Improvement on On-line Ferrograph Image Identification

WU Tonghai; WANG Weigang; WU Jiaoyi; MAO Junhong; XIE Youbai

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Improvement on On-line Ferrograph Image Identification

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A newly developed on-line visual ferrograph(OLVF) gives a new way for engine wear state monitoring. However, the reliability of on-line wear debris image processing is challenged in both monitoring ship engines and the Caterpillar bench test, which weren’t reported in previous studies. Two problems were encountered in monitoring engines and processing images. First, small wear debris becomes hard to be identified from the image background after monitoring for a period of time. Second, the identification accuracy for wear debris is greatly reduced by background noise because of oil getting dark after running a period of time. Therefore, the methods adopted in image processing are examined. Two main reasons for the problems in wear debris identification are generalized as follows. Generally, the binary threshold was determined by global image pixels, and was easily affected by the non-objective zone in the image. The boundary of the objective zone in the binary image was misrecognized because of oil color becoming lighter during monitoring. Accordingly, improvements were made as follows. The objective zone in a global binary image was identified by scanning a column of pixels, and then a secondary binary process confined in the objective zone was carried out to identify small wear debris. Linear filtering with a specific template was used to depress noise in a binary image, and then a low-pass filtering was performed to eliminate the residual noise. Furthermore,the morphology parameters of single wear debris were extracted by separating each wear debris by a gray stack, and two indexes, WRWR (relative wear rate) and WRWS (relative wear severity), were proposed for wear description. New indexes were provided for on-line monitoring of engines.

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《中国机械工程学报：英文版》 |2010年第1期|1-6|共6页
作者
WU Tonghai; WANG Weigang; WU Jiaoyi; MAO Junhong; XIE Youbai;
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作者单位

Theory of Lubrication and Bearing Institute;

Xi＇an Jiaotong University;

Xi＇an 710049;

China;

Post-doctoral Research Center of Material Science and Engineering;

Xi＇an Jiaotong University;

Xi＇an 710049;

China;

School of Mechanical Engineering;

Shanghai Jiao Tong University;

Shanghai 200030;

China;

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原文格式 PDF
正文语种 chi
中图分类摩擦与磨损;
关键词
图像识别; 在线铁谱; 发动机台架试验; 磨损状态监测; 目标区域; 磨粒识别; 图像处理; 背景噪音;

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专利

1. Improvement on On-line Ferrograph Image Identification [J] . WU Tonghai ,WANG Weigang ,WU Jiaoyi . 中国机械工程学报 . 2010,第001期
2. Intelligent Identification of Wear Mechanism via On-line Ferrograph Images [J] . WU Tonghai ,PENG Yeping ,SHENG Chenxing . 中国机械工程学报 . 2014,第002期
3. 基于On-line Boosting的多相机大视场目标跟踪 [C] . Hu Liang ,胡亮 ,Zhao Chunhui . 第六届中国信息融合大会 . 2014
4. Image Filtering Improvement for Producing Artistic Images [A] . AHMED A.HUSSEIN . 2013

Improvement on On-line Ferrograph Image Identification

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