基于逼近理想解和模糊综合评价的机械产品元动作健康状态评估
Evaluation of the meta-action health state of mechanical products based on approximate ideal solution and fuzzy comprehensive evaluation
蔡易峰 1冉琰1
作者信息
- 1. 重庆大学机械与运载工程学院,重庆 400044;重庆大学机械传动国家重点实验室,重庆 400044
- 折叠
摘要
健康状态评估是机械产品高质量发展不可或缺的一环.从运动层面出发,以机械产品中的元动作单元为研究对象,提出一种基于逼近理想解和模糊综合评价的健康状态评估方法.首先,采用M-FMMECA方法,确定元动作单元的关键性能退化指标,给出元动作单元健康指数这一量化指标;接着,将逼近理想解法运用到元动作健康状态评估中,建立元动作单元健康状态量化模型;然后,在完成健康状态分级后,采用模糊综合评价法确定元动作单元健康状态隶属度函数,完成健康状态评估;最后,以某可靠性试验台锥齿轮转动元动作单元为例,进行健康状态评估方法的实例分析.研究表明,将逼近理想解与模糊综合评价结合,可以定量且更加全面地评估元动作单元健康状态.
Abstract
Health status assessment is an indispensable part of the high-quality development of mechanical products.Starting from the motion level,it proposes a health state assessment method based on approximate ideal solution and fuzzy comprehensive eval-uation method based on the meta-action unit in mechanical products as the research object.Firstly,the M-FMMECA method was used to determine the key degradation indicators of meta-action performance,and then the quantitative index of meta-action unit health index was given.Next,the approximate ideal solution was applied to the evaluation of meta-action health state,and a quantitative model of meta-action unit health state was established.Then,after completing the classification of health status,the fuzzy comprehensive evaluation method was used to determine the health status membership function of the meta-action unit,and the health status assessment was completed.Finally,taking the bevel gear rotation element action unit of a reliability test bench as an example,a case analysis of the health state assessment method was carried out.The results show that combining the approx-imation ideal solution with fuzzy comprehensive evaluation can quantitatively and comprehensively evaluate the health status of the meta-action unit.
关键词
元动作单元/逼近理想解法/模糊综合评价/健康状态评估Key words
meta-action unit/approximating the ideal solution/fuzzy comprehensive evaluation/health status assessment引用本文复制引用
基金项目
国家自然科学基金(52275473)
国家自然科学基金(51835001)
出版年
2024
国家科技期刊平台
NSTL
万方数据