A PSO-TRAINED ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM FOR FAULT CLASSIFICATION

Haris M. Khalid, S. Z. Rizvi, Lahouari Cheded, Rajamani Doraiswami, Ammar Khoukhi

Abstract

When a fault occurs during an industrial inspection, workmen have to manually find the location and type of the fault in order to remove it. It is often difficult to accurately find the location and type of fault. Hence, development of an offline intelligent fault diagnosis system for process control industry is of great importance since successful detection of fault is a precursor to fault isolation using corrective actions. This paper presents a novel hybrid Particle Swarm Optimization (PSO) and Subtractive Clustering (SC) based Neuro-Fuzzy Inference System (ANFIS) designed for fault detection. The proposed model uses the PSO algorithm to find optimal parameters for (SC) based ANFIS training. The developed PSO-SC-ANFIS scheme provides critical information about the presence or absence of a fault. The proposed scheme is evaluated on a laboratory scale benchmark two-tank process. Leakage fault is detected and results are presented at the end of the paper showing successful diagnosis of most incipient faults when subjected to a fresh set of data.

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Paper Citation


in Harvard Style

M. Khalid H., Z. Rizvi S., Cheded L., Doraiswami R. and Khoukhi A. (2010). A PSO-TRAINED ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM FOR FAULT CLASSIFICATION . In Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010) ISBN 978-989-8425-32-4, pages 399-405. DOI: 10.5220/0003072303990405


in Bibtex Style

@conference{icnc10,
author={Haris M. Khalid and S. Z. Rizvi and Lahouari Cheded and Rajamani Doraiswami and Ammar Khoukhi},
title={A PSO-TRAINED ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM FOR FAULT CLASSIFICATION},
booktitle={Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)},
year={2010},
pages={399-405},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003072303990405},
isbn={978-989-8425-32-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)
TI - A PSO-TRAINED ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM FOR FAULT CLASSIFICATION
SN - 978-989-8425-32-4
AU - M. Khalid H.
AU - Z. Rizvi S.
AU - Cheded L.
AU - Doraiswami R.
AU - Khoukhi A.
PY - 2010
SP - 399
EP - 405
DO - 10.5220/0003072303990405