Haris M. Khalid, Rajamani Doraiswami, Lahouari Cheded


An intelligent diagnostic scheme using sensor network for incipient faults is proposed using a holistic approach which integrates model-, fuzzy logic-, neural network- based schemes. In case the system is highly non-linear and there are enough training data available, a neural network based scheme is preferred; where the rules relating the input and output can be derived, a Fuzzy-logic approach is chosen; and where a model is available, a linearized model is employed. These three schemes are integrated sequentially ensuring thereby that critical information about the presence or absence of a fault is monitored in the shortest possible time, and the complete status regarding the fault is unfolded in time. The proposed scheme is evaluated extensively on simulated examples and on a physical system exemplified by a benchmarked laboratory-scale two-tank system to detect and isolate faults including sensor, actuator and leakage ones.


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Paper Citation

in Harvard Style

M. Khalid H., Doraiswami R. and Cheded L. (2009). INTELLIGENT FAULT DIAGNOSIS USING SENSOR NETWORK . In Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO, ISBN 978-989-8111-99-9, pages 121-128. DOI: 10.5220/0002165201210128

in Bibtex Style

author={Haris M. Khalid and Rajamani Doraiswami and Lahouari Cheded},
booktitle={Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},

in EndNote Style

JO - Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,
SN - 978-989-8111-99-9
AU - M. Khalid H.
AU - Doraiswami R.
AU - Cheded L.
PY - 2009
SP - 121
EP - 128
DO - 10.5220/0002165201210128