LVQ神经网络分类器在润滑油磨粒识别上的应用

论述了一种用计算机图象系统进行磨粒识别的方法。该系统采用ＬＶＱ神经网络作为分类器来识别润滑油中磨粒的表面结构，从而确定机器的工作状况。识别过程包括４个阶段：（１）获取磨粒的铁谱图像；（２）将图像进行数字化并表提取特征；（３）对从特征集中提取的训练数据进行学习；（４）对磨粒进行识别并且生成机器运行状况的结果报告。对内燃机的滑动和滚动的几类磨粒进行识别的结果表明，这种方法可成功地用于磨粒识别。

RECOGNITION OF WEAR PARTICLES IN LUBRICATING OIL USING LVQ NEURAL CLASSIFIER

A technique for wear particle identification using computer vision system is described. The computer vision system employs LVQ Neural Networks as classifier to recognize the surface texture of wear particles in lubricating oil and determine the conditions of machines. The recognition process includes four stages:(1)capturing image from ferrographies containing wear particles;(2) digitising the image and extracting features;(3) learning the training data selected from the feature data set;(4) identifying the wear particles and generating the result report of machine condition classification. To verify the technique proposed here, the recognition results of several typical classes of wear particles generated at the sliding and rolling surfaces in a diesel engine are presented.