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| 油液在线监测系统中的磨粒识别 | |
| 引用本文： | 李绍成,左洪福,张艳彬.油液在线监测系统中的磨粒识别[J].光学精密工程,2009,17(3). |
| 作者姓名： | 李绍成 左洪福 张艳彬 |
| 作者单位： | 1. 南京航空航天大学,机电学院,江苏,南京,210016 2. 南京航空航天大学,民航学院,江苏,南京,210016 3. 南京邮电大学,通信与信息工程学院,江苏,南京,210046 |
| 基金项目： | 国家高技术研究发展计划(863计划)，中国民航总局科技资金资助项目 |
| 摘 要： | 针对机械设备磨损状态监测要求,构建了基于显微图像分析的油液在线监测系统.根据系统的光路特点,对磨粒图像进行了基于彩色特征的转换,并通过与背景图像的差值处理来快速提取磨粒目标.基于最小二乘支持向量机设计了两类磨粒分类器,并利用粒子群优化算法对最小二乘支持向量机模型中的参数进行了优化选取.在此基础上,根据磨粒识别体系,设计了磨粒综合分类器.最后,利用铁谱分析技术对系统性能和识别效果进行了检验,结果表明,系统的识别精度达到95%以上,满足磨粒在线监测要求. |
| 关 键 词： | HT磨粒 机器磨损 在线监测 图像识别 支持向量机 粒子群优化算法 |
Wear debris recognition for oil on-line monitoring system |
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| LI Shao-cheng,ZUO Hong-fu,ZHANG Yan-bin.Wear debris recognition for oil on-line monitoring system[J].Optics and Precision Engineering,2009,17(3). | |
| Authors: | LI Shao-cheng ZUO Hong-fu ZHANG Yan-bin |
| Affiliation: | 1.College of Mechanical Engineering;Nanjing University of Aeronautics and Astronautics;Nanjing 210016;China;2.College of Civil Aviation;3.College of Communication and Information Engineering;Nanjing University of Posts and Telecommunications;Nanjing 210046;China |
| Abstract: | For the demands of wear on-line monitoring for mechanical equipment, an on-line oil monitoring system based on microscopic image analysis is constructed.According to the characteristic of system light route, the image of wear debris is converted into gray image based on its color feature, and the wear debris object is extracted by subtracting the background image from the wear debris image. The classifier for two kinds of wear debris is designed based on the least square support vector machines, and the par... |
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