A Fault Feature Extraction Method for Rotating Machinery Without Tachometer at Variable Speed

Abstract

This application relates to a method for extracting fault features of rotating machinery without a tachometer at variable speeds. First, the narrow-band filtering method is used to remove the interference frequency components and most of the random noise in the vibration data, and then the filtered The vibration data is divided into multiple segments, and then the frequency or harmonic frequency of each short period of vibration data is extracted by using the matching tracking method, and finally the instantaneous frequency or harmonic frequency of the entire period of the vibration data is synthesized. According to the extracted instantaneous frequency or instantaneous frequency harmonic frequency, the original vibration data is tracked and analyzed to realize the fault feature extraction of variable speed machinery without a tachometer. The frequency accuracy of the instantaneous frequency conversion or instantaneous frequency conversion harmonic extracted by the method designed in the present invention is high, and in the case of small random noise interference, the frequency accuracy of the extracted instantaneous frequency conversion or instantaneous frequency conversion harmonic frequency is close to the measurement accuracy of the tachometer , which can realize accurate extraction of fault features of variable speed rotating machinery.

Description

technical field [0001] The present application relates to a method for extracting fault features of rotating machinery without a tachometer at variable speeds, which is applicable to the technical field of early warning of mechanical faults. Background technique [0002] The variable speed condition is a common condition of rotating machinery in industrial production. For example, the speed of the three-phase asynchronous motor will fluctuate slightly after the load changes, the variable speed operation condition of the wind turbine, and the startup and shutdown of the steam turbine Situation etc. At present, vibration data analysis is the main means to identify the fault characteristics of rotating machinery. Through the analysis of vibration signals of rotating machinery, most of the mechanical component faults of rotating machinery can be identified, such as bearing wear, rotor imbalance, rotor misalignment, and rotor dynamic and static friction. , loose support, gear fa...

AI Technical Summary

Problems solved by technology

The disadvantage is that it depends on the tachometer. This method will fail when there is no tachometer or the speed pulse data is abnormal.

The advantage of the second method is that it does not rely on the tachometer, but this method is limited by the high time domain resolution and frequency domain resolution and cannot have both, resulting in inaccurate speed extraction results.

At this time, it is impossible to extract the instantaneous frequency with higher precision by using the spectrum correction method.

Therefore, the method of spectral correction is used to extract the instantaneous frequency conversion, which essentially has the problem that the time resolution and frequency resolution cannot be improved at the same time.

[0005] It can be seen that the existing fault feature extraction methods for variable speed rotating machinery without tachometers have certain deficiencies and cannot meet the actual needs.

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