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Risk model based on immune algorithm and its application in motor fault diagnosis research

Author: JinYaChao
Tutor: ChenQiang
School: Jiangxi University of Technology
Course: Control Theory and Control Engineering
Keywords: Artificial Immune System Immune Algorithm Danger Theory Fault Diagnosis Anomaly Detection
CLC: TM307.1
Type: Master's thesis
Year: 2009
Downloads: 59
Quote: 0
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Abstract


Biological immune system is a highly parallel adaptive information learning system,which can identify and remove the antigenic eye winkers in vading the body. This system can learn, remember and adjust adaptively to keep the stabilization inside the body,but it has some lackness itself. With the further research and achievements made in Artificial Immune System. these years, a newly-introduced immune system, the Danger Theory, has challenged against the basic theories of modern immune based on the traditional SNS. It has broken the concept of self tolerance and smashed the trammels of those traditional theories by changing the way that we looked at the concept of space and get results. Therefore, this newly introduced immune theory has started a brand- new vision for the research of AIS.Danger signals introduced by Danger Theory are able to demonstrate and process a wealth of data effectively. The traditional immune algorithm is not perfect in its application, such as its high computation complexity态low self-adaptability and so on,Danger Theory is introduced, from which all the problems have been solved and the feasibility of their application into anomaly detection is analyzed. Inspired by Danger Theory and based on the previous theories, the algorithms based on Danger Theory and its application into mechanical equipment has been studied in this paper.The article start from the point of immune theory and algorithms.Firstly,it has the introduction of the theory of artificial immune system and the basic characteristics,summarizes some of the classic algorithms. it has the introduction of the application of artificial immune system for fault diagnosis and the model. For the unequal distribution of detector and the convergence,it has optimized the detector form the artificial immune optimization algorithm.The AIS based on Danger Theory and the traditional theories of AIS are compared in terms of immunology theory and algorithms;the limit of existing SNS is analyzed; and the advantages of AIS based on Danger Theory are expatiated,then the DIA is proposed. Therefore, Danger Theory is introduced, from which principles and structures concerned have been concluded, then the feasibility of their application into anomaly detection is analyzed,a model of anomaly detection for anomaly detection System and a forecasting system for unknown anomaly detection System based on Danger Theory have been proposed. It analyse the sensor signals and the Isomap algorithm for the dimensionality reduction is made too,the experimental results has been analysed too.At last, combined with the immune clone optimize algorithm,the paper describes the respective of anomaly detection system model and motor fault diagnosis model from the application of algorithms based on Danger Theory.The test simulation on anomaly detection system for motor fault diagnosis system is made.Finally,the results are analyzed. and indicates that the work need to be further studied.

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CLC: > Industrial Technology > Electrotechnical > Motor > General issues > Maintenance and repair of motor > Motor failure
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