Adaptive weighted data fusion of muti-sensor based on fuzzy preference relations

Hao, Huijuan; Wang, Maoli; Xu, Mei; Tang, Yongwei

doi:10.1109/icinfa.2016.7831821

2016 IEEE International Conference on Information and Automation (ICIA) 2016

DOI: 10.1109/icinfa.2016.7831821

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Adaptive weighted data fusion of muti-sensor based on fuzzy preference relations

Huijuan Hao

Maoli Wang

Mei Xu

et al.

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2022

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Virtual–real fusion maintainability verification based on adaptive weighting and truncated spot method

Zhang¹,

Zhang²,

Wang³

et al. 2022

Eksploatacja i Niezawodność – Maintenance and Reliability

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Maintainability is an important general quality characteristic of products. Insufficient maintainability will lead to long maintenance time and high maintenance cost, thus affecting the availability of products. Maintainability verification is an important means to ensure maintainability meets design requirements. However, the cost of traditional real maintainability verification method is very high, and the virtual maintenance method has insufficient verification accuracy due to the lack of large maintenance force feedback when the human body is moving. In order to reduce the evaluation error and test sample size, the paper conducts maintainability verification based on the mixed physical and virtual maintainability test scenarios. Aiming at the problem that traditional methods are difficult to deal with the real test information and synchronous virtual simulation information in the test process, this study proposes a virtual–real fusion maintainability evaluation algorithm based on adaptive weighting and truncated SPOT (Sequential Posterior Odd Test) method. It can weigh real test information and virtual human simulation information adaptively to obtain a virtual–real fusion maintainability test sample. Then, the SPOT method is used to evaluate the maintainability of small samples. The adjustment of valve clearance, replacement of air filter element and replacement of starting motor maintenance tasks of ship engine are taken as examples for demonstration. The virtual–real fusion and virtual maintainability verification methods are respectively used for verification, and compared with the physical maintenance scenario constructed by 3D printing, indicating that the accuracy of virtual–real fusion maintainability test verification is 89%, while the virtual maintainability verification is only 33%.

show abstract

Virtual–real fusion maintainability verification based on adaptive weighting and truncated spot method

Zhang¹,

Zhang²,

Wang³

et al. 2022

Eksploatacja i Niezawodność – Maintenance and Reliability

View full text Add to dashboard Cite

show abstract

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Adaptive weighted data fusion of muti-sensor based on fuzzy preference relations

Cited by 1 publication

References 3 publications

Virtual–real fusion maintainability verification based on adaptive weighting and truncated spot method

Virtual–real fusion maintainability verification based on adaptive weighting and truncated spot method

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