A method for monitoring and analyzing faults of an elevator hoisting system

Abstract

The application is suitable for the technical field of elevator fault detection, and particularly relates to a fault monitoring and analyzing method for an elevator traction system, which comprises the following steps: constructing an elevator monitoring system; collecting audio information under different load conditions to obtain running audio data under different load conditions; extracting load data and audio data of corresponding positions in the running audio data, determining a load audio parameter mapping curve corresponding to each monitoring point, and determining whether there is an abnormality based on real-time audio data; when there is an abnormality, moving a steel cable, obtaining real-time audio data in this time period, determining an abnormal area of the steel cable, and outputting a fault monitoring result. The application can realize autonomous inspection of the elevator in the daily operation process of the elevator, actively identify abnormal audio changes caused by broken wires of the steel cable, and output abnormal positions, so that the application can effectively avoid emergency shutdown of the elevator, reduce the frequency of shutdown, and improve the maintenance efficiency.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of elevator fault detection, and particularly relates to a fault monitoring and analysis method for an elevator traction system. BACKGROUND

[0002] The elevator traction system is the core component of modern elevators, mainly responsible for realizing the lifting movement of the elevator car. The system is usually composed of a motor, a traction sheave, a steel wire rope or a steel belt, etc. The motor drives the traction sheave to rotate, and the steel wire rope wound on the traction sheave is connected with the car and the counterweight, and the weight difference between the two and the friction force are used to realize the smooth up and down movement of the car. The design of the traction system needs to consider safety, efficiency and comfort to ensure the safety of passengers and provide a smooth riding experience.

[0003] The current traction elevator mainly relies on manual maintenance for abnormal detection, which is difficult to give early warning before the fault occurs, greatly increases the probability of stopping the elevator, and affects the normal use of the elevator. SUMMARY

[0004] The purpose of the present application is to provide a fault monitoring and analysis method for an elevator traction system, which aims to solve the problem that the current traction elevator mainly relies on manual maintenance for abnormal detection, which is difficult to give early warning before the fault occurs, greatly increases the probability of stopping the elevator, and affects the normal use of the elevator.

[0005] The present application is implemented as follows: a fault monitoring and analysis method for an elevator traction system, the method comprising:

[0006] An elevator monitoring system is constructed, which comprises a plurality of audio collectors and a pressure sensor arranged in the elevator car. The audio collectors are arranged between the traction sheave and the guide sheave for audio information collection at different positions of the steel cable between the traction sheave and the guide sheave.

[0007] Audio information is collected under different load conditions to obtain running audio data under different load conditions.

[0008] The load data and the audio data of the corresponding position in the running audio data are extracted to determine the load audio parameter mapping curve corresponding to each monitoring point, and whether there is an abnormality is determined based on real-time audio data.

[0009] When there is an abnormality, the steel cable is moved to obtain real-time audio data in this time period, the area where the steel cable appears abnormal is determined, and the fault monitoring result is output.

[0010] Preferably, the step of collecting audio information under different load conditions to obtain running audio data under different load conditions comprises:

[0011] obtaining a maximum load of the current elevator, determining a plurality of test loads based on the maximum load;

[0012] placing a corresponding weight of counterweight in the elevator based on the test load, the weight of the counterweight being equivalent to the test load;

[0013] controlling the elevator to run at a preset running speed, recording audio data collected by each audio collector during the running process to obtain running audio data.

[0014] Preferably, the step of extracting load data and audio data of the corresponding position in the running audio data to determine a load audio parameter mapping curve corresponding to each monitoring point, and determining whether an abnormality exists based on real-time audio data, specifically comprises:

[0015] extracting load data of the running audio data to determine audio data collected by different audio collectors under the load test condition, the audio data being represented by a preset audio feature;

[0016] constructing a two-dimensional coordinate system corresponding to each monitoring point, marking the load data corresponding to the monitoring point and the corresponding audio feature in the two-dimensional coordinate system to obtain a load audio parameter mapping curve;

[0017] During the running process, real-time audio data is obtained by the audio collector, and the current real-time load is obtained, and whether an abnormality exists is determined based on the real-time load and the real-time audio data.

[0018] Preferably, the step of controlling the steel cable to move when an abnormality exists, obtaining real-time audio data in this time period, determining an abnormal area of the steel cable, and outputting a fault monitoring result, specifically comprises:

[0019] When it is determined that an abnormality exists, the elevator is controlled to run from the top floor to the bottom floor and from the bottom floor to the top floor, and real-time audio data in the two running processes is recorded.

[0020] extracting an audio feature in the real-time audio data according to the running time, identifying a change trend of the audio feature, and constructing an audio feature curve;

[0021] extracting a turning point in the audio feature curve, regarding the turning point as an abnormal area, recording a position of the elevator at this time, and outputting a fault monitoring result, and recording the position of the abnormal area in the fault monitoring result.

[0022] Preferably, the preset audio feature is an amplitude of the audio.

[0023] Preferably, in the step of collecting audio information under different load conditions to obtain running audio data under different load conditions, the running speed of the elevator remains constant, and when the elevator is in an acceleration stage or a deceleration stage, the running audio data corresponding to the corresponding time period is not recorded.

[0024] Preferably, the audio collector is a directional microphone for collecting audio information at different positions of the steel cable.

[0025] The present application provides a kind of fault monitoring analysis method of elevator hoisting system, by audio acquisition to steel cable, obtain running audio data, based on the change of amplitude in running audio data Determine whether there is abnormality, when there is abnormality, then by dynamic running elevator to determine the position of elevator abnormality, it can realize the self-checking of elevator in the process of daily operation, actively identify the abnormal audio change caused by steel cable broken wire, and output abnormal position, can effectively avoid elevator emergency stop, reduce the frequency of stop, improve the repair efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0026] Figure 1 A flow chart of the fault monitoring analysis method of elevator hoisting system provided by the embodiment of the present application is provided.

[0027] Figure 2 A flow chart of the step of collecting audio information under different load conditions to obtain running audio data under different load conditions provided by the embodiment of the present application is provided.

[0028] Figure 3 A flow chart of the step of extracting load data and corresponding position audio data from running audio data, determining the load audio parameter mapping curve corresponding to each monitoring point, and determining whether there is abnormality based on real-time audio data provided by the embodiment of the present application is provided.

[0029] Figure 4 A flow chart of the step of moving the steel cable when there is abnormality, obtaining real-time audio data in this time period, determining the area of the steel cable where the abnormality occurs, and outputting the fault monitoring result provided by the embodiment of the present application is provided.

[0030] Figure 5 A device installation schematic diagram of the fault monitoring analysis method of elevator hoisting system provided by the embodiment of the present application is provided. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical scheme and advantages of the present application more clear, the present application is further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application, and are not used to limit the present application.

[0032] As Figure 1As shown, a flow chart of a fault monitoring analysis method of an elevator traction system provided by an embodiment of the application, the method comprises:

[0033] S100, an elevator monitoring system is constructed, the elevator monitoring system comprises a plurality of audio collectors and a pressure sensor arranged in an elevator car, the audio collectors are arranged between a traction sheave and a guide sheave, and are used for collecting audio information of different positions of a steel cable between the traction sheave and the guide sheave.

[0034] In this step, the elevator monitoring system is constructed, and during the operation of the elevator, the steel cable will be repeatedly wound due to long-time operation, and the wire breakage is prone to occur in a local position and is difficult to be found through conventional inspection. The elevator monitoring system is constructed in the application, a plurality of audio collectors are arranged on the elevator, for example, five audio collectors are arranged, and the audio collectors are arranged at different positions of the steel cable. Figure 5 As shown, a plurality of audio collectors are arranged between the traction sheave and the guide sheave, the length of the steel cable between the traction sheave and the guide sheave is a fixed value, the audio collectors are installed between the traction sheave and the guide sheave, the audio collectors adopt directional pickups, are used for collecting audio information of different positions of the steel cable, and the pressure sensor arranged at the bottom of the elevator car can detect the total weight of passengers in the car.

[0035] S200, audio information is collected under different load conditions, and running audio data under different load conditions is obtained.

[0036] In this step, the audio information is collected under different load conditions, in order to determine the vibration of the steel cable under different operating states, the test is performed under different load conditions, specifically, a plurality of load weights are determined according to the maximum load of the elevator, a plurality of sampling points are set from the load weight 0 to the maximum load weight, each sampling point corresponds to a load weight, then the elevator is operated under the obtained plurality of load weights, the elevator is controlled to run at a constant speed, during this period, the audio data of different positions of the steel cable are collected by the audio collectors, the audio data are used for recording the vibration, specifically, the audio collectors can also be replaced by a laser vibration tester and other vibration monitoring devices, so that the vibration audio data of each position of the steel cable between the traction sheave and the guide sheave during the operation of the elevator under different load conditions are monitored, and the running audio data are obtained.

[0037] S300, load data and audio data of the corresponding position in the running audio data are extracted, a load audio parameter mapping curve corresponding to each monitoring point is determined, and whether an abnormality exists is determined based on real-time audio data.

[0038] In this step, the load data in the running audio data and the audio data of the corresponding position are extracted. For the same monitoring point, under different load conditions, the tension on the steel cable is different, and the greater the tension, the smaller the vibration amplitude of the steel cable. The vibration of the steel cable at each position is determined without breaking the wire, so as to construct a load audio parameter mapping curve. The load audio parameter mapping curve is used to determine the normal vibration amplitude of the monitoring point under different load weights. In the actual operation of the elevator, the real-time load weight can be obtained through the pressure sensor, and the actual vibration amplitude collected by the audio collector is compared with the normal vibration amplitude. If the difference exceeds the preset range, it is determined that there is vibration anomaly.

[0039] S400, when there is an anomaly, the steel cable is controlled to move, real-time audio data in this time period is obtained, the area where the steel cable appears abnormal is determined, and the fault monitoring result is output.

[0040] In this step, when there is an anomaly, the steel cable is controlled to move. When it is determined that the steel cable has an anomaly, the elevator no longer carries passengers and starts self-checking. The elevator moves uniformly from the top floor to the bottom floor, and then uniformly rises from the bottom floor to the top floor. In this time period, the real-time audio data is recorded by the audio collector, the change curve of the audio parameter is extracted, the running height of the elevator is determined according to the position where the change curve of the audio parameter appears abnormal, so as to determine the position of the steel cable between the traction sheave and the guide sheave at this time, obtain the area where the steel cable appears abnormal, and output the fault monitoring result.

[0041] As shown in Figure 2 As a preferred embodiment of the present application, the step of collecting audio information under different load conditions and obtaining running audio data under different load conditions comprises:

[0042] S201, obtaining the maximum load weight of the current elevator, and determining a plurality of test load weights based on the maximum load weight.

[0043] In this step, the maximum load weight G of the current elevator is obtained. The maximum load weight is the maximum weight that can be loaded by the elevator. If the weight exceeds this weight, the elevator is in an overload state and cannot run. A plurality of test load weights are set according to a preset weight gradient. For example, if the maximum load weight is G and the weight gradient is set to 0.1G, the test load weights obtained are 0G, 0.1G, 0.2G, 0.3G, 0.4G, 0.5G, 0.6G, 0.7G, 0.8G, 0.9G and 1G.

[0044] S202, placing a counterweight with a weight equal to the test load weight in the elevator based on the test load weight.

[0045] S203, controlling the elevator to run according to the preset running speed, and recording the audio data collected by each audio collector to obtain running audio data.

[0046] In this step, when testing, a corresponding weight counterweight is placed in the elevator according to a plurality of test load weights, such as a 0.1G counterweight. In this counterweight condition, the elevator is controlled to uniformly ascend from the bottom floor to the top floor, and then uniformly descend from the top floor to the bottom floor. During the uniform running stage of the elevator, the speed of the elevator is kept constant, and only the audio data collected by the audio collector during the uniform running stage is recorded, which is the running audio data.

[0047] As shown in Figure 3 As a preferred embodiment of the present application, the step of extracting the load data and the audio data of the corresponding position in the running audio data, determining the load audio parameter mapping curve corresponding to each monitoring point, and determining whether there is an abnormality based on the real-time audio data specifically includes:

[0048] S301, extracting the load data of the running audio data, and determining the audio data collected by different audio collectors under the test condition of the load. The audio data is characterized by a preset audio feature.

[0049] In this step, the load data of the running audio data is extracted, and the audio data corresponding to each load condition is extracted through multiple tests under different load conditions. For example, under the condition of a 0.1G load, the elevator is run, and five groups of audio collectors A, B, C, D, and E are obtained. Five groups of audio data a, b, c, d, and e are obtained. The five groups of audio collectors are arranged at different monitoring points, and the monitoring points are defined as 1, 2, 3, 4, and 5. For the No. 1 monitoring point, the corresponding audio data is a, the audio amplitude range in a is extracted, the average value of the amplitude is calculated, and the average value is taken as the audio feature of the monitoring point in the running process.

[0050] S302, constructing a two-dimensional coordinate system corresponding to each monitoring point, marking the load data corresponding to the monitoring point and the corresponding audio feature in the two-dimensional coordinate system, and obtaining a load audio parameter mapping curve.

[0051] In this step, a two-dimensional coordinate system corresponding to each monitoring point is constructed. The values of the audio features detected under different test conditions are different for the same monitoring point, i.e., the average amplitudes are different. The horizontal axis of the two-dimensional coordinate system is the test load weight, and the vertical axis is the average amplitude. Based on the plurality of coordinates generated in the two-dimensional coordinate system, a mapping function is generated, the average amplitude under different test load weights is generated through the mapping function, and the load audio parameter mapping curve corresponding to the monitoring point is obtained.

[0052] S303, in the running process, real-time audio data is acquired by the audio collector, and the current real-time load is acquired, and whether there is a running abnormality is determined based on the real-time load and the real-time audio data.

[0053] In this step, in the running process, the total weight of the passengers in the current car is detected by the pressure sensor, the load audio parameter mapping curve corresponding to each monitoring point is queried based on the total weight, the average amplitude corresponding to each monitoring point is obtained, real-time audio data is acquired by the audio collector, the real-time audio data is sampled based on a preset sliding window size, the real-time average amplitude in the sampling window is counted, the real-time average amplitude of each monitoring point is compared with the average amplitude obtained by querying the load audio parameter mapping curve, if the difference is greater than a preset value, it is determined that the monitoring point has a vibration abnormality, if the proportion of the abnormal monitoring points in the sampling data corresponding to the sliding window is greater than a preset value (such as 80%), it is determined that the sampling data corresponding to the sliding window has an abnormality, if multiple sampling data continuously have an abnormality, it is determined that the current cable has a running abnormality, and the abnormal area needs to be further determined.

[0054] As shown in Figure 4 As a preferred embodiment of the present application, the step of controlling the cable to move when there is an abnormality, acquiring real-time audio data in this time period, determining the area where the cable has an abnormality, and outputting the fault monitoring result, specifically includes:

[0055] S401, when it is determined that there is an abnormality, the elevator is controlled to run from the top floor to the bottom floor and from the bottom floor to the top floor, and real-time audio data in the two running processes is recorded.

[0056] In this step, when it is determined that there is an abnormality, further abnormality positioning is performed, the elevator is controlled to run to the top floor, and when the elevator runs to a preset speed, the speed of the elevator is kept constant, at this time the audio collector is started, and when running to the bottom, the elevator runs again from bottom to top, and real-time audio data in the two running processes is recorded.

[0057] S402, audio features in the real-time audio data are extracted according to the running time, a change trend of the audio features is identified, and an audio feature curve is constructed.

[0058] In this step, audio features in the two running processes are extracted separately, that is, audio features in the upward running process are extracted to construct an upward audio feature curve, the horizontal coordinate of which is the elevator running time and the vertical coordinate of which is the amplitude, and audio data in the downward running process is extracted to obtain a downward audio feature curve, the audio feature curve including the upward audio feature curve and the downward audio feature curve.

[0059] S403, extract the turning point in the audio feature curve, take the turning point as an abnormal area, record the position of the elevator at this time, output the fault monitoring result, and record the position of the abnormal area in the fault monitoring result.

[0060] In this step, the turning point in the audio feature curve is extracted. When the wire breaks, the amplitude corresponding to the area will increase accordingly, and the amplitude of the positions on both sides of the broken wire will gradually decrease to the normal level. The sliding sampling data corresponding to the sliding sampling average amplitude is calculated, and the position where the sliding sampling average amplitude is at the maximum is taken as the turning point. The turning point is the abnormal area, and the average amplitude of the adjacent area of the turning point will be lower than the turning point. The running time of the elevator is determined to determine the height of the elevator, thereby indirectly determining the part of the current wire located in the traction sheave and the guide sheave. Output the fault monitoring result, and record the position of the abnormal area in the fault monitoring result.

[0061] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for failure monitoring analysis of an elevator hoisting system, characterized by The method comprises: The elevator monitoring system comprises a plurality of audio collectors and a pressure sensor arranged in the elevator car, the audio collectors being arranged between the traction sheave and the guide sheave to collect audio information of different positions of the steel cable between the traction sheave and the guide sheave; Audio information is collected under different load conditions to obtain running audio data under different load conditions; Load data and audio data of the corresponding position in the running audio data are extracted to determine a load audio parameter mapping curve corresponding to each monitoring point, and it is determined whether an abnormality exists based on real-time audio data; When an abnormality exists, the steel cable is controlled to move, real-time audio data in this time period is obtained, an abnormal area of the steel cable is determined, and a fault monitoring result is output.

2. The failure monitoring analysis method of an elevator hoisting system according to claim 1, characterized by, The step of collecting audio information under different load conditions to obtain running audio data under different load conditions comprises: The maximum load of the current elevator is obtained, and a plurality of test load weights are determined based on the maximum load; A counterweight with a weight equal to the test load weight is placed in the elevator based on the test load weight; The elevator is controlled to run at a preset running speed, and audio data collected by each audio collector is recorded during running to obtain running audio data.

3. The failure monitoring analysis method of an elevator hoisting system according to claim 1, characterized by, The step of extracting load data and audio data of the corresponding position in the running audio data to determine a load audio parameter mapping curve corresponding to each monitoring point and determining whether an abnormality exists based on real-time audio data comprises: Load data of the running audio data is extracted to determine audio data collected by different audio collectors under the load test condition, and the audio data is represented by a preset audio feature; A two-dimensional coordinate system corresponding to each monitoring point is constructed, the load data corresponding to the monitoring point and the corresponding audio feature are marked in the two-dimensional coordinate system, and a load audio parameter mapping curve is obtained; During running, real-time audio data is obtained by the audio collector, and the current real-time load is obtained, and it is determined whether an abnormality exists based on the real-time load and the real-time audio data.

4. The failure monitoring analysis method of an elevator hoisting system according to claim 1, characterized by, The step of controlling the steel cable to move when an abnormality exists, obtaining real-time audio data in this time period, determining an abnormal area of the steel cable, and outputting a fault monitoring result comprises: When it is determined that an abnormality exists, the elevator is controlled to run from the top floor to the bottom floor and from the bottom floor to the top floor, and real-time audio data in the two running processes is recorded; Audio features in the real-time audio data are extracted according to the running time, a change trend of the audio features is identified, and an audio feature curve is constructed; A turning point in the audio feature curve is extracted, the turning point is regarded as an abnormal area, the position of the elevator at this time is recorded, and a fault monitoring result is output, and the position of the abnormal area is recorded in the fault monitoring result.

5. The failure monitoring analysis method of an elevator hoisting system according to claim 3, characterized by, The preset audio feature is the amplitude of the audio.

6. The failure monitoring analysis method of an elevator hoisting system according to claim 1, characterized by, In the step of collecting audio information under different load conditions to obtain running audio data under different load conditions, the running speed of the elevator remains constant, and when the elevator is in an acceleration stage or a deceleration stage, the running audio data corresponding to the corresponding time period is not recorded.

7. The failure monitoring analysis method of an elevator hoisting system according to claim 1, characterized by, The audio collector is a directional sound collector, which is used for collecting audio information at different positions of the steel cable.

Images