Fuzzy Petri nets for rule-based decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Abduction-based diagnosis: a competition-based neural model simulating abductive reasoning
Journal of Parallel and Distributed Computing
Knowledge Representation Using Fuzzy Petri Nets
IEEE Transactions on Knowledge and Data Engineering
A fuzzy neural network approach to machine condition monitoring
Computers and Industrial Engineering - Special issue: Selected papers from the 25th international conference on computers & industrial engineering in New Orleans, Louisiana
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Computers and Industrial Engineering
One-class support vector machines-an application in machine fault detection and classification
Computers and Industrial Engineering
IEEE Transactions on Fuzzy Systems
Failure mode and effects analysis using fuzzy evidential reasoning approach and grey theory
Expert Systems with Applications: An International Journal
Reversed fuzzy Petri nets and their application for fault diagnosis
Computers and Industrial Engineering
Computers and Industrial Engineering
Towards timed fuzzy Petri net algorithms for chemical abnormality monitoring
Expert Systems with Applications: An International Journal
A simple approach to ranking a group of aggregated fuzzy utilities
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A multilevel weighted fuzzy reasoning algorithm for expert systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Optimal Bayesian estimation and control scheme for gear shaft fault detection
Computers and Industrial Engineering
Automatic bearing fault diagnosis based on one-class ν-SVM
Computers and Industrial Engineering
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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.