嵌入式智能轴承信息感知测点优化方法

Optimization Method for Information Sensing Measuring Points of Embedded Smart Bearing

针对智能轴承结构和感知单元集成中信息感知测点综合最优选取困难的问题,提出了嵌入式智能轴承信息感知测点优化方法。以角接触球轴承为嵌入式智能轴承的轴承本体结构,结合有限元分析研究了考虑3种载荷下轴承外圈开槽前后不同测点的应力和变形信息响应分布及影响,并基于轴承温度建模理论计算了轴承不同感知测点的温度分布。考虑开槽对轴承变形的影响,提出了一种基于主成分分析的嵌入式智能轴承感知测点最优选择方法。研究结果表明,通过应力、变形和温度信息的评估分析,可实现嵌入式轴承集成感知的最优嵌入测点选择。

Aimed at the difficulty of selecting the optimal information sensing measuring points in integration of smart bearing structure and sensing unit, an optimization method for information sensing measuring points of embedded smart bearing is proposed. Taking a angular contact ball bearing as body structure of embedded smart bearing, the distribution and influence of stress and deformation information response of different measuring points before and after slotting of bearing outer ring under three kinds of loads are studied in combination with finite element analysis, and the temperature distribution of different sensing measuring points of the bearing is calculated based on bearing temperature modeling theory. Considering the influence of slotting on bearing deformation, an optimal selection method for sensing measuring points of embedded smart bearing based on principal component analysis is proposed. The research results show that the optimal embedded measuring point selection for integrated sensing of embedded bearing can be realized through evaluation and analysis of stress, deformation and temperature information.