基于动态故障树的汽车系统故障诊断方法

为了提高汽车故障诊断效率,降低诊断代价并解决静态故障树（SFT）无法描述汽车系统中动态失效序列的问题,提出一种基于动态故障树（DFT）的汽车系统故障诊断方法。首先,利用DFT建立系统的失效模式模型,并采用顺序二元决策图（SBDD）计算DFT的最小割集（MCS）;然后计算MCS以及MCS中组件的诊断重要度（DIF）;并在此基础上给出基于统一诊断服务（UDS）协议的汽车故障诊断方法,将诊断故障码对应的MCS过滤并排序,优先诊断DIF大的MCS和系统组件;最后通过一个汽车主动转向系统的应用实例对本文方法的有效性进行验证。案例分析结果表明,所提方法能够计算汽车故障诊断MCS序列,可以有效指导汽车故障诊断工作。

Fault diagnosis method for automobile system based on dynamic fault tree

In order to improve the efficiency of automobile fault diagnosis and reduce the cost of diagnosis, this paper proposes a fault diagnosis method of automobile system based on Dynamic Fault Tree (DFT). Firstly, the failure mode model of the system is the DFT is established by using DFT, and the DFT is transformed into a sequential binary decision diagram (SBDD) to calculate the minimum cut set (MCS). Secondly, the diagnostic importance (DIF) of the MCS and the components in the MCS is calculated. On this basis, a diagnosis method for automobile based on the Unified Diagnostic Service (UDS) protocol is proposed. The MCS corresponding to the diagnostic trouble codes are filtered and sorted, and MCS and components with large DIF are prioritized for diagnosis. Finally, the effectiveness of the proposed method was verified by the case study of an Active Rear Steering system. The case analysis results show that, the proposed method can calculate the fault diagnosis sequence and can effectively guide the vehicle fault diagnosis work.