Study Of Computer Identification And Analysis System For Wear Debris

Ferrography analysis technology for wear debris has been applied broadly in many aspects, such as inspection of machine operation state, failure diagnosis and preventive maintenance, because of its advantages of good effect and economical. However, the issue how to realize the automatization in ferrograph diagnosis has been brought forth owning to manipulative complexity and subjectivity in the judgement for traditional ferrography technology. Thus, the automatic recognition technology for wear debris is a focus research topic and many researchers, whether in overseas or domestic, have paid more attention on studying it last decades.The characteristic parameters of effective debris in a Ferrograph have been calculated in the present thesis, like area, perimeter, aspect ratio and granularity, in which some methods have been adopted such as smoothing, filtering and thresholding and so on, according to tribological theories and computer technologies and digital image preprocessing. Then, an essential database has been founded with these characteristic parameters. Using the related gray relational grade algorithms, a set of software system with C language has been programmed to analyze, recognize and judge the classification of unknown characteristic wear debris which is referring to the characteristic parameters database of standard wear debris. As a matter of fact, three types of wear debris can be classified by the present software programmed in this research, that is, normal, spherical and cutting debris can be identified. By analyzing and processing the actual ferrograph of wear debris from a used oil sample, the experimental results show that the effects of automatic recognition are equal to those of manual recognition, and the automatization of ferrographical diagnosis has been realized simply and partly, which will be helpful to improve the intelligence of the digital Ferrography system.