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基于多传感器数据融合的AMT故障在线自诊断

作  者:
曹亚斌;郑四发;段雄
单  位:
中国矿业大学;清华大学
关键词:
AMT;故障在线自诊断;多传感器数据融合
摘  要:
为了进一步提高AMT工作的可靠性和安全性,本文阐述了一种基于多传感器数据融合的AMT故障在线自诊断方法。根据电控机械式自动变速器(AMT)的结构,在不增加系统硬件的情况下,充分利用多种可以获取的信号,将多传感器数据融合与故障树方法相结合,从而对AMT系统的大部分故障实现在线诊断。
译  名:
Online Fault Self-diagnosis for AMT Based on Merged Multisensor Data
作  者:
CAO Ya-bin~1,ZHENG Si-fa~2,DUAN Xiong~1(1.China University of Mining and Technology,Xuzhou 221008,China;2.Qinghua University,Beijing 100084,China)
关键词:
AMT;Online Fault self-diagnosis;Merged multisensor data
摘  要:
For the sake of more reliability and security of AMT,an online fault self-diagnosis method is put forward in this paper based on merged multisensor information.According to the structure of AMT and by fully utilizing accessible multi-signals without increasing more hardware,it combins the multisensor merged information and the fault tree method to realize the online self-diagnosis to the majority of faults of AMT.The author detailedly states the diagnosis arithmetic and discusses its characteristics.

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