Fault Diagnosis And Condition Monitor Based On Extensis

In recent years, disaster cases have frequently occurred in view of the breakdown of the key equipments, which compels the government of each country, society and researchers to highlight the study of the fault diagnosis and condition monitor in the complicated system. However, considering the matter of security, a great deal of unnecessary maintenance has been carried out on the premise of incorrect diagnosis and condition monitor for the operation system, which greatly increases operation cost. With the rapid development of modern industry and sci-technology, the industry equipments increasingly become large-scaled, continued, high-speeded and automated, which accordingly leads to more and more functions, and more and more complicated structures. Therefore, the traditional fault diagnosis method and technology far from meet the running demand of the complicated equipments system. For this reason, studies on the fault diagnosis and condition monitor theories and application of the complicated systems have aroused researcher's great interest in recent years, furthermore, some great achievements have been abstained in this area.Based on the reflection system state features of qualitative and quantitative of extension relation function, with the combination of relative theories of neural network and immune system, With the background of the national natural science fund item--" Reconfiguration of Fault Diagnosis System Based on Immune Response Theory and Comparability Principle", the scientific research item--"artificial immune network theory and its application"carried by Hubei provincial Education Department,"Fault diagnosis based on fault diagnosis"and Enterprise horizontal item"On-line fault diagnosis and prediction system of excitation system"and"leakage electricity fault diagnosis of circuit system", on the basis of overcoming the flaw of traditional algorithm, it is carried on the detailed analysis to extension immune algorithm, extension neural network, extension K nearest neighbor and extension comprehensive evaluation for fault diagnosis and extension control for condition monitor. The main research result include:①With the background of the item that my supervisor assumes,"the fault diagnosis and prevention system of excitation system development", and the excitation system fault character-element as the study subject, the fault character of excitation signal is extracted by FFT and wavelet packets. With the utilization of the extension comprehensive evaluation method , the extension comprehensive fault diagnosis based on excitation system has be developed, and the results shows that the method can recognize fault signal.②The extension neural network and extension neural element have been designed on the premise of extension and artificial neural network. And then, through BP algorithm and genetic training algorithm, the structure of extension neural network and power are trained and optimized, finally, being tested through the rotary fault.③The Extension Immune Fault Diagnosis Algorithm(EIFDA), which is proposed through extension and artificial immune system, can be used for artificial fault diagnosis. The immune response mechanics and"self and non-self"recognition principle are utilized to identify fault, and extension distance function is designed. Based on above principle, have been established B-cell detector matter-element and test matter-element. The B-cell detector is trained through the immune learning and the fault sample data. The different mature B-cell detector is used to recognize the test ample. The result shows the EIFDA is an effective algorithm for fault diagnosis.④In this part, a new Extension K Nearest Neighbor (EKNN) is proposed for data classification problem and fault diagnosis. Firstly, different attribute numbers impacts the classification correct rate, the data attribute reduction is applied by genetic algorithm. Secondly, the EKNN is described by K Nearest Neighbor(KNN) and extension distance. For each reduction attribute of training samples, the maximum,minimum and mean is computed. The extension distance is measured the test sample and the training samples .The K nearest extension distance allocates the different classes. Finally, two data of UCI and a fault diagnosis sample is used by EKNN, the results shows the EKNN classification correct rate is better than other traditional algorithm.⑤Condition monitor, one of significant parts of the fault diagnosis, is an effective measure to prevent the fault occurrence. In this part, the aim is to find out the method to prevent the traveling crane from tilting through careful monitoring the process of which the traveling crane works. Firstly, the aim is to work out the main factor and danger function index through the analysis of the moment of the crane. Secondly, the impact factor bound value is optimized by immune network algorithm, which helps to work out the classical zone of extension conjunction function that influences each influential factor. Finally, the evaluation for the health evaluation system under the condition of the systems with different heavy goods lifting and danger function, based on extension set and extension transformation, provides an effective assistant support for preventing system from tilting.To sum up ,the creativity of this thesis lies in the following aspects:, first, the extension immune algorithm, has been successfully designed and can be used for steam turbine fault diagnosis, on the basis of utilization of"self and non-self recognition theory in immune system and immune clone selection theory, with the combination of extension matter-element analysis and extension set; second, the concept of extension distance has been put forward and on the basis of it the extension K nearest neighbor has been designed which can be used for data classification and fault diagnosis; third, the problem of condition monitor for the crane in the process of goods lifting has been settled on the basis of immune network and extension control.In the final part, the summary to the research work of the full text is given, furthermore, the direction of further study is pointed out that theories and application in fault diagnosis and condition monitor of the complicated system.