Rolling bearing fault diagnosis method, device, equipment, medium and product

Abstract

The invention discloses a rolling bearing fault diagnosis method, device and equipment, a medium and a product, and relates to the technical field of bearing fault analysis. The method comprises the following steps: respectively sending acceleration time-domain analog signals acquired by an acceleration sensor into two different processing branches, and then, on one hand, obtaining an impact pulse signal frequency spectrum line through Nome analysis; on the other hand, through band-pass filtering processing, half-wave rectification processing, waveform envelope processing, low-pass filtering processing, analog-to-digital conversion processing, impact pulse extraction processing and signal enhancement processing, an impact pulse time domain digital signal is obtained; then, based on the processing result, an impact pulse frequency domain effective value, an impact pulse time domain effective value and a peer-to-peer principle proportionality coefficient are obtained through calculation, finally, the impact pulse time domain digital signal and the proportionality coefficient are multiplied, and a corrected impact pulse time domain digital signal is obtained; and calculating to obtain a rolling bearing state evaluation parameter for fault diagnosis of the rolling bearing.

Description

Technical Field

[0001] The present invention belongs to the technical field of bearing fault analysis, and in particular relates to a rolling bearing fault diagnosis method, device, equipment, medium and product. Background Art

[0002] The shock pulse rolling bearing fault diagnosis instrument is an existing instrument which uses a special shock pulse sensor (which is placed on the rolling bearing seat) to measure the shock pulse vibration generated by the rolling bearing during the operation of the machine to diagnose the rolling bearing fault.

[0003] At present, the existing impact pulse rolling bearing fault diagnosis instrument is mainly a shock pulse meter invented by the Swedish company SPM Instrument AB (its corresponding patent has expired). Its design purpose is to measure the Figure 1 The "shock pulse wave generated by rolling bearing failure" shown in the figure. Since the generation of this shock pulse wave will immediately cause the free decay vibration of "mechanical modal frequencies of various orders", in order to accurately test the shock pulse wave and avoid the vibration of various modal frequencies (the amplitude of the shock pulse wave is generally greater than the amplitude of the modal frequency vibration), SPM has also invented a special sensor to use the shock wave to reflect back and forth in the brass rod, and according to the structural sound propagation speed of the brass rod and the length of the brass rod, a single pulse wave is reflected back and forth in the brass rod to form a Figure 2 The free decay vibration with a frequency of 32kHz is shown in the figure (the actual product of SPM Company uses a stainless steel rod with a length of 79mm. Because the sound velocity of the stainless steel rod is about 5000m / s, the frequency of the pulse wave reflected back and forth is about 32kHz); then the 32kHz frequency signal is processed as follows Figure 3 The demodulation process shown is performed to obtain the amplitude of each pulse, and finally the rolling bearing state assessment parameters such as the maximum pulse decibel HBm, carpet decibel HDc, high-frequency impact value HR and low-frequency impact value LR are calculated to judge the working state of the rolling bearing.

[0004] However, if other vibration parameters of rolling bearings need to be tested, it is necessary to replace the acceleration sensor or other vibration test equipment for testing. Therefore, how to complete the rolling bearing vibration and impact pulse test tasks simultaneously based on the acceleration sensor, and then complete the mechanical vibration evaluation and rolling bearing fault diagnosis in one test, and simplify the rolling bearing detection work, is a topic that technicians in this field need to study urgently. Summary of the invention

[0005] The purpose of the present invention is to provide a rolling bearing fault diagnosis method, device, computer equipment, computer readable storage medium and computer program product to solve the problems of poor applicability, high price and low detection efficiency in existing shock pulse rolling bearing fault diagnosis solutions due to the need for special shock pulse sensors to perform rolling bearing shock pulse testing and fault diagnosis.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, a rolling bearing fault diagnosis method is provided, comprising:

[0008] Receiving an acceleration time-domain analog signal acquired by an acceleration sensor, wherein the acceleration sensor is mounted on a bearing seat of a target rolling bearing;

[0009] Sending the acceleration time domain analog signal to a first processing branch and a second processing branch respectively;

[0010] The first processing branch first converts the acceleration time domain analog signal into an acceleration time domain digital signal, and then obtains the impulse pulse signal spectrum line a through nom analysis based on the acceleration time domain digital signal. ic (f), where f represents the frequency variable;

[0011] The second processing branch sequentially performs bandpass filtering processing with the resonance frequency of the acceleration sensor as the center frequency, half-wave rectification processing, waveform envelope processing, low-pass filtering processing, analog-to-digital conversion processing, impact pulse extraction processing and signal enhancement processing on the acceleration time domain analog signal to obtain an impact pulse time domain digital signal Where t represents the time variable;

[0012] According to the impulse pulse signal spectrum line a ic (f) and the impulse pulse time domain digital signal The effective value A of the impulse pulse frequency domain is calculated according to the following formula ic (f), time domain effective value of the impulse pulse σ ic And the proportionality coefficient p of the equivalence principle:

[0013]

[0014] In the formula, represents half of the length of the fast Fourier transform, N represents the digital signal in the time domain of the shock pulse The total number of discrete points in , t′ represents a positive integer less than or equal to N, represents the amplitude of the t′th discrete point in the impulse time domain digital signal a(t), Represents the time domain digital signal of the shock pulse The average amplitude of

[0015] The time domain digital signal of the shock pulse The modified impulse pulse time domain digital signal is obtained by multiplying the proportional coefficient p of the equivalence principle;

[0016] Calculating and obtaining rolling bearing state assessment parameters according to the corrected impact pulse time-domain digital signal;

[0017] According to the rolling bearing state assessment parameters, the fault diagnosis result of the target rolling bearing is determined and output for display.

[0018] Based on the above invention content, a new solution for rolling bearing fault diagnosis based on acceleration sensor and through shock pulse self-calibration is provided, that is, the acceleration time domain analog signal collected by the acceleration sensor is first sent to two different processing branches respectively, and then on the one hand, the shock pulse signal spectrum line is obtained by nom analysis, and on the other hand, the shock pulse time domain digital signal is obtained by performing bandpass filtering processing with the resonance frequency of the acceleration sensor as the center frequency, half-wave rectification processing, waveform envelope processing, low-pass filtering processing, analog-to-digital conversion processing, shock pulse extraction processing and signal enhancement processing, and then based on the processing results The effective value of the impact pulse frequency domain, the effective value of the impact pulse time domain and the proportional coefficient of the equivalence principle are calculated respectively. Finally, the impact pulse time domain digital signal and the proportional coefficient are multiplied to obtain the corrected impact pulse time domain digital signal. Based on this, the rolling bearing state assessment parameters are calculated for use in rolling bearing fault diagnosis. In this way, the rolling bearing vibration and impact pulse test tasks can be completed simultaneously based on the acceleration sensor, and then the mechanical vibration evaluation and rolling bearing fault diagnosis can be completed in one test, which simplifies the rolling bearing detection work, is conducive to improving applicability, reducing prices and improving detection efficiency, and is convenient for practical application and promotion.

[0019] In a possible design, the acceleration time domain analog signal is sent to a first processing branch and a second processing branch respectively, including:

[0020] Performing signal conditioning processing on the acceleration time-domain analog signal to obtain a conditioned acceleration time-domain analog signal;

[0021] The conditioned acceleration time domain analog signal is sent to the first processing branch and the second processing branch respectively.

[0022] In a possible design, based on the acceleration time domain digital signal, the impulse pulse signal spectrum line a is obtained by nom analysis. ic (f) including:

[0023] According to the acceleration time domain digital signal a(t), the acceleration spectrum A(f n ), where fn represents the frequency of the nth spectral line in the spectrum, and n represents a positive integer;

[0024] According to the acceleration spectrum A(f n ), the velocity spectrum V(f n ) and displacement spectrum D(f n ):

[0025]

[0026] In the formula, π represents 180 degrees;

[0027] According to the acceleration spectrum A(f n ), the speed spectrum V(f n ) and the displacement spectrum D(f n ) are respectively related to the spectral line frequency f n The functional relationship is plotted to obtain a nomogram spectrum in a nomogram coordinate system, wherein the nomogram coordinate system includes an abscissa, a ordinate, a left-inclined coordinate, and a right-inclined coordinate, wherein the abscissa is a frequency value in logarithmic form, the ordinate is a velocity value in logarithmic form, the left-inclined coordinate is an acceleration value in logarithmic form, and the right-inclined coordinate is a displacement value in logarithmic form;

[0028] According to the nomogram, the impulse pulse signal spectrum line a in the nom coordinate system is stripped out. ic (f).

[0029] In one possible design, the method further includes:

[0030] The first processing branch also performs vibration analysis on the acceleration time-domain digital signal to obtain a vibration analysis result and output it for display.

[0031] In a possible design, the acceleration sensor is an acceleration sensor of model A14A050TE-T. In a possible design, the rolling bearing condition assessment parameters include maximum pulse decibel HBm, carpet decibel HDc, high frequency impact value HR and / or low frequency impact value LR.

[0032] In a second aspect, a rolling bearing fault diagnosis device is provided, comprising an analog signal receiving unit, an analog signal distribution unit, a first processing branch, a second processing branch, a proportional coefficient calculation unit, a signal multiplication calculation unit, an evaluation parameter calculation unit and a diagnosis result determination unit;

[0033] The analog signal receiving unit is used to receive the acceleration time domain analog signal acquired by the acceleration sensor, wherein the acceleration sensor is installed on the bearing seat of the target rolling bearing;

[0034] The analog signal distribution unit is communicatively connected to the analog signal receiving unit, and is used to send the acceleration time domain analog signal to the first processing branch and the second processing branch respectively;

[0035] The first processing branch is communicatively connected to the analog signal distribution unit, and is used to first convert the acceleration time domain analog signal into an acceleration time domain digital signal, and then obtain the impulse pulse signal spectrum line a through nom analysis according to the acceleration time domain digital signal. ic (f), where f represents the frequency variable;

[0036] The second processing branch is communicatively connected to the analog signal distribution unit, and is used to sequentially perform bandpass filtering processing with the resonance frequency of the acceleration sensor as the center frequency, half-wave rectification processing, waveform envelope processing, low-pass filtering processing, analog-to-digital conversion processing, impact pulse extraction processing and signal enhancement processing on the acceleration time domain analog signal to obtain an impact pulse time domain digital signal Where t represents the time variable;

[0037] The proportional coefficient calculation unit is respectively connected to the first processing branch and the second processing branch for calculating the proportional coefficient according to the impulse pulse signal spectrum line a ic (f) and the impulse pulse time domain digital signal The effective value A of the impulse pulse frequency domain is calculated according to the following formula ic (f), time domain effective value of the impulse pulse σ ic And the proportionality coefficient p of the equivalence principle:

[0038]

[0039] In the formula, represents half of the length of the fast Fourier transform, N represents the digital signal in the time domain of the shock pulse The total number of discrete points in , t′ represents a positive integer less than or equal to N, represents the amplitude of the t′th discrete point in the impulse time domain digital signal a(t), Represents the time domain digital signal of the shock pulse The average amplitude of

[0040] The signal multiplication calculation unit is respectively connected to the second processing branch and the proportional coefficient calculation unit for calculating the impulse pulse time domain digital signal. The modified impulse pulse time domain digital signal is obtained by multiplying the proportional coefficient p of the equivalence principle;

[0041] The evaluation parameter calculation unit is communicatively connected to the signal multiplication calculation unit, and is used to calculate the rolling bearing state evaluation parameter according to the corrected impact pulse time domain digital signal;

[0042] The diagnosis result determination unit is communicatively connected to the assessment parameter calculation unit, and is used to determine the fault diagnosis result of the target rolling bearing according to the rolling bearing state assessment parameter and output it for display.

[0043] In a third aspect, the present invention provides a computer device comprising a memory, a processor and a transceiver which are communicatively connected in sequence, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program to execute the rolling bearing fault diagnosis method as described in the first aspect or any possible design of the first aspect.

[0044] In a fourth aspect, the present invention provides a computer-readable storage medium having instructions stored thereon, which, when executed on a computer, executes the rolling bearing fault diagnosis method as described in the first aspect or any possible design of the first aspect.

[0045] In a fifth aspect, the present invention provides a computer program product, comprising a computer program or instructions, which, when executed by a computer, implements the rolling bearing fault diagnosis method as described in the first aspect or any possible design of the first aspect.

[0046] Beneficial effects of the above scheme:

[0047] (1) The present invention creatively provides a new solution for completing rolling bearing fault diagnosis based on an acceleration sensor and through shock pulse self-calibration, that is, firstly, the acceleration time domain analog signal collected by the acceleration sensor is respectively sent to two different processing branches, and then, on the one hand, the shock pulse signal spectrum line is obtained through nom analysis, and on the other hand, the shock pulse time domain digital signal is obtained by performing bandpass filtering processing with the resonance frequency of the acceleration sensor as the center frequency, half-wave rectification processing, waveform envelope processing, low-pass filtering processing, analog-to-digital conversion processing, shock pulse extraction processing and signal enhancement processing, and then, based on the processing results, the shock pulse frequency domain effective value, the shock pulse time domain effective value and the equivalence principle proportional coefficient are calculated respectively, and finally, the shock pulse time domain digital signal is multiplied by the proportional coefficient to obtain a corrected shock pulse time domain digital signal, and the rolling bearing state assessment parameter is calculated based on the rolling bearing fault diagnosis. In this way, the rolling bearing vibration and shock pulse test tasks can be completed simultaneously based on the acceleration sensor, and then the mechanical vibration evaluation and rolling bearing fault diagnosis can be completed in one test, simplifying the rolling bearing detection work, which is conducive to improving applicability, reducing prices and improving detection work efficiency;

[0048] (2) No special shock pulse sensor is required, and rolling bearing fault diagnosis can be performed using conventional acceleration sensors;

[0049] (3) It can simultaneously perform rolling bearing fault diagnosis and vibration test analysis and evaluation, simplifying the procurement requirements of test equipment, making one machine multi-purpose, and facilitating practical application and promotion. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] 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 work.

[0051] Figure 1 This is an example diagram of the waveform of the free attenuation vibration of each mechanical modal frequency and the sensor resonant frequency caused by the impact pulse wave generated when the rolling bearing fails.

[0052] Figure 2 This is an example diagram of the principle of waveform conversion caused by the shock pulse wave reflecting back and forth in the brass rod.

[0053] Figure 3 This is an example flow chart of the demodulation process of the rolling bearing impact pulse waveform.

[0054] Figure 4 A schematic flow chart of a rolling bearing fault diagnosis method provided in an embodiment of the present application.

[0055] Figure 5 This is an example diagram of the corresponding relationship between the acceleration time domain simulation signal and the nomogram spectrum provided in the embodiment of the present application, wherein: Figure 5 (a) shows an example diagram of the acceleration time domain simulation signal. Figure 5 (b) in FIG. 1 shows an example graph of a nomogram.

[0056] Figure 6 This is an example diagram of the impact pulse time domain digital signal provided in an embodiment of the present application.

[0057] Figure 7 This is an example diagram comparing the sensor resonance frequency curve and the mechanical modal frequency curve provided in the embodiment of the present application.

[0058] Figure 8 An example diagram of the relationship between the waveform, spectrum and nomogram spectrum of a single unit shock pulse provided in an embodiment of the present application, wherein: Figure 8 (a) shows an example waveform of a single unit shock pulse. Figure 8 (b) shows an example of the spectrum of a single unit shock pulse. Figure 8 (c) in the figure shows an example of the nomogram of a single unit shock pulse.

[0059] Fig. 9 An example diagram of the relationship between the acceleration waveforms, spectra and nomograms of multiple impact pulses provided in an embodiment of the present application, wherein: Figure 8 (a) in FIG. 1 shows an example of acceleration waveforms of multiple impact pulses. Fig. 9 (b) shows an example of the spectrum of multiple impact pulses. Fig. 9 (c) in the figure shows an example of the nomogram spectrum of multiple impact pulses.

[0060] Fig.10 A schematic diagram of the structure of a rolling bearing fault diagnosis device provided in an embodiment of the present application.

[0061] Fig.11 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0062] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be briefly introduced below in combination with the drawings and the description of the embodiments or the prior art. Obviously, the following description of the structures of the drawings is only some embodiments of the present invention. For ordinary technicians in this field, other embodiments can be obtained based on these embodiments without creative work. It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention.

[0063] It should be understood that although the terms first and second, etc. may be used herein to describe various objects, these objects should not be limited by these terms. These terms are only used to distinguish one object from another object. For example, a first object can be referred to as a second object, and similarly, a second object can be referred to as a first object without departing from the scope of the exemplary embodiments of the present invention.

[0064] It should be understood that the term "and / or" that may appear in this document is merely a description of the association relationship between associated objects, indicating that there may be three relationships. For example, A and / or B can indicate three situations: A exists alone, B exists alone, or A and B exist at the same time. For another example, A, B and / or C can indicate the existence of any one of A, B and C or any combination of them. The term " / and" that may appear in this document describes another type of association object relationship, indicating that there may be two relationships. For example, A / and B can indicate two situations: A exists alone or A and B exist at the same time. In addition, the character " / " that may appear in this document generally indicates that the previous and next associated objects are in an "or" relationship.

[0065] Example

[0066] like Figures 4 to 9 As shown, the rolling bearing fault diagnosis method provided in the first aspect of this embodiment can be executed by, but is not limited to, a computer device having certain computing resources and communicating with an acceleration sensor, such as an impact pulse rolling bearing fault diagnosis instrument, a personal computer (PC, a multi-purpose computer with a size, price and performance suitable for personal use; desktops, laptops, small laptops, tablets and ultrabooks are all personal computers), smart phones, personal digital assistants (PDA) or wearable devices. Figure 4 As shown, the rolling bearing fault diagnosis method may include but is not limited to the following steps S1 to S8.

[0067] S1. Receive an acceleration time-domain analog signal acquired by an acceleration sensor, wherein the acceleration sensor is mounted on a bearing seat of a target rolling bearing.

[0068] In step S1, the acceleration sensor is used to replace the dedicated shock pulse sensor to collect the acceleration time domain signal (which is also the original analog signal) of the free decay vibration of the mechanical modal frequencies and the sensor resonance frequency caused by the shock pulse wave generated when the rolling bearing fails. It specifically but not limited to using an acceleration sensor with model A14A050TE-T and conventionally installed on the bearing seat of the target rolling bearing.

[0069] S2. Send the acceleration time domain analog signal to the first processing branch and the second processing branch respectively.

[0070] In step S2, in order to ensure the accuracy and reliability of sensor data, so as to support the stable operation and efficient management of the entire fault diagnosis scheme, preferably, the acceleration time domain analog signal is sent to the first processing branch and the second processing branch respectively, including but not limited to: firstly performing signal conditioning processing on the acceleration time domain analog signal to obtain the conditioned acceleration time domain analog signal; and then sending the conditioned acceleration time domain analog signal to the first processing branch and the second processing branch respectively. The specific process of the aforementioned signal conditioning processing is prior art and will not be repeated here.

[0071] S3. The first processing branch first converts the acceleration time domain analog signal into an acceleration time domain digital signal, and then obtains the impulse pulse signal spectrum line a through the nom analysis according to the acceleration time domain digital signal. ic (f), where f represents the frequency variable.

[0072] In step S3, the nomogram analysis is a signal analysis method based on the principle of a nomogram tool (i.e., a tool that uses images to perform calculations / viewing images, specifically a two-dimensional image, used for inaccurate calculations). Specifically, according to the acceleration time domain digital signal, the impulse pulse signal spectrum line a is obtained by nomogram analysis. ic (f) including but not limited to the following steps S31 to S34.

[0073] S31. According to the acceleration time domain digital signal a(t), the acceleration spectrum A(f n ), where f n Represents the frequency of the nth spectral line in the spectrum, where n is a positive integer.

[0074] In the step S31, the Fourier transform is a linear integral transform used to transform a signal between the time domain (or space domain) and the frequency domain. Currently, it has many applications in physics and engineering. Therefore, the acceleration time domain digital signal a(t) can be Fourier transformed based on a conventional continuous Fourier transform method or a discrete Fourier transform method to obtain the acceleration spectrum A(f n ).

[0075] S32. According to the acceleration spectrum A(f n ), the velocity spectrum V(f n ) and displacement spectrum D(f n ):

[0076]

[0077] In the formula, π represents 180 degrees.

[0078] S33. According to the acceleration spectrum A(f n ), the speed spectrum V(f n ) and the displacement spectrum D(f n ) are respectively related to the spectral line frequency f n The functional relationship is plotted to obtain the nomogram spectrum in the nomogram coordinate system, wherein the nomogram coordinate system includes a horizontal coordinate, a vertical coordinate, a left-inclined coordinate and a right-inclined coordinate, the horizontal coordinate is a frequency value in logarithmic form, the vertical coordinate is a speed value in logarithmic form, the left-inclined coordinate is an acceleration value in logarithmic form, and the right-inclined coordinate is a displacement value in logarithmic form.

[0079] In step S33, the nomogram coordinate system is established based on the nomogram tool principle and the frequency (i.e., the spectral line frequency f n ), speed (i.e., speed spectrum V(f n )), acceleration (i.e., acceleration spectrum A(f n )) and displacement (i.e., displacement spectrum D(f n )) and other four physical quantities, so it can be based on the acceleration spectrum A(f n ), the speed spectrum V(f n ) and the displacement spectrum D(f n ) are respectively related to the functional relationship of the spectral line frequency fn, and the nomogram spectrum in the nom coordinate system is obtained by plotting. For example, Figure 5 The nomogram spectrum corresponding to the acceleration time domain simulation signal shown in the example (a) is as follows Figure 5 As shown in (b).

[0080] S34. According to the nomogram, the impulse pulse signal spectrum line a in the nom coordinate system is stripped out. ic (f), where f represents the frequency variable.

[0081] In the step S34, the conventional calculation method of the nomogram tool can be specifically referred to, and according to the nomogram spectrum, the shock pulse signal spectrum line is determined in the nomogram coordinate system to realize the conversion of the shock pulse signal spectrum line a ic (f) The purpose of stripping away from the actual nomogram, e.g. Figure 5 As shown in (b), the straight line in the low frequency band is the impulse signal spectrum line a ic (f).

[0082] S4. The second processing branch sequentially performs bandpass filtering processing with the resonance frequency of the acceleration sensor as the center frequency, half-wave rectification processing, waveform envelope processing, low-pass filtering processing, analog-to-digital conversion processing, impact pulse extraction processing and signal enhancement processing on the acceleration time domain analog signal to obtain an impact pulse time domain digital signal Here, t represents the time variable.

[0083] In step S4, the specific processing processes of the bandpass filtering, the half-wave rectification, the waveform envelope, the low-pass filtering, the analog-to-digital conversion, the impulse pulse extraction and the signal enhancement are all prior art and will not be described in detail here. For example Figure 6 shown.

[0084] S5. According to the impulse signal spectrum line a ic (f) and the impulse pulse time domain digital signal The effective value A of the impulse pulse frequency domain is calculated according to the following formula ic (f), time domain effective value of the impulse pulse σ ic And the proportionality coefficient p of the equivalence principle:

[0085]

[0086] In the formula, represents half of the length of the fast Fourier transform, N represents the digital signal in the time domain of the shock pulse The total number of discrete points in , t′ represents a positive integer less than or equal to N, represents the amplitude of the t′th discrete point in the impulse time domain digital signal a(t), Represents the time domain digital signal of the shock pulse The average amplitude of .

[0087] In step S5, this embodiment uses Figure 1 The sensor resonance frequency free decay vibration in the free decay vibration of the sensor resonance frequency caused by the impact pulse wave generated by the rolling bearing failure is shown as follows: Assuming that the sensor resonance frequency is also 32kHz, this 32kHz frequency free decay vibration can be obtained after bandpass filtering, half-wave shaping, enveloping and enhancement. Figure 3 The "d. enhanced impact pulse signal" shown in the figure is used to calculate the rolling bearing condition assessment parameters such as the maximum pulse decibel HBm, carpet decibel HDc, high-frequency impact value HR and / or low-frequency impact value LR. The advantage of the above scheme is that it does not require a dedicated sensor and is simple to use, but the disadvantage is that the peak value of the free decay vibration generated by the sensor resonant frequency is not equal to Figure 1 The amplitude of the shock pulse wave generated by the rolling bearing fault shown in the figure needs to be calibrated, that is, the resonance frequency of the acceleration sensor is selected for shock pulse test to diagnose the rolling bearing fault. There is a problem that needs to be solved in this way. When the mechanical modal frequency at the measured mechanical measuring point is the same as (or close to) the sensor resonance frequency, and the mechanical modal frequency has low damping and high resonance frequency gain (even exceeding the sensor resonance frequency gain), the shock pulse test value is too large (even a large number of dB), such as Figure 7 As shown, it will be unfavorable for bearing fault diagnosis, which requires shock pulse self-calibration.

[0088] In step S5, the relationship between the waveform, spectrum and nomological spectrum of a single unit shock pulse is considered as follows: Figure 8 As shown:

[0089] Figure 8 The effective value in the waveform shown in (a) (data length N = 1024):

[0090] Unit pulse waveform effective value

[0091] In the formula, Indicates the waveform average value of the unit shock pulse, a(t) t represents the impulse amplitude at time t;

[0092] Figure 8 The energy in the spectrum shown in (b) (FFT length 1024):

[0093] Effective value

[0094] In the formula, a ic (f) is the spectral line value of frequency f after the a(t) waveform is subjected to spectrum analysis;

[0095] Based on the above two formulas, it can be shown that the effective value in the impact pulse waveform is equal to the effective value in the spectrum. At the same time, the relationship between the acceleration waveform, spectrum and nomogram spectrum of multiple impact pulses is also considered. Fig. 9 As shown:

[0096] Fig. 9 The effective value of the impulse pulse in the waveform shown in (a) Should be equal to Fig. 9 The effective value of the spectrum shown in (b) Based on the above considerations and the resonant frequency generated by the sensor resonant frequency and the mechanical modal frequency, the shock pulse frequency domain effective value A ic (f) and the time domain effective value σ of the shock pulse ic Theoretically, the values ​​should be equal, but in actual tests, the results are not equal due to the influence of modal frequency, so it is necessary to calculate the proportional coefficient p of the equivalence principle used for shock pulse self-calibration.

[0097] S6. The time domain digital signal of the shock pulse The modified impulse pulse time domain digital signal is obtained by multiplying the proportional coefficient p of the equivalence principle.

[0098] In step S6, the multiplication calculation is the specific process of performing the shock pulse self-calibration.

[0099] S7. Calculate and obtain rolling bearing state assessment parameters based on the corrected impact pulse time-domain digital signal.

[0100] In the step S7, specifically, the rolling bearing state assessment parameters include but are not limited to the maximum pulse decibel HBm, carpet decibel HDc, high frequency impact value HR and / or low frequency impact value LR, etc., and their specific physical meanings are as follows:

[0101] (1) Rolling bearing life: The life of a rolling bearing is the number of revolutions before 90% of the bearings of the same model are damaged under the same operating conditions (in 10 6 The life of the bearing is defined as the number of working hours or working hours, and this life is called the rated life. The definition of the impact pulse on the bearing life is that a good new bearing has an initial impact vibration value. When the impact vibration value reaches about 1000 times the initial impact vibration value, it is considered that the bearing has reached the end of its service life. The unit of the above impact vibration value is decibel (dB).

[0102] (2)dB sv : Absolute decibel of shock pulse value, which is used to measure the absolute value of shock pulse energy intensity;

[0103] (3)dBi : Background decibel of the impact pulse value, i.e. the initial value of the rolling bearing, which depends on the inner diameter and rotation speed of the rolling bearing, dB i =20log 10 (n*d i 0.6 / 2150), n represents the speed in rpm, d i Indicates the pitch diameter of a rolling bearing;

[0104] (4)dB n : Standard decibel of shock pulse value, used to evaluate the working condition of rolling bearings, dB n =dB sv -dB i ;

[0105] (5) HD m : Maximum decibel, which is defined as the maximum decibel in the time window and Figure 3 The strongest pulse in "d. shock pulse signal after enhancement" shown indicates the maximum degree of damage to the rolling bearing element;

[0106] (6) HD c : Carpet decibel, Figure 3 The value of "d. Enhanced shock pulse signal" is the highest reading of 200 shock pulse signals per second (5ms), indicating the lubrication status of the rolling bearing. For a rolling bearing in good working condition, the carpet value is less than 10dB. n , HD c Always smaller than HD m ;

[0107] (7) HD m , HD c The reading is a relative reading, not an absolute decibel. sv , but the standard decibel dB n ;

[0108] (8) HD m =dB sv.max -dB i ;

[0109] (9)

[0110] (10) HR: High-frequency shock value, which is the value when 1000 (1ms) shock pulse signals are generated per second; it is equivalent to the minimum value, but not the minimum value. The HR high-frequency shock value is the shock value of the high-frequency shock. Divide 1 second into 1000 equal parts, that is, 1ms per part, find the maximum value within 1ms and store it, find the minimum value among the 1000 maximum values ​​in 1 second, average the minimum values ​​in N seconds, and use this average value as the HR pulse value;

[0111] (11) LR: Low-frequency impact value, which is the average value when 40 (25ms) impact pulse signals are generated per second; it is equivalent to the maximum value, but not the maximum value; the LR low-frequency impact value is the impact value of the low-frequency impact. Divide 1 second into 40 equal parts, that is, 25ms per part, find the maximum value within 25ms and store it, find the minimum value among the 40 maximum values ​​in 1 second, average the minimum values ​​in N seconds, and use this average value as the LR pulse value;

[0112] (12) HR and LR readings are absolute decibels dBsv;

[0113] (13) LR greater than 5dB indicates that the rolling bearing is short of oil; HR greater than -5dB indicates that the rolling bearing has an increased amount of wear particles in the lubricating oil;

[0114] Based on the above physical meaning, the rolling bearing state assessment parameters can be obtained by conventional calculation according to the modified impact pulse time domain digital signal: maximum pulse decibel HBm, carpet decibel HDc, high-frequency impact value HR and / or low-frequency impact value LR, etc.

[0115] S8. According to the rolling bearing state assessment parameters, determine the fault diagnosis result of the target rolling bearing and output it for display.

[0116] In step S8, the specific determination process of the fault diagnosis result is the prior art, for example, when LR is greater than 5dB, it is determined as a rolling bearing oil shortage fault, and when HR is greater than -5dB, it is determined as a rolling bearing lubricant with increased wear particles fault, etc. In addition, in order to achieve the purpose of completing the rolling bearing vibration and impact pulse test tasks at the same time, preferably, the first processing branch also performs vibration analysis on the acceleration time domain digital signal, obtains the vibration analysis result and outputs it for display; the specific process of the aforementioned vibration analysis is the prior art and will not be repeated here.

[0117] Therefore, based on the rolling bearing fault diagnosis method described in the aforementioned steps S1 to S8, a new solution for completing rolling bearing fault diagnosis based on an acceleration sensor and through shock pulse self-calibration is provided, that is, the acceleration time domain analog signal collected by the acceleration sensor is first sent to two different processing branches respectively, and then on the one hand, the shock pulse signal spectrum line is obtained through nom analysis, and on the other hand, the shock pulse time domain digital signal is obtained by performing bandpass filtering processing with the resonance frequency of the acceleration sensor as the center frequency, half-wave rectification processing, waveform envelope processing, low-pass filtering processing, analog-to-digital conversion processing, shock pulse extraction processing and signal enhancement processing, Then, based on the processing results, the frequency domain effective value of the impact pulse, the time domain effective value of the impact pulse and the proportional coefficient of the equivalence principle are calculated respectively. Finally, the impact pulse time domain digital signal and the proportional coefficient are multiplied to obtain the corrected impact pulse time domain digital signal, and the rolling bearing state assessment parameters are calculated based on this for use in rolling bearing fault diagnosis. In this way, the rolling bearing vibration and impact pulse test tasks can be completed simultaneously based on the acceleration sensor, and then the mechanical vibration evaluation and rolling bearing fault diagnosis can be completed in one test, which simplifies the rolling bearing detection work, is conducive to improving applicability, reducing prices and improving detection work efficiency, and is convenient for practical application and promotion.

[0118] like Fig.10 As shown, the second aspect of this embodiment provides a virtual device for implementing the rolling bearing fault diagnosis method described in the first aspect, including an analog signal receiving unit, an analog signal distribution unit, a first processing branch, a second processing branch, a proportional coefficient calculation unit, a signal multiplication calculation unit, an evaluation parameter calculation unit and a diagnosis result determination unit;

[0119] The analog signal receiving unit is used to receive the acceleration time domain analog signal acquired by the acceleration sensor, wherein the acceleration sensor is installed on the bearing seat of the target rolling bearing;

[0120] The analog signal distribution unit is communicatively connected to the analog signal receiving unit, and is used to send the acceleration time domain analog signal to the first processing branch and the second processing branch respectively;

[0121] The first processing branch is communicatively connected to the analog signal distribution unit, and is used to first convert the acceleration time domain analog signal into an acceleration time domain digital signal, and then obtain the impulse pulse signal spectrum line a through nom analysis according to the acceleration time domain digital signal. ic (f), where f represents the frequency variable;

[0122] The second processing branch is communicatively connected to the analog signal distribution unit, and is used to sequentially perform bandpass filtering processing with the resonance frequency of the acceleration sensor as the center frequency, half-wave rectification processing, waveform envelope processing, low-pass filtering processing, analog-to-digital conversion processing, impact pulse extraction processing and signal enhancement processing on the acceleration time domain analog signal to obtain an impact pulse time domain digital signal Where t represents the time variable;

[0123] The proportional coefficient calculation unit is respectively connected to the first processing branch and the second processing branch for calculating the proportional coefficient according to the impulse pulse signal spectrum line a ic (f) and the impulse pulse time domain digital signal The effective value A of the impulse pulse frequency domain is calculated according to the following formula ic (f), time domain effective value of the impulse pulse σ ic And the proportionality coefficient p of the equivalence principle:

[0124]

[0125] In the formula, represents half of the length of the fast Fourier transform, N represents the digital signal in the time domain of the shock pulse The total number of discrete points in , t′ represents a positive integer less than or equal to N, represents the amplitude of the t′th discrete point in the impulse time domain digital signal a(t), Represents the time domain digital signal of the shock pulse The average amplitude of

[0126] The signal multiplication calculation unit is respectively connected to the second processing branch and the proportional coefficient calculation unit for calculating the impulse pulse time domain digital signal. The modified impulse pulse time domain digital signal is obtained by multiplying the proportional coefficient p of the equivalence principle;

[0127] The evaluation parameter calculation unit is communicatively connected to the signal multiplication calculation unit, and is used to calculate the rolling bearing state evaluation parameter according to the corrected impact pulse time domain digital signal;

[0128] The diagnosis result determination unit is communicatively connected to the assessment parameter calculation unit, and is used to determine the fault diagnosis result of the target rolling bearing according to the rolling bearing state assessment parameter and output it for display.

[0129] The working process, working details and technical effects of the aforementioned device provided in the second aspect of this embodiment can be referred to the rolling bearing fault diagnosis method described in the first aspect, and will not be repeated here.

[0130] like Fig.11 As shown, the third aspect of this embodiment provides a computer device for executing the rolling bearing fault diagnosis method as described in the first aspect, including a memory, a processor and a transceiver that are sequentially connected in communication, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program to execute the rolling bearing fault diagnosis method as described in the first aspect. For example, the memory may include, but is not limited to, a random access memory (Random-Access Memory, RAM), a read-only memory (Read-Only Memory, ROM), a flash memory (Flash Memory), a first-in-first-out memory (First Input First Output, FIFO) and / or a first-in-last-out memory (First Input Last Output, FILO), etc.; the processor may include, but is not limited to, a microprocessor of the STM32F105 series. In addition, the computer device may also include, but is not limited to, a power module, a display screen and other necessary components.

[0131] The working process, working details and technical effects of the aforementioned computer device provided in the third aspect of this embodiment can be referred to the rolling bearing fault diagnosis method described in the first aspect, and will not be repeated here.

[0132] The fourth aspect of this embodiment provides a computer-readable storage medium storing instructions including the rolling bearing fault diagnosis method as described in the first aspect, that is, the computer-readable storage medium stores instructions, and when the instructions are run on a computer, the rolling bearing fault diagnosis method as described in the first aspect is executed. Wherein, the computer-readable storage medium refers to a carrier for storing data, which may include but is not limited to computer-readable storage media such as floppy disks, optical disks, hard disks, flash memories, USB flash drives and / or memory sticks, and the computer may be a general-purpose computer, a special-purpose computer, a computer network or other programmable devices.

[0133] The working process, working details and technical effects of the aforementioned computer-readable storage medium provided in the fourth aspect of this embodiment can be referred to the rolling bearing fault diagnosis method described in the first aspect, and will not be repeated here.

[0134] A fifth aspect of this embodiment provides a computer program product, including a computer program or instructions, which, when executed by a computer, implements the rolling bearing fault diagnosis method as described in the first aspect. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0135] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A rolling bearing fault diagnosis method, characterized in that: include: Receiving an acceleration time-domain analog signal acquired by an acceleration sensor, wherein the acceleration sensor is mounted on a bearing seat of a target rolling bearing; Sending the acceleration time domain analog signal to a first processing branch and a second processing branch respectively; The first processing branch first converts the acceleration time domain analog signal into an acceleration time domain digital signal, and then obtains the impulse pulse signal spectrum line a through nom analysis based on the acceleration time domain digital signal. ic (f), where f represents the frequency variable; The second processing branch sequentially performs bandpass filtering processing with the resonance frequency of the acceleration sensor as the center frequency, half-wave rectification processing, waveform envelope processing, low-pass filtering processing, analog-to-digital conversion processing, impact pulse extraction processing and signal enhancement processing on the acceleration time domain analog signal to obtain an impact pulse time domain digital signal Among them, t represents the time variable; According to the impulse pulse signal spectrum line a ic (f) and the impulse pulse time domain digital signal The effective value A of the impulse pulse frequency domain is calculated according to the following formula ic (f), time domain effective value of the impulse pulse σ ic And the proportionality coefficient p of the equivalence principle: In the formula, represents half of the length of the fast Fourier transform, N represents the digital signal in the time domain of the shock pulse The total number of discrete points in , t′ represents a positive integer less than or equal to N, represents the amplitude of the t′th discrete point in the impulse time domain digital signal a(t), where a represents the impulse time domain digital signal The average amplitude of The time domain digital signal of the shock pulse The modified impulse pulse time domain digital signal is obtained by multiplying the proportional coefficient p of the equivalence principle; Calculating and obtaining rolling bearing state assessment parameters according to the corrected impact pulse time-domain digital signal; According to the rolling bearing state assessment parameters, the fault diagnosis result of the target rolling bearing is determined and output for display.

2. The rolling bearing fault diagnosis method according to claim 1, characterized in that: Sending the acceleration time domain analog signal to a first processing branch and a second processing branch respectively includes: Performing signal conditioning processing on the acceleration time-domain analog signal to obtain a conditioned acceleration time-domain analog signal; The conditioned acceleration time domain analog signal is sent to the first processing branch and the second processing branch respectively.

3. The rolling bearing fault diagnosis method according to claim 1, characterized in that: According to the acceleration time domain digital signal, the impulse pulse signal spectrum line a is obtained by nom analysis. ic (f) including: According to the acceleration time domain digital signal a(t), the acceleration spectrum A(f n ), where fn represents the frequency of the nth spectral line in the spectrum, and n represents a positive integer; According to the acceleration spectrum A(f n ), the velocity spectrum V(f n ) and displacement spectrum D(f n ): In the formula, π represents 180 degrees; According to the acceleration spectrum A(f n ), the speed spectrum V(f n ) and the displacement spectrum D(f n ) are respectively related to the spectral line frequency f n The functional relationship is plotted to obtain a nomogram spectrum in a nomogram coordinate system, wherein the nomogram coordinate system includes an abscissa, a ordinate, a left-inclined coordinate, and a right-inclined coordinate, wherein the abscissa is a frequency value in logarithmic form, the ordinate is a velocity value in logarithmic form, the left-inclined coordinate is an acceleration value in logarithmic form, and the right-inclined coordinate is a displacement value in logarithmic form; According to the nomogram, the impulse pulse signal spectrum line a in the nom coordinate system is stripped out. ic (f).

4. The rolling bearing fault diagnosis method according to claim 1, characterized in that: The method further comprises: The first processing branch also performs vibration analysis on the acceleration time-domain digital signal to obtain a vibration analysis result and output it for display.

5. The rolling bearing fault diagnosis method according to claim 1, characterized in that: The acceleration sensor is an acceleration sensor of model A14A050TE-T.

6. The rolling bearing fault diagnosis method according to claim 1, characterized in that: The rolling bearing condition assessment parameters include maximum pulse decibel HBm, carpet decibel HDc, high frequency impact value HR and / or low frequency impact value LR.

7. A rolling bearing fault diagnosis device, characterized in that: It includes an analog signal receiving unit, an analog signal distributing unit, a first processing branch, a second processing branch, a proportional coefficient calculating unit, a signal multiplication calculating unit, an evaluation parameter calculating unit and a diagnosis result determining unit; The analog signal receiving unit is used to receive the acceleration time domain analog signal acquired by the acceleration sensor, wherein the acceleration sensor is installed on the bearing seat of the target rolling bearing; The analog signal distribution unit is communicatively connected to the analog signal receiving unit, and is used to send the acceleration time domain analog signal to the first processing branch and the second processing branch respectively; The first processing branch is communicatively connected to the analog signal distribution unit, and is used to first convert the acceleration time domain analog signal into an acceleration time domain digital signal, and then obtain the impulse pulse signal spectrum line a through nom analysis according to the acceleration time domain digital signal. ic (f), where f represents the frequency variable; The second processing branch is communicatively connected to the analog signal distribution unit, and is used to sequentially perform bandpass filtering processing with the resonance frequency of the acceleration sensor as the center frequency, half-wave rectification processing, waveform envelope processing, low-pass filtering processing, analog-to-digital conversion processing, impact pulse extraction processing and signal enhancement processing on the acceleration time domain analog signal to obtain an impact pulse time domain digital signal Among them, t represents the time variable; The proportional coefficient calculation unit is respectively connected to the first processing branch and the second processing branch for calculating the proportional coefficient according to the impulse pulse signal spectrum line a ic (f) and the impulse pulse time domain digital signal The effective value A of the impulse pulse frequency domain is calculated according to the following formula ic (f), time domain effective value of the impulse pulse σ ic And the proportionality coefficient p of the equivalence principle: In the formula, represents half of the length of the fast Fourier transform, N represents the digital signal in the time domain of the shock pulse The total number of discrete points in , t′ represents a positive integer less than or equal to N, represents the amplitude of the t′th discrete point in the impulse time domain digital signal a(t), where a represents the impulse time domain digital signal The average amplitude of The signal multiplication calculation unit is respectively connected to the second processing branch and the proportional coefficient calculation unit for calculating the impulse pulse time domain digital signal. The modified impulse pulse time domain digital signal is obtained by multiplying the proportional coefficient p of the equivalence principle; The evaluation parameter calculation unit is communicatively connected to the signal multiplication calculation unit, and is used to calculate the rolling bearing state evaluation parameter according to the corrected impact pulse time domain digital signal; The diagnosis result determination unit is communicatively connected to the assessment parameter calculation unit, and is used to determine the fault diagnosis result of the target rolling bearing according to the rolling bearing state assessment parameter and output it for display.

8. A computer device, characterized in that: It comprises a memory, a processor and a transceiver which are communicatively connected in sequence, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program to execute the rolling bearing fault diagnosis method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed on the computer, the rolling bearing fault diagnosis method as described in any one of claims 1 to 6 is executed.

10. A computer program product comprising a computer program or instructions, characterized in that The computer program or the instructions, when executed by a computer, implements the rolling bearing fault diagnosis method according to any one of claims 1 to 6.

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