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Adaptive fault detection for complex dynamic processes based on JIT updated data set
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نویسنده
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li j. ,li y. ,yu h. ,xie y. ,zhang c.
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منبع
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journal of applied mathematics - 2012 - دوره : 2012 - شماره : 0
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چکیده
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A novel fault detection technique is proposed to explicitly account for the nonlinear,dynamic,and multimodal problems existed in the practical and complex dynamic processes. just-in-time (jit) detection method and k-nearest neighbor (knn) rule-based statistical process control (spc) approach are integrated to construct a flexible and adaptive detection scheme for the control process with nonlinear,dynamic,and multimodal cases. mahalanobis distance,representing the correlation among samples,is used to simplify and update the raw data set,which is the first merit in this paper. based on it,the control limit is computed in terms of both knn rule and spc method,such that we can identify whether the current data is normal or not by online approach. noted that the control limit obtained changes with updating database such that an adaptive fault detection technique that can effectively eliminate the impact of data drift and shift on the performance of detection process is obtained,which is the second merit in this paper. the efficiency of the developed method is demonstrated by the numerical examples and an industrial case. copyright © 2012 jinna li et al.
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آدرس
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department of science,shenyang university of chemical technology,liaoning,shenyang 110142,china,lab of industrial control networks and systems,shenyang institute of automation,chinese academy of sciences,liaoning, China, college of information engineering,shenyang university of chemical technology,liaoning, China, lab of industrial control networks and systems,shenyang institute of automation,chinese academy of sciences,liaoning, China, department of science,shenyang university of chemical technology,liaoning, China, department of science,shenyang university of chemical technology,liaoning, China
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Authors
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