves of door movement distance, door speed and door acceleration, and the door width is the maximum door movement distance of one-time door opening or door closing movement; the one-time complete door opening/closing is divided into four processes of slow acceleration, deceleration and slow deceleration, and certain noise influence is generated when people go up and down after the door is opened; when a single door opening or closing curve is intercepted, an upper threshold and a lower threshold are set and divided into a data section continuously larger than the upper threshold and a data section continuously smaller than the lower threshold; the middle constant speed section in the acceleration and deceleration process of the opening and closing of the elevator door is smaller than a set threshold value, and if the difference time of the acceleration and deceleration data sections of the opening and closing door is smaller than a set value, a one-time door opening or closing curve is obtained.
4. The device-attribute acquiring system according to claim 1, wherein: the apparatus includes a door; the system further comprises a door data acquisition module used for acquiring at least one of the time for opening the door, the time for closing the door, the door width and the standby position of the equipment according to the acceleration data of the set direction of the equipment.
5. The device-attribute acquiring system according to claim 1, wherein: the acceleration acquisition module is used for acquiring triaxial acceleration data of the equipment; the system comprises an orientation determining module, a three-axis acceleration sensor and a three-axis direction determining module, wherein the orientation determining module is used for determining three orientations in an actual space represented by three axes according to information returned by the three-axis acceleration sensor; the x-axis represents the direction of movement between elevator floors, the y-axis represents the direction of opening and closing of the car doors, and the z-axis represents the direction perpendicular to the x-and y-axes.
6. The device-attribute acquiring system according to claim 1, wherein: the system comprises: the elevator inter-floor motion data acquisition module is used for converting unit LSB/g of x-axis data returned by a sensor of the elevator inter-floor motion, namely the motion of an x axis, into m/s2Specifically, a = (k-b) × 9.8/b, where a is a converted acceleration value in meters per second, 9.8 is a value of gravitational acceleration g, b is a value of an x-axis when the elevator is in a stationary period, and k is a value of a sensor at a certain time.
7. The device-attribute acquiring system according to claim 1, wherein: assuming a complete acceleration of the vertical movement between the elevator floors starting from 0 and ending at T, the speed of the elevator at time T is the integral of the acceleration over time from 0 to time T, i.e. the acceleration is measured as a function of the time
Wherein T is more than or equal to 0 and less than or equal to T,
is the velocity at time t, and a (t) is the acceleration at time t; after the speed at all the moments is calculated by the method, the data of the change of the speed of the complete elevator floor vertical motion along with the time is obtained, and the distance of the complete elevator floor vertical motion is the integral of the speed on the time;
at the moment, three pieces of data of the complete motion of all the elevators are obtained, namely data of the change of the acceleration relative to time, data of the change of the speed relative to time and data of the change of the motion distance of the elevator relative to time under the complete motion of one elevator; assuming that the elevator has moved N times in total, 3N pieces of data are obtained.
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| CN112320519B (en) * | 2020-10-23 | 2022-06-24 | 猫岐智能科技（上海）有限公司 | Elevator running condition display method and system |
| CN113602920B (en) * | 2021-08-05 | 2023-11-28 | 猫岐智能科技（上海）有限公司 | Floor calculation method and system based on displacement of acceleration sensor |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1486918A (en) * | 2002-10-01 | 2004-04-07 | 三菱电机株式会社 | Controller for elevator |
| CN102112388A (en) * | 2008-06-13 | 2011-06-29 | 因温特奥股份公司 | Elevator system, and method for servicing such an elevator system |
| US8521782B2 (en) * | 2011-07-20 | 2013-08-27 | Salesforce.Com, Inc. | Methods and systems for processing large graphs using density-based processes using map-reduce |
| CN103974887A (en) * | 2011-12-07 | 2014-08-06 | 皇家飞利浦有限公司 | Method and apparatus for elevator motion detection |
| CN105718946A (en) * | 2016-01-20 | 2016-06-29 | 北京工业大学 | Passenger going-out behavior analysis method based on subway card-swiping data |
| CN107657277A (en) * | 2017-09-22 | 2018-02-02 | 上海斐讯数据通信技术有限公司 | A kind of human body unusual checking based on big data and decision method and system |
| CN108408520A (en) * | 2018-04-26 | 2018-08-17 | 上海贝思特电气有限公司 | A kind of elevator floor acquisition device, elevator floor acquisition methods and storage medium |
| CN108428015A (en) * | 2018-04-03 | 2018-08-21 | 上海电力学院 | A kind of wind power forecasting method based on history meteorological data and stochastic simulation |
| WO2019141598A1 (en) * | 2018-01-22 | 2019-07-25 | Inventio Ag | Method and device for determining a mapping of a number of floors to be served by an elevator and for determining relative trip-dependent data of an elevator cabin |
Family Cites Families (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4305479A (en) * | 1979-12-03 | 1981-12-15 | Otis Elevator Company | Variable elevator up peak dispatching interval |
| CN102633173B (en) * | 2012-05-04 | 2014-10-15 | 林创鲁 | System and method for monitoring operation state of elevator car |
| US10603056B2 (en) * | 2012-08-31 | 2020-03-31 | Smith & Nephew, Inc. | Patient specific implant technology |
| CN104361259B (en) * | 2014-12-03 | 2017-03-01 | 广东电网有限责任公司电力科学研究院 | A kind of transformer violation operation characteristic analysis method |
| WO2016091198A1 (en) * | 2014-12-11 | 2016-06-16 | 冯春魁 | Method and system for parameter acquisition, control, operation and load monitoring for elevator |
| US20170277826A1 (en) * | 2016-03-27 | 2017-09-28 | Insilico Medicine, Inc. | System, method and software for robust transcriptomic data analysis |
| CN208361622U (en) * | 2018-04-26 | 2019-01-11 | 上海贝思特电气有限公司 | A kind of elevator floor acquisition device |
| CN109466980B (en) * | 2018-12-28 | 2020-09-15 | 长沙慧联智能科技有限公司 | Real-time floor detection device and method for vertical elevator |
| CN109840358B (en) * | 2019-01-09 | 2023-04-07 | 上海海洋大学 | Track time domain difference-based track segmentation method |
| CN110526067B (en) * | 2019-09-23 | 2021-05-28 | 猫岐智能科技（上海）有限公司 | Elevator door opening and closing time accurate acquisition system |
-
2019
- 2019-12-10 CN CN201911259891.1A patent/CN110921446B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1486918A (en) * | 2002-10-01 | 2004-04-07 | 三菱电机株式会社 | Controller for elevator |
| CN102112388A (en) * | 2008-06-13 | 2011-06-29 | 因温特奥股份公司 | Elevator system, and method for servicing such an elevator system |
| US8521782B2 (en) * | 2011-07-20 | 2013-08-27 | Salesforce.Com, Inc. | Methods and systems for processing large graphs using density-based processes using map-reduce |
| CN103974887A (en) * | 2011-12-07 | 2014-08-06 | 皇家飞利浦有限公司 | Method and apparatus for elevator motion detection |
| CN105718946A (en) * | 2016-01-20 | 2016-06-29 | 北京工业大学 | Passenger going-out behavior analysis method based on subway card-swiping data |
| CN107657277A (en) * | 2017-09-22 | 2018-02-02 | 上海斐讯数据通信技术有限公司 | A kind of human body unusual checking based on big data and decision method and system |
| WO2019141598A1 (en) * | 2018-01-22 | 2019-07-25 | Inventio Ag | Method and device for determining a mapping of a number of floors to be served by an elevator and for determining relative trip-dependent data of an elevator cabin |
| CN108428015A (en) * | 2018-04-03 | 2018-08-21 | 上海电力学院 | A kind of wind power forecasting method based on history meteorological data and stochastic simulation |
| CN108408520A (en) * | 2018-04-26 | 2018-08-17 | 上海贝思特电气有限公司 | A kind of elevator floor acquisition device, elevator floor acquisition methods and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 面向大数据的电梯工况智能分析***的设计与实现;王丽园;《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》;20190815(第8期);C038-565 * |
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