摘要
针对当前机床轴承的可靠性评估不涉及使用过程中状态特征量的特点,提出了基于状态量监测维修的视情维修决策.首先,通过加速度传感器采集轴承的运行状态信息.然后,对其提取均方根、频率中心等状态特征量,并建立了以威布尔分布为失效率函数的比例风险模型(Weibull proportional hazard model,WPHM),再通过牛顿迭代法结合同类型部件的寿命数据估算出风险模型中的3个参数.最后,建立了基于威布尔比例风险模型的维修时机决策模型,利用同类型部件寿命数据确定维修的失效阈值,根据此阈值即可进行维修决策.结果表明:该决策能够明显提高机床轴承的可利用率,最大程度地发挥机床的有效寿命.
The traditional reliability evaluation of the bearings of machine tool is not related to the condition characteristics of the using process. A condition maintenance decision utilization of condition- based maintenance was proposed. First,operation condition information of the bearings was obtained by the senor,such as the acceleration senor. Then,the condition characteristics of the root mean square and frequency center were extracted,Weibull proportional hazard model （WPHM） was also establish,which regarded Weibull distribution as failure rate function. Then,combined with the lifetime data of similar parts, three parameters were estimated through Newton-Raphson method. Finally, a maintenance decision model based on WPHM was established. Using the similar type of parts lifetime data to determine the maintenance failure threshold,according to failure threshold,maintenance decision can be conducted. Results show that this maintenance decision model can improve the availability of the bearings greatly,and make full use of the effective life of the machine tools.
出处
《北京工业大学学报》
CAS
CSCD
北大核心
2016年第11期1617-1622,共6页
Journal of Beijing University of Technology
基金
国家科技重大专项资助项目(2012ZX04010021-001-004)
北京市教育委员会科技计划项目(KZ201410005026)
关键词
状态量监测维修
状态特征量
比例风险模型
牛顿迭代法
维修决策
condition-based maintenance
condition characteristics
proportional hazards models
Newton-raphson method
maintenance decision
