Cold test test denoising method and system based on wavelet threshold
By improving the wavelet threshold function to reduce noise in the vibration signal of a diesel engine during cold testing, the problems of signal oscillation and distortion were solved, the noise reduction effect was improved, and the accuracy of the signal was ensured.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHANDONG UNIV
- Filing Date
- 2023-05-30
- Publication Date
- 2026-07-03
Smart Images
Figure CN119066325B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of engine testing technology, specifically to a method and system for noise reduction in cold testing based on wavelet thresholding. Background Technology
[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.
[0003] Diesel engine cold testing involves rotating the diesel engine using an electric motor and collecting various data from sensors to determine the engine's assembly condition. Because cold testing does not require ignition testing, it is less polluting, lower in cost, and less time-consuming. Diesel engine cold testing includes various tests such as high-speed vibration testing, intake air testing, and exhaust pressure testing. In particular, the vibration signals acquired during high-speed vibration testing are often accompanied by noise, which reduces signal accuracy and can easily lead to misjudgments in subsequent analysis. Therefore, noise reduction of the vibration signals is necessary.
[0004] For noise reduction of vibration signals during cold testing, existing technologies employ methods such as empirical mode decomposition, variational mode decomposition, and wavelet transform. Wavelet transform uses hard and soft thresholding to process the original signal to obtain the noise-reduced vibration signal. However, because the hard thresholding function itself is not continuous, it may cause oscillations in the reconstructed signal. While the soft thresholding function is continuous, the estimated wavelet coefficients outside the threshold range deviate from the original wavelet coefficients, which may distort the reconstructed signal.
[0005] Therefore, the existing technology of using wavelet transform for noise reduction of vibration signals is not ideal. The noise-reduced signal is prone to oscillation and distortion, which is not conducive to subsequent vibration analysis. Summary of the Invention
[0006] To address the technical problems existing in the background art, the present invention provides a cold test noise reduction method and system based on wavelet threshold. By improving the threshold function, the wavelet coefficients within the threshold range shrink to zero, while the wavelet coefficients outside the threshold remain unchanged. Furthermore, the threshold function itself has continuity, thereby solving the existing oscillation and distortion problems.
[0007] To achieve the above objectives, the present invention adopts the following technical solution:
[0008] The first aspect of the present invention provides a cold test noise reduction method based on wavelet thresholding, comprising the following steps:
[0009] The vibration signal of the diesel engine during cold testing was acquired. Based on the selected wavelet basis function and the number of decomposition levels, the vibration parameters in the vibration signal were decomposed by wavelet to obtain the wavelet coefficients.
[0010] Based on the threshold function, wavelet reconstruction is performed on the vibration parameters to obtain the noise-reduced cold test vibration parameters, so that the wavelet coefficients within the threshold range shrink to zero, while the wavelet coefficients outside the threshold remain unchanged.
[0011] The acquired cold test vibration signal of the diesel engine was processed using the noise-reduced cold test vibration parameters to obtain the noise-reduced cold test vibration signal.
[0012] A second aspect of the present invention provides a system for implementing the above-described method, comprising:
[0013] The data acquisition module is configured to: construct a vibration parameter database based on the acquired diesel engine cold test vibration signals;
[0014] The wavelet decomposition module is configured to perform wavelet decomposition on the vibration parameters in the database based on the selected wavelet basis functions and the number of decomposition levels to obtain wavelet coefficients.
[0015] The wavelet reconstruction module is configured to: reconstruct the vibration parameters based on the threshold function to obtain the noise-reduced cold test vibration parameters, specifically: shrink the wavelet coefficients within the threshold range to zero, and keep the wavelet coefficients outside the threshold unchanged.
[0016] The noise reduction signal output module is configured to process the acquired diesel engine cold test vibration signal using the noise-reduced cold test vibration parameters to obtain the noise-reduced cold test vibration signal.
[0017] A third aspect of the present invention provides a computer-readable storage medium.
[0018] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the wavelet threshold-based cold test noise reduction method described above.
[0019] A fourth aspect of the present invention provides a computer device.
[0020] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the wavelet threshold-based cold test noise reduction method described above.
[0021] Compared with existing technologies, one or more of the above technical solutions have the following beneficial effects:
[0022] By improving the threshold function, wavelet coefficients within the threshold range shrink towards zero and smoothly transition at the threshold, thus overcoming the discontinuity of the hard threshold function at the threshold. For the interval outside the threshold, as the wavelet coefficients increase, the deviation between the estimated and original wavelet coefficients gradually decreases, thereby keeping the wavelet coefficients as constant as possible. This overcomes the fixed deviation of the soft threshold function, making the improved threshold function itself continuous. Based on the improved threshold function, wavelet reconstruction is performed on the original data to obtain denoised cold test vibration parameter data. Using the denoised cold test vibration parameter data, the acquired diesel engine cold test vibration signal is processed to obtain a denoised cold test vibration signal, solving the problems of signal oscillation and distortion and improving the denoising effect. Attached Figure Description
[0023] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.
[0024] Figure 1 This is a schematic diagram of a cold test noise reduction process based on wavelet threshold provided by one or more embodiments of the present invention. Detailed Implementation
[0025] The present invention will be further described below with reference to the accompanying drawings and embodiments.
[0026] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.
[0027] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.
[0028] As described in the background section, the noise reduction effect of wavelet transform on vibration signals is not ideal. The noise-reduced signal is prone to oscillation and distortion, which is not conducive to subsequent vibration analysis.
[0029] Therefore, the following embodiments present a wavelet threshold-based denoising method and system for cold test. By improving the threshold function, wavelet coefficients within the threshold range shrink to zero, while wavelet coefficients outside the threshold remain unchanged. Furthermore, the threshold function itself possesses continuity, thus overcoming the shortcomings of traditional threshold selection methods. Based on the improved threshold function, wavelet reconstruction is performed on the original data to obtain denoised cold test vibration parameter data. Using this denoised cold test vibration parameter data, the acquired diesel engine cold test vibration signal is processed to obtain a denoised cold test vibration signal, solving the problems of signal oscillation and distortion, and improving the denoising effect.
[0030] Example 1:
[0031] like Figure 1 As shown, the cold test noise reduction method based on wavelet thresholding includes the following steps:
[0032] The vibration signal of the diesel engine during cold testing can be obtained. The vibration signal can be the high-speed cylinder head vibration signal or the vibration signal obtained from other parts. The vibration signal of the diesel engine is obtained through a vibration sensor under the cold test environment.
[0033] A vibration parameter database was constructed based on the acquired diesel engine cold test vibration signals.
[0034] By selecting appropriate wavelet basis functions and decomposition levels, wavelet decomposition is performed on the data in the vibration parameter database.
[0035] Regarding the selection of wavelet basis functions, different wavelet basis functions yield different results when processing signals. In this embodiment, any one of the following can be selected: Meyer wavelet, Haar wavelet, Morlet wavelet, dbN wavelet system, colfN wavelet system, and SymN wavelet system. In actual signal processing, selecting wavelet basis functions according to different signal characteristics can achieve the best noise reduction effect. The specific selection process is well known in the art.
[0036] Regarding the number of decomposition layers, in wavelet decomposition, selecting too many decomposition layers will affect the signal reconstruction effect and lead to signal distortion, while selecting too few decomposition layers will result in incomplete noise removal. This embodiment selects a decomposition layer of 3-5 layers.
[0037] In this embodiment, wavelet transform is used to decompose the signal and the corresponding wavelet coefficients for each decomposition layer are calculated. The signal energy is mainly concentrated in some relatively large wavelet coefficients in the wavelet domain, while the noise energy is distributed in a large number of relatively small expansion coefficients in the wavelet domain after wavelet decomposition. By setting the coefficients with smaller amplitudes to zero and retaining the larger coefficients, the signal is reconstructed to reduce noise.
[0038] Regarding the selection of the threshold, given that the wavelet coefficients corresponding to the noise are small and follow a Gaussian distribution, noise elimination can be achieved by selecting a threshold and setting the wavelet coefficients within that range to zero. Commonly used thresholds include the unbiased risk estimation function (rigrsure), the fixed threshold (sqtwolog), the heuristic threshold (heursure), and the minimax threshold (minimaxi).
[0039] In this embodiment, wavelet reconstruction is performed on the vibration parameters based on a threshold function to obtain the denoised cold test vibration parameters, specifically:
[0040] Based on the threshold function, the wavelet coefficients within the threshold range shrink towards zero and transition smoothly at the threshold, thus improving the discontinuity of the hard threshold function at the threshold. For the interval outside the threshold, as the wavelet coefficients increase, the deviation between the predicted wavelet coefficients and the original wavelet coefficients gradually decreases, thereby keeping the wavelet coefficients as constant as possible. This improves the fixed deviation of the soft threshold function, making the improved threshold function itself continuous, as shown in the following equation:
[0041]
[0042] In the formula, tanh is the hyperbolic tangent function, b is the adjustment factor, h1 and h2 are correction coefficients with values ranging from 0.8 to 1.2, and T is the threshold.
[0043] After wavelet reconstruction based on a threshold function, the denoised cold test vibration parameters are obtained, and the vibration parameter database is updated. Using the denoised cold test vibration parameter data, the acquired diesel engine cold test vibration signal is processed to obtain the denoised cold test vibration signal. This process forms a wavelet threshold-based cold test denoising method, which solves the problems of signal oscillation and distortion, and improves the denoising effect.
[0044] Example 2:
[0045] A system for implementing the above method includes:
[0046] The data acquisition module is configured to: construct a vibration parameter database based on the acquired diesel engine cold test vibration signals;
[0047] The wavelet decomposition module is configured to perform wavelet decomposition on the vibration parameters in the database based on the selected wavelet basis functions and the number of decomposition levels to obtain wavelet coefficients.
[0048] The wavelet reconstruction module is configured to: reconstruct the vibration parameters based on the threshold function to obtain the noise-reduced cold test vibration parameters, specifically: shrink the wavelet coefficients within the threshold range to zero, and keep the wavelet coefficients outside the threshold unchanged.
[0049] The noise reduction signal output module is configured to process the acquired diesel engine cold test vibration signal using the noise-reduced cold test vibration parameters to obtain the noise-reduced cold test vibration signal.
[0050] Example 3:
[0051] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the wavelet threshold-based cold test noise reduction method described in Embodiment 1 above.
[0052] Example 4:
[0053] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the wavelet threshold-based cold test noise reduction method described in Embodiment 1 above.
[0054] The steps or modules involved in Embodiments 2 to 4 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.
[0055] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.
Claims
1. A cold test noise reduction method based on wavelet thresholding, characterized in that, Includes the following steps: The vibration signal of the diesel engine during cold testing was acquired. Based on the selected wavelet basis function and the number of decomposition levels, the vibration parameters in the vibration signal were decomposed by wavelet to obtain the wavelet coefficients. Based on the threshold function, wavelet reconstruction is performed on the vibration parameters to obtain the noise-reduced cold test vibration parameters, so that the wavelet coefficients within the threshold range shrink to zero, while the wavelet coefficients outside the threshold remain unchanged. The acquired cold test vibration signal of the diesel engine was processed using the noise-reduced cold test vibration parameters to obtain the noise-reduced cold test vibration signal. The threshold function is shown in the following formula: ； In the formula, It is the hyperbolic tangent function. As a regulating factor, , This is a correction factor, with a value ranging from 0.8 to 1.
2. The threshold value is used.
2. The wavelet threshold-based cold test noise reduction method as described in claim 1, characterized in that, The wavelet basis functions include at least one of the following: Meyer wavelet, Haar wavelet, Morlet wavelet, dbN wavelet system, colfN wavelet system, and SymN wavelet system.
3. The wavelet threshold-based cold test noise reduction method as described in claim 2, characterized in that, The wavelet basis functions are selected according to different signal characteristics to obtain the desired noise reduction effect.
4. The cold test noise reduction method based on wavelet threshold as described in claim 1, characterized in that, The number of decomposition layers is 3-5.
5. The cold test noise reduction method based on wavelet threshold as described in claim 1, characterized in that, A vibration parameter database is constructed based on the acquired diesel engine cold test vibration signal, and wavelet decomposition is performed on the vibration parameters in the database.
6. The cold test noise reduction method based on wavelet threshold as described in claim 1, characterized in that, After wavelet reconstruction based on the threshold function, the noise-reduced cold test vibration parameters are obtained and the vibration parameter database is updated. The noise-reduced cold test vibration parameter data is used to process the acquired diesel engine cold test vibration signal to obtain the noise-reduced cold test vibration signal.
7. A cold test noise reduction system based on wavelet thresholding, characterized in that, include: The data acquisition module is configured to acquire vibration signals during cold testing of the diesel engine. The wavelet decomposition module is configured to perform wavelet decomposition on the vibration parameters in the vibration signal according to the selected wavelet basis function and the number of decomposition levels to obtain wavelet coefficients. The wavelet reconstruction module is configured to: reconstruct the vibration parameters based on the threshold function to obtain the noise-reduced cold test vibration parameters, so that the wavelet coefficients within the threshold range shrink to zero, and the wavelet coefficients outside the threshold remain unchanged; The noise reduction signal output module is configured to process the acquired diesel engine cold test vibration signal using the noise-reduced cold test vibration parameters to obtain the noise-reduced cold test vibration signal. The threshold function is shown in the following formula: ； In the formula, It is the hyperbolic tangent function. As a regulating factor, , This is a correction factor, with a value ranging from 0.8 to 1.
2. The threshold value is used.
8. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the wavelet threshold-based cold test noise reduction method as described in any one of claims 1-6.
9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the wavelet threshold-based cold test noise reduction method as described in any one of claims 1-6.