A denoising method of construction machinery transmission load signal based on wavelet analysis
A technology of construction machinery and wavelet analysis, applied in the field of signal processing, can solve the problems of inaccurate denoising and large amount of calculation, and achieve the effect of simplifying the denoising process, simple accuracy and easy extraction
Active Publication Date: 2018-03-16
BEIJING INSTITUTE OF TECHNOLOGYGY
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It can be seen that the denoising method in the prior art has a large amount of calculation and the denoising is not accurate enough
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[0036] The present invention provides a method for denoising construction machinery transmission signals based on wavelet analysis. Its core idea is: based on the wavelet analysis theory combined with the characteristics of the vehicle transmission system, the load signal denoising process is carried out in a manner of dividing working conditions. During the same data collection process, the working conditions of the on-board test system, the external environment and other interference factors are basically the same, and the noise characteristics are the same during the same data collection process. In addition to idling conditions and other complex conditions under load, they are called random conditions, so that the denoising experience of idling conditions can provide a reference for the denoising of random conditions, so that the denoising process can be based on evidence, so as to achieve a good denoising effect.
[0037] The present invention will be described in detail ...
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The invention discloses a method for denoising construction machinery transmission signals based on wavelet analysis. Based on the theory of wavelet analysis, the vehicle running state is divided into idling working condition and random working condition, so that the denoising experience of idling working condition is random working condition. Provide a reference for the denoising of the situation. First, under the idle condition, the load data is obtained and the wavelet coefficients and thresholds on each decomposition scale are calculated, the threshold quantization is performed on the wavelet coefficients with the threshold value, the wavelet coefficients smaller than the threshold value are removed, and the remaining wavelet coefficients are retained; the retained wavelet coefficients are used to Coefficients carry out one-dimensional wavelet reconstruction on the load data to complete the denoising process. Secondly, under random working conditions, the load data is obtained and the wavelet coefficients on each decomposition scale are calculated, and the threshold value in the idling condition is used to perform threshold quantization processing on the wavelet coefficients, and the wavelet coefficients smaller than the threshold are removed, and the remaining wavelet coefficients are retained; The retained wavelet coefficients are used to perform one-dimensional wavelet reconstruction on the load data to complete the denoising process.
Description
technical field [0001] The invention relates to the field of signal processing, in particular to a method for denoising engineering machinery transmission signals based on wavelet analysis. Background technique [0002] Load spectrum is the basis of fatigue life estimation and reliability analysis of traditional system components. Due to the complex driving conditions, harsh driving environment and special purposes of construction machinery, the loads it bears are mostly random loads, such as the vibration generated during the operation of the engine, the impact of various components of the transmission system from external loads such as roads, and the transmission process. The torsional additional load generated in the transmission, the shock and vibration generated during the shifting process, etc., these loads are mostly medium and high frequency signal loads. Since the components of the transmission system are subjected to random additional loads for a long time, they a...
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IPC IPC(8): G06F19/00
Inventor 席军强张国鑫刘海鸥陈慧岩赵亦农
Owner BEIJING INSTITUTE OF TECHNOLOGYGY