Application of Image Recognition Based on Grey Relational Analysis

Li, Hua

doi:10.3103/s0146411620040070

Aut. Control Comp. Sci.

2020

DOI: 10.3103/s0146411620040070

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Application of Image Recognition Based on Grey Relational Analysis

Hua Li

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Cited by 2 publications

References 22 publications

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Failure mode and effects analysis using an improved pignistic probability transformation function and grey relational projection method

Tang,

Sun,

Zhou

et al. 2023

Complex Intell. Syst.

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Failure mode and effects analysis (FMEA) is an important risk analysis tool that has been widely used in diverse areas to manage risk factors. However, how to manage the uncertainty in FMEA assessments is still an open issue. In this paper, a novel FMEA model based on the improved pignistic probability transformation function in Dempster–Shafer evidence theory (DST) and grey relational projection method (GRPM) is proposed to improve the accuracy and reliability in risk analysis with FMEA. The basic probability assignment (BPA) function in DST is used to model the assessments of experts with respect to each risk factor. Dempster’s rule of combination is adopted for fusion of assessment information from different experts. The improved pignistic probability function is proposed and used to transform the fusion result of BPA into probability function for getting more accurate decision-making result in risk analysis with FMEA. GRPM is adopted to determine the risk priority order of all the failure modes to overcome the shortcoming in traditional risk priority number in FMEA. Applications in aircraft turbine rotor blades and steel production process are presented to show the rationality and generality of the proposed method.

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Failure mode and effects analysis using an improved pignistic probability transformation function and grey relational projection method

Tang,

Sun,

Zhou

et al. 2023

Complex Intell. Syst.

View full text Add to dashboard Cite

show abstract

A New Fault Diagnosis Method for Quality Control of Electromagnet Based on T–S Fault Tree and Grey Relation

Pang

Dai

Zhou

et al. 2022

Int. J. Rel. Qual. Saf. Eng.

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Product fault diagnosis has been a focus of research in the field of quality control. Many studies have been made to ensure the accuracy of fault diagnosis in electromagnet quality control direction. However, in the pursuit of perfect identification method, the fault diagnosis process is extremely complex in quality control management. A new fault diagnosis method for quality control of electromagnet machining processes based on [Formula: see text]–[Formula: see text] fault tree and grey relation degree analysis is proposed in this paper. First, [Formula: see text]–[Formula: see text] fault tree is used to analyze and describe the dynamic fault relationship of the electromagnet machining processes. In order to make the fault mode more intuitive and specific, [Formula: see text]–[Formula: see text] fault tree logic diagram is used to describe the actual fault form of machining processes. Second, according to the fault output algorithm of [Formula: see text]–[Formula: see text] fault tree, the fault rate of basic event in each cycle is calculated and the fault rate of intermediate event and top event in each cycle is obtained. Then, the grey relation method is applied to calculate the relation between the basic event and the trend of top event failure rates in electromagnet machining processes. Based on the obtained relation degree, the faulty system of electromagnet machining processes can be repaired pertinently and achieve the purpose of quality control. Finally, an example of electromagnet quality control’s fault diagnosis is used to verify the objectivity and simplicity of the new method.

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Application of Image Recognition Based on Grey Relational Analysis

Cited by 2 publications

References 22 publications

Failure mode and effects analysis using an improved pignistic probability transformation function and grey relational projection method

Failure mode and effects analysis using an improved pignistic probability transformation function and grey relational projection method

A New Fault Diagnosis Method for Quality Control of Electromagnet Based on T–S Fault Tree and Grey Relation

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