Automated Diagnosis of Faults in Rotating Machinery using Adaptive Network Based Fuzzy Inference

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Automated Diagnosis of Faults in Rotating Machinery using Adaptive Network Based Fuzzy Inference. The long-term integrity of engineering assets depends on the quality of their maintenance which runs into billions of dollars per year in Australia. This project aims to develop a new fundamental automated technique for the detection and diagnosis of machinery faults. The innovation lies in the ability of this technique to not depend on knowledge of fault components in the discrete wavelet packet analysis. All other work conducted to date depends on knowledge of these components and their location. The results of this work will vastly improve the costly manually based diagnostics procedures in the maintenance of plant and industrial assets.