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航空发电机综合故障诊断技术研究 被引量:21
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作者 刘海港 董芷岑 《电子测量技术》 2014年第3期125-127,133,共4页
针对航空发电机的故障难以准确诊断的问题,提出了一种基于BP神经网络的航空发电机综合故障诊断方法,通过对BP神经网络数学原理及算法的深入分析与研究,构建基于BP神经网络的航空发电机故障诊断模型。结合某型航空发电机的真实试验数据,... 针对航空发电机的故障难以准确诊断的问题,提出了一种基于BP神经网络的航空发电机综合故障诊断方法,通过对BP神经网络数学原理及算法的深入分析与研究,构建基于BP神经网络的航空发电机故障诊断模型。结合某型航空发电机的真实试验数据,对所构建故障诊断模型的正确性进行了试验验证。在试验验证过程中,利用航空发电机真实试验数据的前60组对神经网络进行训练,后40组数据对神经网络进行测试,最终验证了所构建的故障诊断模型能够较好实现对航空发电机故障进行准确诊断的效能,且所采用的BP神经网络方法具有收敛速度快、识别能力强、精度高以及准确性高等优点。 展开更多
关键词 航空发电机 健康状态向量 BP神经网络 故障诊断
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Life prediction of ZPW-2000A track circuit equipment based on SVDD and gray prediction 被引量:2
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作者 WANG Rui-feng JIA Nan 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2018年第4期373-379,共7页
Evaluation of the health state and prediction of the remaining life of the track circuit are important for the safe operation of the equipment of railway signal system.Based on support vector data description(SVDD)and... Evaluation of the health state and prediction of the remaining life of the track circuit are important for the safe operation of the equipment of railway signal system.Based on support vector data description(SVDD)and gray prediction,this paper illustrates a method of life prediction for ZPW-2000A track circuit,which combines entropy weight method,SVDD,Mahalanobis distance and negative conversion function to set up a health state assessment model.The model transforms multiple factors affecting the health state into a health index named H to reflect the health state of the equipment.According to H,the life prediction model of ZPW-2000A track circuit equipment is established by means of gray prediction so as to predict the trend of health state of the equipment.The certification of the example shows that the method can visually reflect the health state and effectively predict the remaining life of the equipment.It also provides a theoretical basis to further improve the maintenance and management for ZPW-2000A track circuit. 展开更多
关键词 track circuit health state assessment life prediction support vector data description(SVDD) gray prediction
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