The analysis of oil in an operating machine is considered as a very useful means to assess the condition of the machine. However, classical techniques of oil analysis are strongly dependent on the analyst’s expertise to perform wear particle inspection, condition classification, colligation of the test results by ferrography, AES. and physical or chemical detection and interpretation of the possible existing faults in a machine. To solve these problems and realize the intelligence of oil analysis, a Web-based intelligence system for oil analysis has been devised. This system is composed of an automatic ferroscope controlled by a computer to obtain improved wear debris images, a platform to process the images and to connect the field analyst with the experts in machine diagnosis through internet and an intelligent software platform to evaluate the tribological conditions and diagnose the faults. Furthermore, some intelligent diagnosis methods used in the system are introduced.

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