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• W2436151569 abstract "Fault detection and isolation (FDI) is an important part of modern industrial systems, and plays a vital role in maintainability, safety, and reliability of process. We propose a novel FDI architecture based on a predictive model for fault-free process. We use the least-square support vector machine for identifying a nonlinear system and detecting its faults that may occur. Wavelet analysis on residual is used for fault isolation. An average accuracy of 95% has been achieved for all the abrupt faults of the well-known development and application of methods for actuator diagnosis in industrial control systems benchmark." @default.
• W2436151569 created "2016-06-24" @default.
• W2436151569 creator A5014961146 @default.
• W2436151569 creator A5040401289 @default.
• W2436151569 date "2016-10-01" @default.
• W2436151569 modified "2023-10-16" @default.
• W2436151569 title "A Two-Stage Fault Detection and Isolation Platform for Industrial Systems Using Residual Evaluation" @default.
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• W2436151569 doi "https://doi.org/10.1109/tim.2016.2575179" @default.
• W2436151569 hasPublicationYear "2016" @default.
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