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Study on fault diagnosis algorithm based on artificiall immune danger theory

机译:基于人工免疫危险理论的故障诊断算法研究

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In order to improve precision of fault diagnosis which based on artificial immune system, a kind of fault diagnosis algorithm based on immune danger theory was presented. The algorithm can make judgment according to whether existing danger signals and reduce false rate. The algorithm also can adjust databases online. The algorithm was applied to automobile axle driving fault diagnosis. the result shows that 6% normal axle drivings are judged as abnormal axle drivings, 4% abnormal axle drivings are judged as normal axle drivings. Compared with testing result of advanced negative selection algorithm which based on self-nonself recognition, the fault diagnosis algorithm based on artificial immune danger theory result has a lower false rate.
机译:为了提高基于人工免疫系统的故障诊断精度,提出了一种基于免疫危险理论的故障诊断算法。该算法可以根据是否存在危险信号做出判断,降低错误率。该算法还可以在线调整数据库。该算法被应用于汽车轴驱动故障诊断。结果表明,将6%正常轴驱动器判断为异常轴驱动器,将4%异常轴驱动器判断为正常轴驱动器。与基于非自我识别的高级否定选择算法的测试结果相比,基于人工免疫危险理论结果的故障诊断算法的误报率更低。

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