Research on optimal maintenance cycle model of nuclear equipment based on left and right fuzzy sorting method Article Swipe
Na Liu
,
Shuliang Zou
,
Binhai Huang
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1088/1755-1315/983/1/012095
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1088/1755-1315/983/1/012095
For the nuclear equipment with high reliability, the optimal maintenance cycle model of nuclear equipments is established by balancing the relationship between working time before component failure and maintenance cost. According to the expert evaluation, the failure of the equipment is analyzed. In the study, the ridge membership function is improved, and the failure probability model is established by using the left and right fuzzy sorting method. It transforms the fuzzy number into the fuzzy probability, so the component fault distribution function is determined. By testing, the model has good applicability and sensitivity. Taking the spent fuel shearing machine as an example, the optimal maintenance cycle of the key parts of the shearing machine is calculated. The results are consistent with the actual conditions, which can provide the basis for the formulation of the nuclear equipment maintenance plan. The results of the study show that the proposed method is of great significance for improving the reliability and maintenance efficiency of nuclear equipment.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1755-1315/983/1/012095
- OA Status
- diamond
- Cited By
- 1
- References
- 9
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4212996534
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4212996534Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1088/1755-1315/983/1/012095Digital Object Identifier
- Title
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Research on optimal maintenance cycle model of nuclear equipment based on left and right fuzzy sorting methodWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2022Year of publication
- Publication date
-
2022-02-01Full publication date if available
- Authors
-
Na Liu, Shuliang Zou, Binhai HuangList of authors in order
- Landing page
-
https://doi.org/10.1088/1755-1315/983/1/012095Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1088/1755-1315/983/1/012095Direct OA link when available
- Concepts
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Reliability engineering, Fuzzy logic, Shearing (physics), Sorting, Preventive maintenance, Engineering, Reliability (semiconductor), Computer science, Artificial intelligence, Algorithm, Power (physics), Physics, Geotechnical engineering, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2022: 1Per-year citation counts (last 5 years)
- References (count)
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9Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.provide | 127 |
| abstract_inverted_index.results | 118, 140 |
| abstract_inverted_index.sorting | 66 |
| abstract_inverted_index.working | 23 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.example, | 102 |
| abstract_inverted_index.function | 49, 82 |
| abstract_inverted_index.proposed | 147 |
| abstract_inverted_index.shearing | 98, 113 |
| abstract_inverted_index.testing, | 86 |
| abstract_inverted_index.According | 31 |
| abstract_inverted_index.analyzed. | 42 |
| abstract_inverted_index.balancing | 19 |
| abstract_inverted_index.component | 26, 79 |
| abstract_inverted_index.equipment | 4, 40, 136 |
| abstract_inverted_index.improved, | 51 |
| abstract_inverted_index.improving | 154 |
| abstract_inverted_index.consistent | 120 |
| abstract_inverted_index.efficiency | 159 |
| abstract_inverted_index.equipment. | 162 |
| abstract_inverted_index.equipments | 15 |
| abstract_inverted_index.membership | 48 |
| abstract_inverted_index.transforms | 69 |
| abstract_inverted_index.calculated. | 116 |
| abstract_inverted_index.conditions, | 124 |
| abstract_inverted_index.determined. | 84 |
| abstract_inverted_index.established | 17, 58 |
| abstract_inverted_index.evaluation, | 35 |
| abstract_inverted_index.formulation | 132 |
| abstract_inverted_index.maintenance | 10, 29, 105, 137, 158 |
| abstract_inverted_index.probability | 55 |
| abstract_inverted_index.reliability | 156 |
| abstract_inverted_index.distribution | 81 |
| abstract_inverted_index.probability, | 76 |
| abstract_inverted_index.relationship | 21 |
| abstract_inverted_index.reliability, | 7 |
| abstract_inverted_index.sensitivity. | 93 |
| abstract_inverted_index.significance | 152 |
| abstract_inverted_index.applicability | 91 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5070030556 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| corresponding_institution_ids | https://openalex.org/I91935597 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.5 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.43781095 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |