Method for predicting wear degree of magnetic friction plate of fan coupler

Abstract

The invention discloses a method for predicting the abrasion degree of a magnetic friction plate of a fan coupler. The method comprises the steps that whether the coupler slips or not is monitored through a strain gauge; acquiring magnetic characteristic data of the magnetic friction plate, the frequency converter and the wind power motor when the coupler slips; magnetic property phase differences between the magnetic friction plate and the frequency converter and between the magnetic friction plate and the wind power motor in the slipping time period are obtained; fourier transform is carried out on the magnetic characteristic data of the three in the slipping time period to obtain frequency spectrum information of the three; reconstructing magnetic characteristic data of the three according to the frequency spectrum information of the three; calculating real magnetic characteristic data of the magnetic friction plate according to the reconstructed magnetic characteristic data of the three; the magnetic conductivity is calculated according to the real magnetic characteristic data; comparing the magnetic conductivity with a magnetic conductivity threshold value; and when the magnetic conductivity is smaller than or equal to the magnetic conductivity threshold value, the magnetic friction plate is replaced or maintained. The magnetic conductivity of the magnetic friction plate is used as a wear judgment basis, so that the wear degree of the magnetic friction plate can be more intuitively and accurately represented.

Description

Technical Field

[0001] The invention relates to the technical field of mechanical equipment fault monitoring, in particular to a method for predicting the wear degree of a magnetic friction plate of a fan coupling. Background Art

[0002] In wind power generation systems, friction plates are divided into traditional friction plates and magnetic friction plates. The monitoring methods for the wear degree of traditional friction plates usually rely on monitoring their yaw load and yaw angle, or evaluating the wear condition by analyzing the operating temperature generated by the friction plates. Although these methods can also be used to detect magnetic friction plates, they are insufficient in accuracy and intuitiveness and cannot effectively reflect the actual wear degree of magnetic friction plates. This monitoring method, which is not intuitive and accurate, may lead to a lack of necessary information support for maintenance personnel when making decisions, thus affecting the safe operation and maintenance efficiency of the equipment.

[0003] Therefore, there is an urgent need for a new detection method to more intuitively and accurately evaluate the wear state of the magnetic friction plate and provide a solid scientific basis for the maintenance of wind power equipment, which has become a problem to be solved. Summary of the invention

[0004] In order to at least overcome the above-mentioned deficiencies in the prior art, the purpose of the present application is to provide a method for predicting the degree of wear of the magnetic friction plate of a fan coupling.

[0005] The embodiment of the present application provides a method for predicting the wear degree of a magnetic friction plate of a fan coupling, comprising: S1: Monitor whether the coupling is slipping by installing a strain gauge on the coupling; S2: using a Hall sensor and a flux meter to obtain magnetic characteristic data generated by the magnetic friction plate, the frequency converter and the wind motor when the coupling slips, wherein the magnetic characteristic data includes the magnetic field intensity and magnetic induction intensity of the magnetic friction plate, the frequency converter and the wind motor; S3: Use an interferometer to measure the magnetic characteristic phase difference between the magnetic friction plate and the inverter, and between the magnetic friction plate and the wind turbine during the slip period; S4: extracting magnetic characteristic data of the magnetic friction plate, the frequency converter and the wind motor during the slip period, and performing Fourier transform according to the magnetic characteristic phase difference between the magnetic friction plate and the frequency converter, and between the magnetic friction plate and the wind motor, to obtain the frequency spectrum information of the three; S5: reconstructing the magnetic characteristic data of the magnetic friction plate, the inverter and the wind turbine according to the frequency spectrum information of the three; S6: Calculating the real magnetic characteristic data of the reconstructed magnetic friction plate according to the reconstructed magnetic characteristic data of the inverter and the wind turbine; S7: Calculate the magnetic permeability of the magnetic friction plate according to the real magnetic characteristic data; S8: extracting the magnetic permeability of the magnetic friction plate during the slipping period as a basis for wear judgment, and comparing it with a preset magnetic permeability threshold value; S9: When the magnetic permeability is less than or equal to the preset magnetic permeability threshold value, notify the maintenance personnel to replace or repair the magnetic friction plate.

[0006] In wind power generation systems, the degree of wear of friction plates has an important impact on the operating efficiency and safety of the equipment. At present, the wear detection of traditional friction plates mainly relies on the monitoring of yaw load and yaw angle, or the evaluation of wear by analyzing the operating temperature generated by the friction plates. Although these traditional monitoring indicators can provide certain information, they are often not intuitive enough, and there are too many interference factors, which cannot accurately reflect the actual wear condition of the friction plates. Firstly, the yaw load and yaw angle of the traditional friction plate may be affected by the change of wind speed due to the change of external wind speed, and the change of wind force and wind direction is complex and changeable and difficult to predict. The friction plate is wrapped in the output shaft of the coupling, and the coupling is wrapped in the wind turbine box, which may cause the measured yaw load and yaw angle to be inaccurate. On the other hand, the working temperature analysis of the friction plate is also affected by environmental factors. For example, the changes in external temperature in different seasons and weather are complex. Under different ambient temperatures, the working temperature of the friction plate when it is not slipping and the working temperature when it is slipping will also change. Therefore, it becomes complicated to evaluate the wear degree of the friction plate by temperature. Due to the combined effect of these environmental interference factors, it is difficult for traditional monitoring methods to provide intuitive and reliable evaluation of the wear status of the friction plate in actual applications.

[0007] In the implementation of this embodiment, most of the research on the wear degree of the friction plate is aimed at the traditional friction plate, while the research on the wear degree of the magnetic friction plate is less. Although the above-mentioned technical means for monitoring the traditional friction plate can also be used for the magnetic friction plate, it is limited by many environmental interference factors. Therefore, judging the wear degree of the magnetic friction plate by these methods is often not intuitive and accurate. The inventor of the present application found that it is a feasible solution to reflect the wear degree of the friction plate by detecting and calculating the magnetic permeability of the magnetic friction plate. As the use time of the magnetic friction plate increases, the magnetic material on the surface of the disk will be worn off and pits, wrinkles and / or cracks will appear, which will cause the distribution and intensity of the magnetic field of the magnetic friction plate to change. Specifically, the wear, pits, wrinkles and cracks of magnetic materials will increase the non-uniformity of the material, thereby reducing its overall magnetic permeability. The magnetic field distribution and strength of the magnetic friction plate are less affected by wind speed, ambient temperature and yaw load, and are mainly affected by the magnetic field distribution and strength of the inverter and wind turbine. Therefore, it is a more intuitive and accurate technical means to measure the magnetic permeability of the magnetic friction plate to evaluate its degree of wear by eliminating the interference of the magnetic field distribution and strength of the inverter and wind turbine on the magnetic friction plate.

[0008] When this embodiment is implemented, in order to accurately measure the real magnetic field strength and magnetic induction strength of the magnetic friction plate, it is necessary to gradually eliminate the interference of the frequency converter and the wind turbine on the magnetic friction plate. First, when the coupling works normally, the strain gauge will record a stable strain signal; when it slips, the signal will fluctuate abnormally or change suddenly. When this fluctuation exceeds the set strain signal threshold, the coupling is determined to be in a slipping state. Then, the slipping time period is calibrated to extract the magnetic characteristic data generated by the magnetic friction plate, the frequency converter and the wind motor recorded by the Hall sensor and the flux meter within the calibration time range; and the magnetic characteristic phase difference between the magnetic friction plate and the frequency converter, and the magnetic characteristic phase difference between the magnetic friction plate and the wind motor measured by the interferometer within the calibration time range are extracted. In this embodiment, because the magnetic field fluctuation of the magnetic friction plate is affected by the magnetic field fluctuation generated by the frequency converter and the wind motor, wave interference will occur, which will cause the magnetic field strength and magnetic induction strength of the magnetic friction plate to change and shift during the slipping time period, resulting in distortion of the measured magnetic characteristic data of the magnetic friction plate. Therefore, in order to accurately measure the true magnetic field strength and magnetic induction strength of the magnetic friction plate, it is necessary to gradually eliminate the interference of the frequency converter and the wind motor on the magnetic friction plate. Specific measures include extracting the magnetic characteristic data of the magnetic friction plate, frequency converter and wind motor during the slipping period, and performing Fourier transform according to the magnetic characteristic phase difference between the magnetic friction plate and the frequency converter, and between the frequency converter and the wind motor, so as to eliminate the influence of environmental noise and other interference signals on the measurement results; then, reconstructing the magnetic characteristic data of the magnetic friction plate, the frequency converter and the wind motor according to the spectrum information of the three; calculating the real magnetic field strength and magnetic induction strength of the magnetic friction plate according to the reconstructed magnetic characteristic data, and eliminating the interference influence of the magnetic field fluctuation generated by the frequency converter and the wind motor on the magnetic friction plate by calculation, so that the calculated magnetic field strength and magnetic induction strength generated by the magnetic friction plate are the real magnetic field strength and magnetic induction strength not interfered by the frequency converter and the wind motor, and then calculating the real magnetic permeability of the magnetic friction plate according to the magnetic field strength and magnetic induction strength, and then comparing the magnetic permeability during the slipping period with the preset magnetic permeability threshold value, and when the magnetic permeability is less than or equal to the preset magnetic permeability threshold value, notifying the maintenance personnel to replace or repair the magnetic friction plate.

[0009] Furthermore, the magnetic characteristic phase difference includes a magnetic field strength phase difference between the magnetic friction plate and the inverter, and a magnetic field strength phase difference between the inverter and the wind turbine.

[0010] Further, step S4 includes: S401: pre-processing the extracted magnetic field strength and magnetic induction strength of the magnetic friction plate, the inverter and the wind turbine, including denoising and signal smoothing; S402: using Fourier transform algorithm, converting the time domain signals of the magnetic friction plate, the inverter and the wind turbine into frequency domain signals to obtain spectrum data; S403: Analyze the spectrum data, and calculate the amplitudes of the magnetic friction plate, the frequency converter and the wind motor respectively, and analyze the magnetic field intensity phase difference between the magnetic friction plate and the frequency converter, and between the magnetic friction plate and the wind motor; S404: performing normalization processing on the frequency spectrum data of the magnetic friction plate, the frequency converter and the wind turbine according to the amplitude and the phase difference.

[0011] Further, step S5 includes: S501: Perform inverse Fourier transform on the frequency spectrum data of the magnetic friction plate, the inverter and the wind turbine, and convert the identified main frequency components back into time domain signals; S502: Calculate the instantaneous magnetic field intensity and magnetic induction intensity of the reconstructed magnetic friction plate, the inverter and the wind turbine by using an inverse Fourier transform algorithm; S503: Phase-align the instantaneous magnetic field intensity and magnetic induction intensity of the magnetic friction plate, the inverter, and the wind turbine to ensure that the reconstructed time domain signal is consistent with the original time domain signal in phase.

[0012] Further, in step S6, the real magnetic characteristic data of the reconstructed magnetic friction plate including the magnetic induction intensity of the magnetic friction plate is calculated, and the calculation formula is: ; In the formula, t1 and t2 are the start time and end time of coupling slippage, respectively. For t The actual magnetic induction intensity of the magnetic friction plate at any moment, For t The initial magnetic induction intensity of the magnetic friction plate at time For t The magnetic induction intensity of the inverter at any moment, is the distance between the inverter and the magnetic friction plate, is the temperature influence coefficient between the inverter and the magnetic friction plate, For t The magnetic induction intensity of the wind turbine at the moment, is the distance between the wind turbine and the magnetic friction plate, is the temperature influence coefficient between the wind turbine and the magnetic friction plate.

[0013] Furthermore, in step S6, the real magnetic characteristic data of the reconstructed magnetic friction plate is calculated, which also includes the magnetic field strength of the magnetic friction plate, and the calculation formula is: ; In the formula, t1 and t2 are the start time and end time of coupling slippage, respectively. For t The actual magnetic field strength of the magnetic friction plate at any moment, For t The initial magnetic field strength of the magnetic friction plate at time For t The magnetic field strength of the inverter at any moment, is the distance between the inverter and the magnetic friction plate, is the temperature influence coefficient between the inverter and the magnetic friction plate, For t The magnetic field strength of the wind turbine at the moment, is the distance between the wind turbine and the magnetic friction plate, is the temperature influence coefficient between the wind turbine and the magnetic friction plate.

[0014] Furthermore, in step S7, the formula for calculating the magnetic permeability of the magnetic friction plate is: ; In the formula, For t The actual magnetic permeability of the magnetic friction plate at that moment.

[0015] Furthermore, the specific steps of steps S8 and S9 include: S891: Establish an early warning notification model; S892: establishing a magnetic permeability curve graph based on the magnetic permeability of the magnetic friction plate during the slipping period; S893: extracting features from the magnetic permeability curve to form a set of magnetic permeability feature values; S894: assigning the magnetic permeability characteristic value set and the preset magnetic permeability threshold value to the early warning notification model for comparison; S895: The early warning notification model performs a traversal operation on the magnetic permeability characteristic value set to detect whether at least one value therein is less than or equal to a preset magnetic permeability threshold value; S896: When the detection condition is met, the traversal operation is stopped, and the warning notification model triggers the warning notification switch state to be turned on; S897: The warning notification model calls the SMS service interface to send the warning maintenance information to the maintenance personnel.

[0016] In summary, the present invention has the following beneficial effects compared with the prior art: Compared with the traditional monitoring methods, the method for predicting the wear degree of the magnetic friction plate of the fan coupling provided by the present invention mainly relies on the monitoring of the yaw load and yaw angle, or judges the wear condition of the friction plate by the working temperature. These methods have certain limitations. First, the temperature change is affected by many factors, which may lead to errors in the monitoring results and cannot accurately reflect the actual wear degree of the friction plate. Second, the monitoring of the yaw load and angle often needs to rely on indirect methods to infer the wear state. In this way, the transmission and interpretation of information become less intuitive, and it may be difficult for maintenance personnel to make accurate decisions quickly; while the present method overcomes the limitation of the traditional method being interfered by the external environment by accurately monitoring and analyzing the magnetic characteristic data of the magnetic friction plate under different working conditions, especially using magnetic permeability as the basis for judgment. The method can more intuitively reflect the actual wear condition of the friction plate, discover potential problems in time, and improve the accuracy and reliability of monitoring the wear degree of the friction plate. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings: Figure 1 is a flow chart of the prediction method of the present invention; Figure 2 A flow chart of the present invention for Fourier transforming the magnetic characteristic data of the magnetic friction plate, the frequency converter and the wind turbine; Figure 3 This is a flow chart of the present invention for reconstructing magnetic characteristic data of the magnetic friction plate, the frequency converter and the wind turbine according to the frequency spectrum information of the three; Figure 4 The present invention uses the magnetic permeability of the magnetic friction plate as a basis for judging wear and tear, and notifies maintenance personnel to replace or repair the magnetic friction plate. DETAILED DESCRIPTION

[0018] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0019] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0020] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0021] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0022] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may include that the first and second features are in direct contact, or may include that the first and second features are not in direct contact but are in contact through another feature between them. Moreover, a first feature being "above", "above" and "above" a second feature includes that the first feature is directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. A first feature being "below", "below" and "below" a second feature includes that the first feature is directly below and obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature.

[0023] In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the fact that ordinary technicians in the field can implement it. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of the present invention.

[0024] In the following description, suffixes such as "module", "component", "assembly" or "unit" are used only to facilitate the description of the present invention and have no specific meanings. Therefore, they can be used in combination.

[0025] The present invention will be further described in detail below through specific implementation modes in conjunction with the accompanying drawings.

[0026] Please refer to Figure 1 , which is a flow chart of a method for predicting the degree of wear of a magnetic friction plate of a fan coupling provided by an embodiment of the present invention. Furthermore, the method for predicting the degree of wear of a magnetic friction plate of a fan coupling may specifically include the contents described in the following steps S1 to S9.

[0027] S1: Monitor whether the coupling is slipping by installing a strain gauge on the coupling; S2: using a Hall sensor and a fluxmeter to obtain magnetic characteristic data generated by the magnetic friction plate, the frequency converter and the wind motor when the coupling slips, wherein the magnetic characteristic data includes the magnetic field strength and magnetic induction strength of the magnetic friction plate, the frequency converter and the wind motor; S3: using an interferometer to measure the magnetic characteristic phase difference between the magnetic friction plate and the frequency converter, and between the magnetic friction plate and the wind turbine during the slip period; S4: extracting magnetic characteristic data of the magnetic friction plate, the frequency converter and the wind motor during the slip period, and performing Fourier transform according to the magnetic characteristic phase difference between the magnetic friction plate and the frequency converter, and between the magnetic friction plate and the wind motor, to obtain frequency spectrum information of the three; S5: reconstructing the magnetic characteristic data of the magnetic friction plate, the frequency converter and the wind turbine according to the frequency spectrum information of the three; S6: Calculating the real magnetic characteristic data of the reconstructed magnetic friction plate according to the reconstructed magnetic characteristic data of the frequency converter and the wind turbine; S7: Calculating the magnetic permeability of the magnetic friction plate according to the real magnetic property data; S8: extracting the magnetic permeability of the magnetic friction plate during the slipping period as a basis for wear judgment, and comparing it with a preset magnetic permeability threshold value; S9: When the magnetic permeability is less than or equal to the preset magnetic permeability threshold value, notify maintenance personnel to replace or repair the magnetic friction plate.

[0028] In wind power generation systems, the degree of wear of friction plates has an important impact on the operating efficiency and safety of the equipment. At present, the wear detection of traditional friction plates mainly relies on the monitoring of yaw load and yaw angle, or the evaluation of wear by analyzing the operating temperature generated by the friction plates. Although these traditional monitoring indicators can provide certain information, they are often not intuitive enough, and there are too many interference factors, which cannot accurately reflect the actual wear condition of the friction plates. Firstly, the yaw load and yaw angle of the traditional friction plate may be affected by the change of wind speed due to the change of external wind speed, and the change of wind force and wind direction is complex and changeable and difficult to predict. The friction plate is wrapped in the output shaft of the coupling, and the coupling is wrapped in the wind turbine box, which may cause the measured yaw load and yaw angle to be inaccurate. On the other hand, the working temperature analysis of the friction plate is also affected by environmental factors. For example, the changes in the outside temperature in different seasons and weather are different. Under different ambient temperatures, the working temperature of the friction plate when it is not slipping and the working temperature when it is slipping will also change. Therefore, it becomes complicated to evaluate the wear degree of the friction plate by temperature. Due to the combined effect of these environmental interference factors, it is difficult for traditional monitoring methods to provide intuitive and reliable evaluation of the wear status of the friction plate in practical applications.

[0029] In the implementation of this embodiment, most of the research on the wear degree of the friction plate is aimed at the traditional friction plate, while the research on the wear degree of the magnetic friction plate is less. Although the above-mentioned technical means for monitoring the traditional friction plate can also be used for the magnetic friction plate, it is limited by many environmental interference factors. Therefore, judging the wear degree of the magnetic friction plate by these methods is often not intuitive and accurate. The inventor of the present application found that it is a feasible solution to detect the magnetic permeability of the magnetic friction plate by magnetic permeability to reflect the wear degree of the friction plate. As the use time of the magnetic friction plate increases, the magnetic material on the surface of the disk will be worn off and pits, wrinkles and / or cracks will appear, which will cause the distribution and intensity of the magnetic field of the magnetic friction plate to change. Specifically, the wear, pits, wrinkles and cracks of magnetic materials will increase the non-uniformity of the material, thereby reducing its overall magnetic permeability. The magnetic field distribution and strength of the magnetic friction plate are less affected by wind speed, ambient temperature and yaw load, and are mainly affected by the magnetic field distribution and strength of the inverter and wind turbine. Therefore, it is a more intuitive and accurate technical means to measure the magnetic permeability of the magnetic friction plate to evaluate its degree of wear by eliminating the interference of the magnetic field distribution and strength of the inverter and wind turbine on the magnetic friction plate.

[0030] When this embodiment is implemented, in order to accurately measure the real magnetic field strength and magnetic induction strength of the magnetic friction plate, it is necessary to gradually eliminate the interference of the frequency converter and the wind turbine on the magnetic friction plate. First, when the coupling works normally, the strain gauge will record a stable strain signal; when it slips, the signal will fluctuate abnormally or change suddenly. When this fluctuation exceeds the set strain signal threshold, the coupling is determined to be in a slipping state. Then, the slipping time period is calibrated to extract the magnetic characteristic data generated by the magnetic friction plate, the frequency converter and the wind motor recorded by the Hall sensor and the flux meter within the calibration time range; and the magnetic characteristic phase difference between the magnetic friction plate and the frequency converter, and the magnetic characteristic phase difference between the magnetic friction plate and the wind motor measured by the interferometer within the calibration time range are extracted. In this embodiment, because the magnetic field fluctuation of the magnetic friction plate is affected by the magnetic field fluctuation generated by the frequency converter and the wind motor, wave interference will occur, which will cause the magnetic field strength and magnetic induction strength of the magnetic friction plate to change and shift during the slipping time period, resulting in distortion of the measured magnetic characteristic data of the magnetic friction plate. Therefore, in order to accurately measure the true magnetic field strength and magnetic induction strength of the magnetic friction plate, it is necessary to gradually eliminate the interference of the frequency converter and the wind motor on the magnetic friction plate. Specific measures include extracting the magnetic characteristic data of the magnetic friction plate, frequency converter and wind motor during the slipping period, and performing Fourier transform according to the magnetic characteristic phase difference between the magnetic friction plate and the frequency converter, and between the frequency converter and the wind motor, so as to eliminate the influence of environmental noise and other interference signals on the measurement results; then, reconstructing the magnetic characteristic data of the magnetic friction plate, the frequency converter and the wind motor according to the spectrum information of the three; calculating the real magnetic field strength and magnetic induction strength of the magnetic friction plate according to the reconstructed magnetic characteristic data, and eliminating the interference influence of the magnetic field fluctuation generated by the frequency converter and the wind motor on the magnetic friction plate by calculation, so that the calculated magnetic field strength and magnetic induction strength generated by the magnetic friction plate are the real magnetic field strength and magnetic induction strength not interfered by the frequency converter and the wind motor, and then calculating the real magnetic permeability of the magnetic friction plate according to the magnetic field strength and magnetic induction strength, and then comparing the magnetic permeability during the slipping period with the preset magnetic permeability threshold value, and when the magnetic permeability is less than or equal to the preset magnetic permeability threshold value, notifying the maintenance personnel to replace or repair the magnetic friction plate.

[0031] In a possible implementation, the magnetic characteristic phase difference includes a magnetic field strength phase difference between the magnetic friction plate and the frequency converter, and a magnetic field strength phase difference between the magnetic friction plate and the wind turbine.

[0032] In one possible implementation, please refer to Figure 2 , the step S4 comprises: S401: preprocessing the extracted magnetic field strength and magnetic induction strength of the magnetic friction plate, the frequency converter and the wind turbine, including denoising and signal smoothing; S402: using a Fourier transform algorithm to convert the time domain signals of the magnetic friction plate, the frequency converter and the wind turbine into frequency domain signals to obtain spectrum data; S403: Analyze the frequency spectrum data, and calculate the amplitudes of the magnetic friction plate, the frequency converter and the wind motor respectively, and analyze the magnetic field intensity phase difference between the magnetic friction plate and the frequency converter, and between the magnetic friction plate and the wind motor; S404: Normalizing the frequency spectrum data of the magnetic friction plate, the frequency converter and the wind turbine according to the amplitude and the phase difference.

[0033] When this embodiment is implemented, the electromagnetic waves generated by the frequency converter and the wind motor will interfere with the magnetic field strength and induction strength of the magnetic friction plate. The frequency converter and the wind motor will generate electromagnetic waves of different amplitudes and frequencies when running. These changes cause the magnetic field strength and magnetic induction strength of the magnetic friction plate to fluctuate, thereby affecting the phase difference between the magnetic friction plate and the frequency converter and the wind motor; the electromagnetic waves generated by the frequency converter and the wind motor when running cause the magnetic field inside the friction plate to be unstable, generating noise. In addition, the presence of electromagnetic waves will cause the magnetic field of the friction plate to overlap with the electromagnetic waves, causing resonance, thereby significantly changing the magnetic field strength and magnetic induction strength of the magnetic friction plate; in this embodiment, Step S401 mainly eliminates the noise in the magnetic field strength and magnetic induction strength of the magnetic friction plate, frequency converter and wind motor by denoising and signal smoothing; in steps S402-404, the main frequency components of the magnetic friction plate, frequency converter and wind motor signals are identified by Fourier transform algorithm and spectrum data analysis, so as to distinguish the electromagnetic interference caused by the electromagnetic waves generated by the frequency converter and wind motor to the magnetic friction plate; the spectrum data of the magnetic friction plate, frequency converter and wind motor are normalized so that the influence of each frequency data component is standardized, thereby avoiding the misjudgment of the changes in the magnetic field strength and magnetic induction strength of the magnetic friction plate due to amplitude differences.

[0034] In one possible implementation, please refer to Figure 3 , the step S5 comprises: S501: performing inverse Fourier transform on the frequency spectrum data of the magnetic friction plate, the frequency converter and the wind turbine, and converting the identified main frequency components back into time domain signals; S502: Calculating the instantaneous magnetic field intensity and magnetic induction intensity of the reconstructed magnetic friction plate, the frequency converter and the wind turbine by an inverse Fourier transform algorithm; S503: Phase-aligning the instantaneous magnetic field intensity and magnetic induction intensity of the magnetic friction plate, the frequency converter and the wind turbine to ensure that the reconstructed time domain signal is consistent with the original time domain signal in phase.

[0035] When this embodiment is implemented, the frequency domain signals of the preprocessed and standardized magnetic friction plate, inverter and wind motor signals are converted into time domain signals through inverse Fourier transform. In step S503, the instantaneous magnetic field strength and magnetic induction strength of the magnetic friction plate, inverter and wind motor are aligned with their original phases, ensuring that the reconstructed time domain signal is consistent with the original signal in phase, ensuring the accuracy of the actual magnetic field strength and magnetic induction strength when the magnetic friction plate is subsequently calculated.

[0036] In a possible implementation, in step S6, the real magnetic characteristic data of the magnetic friction plate after reconstruction is calculated, including the magnetic induction intensity of the magnetic friction plate, and the calculation formula is: ; In the formula, t1 and t2 are the start time and end time of coupling slippage, respectively. For t The actual magnetic induction intensity of the magnetic friction plate at any moment, For t The initial magnetic induction intensity of the magnetic friction plate at time For t The magnetic induction intensity of the inverter at any moment, is the distance between the inverter and the magnetic friction plate, is the temperature influence coefficient between the inverter and the magnetic friction plate, For t The magnetic induction intensity of the wind turbine at the moment, is the distance between the wind turbine and the magnetic friction plate, is the temperature influence coefficient between the wind turbine and the magnetic friction plate.

[0037] In a possible implementation, in step S6, the real magnetic characteristic data of the magnetic friction plate after calculation and reconstruction also includes the magnetic field strength of the magnetic friction plate, and the calculation formula is: ; In the formula, t1 and t2 are the start time and end time of coupling slippage, respectively. For t The actual magnetic field strength of the magnetic friction plate at any moment, For t The initial magnetic field strength of the magnetic friction plate at time For t The magnetic field strength of the inverter at any moment, is the distance between the inverter and the magnetic friction plate, is the temperature influence coefficient between the inverter and the magnetic friction plate, For t The magnetic field strength of the wind turbine at the moment, is the distance between the wind turbine and the magnetic friction plate, is the temperature influence coefficient between the wind turbine and the magnetic friction plate.

[0038] When this embodiment is implemented, when calculating the actual magnetic field strength of the magnetic friction plate, it is necessary to consider the distance between the wind motor and the magnetic friction plate, as well as the distance between the frequency converter and the magnetic friction plate. The main reason is the influence of distance on the magnetic field. Specifically, due to the distance relationship between the magnetic friction plate, the frequency converter and the wind motor, when the electromagnetic waves generated by the frequency converter and the wind motor are transmitted to the magnetic friction plate, attenuation will occur. Therefore, the distance factor must be taken into account to improve the accuracy of the calculation. In addition, during the operation of the wind motor and the frequency converter, the temperature will affect the magnetic characteristics of the material. Under conditions where the temperature changes too much, the magnetic field strength of the material may change. Therefore, it is necessary to consider the temperature influence coefficient, so that the calculation of the magnetic field strength can be adjusted according to the actual working environment to ensure the accuracy of the calculation results.

[0039] In a possible implementation, in step S7, the formula for calculating the magnetic permeability of the magnetic friction plate is: ; In the formula, For t The actual magnetic permeability of the magnetic friction plate at that moment.

[0040] In one possible implementation, please refer to Figure 4 The specific steps of steps S7 and S8 include: S891: Establish an early warning notification model; S892: Establishing a magnetic permeability curve graph based on the magnetic permeability of the magnetic friction plate during the slipping period; S893: extracting features from the magnetic permeability curve to form a set of magnetic permeability feature values; S894: assigning the magnetic permeability characteristic value set and the preset magnetic permeability threshold value to the early warning notification model for comparison; S895: The early warning notification model performs a traversal operation on the magnetic permeability characteristic value set to detect whether at least one value therein is less than or equal to the preset magnetic permeability threshold value; S896: When the detection condition is met, the traversal operation is stopped, and the warning notification model triggers the warning notification switch state to be turned on; S897: The warning notification model calls the SMS service interface to send the warning maintenance information to the maintenance personnel.

[0041] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. 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 method for predicting the degree of wear of a magnetic friction plate of a fan coupling, characterized in that: The steps of the prediction method include: S1: Monitor whether the coupling is slipping by installing a strain gauge on the coupling; S2: using a Hall sensor and a fluxmeter to obtain magnetic characteristic data generated by the magnetic friction plate, the frequency converter and the wind motor when the coupling slips, wherein the magnetic characteristic data includes the magnetic field strength and magnetic induction strength of the magnetic friction plate, the frequency converter and the wind motor; S3: using an interferometer to measure the magnetic characteristic phase difference between the magnetic friction plate and the frequency converter, and between the magnetic friction plate and the wind turbine during the slip period; S4: extracting magnetic characteristic data of the magnetic friction plate, the frequency converter and the wind motor during the slip period, and performing Fourier transform according to the magnetic characteristic phase difference between the magnetic friction plate and the frequency converter, and between the magnetic friction plate and the wind motor, to obtain frequency spectrum information of the three; S5: reconstructing the magnetic characteristic data of the magnetic friction plate, the frequency converter and the wind turbine according to the frequency spectrum information of the three; S6: Calculating the real magnetic characteristic data of the reconstructed magnetic friction plate according to the reconstructed magnetic characteristic data of the frequency converter and the wind turbine; S7: Calculating the magnetic permeability of the magnetic friction plate according to the real magnetic property data; S8: extracting the magnetic permeability of the magnetic friction plate during the slipping period as a basis for wear judgment, and comparing it with a preset magnetic permeability threshold value; S9: When the magnetic permeability is less than or equal to the preset magnetic permeability threshold value, notify maintenance personnel to replace or repair the magnetic friction plate.

2. A method for predicting the degree of wear of a magnetic friction plate of a fan coupling according to claim 1, characterized in that: The magnetic characteristic phase difference includes a magnetic field strength phase difference between the magnetic friction plate and the frequency converter, and a magnetic field strength phase difference between the magnetic friction plate and the wind turbine.

3. A method for predicting the degree of wear of a magnetic friction plate of a fan coupling according to claim 2, characterized in that: The step S4 comprises: S401: preprocessing the extracted magnetic field strength and magnetic induction strength of the magnetic friction plate, the frequency converter and the wind turbine, including denoising and signal smoothing; S402: using a Fourier transform algorithm to convert the time domain signals of the magnetic friction plate, the frequency converter and the wind turbine into frequency domain signals to obtain spectrum data; S403: Analyze the frequency spectrum data, and calculate the amplitudes of the magnetic friction plate, the frequency converter and the wind motor respectively, and analyze the magnetic field intensity phase difference between the magnetic friction plate and the frequency converter, and between the magnetic friction plate and the wind motor; S404: Normalizing the frequency spectrum data of the magnetic friction plate, the frequency converter and the wind turbine according to the amplitude and the phase difference.

4. The method for predicting the degree of wear of the magnetic friction plate of a fan coupling according to claim 3, characterized in that: The step S5 comprises: S501: performing inverse Fourier transform on the frequency spectrum data of the magnetic friction plate, the frequency converter and the wind turbine, and converting the identified main frequency components back into time domain signals; S502: Calculating the instantaneous magnetic field intensity and magnetic induction intensity of the reconstructed magnetic friction plate, the frequency converter and the wind turbine by an inverse Fourier transform algorithm; S503: Phase-aligning the instantaneous magnetic field intensity and magnetic induction intensity of the magnetic friction plate, the frequency converter and the wind turbine to ensure that the reconstructed time domain signal is consistent with the original time domain signal in phase.

5. A method for predicting the degree of wear of a magnetic friction plate of a fan coupling according to claim 4, characterized in that: In the step S6, the real magnetic characteristic data of the magnetic friction plate after reconstruction is calculated, including the magnetic induction intensity of the magnetic friction plate, and the calculation formula is: ； In the formula, t1 and t2 are the start time and end time of coupling slippage, respectively. For t The actual magnetic induction intensity of the magnetic friction plate at any moment, For t The initial magnetic induction intensity of the magnetic friction plate at time For t The magnetic induction intensity of the inverter at any moment, is the distance between the inverter and the magnetic friction plate, is the temperature influence coefficient between the inverter and the magnetic friction plate, For t The magnetic induction intensity of the wind turbine at the moment, is the distance between the wind turbine and the magnetic friction plate, is the temperature influence coefficient between the wind turbine and the magnetic friction plate.

6. A method for predicting the degree of wear of a magnetic friction plate of a fan coupling according to claim 5, characterized in that: In the step S6, the real magnetic characteristic data of the magnetic friction plate after calculation and reconstruction also includes the magnetic field strength of the magnetic friction plate, and the calculation formula is: ； In the formula, t1 and t2 are the start time and end time of coupling slippage, respectively. For t The actual magnetic field strength of the magnetic friction plate at any moment, For t The initial magnetic field strength of the magnetic friction plate at time For t The magnetic field strength of the inverter at any moment, is the distance between the inverter and the magnetic friction plate, is the temperature influence coefficient between the inverter and the magnetic friction plate, For t The magnetic field strength of the wind turbine at the moment, is the distance between the wind turbine and the magnetic friction plate, is the temperature influence coefficient between the wind turbine and the magnetic friction plate.

7. A method for predicting the degree of wear of a magnetic friction plate of a fan coupling according to claim 6, characterized in that: In step S7, the formula for calculating the magnetic permeability of the magnetic friction plate is: ； In the formula, For t The actual magnetic permeability of the magnetic friction plate at that moment.

8. A method for predicting the degree of wear of a magnetic friction plate of a fan coupling according to claim 7, characterized in that: The specific steps of steps S8 and S9 include: S891: Establish an early warning notification model; S892: Establishing a magnetic permeability curve graph based on the magnetic permeability of the magnetic friction plate during the slipping period; S893: extracting features from the magnetic permeability curve to form a set of magnetic permeability feature values; S894: assigning the magnetic permeability characteristic value set and the preset magnetic permeability threshold value to the early warning notification model for comparison; S895: The early warning notification model performs a traversal operation on the magnetic permeability characteristic value set to detect whether at least one value therein is less than or equal to the preset magnetic permeability threshold value; S896: When the detection condition is met, the traversal operation is stopped, and the warning notification model triggers the warning notification switch state to be turned on; S897: The warning notification model calls the SMS service interface to send the warning maintenance information to the maintenance personnel.

Images