A Health Evaluation Method based on Fuzzy Grey Clustering and Combination Weighting for Artillery Fire System
Ruixiang Zhang, Manyi Wang, Pengju Zhao, Xiaohai Liu
Nanjing University of Science and Technology
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The evaluation of the fire system health status of the artillery fire system is an important basis for ensuring the normal working performance of the artillery. In this paper, we propose a method to evaluate the health status for Artillery Fire System. Firstly, collecting the health index parameters of key components that can reflect the health of the artillery, and utilizing these index parameters to construct an evaluation factor set. Secondly, constructing the evaluation set through the definition of the fire system health level. Then adopting the entropy method and gray clustering method to assess the health status of each key unit of the fire system. Finally, establishing the fuzzy evaluation matrix according to the assessment results, and the combination weighting method is used to obtain the combination weights. Then, obtaining the comprehensive evaluation result of the health status of the fire system through the fuzzy comprehensive evaluation method. In order to verify the effectiveness of the method, the measured data and simulation data are used to verify our method. The experimental results show that the method can quickly and accurately obtain the fire system health evaluation results.
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