کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1133843 956045 2013 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fault diagnosis and cause analysis using fuzzy evidential reasoning approach and dynamic adaptive fuzzy Petri nets
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی صنعتی و تولید
پیش نمایش صفحه اول مقاله
Fault diagnosis and cause analysis using fuzzy evidential reasoning approach and dynamic adaptive fuzzy Petri nets
چکیده انگلیسی


• A novel fault diagnosis and cause analysis model is presented.
• Incomplete, imprecise and uncertain information is modeled by FER approach.
• Forward inference and the abductive inference are combined by DAFPNs.
• The new model is based on matrix presentation for its parallel capability.

Fault diagnosis is of great importance to all kinds of industries in the competitive global market today. However, as a promising fault diagnosis tool, fuzzy Petri nets (FPNs) still suffer a couple of deficiencies. First, traditional FPN-based fault diagnosis methods are insufficient to take into account incomplete and unknown information in diagnosis process. Second, most of the fault diagnosis methods using FPNs are only concerned with forward fault diagnosis, and no or less consider backward cause analysis. In this paper, we present a novel fault diagnosis and cause analysis (FDCA) model using fuzzy evidential reasoning (FER) approach and dynamic adaptive fuzzy Petri nets (DAFPNs) to address the problems mentioned above. The FER is employed to capture all types of abnormal event information which can be provided by experts, and processed by DAFPNs to identify the root causes and determine the consequences of the identified abnormal events. Finally, a practical fault diagnosis example is provided to demonstrate the feasibility and efficacy of the proposed model.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Industrial Engineering - Volume 66, Issue 4, December 2013, Pages 899–908
نویسندگان
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