Som Based Decision Support in Failure Management

Abstract

Computerized decision support system field covers many methodologies and application areas. In this paper Self-Organizing Map (SOM) and knowledge-based techniques are used in combination to reason problematic situations in failure management. A process model that consists of individual connected process components has been developed. A primary circuit of a boiling water nuclear power plant including two branches has been composed. A failure management scenario is thoroughly analyzed and solved with the SOM based decision support system. The structure and reasoning of the Computerized Decision Support System (CDSS) is also shortly discussed. The process model is demonstrated together with the CDSS and shown to be useful. The tool helps operators decision making with various visualizations, and by giving concrete recommendations for possible control actions or other acts.

Self-Organizing Map Based Fault Diagnosis Technique for Non-Gaussian Processes

“…The normal region of SOM can be defined by specifying a control limit for the quantization error of the process data. ,,− The quantization error provides a measure of similarity between the process data vector and the weight vector of the corresponding best matching neuron. For fault diagnosis, SOM is used to visualize the dynamic behavior of the process as a two-dimensional trajectory which can easily be interpreted to identify the root cause of fault. ,,− These conventional SOM based fault detection and diagnosis techniques rely heavily on the availability of various types of faulty process data. ,, However, in practice, generating faulty process data that takes into account all possible fault conditions of the process is infeasible. As a result, these techniques can only detect and diagnose a limited number of faults.…”