In this thesis, an algorithm for PLC(Programmable Logic Controller) fault diagnosis system is proposed and experimentation is conducted with a PLC and a virtual plant.
To build a fault diagnosis system, the structure of a widely used PLC, is studied and fault examples are analyzed. From this, fault diagnostic method is developed which consists of self diagnostics, backward tracking algorithm, query with keywords of symptoms, and test by sequence programs for each unit. The self diagnostics given by PLC makers, which is a unique method to diagnose PLC till now in the field, is combined with proposed algorithm by modularized data base for each PLC. The backward tracking algorithm by analysis of the user sequence program can help to find the external faults for sensors. Query with keywords of the fault symptoms is to help to find the fault especially when similar symptoms are shown. Test sequence programs are used to test each unit to find where the location is.
It is shown experimentally that the proposed algorithm can find the faults which a typical self diagnostics in the commercially available PLC cannot.
