A Transfer Fault Diagnosing Method for Protocol Conformance Test Based on FSMs

Zhang, Xingchang; Luo, Wei; Li, Xiaodong; Yan, Binbin

doi:10.1109/apcip.2009.51

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…Changrui Chen et al [2] proposed a 3D associated dimension diagnosis method, it is improved by K-Medoids clustering technology for different typical states of satellite flywheel bearings and verified the feasibility of the method through experiments. Xinchang Zhang et al [3] developed a set of methods for inputting correct premises, and based on consistency test results, presented a fault diagnosis model based on finite state machines, which could locate and diagnose some faults. Junweir Lin et al [4] proposed a new fault diagnosis scheme for linear analog circuits.…”

Section: Introductionmentioning

confidence: 99%

A Model for Flywheel Fault Diagnosis Based on Fuzzy Fault Tree Analysis and Belief Rule Base

Cheng¹,

Liu²,

He³

et al. 2022

Machines

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In the fault diagnosis of the flywheel system, the input information of the system is uncertain. This uncertainty is mainly caused by the interference of environmental factors and the limited cognitive ability of experts. The BRB (belief rule base) shows a good ability for dealing with problems of information uncertainty and small sample data. However, the initialization of the BRB relies on expert knowledge, and it is difficult to obtain the accurate knowledge of flywheel faults when constructing BRB models. Therefore, this paper proposes a new BRB model, called the FFBRB (fuzzy fault tree analysis and belief rule base), which can effectively solve the problems existing in the BRB. The FFBRB uses the Bayesian network as a bridge, uses an FFTA (fuzzy fault tree analysis) mechanism to build the BRB’s expert knowledge, uses ER (evidential reasoning) as its reasoning tool, and uses P-CMA-ES (projection covariance matrix adaptation evolutionary strategies) as its optimization model algorithm. The feasibility and superiority of the proposed method are verified by an example of a flywheel friction torque fault tree.

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Section: Introductionmentioning

confidence: 99%