OPTIMAL TESTING INPUT SETS FOR REDUCED DIAGNOSIS TIME OF NUCLEAR-POWER-PLANT DIGITAL ELECTRONIC-CIRCUITS

Abstract

This paper describes the optimal testing input sets required for the fault diagnosis of the unclear power plant digital electronic circuits. With the 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, diagnosis time grows quickly with the complexity of the component In this research, for reduced diagnosis time we derived the optimal testing sets that are the minimal testing sets required for detecting the failure and for locating of the failed component. For reduced diagnosis time, the technique presented by Hayes fits best for our approach to testing sets generation among many conventional methods. However, this method has the following disadvantages; a) it considers only the simple network b) it concerns only whether the system is in 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 artificial intelligence technique, we found that the fault diagnosis using the optimal testing sets makes testing 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 up to about 100 times.