基于组合赋权法的采煤机健康状态评估方法研究
Study on health assessment method of shearer based on combination weighting method
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摘要: 采煤机作为煤矿开采的核心设备，结构复杂、运行环境恶劣、采煤落煤时受巨大负载冲击，易发生各种故障导致停机停产。因此，采煤机的健康状态直接影响煤矿企业生产效益。针对采煤机健康状态评估难的问题，提出一种基于组合赋权法的采煤机健康状态评估模型，根据采煤机运行特点构建其健康状态指标体系，采用基于层次分析法与熵权法的组合赋权法得到同时具有主观与客观意义的综合权重；依据灰色聚类法与模糊综合评价法分别完成对采煤机关键部件及整机的健康状态评估。仿真结果表明：基于组合赋权法所得状态评估结果准确率为84.33%，高于层次分析法或熵权法单一使用所得评估结果的准确率。该方法可有效解决采煤机状态评估困难的问题，为后续寿命预测与维护决策奠定基础。Abstract: As the core equipment for coal mining, the shearer has complicated structure, poor operating environment, and is susceptible to huge loads at the time of mining and coal falling, causing various failures and shutdown. Therefore, the health status of the shearer directly affects the production efficiency of coal mining enterprises. In view of the difficulty of assessing the health status of the shearer, a shearer′s health status evaluation model based on the combined weighting method is proposed. Firstly, according to the operation characteristics of the shearer, the health status indicator system is constructed. The combined weighting method based on the analytical hierarchy process and the entropy weight method is used to obtain the comprehensive weights with both subjective and objective meanings. According to the gray clustering method and the fuzzy comprehensive evaluation method, the assessment of the health status of the key components of the shearer and the complete machine were completed. The simulation results show that the accuracy of the state evaluation results based on the combination weighting method is 84.33%, which is higher than the accuracy of the evaluation results obtained by using the analytic hierarchy process method or the entropy weight method. The method can effectively solve the problem of difficulty in the state evaluation of the shearer, and lays a foundation for the subsequent life prediction and maintenance decision.
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