Optimal testing input sets for reduced diagnosis time of nuclear power plant digital electronic circuits

This paper describes the optimal testing input sets required for fault diagnosis of nuclear power plant digital electronic circuits. With complicated systems such as very large scale integration (VLSI), nuclear power plant (NPP), and aircraft, testing is the major factor of the maintenance of the system. Particularly, the diagnosis time grows quickly with the complexity of the component. For a reduced diagnosis time we derived the optimal testing sets that are the minimal testing sets required for detecting the failure and for locating the failed component. For a reduced diagnosis time, the technique presented by Hayes (1971) fits best for our approach to testing set generation among many conventional methods. However, this method has the following disadvantages: a) it considers only a simple network; b) it concerns only whether the system is in a failed state or not and does not provide the way to locate the failed component. Therefore we have derived the optimal testing input sets that resolve these problems by Hayes while preserving its advantages. When we applied the optimal testing sets to the automatic fault diagnosis system (AFDS) which incorporates the advanced fault diagnosis method of the artificial intelligence technique, we found that fault diagnosis using the optimal testing sets makes testing of the digital electronic circuits much faster than that using exhaustive testing input sets; when we applied them to test the Universal (UV) Card which is a nuclear power plant digital input/output solid state protection system card, we reduced the testing time by up to about 100.<
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