Study And Realization Of Wear Debris Image Computer Analysis And Recognition Methods

The ferrography is a fault diagnosis method based on the analysis of wear debris. Ferrogram wear debris analysis technology has been applied broadly in many aspects, such as inspection of machine operation state, failure diagnose and preventive maintenance, because of its advantage of good effect and economical. The recognition of the wear particle is the core step of the ferrography. Because of the diversity and complicacy of the wear particle, the recognition procedure is carried out without guidance of mature theory. Currently, the recognition of the wear debris is carried out by experts. The development of computer image processing and artificial intelligence technologies would be helpful for the improvement of accuracy and automation of ferrography analysis. With the use of the basic theory and technique of image processing, the calculation of ferrogram cover area was studied. Then, based on the basic theory of ferrography fault diagnosis, regress analysis was applied to a set of oil sample ferrogram cover area. The feasibility of the method was than tested. With the use of the theory and technique of pattern recognition in the analysis of wear debris image, the use of neural network in the recognition of wear debris was studied. With all the studies above, a realization of the real time analysis of wear debris was given. The study will promote the use of wear debris analysis in the use of the machinery wear status monitor.The main contents of the thesis are as follows:1. The development and up-to-date status of wear particle analysis technology at home and abroad are evaluated synthetically. The study plan and main content are presented.2. Wear mechanism and classification including wear particle classification and characters are analyzed and discussed. The inner relations between each basic kind of wear particle and wear type, wear particle characters, wear mechanism, machine running status are analyzed and expatiated.3. According to digital image processing technologies, some methods such as smoothing, filtering are applied to process wear debris images. Wear debris segmentation of different background is also discussed as a main aspect.4. Lots of experiment was carried out and a set of oil samples ferrogram were studied to analyze the feasibility of quantitative analysis based on image processing.5. By analyzing and calculating the shape, color and texture characteristic parameters of wear particles, a complete set of wear particle quantification characterization comes into being.6. The use of neural network in the recognition of wear debris was discussed. With all the studies listed above and the combine of video collection, image processing and pattern recognition, a real time wear debris recognition system is designed and tested using the VC++.net programming platform. The system could give a real time collection, segmentation, characteristic parameters calculation and classification of wear debris image.