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Báo cáo hóa học: "Fault diagnosis of Tennessee Eastman process using signal geometry matching technique"

Tuyển tập các báo cáo nghiên cứu về hóa học được đăng trên tạp chí sinh học đề tài :Tuyển tập các báo cáo nghiên cứu về hóa học được đăng trên tạp chí sinh học đề tài :Fault diagnosis of Tennessee Eastman process using signal geometry matching technique | Li and Xiao EURASIP Journal on Advances in Signal Processing 2011 2011 83 http asp.eurasipjournals.eom content 2011 1 83 o EURASIP Journal on Advances in Signal Processing a SpringerOpen Journal RESEARCH Open Access Fault diagnosis of Tennessee Eastman process using signal geometry matching technique Han Li and De-yun Xiao Abstract This article employs adaptive rank-order morphological filter to develop a pattern classification algorithm for fault diagnosis in benchmark chemical process Tennessee Eastman process. Rank-order filtering possesses desirable properties of dealing with nonlinearities and preserving details in complex processes. Based on these benefits the proposed algorithm achieves pattern matching through adopting one-dimensional adaptive rank-order morphological filter to process unrecognized signals under supervision of different standard signal patterns. The matching degree is characterized by the evaluation of error between standard signal and filter output signal. Initial parameter settings of the algorithm are subject to random choices and further tuned adaptively to make output approach standard signal as closely as possible. Data fusion technique is also utilized to combine diagnostic results from multiple sources. Different fault types in Tennessee Eastman process are studied to manifest the effectiveness and advantages of the proposed method. The results show that compared with many typical multivariate statistics based methods the proposed algorithm performs better on the deterministic faults diagnosis. Keywords fault diagnosis pattern matching adaptive rank-order morphological filtering Tennessee Eastman process 1. Introduction The last decades have been witnessing the modern large-scale processes developing toward high complexity and multiplicity in industries such as chemical metallurgical mechanical logistics and etc. These processes are generally characterized by a long-process flow with large operation scales and complicated .