Fault Diagnosis Method and Device, Storage Medium

Abstract

The present disclosure provides a fault diagnosis method, a device, and a storage medium, relating to the technical field of fault diagnosis. The fault diagnosis method includes: acquiring a vibration signal of a device under test; calculating an envelope signal of the vibration signal; processing the envelope information by using a first frequency-modulated wavelet transform to obtain a first time-frequency diagram, wherein a frequency modulation factor in the first frequency-modulated wavelet transform is a function of an instantaneous frequency, and a window function in the first frequency-modulated wavelet transform is a differentiable window function; constructing a synchronous extraction operator by using the first time-frequency diagram; obtaining a target time-frequency diagram by using the first time-frequency diagram and the synchronous extraction operator; and identifying a ridge line in the target time-frequency diagram so as to determine a fault type of the device under test according to the ridge line.

Description

Technical Field

[0001] The present disclosure relates to the technical field of fault diagnosis, and particularly to a fault diagnosis method, apparatus, and storage medium. Background Art

[0002] Rotating machinery is an important part of modern industry, and its fault diagnosis is crucial for improving operation reliability and avoiding serious accidents. Vibration signals contain rich information characterizing the health status of the monitored equipment. Conducting vibration signal analysis can effectively achieve fault diagnosis of rotating machinery. In industrial sites, rotating machinery often operates under variable speed conditions. The change in speed will cause the vibration signal to exhibit non-stationary characteristics such as amplitude modulation and frequency modulation, posing great challenges to vibration signal analysis and fault diagnosis of variable speed rotating machinery.

[0003] Time-frequency analysis is a feasible non-stationary signal analysis technique that can expand a one-dimensional signal into a two-dimensional time-frequency diagram, thereby simultaneously characterizing the inherent time-varying non-stationary characteristics of the signal in the time domain and the frequency domain. Currently, time-frequency analysis has been widely applied to non-stationary vibration signal analysis for fault diagnosis of variable speed rotating machinery. Summary of the Invention

[0004] The inventors have found through research that the vibration signal collected from rotating machinery is a signal composed of multiple signal components, and the instantaneous frequency of each signal component is related to the rotational frequency of the rotating machinery and has a proportional relationship. However, the existing time-frequency analysis methods fail to fully consider the above unique characteristics of the rotating machinery vibration signal, so it is difficult to obtain a high-quality time-frequency diagram and accurately characterize the inherent time-varying non-stationary characteristics when analyzing the rotating machinery vibration signal, especially for multi-component vibration signals with small frequency intervals and noise interference, which may lead to diagnostic errors in the fault diagnosis of variable speed rotating machinery.

[0005] Accordingly, the present disclosure provides a fault diagnosis solution that can accurately diagnose the faults of rotating machinery, thereby ensuring the operation safety of rotating machinery.

[0006] According to a first aspect of an embodiment of the present disclosure, there is provided a fault diagnosis method, which is executed by a fault diagnosis apparatus and includes: acquiring a vibration signal of a device under test; calculating an envelope signal of the vibration signal; processing the envelope information by using a first frequency-modulated wavelet transform to obtain a first time-frequency diagram, where the frequency modulation factor in the first frequency-modulated wavelet transform is a function of the instantaneous frequency, and the window function in the first frequency-modulated wavelet transform is a differentiable window function; constructing a synchronous extraction operator by using the first time-frequency diagram; obtaining a target time-frequency diagram by using the first time-frequency diagram and the synchronous extraction operator; and identifying a ridge line in the target time-frequency diagram so as to determine the fault type of the device under test according to the ridge line.

[0007] In some embodiments, the frequency modulation factor is κw, where w is the instantaneous frequency and κ is a frequency parameter.

[0008] In some embodiments, the frequency parameter κ is the tangent value of the angle parameter θ.

[0009] In some embodiments, the optimal value θ * of the angle parameter θ is:

[0010]

[0011]

[0012] where is the time-frequency diagram when the angle parameter θ is θ n , and is the kurtosis value in the direction of the instantaneous frequency, and represents the angle parameter used for the time-frequency diagram with the maximum kurtosis value.

[0013] In some embodiments, constructing the synchronization extraction operator using the first time-frequency diagram includes: respectively processing the envelope information using the second frequency-modulated wavelet transform, the third frequency-modulated wavelet transform, the fourth frequency-modulated wavelet transform, and the fifth frequency-modulated wavelet transform to respectively obtain a second time-frequency diagram, a third time-frequency diagram, a fourth time-frequency diagram, and a fifth time-frequency diagram, where the frequency modulation factors in the second to fifth frequency-modulated wavelet transforms are the same as the frequency modulation factor of the first frequency-modulated wavelet transform, the window function in the second frequency-modulated wavelet transform is the first derivative g′ of the window function g of the first frequency-modulated wavelet transform, the window function in the third frequency-modulated wavelet transform is the second derivative g″ of the window function g, the window function in the fourth frequency-modulated wavelet transform is the product tg of the window function g and time t, and the window function in the fifth frequency-modulated wavelet transform is the product tg′ of the window function g′ and time t; obtaining an instantaneous frequency estimation operator using the first time-frequency diagram, the second time-frequency diagram, the third time-frequency diagram, the fourth time-frequency diagram, the fifth time-frequency diagram, and the instantaneous frequency; and constructing the synchronization extraction operator according to the first time-frequency diagram and the instantaneous frequency estimation operator.

[0014] In some embodiments, obtaining the instantaneous frequency estimation operator by using the first time-frequency diagram, the second time-frequency diagram, the third time-frequency diagram, the fourth time-frequency diagram, the fifth time-frequency diagram, and the instantaneous frequency includes: multiplying the second time-frequency diagram and the fifth time-frequency diagram to obtain a first product; multiplying the third time-frequency diagram and the fourth time-frequency diagram to obtain a second product; multiplying the second time-frequency diagram and the fourth time-frequency diagram to obtain a third product; multiplying the first time-frequency diagram and the fifth time-frequency diagram to obtain a fourth product; subtracting the second product from the first product to obtain a first difference; subtracting the fourth product from the third product to obtain a second difference; obtaining the instantaneous frequency estimation operator according to the imaginary part of the ratio of the first difference to the second difference and the instantaneous frequency.

[0015] In some embodiments, the instantaneous frequency estimation operator is the sum of the imaginary part of the ratio and the instantaneous frequency.

[0016] In some embodiments, when the first condition and the second condition are both satisfied, the synchronization extraction operator is 1; wherein, the first condition is that the amplitude of the first time-frequency diagram is greater than the first threshold η, the second condition is that the amplitude of the imaginary part of the ratio is less than the second threshold ξ, and the first threshold η and the second threshold ξ are non-negative values.

[0017] In some embodiments, when the first condition or the second condition is not satisfied, the synchronization extraction operator is 0.

[0018] In some embodiments, the first threshold v is determined by the number of signal points M and the noise variance σ; the second threshold ξ is less than the frequency resolution.

[0019] In some embodiments, the first threshold A is a preset parameter.

[0020] In some embodiments, the noise variance σ is determined by using the first time-frequency diagram and the median of the amplitude of the first time-frequency diagram.

[0021] In some embodiments, determining the noise variance σ by using the first time-frequency diagram and the median of the amplitude of the first time-frequency diagram includes: subtracting the median of the amplitude of the first time-frequency diagram from the first time-frequency diagram to obtain a time-frequency diagram to be processed; taking the ratio of the median of the amplitude of the time-frequency diagram to be processed to a preset parameter as the noise variance σ.

[0022] In some embodiments, the second threshold ξ is one-half of the frequency resolution.

[0023] In some embodiments, the target time-frequency diagram is the product of the first time-frequency diagram and the synchronization extraction operator.

[0024] In some embodiments, calculating the envelope signal of the vibration signal includes: performing a Hilbert transform on the vibration signal to obtain a transform result; and obtaining the envelope signal based on the vibration signal and the transform result.

[0025] In some embodiments, the envelope signal x is:

[0026]

[0027] where s is the vibration signal and Hilbert() is the Hilbert transform function.

[0028] According to a second aspect of the embodiments of the present disclosure, there is provided a fault diagnosis device, including: a first processing module configured to acquire a vibration signal of a device under test and calculate an envelope signal of the vibration signal; a second processing module configured to process the envelope information by using a first frequency-modulated wavelet transform to obtain a first time-frequency diagram, where a frequency modulation factor in the first frequency-modulated wavelet transform is a function of an instantaneous frequency, and a window function in the first frequency-modulated wavelet transform is a differentiable window function; a third processing module configured to construct a synchronous extraction operator by using the first time-frequency diagram and obtain a target time-frequency diagram by using the first time-frequency diagram and the synchronous extraction operator; and a fourth processing module configured to identify a ridge line in the target time-frequency diagram so as to determine a fault type of the device under test according to the ridge line.

[0029] According to a third aspect of the embodiments of the present disclosure, there is provided a fault diagnosis device, including: a memory configured to store instructions; and a processor coupled to the memory, where the processor is configured to execute, based on the instructions stored in the memory, to implement the method as described in any one of the above embodiments.

[0030] According to a fourth aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium, where the computer-readable storage medium stores computer instructions, and when the instructions are executed by a processor, the method as described in any one of the above embodiments is implemented.

[0031] Other features and advantages of the present disclosure will become clear through the following detailed description of the exemplary embodiments of the present disclosure with reference to the accompanying drawings. Description of the Drawings

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present disclosure. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0033] Figure 1 Schematic diagram of a rotating machinery structure according to an embodiment of the present disclosure;

[0034] Figure 2 Schematic diagram of a rotating machinery fault according to an embodiment of the present disclosure;

[0035] Figure 3 Schematic flow diagram of a fault diagnosis method according to an embodiment of the present disclosure;

[0036] Figure 4 Schematic diagram of a vibration signal according to an embodiment of the present disclosure;

[0037] Figure 5 Schematic diagram of an instantaneous rotational frequency curve of an input shaft according to an embodiment of the present disclosure;

[0038] Figure 6 Schematic diagram of a time-frequency diagram according to an embodiment of the present disclosure;

[0039] Figure 7 Schematic diagram of a time-frequency diagram according to another embodiment of the present disclosure;

[0040] Figure 8 Schematic diagram of the structure of a fault diagnosis device according to an embodiment of the present disclosure;

[0041] Figure 9 Schematic diagram of the structure of a fault diagnosis device according to another embodiment of the present disclosure. Detailed implementation manners

[0042] Next, the technical solutions in the embodiments of the present disclosure will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and in no way limits the present disclosure and its application or use. Based on the embodiments in the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present disclosure.

[0043] Unless otherwise specifically stated, the relative arrangements of components and steps, numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present disclosure.

[0044] At the same time, it should be understood that, for the sake of convenience of description, the dimensions of the various parts shown in the drawings are not drawn in actual proportional relationships.

[0045] For technologies, methods, and devices known to those of ordinary skill in the relevant art, detailed discussions may not be made, but where appropriate, the technologies, methods, and devices should be regarded as part of the authorization specification.

[0046] In all examples shown and discussed here, any specific values should be construed as merely exemplary and not as a limitation. Thus, other examples of the exemplary embodiments may have different values.

[0047] It should be noted that like reference numerals and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof in subsequent figures is not necessary.

[0048] Figure 1 Schematic diagram of the rotating machinery structure according to an embodiment of the present disclosure. In Figure 1 this example, the rotating machinery is introduced by taking the planetary gearbox as an example. The planetary gearbox test bench includes a driving motor 1, a coupling 2, an input shaft encoder 3, a planetary gearbox 4, an output shaft encoder 5, a coupling 6, and a magnetic powder brake 7. The planetary gearbox 4 mainly consists of a ring gear 41, a sun gear 42, and three evenly distributed planet gears 43. In addition, the planet gear 43 is connected to the output shaft, the sun gear 42 is connected to the input shaft, the input shaft encoder 3 is installed on the input shaft, and the output shaft encoder 5 is installed on the output shaft. The entire test bench is driven by the driving motor 1, the magnetic powder brake 7 is used for loading, and the input shaft encoder 3 and the output shaft encoder 5 are respectively used to measure the instantaneous rotational frequency of the input shaft and the output shaft.

[0049] For example, the specific parameters of the planetary gearbox test bench are as follows: the rated power of the driving motor 1 is 1.2 kW, the transmission ratio of the planetary gearbox 4 is 5.1:1, the number of teeth and the module of the ring gear 41 are 82 and 1 respectively, the number of teeth and the module of the sun gear 42 are 20 and 1 respectively, and the number of teeth and the module of the planet gear 43 are 31 and 1 respectively. The torque under the rated power of the magnetic powder brake 7 is 0.06 N*m.

[0050] As Figure 2 shown, the planetary gearbox has a fault of ring gear spalling, at the position indicated by the white arrow in Figure 2 this figure.

[0051] By using the fault diagnosis scheme provided by the present disclosure, the faults of the rotating machinery can be accurately diagnosed, thereby ensuring the operation safety of the rotating machinery.

[0052] Figure 3 Schematic flow diagram of the fault diagnosis method according to an embodiment of the present disclosure. In some embodiments, the following fault diagnosis method is executed by a fault diagnosis device.

[0053] In step 301, the vibration signal of the device under test is acquired.

[0054] In some embodiments, a vibration sensor is installed on the device under test, the driving motor is controlled to rotate at a variable speed, a vibration signal is collected by a data acquisition card, and then the vibration signal in a preset time period (for example, 12 seconds) is intercepted, and the obtained vibration signal is processed to remove the mean value to obtain a vibration signal s, as Figure 4 shown. From Figure 5 the instantaneous rotational frequency curve of the input shaft shown, it can be seen that the test bench is operating under variable speed conditions, and thus Figure 4 the vibration signal shown is a non-stationary signal with amplitude-frequency modulation.

[0055] In step 302, calculate the envelope signal of the vibration signal.

[0056] In some embodiments, the vibration signal is subjected to Hilbert transform to obtain a transformation result, and an envelope signal is obtained based on the vibration signal and the transformation result.

[0057] For example, the envelope signal x is as shown in formula (1).

[0058]

[0059] where s is the vibration signal and Hilbert() is the Hilbert transform function.

[0060] In step 303, the envelope information is processed using the first frequency-modulated wavelet transform to obtain a first time-frequency diagram. The frequency modulation factor in the first frequency-modulated wavelet transform is a function of the instantaneous frequency, and the window function in the first frequency-modulated wavelet transform is a differentiable window function.

[0061] In some embodiments, the frequency modulation factor is κw, w is the instantaneous frequency, and κ is the frequency parameter.

[0062] For example, the first time-frequency diagram is as shown in formula (2).

[0063]

[0064] where t is time, w is the instantaneous frequency, g() is the differentiable window function, κw is the frequency modulation factor, and the value range of the frequency parameter κ is κ ∈ (-∞, +∞).

[0065] In some embodiments, in order to reduce the difficulty of selecting the frequency parameter κ, the frequency parameter κ is set to the tangent value of the angle parameter θ, as shown in formula (3).

[0066] κ = tan(θ) (3)

[0067] where,

[0068] Thus, the selection of the frequency parameter κ is converted to the selection of the angle parameter θ.

[0069] In some embodiments, in order to select a suitable angular parameter θ, the angular range is equally divided into N θ parts, as shown in formula (4).

[0070]

[0071] It should be noted that the larger the value of N θ , the more angular parameters θ n can be obtained, and thus the closer to the optimal parameters can be obtained. However, a larger value of N θ will increase the computational complexity. Therefore, it is recommended to set the parameter N θ to 10 to 50. For example, the parameter N θ is set to 30.

[0072] In some embodiments, when the angular parameter θ n matches the vibration signal to be analyzed, the energy in the time-frequency diagram will be concentrated near the ridge line of the instantaneous frequency, and the amplitude will reach the maximum value. Therefore, kurtosis is introduced here as an evaluation index, and the optimal parameter θ * is determined according to the maximum kurtosis value, as shown in formula (5).

[0073]

[0074] is the kurtosis value in the direction of the instantaneous frequency, and represents the angular parameter used for the time-frequency diagram with the maximum kurtosis value.

[0075] Thus, the optimal parameter θ * is obtained by using formula (5), and the optimal parameter θ * is substituted into formula (3) to obtain the frequency parameter κ, and then the frequency parameter κ is substituted into formula (2) to obtain the first time-frequency diagram.

[0076] In step 304, a synchronous extraction operator is constructed using the first time-frequency diagram.

[0077] In some embodiments, the envelope information is processed using a second chirplet transform to obtain a second time-frequency diagram. The envelope information is processed using a third chirplet transform to obtain a third time-frequency diagram respectively. The envelope information is processed using a fourth chirplet transform to obtain a fourth time-frequency diagram. The envelope information is processed using a fifth chirplet transform to obtain a fifth time-frequency diagram respectively.

[0078] ​It should be noted that the frequency modulation factors in the second to fifth frequency modulation wavelet transforms are the same as that in the first frequency modulation wavelet transform. The window function in the second frequency modulation wavelet transform is the first derivative g′ of the window function g in the first frequency modulation wavelet transform. The window function in the third frequency modulation wavelet transform is the second derivative g″ of the window function g. The window function in the fourth frequency modulation wavelet transform is the product tg of the window function g and time t. The window function in the fifth frequency modulation wavelet transform is the product tg′ of the window function g′ and time t.

[0079] That is to say, the window function g′ in the second frequency modulation wavelet transform is The window function g″ in the third frequency modulation wavelet transform is The window function in the fourth frequency modulation wavelet transform is tg, and the window function in the fifth frequency modulation wavelet transform is tg′.

[0080] Next, an instantaneous frequency estimation operator is obtained by using the first time-frequency diagram, the second time-frequency diagram, the third time-frequency diagram, the fourth time-frequency diagram, the fifth time-frequency diagram, and the instantaneous frequency. A synchronous extraction operator is constructed based on the first time-frequency diagram and the instantaneous frequency estimation operator.

[0081] In some embodiments, the second time-frequency diagram and the fifth time-frequency diagram are multiplied to obtain a first product. The third time-frequency diagram and the fourth time-frequency diagram are multiplied to obtain a second product. The second time-frequency diagram and the fourth time-frequency diagram are multiplied to obtain a third product. The first time-frequency diagram and the fifth time-frequency diagram are multiplied to obtain a fourth product. The first product is subtracted from the second product to obtain a first difference. The third product is subtracted from the fourth product to obtain a second difference. An instantaneous frequency estimation operator is obtained based on the imaginary part of the ratio of the first difference to the second difference and the instantaneous frequency.

[0082] For example, the instantaneous frequency estimation operator is the sum of the imaginary part of the ratio and the instantaneous frequency.

[0083] In some embodiments, the instantaneous frequency estimation operator is as shown in formula (6).

[0084]

[0085] Wherein, is the first time-frequency diagram, is the second time-frequency diagram, is the third time-frequency diagram, is the fourth time-frequency diagram, is the fifth time-frequency diagram, w is the instantaneous frequency, and Im() is the imaginary part of a complex number.

[0086] It should be noted that and both represent the first time-frequency diagram, and The first time-frequency diagram is shown only to make Equation (6) more concise. Similarly, the second to fifth time-frequency diagrams can also be represented in the same way. is represented.

[0087] In some embodiments, when the first condition and the second condition are both satisfied, the synchronous extraction operator is 1. When the first condition or the second condition is not satisfied, the synchronous extraction operator is 0. The first condition is that the amplitude of the first time-frequency diagram is greater than the first threshold η, and the second condition is that the amplitude of the imaginary part of the ratio is less than the second threshold ξ. The first threshold η and the second threshold ξ are non-negative values. For example, the synchronous extraction operator is as shown in Equation (7).

[0088]

[0089] wherein, the first condition is as shown in Equation (8), and the second condition is as shown in Equation (9).

[0090]

[0091]

[0092] It should be noted that the first threshold η is a non-negative value, which is used to eliminate the influence of noise interference, and its value is related to the noise intensity. For example, the first threshold η is determined by the number of signal points M and the noise variance σ, as shown in Equation (10).

[0093]

[0094] wherein, M is the number of signal points, σ is the noise variance, and A is a preset parameter. For example, A is 2. The noise variance σ is determined by the first time-frequency diagram and the median of the amplitude of the first time-frequency diagram.

[0095] For example, subtract the median of the amplitude of the first time-frequency diagram from the first time-frequency diagram to obtain the time-frequency diagram to be processed. Next, take the ratio of the median of the amplitude of the time-frequency diagram to be processed to the preset parameter as the noise variance σ. For example, the noise variance σ is as shown in Equation (11).

[0096]

[0097] wherein, median() is the median function, and B is a preset parameter. For example, B is 0.6754.

[0098] In addition, the second threshold ξ is a non-negative value and is less than the frequency resolution. For example, the second threshold ξ is one-half of the frequency resolution.

[0099] In step 305, the target time-frequency diagram is obtained by using the first time-frequency diagram and the synchronous extraction operator.

[0100] In some embodiments, the target time-frequency diagram \(T_c(t, w)\) is the first time-frequency diagram and the synchronization extraction operator The product is shown in Equation (12).

[0101]

[0102] It should be noted that it can be seen from Equation (12) that in the target time-frequency diagram \(T_c(t, w)\), only the time-frequency coefficients near are retained. Therefore, through Equation (12), a time-frequency diagram with high energy concentration and clear time-varying non-stationary characteristics can be obtained, as Figure 6 shown.

[0103] In step 306, identify the ridge line in the target time-frequency diagram to determine the fault type of the device under test according to the ridge line.

[0104] For example, for the structural parameters of the planetary gearbox shown in Figure 1 , the fault orders of the sun gear, planetary gear, and ring gear relative to the input shaft are calculated to be 2.1118, 0.51866, and 0.58824 respectively. Then, the fault characteristic frequencies of the sun gear, planetary gear, and ring gear are \(f Sun = 2.1118f r , \(f Plant = 0.51886f r and \(f Ring = 0.58824f r , where \(f r represents the instantaneous rotational frequency of the input shaft. As shown in Figure 6 , the ridge line in the time-frequency diagram is close to the instantaneous rotational frequency \(f r of the input shaft, the fault characteristic frequency \(f Ring of the ring gear, and its harmonics 2f Ring , 3f Ring and 4f Ring . That is, the distribution pattern of the ridge line in the time-frequency diagram is related to the fault of the ring gear. Therefore, the fault of the ring gear of the planetary gearbox can be accurately diagnosed under variable rotational speed conditions.

[0105] Figure 7 is the time-frequency diagram generated by using the existing short-time Fourier transform. By comparing Figure 6 and Figure 7 , it can be seen that in the target time-frequency diagram shown in Figure 6 obtained by using the above embodiments of the present disclosure, the energy concentration is higher, the time-varying instantaneous frequency is clearer, and the noise interference component is effectively suppressed. That is to say, compared with the prior art, the solution provided by the present disclosure can effectively improve the fault diagnosis accuracy.

[0106] Figure 8 Schematic diagram of the structure of a fault diagnosis device according to an embodiment of the present disclosure. As Figure 8 shown, the fault diagnosis device includes a first processing module 81, a second processing module 82, a third processing module 83, and a fourth processing module 84.

[0107] The first processing module 81 is configured to acquire a vibration signal of a device under test and calculate an envelope signal of the vibration signal.

[0108] In some embodiments, the first processing module 81 performs a Hilbert transform on the vibration signal to obtain a transform result, and obtains an envelope signal based on the vibration signal and the transform result.

[0109] For example, the envelope signal x is shown in formula (1).

[0110] The second processing module 82 is configured to process the envelope information by using a first frequency-modulated wavelet transform to obtain a first time-frequency diagram, where the frequency modulation factor in the first frequency-modulated wavelet transform is a function of the instantaneous frequency, and the window function in the first frequency-modulated wavelet transform is a differentiable window function.

[0111] In some embodiments, the frequency modulation factor is κw, w is the instantaneous frequency, and κ is a frequency parameter.

[0112] For example, the first time-frequency diagram is shown in formula (2).

[0113] In some embodiments, the frequency parameter κ is set to the tangent value of the angular parameter θ, as shown in formula (3).

[0114] In some embodiments, the optimal value θ of the angular parameter θ * is shown in formula (5).

[0115] The third processing module 83 is configured to construct a synchronous extraction operator by using the first time-frequency diagram, and obtain a target time-frequency diagram by using the first time-frequency diagram and the synchronous extraction operator.

[0116] In some embodiments, the third processing module 83 calculates an instantaneous frequency estimation operator by using formula (6) and constructs a synchronous extraction operator according to the first time-frequency diagram and the instantaneous frequency estimation operator where the synchronous extraction operator where the synchronous extraction operator is shown in formula (7).

[0117] In some embodiments, the target time-frequency diagram Tc(t, w) is the first time-frequency diagram and the synchronous extraction operator The product is shown in Formula (12).

[0118] The fourth processing module 84 is configured to identify the ridge line in the target time-frequency diagram so as to determine the fault type of the device under test according to the ridge line.

[0119] Figure 9 It is a schematic structural diagram of a fault diagnosis device according to another embodiment of the present disclosure. As Figure 9 shown, the fault diagnosis device includes a memory 91 and a processor 92.

[0120] The memory 91 is used to store instructions. The processor 92 is coupled to the memory 91. The processor 92 is configured to execute the methods related to any one of the embodiments as Figure 3 described.

[0121] As Figure 9 shown, the fault diagnosis device further includes a communication interface 93 for information interaction with other devices. At the same time, the fault diagnosis device further includes a bus 94. The processor 92, the communication interface 93, and the memory 91 complete mutual communication through the bus 94.

[0122] The memory 91 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory. The memory 91 may also be a memory array. The memory 91 may also be partitioned, and the blocks may be combined into virtual volumes according to certain rules.

[0123] In addition, the processor 92 may be a central processing unit CPU, or may be an application specific integrated circuit ASIC, or may be one or more integrated circuits configured to implement the embodiments of the present disclosure.

[0124] The present disclosure also relates to a computer-readable storage medium, where the computer-readable storage medium stores computer instructions, and when the instructions are executed by a processor, the methods related to any one of the embodiments as Figure 3 described are implemented.

[0125] By implementing the solutions of the above embodiments of the present disclosure, in the process of fault diagnosis of the rotating mechanism, a time-frequency diagram with high energy concentration and clear time-varying non-stationary characteristics can be generated, so that the fault-related ridge line can be accurately identified, and thus the fault of the rotating machinery can be accurately diagnosed to ensure the safe operation of the rotating machinery.

[0126] In some embodiments, the functional unit modules described above may be implemented as a general-purpose processor, a programmable logic controller (PLC), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or any suitable combination thereof for performing the functions described in this disclosure.

[0127] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above embodiments can be completed by hardware, or can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable storage medium. The storage medium mentioned above can be a read-only memory, a magnetic disk, an optical disk, or the like.

[0128] The description of the present disclosure is given for purposes of illustration and description, and is not intended to be exhaustive or to limit the present disclosure to the disclosed form. Many modifications and variations are obvious to those of ordinary skill in the art. The embodiments are chosen and described in order to best explain the principles of the present disclosure and its practical application, and to enable those of ordinary skill in the art to understand the present disclosure so as to design various embodiments with various modifications suitable for a particular purpose.

Claims

1. A fault diagnosis method, executed by a fault diagnosis device, comprising: Obtaining a vibration signal of a device under test; Calculating an envelope signal of the vibration signal; Processing the envelope information by using a first frequency-modulated wavelet transform to obtain a first time-frequency diagram, wherein a frequency modulation factor in the first frequency-modulated wavelet transform is a function of an instantaneous frequency, and a window function in the first frequency-modulated wavelet transform is a differentiable window function; Constructing a synchronous extraction operator by using the first time-frequency diagram; Obtaining a target time-frequency diagram by using the first time-frequency diagram and the synchronous extraction operator; Identifying a ridge line in the target time-frequency diagram so as to determine a fault type of the device under test according to the ridge line; Wherein, constructing the synchronous extraction operator by using the first time-frequency diagram comprises: Processing the envelope information by using a second frequency-modulated wavelet transform, a third frequency-modulated wavelet transform, a fourth frequency-modulated wavelet transform, and a fifth frequency-modulated wavelet transform respectively to obtain a second time-frequency diagram, a third time-frequency diagram, a fourth time-frequency diagram, and a fifth time-frequency diagram respectively, wherein frequency modulation factors in the second frequency-modulated wavelet transform to the fifth frequency-modulated wavelet transform are the same as the frequency modulation factor in the first frequency-modulated wavelet transform, a window function in the second frequency-modulated wavelet transform is a first derivative g′ of a window function g in the first frequency-modulated wavelet transform, a window function in the third frequency-modulated wavelet transform is a second derivative g′′ of the window function g, a window function in the fourth frequency-modulated wavelet transform is a product tg of the window function g and time t, and a window function in the fifth frequency-modulated wavelet transform is a product tg′ of the window function g′ and time t; Multiplying the second time-frequency diagram and the fifth time-frequency diagram to obtain a first product; multiplying the third time-frequency diagram and the fourth time-frequency diagram to obtain a second product; multiplying the second time-frequency diagram and the fourth time-frequency diagram to obtain a third product; multiplying the first time-frequency diagram and the fifth time-frequency diagram to obtain a fourth product; subtracting the second product from the first product to obtain a first difference; subtracting the fourth product from the third product to obtain a second difference; obtaining an instantaneous frequency estimation operator according to an imaginary part of a ratio of the first difference to the second difference and the instantaneous frequency; Constructing the synchronous extraction operator according to the first time-frequency diagram and the instantaneous frequency estimation operator, wherein when a first condition and a second condition are both satisfied, the synchronous extraction operator is 1, wherein the first condition is that an amplitude of the first time-frequency diagram is greater than a first threshold η, the second condition is that an amplitude of the imaginary part of the ratio is less than a second threshold ξ, the first threshold η and the second threshold ξ are non-negative values, the first threshold η is determined by a signal point number M and a noise variance σ, and the second threshold ξ is less than a frequency resolution.

2. The method according to claim 1, wherein, The frequency modulation factor is κw, w is the instantaneous frequency, and κ is a frequency parameter.

3. The method according to claim 2, wherein, The frequency parameter κ is the tangent value of the angular parameter θ.

4. The method according to claim 3, wherein, An optimal value θ* of the angle parameter θ is: Among them, is the time-frequency diagram when the angle parameter θ is θ n , and is the kurtosis value in the direction of the instantaneous frequency, indicating the angle parameter used for the time-frequency diagram with the maximum kurtosis value.

5. The method according to claim 1, wherein, The instantaneous frequency estimation operator is the sum of the imaginary part of the ratio and the instantaneous frequency.

6. The method according to claim 1, wherein when the first condition or the second condition is not satisfied, the synchronization extraction operator is 0.

7. The method according to claim 1, wherein The first threshold A is a preset parameter.

8. The method according to claim 1, further comprising: determining the noise variance σ by using the first time-frequency diagram and the median of the amplitudes of the first time-frequency diagram.

9. The method according to claim 8, wherein Determining the noise variance σ by using the first time-frequency diagram and the median of the amplitudes of the first time-frequency diagram includes: subtracting the median of the amplitudes of the first time-frequency diagram from the first time-frequency diagram to obtain a time-frequency diagram to be processed; taking the ratio of the median of the amplitudes of the time-frequency diagram to be processed to a preset parameter as the noise variance σ.

10. The method according to claim 1, wherein the second threshold ξ is one-half of the frequency resolution.

11. The method according to claim 1, wherein the target time-frequency diagram is the product of the first time-frequency diagram and the synchronization extraction operator.

12. The method according to any one of claims 1-11, wherein Calculating the envelope signal of the vibration signal includes: performing a Hilbert transform on the vibration signal to obtain a transform result; obtaining the envelope signal according to the vibration signal and the transform result.

13. The method according to claim 12, wherein the envelope signal x is: where s is the vibration signal and Hilbert() is the Hilbert transform function.

14. A fault diagnosis device, comprising: a first processing module configured to acquire a vibration signal of a device under test and calculate an envelope signal of the vibration signal; a second processing module configured to process the envelope information by using a first frequency-modulated wavelet transform to obtain a first time-frequency diagram, wherein the frequency modulation factor in the first frequency-modulated wavelet transform is a function of the instantaneous frequency, and the window function in the first frequency-modulated wavelet transform is a differentiable window function; A third processing module, configured to construct a synchronization extraction operator by using the first time-frequency diagram, and obtain a target time-frequency diagram by using the first time-frequency diagram and the synchronization extraction operator, wherein the envelope information is processed by using a second frequency-modulated wavelet transform, a third frequency-modulated wavelet transform, a fourth frequency-modulated wavelet transform, and a fifth frequency-modulated wavelet transform respectively to obtain a second time-frequency diagram, a third time-frequency diagram, a fourth time-frequency diagram, and a fifth time-frequency diagram respectively, wherein the frequency modulation factors in the second to fifth frequency-modulated wavelet transforms are the same as the frequency modulation factor of the first frequency-modulated wavelet transform, the window function in the second frequency-modulated wavelet transform is the first derivative g′ of the window function g of the first frequency-modulated wavelet transform, the window function in the third frequency-modulated wavelet transform is the second derivative g″ of the window function g, the window function in the fourth frequency-modulated wavelet transform is the product tg of the window function g and time t, and the window function in the fifth frequency-modulated wavelet transform is the product tg′ of the window function g′ and time t; multiplying the second time-frequency diagram and the fifth time-frequency diagram to obtain a first product; multiplying the third time-frequency diagram and the fourth time-frequency diagram to obtain a second product; multiplying the second time-frequency diagram and the fourth time-frequency diagram to obtain a third product; multiplying the first time-frequency diagram and the fifth time-frequency diagram to obtain a fourth product; subtracting the second product from the first product to obtain a first difference; subtracting the fourth product from the third product to obtain a second difference; obtaining an instantaneous frequency estimation operator according to the imaginary part of the ratio of the first difference to the second difference and the instantaneous frequency; constructing the synchronization extraction operator according to the first time-frequency diagram and the instantaneous frequency estimation operator, wherein when a first condition and a second condition are satisfied simultaneously, the synchronization extraction operator is 1, wherein the first condition is that the amplitude of the first time-frequency diagram is greater than a first threshold η, the second condition is that the amplitude of the imaginary part of the ratio is less than a second threshold ξ, the first threshold η and the second threshold ξ are non-negative values, the first threshold η is determined by the number of signal points M and the noise variance σ, and the second threshold ξ is less than the frequency resolution; A fourth processing module, configured to identify a ridge line in the target time-frequency diagram so as to determine a fault type of the device under test according to the ridge line.

15. A fault diagnosis device, comprising: A memory, configured to store instructions; A processor, coupled to the memory, the processor being configured to execute the method according to any one of claims 1-13 based on the instructions stored in the memory.

16. A computer-readable storage medium, wherein, A computer-readable storage medium stores computer instructions, and when the instructions are executed by a processor, the method according to any one of claims 1-13 is implemented.

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