Research And Development Of Machinery Oil Pollution On-line Monitoring System Based On Image Processing

In this paper, the problems of oil pollution examination and wear debris identification are studied in oil pollution on-line monitoring system, furthermore, an analysis system of oil particles pollution is carried out for monitoring the wear debris of an engine bearing test. Based on the engineering background, the main research work is introduced as follows:1. Research on the methods of image processing. According to the characteristics of micro-flow oil, a new method for image quality descending analysis to the motion blur images based on the Kalman motion model is presented and a new method for target extraction is proposed based on the background segmentation technology in the paper.2. Oil pollution examination. Firstly, according to the evaluation method and grading partition, different dimension parameters are calculated based on different judging standards of pollution grading; Then, a new method for calculating micro-flow oil volume is presented according to oil speed field analysis in micro-piping; Finally, the possible errors of system are discussed from two aspects of particle size and number.3. Research on the wear debris identification. The classification parameters are chosen depending on the analysis of particles morphologic characteristics. A new arithmetic combined the SVM and the Nearest Neighbor is studied to identify the wear debris accurately and rapidly.4. Development of oil pollution on-line monitoring prototype system. Firstly, the hardware configuration of system is improved and the analysis software system of oil particles pollution is designed. Then, some key problems of system are discussed. Finally, contrastive experiments are designed to validate the methods of oil pollution examination calculation and wear debris identification introduced in this paper effective.