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In this paper, by employing the idea of “dispersion first, then concentration” adhering to the biological perceptual system, an idea of the multi-symptom-domain based fault consensus diagnosis is developed. From the point of group decision-making, the method based on neural networks to realize this diagnosis idea is studied, and a particular multi-symptom-domain based diagnosis strategy is proposed, which is based on fuzzy integral theory. Finally, a case study is given. The research results show that the proposed diagnosis strategy is available and more efficient than conventional methods.
In this paper, by employing the idea of “dispersion first, then concentration ” adhering to the biological perceptual system, an idea of the multi-symptom-domain based fault consensus diagnosis is developed. From the point of group decision-making, the method based on neural networks to realize this diagnosis idea is studied, and a particular multi-symptom-domain based diagnosis strategy is proposed, which is based on fuzzy integral theory. Finally, a case study is given. The research results show that the proposed diagnosis strategy is available and more efficient than conventional methods.