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Typical Fault Diagnosis Method Research on Rolling Bearing Based on Walsh Transform

Author: XiaoJie
Tutor: LiuShuLin
School: Daqing Petroleum Institute
Course: Chemical Process Equipment
Keywords: Rolling bearings Walsh power spectrum Fourier power spectrum Fault Feature Extraction
CLC: TH133.33
Type: Master's thesis
Year: 2010
Downloads: 65
Quote: 0
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Abstract


Rotating equipment is extremely broad field of applications such as oil, petrochemical , light industry , and transportation of large equipment . Rolling is most commonly used in rotating machinery , but also one of the most easily damaged parts . According to statistics , about 30% of the rotating equipment failure is caused due to the rolling bearing damage can be seen , the rolling bearing running state whether normal often directly affect the performance of the whole machine , so the research roller bearing fault diagnosis technology has very real significance. Roller bearing fault diagnosis , most important , the most critical , is also one of the most difficult problems is a signal fault feature extraction, it is related to the accuracy of fault diagnosis and early failure prediction reliability . This article by reading a lot of literature , have a more comprehensive understanding of the status quo and development trend of the rolling bearing vibration detection and fault diagnosis technology based on proposed based the Walsh transform the Roller Bearing typical fault diagnosis method , the method can accurate extract rolling bearing fault features . This paper studies two aspects : First , with the traditional method of frequency domain analysis , Fourier power spectrum simulation comparative study confirmed the the Walsh power spectral processing sinusoidal signal , noisy signal and mutation signal has advantages . Walsh power spectrum sensitivity in weak signal extraction is better than the Fourier power spectrum of the noise signal on Walsh power spectrum is smaller , its strong resistance to noise in the Fourier power spectrum . Walsh power spectrum stronger than the Fourier power spectrum signal processing mutations . Second Walsh power spectrum and Fourier power spectrum for Machine rolling body , the inner ring and the outer ring of three fault vibration data and trouble-free vibration data , the results show that the Walsh power spectrum than in the identification of rolling bearing fault signal Fourier power spectrum more efficiently , highlighting the advantages of the characteristic frequency and signal . Confirmed fault diagnosis method based on the Walsh transform , more accurate to extract fault vibration signal failure characteristics , and provide a new diagnostic method for rolling bearing fault .

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CLC: > Industrial Technology > Machinery and Instrument Industry > Mechanical parts and gear > Moving parts > Bearing > Rolling
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