A syntactic pattern-recognition approach for process monitoring and fault diagnosis

Engineering Applications of Artificial Intelligence

Volumn 8, Issue 1, 1995, Pages 35-51

  Rengaswamy, Raghunathan ^a   Venkatasubramanian, Venkat ^a  

^a PURDUE UNIVERSITY   (United States)

Author keywords

Fault diagnosis; knowledge based systems; neural networks; qualitative modeling; sensor monitoring; trend analysis

Indexed keywords

COMPUTATIONAL GRAMMARS; COMPUTER HARDWARE DESCRIPTION LANGUAGES; DECISION MAKING; ERROR CORRECTION; KNOWLEDGE BASED SYSTEMS; MATHEMATICAL MODELS; MONITORING; PATTERN RECOGNITION; PROCESS CONTROL; PROCESS ENGINEERING; REAL TIME SYSTEMS; SENSORS;

FAULT DIAGNOSIS; QUALITATIVE MODELING; SENSOR MONITORING; TREND ANALYSIS;

NEURAL NETWORKS;

EID: 0029251896     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/0952-1976(94)00058-U     Document Type: Article

References (10)

1. Towards the intelligent controller: formal integration of pattern recognition with control theory
2. Automatic generation of qualitative description of process trends for fault detection and diagnosis
3. Representation of process trends part I. A formal representation framework
4. Real-time qualitative analysis of the temporal shapes of the (bio)process variables
5. Process fault detection and diagnosis using neural networks—I. Steady-state processes
6. Limitations of the backpropagation approach to fault diagnosis and improvement with radial basis functions
7. Neural network decomposition strategies for large-scale fault diagnosis
8. Dynamic simulator for a model IV fluid catalytic cracking unit