Data processing method of signal random average spectrums

Abstract

The invention discloses a data processing method of signal random average spectrums. The method comprises the steps that according to mechanical vibration original time-domain signals collected by a vibration sensor, n sections of signals which are randomly and continuously extracted from the original time-domain signals are used as sample signals, and the lengths of the n sections of sample signals are the same; Fourier transformation is respectively carried out on the n sections of sample signals, and a frequency spectrum of each section of sample signal is obtained; average value calculation is carried out on each spectrum line amplitude of the obtained frequency spectrums of the n sections of sample signals, and the average value of each spectrum line amplitude is obtained, namely the random average spectrums of the n sections of sample signals. According to the data processing method of the signal random average spectrums, the noise intensity in the signal frequency spectrums can be remarkably reduced, the data processing process is simple and easy to operate, the noise intensity can be effectively reduced, and the signal to noise ratio of the signals is improved.

Description

technical field [0001] The invention relates to a data processing method of a signal random average spectrum, which is especially suitable for pre-processing the vibration signal and reducing the noise intensity in the frequency spectrum of the vibration signal. Background technique [0002] Vibration detection is the most commonly used method in fault diagnosis of mechanical systems. The vibration signals of mechanical components under normal working conditions and fault conditions often contain different information, and the mechanical fault diagnosis based on vibration signals can be realized through signal analysis technology. However, vibration signals in actual situations often contain strong noise, and environmental noise and other interfering vibrations often have an impact on the detection results. Only by reducing the noise intensity in the signal through relevant signal processing methods can the vibration signal be effectively detected. for follow-up analysis. ...

AI Technical Summary

Problems solved by technology

However, vibration signals in actual situations often contain strong noise, and environmental noise and other interfering vibrations often have an impact on the detection results. Only by reducing the noise intensity in the signal through relevant signal processing methods can the vibration signal be effectively detected. for follow-up analysis

[0003] At present, for the noise contained in the signal, one method is to process it through a filter. This method is complicated to deal with, and may destroy useful information in the signal while eliminating the noise; another method is to divide the original signal into Several segments are processed and averaged for each segment. Due to the limited length of the original signal and the small number of samples, this method cannot effectively reduce the noise intensity in the signal.

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