Abstract
By' experiments, at valves used at production lines in Shanghai Baoshan Iron and Steel Company some techniques of inspection on faults and acquisition of fault characteristics are obtained. The fault diagnostic expert system for servo valve is accomplished. The traditional symbolic reasoning is based on knowledge representation in regular forms and pattern matching technique. And artificial neural network (ANN), in which knowledge is distributed over joints and reasoning is done by numerical calculation, combines representation and memory of knowledge with reasoning. Therefore, an expert system integrated fuzzy ANN with symbolic reasoning is constructed. This expert system is open to knowledge acquisition and management. By experiments, it is proven that the expert system is maintainable and efficient.
| Original language | English |
|---|---|
| Pages (from-to) | 315-320 |
| Number of pages | 6 |
| Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
| Volume | 17 |
| Issue number | 3 |
| Publication status | Published - 1997 |
Keywords
- Artificial neural network
- Electrohydraulic servo-valve
- Expert system
- Fault diagnosis
- Symbolic reasoning