CN111675062A - Elevator car fault determination method and system based on multi-axis sensor technology - Google Patents
Elevator car fault determination method and system based on multi-axis sensor technology Download PDFInfo
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- CN111675062A CN111675062A CN202010646628.4A CN202010646628A CN111675062A CN 111675062 A CN111675062 A CN 111675062A CN 202010646628 A CN202010646628 A CN 202010646628A CN 111675062 A CN111675062 A CN 111675062A
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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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- 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
- B66B5/02—Applications of checking, fault-correcting, or safety devices in elevators responsive to abnormal operating conditions
Abstract
The invention provides an elevator car fault determination method and system based on a multi-axis sensor technology, wherein the system comprises a multi-axis sensor unit, a multi-axis sensor unit and a control unit, wherein the multi-axis sensor unit is used for acquiring the acceleration and deceleration, the running speed and vibration data of a car in the three-axis directions of XYZ in real time; the data acquisition unit is used for acquiring data fed back by the multi-axis sensor unit and uploading the data to the platform processing unit and is provided with a wireless module connected with a network; the platform processing unit is used for storing and analyzing the data and starting early warning on the abnormal data condition discovered by analysis; and the fault early warning unit is used for displaying early warning prompt when the running state of the car is abnormal and comprises WEB application and APP application. The method is based on the system to realize self-monitoring, self-diagnosis and intelligent early warning of faults such as acceleration and deceleration, real-time speed, position deviation, abnormal vibration in the XYZ three-axis direction and the like when the elevator car runs.
Description
Technical Field
The invention belongs to the technical field of elevators, and particularly relates to an elevator car fault determination method and system based on a multi-axis sensor technology.
Background
At present, there are two kinds mainly to the judgement mode of elevator car trouble, one is through using the operation curve of special vibration test instrument data acquisition analysis car, but its limitation and the problem that exists: before each test, calibration related parameters need to be reset manually, and the operation process is complex; in order to avoid human interference during the test, the elevator can not bear passengers, and the normal use of the elevator can be interrupted in the test process. The test instrument can only test the running state of the elevator car in the current short time and cannot run and use on the same elevator all weather for a long time; after the test is finished, the data needs to be copied and stored on a computer manually, corresponding analysis software is installed to read the data, the specific result needs to be analyzed and judged manually, and the professional dependence of the data result on technicians is high. And the data result is not accurate, and misjudgment is easily caused. The failure judgment does not form a closed-loop early warning process, detection is carried out only when the abnormal operation of the car is sensed artificially, and the failure detection processing efficiency is low. The other type is that a fitting curve is obtained through calculation based on a cloud end, a vibration abnormal point is searched on the fitting curve, and then a section is taken respectively before and after the vibration abnormal point to form a vibration abnormal section, wherein the abnormal vibration section represents an elevator fault. The problems and disadvantages of this solution are: the data processing has no pre-screening process, and the invalid data greatly reduces the accuracy of fault analysis and the accuracy of fault early warning according to a fitting curve established by the non-screened data; and the fault can be judged only after the data is uploaded to a server for analysis.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides an elevator car fault judgment method and system based on a multi-axis sensor technology, which realize self-monitoring, self-diagnosis and intelligent early warning of faults such as acceleration and deceleration, real-time speed, position deviation, abnormal vibration in the XYZ three-axis direction and the like when an elevator car runs; the specific technical content is as follows:
the invention relates to an elevator car fault judgment system based on a multi-axis sensor technology, which comprises a multi-axis sensor unit, a data acquisition unit, a platform processing unit and a fault early warning unit, wherein the multi-axis sensor unit is connected with the platform processing unit; the multi-axis sensor unit is used for acquiring the acceleration and deceleration, the running speed and vibration data of the car in the XYZ three-axis directions in real time; the data acquisition unit is used for acquiring data fed back by the multi-axis sensor unit and uploading the data to the platform processing unit and is provided with a wireless module connected with a network; the platform processing unit is used for storing and analyzing data and starting early warning on abnormal data conditions discovered by analysis; the fault early warning unit is used for displaying early warning reminding when the running state of the car is abnormal, and comprises WEB application and APP application.
In one or more embodiments of the present invention, the multi-axis sensor unit includes an acceleration sensor and a gyroscope.
In one or more embodiments of the present invention, the multi-axis sensor unit further includes an air pressure sensor.
In one or more embodiments of the present invention, a signal conversion unit is disposed between the multi-axis sensor unit and the data acquisition unit, and is configured to convert TTL signals output by the multi-axis sensor unit into serial port signals, and output the serial port signals to the data acquisition unit.
In one or more embodiments of the present invention, the multi-axis sensor unit is disposed on the ceiling platform or the ceiling beam.
The invention relates to an elevator car fault judgment method based on a multi-axis sensor technology, which comprises a vibration amplitude judgment step, and specifically comprises the following operations:
setting acceleration threshold values in XYZ three-axis directions as Xmax, Ymax and Zmax respectively;
acceleration data of the car in the XYZ three-axis directions are obtained in real time through an acceleration sensor, and when the absolute value of the acceleration peak value in any one direction exceeds the acceleration threshold value, the car is judged to be too large in vibration amplitude in the direction, and early warning is carried out.
In one or more embodiments of the present invention, the vibration amplitude determining step is performed after the car travels for a time T1.
In one or more embodiments of the present invention, the method includes a speed determination step, which specifically operates as follows:
setting an elevator running speed threshold value as Vmax;
and acquiring the speed of the car in the Y-axis direction in real time, and judging that the speed of the car is abnormal when the absolute value of the speed of the car exceeds the running speed threshold value, and early warning.
In one or more embodiments of the present invention, in the speed determining step, when it is detected that the speed in the Y-axis direction exceeds the threshold value within a certain time period T2, it is determined that the car speed overspeed is abnormal.
In one or more embodiments of the invention, the current position height of the car is obtained through the air pressure sensor, so that the position of the car is conveniently located when the running state of the car is in failure.
The invention has the beneficial effects that: utilize thing networking wireless transmission technology, pass through signal conversion unit, data acquisition unit autofilter with elevator car's operation data in real time, calculate the platform processing unit who uploads to the high in the clouds after handling again, combine high in the clouds AI artificial intelligence analysis technique, realize elevator car operation at the self-monitoring, self-diagnosis and the intelligent early warning of faults such as acceleration and deceleration, real-time speed, positional deviation, XYZ triaxial direction's abnormal vibration. Its advantages include:
1) when the device is installed and debugged for the first time, the device is manually calibrated; and the current real-time motion attitude of the module can be rapidly solved through advanced dynamic solution and Kalman dynamic filtering algorithm of the multi-axis sensor unit.
2) The device detects the running condition of the elevator car in real time at all times, is independent of a control system of the elevator, and does not influence the daily normal use of the elevator.
3) The sensor sends data to the data acquisition unit in real time, and the platform processing unit can perform data analysis, data comparison and fault judgment.
4) The elevator early warning system has rich fault early warning functions and can early warn functions of abnormal vibration, abnormal acceleration and deceleration, abnormal operation speed and the like during operation of the elevator.
Drawings
FIG. 1 is a system framework diagram of the present invention.
Fig. 2 is a schematic diagram of the system installation structure of the present invention.
FIG. 3 is a flow chart of the method of the present invention.
FIG. 4 is a graph of acceleration curves for the present invention.
Fig. 5 is a velocity profile of the present invention.
Detailed Description
The scheme of the application is further described as follows:
referring to fig. 1 and 2, the elevator car fault determination system based on the multi-axis sensor technology of the present invention includes a multi-axis sensor unit 1, a signal conversion unit 2, a data acquisition unit 3, a platform processing unit 4 and a fault early warning unit 5;
the multi-axis sensor unit 1 comprises an air pressure sensor, an acceleration sensor and a gyroscope, and is used for acquiring the acceleration and deceleration, the running speed and vibration data of the car in three-axis directions of XYZ in real time, namely converting physical signals of car running into analog signals;
the signal conversion unit 2 is connected between the multi-axis sensor unit 1 and the data acquisition unit 2, and is used for converting TTL signals output by the multi-axis sensor unit 1 into RS232 serial port signals and outputting the RS232 serial port signals to the data acquisition unit 3 through a DB9 data line;
the data acquisition unit 3 is used for acquiring data fed back by the multi-axis sensor unit 1, screening the acquired data, integrating effective data, processing the effective data into a protocol of a docking platform processing unit, and uploading the protocol to the platform processing unit 4, wherein the platform processing unit has a wireless module connected with a network;
the platform processing unit 4 is used for storing and analyzing data and comprises an internet of things access unit, a database unit and an AI (artificial intelligence) analysis unit, the internet of things access unit receives the data sent by the data acquisition unit 3, the database unit is used for storing sensor data reported in real time in a rolling mode, the AI analysis unit realizes modeling by calling the data in the database, establishes a model of the normal running condition of the elevator car, compares the data sent by the sensor in real time, and immediately sends an early warning signal to the early warning unit when an abnormal condition occurs;
and the fault early warning unit 5 is used for displaying early warning prompt when the running state of the car is abnormal, and comprises WEB application and APP application. The Web application is used for a monitoring center of an elevator maintenance unit or a property unit, the APP application is equipped for a mobile phone of maintenance personnel, and the two applications can both see a real-time physical examination report of an elevator car and display early warning and reminding when the running state of the elevator car is abnormal.
The multi-axis sensing unit 1 is fixed on a vertical and flat surface of the car top upper beam component 6, and the signal conversion unit 2 and the data acquisition unit 3 are placed at proper positions of the car top 7, so that the multi-axis sensing unit does not interfere with the car top component and does not affect maintenance.
Referring to fig. 3 to 5, the elevator car fault determining method based on the above system includes
A vibration amplitude determination step:
setting acceleration threshold values in XYZ three-axis directions as Xmax, Ymax and Zmax respectively; when the elevator runs, real-time car acceleration data are continuously sent to the data acquisition unit, after a period of time T1 (such as 2 seconds), if the absolute value peak value d of the detected acceleration in a certain direction exceeds a threshold range, the vibration amplitude in the direction is judged to be too large, the running state of the elevator is abnormal, and early warning is carried out.
A speed determination step:
setting an elevator running speed threshold value as Vmax; when the elevator runs, the acceleration sensor continuously sends real-time car speed data to the data acquisition module, a dynamic curve of elevator speed change is generated in real time according to the set rated speed Ve of the elevator, and when the speed Vt in the Y-axis direction is detected to exceed a threshold value Vmax within a certain time period T2 (such as 3 seconds), the overspeed abnormality of the car is judged, and early warning is performed.
The air pressure sensor directly outputs the current position height of the car, so that the position of the car is conveniently positioned when the running state of the car is in fault.
The above preferred embodiments should be considered as examples of the embodiments of the present application, and technical deductions, substitutions, improvements and the like similar to, similar to or based on the embodiments of the present application should be considered as the protection scope of the present patent.
Claims (10)
1. The utility model provides an elevator car fault determination system based on multiaxis sensor technique which characterized in that: the system comprises a multi-axis sensor unit, a data acquisition unit, a platform processing unit and a fault early warning unit;
the multi-axis sensor unit is used for acquiring the acceleration and deceleration, the running speed and vibration data of the car in the XYZ three-axis directions in real time;
the data acquisition unit is used for acquiring data fed back by the multi-axis sensor unit and uploading the data to the platform processing unit and is provided with a wireless module connected with a network;
the platform processing unit is used for storing and analyzing data and starting early warning on abnormal data conditions discovered by analysis;
the fault early warning unit is used for displaying early warning reminding when the running state of the car is abnormal, and comprises WEB application and APP application.
2. The multi-axis sensor technology-based elevator car malfunction determination system according to claim 1, wherein: the multi-axis sensor unit includes an acceleration sensor and a gyroscope.
3. The multi-axis sensor technology-based elevator car malfunction determination system of claim 2, wherein: the multi-axis sensor unit further includes an air pressure sensor.
4. Elevator car fault determination system based on multiaxis sensor technology as claimed in claim 1 or 2 or 3, characterized in that: and a signal conversion unit is arranged between the multi-axis sensor unit and the data acquisition unit and is used for converting the TTL signals output by the multi-axis sensor unit into serial port signals and outputting the serial port signals to the data acquisition unit.
5. Elevator car fault determination system based on multiaxis sensor technology as claimed in claim 1 or 2 or 3, characterized in that: the multi-axis sensor unit is arranged on the car top platform or the car top beam.
6. A method for judging elevator car faults based on a multi-axis sensor technology is characterized by comprising the following steps: the method comprises a vibration amplitude judgment step, and specifically comprises the following operations:
setting acceleration threshold values in XYZ three-axis directions as Xmax, Ymax and Zmax respectively;
acceleration data of the car in the XYZ three-axis directions are obtained in real time through an acceleration sensor, and when the absolute value of the acceleration peak value in any one direction exceeds the acceleration threshold value, the car is judged to be too large in vibration amplitude in the direction, and early warning is carried out.
7. The elevator car failure determination method based on the multi-axis sensor technology as claimed in claim 6, wherein: and executing the vibration amplitude judging step after the time T1 passes when the car runs.
8. The elevator car failure determination method based on the multi-axis sensor technology as claimed in claim 6, wherein: the method comprises a speed judging step, and the specific operation is as follows:
setting an elevator running speed threshold value as Vmax;
and acquiring the speed of the car in the Y-axis direction in real time, and judging that the speed of the car is abnormal when the absolute value of the speed of the car exceeds the running speed threshold value, and early warning.
9. The elevator car failure determination method based on the multiaxis sensor technology as claimed in claim 8, wherein: in the speed determination step, when the speed in the Y-axis direction is detected to exceed the threshold value within a certain time period T2, the overspeed abnormality of the car is determined.
10. Elevator car fault determination method based on multiaxis sensor technology as claimed in any of the claims 6-9, characterized in that: the current position height of the car is obtained through the air pressure sensor, and the position of the car is convenient to locate when the running state of the car is in fault.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202010646628.4A CN111675062A (en) | 2020-07-07 | 2020-07-07 | Elevator car fault determination method and system based on multi-axis sensor technology |
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| CN202010646628.4A CN111675062A (en) | 2020-07-07 | 2020-07-07 | Elevator car fault determination method and system based on multi-axis sensor technology |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114229640A (en) * | 2021-12-18 | 2022-03-25 | 广州鲁邦通物联网科技股份有限公司 | Elevator operation and maintenance judgment method and elevator maintenance system |
| CN114261862A (en) * | 2021-11-08 | 2022-04-01 | 闽江学院 | Elevator running state monitoring method and system |
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