Fault monitoring and analyzing method for elevator traction system

Abstract

The invention is applicable to 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 of: constructing an elevator monitoring system; audio information collection is carried out under different load conditions, and operation audio data under different load conditions are obtained; extracting load data in the operation audio data and audio data at corresponding positions, determining a load audio parameter mapping curve corresponding to each monitoring point, and judging whether abnormity exists or not based on the real-time audio data; and when the abnormity exists, controlling the steel cable to move, acquiring real-time audio data in the time period, determining an area where the steel cable is abnormal, and outputting a fault monitoring result. According to the method, automatic inspection of the elevator can be achieved in the daily operation process of the elevator, abnormal audio changes caused by wire breakage of the steel cable are actively recognized, the abnormal position is output, emergency shutdown of the elevator can be effectively avoided, the shutdown frequency is reduced, and the overhaul efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of elevator fault detection, and in particular relates to a fault monitoring and analysis method for an elevator traction system. Background Art

[0002] The elevator traction system is a core component of modern elevators, primarily responsible for the raising and lowering motion of the elevator car. This system typically consists of an electric motor, a traction sheave, and steel ropes or belts. The motor drives the traction sheave, which is connected to the car and counterweight via a steel rope wound around the traction sheave. The weight difference between the two and friction create a smooth upward and downward motion of the car. The traction system's design must consider safety, efficiency, and comfort to ensure passenger safety and a smooth ride.

[0003] Current traction elevators mainly rely on manual maintenance for abnormality detection, which makes it difficult to provide early warning before a fault occurs, greatly increasing the probability of elevator shutdown and affecting the normal use of the elevator. Summary of the Invention

[0004] The purpose of the present invention is to provide a fault monitoring and analysis method for an elevator traction system, aiming to solve the problem that current traction elevators mainly rely on manual maintenance to detect abnormalities, making it difficult to provide early warning before a fault occurs, greatly increasing the probability of elevator shutdown and affecting the normal use of the elevator.

[0005] The present invention is implemented as follows: a fault monitoring and analysis method for an elevator traction system, the method comprising: Constructing an elevator monitoring system, the elevator monitoring system includes multiple audio collectors and a pressure sensor disposed in the elevator car, wherein the audio collector is disposed between the traction sheave and the guide sheave and is used to collect audio information at different positions of the steel rope between the traction sheave and the guide sheave; Collect audio information under different load conditions to obtain operating audio data under different load conditions; Extract the load data and audio data of the corresponding position from the running audio data, determine the load audio parameter mapping curve corresponding to each monitoring point, and determine whether there is an abnormality based on the real-time audio data; When an abnormality occurs, the steel cable is controlled to move, real-time audio data within this time period is obtained, the area where the abnormality occurs is determined, and the fault monitoring results are output.

[0006] Preferably, the step of collecting audio information under different load conditions and obtaining operating audio data under different load conditions includes: Obtain the maximum load capacity of the current elevator, and determine multiple test load weights based on the maximum load capacity; Place a ballast of corresponding weight in the elevator based on the test load weight. The weight of the ballast is equal to the test load weight. The elevator is controlled to run at a preset speed. During the running process, the audio data collected by each audio collector is recorded to obtain running audio data.

[0007] Preferably, the steps of extracting the load data and the audio data of the corresponding position from 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 include: Extract the load data of the running audio data, determine the audio data collected by different audio collectors under the load test conditions, and characterize the audio data using preset audio features; Construct a two-dimensional coordinate system corresponding to each monitoring point, mark the load data and corresponding audio features corresponding to the monitoring point in the two-dimensional coordinate system, and obtain a load audio parameter mapping curve; During operation, real-time audio data is obtained through the audio collector, and the current real-time load is obtained. Based on the real-time load and real-time audio data, it is determined whether there is any operation abnormality.

[0008] Preferably, the steps of controlling the steel cable to move when an abnormality occurs, acquiring real-time audio data within this time period, determining the area where the abnormality occurs in the steel cable, and outputting the fault monitoring result specifically include: When an abnormality is determined, the elevator is controlled to run from the top floor to the bottom floor and from the bottom floor to the top floor, and the real-time audio data of the two operations is recorded; Extract audio features from real-time audio data according to runtime, identify changing trends of audio features, and construct audio feature curves; Extract the turning point in the audio feature curve, regard the turning point as the 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.

[0009] Preferably, the preset audio feature is the amplitude of the audio.

[0010] Preferably, in the step of collecting audio information under different load conditions and obtaining operating audio data under different load conditions, the operating speed of the elevator remains constant, and when the elevator is in the acceleration stage or deceleration stage, the operating audio data corresponding to the corresponding time period is not recorded.

[0011] Preferably, the audio collector is a directional microphone for collecting audio information at different positions of the steel cable.

[0012] The present invention provides a fault monitoring and analysis method for an elevator traction system. The method obtains operating audio data by collecting audio from a steel cable, determines whether an abnormality exists based on changes in the amplitude of the operating audio data, and determines the location of the abnormality by dynamically operating the elevator when an abnormality exists. The method can realize autonomous inspection of the elevator during its daily operation, actively identify abnormal audio changes caused by broken steel cables, and output the abnormal location. The method can effectively avoid emergency shutdowns of the elevator, reduce the frequency of shutdowns, and improve maintenance efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A flowchart of a fault monitoring and analysis method for an elevator traction system provided by an embodiment of the present invention; Figure 2 A flowchart of the steps of collecting audio information under different load conditions and obtaining operating audio data under different load conditions provided by an embodiment of the present invention; Figure 3 A flowchart of the steps of extracting load data and audio data of corresponding positions from operating audio data, determining a load audio parameter mapping curve corresponding to each monitoring point, and determining whether an anomaly exists based on real-time audio data, provided by an embodiment of the present invention; Figure 4 A flowchart of the steps of controlling the movement of a steel cable when an abnormality occurs, acquiring real-time audio data within this time period, determining the area where the abnormality occurs, and outputting fault monitoring results, provided by an embodiment of the present invention; Figure 5 A schematic diagram of equipment installation for a fault monitoring and analysis method for an elevator traction system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0014] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0015] like Figure 1 FIG. 1 is a flow chart of a fault monitoring and analysis method for an elevator traction system provided by an embodiment of the present invention, the method comprising: S100, constructing an elevator monitoring system, which includes multiple audio collectors and a pressure sensor arranged in the elevator car. The audio collector is arranged between the traction wheel and the guide wheel, and is used to collect audio information at different positions of the steel cable between the traction wheel and the guide wheel.

[0016] In this step, an elevator monitoring system is constructed. During the operation of the elevator, due to long-term operation, the steel cable will be repeatedly wound, which is prone to wire breakage. The wire breakage occurs in a local position and is difficult to be found by conventional inspection. The present invention constructs an elevator monitoring system and sets multiple groups of audio collectors on the elevator, such as setting 5 groups of audio collectors, such as Figure 5 As shown, multiple audio collectors are set between the traction wheel and the guide wheel of the elevator. The length of the steel cable between the traction wheel and the guide wheel is a fixed value. The audio collector is installed between the traction wheel and the guide wheel. The audio collector uses a directional pickup to collect audio information at different positions of the steel cable. The pressure sensor installed at the bottom of the elevator car can detect the total weight of the passengers in the car.

[0017] S200: Collect audio information under different load conditions to obtain operating audio data under different load conditions.

[0018] In this step, audio information is collected under different load conditions. In order to determine the vibration of the steel cable under different operating conditions, tests are performed under different load conditions. Specifically, multiple load weights are determined according to the maximum load of the elevator. From load weight 0 to the maximum load weight, multiple sampling points are set. Each sampling point corresponds to a load weight. The elevator is operated under the obtained multiple load weights to control the elevator to run at a uniform speed. During this period, audio data at different positions of the steel cable are collected by an audio collector, and the audio data is used to record its vibration conditions. Specifically, the audio collector can also be replaced by vibration monitoring equipment such as a laser vibrometer, so as to monitor and obtain vibration audio data at various locations on the steel cable between the traction wheel and the guide wheel when the elevator is running under different load conditions, and obtain operating audio data.

[0019] S300, extracting the load data and the audio data of the corresponding position from 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.

[0020] In this step, the load data and the audio data of the corresponding position in the running audio data are extracted. For the same monitoring point, under different load conditions, the tension on the steel cable is different. The greater the tension, the smaller the vibration amplitude of the steel cable will be. The vibration conditions of the steel cable at various locations are measured when there is no wire breakage in the steel cable, 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. During the actual operation of the elevator, the real-time load weight can be obtained through the pressure sensor to query the normal vibration amplitude of each monitoring point, and the actual vibration amplitude collected by the audio collector is compared with it. If the difference exceeds the preset range, it is determined that there is a vibration abnormality.

[0021] S400, when an abnormality occurs, controls the steel cable to move, obtains real-time audio data within this time period, determines the area where the abnormality occurs, and outputs the fault monitoring result.

[0022] In this step, when there is an abnormality, the steel cable is controlled to move. When it is determined that there is an abnormality in the steel cable, the elevator stops carrying passengers and starts self-inspection. The elevator is controlled to move at a constant speed from the top floor to the bottom floor, and then rises at a constant speed from the bottom floor to the top floor. During this time period, real-time audio data is recorded by the audio collector, and the change curve of the audio parameters is extracted. The operating height of the elevator is determined according to the position where the change curve of the audio parameters changes, thereby determining the position of the steel cable passing between the traction wheel and the guide wheel at this time, obtaining the area where the steel cable has an abnormality, and outputting the fault monitoring results.

[0023] like Figure 2 As shown, as a preferred embodiment of the present invention, the step of collecting audio information under different load conditions and obtaining operating audio data under different load conditions includes: S201, obtaining the maximum load capacity of the current elevator, and determining a plurality of test load weights based on the maximum load capacity.

[0024] In this step, the maximum load weight G of the current elevator is obtained. The maximum load weight is the maximum weight that the elevator can load. If this weight is exceeded, the elevator is in an overloaded state and cannot run. Multiple test load weights are set according to the 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.

[0025] S202: placing a counterweight of corresponding weight in the elevator based on the test load weight, wherein the weight of the counterweight is equal to the test load weight.

[0026] S203, controlling the elevator to run according to a preset running speed, and during the running process, recording the audio data collected by each audio collector to obtain running audio data.

[0027] In this step, when conducting the test, counterweights of corresponding weights are placed in the elevator according to multiple test load weights. For example, a counterweight of 0.1G is placed. Under this counterweight condition, the elevator is controlled to rise from the ground floor to the top floor at a uniform speed, and then descend from the top floor to the ground floor at a uniform speed. During the uniform speed operation 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 speed stage is recorded, which is the running audio data.

[0028] like Figure 3As shown, as a preferred embodiment of the present invention, the steps of extracting load data and audio data of corresponding positions from the operating 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 include: S301, extracting load data of running audio data, determining audio data collected by different audio collectors under the load test condition, and characterizing the audio data using preset audio features.

[0029] In this step, the load data of the running audio data is extracted. Multiple tests are carried out under different load conditions, and the audio data corresponding to each load condition is extracted each time. For example, under the load condition of 0.1G, the elevator is running, and the five groups of audio collectors are A, B, C, D and E, and the five groups of audio data are a, b, c, d and e. The five groups of audio collectors are set at different monitoring points, and the monitoring points are defined as 1, 2, 3, 4 and 5. For monitoring point 1, the corresponding audio data is a. The audio amplitude range in a is extracted, and the average value of its amplitude is calculated. The average value is used as the audio feature of the monitoring point during operation.

[0030] S302: Construct a two-dimensional coordinate system corresponding to each monitoring point, mark the load data and corresponding audio features corresponding to the monitoring point in the two-dimensional coordinate system, and obtain a load audio parameter mapping curve.

[0031] In this step, a two-dimensional coordinate system corresponding to each monitoring point is constructed. The values ​​of the audio features detected at the same monitoring point under different test conditions are different, that is, the average amplitude is different. The horizontal axis of the two-dimensional coordinate system is the test load weight, and the vertical axis is the average amplitude. Function fitting is performed based on the multiple coordinates generated in the two-dimensional coordinate system to generate a corresponding mapping function. The average amplitude under different test load weights is generated through the mapping function to obtain the load audio parameter mapping curve corresponding to the monitoring point.

[0032] S303, during operation, real-time audio data is obtained through the audio collector, and the current real-time load is obtained, and whether there is an operation abnormality is determined based on the real-time load and the real-time audio data.

[0033] In this step, during operation, the total weight of the passengers in the current car is detected by a pressure sensor, and the load audio parameter mapping curve corresponding to each monitoring point is queried based on the total weight to obtain the average amplitude corresponding to each monitoring point. Real-time audio data is obtained through an audio collector, and the real-time audio data is sampled based on a preset sliding window size. The real-time average amplitude within the sampling window is counted, and 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 the preset value, it is determined that the monitoring point has abnormal vibration. If the proportion of abnormal monitoring points in the sampling data corresponding to the sliding window is greater than the preset value (such as 80%), it is determined that the sampling data corresponding to the sliding window has an abnormality. If there are multiple consecutive sampling data with abnormalities, it is determined that the current steel cable has an abnormal operation and the abnormal area needs to be further determined.

[0034] like Figure 4 As shown, as a preferred embodiment of the present invention, the steps of controlling the steel cable to move when an abnormality occurs, acquiring real-time audio data within this time period, determining the area where the steel cable has an abnormality, and outputting the fault monitoring result specifically include: 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 during the two operations is recorded.

[0035] In this step, when it is determined that there is an abnormality, further abnormality positioning is performed, and the elevator is controlled to run to the top floor and then run downward from the top floor. After the elevator runs to the preset speed, the speed of the elevator is kept constant. At this time, the audio collector is started, and when it runs to the bottom, it runs from bottom to top again, and the real-time audio data during the two runs is recorded.

[0036] S402 , extracting audio features from real-time audio data according to the running time, identifying the changing trend of the audio features, and constructing an audio feature curve.

[0037] In this step, the audio features of the two running processes are extracted separately. That is, the audio features of the upward process are extracted to construct the upward audio feature curve, whose horizontal axis is the elevator running time and the vertical axis is the amplitude. Similarly, the audio data of the downward process is retrieved to obtain the downward audio feature curve. The audio feature curve includes the upward audio feature curve and the downward audio feature curve.

[0038] S403, extracting the turning point in the audio feature curve, treating the turning point as an abnormal area, recording the position of the elevator at this time, outputting the fault monitoring result, and recording the position of the abnormal area in the fault monitoring result.

[0039] In this step, the turning point in the audio characteristic curve is extracted. When a wire breaks in the wire rope, the amplitude corresponding to the area will increase accordingly, while the amplitude at the positions on both sides of the broken wire will gradually decrease to a normal level. The audio characteristic curve is slip sampled, and the sampling average amplitude corresponding to the slip sampling data is calculated. The position where the sampling average amplitude is at the maximum value is taken as the turning point. This turning point is the abnormal area, and the average amplitude of the area adjacent to the turning point will be lower than the turning point. The elevator height is determined based on the elevator's running time, thereby indirectly determining the part of the current wire rope located at the traction wheel and guide wheel, outputting the fault monitoring result, and recording the position of the abnormal area in the fault monitoring result.

[0040] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A fault monitoring and analysis method for an elevator traction system, characterized in that: The method comprises: Constructing an elevator monitoring system, the elevator monitoring system includes multiple audio collectors and a pressure sensor disposed in the elevator car. The audio collector is disposed between the traction sheave and the guide sheave to collect audio information at different positions of the steel rope between the traction sheave and the guide sheave. Collect audio information under different load conditions to obtain operating audio data under different load conditions; Extract the load data and audio data of the corresponding position from the running audio data, determine the load audio parameter mapping curve corresponding to each monitoring point, and determine whether there is an abnormality based on the real-time audio data; When an abnormality occurs, the steel cable is controlled to move, real-time audio data within this time period is obtained, the area where the abnormality occurs is determined, and the fault monitoring results are output.

2. The fault monitoring and analysis method for an elevator traction system according to claim 1, characterized in that: The step of collecting audio information under different load conditions to obtain operating audio data under different load conditions includes: Obtain the maximum load capacity of the current elevator, and determine multiple test load weights based on the maximum load capacity; Place a ballast of corresponding weight in the elevator based on the test load weight. The weight of the ballast is equal to the test load weight. The elevator is controlled to run at a preset speed. During the running process, the audio data collected by each audio collector is recorded to obtain running audio data.

3. The fault monitoring and analysis method for an elevator traction system according to claim 1, characterized in that: The steps of extracting the load data and the audio data of the corresponding position from 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 include: Extract the load data of the running audio data, determine the audio data collected by different audio collectors under the load test conditions, and characterize the audio data using preset audio features; Construct a two-dimensional coordinate system corresponding to each monitoring point, mark the load data and corresponding audio features corresponding to the monitoring point in the two-dimensional coordinate system, and obtain a load audio parameter mapping curve; During operation, real-time audio data is obtained through the audio collector, and the current real-time load is obtained. Based on the real-time load and real-time audio data, it is determined whether there is any operation abnormality.

4. The fault monitoring and analysis method for an elevator traction system according to claim 1, characterized in that: The steps of controlling the steel cable to move when an abnormality occurs, acquiring real-time audio data within this time period, determining the area where the abnormality occurs, and outputting the fault monitoring result specifically include: When an abnormality is determined, the elevator is controlled to run from the top floor to the bottom floor and from the bottom floor to the top floor, and the real-time audio data of the two operations is recorded; Extract audio features from real-time audio data according to runtime, identify changing trends of audio features, and construct audio feature curves; Extract the turning point in the audio feature curve, regard the turning point as the 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.

5. The fault monitoring and analysis method for an elevator traction system according to claim 3, characterized in that: The preset audio feature is the amplitude of the audio.

6. The fault monitoring and analysis method for an elevator traction system according to claim 1, characterized in that: In the steps of collecting audio information under different load conditions and obtaining operating audio data under different load conditions, the operating speed of the elevator remains constant. When the elevator is in the acceleration stage or deceleration stage, the operating audio data corresponding to the corresponding time period is not recorded.

7. The fault monitoring and analysis method for an elevator traction system according to claim 1, characterized in that: The audio collector is a directional pickup used to collect audio information at different positions of the cable.

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