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基于神经网络的掘进机截割头截齿的强度可靠性灵敏度设计 被引量:3

Reliability Sensitivity Design for Shearer Based on Artificial Neural Network
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摘要 由于煤岩材质的不均匀性及掘进机截割过程中往往会遇到其他的岩石成分,导致掘进机截割过程中截齿受到的载荷具有很大的不确定性,有必要对截齿工作过程中的强度可靠性进行研究。结合有限单元法、神经网络技术和可靠性理论,对截齿在极限载荷状态下的静强度可靠性及可靠性灵敏度进行分析,获得了截齿关键尺寸对截齿可靠度的影响大小排序,从而为截齿的可靠性设计提供指导。 Because of the non-uniformity of the coal,force loading on shearer is probabilistic. Reliability-based analysis for the shearer is important. An algorithm is presented for evaluating the analytical sensitivity of reliability for shearers. In doing so, based on the stress-strength interference model, mean value first order reliability method, artificial neutral network and finite element method are extended to discuss the reliability for shearer with strength failure mode. Then the variation rules of reliability sensitivity are obtained and the effects of design parameters on reliability of shearer are obtained. The method presented in this paper provides the theoretical basis for reliability design of shearer.
出处 《煤矿机械》 北大核心 2012年第6期43-45,共3页 Coal Mine Machinery
关键词 截齿 强度可靠性 可靠性灵敏度 神经网络 shearer strength reliability reliability-based sensitivity neutral network
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