摘要
针对起重机金属结构健康评估过程中模糊性与随机性并存的问题,提出一种基于云模型和EAHP的多层次分级评估方法。以云模型相关理论为基础,计算各评估指标隶属不同评判等级的确定度,实现模糊概念的随机表示。在评估指标赋权计算中,运用EAHP改进传统点值表示的判断矩阵,生成可信度更高的指标权重。根据各层指标的确定度和权重逐层计算得到评估对象的综合确定度,从而确定整机结构的健康等级。通过相关案例验证了该方法的准确性与有效性。
Aiming at the problem of the coexistence of fuzziness and randomness in structural health evaluation of crane,a multi-level hierarchical evaluation method based on cloud model and EAHP is proposed.On the basis of cloud model correlation theory,the determination degree of each evaluation index is calculated to realize the random representation of fuzzy concepts.In the weight calculation of evaluation index,the EAHP is used to improve the judgment matrix of traditional point value representation to generate more reliable index weight.According to the determination of each layer index and the weight of each layer,the comprehensive determination of the evaluation object is obtained.The effectiveness of the method are proved by relevant case studies.
作者
梅潇
王鑫
MEI Xiao;WANG Xin(School of Logistics Engineering,Shanghai Maritime University,Shanghai 201306,China)
出处
《机械设计与研究》
CSCD
北大核心
2020年第6期200-204,共5页
Machine Design And Research
基金
上海市扬帆计划省部级项目(19YF1418600)
上海市科学技术委员会科技创新行动计划重大专项(18DZ1100901,18DZ1100800)。
