On the Linear Separability of Diagnostic Models

As new approaches and algorithms are developed for system diagnosis, it is important to reflect on existing approaches to determine their strengths and weaknesses. Of concern is identifying potential reasons for false pulls during maintenance. Within the aerospace community, one approach to system diagnosis-based on the D-matrix derived from test dependency modeling-is used widely, yet little has been done to perform any theoretical assessment of the merits of the approach. Past assessments have been limited, largely, to empirical analysis and case studies. In this paper, we provide a theoretical assessment of the representation power of the D-matrix and suggest algorithms and model types for which the D-matrix is appropriate. Finally, we relate the processing of the D-matrix with several diagnostic approaches and suggest how to extend the power of the D-matrix to take advantage of the power of those approaches.