Abstract


 
 
 Diagnostics is an important concept in system health and monitoring of space operations. Many of the existing diagnostic algorithms utilize system knowledge in the form of diagnostic matrix (D-matrix, also popularly known as diagnostic dictionary, fault signature matrix or reachability matrix). The D-matrix maps tests on observed conditions to failures. This matrix is mostly gleaned from physical models during system development. But, sometimes, this may not be enough to obtain high diagnostic performance during operation due to system modifications and lag and noise in sensor measurements. In such a case, it is important to modify this D-matrix based on knowledge obtained from sources such as time-series data stream (simulated or maintenance data) within a framework that includes the diagnostic/inference algorithm. A systematic and sequential update procedure, diagnostic modeling evaluator (DME) is proposed to modify D-matrix and wrapper/test logic considering the least expensive update first. The user sets the diagnostic performance criteria. This iterative procedure includes conditions ranging from modifying 0’s and 1’s in the matrix, adding/removing the rows (failure sources)/columns (tests), or modifying test/wrapper logic used to determine test results. We will experiment this framework on ADAPT datasets from DX challenge 2009.
 
 

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