BohYoh Shibata

The Improvement of Fault Diagnosis Algorithm Using Signed Directed Graph

Abstract As a fault diagnosis method for a large-scale chemical plant, qualitative model-based method using signed directed graph has been proposed. This method has high diagnostic reliability (high probability of finding the real fault cause) but low diagnostic accuracy (poor information content obtained from diagnostic result). To overcome low diagnostic accuracy, the method is improved to use information about delays in fault propagation among state variables, representing the delays by fuzzy numbers. Furthermore, the diagnostic accuracy of the improved method is evaluated by introducing a concept of information content Finally, diagnostic experiments with the use of a mini-plant demonstrate that the improved method has higher diagnostic accuracy and the robustness for ambiguity contained in the delays.

FAULT DIAGNOSIS OF THE CHEMICAL PROCESS UTILIZING SIGNED DIRECTED GRAPH; Improvement and Evaluation of the Diagnosis Accuracy

Abstract The fault diagnosis algorithm using a signed directed graph as a model of the system is useful to real-time diagnosis of failures that occur in processes. The accuracy of the algorithm has been improved so much that it can select the candidates that are the most likely to be the real cause of failure, utilizing the concept of amplifying branch. The accuracy of the improved algorithm has been examined by its application to data obtained in the experiments of fault diagnosis in tank-pipeline systems, and estimated by the size of the greatest set of candidates.

Optimal Allocation of Sensors for Fault Diagnosis System Using the Signed Directed Graph

Abstract An allocation of sensors in a chemical plant is usually decided for the purpose of not fault diagnosis but process control, production control and so on. This is one reason for poor accuracy of fault diagnosis. This paper discusses the problem to search the optimal allocation of sensors with the constraint of the required specification (especially, diagnostic accuracy) for a fault diagnosis system using a signed directed graph. An algorithm to solve the problem is successfully applied to a mini-plant to demonstrate its usefulness.

HIERARCHICAL FAULT DIAGNOSIS SYSTEM UTILIZING THE SIGNED DIRECTED GRAPH AND THE EXTENDED KALMAN FILTER

Abstract The hierarchical fault diagnosis system containing a two-level strategy has been developed. This system involves the fault diagnosis method using signed directed graph as a qualitative model-based method and the fault diagnosis method using extended Kalman filter as a quantitative model-based method. In the upper-level strategy, a set of candidates for the cause of failure is obtained by use of the fault diagnosis method using signed directed graph. In the lower-level strategy, the most likely candidate to be the real cause of failure is selected out of the set of candidates by utilizing the extended Kalman filter. The efficiency of the present method is demonstrated by applying it to the tank-pipeline system.

Hierarchical Fault Diagnosis System Utilizing the Signed Directed Graph and the Extended Kalman Filter

Abstract The hierarchical fault diagnosis system containing a two- level strategy has been developed. This system involves the fault diagnosis method using signed directed graph as a qualitative model- based method and the fault diagnosis method using extended Kalman filter as a quantitative model-based method. In the upper-level strategy, a set of candidates for the cause of failure is obtained by use of the fault diagnosis method using signed directed graph. In the lower- level strategy, the most likely candidate to be the real cause of failure is selected out of the set of candidates by utilizing the extended Kalman filter. The efficiency of the present method is demonstrated by applying it to the tank-pipeline system.

Fault diagnosis of chemical processes utilizing the signed digraph. Improvement of accuracy by use of the fault revealing time.

プラントの測定変数が異常を示す時刻を利用して測定変数の経時変化の特徴を表現し, 符号付有向グラフによる異常診断法を改良して, 真の原因である可能性の高い候補だけを選び出すことのできる異常診断法を提案する. また, 槽・配管系の異常診断の実験データに適用してその速度と精度を検討する.