An intelligent sensor validation and fault diagnostic technique for diesel engines

E. Mesbahi

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

An intelligent sensor validation and on-line fault diagnosis technique for a 6 cylinder turbocharged diesel engine is proposed and studied. A single auto-associative 3-layer Artificial Neural Network (ANN), is trained to examine the accuracy of the measured data and allocate a confidence level to each signal. The same ANN is used to recover the missing or faulty data with a close approximation. For on-line fault detection a feed-forward ANN is trained to classify and consequently recognize faulty and healthy behavior of the engine for a wide range of operating conditions. The proposed technique is also equipped with an on-line learning mechanism, which is activated when the confidence level in predicted fault is poor. It is hoped that a feasible, practical, and reliable sensor reading, as well as highly accurate fault diagnosis system, would be achieved.
Original languageEnglish
Pages (from-to)141-144
JournalJournal of Dynamic Systems, Measurement and Control
Volume123
Issue number1
Publication statusPublished - Mar 2001
Externally publishedYes

Keywords

  • Neural networks
  • identification

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