A method for intelligent monitoring of belt wear in a belt conveyor

Abstract

This invention relates to an intelligent monitoring method for belt wear of a belt conveyor. It collects acceleration signals during the constant-speed operation of the motor, and converts these signals from the time domain to the frequency domain through data processing and FFT calculation. A belt wear frequency model and a motor output shaft wear frequency model are constructed to calculate the belt wear frequency and motor output shaft wear frequency values. The method then determines whether there exists an amplitude in the frequency domain signal equal to these values. Furthermore, it combines frequency domain signal values ​​from other operating stages of the belt conveyor to analyze and determine the degree of belt wear. This method eliminates the need for extensive calculations using edge detection algorithms, allowing for real-time monitoring and assessment of belt wear directly from the belt conveyor's operation.

Description

Technical Field

[0001] This invention relates to the field of belt wear measurement technology, and more specifically, to an intelligent monitoring method for belt wear of a belt conveyor. Background Technology

[0002] In industrial production, belt conveyors are commonly used conveying equipment that transports materials longitudinally via belt conveying. They are widely used in building materials, mining, chemical, light industry, machinery, power, and grain industries. During operation, the weight of the conveyed material and its impact on the belt cause wear. Insufficient friction between the belt and the drive pulley can cause the belt to stop rotating, leading to belt damage due to friction, and even serious consequences such as belt failure. This affects the conveying efficiency and belt life of the belt conveyor.

[0003] Traditional manual inspection struggles to detect wear defects on belts operating at high speeds, easily overlooking hidden, minute damage and leading to missed detections. Furthermore, it cannot predict belt wear. In recent years, machine vision technology has developed rapidly, and machine vision-based inspection technologies are increasingly widely used in production and daily life. Existing belt wear detection technologies utilize visible light image edge detection. This involves acquiring belt images with a visible light camera, extracting crack information using edge detection algorithms, and then using SVM (Support Vector Machine) for supervised machine learning to classify the damaged belt images. While this method offers advantages such as being non-contact and highly intelligent, traditional edge detection algorithms struggle to identify cracks with depth information in two-dimensional belt images, resulting in limited detection accuracy. Moreover, such deep learning network models are often computationally intensive, hindering efficient defect detection. Summary of the Invention

[0004] The problem addressed by this invention is how to provide an intelligent belt wear monitoring method that can reduce computational load and monitor belt wear in real time.

[0005] To address the aforementioned problems, this invention provides an intelligent monitoring method for belt wear in a belt conveyor. The belt conveyor includes a frame and a motor, pulleys, and a belt mounted on the frame. Each pulley includes a drive pulley and a driven pulley. The drive pulley is located at the top of the frame, and the driven pulley is located at the bottom of the frame. The belt passes over the drive pulley and forms a belt loop with the driven pulley. The output shaft of the motor is connected to the drive pulley. The frame is equipped with an inductive sensor for sensing the speed of the motor output shaft and an acceleration sensor for collecting the motor's acceleration signal at the location corresponding to the motor's output shaft. The operating stages of the belt conveyor include lifting acceleration, lifting at constant speed, lifting deceleration, descent acceleration, descent at constant speed, and descent deceleration. The intelligent monitoring method for belt wear includes:

[0006] Step 1: The belt conveyor is in operation. The inductive sensor senses the speed of the motor output shaft in real time and determines the operating stage of the belt conveyor in real time; the accelerometer collects the acceleration signal of the motor in real time.

[0007] Step 2: Clean the acceleration signal and then convert it into a frequency domain signal using FFT calculation;

[0008] Step 3: Construct a model for calculating belt wear frequency:

[0009] Belt wear frequency = π × drive wheel speed × drive wheel diameter / belt length;

[0010] Construct a calculation model for the wear frequency of the motor output shaft:

[0011] Driven wheel wear frequency = Driven wheel speed × Driven wheel diameter / Driven wheel diameter;

[0012] Step 4: Determine whether the belt wear frequency value and the driven wheel wear frequency value calculated in Step 3 exist in the frequency domain signal corresponding to the constant speed lifting or constant speed lowering phase of the belt elevator. If they exist, the belt of the belt elevator has a wear fault, and proceed to Step 5. If they do not exist, the process ends.

[0013] Step 5: First, determine whether the amplitude of the frequency domain signal corresponding to the constant speed lifting stage and the constant speed descent stage of the belt conveyor shows an upward trend. If yes, proceed to Step 6; otherwise, end the process.

[0014] Step 6: Determine whether the amplitude change of the frequency domain signal corresponding to the lifting acceleration and lowering acceleration operation phases of the belt elevator exceeds the preset threshold Y. If yes, proceed to step 7; otherwise, the belt wear degree is determined to be slight belt wear.

[0015] Step 7: Determine whether the amplitude change of the frequency domain signal corresponding to the lifting and deceleration phases of the belt conveyor exceeds the preset threshold Z. If yes, the belt wear is determined to be severe; otherwise, the belt wear is determined to be moderate.

[0016] The beneficial effects of this invention are as follows: By collecting the acceleration signal during the uniform speed operation of the motor, and converting the time-domain signal into a frequency-domain signal through data processing and FFT calculation, the belt wear frequency model and the wear rotation frequency model of the motor output shaft are constructed to calculate the belt wear frequency value and the wear rotation frequency value of the motor output shaft. It is determined whether there is an amplitude in the frequency domain signal that is equal to the belt wear frequency value and the wear rotation frequency value of the motor output shaft. Furthermore, the degree of belt wear is analyzed and judged by combining the frequency domain signal values ​​of other operating stages of the belt elevator. It does not require a large amount of calculation through edge detection algorithms, and the belt wear condition can be judged directly through real-time monitoring of the operation of the belt elevator.

[0017] Preferably, the inductive sensor in step one, which senses the speed of the motor output shaft in real time and determines the operating stage of the belt conveyor in real time, specifically includes:

[0018] Set the initial position of the belt elevator to the bottom of the belt elevator, which is the stop position, and preset the maximum speed of the belt elevator to X;

[0019] The belt conveyor begins its upward movement, first entering an acceleration phase. During this phase, the inductive sensor detects that the motor output shaft speed increases from zero to its maximum speed X. Next, the conveyor enters a constant-speed phase, where the inductive sensor detects that the motor output shaft speed remains at its maximum speed X. Then, the conveyor enters a deceleration phase, where the inductive sensor detects that the motor output shaft speed decreases from its maximum speed X back to zero. Finally, the conveyor reaches the top of the frame.

[0020] The belt conveyor begins its downward movement, entering a descent acceleration phase. During this phase, the inductive sensor detects that the motor output shaft speed increases from zero to the maximum speed -X. Next, the conveyor enters a descent constant speed phase, where the inductive sensor detects that the motor output shaft speed remains at the maximum speed -X. Then, the conveyor enters a descent deceleration phase, where the inductive sensor detects that the motor output shaft speed decelerates from the maximum speed -X back to zero. Finally, the conveyor returns to its stop position.

[0021] Preferably, the accelerometer acquires the motor acceleration signal at a fixed sampling rate of 2.5 kHz;

[0022] Preferably, step five, determining whether the amplitude of the frequency domain signal corresponding to the uniform lifting and descent running phases of the belt conveyor shows an upward trend, specifically includes: sequentially comparing the amplitude difference ΔW between two adjacent frequency domain signals; if 85% of the amplitude difference ΔW is greater than zero, then it is determined that the amplitude of the frequency domain signal corresponding to the uniform lifting and descent running phases of the belt conveyor shows an upward trend.

[0023] Preferably, step six, determining whether the amplitude change of the frequency domain signal corresponding to the lifting acceleration and descent acceleration phases of the belt conveyor exceeds a preset threshold Y, specifically includes: sequentially comparing the amplitude differences ΔW1, ΔW2, ... ΔW of two adjacent frequency domain signals. n And calculate the rate of change f1, f2, ... f between adjacent amplitude differences. n-1Determine each rate of change |f1|, |f2|, ..., |f n-1 Is it greater than the preset threshold Y?

[0024] Preferably, the preset threshold Y is 0.3.

[0025] Preferably, step seven, determining whether the amplitude change of the frequency domain signal corresponding to the lifting deceleration and lowering deceleration phases of the belt conveyor exceeds a preset threshold Z, specifically includes: sequentially comparing the amplitude differences ΔW1, ΔW2, ... ΔW of two adjacent frequency domain signals. n And calculate the rate of change q1, q2, ... q between adjacent amplitude differences. n-1 Determine each rate of change |q1|, |q2|, ..., |q n-1 Is it greater than the preset threshold Z?

[0026] Preferably, the preset threshold Z is 0.2. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the belt conveyor.

[0028] Figure 2 This is a schematic diagram illustrating the operational stages of a belt conveyor.

[0029] Figure 3 To calculate the amplitude diagram by segmenting the acceleration signal;

[0030] Figure 4 To obtain the amplitude spectrum of the frequency domain signal;

[0031] Explanation of reference numerals in the attached figures:

[0032] 1. Frame; 2. Motor; 3. Belt; 4. Drive wheel; 5. Driven wheel; 6. Inductive sensor; 7. Accelerometer. Detailed Implementation

[0033] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0034] A method for intelligent monitoring of belt wear in a belt conveyor, wherein the belt conveyor is as follows: Figure 1As shown, the system includes a frame 1 and a motor 2, pulleys, and a belt 3 mounted on the frame 1. The pulleys include a drive pulley 4 and a driven pulley 5. The drive pulley 4 is located at the top of the frame 1, and the driven pulley 5 is located at the bottom of the frame 1. The belt 3 loops around the drive pulley 4 and the driven pulley 5, forming a belt loop. The output shaft of the motor 2 is connected to the drive pulley 4. The frame 1 is equipped with an inductive sensor 6 for sensing the speed of the motor 2's output shaft and an acceleration sensor 7 for collecting the acceleration signal of the motor 2 at the location corresponding to the output shaft of the motor 2. The operating stages of the belt conveyor include lifting acceleration, lifting constant speed, lifting deceleration, descent acceleration, descent constant speed, and descent deceleration. Figure 2 As shown, the intelligent monitoring method for belt 3 wear includes:

[0035] Step 1: The belt conveyor operates. The inductive sensor 6 senses the speed of the output shaft of the motor 2 in real time and determines the operating stage of the belt conveyor in real time; the accelerometer 6 collects the acceleration signal of the motor 2 in real time. Specifically, the inductive sensor 6's real-time sensing of the speed of the output shaft of the motor 2 and determination of the operating stage of the belt conveyor includes:

[0036] Set the initial position of the belt elevator to the bottom of the belt elevator, which is the stop position, and preset the maximum speed of the belt elevator to X;

[0037] The belt conveyor begins its upward movement, first entering an acceleration phase. During this phase, the inductive sensor 6 detects that the rotational speed of the motor 2 output shaft increases from zero to its maximum speed X. Next, the conveyor enters a constant-speed phase, where the inductive sensor 6 detects that the rotational speed of the motor 2 output shaft remains at its maximum speed X. Then, the conveyor enters a deceleration phase, where the inductive sensor 6 detects that the rotational speed of the motor 2 output shaft decelerates from its maximum speed X back to zero. The conveyor then reaches the top of the frame.

[0038] The belt conveyor begins its downward movement, entering a descent acceleration phase. During this phase, the inductive sensor 6 detects that the rotational speed of the motor 2 output shaft increases from zero to its maximum speed -X. Next, the conveyor enters a descent constant-speed phase, where the inductive sensor 6 detects that the rotational speed of the motor 2 output shaft remains at its maximum speed -X. Then, the conveyor enters a descent deceleration phase, during which the inductive sensor 6 detects that the rotational speed of the motor 2 output shaft decelerates from its maximum speed -X back to zero. The conveyor then returns to its stop position.

[0039] The accelerometer 7 acquires the motor acceleration signal at a fixed sampling rate of 2.5 kHz;

[0040] Step 2: Clean the acceleration signal and then convert it into a frequency domain signal using FFT calculation. Data cleaning of the acceleration signal is existing technology and will not be elaborated upon here. FFT calculation (Fast Fourier Transform) is also existing technology; it is an efficient algorithm for calculating the Discrete Fourier Transform, which can convert time-domain signals into frequency-domain signals. This is also existing technology and will not be elaborated upon here. In this specific embodiment, the acquired acceleration signal is decomposed into several data segments according to a fixed ratio. Each segment undergoes FFT calculation, and the frequency amplitude after each FFT calculation is averaged using an averaging algorithm, i.e., F(n) = (X1 + X2 + ... + X...). n ) / N, where X1 is the frequency amplitude calculated in the first section, X n The frequency amplitude is calculated in the nth section, where N represents the number of sections of data. Figure 3 As shown, it can effectively remove noise from the data; the final result is as follows. Figure 4 The frequency domain signal shown;

[0041] Step 3: Construct a model for calculating belt wear frequency:

[0042] Belt wear frequency = π × drive wheel speed × drive wheel diameter / belt length;

[0043] Construct a calculation model for the wear frequency of the motor output shaft:

[0044] Driven wheel wear frequency = Driven wheel speed × Driven wheel diameter / Driven wheel diameter;

[0045] Step 4: Determine whether the belt wear frequency value and the driven wheel wear frequency value calculated in Step 3 exist in the frequency domain signal corresponding to the uniform speed lifting or descent phase of the belt elevator. If they exist, the belt 3 of the belt elevator has a wear fault, and proceed to Step 5. If they do not exist, the process ends.

[0046] Step 5: First, determine whether the amplitude of the frequency domain signal corresponding to the constant lifting speed stage and the constant descent speed stage of the belt elevator shows an upward trend. If yes, proceed to Step 6; otherwise, end. Specifically, this includes: comparing the amplitude difference ΔW between two adjacent frequency domain signals in turn. If 85% of the amplitude differences ΔW are greater than zero, it is determined that the amplitude of the frequency domain signal corresponding to the constant lifting speed stage and the constant descent speed stage of the belt elevator shows an upward trend.

[0047] Step Six: Determine whether the amplitude change of the frequency domain signal corresponding to the lifting acceleration and descent acceleration phases of the belt conveyor exceeds the preset threshold Y. If yes, proceed to Step Seven; otherwise, the belt wear degree is determined to be slight belt wear. Specifically, this includes: sequentially comparing the amplitude differences ΔW1, ΔW2, ... ΔW of two adjacent frequency domain signals. nAnd calculate the rate of change f1, f2, ... f between adjacent amplitude differences. n-1 Determine each rate of change |f1|, |f2|, ..., |f n-1 |Whether it is greater than a preset threshold Y, in this specific embodiment the preset threshold Y is 0.3;

[0048] Step 7: Determine whether the amplitude change of the frequency domain signal corresponding to the lifting and lowering deceleration phases of the belt conveyor exceeds the preset threshold Z. If yes, the belt wear is determined to be severe; otherwise, the belt wear is determined to be moderate. Specifically, this includes sequentially comparing the amplitude differences ΔW1, ΔW2, ..., ΔW of two adjacent frequency domain signals. n And calculate the rate of change q1, q2, ... q between adjacent amplitude differences. n-1 Determine each rate of change |q1|, |q2|, ..., |q n-1 |Whether it is greater than a preset threshold Z, in this specific embodiment, the preset threshold Z is 0.2.

[0049] While the disclosure is as stated above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of this disclosure, and all such changes and modifications will fall within the protection scope of this invention.

Claims

1. A method for intelligent monitoring of belt wear in a belt conveyor, characterized in that, The belt conveyor includes a frame (1) and a motor (2), pulleys, and belt (3) mounted on the frame (1). The pulleys include a drive wheel (4) and a driven wheel (5). The drive wheel (4) is located at the top of the frame (1), and the driven wheel (5) is located at the bottom of the frame (1). The belt (3) passes around the drive wheel (4) and forms a belt loop with the driven wheel (5). The output shaft of the motor (2) is connected to the drive wheel (4). The frame (1) is provided with an inductive sensor (6) for sensing the speed of the motor output shaft and an acceleration sensor (7) for collecting the motor acceleration signal at the output shaft of the motor (2). The operating stages of the belt conveyor include lifting acceleration, lifting constant speed, lifting deceleration, descent acceleration, descent constant speed, and descent deceleration. The intelligent monitoring method for belt wear includes: Step 1: The belt conveyor is in operation. The inductive sensor (6) senses the speed of the output shaft of the motor (2) in real time and determines the operating stage of the belt conveyor in real time; the acceleration sensor (7) collects the acceleration signal of the motor (2) in real time. Step 2: Clean the acceleration signal and then convert it into a frequency domain signal using FFT calculation; Step 3: Construct a model for calculating belt wear frequency: Belt wear frequency = π × drive wheel speed × drive wheel diameter / belt length; Construct a calculation model for the wear frequency of the motor output shaft: Driven wheel wear frequency = Driven wheel speed × Driven wheel diameter / Driven wheel diameter; Step 4: Determine whether the belt wear frequency value and the driven wheel wear frequency value calculated in Step 3 exist in the frequency domain signal corresponding to the constant speed lifting or constant speed lowering phase of the belt elevator. If they exist, the belt of the belt elevator has a wear fault, and proceed to Step 5. If they do not exist, the process ends. Step 5: First, determine whether the amplitude of the frequency domain signal corresponding to the constant speed lifting stage and the constant speed descent stage of the belt conveyor shows an upward trend. If yes, proceed to Step 6; otherwise, end the process. Step 6: Determine whether the amplitude change of the frequency domain signal corresponding to the lifting acceleration and lowering acceleration operation phases of the belt elevator exceeds the preset threshold Y. If yes, proceed to step 7; otherwise, the belt wear degree is determined to be slight belt wear. Step 7: Determine whether the amplitude change of the frequency domain signal corresponding to the lifting and deceleration phases of the belt conveyor exceeds the preset threshold Z. If yes, the belt wear is determined to be severe; otherwise, the belt wear is determined to be moderate.

2. The intelligent monitoring method for belt wear of a belt conveyor according to claim 1, characterized in that, In step one, the inductive sensor (6) senses the speed of the output shaft of the motor (2) in real time and determines the operating stage of the belt conveyor in real time, specifically including: Set the initial position of the belt elevator to the bottom of the belt elevator, which is the stop position, and preset the maximum speed of the belt elevator to X; The belt elevator begins to move upwards. First, it enters the acceleration phase. During the acceleration phase, the inductive sensor (6) detects that the speed of the output shaft of the motor (2) increases from zero to the maximum speed X. Then, the belt elevator enters the constant speed phase. During the constant speed phase, the inductive sensor (6) detects that the speed of the output shaft of the motor (2) remains at the maximum speed X. Then, the belt elevator enters the deceleration phase. During the deceleration phase, the inductive sensor (6) detects that the speed of the output shaft of the motor (2) decreases from the maximum speed X to zero. The belt elevator reaches the top of the frame. The belt elevator begins to move downwards, entering the acceleration phase. During this phase, the inductive sensor (6) detects that the speed of the output shaft of the motor (2) increases from zero to the maximum speed -X. Then, the belt elevator enters the constant speed phase, where the inductive sensor (6) detects that the speed of the output shaft of the motor (2) remains at the maximum speed -X. Next, the belt elevator enters the deceleration phase, during which the inductive sensor (6) detects that the speed of the output shaft of the motor (2) decreases from the maximum speed -X to zero. The belt elevator then returns to the stop position.

3. The intelligent monitoring method for belt wear of a belt conveyor according to claim 1, characterized in that, The accelerometer (7) acquires the motor acceleration signal at a fixed sampling rate of 2.5KHz.

4. The intelligent monitoring method for belt wear of a belt conveyor according to claim 1, characterized in that, Step five, determining whether the amplitude of the frequency domain signal corresponding to the uniform lifting and descent phases of the belt conveyor shows an upward trend, specifically includes: comparing the amplitude difference ΔW between two adjacent frequency domain signals sequentially. If 85% of the amplitude differences ΔW are greater than zero, then it is determined that the amplitude of the frequency domain signal corresponding to the uniform lifting and descent phases of the belt conveyor shows an upward trend.

5. The intelligent monitoring method for belt wear of a belt conveyor according to claim 1, characterized in that, Step six, determining whether the amplitude change of the frequency domain signal corresponding to the lifting acceleration and descent acceleration phases of the belt conveyor exceeds the preset threshold Y, specifically includes: sequentially comparing the amplitude differences ΔW1, ΔW2, ... ΔW of two adjacent frequency domain signals. n And calculate the rate of change f1, f2, ... f between adjacent amplitude differences. n-1 Determine each rate of change |f1|, |f2|, ..., |f n-1 Is it greater than the preset threshold Y? 6. The intelligent monitoring method for belt wear of a belt conveyor according to claim 5, characterized in that, The preset threshold Y is 0.

3.

7. The intelligent monitoring method for belt wear of a belt conveyor according to claim 1, characterized in that, Step seven, determining whether the amplitude change of the frequency domain signal corresponding to the lifting deceleration and lowering deceleration phases of the belt conveyor exceeds the preset threshold Z, specifically includes: sequentially comparing the amplitude differences ΔW1, ΔW2, ... ΔW of two adjacent frequency domain signals. n And calculate the rate of change q1, q2, ... q between adjacent amplitude differences. n-1 Determine each rate of change |q1|, |q2|, ..., |q n-1 Is it greater than the preset threshold Z? 8. The intelligent monitoring method for belt wear of a belt conveyor according to claim 7, characterized in that, The preset threshold Z is 0.2.

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