Fault Detection of Multimodal Process Based on Score Difference MMP
A fault detection algorithm of multimodal process based on score difference multi-manifold projections(SDMMP)was proposed for the multimodal problem in industrial process.Firstly,the multi-manifold projections(MMP)algorithm was used to construct a unified global graph and a local graph to calculate the score of the original samples.Secondly,the k-nearest neighbor method was used to calculate the mean vector of neighbor samples.The estimated score of the samples were calculated.The score difference matrix and residual matrix were calculated by the estimated score.Third,the new SPE and T2 monitoring indexes were established to monitor the changes of score difference subspace and residual subspace,and the control limit was calculated by kernel density estimation(KDE).Finally,the new statistics were compared with the control limit for fault detection.The SDMMP algorithm was applied to a numerical example and the Tennessee Eastman process for monitoring and diagnosis.Simulation results showed that,the SDMMP algorithm had obvious advantages in fault detection of industrial process with multimodal characteristics compared with principal component analysis(PCA),locality preserving projections(LPP)and MMP.
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