Method for analyzing hidden damage of conveyor belt by using magnetic characteristics

Abstract

The invention relates to the technical field of material physical property detection in the aspect of conveyer belt hidden damage, and discloses a method for analyzing conveyer belt hidden damage by utilizing magnetic characteristics, which comprises the following steps: acquiring hysteresis loop data in real time, identifying slope inflection points of magnetization and demagnetization stages as reference marks, and determining the conveyer belt hidden damage on the basis of a dynamic mapping relation between a time interval and an amplitude ratio. Morphological distortion caused by speed fluctuation is corrected through a phase synchronization mechanism, and damage judgment is achieved in combination with energy integral correction and gradient direction analysis. According to the method, speed interference and damage signals are decoupled through phase attributes in a hysteresis loop, total element analysis logic of damage characteristics is constructed through multi-dimensional data cooperation, and the detection confidence coefficient and the positioning precision under the complex working condition are remarkably improved; meanwhile, based on single sensor deep analysis and dynamic reference adaptive calibration, all-weather stable monitoring under zero hardware transformation cost is realized, and a high-robustness and low-cost hidden damage detection solution is provided for heavy industrial scenes such as mines and ports.

Description

Technical Field

[0001] The present invention relates to the technical field of material physical property detection for hidden damage of conveyor belts, and in particular to a method for analyzing hidden damage of conveyor belts by utilizing magnetic characteristics. Background Art

[0002] In terms of quality control and safety testing of conveyor belts, identifying potential defects by measuring the physical properties of materials is an important technical means. In the prior art, the magnetic characteristic analysis method for conveyor belt damage is mainly through measuring and analyzing the magnetic response of the conveyor belt under the action of a magnetic field, that is, the hysteresis loop. The hysteresis loop can reflect the magnetization characteristics of the material, and the physical defects inside the conveyor belt material, such as cracks, fractures or non-uniformity, will directly affect its magnetic behavior and show specific changes or distortions on the hysteresis loop. By extracting and analyzing these hysteresis loop features, the physical state of the conveyor belt can be evaluated and whether there is damage.

[0003] However, in practical applications, especially in the online detection scenario of conveyor belts, a key technical challenge is how to accurately measure and analyze its inherent magnetic physical properties without being interfered by external factors. Among them, the dynamic fluctuation of the conveyor belt running speed is a significant interference factor. Due to load changes, motor speed regulation and other reasons, the speed of the conveyor belt is not constant. This speed change will directly affect the magnetization and demagnetization process of the conveyor belt material, resulting in distortion of the measured hysteresis loop morphology. This change in the hysteresis loop morphology caused by speed fluctuations is similar in some aspects to the distortion caused by the physical defects of the material itself, which brings serious troubles to the damage analysis based on magnetic physical properties and easily leads to misjudgment of the true physical state of the conveyor belt. In order to reduce the impact of speed fluctuations on the measurement of magnetic physical properties, the commonly used methods in the prior art are:

[0004] 1. Sacrificing the sensitivity of the measurement, by reducing the sensitivity of the magnetic detection system, the impact of speed changes on the hysteresis loop shape can be reduced, thereby reducing the risk of misjudgment. However, the direct consequence of this approach is that for subtle physical damage in the conveyor belt, the changes in magnetic characteristics caused by it may be small, and it is difficult to be effectively captured under low-sensitivity measurement conditions, resulting in potential minor damage that cannot be discovered in time, which is obviously not conducive to the comprehensive assessment and safety of the conveyor belt's physical state. 2. Some existing technical solutions attempt to introduce additional speed measurement devices, such as speed sensors, to obtain real-time speed information of the conveyor belt, and establish mathematical models based on these speed data to compensate or correct the measured hysteresis loop. These methods attempt to separate the impact of speed changes from the measured magnetic physical data, thereby more accurately reflecting the true magnetic physical properties of the conveyor belt material. However, these solutions also have some inherent problems, such as increasing the complexity and cost of the test system: additional sensors and complex signal processing units will undoubtedly increase hardware costs and system integration difficulties, and establishing an accurate speed compensation model often requires a large amount of experimental data and complex algorithms. When the conveyor belt speed changes rapidly, the accuracy and real-time performance of the model are difficult to guarantee, and may not truly reflect the instantaneous magnetic physical properties of the material. In addition, the additional sensors themselves may also have measurement errors and may be affected by environmental factors, which will have an adverse effect on the final physical property analysis results. Summary of the invention

[0005] The technical problem solved by the present invention is to provide a method for analyzing hidden damage of a conveyor belt using magnetic characteristics in response to the defects existing in the above-mentioned prior art, so as to solve the problems of hysteresis loop morphology distortion caused by dynamic fluctuation of the conveyor belt running speed proposed in the above-mentioned background technology, as well as high implementation cost and poor real-time performance of traditional multi-sensor solutions.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows: a method for analyzing hidden damage of a conveyor belt using magnetic characteristics, comprising the following steps: Step S1, acquiring in real time the hysteresis loop data of the conveyor belt during operation, wherein the hysteresis loop data includes the corresponding relationship between the magnetic field intensity and the time series in the magnetization stage and the demagnetization stage; Step S2, identifying a first slope inflection point as a magnetization reference mark in the magnetization stage, wherein the first slope inflection point is a critical point where the slope first suddenly changes in a rising edge of the magnetic field intensity varying with time; Step S3, identifying a second slope inflection point as a demagnetization reference mark in the demagnetization stage, wherein the second slope inflection point is a critical point where the slope of the falling edge of the magnetic field intensity changing with time first undergoes a sudden change; Step S4, according to the time interval between the magnetized reference mark and the demagnetized reference mark , calculate the ratio of the magnetic field strength amplitudes of the two ,in is the magnetic field intensity amplitude corresponding to the magnetized reference mark, is the magnetic field intensity amplitude corresponding to the demagnetization reference mark, and the amplitude ratio satisfies the following relationship: , in, is the preset phase synchronization constant, It is the reference time interval of the conveyor belt at the standard operating speed; Step S5, based on the amplitude ratio The mapping relationship with the preset phase synchronization baseline dynamically adjusts the time axis ratio and the amplitude axis ratio of the hysteresis loop so that the slope inflection points of the adjusted magnetization stage and demagnetization stage are aligned to the phase synchronization baseline; Step S6, outputting the corrected hysteresis loop data, and determining the hidden damage position of the conveyor belt according to the abnormal distortion characteristics of the magnetic field intensity distribution in the corrected data.

[0007] As a further solution of the present invention, the method for identifying the first slope inflection point in step S2 includes: performing a first-order derivative calculation on the curve of magnetic field intensity variation with time during the magnetization stage, and defining the position where the derivative first drops below 20% of the peak value as the first slope inflection point.

[0008] As a further solution of the present invention, the dynamic adjustment in step S5 includes: When it is less than a preset threshold, the time axis ratio of the hysteresis loop is compressed and the amplitude axis ratio is enlarged; when When the time difference between the magnetized reference mark and the demagnetized reference mark is greater than a preset threshold, the time axis ratio is stretched and the amplitude axis ratio is reduced until the time difference between the magnetized reference mark and the demagnetized reference mark is Ratio to Amplitude The product of reaches the preset synchronization constant.

[0009] As a further solution of the present invention, the method for setting the phase synchronization reference line includes: when the conveyor belt is in an undamaged state, collecting the temporal and spatial distribution characteristics of the magnetization reference mark and the demagnetization reference mark of the hysteresis loop when the conveyor belt is running at the standard speed, and calculating the synchronization constant by the following formula : , in, is the magnetic field intensity amplitude of the magnetized reference mark in the undamaged state, is the magnetic field intensity amplitude of the demagnetized reference mark in an undamaged state, is the base time interval for both.

[0010] As a further solution of the present invention, the method for determining abnormal distortion characteristics in step S6 includes: calculating the local curvature of the corrected hysteresis loop, marking the continuous area where the curvature exceeds a preset threshold as a potential damage area, and performing a magnetic field intensity gradient analysis on the area; if the gradient change rate exceeds 3 times the historical baseline value, it is determined to be hidden damage.

[0011] As a further solution of the present invention, the method further includes a dynamic phase synchronization verification step: in the corrected hysteresis loop data, if the slope inflection points of the magnetization stage and the demagnetization stage are not completely aligned to the phase synchronization baseline, then steps S2 to S5 are repeatedly executed until the time difference between the two is Ratio to Amplitude The product error is less than 5%.

[0012] As a further solution of the present invention, the amplitude ratio in step S4 The calculation method includes: performing sliding window mean filtering on the magnetic field intensity data of the magnetized reference mark and the demagnetized reference mark, and taking 80% of the peak value after filtering as and The calculation base value of .

[0013] As a further solution of the present invention, the method also includes a damage verification step: when hidden damage is detected, the conveyor belt is triggered to slow down to 50% of the standard speed, the hysteresis loop data is recollected and a secondary correction is performed, and if the damage characteristics still exist after the secondary correction, a damage alarm signal is generated.

[0014] As a further solution of the present invention, the method for acquiring hysteresis loop data includes: symmetrically arranging magnetic induction probe arrays on both sides of the conveyor belt, collecting magnetic field intensity distribution data in real time, and eliminating environmental magnetic field interference through differential calculation.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: based on the spatiotemporal alignment characteristics of the slope inflection points of the magnetization and demagnetization stages of the hysteresis loop, the morphological distortion caused by speed fluctuations is converted into reversible correction parameters, and the physical separation of speed interference and damage signals is achieved through endogenous phase difference perception and dynamic scaling of the time axis. Since the mechanism does not need to rely on external sensors or complex compensation models, it fundamentally solves the misjudgment problem caused by speed-damage coupling in the dynamic speed regulation scenario of the traditional method; by integrating the time evolution characteristics of the hysteresis loop (inflection point amplitude ratio), energy integral difference and gradient direction distribution, a multi-dimensional cross-validation logic for damage judgment is constructed, for example, the energy integral difference compensates for the interference of load mutation on magnetization energy, and the gradient direction maps the material failure mode (gradient attenuation of surface cracks and step mutation of internal peeling), so as to significantly improve the detection confidence under complex working conditions through multi-dimensional collaboration; it avoids relying on multi-sensor fusion in hardware, for example, using the spatiotemporal multi-dimensional data analysis of a single magnetic sensor (time axis stretching, amplitude axis scaling, energy integral calculation) to achieve full-factor detection of hidden damage to the conveyor belt. This path can directly reuse the existing production line magnetic induction equipment to avoid hardware transformation costs, and provide a plug-and-play detection upgrade solution for heavy industrial scenarios such as mines and ports. At the same time, it adopts lightweight inflection point detection algorithms (such as first-order derivative threshold truncation) and closed-loop verification processes to achieve real-time processing and anti-electromagnetic interference capabilities under extreme working conditions such as sudden stops of conveyor belts and sudden load changes, ensuring stable operation around the clock in strong noise environments such as mines and metallurgy. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0017] Figure 1 The present invention is a flow chart of the method for analyzing hidden damage of a conveyor belt using magnetic characteristics.

[0018] Figure 2 This is a flow chart of the dynamic phase synchronization correction of the present invention.

[0019] Figure 3 This is a flow chart of the hidden damage determination based on local curvature and magnetic field gradient of the present invention.

[0020] Figure 4 This is a functional module structure diagram of the conveyor belt hidden damage detection system of the present invention.

[0021] Figure 5 It is a schematic diagram of the structure of the multi-dimensional damage analysis module of the present invention. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] See also Figure 1 , a method for analyzing hidden damage of a conveyor belt using magnetic characteristics, comprising the following steps: Step S1, acquiring in real time the hysteresis loop data of the conveyor belt during operation, wherein the hysteresis loop data includes the corresponding relationship between the magnetic field intensity and the time series in the magnetization stage and the demagnetization stage; Step S2, identifying a first slope inflection point as a magnetization reference mark in the magnetization stage, wherein the first slope inflection point is a critical point where the slope first suddenly changes in a rising edge of the magnetic field intensity varying with time; Step S3, identifying a second slope inflection point as a demagnetization reference mark in the demagnetization stage, wherein the second slope inflection point is a critical point where the slope of the falling edge of the magnetic field intensity changing with time first undergoes a sudden change; Step S4, according to the time interval between the magnetized reference mark and the demagnetized reference mark , calculate the ratio of the magnetic field strength amplitudes of the two ,in is the magnetic field intensity amplitude corresponding to the magnetized reference mark, is the magnetic field intensity amplitude corresponding to the demagnetization reference mark, and the amplitude ratio satisfies the following relationship: , in, is the preset phase synchronization constant, It is the reference time interval of the conveyor belt at the standard operating speed; Step S5, based on the amplitude ratio The mapping relationship with the preset phase synchronization baseline dynamically adjusts the time axis ratio and the amplitude axis ratio of the hysteresis loop so that the slope inflection points of the adjusted magnetization stage and demagnetization stage are aligned to the phase synchronization baseline; Step S6, outputting the corrected hysteresis loop data, and determining the hidden damage position of the conveyor belt according to the abnormal distortion characteristics of the magnetic field intensity distribution in the corrected data.

[0024] As a further solution of the present invention, the method for identifying the first slope inflection point in step S2 includes: performing a first-order derivative calculation on the curve of magnetic field intensity variation with time during the magnetization stage, and defining the position where the derivative first drops below 20% of the peak value as the first slope inflection point.

[0025] As a further solution of the present invention, the dynamic adjustment in step S5 includes: When it is less than a preset threshold, the time axis ratio of the hysteresis loop is compressed and the amplitude axis ratio is enlarged; when When the time difference between the magnetized reference mark and the demagnetized reference mark is greater than a preset threshold, the time axis ratio is stretched and the amplitude axis ratio is reduced until the time difference between the magnetized reference mark and the demagnetized reference mark is Ratio to Amplitude The product of reaches the preset synchronization constant.

[0026] As a further solution of the present invention, the method for setting the phase synchronization reference line includes: when the conveyor belt is in an undamaged state, collecting the temporal and spatial distribution characteristics of the magnetization reference mark and the demagnetization reference mark of the hysteresis loop when the conveyor belt is running at the standard speed, and calculating the synchronization constant by the following formula : , in, is the magnetic field intensity amplitude of the magnetized reference mark in the undamaged state, is the magnetic field intensity amplitude of the demagnetized reference mark in an undamaged state, is the base time interval for both.

[0027] As a further solution of the present invention, the method for determining abnormal distortion characteristics in step S6 includes: calculating the local curvature of the corrected hysteresis loop, marking the continuous area where the curvature exceeds a preset threshold as a potential damage area, and performing a magnetic field intensity gradient analysis on the area; if the gradient change rate exceeds 3 times the historical baseline value, it is determined to be hidden damage.

[0028] As a further solution of the present invention, the method further includes a dynamic phase synchronization verification step: in the corrected hysteresis loop data, if the slope inflection points of the magnetization stage and the demagnetization stage are not completely aligned to the phase synchronization baseline, then steps S2 to S5 are repeatedly executed until the time difference between the two is Ratio to Amplitude The product error is less than 5%.

[0029] As a further solution of the present invention, the amplitude ratio in step S4 The calculation method includes: performing sliding window mean filtering on the magnetic field intensity data of the magnetized reference mark and the demagnetized reference mark, and taking 80% of the peak value after filtering as and The calculation base value of .

[0030] As a further solution of the present invention, the method also includes a damage verification step: when hidden damage is detected, the conveyor belt is triggered to slow down to 50% of the standard speed, the hysteresis loop data is recollected and a secondary correction is performed, and if the damage characteristics still exist after the secondary correction, a damage alarm signal is generated.

[0031] As a further solution of the present invention, the method for acquiring hysteresis loop data includes: symmetrically arranging magnetic induction probe arrays on both sides of the conveyor belt, collecting magnetic field intensity distribution data in real time, and eliminating environmental magnetic field interference through differential calculation.

[0032] See also Figure 2 This is a dynamic phase synchronization correction flow chart of the present invention, which shows the process of dynamic phase synchronization verification of the corrected hysteresis loop data. The user first checks the corrected hysteresis loop data, and the data will be input into the slope inflection point recognition module and the time interval and amplitude ratio calculation module. After the two modules work together, the results are input into the dynamic adjustment module; at the same time, the judgment step of analyzing whether the slope inflection point is aligned will evaluate the corrected hysteresis loop data. If it is not completely aligned, it will trigger the re-identification step and re-enter the calculation. and / The loop is adjusted based on the amplitude ratio until the slope inflection point is analyzed again to determine whether the alignment is complete, that is, the alignment error is less than 5%. At this time, new correction data is output for the user to view, thereby ensuring that the slope inflection points in the magnetization stage and the demagnetization stage can be accurately aligned. Figure 3 , the hidden damage determination process provided by the present invention includes the following steps: first input the corrected hysteresis loop data, and then calculate the local curvature to preliminarily identify abnormal changes in the hysteresis loop morphology; when the curvature is greater than the threshold, the system will extract the abnormal area and further calculate the magnetic field gradient to quantify the rate of change of the magnetic field intensity along the spatial distribution; if the calculated gradient exceeds three times the historical benchmark, that is, it is judged that the gradient is greater than the historical benchmark × 3, then the hidden damage confirmation is performed; on the contrary, if the curvature does not exceed the threshold or the gradient does not meet the judgment conditions, it is judged to be lossless or return to the process for further analysis, to ensure that the damage identification results have high accuracy and anti-interference capabilities. And if Figure 4As shown, the conveyor belt hidden damage detection system provided by the present invention includes a magnetic induction probe array, a hysteresis loop acquisition module, a data preprocessing module, a reference mark recognition module, a phase synchronization correction module, a damage judgment module and an alarm output module. Among them, the magnetic induction probe array is arranged on both sides of the conveyor belt to collect magnetic field intensity distribution data in real time; the hysteresis loop acquisition module receives the probe signal and forms hysteresis loop data; the data preprocessing module performs operations such as denoising and sliding mean filtering on the original hysteresis loop; the reference mark recognition module determines the magnetization reference mark and the demagnetization reference mark by analyzing the slope mutation points in the magnetization stage and the demagnetization stage; the phase synchronization correction module dynamically adjusts the time axis and amplitude axis ratio of the hysteresis loop according to the time interval and amplitude ratio between the reference marks to achieve the correction of morphological distortion; the damage judgment module identifies potential hidden damage according to the local curvature of the corrected hysteresis loop and the magnetic field intensity gradient characteristics; the alarm output module generates an alarm signal after determining that it is damaged, so as to achieve the system's highly robust online monitoring capability. See. Figure 5 The multi-dimensional damage analysis module of the present invention integrates three characteristic dimensions: magnetic intensity gradient direction, energy integral calculation, and time evolution analysis, and inputs them into the judgment center for comprehensive evaluation. The magnetic intensity gradient direction is used to reflect the spatial trend of the local magnetic field change of the material, the energy integral calculation is used to measure the energy difference of the hysteresis loop to identify the impact of load mutation, and the time evolution analysis is used to track the dynamic changes of characteristic points over time during magnetization and demagnetization. The judgment center combines the above three data sources to realize multi-angle cross-validation analysis of potential defects, and finally outputs the hidden damage results, which significantly improves the judgment reliability and result accuracy under complex working conditions.

[0033] Embodiment 1: In the current technology, the distortion of the hysteresis loop will bring inaccuracy to the damage detection, especially when the conveyor belt running speed changes, this distortion may mislead the damage judgment. To this end, the specific steps adopted in this implementation description are: Step 1: Real-time acquisition of hysteresis loop data, this step is to arrange magnetic induction sensor arrays on both sides of the conveyor belt to collect the hysteresis loop data of the conveyor belt in real time when it is running. These data include the corresponding relationship between the magnetic field intensity and the time series in the magnetization and demagnetization stages. The data acquisition system can automatically transmit these data to the processing system for further analysis; Step 2: Identify the slope inflection point in the magnetization stage. In the magnetization stage, the system identifies the first mutation point of the slope by calculating the first-order derivative of the curve of the change of magnetic field intensity over time. In this way, the magnetization reference mark is determined, avoiding the potential errors in the traditional method through fixed thresholds or over-reliance on hardware sensors. The key to this step is to accurately calculate the change of the first-order derivative to ensure that the identification of the reference mark is more accurate; Step 3: Identify the slope inflection point in the demagnetization stage. Similarly, in the demagnetization stage, the system uses the curve of the change of magnetic field intensity over time to calculate the mutation point of the slope. The identification method of this inflection point is similar to that of the magnetization stage, ensuring the accurate determination of the demagnetization reference mark. This method avoids the errors that may be caused by the traditional fixed model and increases the adaptability of the system; Step 4: Calculation and dynamic adjustment of time interval and amplitude ratio. The amplitude ratio is calculated based on the time interval between the magnetization reference mark and the demagnetization reference mark. The calculation formula of the amplitude ratio is the ratio of the magnetic field strength in the magnetization stage to the demagnetization stage. Through this ratio, the operation status of the conveyor belt is further analyzed. In order to cope with the interference caused by speed fluctuations during the operation of the conveyor belt, the system dynamically adjusts the ratio of the time axis to the amplitude axis. This adjustment is carried out through the mapping relationship between the ratio and the preset synchronization baseline. Through this mechanism, the distortion caused by the change in operating speed can be eliminated in real time to ensure the accuracy of the data; Step 5: Correction and damage judgment of hysteresis loop data. After dynamic adjustment, the corrected hysteresis loop data is output. By analyzing these correction data, it is determined whether there is hidden damage. The damage location is determined based on the abnormal distortion characteristics of the magnetic field intensity distribution, especially in the local curvature and gradient change rate; Step 6: Dynamic phase synchronization verification, in order to further eliminate the influence of speed fluctuations, the system repeats the dynamic phase synchronization step based on the corrected data to ensure that the magnetization and demagnetization reference marks are fully aligned to the phase synchronization reference line. This verification step has a high degree of completion, ensuring the detection accuracy under complex working conditions.

[0034] At the same time, in order to adapt to the impact of equipment aging and environmental changes, this embodiment introduces a dynamic adaptive update mechanism. By real-time monitoring of the hysteresis loop data of the conveyor belt in an undamaged state, the synchronization constant is recalculated regularly to compensate for the drift of the synchronization baseline caused by equipment aging. This design greatly improves the long-term stability and robustness of the system, ensuring that even under extreme working conditions, it can still maintain efficient hidden damage detection capabilities. Compared with traditional methods, this embodiment no longer requires a complex multi-sensor array, but instead uses a single magnetic sensor combined with algorithm processing to achieve efficient and low-cost hidden damage detection. The simplification of this hardware solution not only reduces the equipment investment cost, but also improves the application flexibility of the system. And in order to improve the credibility of the detection, this embodiment comprehensively considers multiple factors such as the time evolution characteristics of the hysteresis loop, the energy integral difference, and the gradient direction distribution. Through this multi-dimensional cross-validation, not only can surface cracks be identified, but also hidden damage such as internal interlayer peeling can be accurately diagnosed.

[0035] Example 2: In the amplitude ratio formula, is the magnetic field intensity amplitude corresponding to the magnetized reference mark, defined as the amplitude when the magnetic field intensity reaches its peak value in the rising phase, The amplitude of the magnetic field intensity corresponding to the demagnetization reference mark is defined as the amplitude when the magnetic field intensity drops to the minimum value during the demagnetization stage. Through the amplitude of the magnetic field intensity of these reference marks, the hysteresis loop can be dynamically adjusted to eliminate the interference caused by speed fluctuations. It is a parameter determined by the system under standard working conditions, which is used to describe the relationship between the time interval between the magnetization and demagnetization stages and the ratio of the magnetic field intensity amplitude. The formula is: , in, is the magnetic field intensity amplitude of the magnetized reference mark in the undamaged state, is the magnetic field intensity amplitude of the demagnetized reference mark in an undamaged state, is the base time interval for both.

[0036] In this embodiment, by calculating the amplitude ratio of the magnetic field strength in the magnetization stage and the demagnetization stage, the health status of the conveyor belt can be effectively reflected. The amplitude ratio formula is: , Where ΔT is the time interval between magnetization and demagnetization, is the time interval at standard operating speed, is the preset synchronization constant.

[0037] Dynamic adjustment process: When When it is less than the preset threshold, the system will compress the time axis ratio and expand the amplitude axis ratio; When it is greater than the preset threshold, the system will stretch the time axis scale and reduce the amplitude axis scale; this process ensures that the slope inflection points of the magnetization stage and the demagnetization stage are aligned to the phase synchronization reference line.

[0038] Through the above optimization steps, high-precision detection of hidden damage to the conveyor belt can be achieved, avoiding misjudgment caused by speed fluctuations or load changes, and ensuring the stability of the equipment after long-term use through an adaptive benchmark update mechanism. The specific implementation is as follows: Step S1: Acquire hysteresis loop data in real time. Magnetic induction probe arrays are arranged on both sides of the conveyor belt to collect the relationship between the magnetic field intensity and the time series when the conveyor belt is running.

[0039] Step S2: In the magnetization stage, the first-order derivative calculation is used to identify the slope inflection point and determine the position of the magnetization reference mark. Similarly, in the demagnetization stage, the demagnetization reference mark is determined by a similar method.

[0040] Step S3: Calculate the amplitude ratio of the magnetic field strength of the magnetized and demagnetized reference marks to determine the amplitude ratio and compare it with the preset synchronization constant.

[0041] Step S4: If the amplitude ratio is less than the threshold, compress the time axis ratio and enlarge the amplitude axis ratio; if the amplitude ratio is greater than the threshold, stretch the time axis ratio and reduce the amplitude axis ratio to ensure that after the time axis and amplitude axis ratio of the hysteresis loop are adjusted, the magnetization and demagnetization reference marks are aligned to the phase synchronization reference line.

[0042] Step S5: The corrected hysteresis loop data determines the location of hidden damage according to the abnormal distortion characteristics of the magnetic field intensity distribution. The damaged area is further determined by local curvature calculation and magnetic field intensity gradient analysis.

[0043] Step S6: In the corrected data, if the slope inflection points of the magnetization phase and the demagnetization phase are not completely aligned to the phase synchronization reference line, repeat steps S2 to S4 until the synchronization accuracy reaches a preset standard.

[0044] Step S7: Regularly collect hysteresis loop data in an undamaged state and update the synchronization constant To compensate for the impact of equipment aging or environmental factors on hysteresis characteristics.

[0045] In the dynamic correction mechanism, the present invention realizes effective correction for speed fluctuation or load change by dynamically adjusting the time axis ratio and amplitude axis ratio. The system can achieve high robustness and low misjudgment rate under high-speed operation conditions; through endogenous phase difference perception and dynamic adjustment of time and space, the high cost and synchronization problems of external sensors and complex data fusion models are avoided; through real-time updating of synchronization constants, the system can adapt to environmental factors such as equipment aging, temperature and humidity changes, and ensure long-term stable operation, which are all extended implementation methods known to ordinary technicians in this field.

[0046] Embodiment 3: In this embodiment, the preset phase synchronization constant It can be obtained by collecting and analyzing the hysteresis loop data of the conveyor belt in an intact state for many times. Specifically, when the conveyor belt is in a healthy and undamaged state, its hysteresis loop data at different operating speeds can be collected, and according to the formula:

[0047] , Calculate a reference phase synchronization constant .in, and Represent the magnetic field intensity amplitude at the reference mark in the magnetization and demagnetization stages under lossless conditions, Represents the time interval between the two reference marks in the lossless state. This reference value reflects the inherent relationship between the amplitude ratio of the hysteresis loop and the time interval under ideal conditions, and is used to correct the deviation caused by speed fluctuations in actual operation in the future; the preset phase synchronization reference line essentially represents the target position where the magnetization and demagnetization reference marks should be aligned after the time axis and amplitude axis ratio adjustment under ideal uniform speed operation. This reference line can be set based on statistical analysis or theoretical models of a large number of lossless conveyor belt samples. For example, the reference mark positions of the lossless conveyor belt hysteresis loops collected multiple times after synchronous correction can be averaged to obtain this reference line. As well as the threshold used to determine whether the time axis and amplitude axis ratio adjustment is required in step S4, and the threshold used to determine hidden damage in step S5, are all determined by experimental analysis and data statistics of a large number of conveyor belt samples with known states (including healthy and different degrees of damage). The specific values ​​of these thresholds will be adjusted according to factors such as the material, structure, and running speed of the conveyor belt in the actual application scenario to achieve the best detection effect. For example, a smaller range can be set for the threshold for determining whether adjustment is needed. When it exceeds this range, it is considered that correction is needed. The threshold for determining damage needs to be set according to the hysteresis loop distortion characteristics caused by different types and degrees of damage to ensure that potential hidden damage can be effectively identified. The characteristic amplitude ratio of the magnetization phase and the demagnetization phase in the hysteresis loop is shown in ) and the time interval between these two feature points ( ) has a mapping relationship related to the conveyor belt running speed. Under ideal uniform speed conditions, this ratio should be close to the synchronization constant calculated through lossless data. However, when the conveyor belt speed fluctuates, will change accordingly, resulting in Deviation The present invention dynamically adjusts the time axis and amplitude axis ratio of the hysteresis loop so that the hysteresis loops collected at different speeds can be aligned to a unified benchmark, thereby eliminating the interference caused by speed fluctuations and more accurately analyzing the changes in magnetic characteristics caused by internal damage of the material. The goal is to achieve the decoupling of speed interference and highlight the abnormal distortion of the hysteresis loop caused by hidden damage; while the formula The phase synchronization constant is defined in , which is calculated using the collected benchmark data in a lossless state. and Represent the magnetic field intensity amplitude at the reference mark in the magnetization and demagnetization stages under lossless conditions, is the time interval between these two reference marks. This constant It can be regarded as an inherent magnetic characteristic parameter of a lossless conveyor belt under ideal conditions. In the subsequent damage detection process, the amplitude value collected in real time can be compared with the With the current time interval and the base time interval ( It can be calculated by the average time interval in the lossless state. Compare to determine whether correction is needed, and use this formula to provide a reliable benchmark value for subsequent dynamic correction. It should be noted that and Specifically, it refers to the magnetic field intensity amplitude at the slope inflection point identified by first-order derivative calculation during the magnetization and demagnetization stages of the hysteresis loop. It refers to the time interval between these two slope inflection points. It can be understood as a reference time interval, for example, the average time interval between the two inflection points in a lossless state, which belongs to an extended implementation method known to ordinary technicians in this field.

[0048] The present invention effectively eliminates the morphological distortion of the hysteresis loop caused by the fluctuation of the conveyor belt running speed by introducing a dynamic correction mechanism based on the intrinsic phase property of the hysteresis loop, so that the data collected under complex working conditions can more accurately reflect the changes in the magnetic characteristics of the material itself. At the same time, combined with multi-dimensional data collaborative analysis methods such as local curvature calculation and magnetic field intensity gradient analysis, it is possible to more finely identify and locate hidden damage. For example, abnormal changes in local curvature can indicate the occurrence of damage, while sudden changes in magnetic field intensity gradients help to determine the specific location of the damage, and the present invention mainly relies on in-depth analysis and processing of data collected by magnetic induction probes already in the existing conveyor belt system, without the need to add new hardware equipment, thereby realizing the detection of hidden damage to the conveyor belt without increasing the hardware cost. Through the dynamic reference adaptive calibration mechanism, the present invention can adapt to the operation of the conveyor belt under different working conditions and environmental conditions, and calibrate and analyze the hysteresis loop data in real time, thereby realizing all-weather stable monitoring of hidden damage to the conveyor belt.

[0049] The sliding window mean filtering mentioned in step S5 is intended to reduce the noise interference in the hysteresis loop data and make the subsequent damage feature analysis more accurate. For example, a sliding window with a window size of 5 data points can be used to perform mean filtering on the hysteresis loop data. In specific implementation, the window will slide along the time series, and the average value of the 5 data points in the window will be calculated each time, and the average value will be used as the magnetic field intensity value after filtering at the current time point. The selection of the window size can be adjusted according to the characteristics of the noise in practical applications, and the magnetic field intensity gradient analysis is to identify damage by calculating the rate at which the magnetic field intensity on the hysteresis loop changes with position. Specifically, the difference in magnetic field intensity collected by two adjacent magnetic induction probes in the length direction of the conveyor belt can be calculated, and divided by the distance between the two probes to obtain the magnetic field intensity gradient. The historical benchmark value can be calculated by performing gradient calculation on a known lossless conveyor belt area, and taking its average value as the benchmark. When the gradient value calculated in real time deviates significantly from the historical benchmark value, there may be hidden damage. In the example, the synchronization accuracy threshold can be, for example, a product error of less than 5%. The setting of this threshold is based on a comprehensive consideration of detection accuracy and system robustness. Specifically, when the slope inflection points of the magnetization stage and the demagnetization stage are corrected, the product error of the time interval is less than 5%, then it is considered that the synchronization accuracy has met the requirements and subsequent damage determination can be performed. The specific value of this threshold can be adjusted according to the needs of the actual application. For example, for scenarios with higher requirements for detection accuracy, the threshold can be set smaller, which are all extended implementation methods known to ordinary technicians in this field.

[0050] Embodiment 4: This embodiment uses the critical point where the slope first changes suddenly in the magnetization stage and the demagnetization stage as a reference mark. In order to improve the accuracy of inflection point identification under actual complex working conditions, this embodiment introduces a dynamic threshold adjustment mechanism. Specifically, in the initial stage, the first-order derivative mentioned in the specification can be used to drop to less than 20% of the peak value as the preliminary inflection point identification threshold. However, considering the fluctuation of the conveyor belt running speed and the influence of sensor noise, this fixed threshold may not accurately identify the true inflection point in all cases. Therefore, after the inflection point is initially identified, this embodiment will perform an adaptive adjustment process. This process is based on the statistical analysis of historical data and the local characteristics of the current hysteresis loop. For example, a sliding window can be maintained to record the first-order derivative values ​​of the magnetization and demagnetization inflection points identified in the recent period of time. Then, the mean and standard deviation of these historical first-order derivative values ​​are calculated.

[0051] When identifying the inflection point of the current hysteresis loop, the first-order derivative value of the initially identified inflection point will be compared with the historical mean and standard deviation. If the current first-order derivative value deviates from the historical mean by more than a certain multiple of the standard deviation (for example, 3 times the standard deviation), it is considered that the initially identified inflection point may be a misjudgment caused by noise, and the identification threshold needs to be readjusted. The adjustment strategy can be: if the current first-order derivative value is much higher than the historical mean, then the threshold for inflection point identification is appropriately increased; if it is much lower than the historical mean, then the threshold is appropriately lowered. The step size of the adjustment can be adaptively determined according to the degree of deviation. Through this dynamic threshold adjustment mechanism, the robustness of inflection point identification can be improved and the interference of speed fluctuations and noise can be reduced.

[0052] In terms of adaptively constructing and applying the baseline, in the initial stage, the time interval between the magnetization and demagnetization inflection points can be extracted by analyzing the hysteresis loop data collected at different operating speeds for a known undamaged conveyor belt. And the corresponding amplitude ratio Then, the initial phase synchronization baseline can be obtained by fitting these data points. The baseline can be expressed as To indicate that, in the actual monitoring process, as the running state of the conveyor belt changes, the initial baseline may no longer be completely applicable. Therefore, this embodiment introduces an adaptive update mechanism. The hysteresis loop data in the current undamaged state can be collected regularly (for example, at regular intervals or when a significant change in the running state of the conveyor belt is detected), the inflection point time interval and amplitude ratio can be recalculated, and the original baseline can be updated using these new data points. The update method can be to use weighted average or re-fit the function.

[0053] When performing phase synchronization correction, for the currently acquired hysteresis loop, first identify the time interval between its magnetization and demagnetization inflection points. and amplitude ratio Then, the time interval Substitute the adaptive updated baseline function , and obtain the expected amplitude ratio By comparing the actual amplitude ratio The ratio to the expected amplitude , the dynamic adjustment ratio of the time axis and amplitude axis of the hysteresis loop can be calculated. For example, the adjustment ratio of the time axis can be The adjustment ratio of the amplitude axis can be related to Related.

[0054] In addition to the local curvature and magnetic field gradient analysis, the following features can also be introduced for comprehensive judgment, such as calculating the energy integral of the corrected hysteresis loop during magnetization and demagnetization. In the absence of damage, the two energy integrals should be close. When damage exists, it may cause increased energy loss, thereby increasing the difference between the two energy integrals. Analysis of specific frequency components: Perform spectrum analysis on the corrected magnetic field intensity signal to extract the amplitude and phase information of specific frequency components. Damage may cause abnormal signal changes within a specific frequency range. Deviation from historical data: Compare the current corrected hysteresis loop with the historical hysteresis loop in the undamaged state, and calculate the similarity or difference index between them. Significant deviation may indicate the presence of damage. At the same time, for each of the above features, a corresponding threshold can be set. When the value of one or more features exceeds the set threshold, it can be preliminarily determined that there is damage. In order to further improve the reliability of the judgment, a weighted fusion method can be used to assign different weights to each feature, and then the weighted comprehensive score can be used to finally determine whether there is damage. The setting of the weight can be determined and adjusted based on a large amount of experimental data. Specifically, the initial setting of the weight can be based on the results of a large number of experimental analyses of conveyor belt damage of different types and degrees. For example, by collecting hysteresis loop data and extracting features of conveyor belts with different types (such as cracks, wear, faults, etc.) and different severity (such as slight, moderate, and severe) of damage, the significance and reliability of features such as energy integral difference, specific frequency component amplitude, deviation from historical data, local curvature, and magnetic field gradient under each damage type and degree are analyzed. For features that show higher discrimination under specific damage types or degrees, higher initial weights can be assigned, and in practical applications, the rationality of the current weight setting can be evaluated by monitoring the performance of the system (for example, false alarm rate and missed alarm rate). If it is found that a certain type of damage is often misjudged or missed, the weight of the relevant features can be adjusted in a targeted manner. For example, if the energy integral difference is easily disturbed under certain working conditions, resulting in false alarms, its weight can be appropriately reduced. The adjustment method may include regular performance evaluation and manual adjustment of weights based on the evaluation results; or, an adaptive weight adjustment algorithm may be introduced, such as a machine learning-based method, which automatically adjusts the weights of different features through continuous learning and optimization to achieve the best damage determination effect, all of which are extended implementation methods known to ordinary technicians in the field.

[0055] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. Therefore, the embodiments should be considered exemplary and non-restrictive in all respects, and the scope of the present invention is defined by the appended claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims be included in the present invention.

Claims

1. A method for analyzing hidden damage of a conveyor belt using magnetic characteristics, characterized in that: The following steps are involved: Step S1, acquiring in real time the hysteresis loop data of the conveyor belt during operation, wherein the hysteresis loop data includes the corresponding relationship between the magnetic field intensity and the time series in the magnetization stage and the demagnetization stage; Step S2, identifying a first slope inflection point as a magnetization reference mark in the magnetization stage, wherein the first slope inflection point is a critical point where the slope first suddenly changes in a rising edge of the magnetic field intensity varying with time; Step S3, identifying a second slope inflection point as a demagnetization reference mark in the demagnetization stage, wherein the second slope inflection point is a critical point where the slope of the falling edge of the magnetic field intensity changing with time first undergoes a sudden change; Step S4, according to the time interval between the magnetized reference mark and the demagnetized reference mark , calculate the ratio of the magnetic field strength amplitudes of the two ,in is the magnetic field intensity amplitude corresponding to the magnetized reference mark, is the magnetic field intensity amplitude corresponding to the demagnetization reference mark, and the amplitude ratio satisfies the following relationship: ， in, is the preset phase synchronization constant, It is the reference time interval of the conveyor belt at the standard operating speed; Step S5, based on the amplitude ratio The mapping relationship with the preset phase synchronization baseline dynamically adjusts the time axis ratio and the amplitude axis ratio of the hysteresis loop so that the slope inflection points of the adjusted magnetization stage and demagnetization stage are aligned to the phase synchronization baseline; Step S6, outputting the corrected hysteresis loop data, and determining the hidden damage position of the conveyor belt according to the abnormal distortion characteristics of the magnetic field intensity distribution in the corrected data.

2. The method for analyzing hidden damage of a conveyor belt using magnetic characteristics according to claim 1, characterized in that: The method for identifying the first slope inflection point in step S2 includes: calculating the first-order derivative of the curve of magnetic field intensity variation with time in the magnetization stage, and defining the position where the derivative first drops below 20% of the peak value as the first slope inflection point.

3. The method for analyzing hidden damage of a conveyor belt using magnetic characteristics according to claim 2, characterized in that: The dynamic adjustment in step S5 includes: When it is less than a preset threshold, the time axis ratio of the hysteresis loop is compressed and the amplitude axis ratio is enlarged; when When the time difference between the magnetized reference mark and the demagnetized reference mark is greater than a preset threshold, the time axis ratio is stretched and the amplitude axis ratio is reduced until the time difference between the magnetized reference mark and the demagnetized reference mark is Ratio to Amplitude The product of reaches the preset synchronization constant.

4. The method for analyzing hidden damage of a conveyor belt using magnetic characteristics according to claim 1, characterized in that: The method for setting the phase synchronization reference line includes: collecting the temporal and spatial distribution characteristics of the magnetization reference mark and the demagnetization reference mark of the hysteresis loop when the conveyor belt is running at the standard speed when the conveyor belt is not damaged, and calculating the synchronization constant by the following formula : ， in, is the magnetic field intensity amplitude of the magnetized reference mark in the undamaged state, is the magnetic field intensity amplitude of the demagnetized reference mark in an undamaged state, is the base time interval for both.

5. The method for analyzing hidden damage of a conveyor belt using magnetic characteristics according to claim 1, characterized in that: The abnormal distortion feature determination method in step S6 includes: calculating the local curvature of the corrected hysteresis loop, marking the continuous area whose curvature exceeds a preset threshold as a potential damage area, and performing a magnetic field intensity gradient analysis on the area. If the gradient change rate exceeds 3 times of the historical baseline value, it is determined to be a hidden damage.

6. The method for analyzing hidden damage of a conveyor belt using magnetic characteristics according to claim 5, characterized in that: The method further comprises a dynamic phase synchronization verification step: in the corrected hysteresis loop data, if the slope inflection points of the magnetization phase and the demagnetization phase are not completely aligned to the phase synchronization reference line, then steps S2 to S5 are repeatedly executed until the time difference between the two is equal to or greater than 100. Ratio to Amplitude The product error is less than 5%.

7. The method for analyzing hidden damage of a conveyor belt using magnetic characteristics according to claim 6, characterized in that: The amplitude ratio in step S4 The calculation method includes: performing sliding window mean filtering on the magnetic field intensity data of the magnetized reference mark and the demagnetized reference mark, and taking 80% of the peak value after filtering as and The calculation base value of .

8. The method for analyzing hidden damage of a conveyor belt using magnetic characteristics according to claim 1, characterized in that: The method also includes a damage verification step: when hidden damage is detected, the conveyor belt is triggered to slow down to 50% of the standard speed, the hysteresis loop data is recollected and a secondary correction is performed, and if the damage feature still exists after the secondary correction, a damage alarm signal is generated.

9. The method for analyzing hidden damage of a conveyor belt using magnetic characteristics according to claim 1, characterized in that: The method for acquiring hysteresis loop data includes: symmetrically arranging magnetic induction probe arrays on both sides of the conveyor belt, collecting magnetic field intensity distribution data in real time, and eliminating environmental magnetic field interference through differential calculation.

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