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The Research and Development of Rolling Bearing Fault Diagnosis System Based on DSP

Author: LiJing
Tutor: YangBaoQing
School: Dalian Jiaotong University
Course: Mechanical and Electronic Engineering
Keywords: Vehicles rolling bearings Fault Diagnosis DSP The wavelet analysis Mallat algorithm Power spectral analysis
CLC: TH133.33
Type: Master's thesis
Year: 2008
Downloads: 130
Quote: 3
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Abstract


Rolling Bearing Fault Diagnosis is through observation , analysis and processing of the signal can reflect the state of the bearings work to identify the state of the bearing to ensure the bearing to withstand a certain load , reliable and effective functioning work environment to a certain speed and a certain amount of work during the next operation. The complete process of rolling bearing fault diagnosis includes signal measurements taken , feature extraction , fault diagnosis of three parts . Signal measured take : This part is the key to the whole course of the study , but also difficult part , directly related to the rolling bearing fault diagnosis accuracy . Through theoretical analysis and comparison , using the sound level meter acquisition Rolling condition signal , under the conditions of the Nyquist sampling theorem , the signal sampling through WT6701PA board A / D , based on the DSP internal memory space is limited , the use of CCS 's real-time data tracking , DSP external interrupt is triggered by the C programming language , and start direct memory access to the DMA , real-time transmission of sampled data stored in a data file to the host . The feature extraction process : that the sampling signal analysis process . With the development of wavelet analysis and spectral analysis technology , creating a new field of frequency domain analysis methods used to detect and diagnosis of bearing failure . Wavelet transform is a time - scale analysis , corresponding to the scale and frequency , and therefore is a kind of time-frequency analysis ; wavelet transform has the following characteristics : high time resolution in the high frequency range , high frequency resolution in the low frequency range ; -Mallat algorithm ; fast algorithm using discrete wavelet transform can decompose the signal into various scales . The key to this analysis method must know the sampling frequency variation Mallat algorithm . Based on the the unique DSP internal structure and programmability , making the DSP as the core of the high-speed real-time processing system that can quickly handle large quantities of data , but also real-time signal processing , so this topic selection programmable TMS320C6701DSP chip to achieve the Rolling signal wavelet transform . Sampled signal spectrum analysis via Matlab . By contrast, the characteristics of the completion signal is extracted. Fault diagnosis : analysis and comparison of the of multiple rolling bearing signal , as well as the calculation of the characteristic frequency of rolling bearing fault diagnosis of rolling bearing failure .

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