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The Research of Diagnosis Instrument for Railway based on Frequency Spectral Analysis and Fuzzy Neur

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Tutor: HuangHanZhou HanGuangSheng
School: Beijing University of Technology
Course: Control Theory and Engineering
Keywords: Diagnosis , spectrum analysis , fuzzy neural network , track disease
CLC: TP183
Type: Master's thesis
Year:  2000
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Abstract:
Industrial production since the 20th century , more and more intensive and continuous, precision, they made ??many requests of industrial equipment , which is a very important point : how to ensure that the equipment stability ; equipment failure when , how confirmed the source of the fault and troubleshooting as soon as possible . This is the actual fault diagnosis theory and industrial background . After the 19th century , scientific development by leaps and bounds , and at the same time , the production of industrial equipment reached an unprecedented height and accuracy . Both stimulate and promote the development of fault diagnostic technology , which is the theoretical and technical background of the development of the theory of fault diagnosis . Looking at the history of diagnostic technology development , the huge economic benefits generated by the fault diagnosis , is the direct cause of it by the national industrial sector attention . In modern society , the railway has a unique and irreplaceable role . Megacities of the subway , in the long-distance transport of bulk goods , are inseparable from the railway . When the railway is not working properly , that the railroad failed ( professional , called \At this point, you can use the the track inspection instrument , and the track inspection car to troubleshooting . The object of this thesis is based on spectral analysis and fuzzy neural network to track disease diagnostic . The first chapter describes the overview of the development of fault diagnosis . The second chapter tells of Track Irregularities various manifestations of the source of the fault . Chapter 3 describes the horizontal track inspection overview . Chapters IV and V tells spectrum analysis and fuzzy theory , neural networks , background knowledge , and the topic is how to use this knowledge to solve problems , and therefore is a core part of this paper . Chapter VI from the hardware point of view about how to track inspection instrument .
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