电感式磨粒在线监测传感器结构参数优化  

Optimization of structural parameters of inductive abrasive online monitoring sensor

作　　者：苏连成[1] 崔雪 SU Liancheng;CUI Xue(School of Electrical Engineering,Yanshan University,Qinhuangdao,Hebei 066004,China)

机构地区：[1]燕山大学电气工程学院,河北秦皇岛066004

出　　处：《燕山大学学报》2021年第1期51-57,69,共8页Journal of Yanshan University

基　　金：河北省自然科学基金资助项目(F2018203256)。

摘　　要：润滑油液中金属磨损颗粒的浓度和尺寸大小能够反映系统的健康状况,为实现对油液磨粒上述信息的实时监测,基于三线圈电感式磨粒监测传感器数学模型,分析了传感器的灵敏度与线圈结构参数的关系。同时为满足在线监测系统的需求,提出了基于改进的粒子群算法来优化传感器参数,在不同迭代阶段实现对参数的自适应调整,以平衡局部和全局搜索能力,将励磁线圈的长度、励磁线圈与感应线圈之间的距离以及管子的半径选定为合理的值,以达到最优配置。仿真结果验证了该方法能够有效提高传感器的灵敏度,具有一定的工程应用价值。The concentration and size of metal wear particles in lubricating oil can reflect the health status of the system.In order to realize real-time monitoring of the above information of oil wear particles,based on the mathematical model of three-coil inductive wear particle monitoring sensor,the relationship between the sensitivity of the sensor and the coil structure parameters is analyzed.At the same time,in order to meet the needs of on-line monitoring system,an improved particle swarm optimization algorithm is proposed to optimize the sensor parameters.The parameters can be adjusted adaptively at different iteration stages to balance the local and global search ability.The length of excitation coil,the distance between excitation coil and induction coil and the radius of the tube are considered.The simulation results show that this method can effectively improve the sensitivity of the sensor and has a certain engineering application value.

关 键 词：电感式传感器 磨粒监测 改进的粒子群算法 优化灵敏度 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]