标题：An Online Data Driven Fault Detection Method in Dynamic Process based on Sparse Representation
作者：Yang, Rui; Huang, Mengjie
作者机构：[Yang, Rui] Shandong Univ Sci & Technol, Coll Elect Engn & Automat, Qingdao 266590, Peoples R China.; [Huang, Mengjie] China Univ Petr, Coll Mech & 更多
会议名称：IEEE International Conference on Mechatronics and Automation (ICMA)
会议日期：AUG 06-09, 2017
来源：2017 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (ICMA)
关键词：intermittent fault; fault detection; sparse representation
摘要：With the development of science and industrial technologies, the intermittent fault has become the main fault of actual system, and the fault diagnosis on intermittent fault has progressed. However, with the increase in the complexity and uncertainty of modern engineering system, it is not feasible to establish accurate mathematical models. Thus, data-driven method is required for fault detection. Based on the sparsity of intermittent faults in some domains, an intermittent fault detection method based on sparse representation is proposed, with the online update of over-complete dictionary and fault detection threshold. With the simulation verification, the proposed method is suitable for intermittent fault detection in dynamic system.