Test point selection for analog fault diagnosis of unpowered circuit boards

Abstract

Modern densely loaded circuit boards have posed problems for fault diagnosis with in-circuit testers because only limited physical access to the boards is allowed. In this paper, we present an efficient graph-based test-point selection algorithm for analog fault diagnosis of unpowered circuit boards. In addition to finding the sets of test points that allow one to differentiate between the elements under diagnosis, the algorithm can serve as a design for testability (DfT) guide for circuit board design. Experimental results on some industrial designs show that, in general, access to 50% of the nodes is sufficient to diagnose all the elements.Index Terms-Analog fault diagnosis, board testing, design for testability, test point selection.

A Diagnosability-Integrated Design Approach Based on Graph Theory

“…Firstly, the data of measurement points 5 and 6 were extracted according to the signal features in Table 2, and the feature vectors of multiple measurement points were then pieced together to form a new vector or matrix for diagnosis [27], and the schematic diagram of the piecing method is shown in Figure 10.…”

“…Firstly, the data of measurement points 5 and 6 were extracted according to the signal features in Table 2, and the feature vectors of multiple measurement points were then pieced together to form a new vector or matrix for diagnosis [27], and the schematic diagram of the piecing method is shown in Figure 10. The four methods in the literature and the method in this paper were subjected to 50 simulation experiments, and the number of samples that were misdiagnosed in each experiment was recorded, and the statistical indexes such as the mean and quartile of the experimental results of each method were counted and plotted as a box-and-line diagram, as shown in Figure 11.…”

Design of test stimuli and minimisation of ambiguity in fault diagnosis of analogue circuits with tolerance

“…Proper sources can reduce the ambiguity of faults, leading to high precision and speed of diagnosis. Much research work has been done in the area of test node selection and stimuli selection (Hamida and Kaminska 1993;Pan, Cheng and Gupa 1994;Slamani, Kamiska and Quesnel 1994;Sheng and Chang 1996;Wang, Gielen and Sansen 1998;Fedi, Manetti and Piccirilli 1999;Zheng 1999;Huang and Cheng 2000;Prasad, Sarat and Babu 2000;Starzyk et al 2000;Variyam and Chatterjee 2000;Starzyk et al 2004;Sun 2008b). Principles for selecting stimuli sources have been proposed by Pan, Cheng and Gupa (1994); Sheng and Chang (1996); Wang, Gielen and Sansen (1998); and Zheng (1999).…”

A multi-attribute decision based optimum test point selection for analog fault dictionary techniques

“…But the selected optimum test point set can only assure structural correctness, while not assuring diagnosis performance optimality. In reference [2][3][4][5][6], a quantitative/qualitative model is adopted, which means the modeling process is very complicated, requiring the complete or partial knowledge of system. Thus, this model is not applicable to large-scale electronic system.…”