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Increasing complexity and automation of the chemical process industries requires more reliable and efficient real-time fault diagnosis systems. Here, a real-time expert system based on wavelet transform and fuzzy ART neural network is introduced for fault diagnosis, providing fault prediction to help operators before abnormal situations occur. Data preprocessing, knowledge base structure, representation...
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