CN111268527A - Elevator mechanical fault monitoring method and system - Google Patents
Elevator mechanical fault monitoring method and system Download PDFInfo
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- CN111268527A CN111268527A CN202010004249.5A CN202010004249A CN111268527A CN 111268527 A CN111268527 A CN 111268527A CN 202010004249 A CN202010004249 A CN 202010004249A CN 111268527 A CN111268527 A CN 111268527A
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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
- 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
- B66B5/0025—Devices monitoring the operating condition of the elevator system for maintenance or repair
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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
- B66B5/0031—Devices monitoring the operating condition of the elevator system for safety reasons
Abstract
The invention discloses a method and a system for monitoring mechanical faults of an elevator, which are timely and accurate in fault judgment. The method of the invention comprises the following steps: (10) elevator data acquisition: collecting elevator operation data, including traction sheave temperature, machine room operation noise, real-time scene inside the machine room, horizontal acceleration of the car, horizontal angular velocity of the car, vertical acceleration of the car and real-time scene inside the car; (20) elevator data processing: the real-time state in the elevator car and the real-time state in the machine room are obtained by analyzing and processing the elevator operation data; (30) and (3) judging the mechanical fault of the elevator: and judging the mechanical fault of the elevator according to the real-time state in the elevator car and the real-time state in the machine room. The system comprises an elevator end (1) and a remote end (2), wherein the remote end (2) comprises a remote monitoring center (21), a 5.8G wireless network bridge 2(22) and an Ali cloud Internet of things platform (23), wherein the wireless network bridge 2 is in signal connection with the remote monitoring center (21).
Description
Technical Field
The invention belongs to the technical field of elevator intelligent safety monitoring, and particularly relates to an elevator mechanical fault monitoring method and system.
Background
With the increasing urbanization process, the number of elevators is greatly increased in recent years by the built high-rise building, but the problems of elevator safety and maintenance are also increased.
The mechanical failure of the elevator is mainly caused by the long-time abrasion loss of a traction wheel, the instable installation of a traction machine, the large installation error of a steel wire rope and other factors to cause the vibration of a lift car.
At the present stage, the detection of the mechanical fault of the elevator is mainly based on the regular inspection of manually carried equipment, so that the problems of manpower and financial resources consumption, failure problem incapable of real-time detection and easy detection omission and error detection are solved.
The Chinese utility model 'elevator trouble network monitoring platform' (application number: 201820676285.4, published: 2018-12-14, published: 208234328U) discloses an elevator trouble network monitoring platform, which comprises a monitoring server, a network video monitoring camera and a smoke sensor which are positioned in an elevator car, and a control monitoring center, and further comprises an infrared sensor, a temperature and humidity sensor and a photoelectric sensor which are positioned in the elevator car, wherein the output ends of the network video monitoring camera, the smoke sensor and the infrared sensor, the temperature and humidity sensor and the photoelectric sensor are connected on an information acquisition integrated board, the information acquisition integrated board is connected with the monitoring server, the control monitoring center comprises an embedded MCU, a current and voltage monitoring module, The temperature and humidity monitoring module and the wireless communication module are respectively connected with the embedded MCU.
The problem of elevator trouble remote monitoring has partly been solved to above-mentioned patent, but because can only monitor the interior external trouble performance of car, just simply upload the data to the server and save in addition, can not confirm the specific mechanical fault's of elevator system emergence point in time, also can not carry out analysis and utilization to trouble data simultaneously, be not convenient for later stage more timely, more accurate to elevator mechanical fault detection and safety monitoring.
Disclosure of Invention
The invention aims to provide a method for monitoring mechanical faults of an elevator, which can judge the faults timely and accurately.
Another object of the present invention is to provide an elevator machine fault monitoring system that implements the above method.
The technical solution for realizing the purpose of the invention is as follows:
an elevator mechanical failure monitoring method comprises the following steps:
(10) elevator data acquisition: collecting elevator operation data, including traction sheave temperature, machine room operation noise, real-time scene inside the machine room, horizontal acceleration of the car, horizontal angular velocity of the car, vertical acceleration of the car and real-time scene inside the car;
(20) elevator data processing: the real-time state in the elevator car and the real-time state in the machine room are obtained by analyzing and processing the elevator operation data;
(30) and (3) judging the mechanical fault of the elevator: and judging the mechanical fault of the elevator according to the real-time state in the elevator car and the real-time state in the machine room.
The technical scheme for realizing the other purpose of the invention is as follows:
an elevator mechanical fault monitoring device comprises an elevator end 1 and a remote end 2, wherein the remote end 2 comprises a remote monitoring center 21, a 5.8G wireless network bridge 222 and an Aliyun Internet of things platform 23, wherein the wireless network bridge 222 is in signal connection with the remote monitoring center 21;
the elevator end 1 comprises a temperature sensor 11 arranged on a traction sheave in a machine room, a noise sensor 12 and a first network camera 13 arranged in the machine room, a 2.4G wireless network bridge 214, a 5.8G wireless network bridge 115, an industrial personal computer 16 arranged at the top of the machine room, a second network camera 17 arranged in a car, a simplified inertia measurement unit 18 arranged in the car, a microprocessor 19 arranged at the top of the car and a 2.4G wireless network bridge 1110;
the temperature sensor 11, the noise sensor 12, the first network camera 13, the 2.4G wireless network bridge 214 and the 5.8G wireless network bridge 115 are respectively connected with the industrial personal computer 16 through signals.
The second network camera 17, the simplified inertia measurement unit 18 and the 2.4G wireless network bridge 1110 are respectively connected with the microprocessor 19 through signals;
the 2.4G wireless bridge 1110 is connected to the 2.4G wireless bridge 214 through wireless signals, and the 5.8G wireless bridge 115 is connected to the 5.8G wireless bridge 222 through wireless signals.
Compared with the prior art, the invention has the following remarkable advantages:
1. the fault positioning is accurate: according to the invention, the Kalman filtering fusion algorithm is utilized, so that the mechanical fault existing in the elevator can be more accurately positioned, the safety of the elevator system can be remotely monitored in real time, and a specific mechanical fault point can be checked in real time;
2. the cost is reduced: the simplified inertia measurement unit in the car reduces the cost and complexity of the system;
3. the method is stable and reliable: the 2.4G wireless network bridge with low power is arranged in the elevator system, so that the car data can be sent to the industrial personal computer of the machine room in real time under the anti-interference condition; in addition, the machine room communicates with a remote place by using a 5.8G high-power wireless network bridge, so that the cost of using a long-distance cable for communication can be saved, and the stability is high under the condition of ensuring the communication distance;
4. and (3) effective accumulation of data: the fault data are analyzed and processed by the aid of an intelligent algorithm through the Ali cloud Internet of things platform, and early warning and troubleshooting can be performed on mechanical faults of the elevator more early and accurately in the later period of convenience.
The invention is described in further detail below with reference to the figures and the detailed description.
Drawings
Fig. 1 is a main flow chart of the elevator machinery fault monitoring method of the present invention.
Fig. 2 is a flowchart of the elevator machine fault determination step of fig. 1.
Fig. 3 is a block diagram of the elevator machinery fault monitoring system of the present invention.
In the figure, the elevator end 1, the remote end 2, the remote monitoring center 21, the 5.8G wireless network bridge 222, the airy cloud internet of things platform 23, the temperature sensor 11, the noise sensor 12, the first network camera 13, the 2.4G wireless network bridge 214, the 5.8G wireless network bridge 115, the industrial personal computer 16, the second network camera 17, the simplified inertia measurement unit 18, the microprocessor 19 and the 2.4G wireless network bridge 1110.
Detailed Description
As shown in fig. 1, the elevator mechanical failure monitoring method of the invention comprises the following steps:
(10) elevator data acquisition: collecting elevator operation data, including traction sheave temperature, machine room operation noise, real-time scene inside the machine room, horizontal acceleration of the car, horizontal angular velocity of the car, vertical acceleration of the car and real-time scene inside the car;
(20) elevator data processing: the real-time state in the elevator car and the real-time state in the machine room are obtained by analyzing and processing the elevator operation data;
preferably, the (20) elevator data processing step comprises:
(21) obtaining the real-time state in the elevator car: integrating angular velocity of the car in the horizontal direction to obtain an angle of the first car in the horizontal direction;
according to the ratio relation between the acceleration of the car in the horizontal direction and the acceleration of gravity, the angle of the second car in the horizontal direction is obtained;
fusing the horizontal direction angle of the first car and the horizontal direction angle of the second car by using a Kalman filtering algorithm to obtain the shaking angles of the x axis and the y axis of the car in the horizontal direction;
and integrating the acceleration of the car in the vertical direction to obtain the real-time speed and position of the car in the vertical direction.
(22) Acquiring a real-time state in a machine room: and obtaining the real-time state in the machine room according to the temperature of the traction sheave, the operation noise of the machine room and the real-time scene in the machine room.
(30) And (3) judging the mechanical fault of the elevator: and judging the mechanical fault of the elevator according to the real-time state in the elevator car and the real-time state in the machine room.
As shown in fig. 2, the (30) elevator mechanical failure determining step includes:
(31) and (3) fault judgment of the traction sheave: comparing the temperature of the traction sheave with a normal temperature value, and judging that the traction sheave has a mechanical fault when the temperature of the traction sheave exceeds the range of the normal temperature value;
(32) and (3) judging the fault of the traction machine in the machine room: comparing the machine room operation noise with a normal noise value, and preferentially judging that the tractor in the machine room has a mechanical fault when the machine room operation noise exceeds the normal noise value range and the temperature of the traction wheel is in the normal value range;
(33) judging the internal abnormality of the machine room: according to the real-time state in the machine room, if the machine room is filled with obvious water, and dangerous articles or key mechanical parts are damaged obviously, the internal abnormality of the machine room is judged.
(34) Judging abnormity in the elevator car: according to the real-time state in the elevator car, if passengers in the car have abnormal behaviors, obvious water quantity in the car or objects which are easy to cause danger, the abnormality in the elevator car is judged;
(35) and (3) elevator steel wire rope fault judgment: if the traction wheel and the traction machine in the machine room are not abnormal, the mechanical fault of the elevator steel wire rope is preferentially judged according to the abnormal swaying angle of the car and the abnormal acceleration of the car.
Preferably, the (35) elevator rope fault determining step includes:
(351) the car shakes and judges abnormally: when the shaking angle value of the x axis or/and the y axis of the lift car is larger than a normal value, judging that the elevator shakes abnormally;
(352) judging the abnormal acceleration of the car: and when the acceleration in the vertical direction of the car continuously exceeds the specified maximum acceleration, judging that the acceleration of the car is abnormal.
As shown in fig. 3, the elevator mechanical failure monitoring device of the invention comprises an elevator end 1 and a remote end 2.
The remote end 2 comprises a remote monitoring center 21, a 5.8G wireless network bridge 222 in signal connection with the remote monitoring center 21 and an Aliyun Internet of things platform 23;
the elevator end 1 comprises a temperature sensor 11 arranged on a traction sheave in a machine room, a noise sensor 12 and a first network camera 13 arranged in the machine room, a 2.4G wireless network bridge 214, a 5.8G wireless network bridge 115, an industrial personal computer 16 arranged at the top of the machine room, a second network camera 17 arranged in a car, a simplified inertia measurement unit 18 arranged in the car, a microprocessor 19 arranged at the top of the car and a 2.4G wireless network bridge 1110;
the temperature sensor 11, the noise sensor 12, the first network camera 13, the 2.4G wireless network bridge 214 and the 5.8G wireless network bridge 115 are respectively connected with the industrial personal computer 16 through signals.
The second network camera 17, the simplified inertia measurement unit 18 and the 2.4G wireless network bridge 1110 are respectively connected with the microprocessor 19 through signals;
the 2.4G wireless bridge 1110 is connected to the 2.4G wireless bridge 214 through wireless signals, and the 5.8G wireless bridge 115 is connected to the 5.8G wireless bridge 222 through wireless signals.
Preferably, the simplified inertial measurement unit 18 placed inside the car comprises accelerometers mounted orthogonally in the three directions x, y and z, and two gyroscopes mounted orthogonally in the directions x and y, in the coordinate system of the elevator car;
the two gyroscopes which are orthogonally arranged in the x direction and the y direction are used for measuring the angular velocity of the car in the horizontal direction;
and the accelerometers are orthogonally arranged in the x direction, the y direction and the z direction and are respectively used for measuring the acceleration of the car in the horizontal direction and the acceleration of the car in the vertical direction.
The angle of the car in the horizontal direction can be obtained by integrating the angular velocities in the horizontal direction measured by the two gyroscopes orthogonally installed in the horizontal direction, and the angle of the car in the horizontal direction can also be obtained by the ratio relation between the acceleration of the horizontal plane measured by the two accelerometers orthogonally installed in the horizontal direction and the acceleration of gravity. Then, a Kalman filtering algorithm is used for fusing angles measured and calculated by a gyroscope and an accelerometer in the horizontal direction to obtain an accurate horizontal direction shaking angle of the lift car; directly measuring the acceleration of the car in the vertical direction by using an accelerometer in the vertical direction; the network camera of installation in the car can real-time supervision go out in the car personnel safety condition, whether inside the car has into water and other article that easily cause danger.
A temperature sensor on the traction sheave measures a real-time working temperature value of the traction sheave; noise sensor measures the noise value that key mechanical part produced in the computer lab in real time in the computer lab, and the network camera real-time supervision computer lab of installation has into water and other easy dangerous article that cause in the computer lab to whether real-time supervision key mechanical part has obvious damage.
The elevator mechanical failure early warning system can monitor the safety of an elevator system in real time and can investigate specific mechanical failure points in real time, and in addition, the intelligent algorithm is applied to analyze and process failure data through the Aliskian Internet of things platform, so that the elevator mechanical failure can be early and accurately early warned and investigated in the later stage.
The simplified inertia measurement unit in the car not only reduces the system cost and complexity, but also can more accurately position the mechanical fault of the elevator by using the Kalman filtering fusion algorithm.
The 2.4G wireless network bridge with low power is arranged in the elevator system, so that the car data can be sent to the industrial personal computer of the machine room in real time under the anti-interference condition; in addition, the machine room communicates with the remote place by using a 5.8G high-power wireless network bridge, so that the cost of using long-distance cable communication can be saved, and the stability is high under the condition of ensuring the communication distance.
Claims (6)
1. An elevator mechanical fault monitoring method is characterized by comprising the following steps:
(10) elevator data acquisition: collecting elevator operation data, including traction sheave temperature, machine room operation noise, real-time scene inside the machine room, horizontal acceleration of the car, horizontal angular velocity of the car, vertical acceleration of the car and real-time scene inside the car;
(20) elevator data processing: the real-time state in the elevator car and the real-time state in the machine room are obtained by analyzing and processing the elevator operation data;
(30) and (3) judging the mechanical fault of the elevator: and judging the mechanical fault of the elevator according to the real-time state in the elevator car and the real-time state in the machine room.
2. The elevator machine fault monitoring method of claim 1, wherein the (20) elevator data processing step comprises:
(21) obtaining the real-time state in the elevator car: integrating angular velocity of the car in the horizontal direction to obtain an angle of the first car in the horizontal direction;
according to the ratio relation between the acceleration of the car in the horizontal direction and the acceleration of gravity, the angle of the second car in the horizontal direction is obtained;
fusing the horizontal direction angle of the first car and the horizontal direction angle of the second car by using a Kalman filtering algorithm to obtain the shaking angles of the x axis and the y axis of the car in the horizontal direction;
and integrating the acceleration of the car in the vertical direction to obtain the real-time speed and position of the car in the vertical direction.
(22) Acquiring a real-time state in a machine room: and obtaining the real-time state in the machine room according to the temperature of the traction sheave, the operation noise of the machine room and the real-time scene in the machine room.
3. The elevator machine fault monitoring method according to claim 2, wherein the (30) elevator machine fault determining step includes:
(31) and (3) fault judgment of the traction sheave: comparing the temperature of the traction sheave with a normal temperature value, and judging that the traction sheave has a mechanical fault when the temperature of the traction sheave exceeds the range of the normal temperature value;
(32) and (3) judging the fault of the traction machine in the machine room: comparing the machine room operation noise with a normal noise value, and preferentially judging that the tractor in the machine room has a mechanical fault when the machine room operation noise exceeds the normal noise value range and the temperature of the traction wheel is in the normal value range;
(33) judging the internal abnormality of the machine room: according to the real-time state in the machine room, if the machine room is filled with obvious water, and dangerous articles or key mechanical parts are damaged obviously, the internal abnormality of the machine room is judged.
(34) Judging abnormity in the elevator car: according to the real-time state in the elevator car, if passengers in the car have abnormal behaviors, obvious water quantity in the car or objects which are easy to cause danger, the abnormality in the elevator car is judged;
(35) and (3) elevator steel wire rope fault judgment: if the traction wheel and the traction machine in the machine room are not abnormal, the mechanical fault of the elevator steel wire rope is preferentially judged according to the abnormal swaying angle of the car and the abnormal acceleration of the car.
4. The elevator machine fault monitoring method of claim 3, wherein the (35) elevator rope fault determining step comprises:
(351) the car shakes and judges abnormally: when the shaking angle value of the x axis or/and the y axis of the lift car is larger than a normal value, judging that the elevator shakes abnormally;
(352) judging the abnormal acceleration of the car: and when the acceleration in the vertical direction of the car continuously exceeds the specified maximum acceleration, judging that the acceleration of the car is abnormal.
5. An elevator machinery fault monitoring system, includes elevator end (1) and remote end (2), its characterized in that:
the remote end (2) comprises a remote monitoring center (21), a 5.8G wireless network bridge 2(22) and an Ali cloud Internet of things platform (23), wherein the wireless network bridge 2(22) is in signal connection with the remote monitoring center (21);
the elevator end (1) comprises a temperature sensor (11) arranged on a traction sheave in a machine room, a noise sensor (12) and a first network camera (13) arranged in the machine room, a 2.4G wireless network bridge 2(14) and a 5.8G wireless network bridge 1(15) arranged at the top of the machine room, an industrial personal computer (16) arranged at the top of the machine room, a second network camera (17) arranged in a car, a simplified inertia measurement unit (18) arranged in the car, a microprocessor (19) arranged at the top of the car and a 2.4G wireless network bridge 1 (110);
the temperature sensor (11), the noise sensor (12), the first network camera (13), the 2.4G wireless network bridge 2(14) and the 5.8G wireless network bridge 1(15) are respectively connected with an industrial personal computer (16) through signals.
The second network camera (17), the simplified inertia measurement unit (18) and the 2.4G wireless network bridge 1(110) are respectively in signal connection with the microprocessor (19);
the 2.4G wireless bridge 1(110) is connected with the 2.4G wireless bridge 2(14) through wireless signals, and the 5.8G wireless bridge 1(15) is respectively connected with the 5.8G wireless bridge 2(22) through wireless signals.
6. The elevator machine fault monitoring system of claim 1, wherein:
the simplified inertial measurement unit (18) arranged in the elevator car comprises accelerometers which are orthogonally arranged in the x direction, the y direction and the z direction under the coordinate system of the elevator car, and two gyroscopes which are orthogonally arranged in the x direction and the y direction;
the two gyroscopes which are orthogonally arranged in the x direction and the y direction are used for measuring the angular velocity of the car in the horizontal direction;
and the accelerometers are orthogonally arranged in the x direction, the y direction and the z direction and are respectively used for measuring the acceleration of the car in the horizontal direction and the acceleration of the car in the vertical direction.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202010004249.5A CN111268527A (en) | 2020-01-03 | 2020-01-03 | Elevator mechanical fault monitoring method and system |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202010004249.5A CN111268527A (en) | 2020-01-03 | 2020-01-03 | Elevator mechanical fault monitoring method and system |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112141846A (en) * | 2020-09-29 | 2020-12-29 | 深圳市海和科技股份有限公司 | Elevator based on MCU and wireless communication system |
| CN113277396A (en) * | 2021-06-07 | 2021-08-20 | 常熟理工学院 | Elevator health state monitoring method and device and early warning system |
| CN114620572A (en) * | 2022-02-22 | 2022-06-14 | 深圳桥通物联科技有限公司 | System and method for video intercommunication between elevator car and outside |
| CN114671313A (en) * | 2022-04-15 | 2022-06-28 | 苏州汇川控制技术有限公司 | Elevator operation detection method, elevator and computer readable storage medium |
-
2020
- 2020-01-03 CN CN202010004249.5A patent/CN111268527A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112141846A (en) * | 2020-09-29 | 2020-12-29 | 深圳市海和科技股份有限公司 | Elevator based on MCU and wireless communication system |
| CN113277396A (en) * | 2021-06-07 | 2021-08-20 | 常熟理工学院 | Elevator health state monitoring method and device and early warning system |
| CN114620572A (en) * | 2022-02-22 | 2022-06-14 | 深圳桥通物联科技有限公司 | System and method for video intercommunication between elevator car and outside |
| CN114671313A (en) * | 2022-04-15 | 2022-06-28 | 苏州汇川控制技术有限公司 | Elevator operation detection method, elevator and computer readable storage medium |
| CN114671313B (en) * | 2022-04-15 | 2024-03-22 | 苏州汇川控制技术有限公司 | Elevator operation detection method, elevator and computer readable storage medium |
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