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《Machine Tool & Hydraulics》 2011-17
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Fault Detection of Aeroengine Coupled Rotor System Based on Immune-neural Network

HOU Shengli1,WANG Wei1,SHI Xiaopei1,ZHONG Xinhui1,HU Jinhai2(1.Xuzhou Air Force College,Xuzhou Jiangsu 221000,China; 2.The Engineering Institute,Air Force Engineering University,Xi'an Shaanxi 710038,China)  
A new vibration fault detection model of aeroengine coupled dual-rotor system was proposed based on immune-neural networks.In this model,neural networks-based detectors were constructed based on the principle of immune recognition.These detectors were used to capture the anomalous pattern features of vibration signal.Taking advantage of neural networks training,the information of fault patterns was stored in the distributed neural networks-based detectors.When a detector was matched up with a feature sample,the detector was stimulated.Through the relevant stimulated detectors,a fault could be found out.Vibration experiments results of dual-rotor system shows that the proposed model has high resolution for locations of signal singularities,which are caused by characteristics of coupled rotor system.This method is contributive for rotor system monitoring.
【Fund】: 国家自然科学基金资助项目(60672179)
【CateGory Index】: V263.6;TP183
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【Citations】
Chinese Journal Full-text Database 6 Hits
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【Co-citations】
Chinese Journal Full-text Database 10 Hits
1 HOU Shengli, WANG Wei,QIAO Li, SHI Xiaopei,BI Zhirong(Xuzhou Air Force College,Xuzhou221000,China);A Neural Network Model of Compressor Stall Detection Based on Negative Selection Principle[J];Electronics Optics & Control;2010-05
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【Secondary Citations】
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