A weighted fuzzy inference method and application on wheel damage analysis.

QingE Wu, Fan Wu, Bofeng Zhang, Shaojing Song

Abstract read

In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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2 · The registry

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

QingE WuSchool of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai, 201209, China. qewu@sspu.edu.cn.

Fan WuSchool of Intelligent Manufacturing and Control Engineering, Shanghai Polytechnic University, Shanghai, 201209, China.

Bofeng ZhangSchool of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai, 201209, China.

Shaojing SongSchool of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai, 201209, China.

Funding

Key Science and Technology Program of Henan Province 222102210084Key Science and Technology Project of Henan Province University 23A413007

6 · The paper itself

Abstract

To mitigate the safety risks and economic losses caused by wheel damage, this paper proposes an interval valued fuzzy inference-based sound analysis method for wheel damage detection. Firstly, interval valued fuzzy sets are defined to represent various levels of damage severity. A similarity calculation method is then designed, based on the defined interval valued fuzzy sets, to assess the damage level of wheel components. Moreover, the OWA operator is employed to assign higher weights to key features while reducing the influence of noise or redundant features. Finally, a double-threshold interval valued fuzzy inference approach is proposed for comprehensive decision-making regarding the wheel damage degree. The proposed method is applied to wheel damage sound analysis, and a corresponding detection system is developed. Experimental results demonstrate that the proposed method outperforms existing techniques in detection accuracy, response speed, and robustness, and it is adaptable to various wheel operating environments.

Indexed as

Dual thresholdInterval valued fuzzy inferenceOWA operatorSimilarity degreeSound discrimination

Identifiers

PMID39732916

DOI10.1038/s41598-024-82792-y

PMCPMC11682258

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.