CN212893314U - Elevator car fault determination system based on multi-axis sensor technology - Google Patents
Elevator car fault determination system based on multi-axis sensor technology Download PDFInfo
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Abstract
The utility model provides an elevator car fault determination system based on multiaxis sensor technology, the system includes multiaxis sensor unit for acquire the acceleration and deceleration, the functioning speed of car and the vibration data of XYZ triaxial direction 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 system realizes 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 utility model belongs to the technical field of the elevator, concretely relates to elevator car fault determination system based on multiaxis sensor technique.
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.
SUMMERY OF THE UTILITY MODEL
In order to overcome the defects of the prior art, the utility model provides an elevator car fault judgment system based on the multi-axis sensor technology, which realizes the self-monitoring, self-diagnosis and intelligent early warning of faults such as acceleration and deceleration, real-time speed, position deviation, abnormal vibration in the three-axis directions of XYZ when the elevator car runs; the specific technical content is as follows:
the utility model discloses an elevator car trouble decision system based on multiaxis sensor technique, it includes multiaxis sensor unit, data acquisition unit, platform processing unit and trouble 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.
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 the middle of one or more embodiments of the utility model, be provided with the signal conversion unit between multiaxis sensor unit and the data acquisition unit, it is used for converting the TTL signal of multiaxis sensor unit output into serial signals, exports to the data acquisition unit again.
In one or more embodiments of the present invention, the multi-axis sensor unit is disposed on the car top platform or the car top beam.
The utility model has the advantages 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 utility model is only installed and debugged for the first time, the equipment 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 schematic diagram of the system framework of the present invention.
Fig. 2 is a schematic view 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 an acceleration curve diagram of 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 sensor unit 1 is fixed on a vertical and flat surface of a car top upper beam component 6, and the signal conversion unit 2 and the data acquisition unit 3 are placed at proper positions of a car top 7, so that the multi-axis sensor 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 car speed overspeed is judged to be abnormal, 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 (6)
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| Application Number | Priority Date | Filing Date | Title |
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| CN202021312103.9U CN212893314U (en) | 2020-07-07 | 2020-07-07 | Elevator car fault determination system based on multi-axis sensor technology |
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| CN202021312103.9U CN212893314U (en) | 2020-07-07 | 2020-07-07 | Elevator car fault determination system based on multi-axis sensor technology |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111675062A (en) * | 2020-07-07 | 2020-09-18 | 广东卓梅尼技术股份有限公司 | Method and system for elevator car fault determination based on multi-axis sensor technology |
| CN119117850A (en) * | 2024-10-11 | 2024-12-13 | 广东华凯电梯有限公司 | Elevator operation fault detection and alarm system based on artificial intelligence |
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2020
- 2020-07-07 CN CN202021312103.9U patent/CN212893314U/en active Active
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111675062A (en) * | 2020-07-07 | 2020-09-18 | 广东卓梅尼技术股份有限公司 | Method and system for elevator car fault determination based on multi-axis sensor technology |
| CN119117850A (en) * | 2024-10-11 | 2024-12-13 | 广东华凯电梯有限公司 | Elevator operation fault detection and alarm system based on artificial intelligence |
| CN119117850B (en) * | 2024-10-11 | 2025-04-01 | 广东华凯电梯有限公司 | Elevator operation fault detection alarm system based on artificial intelligence |
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