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机构地区:[1]装甲兵工程学院控制工程系,北京100072 [2]装甲兵工程学院外训系,北京100072
出 处:《通信电源技术》2015年第1期10-13,共4页Telecom Power Technology
基 金:电气设备中修检测与调校系统(2012ZJ47)
摘 要:为了提高装甲车辆发电机故障的诊断能力,文中针对某型装甲车辆发电机不易检测、故障样本少的结构单元,进行故障辨识研究。首先,建立旋转励磁机Matlab仿真模型,对励磁电流进行谐波分析选取故障样本,然后借助BP神经网络构建专用故障辨识器,通过测试实验验证故障辨识器可靠有效,可使这部分不易检测单元得到精准化检测维修。因此,研究设计发电机故障辨识器对提高发电机的故障诊断能力,具有一定实际意义。In order to improve the fault diagnosis ability of armored vehicle generator, this paper does fault identifica- tion research on the units whose faults are difficult to be detected of a certain type of armored vehicle power generator. First of all, a Matlab simulation model of rotating exciter is set up. Harmonic analysis of exciting current is conducted to select the failure sample. Then a special fault identifier is built with the aid of the BP neural network. Through testing experi- ment, the fault identifier is proved to be reliable and efficient which can make these units not readily noticeable get accurate detection and maintenance. Therefore, the research on generator fault identifier has certain practical significance in impro- ving the generator fault diagnosis ability
分 类 号:TJ810.6[兵器科学与技术—武器系统与运用工程] U472.9[机械工程—车辆工程]
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