Health Status Evaluation of Welding Robots Based on the Evidential Reasoning Rule Article Swipe
Bangcheng Zhang
,
Jidong Wang
,
Shuo Gao
,
Xiaojing Yin
,
Zhi Gao
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/electronics12081755
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/electronics12081755
It is extremely important to monitor the health status of welding robots for the safe and stable operation of a body-in-white (BIW) welding production line. In the actual production process, the robot degradation rate is slow and the effective data are poor, which can reflect a degradation state in the large amount of obtained monitoring data, which causes difficulties in health status evaluation. In order to realize the accurate evaluation of the health status of welding robots, this paper proposes a health status evaluation method based on the evidential reasoning (ER) rule, which reflects the health status of welding robots by using the running state data monitored in actual engineering and through the qualitative knowledge of experts, which makes up for the lack of effective data. In the ER rule evaluation model, the covariance matrix adaptive evolutionary strategy (CMA-ES) algorithm is used to optimize the initial parameters of the evaluation model, which improved the accuracy of health status evaluations. Finally, a BIW welding robot was taken as an example for verification. The results show that the proposed model is able to accurately estimate the health status of the welding robot by using the monitored degradation data.
Related Topics
Concepts
Welding
Robot
Computer science
Artificial intelligence
Robot welding
Gas tungsten arc welding
Machine learning
Data mining
Engineering
Mechanical engineering
Arc welding
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/electronics12081755
- https://www.mdpi.com/2079-9292/12/8/1755/pdf?version=1681190337
- OA Status
- gold
- Cited By
- 2
- References
- 26
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4362698786
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4362698786Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/electronics12081755Digital Object Identifier
- Title
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Health Status Evaluation of Welding Robots Based on the Evidential Reasoning RuleWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-04-07Full publication date if available
- Authors
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Bangcheng Zhang, Jidong Wang, Shuo Gao, Xiaojing Yin, Zhi GaoList of authors in order
- Landing page
-
https://doi.org/10.3390/electronics12081755Publisher landing page
- PDF URL
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https://www.mdpi.com/2079-9292/12/8/1755/pdf?version=1681190337Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2079-9292/12/8/1755/pdf?version=1681190337Direct OA link when available
- Concepts
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Welding, Robot, Computer science, Artificial intelligence, Robot welding, Gas tungsten arc welding, Machine learning, Data mining, Engineering, Mechanical engineering, Arc weldingTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
- Citations by year (recent)
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2024: 2Per-year citation counts (last 5 years)
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26Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| publication_date | 2023-04-07 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W6799708014, https://openalex.org/W2168892251, https://openalex.org/W2774410030, https://openalex.org/W4283386643, https://openalex.org/W4313274437, https://openalex.org/W4309852676, https://openalex.org/W2971616487, https://openalex.org/W2902853557, https://openalex.org/W2946048316, https://openalex.org/W4320490945, https://openalex.org/W4313559020, https://openalex.org/W3094156519, https://openalex.org/W2973074683, https://openalex.org/W2979143497, https://openalex.org/W1973573653, https://openalex.org/W2049337423, https://openalex.org/W4292264304, https://openalex.org/W3092992834, https://openalex.org/W3172471338, https://openalex.org/W6847851158, https://openalex.org/W3138287587, https://openalex.org/W2473262664, https://openalex.org/W2783325233, https://openalex.org/W2923575555, https://openalex.org/W4312543413, https://openalex.org/W3193893990 |
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| corresponding_author_ids | https://openalex.org/A5011254289 |
| countries_distinct_count | 1 |
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| corresponding_institution_ids | https://openalex.org/I4210143016, https://openalex.org/I4385474403 |
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