Ontology-Based Method for Fault Diagnosis of Loaders.

Feixiang Xu, Xinhui Liu, Wei Chen, Chen Zhou, Bingwei Cao

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

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.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

A Review of Fault Diagnosis and Intelligent Operations and Maintenance for Agricultural Machinery: Fault Mechanisms, Key Technologies, and Practical Recommendations.Sensors (Basel, Switzerland) · 2026
Review

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Feixiang XuSchool of Mechanical Science and Engineering, Jilin University, Changchun 130022, China. xufeixiangsdut@163.com.ORCID 0000-0003-2734-1924

Xinhui LiuSchool of Mechanical Science and Engineering, Jilin University, Changchun 130022, China. liuxh@jlu.edu.cn.

Wei ChenSchool of Mechanical Science and Engineering, Jilin University, Changchun 130022, China. chenwei_1979@jlu.edu.cn.

Chen ZhouSchool of Mechanical Science and Engineering, Jilin University, Changchun 130022, China. zhouchen17@mails.jlu.edu.cn.

Bingwei CaoSchool of Mechanical Science and Engineering, Jilin University, Changchun 130022, China. caobw16@mails.jlu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper proposes an ontology-based fault diagnosis method which overcomes the difficulty of understanding complex fault diagnosis knowledge of loaders and offers a universal approach for fault diagnosis of all loaders. This method contains the following components: (1) An ontology-based fault diagnosis model is proposed to achieve the integrating, sharing and reusing of fault diagnosis knowledge for loaders; (2) combined with ontology, CBR (case-based reasoning) is introduced to realize effective and accurate fault diagnoses following four steps (feature selection, case-retrieval, case-matching and case-updating); and (3) in order to cover the shortages of the CBR method due to the lack of concerned cases, ontology based RBR (rule-based reasoning) is put forward through building SWRL (Semantic Web Rule Language) rules. An application program is also developed to implement the above methods to assist in finding the fault causes, fault locations and maintenance measures of loaders. In addition, the program is validated through analyzing a case study.

Indexed as

CBRfault diagnosisloadersontologyRBR

Identifiers

PMID29495646

DOI10.3390/s18030729

PMCPMC5876616

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LicenceCC BY

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