Wheelset bearing fault detection using morphological signal and image analysis

Abstract This paper presents a digital low computation detection method for signal nonlinear distortion. After presetting ADC sampling rate and completing data sampling, the low sampling rate data extracted from the sampling data complete the autocorrelation analysis to correct and calculate the accurate fundamental frequency. According to the relationship between the fundamental frequency and the sampling rate, the complete periodic segment data of the signal cutting out from the sampling data carry out the digital quadrature detection operation to obtain the value of each harmonic component and nonlinear distortion. Experiments show that the calculation of this method is less than that of FFT spectrum analysis method when measuring the THD lower than 15 order. When calculating the 15-order THD at 1024 points, the calculation time is reduced by 44.26%. Moreover, the digital quadrature detection method has high measurement accuracy with less than 0.6% error of detecting 5-order THD. 

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A low computation detection method of signal nonlinear distortion based on digital quadrature detection principle

A way (involving the use of line delta functions) of formulating and depicting convolutions, autocorrelation and cross correlation is discussed.

On the formulation of convolution, autocorrelation and cross correlation

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On the formulation of convolution, autocorrelation and cross correlation