Application And Research Of FMEA Based Board-level Automatic Diagnosis

ABSTRACT:Communication Based Train Control (CBTC) System has already been the main trend in urban rail transit control system domain. The passenger convenience and safety directly related to the functional performance, security and reliability of CTBC. It leads to higher and higher requirement for CBTC equipment. Board-level design verification becomes key point of functional performance, security and reliability analysis during the whole life of CBTC equipment. Functional test and diagnosis can reveal the defect in design phase. Restricted to existing methods, board-level diagnosis encounters a lot of problems like personnel dependence, low accuracy and lack of strategy.FMEA is a common method on reliability analysis. This article mainly deals with the diagnosis problem by FMEA. Based on hardware FMEA from the components can obtain the all the board-level failure information. Relationship between board-level failure mode and causes, which can be used to build the failure information database, can be revealed by means of qualitative and quantitative of fault tree model. But current FMEA process does not fit failure information achievement.According to CBTC hardware points, this article adjusts the current FMEA process to meet the requirement of failure information achievement. Then a typical board is chosen to show the process of the analysis. The result of FMEA is loaded on fault tree model to show the direct relationship between board-level failure modes and components. Then qualitative and quantitative analyses are taken to match the each failure with the list of components. The sequence of the list is determined by a new concept called component importance degree, which is mentioned in the article.In this article, a diagnosis tool, which based on FMEA method, is designed to be used on CBTC board-level diagnosis. A typical board is tested to show the method performs. The result shows the method satisfies the requirement of CBTC board-level diagnosis. At last the article shows research orientation of the next work.