Dissertation > Industrial Technology > Machinery and Instrument Industry > Machinery Manufacturing Technology > Flexible manufacturing systems and flexible manufacturing cell > Fault diagnosis and maintenance

Optimization of the Matching Pursuit Algorithm and Its Application on Fault Diagnosis for Rolling Element Bearing

Author TaoShaoFei
Tutor ChenJin
School Shanghai Jiaotong University
Course Mechanical Design and Theory
Keywords Rolling Element Bearing Fault Diagnosis Virtual Instrument LabVIEW Data Acquisition MP
CLC TH165.3
Type Master's thesis
Year 2012
Downloads 179
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Development of Information Technology drives industries towards continuous, high-speed and large-load. On one hand, the development lowers product cost, improves efficiency, speed up product design, manufacturing and service. On the other hand, the development needs higher level design, manufacturing, and the ability of work and maintenance. Furthermore, each enterprise has to cut down the fault time and lengthen the effective life cycle to strengthen their marketing competition.A denoising method based on Matching Pursuit (MP) not only can denoise successfully,but also will not damage the significant wave of the signal,and need not foreknow the statistical properties of the signal and noise,so it has an important value on the fault diagnosis field. The most shortages of Matching Pursuit is it need lots of computer internal storage and has very big calculation quantity. In order to use the MP successfully in fault diagnose field, we need to do some work in the optimization of the MP Algorithm. Considering all these,a study on f the optimization of the MP Algorithm has been done, and then use it on fault diagnosis for rolling element bearing. By these way, we can maintain and repair the machine or equipment that has a fault on the rolling element bearing immediately. Therefore, the fault time will be shortened and the effective life lengthened. The main contents of this dissertation are as follows:(1) In order to improve the MP calculation speed and reduce the use of computer internal storage,we use the Intelligent optimization algorithm to find the best atom in the signal sparse decomposition with MP. The Intelligent optimization algorithm is called Differential Evolution algorithms.(2) Use the MP method to denoise the Machinery fault signal, and then analyze the denoising signal with Amplitude Spectrum Analysis and Envelope Spectrum Analysis and STFT, WVD, CWD Analysis. By these method,we can have an upstanding capability and high reliability on fault diagnosis.(3) Acquire rolling element bearing vibration signal on the bearing test rig,and then analyze the signal with the MP denoising method. The result shows that the denoising method based on MP is reliable and effective.(4) The Machinery fault diagnosis system based on MP is developed under the platform of LabVIEW8.6.1,it includes data acquisition module,history data query module,analysis of the original signal model,MP model,and reports to generate model and so on. In the system,Microsoft Access is used to set up a database,NI-DAQmx is used to acquisition data,Database Connectivity Toolkit is used to store data to database or query data from database, and MathScript node is used to program for MP. The system has a good performance in the fault diagnosis, and it is successful in the use of MP on the fault diagnosis for rolling element bearing

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