Conversion and fusion method of multi-source and different populations maintainability prior data
Maintainability is an important universal quality characteristic that reflects the convenience, speed and economy of weapon and equipment maintenance. Making full use of multi-source data to accurately verify the degree to which the developed equipment meets the maintainability requirements is an im...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-11-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023084165 |
| _version_ | 1797429905939496960 |
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| author | Cheng Zhou Da Xu Zhaoyang Wang |
| author_facet | Cheng Zhou Da Xu Zhaoyang Wang |
| author_sort | Cheng Zhou |
| collection | DOAJ |
| description | Maintainability is an important universal quality characteristic that reflects the convenience, speed and economy of weapon and equipment maintenance. Making full use of multi-source data to accurately verify the degree to which the developed equipment meets the maintainability requirements is an important basis for equipment identification and acceptance. To solve the low reliability of equipment maintainability verification results caused by inaccurate comprehensive prior distribution obtained by fusing multi-source and different populations' prior data, a method of data conversion and fusion is proposed. A data conversion model based on the mean value ratio of failure mode maintenance data is constructed. The conversion factor is defined according to objective data to convert the different populations' prior data to the same populations. Next, a comparison of the prior distribution fitting performance of Bayes bootstrap, bootstrap, and two improved sample-resampling methods to are used obtain the closest fitting distribution to the true distribution. By constructing a multi-source data fusion model based on improved KL divergence, a symmetrical KL divergence is constructed to describe the similarity between each prior distribution and the field distribution for the weighted fusion of multi-source prior distribution in addition to determining and testing the normal comprehensive prior distribution. The results show that the conversion and fusion method effectively converts the multi-source and different populations’ maintainability prior data and obtains an accurate, comprehensive prior distribution by fusion, laying the foundation for applying the Bayes test method to verify the quantitative index of equipment maintainability. |
| first_indexed | 2024-03-09T09:19:39Z |
| format | Article |
| id | doaj.art-524b834db04441cca22d920bf5f334c1 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-09T09:19:39Z |
| publishDate | 2023-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-524b834db04441cca22d920bf5f334c12023-12-02T07:01:28ZengElsevierHeliyon2405-84402023-11-01911e21208Conversion and fusion method of multi-source and different populations maintainability prior dataCheng Zhou0Da Xu1Zhaoyang Wang2Department of Arms and Control, Army Academy of Armored Forces, Beijing, 100072, ChinaCorresponding author.; Department of Arms and Control, Army Academy of Armored Forces, Beijing, 100072, ChinaDepartment of Arms and Control, Army Academy of Armored Forces, Beijing, 100072, ChinaMaintainability is an important universal quality characteristic that reflects the convenience, speed and economy of weapon and equipment maintenance. Making full use of multi-source data to accurately verify the degree to which the developed equipment meets the maintainability requirements is an important basis for equipment identification and acceptance. To solve the low reliability of equipment maintainability verification results caused by inaccurate comprehensive prior distribution obtained by fusing multi-source and different populations' prior data, a method of data conversion and fusion is proposed. A data conversion model based on the mean value ratio of failure mode maintenance data is constructed. The conversion factor is defined according to objective data to convert the different populations' prior data to the same populations. Next, a comparison of the prior distribution fitting performance of Bayes bootstrap, bootstrap, and two improved sample-resampling methods to are used obtain the closest fitting distribution to the true distribution. By constructing a multi-source data fusion model based on improved KL divergence, a symmetrical KL divergence is constructed to describe the similarity between each prior distribution and the field distribution for the weighted fusion of multi-source prior distribution in addition to determining and testing the normal comprehensive prior distribution. The results show that the conversion and fusion method effectively converts the multi-source and different populations’ maintainability prior data and obtains an accurate, comprehensive prior distribution by fusion, laying the foundation for applying the Bayes test method to verify the quantitative index of equipment maintainability.http://www.sciencedirect.com/science/article/pii/S2405844023084165Maintainability verificationDifferent populations dataConversion factorData conversionMulti-source data fusion |
| spellingShingle | Cheng Zhou Da Xu Zhaoyang Wang Conversion and fusion method of multi-source and different populations maintainability prior data Heliyon Maintainability verification Different populations data Conversion factor Data conversion Multi-source data fusion |
| title | Conversion and fusion method of multi-source and different populations maintainability prior data |
| title_full | Conversion and fusion method of multi-source and different populations maintainability prior data |
| title_fullStr | Conversion and fusion method of multi-source and different populations maintainability prior data |
| title_full_unstemmed | Conversion and fusion method of multi-source and different populations maintainability prior data |
| title_short | Conversion and fusion method of multi-source and different populations maintainability prior data |
| title_sort | conversion and fusion method of multi source and different populations maintainability prior data |
| topic | Maintainability verification Different populations data Conversion factor Data conversion Multi-source data fusion |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023084165 |
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