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This paper presents the development of an algorithm based on K-Means clustering and probabilistic neural network (PNN) for classifying the industrial system faults. The proposed technique consists of a preprocessing unit based on K-Means clustering and probabilistic neural network (PNN). Given a set of data points, firstly the K-Means algorithm is used to obtain K-temporary clusters, and then PNN...
To fast monitor process, a combined approach of fault diagnosis approach based on Lifting Wavelets and SVM(LWSVM) was presented. Firstly the data was pre-processed to remove noise and spikes through lifting scheme wavelets, which is faster than the traditional wavelets. Then SVM was used to diagnose the faults in process. To validate the performance and effectiveness of the proposed scheme, LWSVM...
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