Research On The Engine Wearing Analysis System Of The DMU Based On Lubricating Oil Inspection Methods

Mechanical wear is the major problem for industrial equipment and lubricating oil isimportant to reduce the wear and it has been a major research topic to build up the wear andlubrication oil for many years. Mechanical wear testing involves a lot of chemistry andchemical engineering and is one of the important research problems, People committe todetect oil morphology and component to monitoring mechanical equipment wear and theestablishment many methods through the lubricating oil change to analyze wear testingmachine.Based on the DF11type DMUs as the research target and the analysis of internalcombustion engine wear of oil detection method, determining the oil detection factor bymorphological analysis of locomotives and lubricating oil and establishing the suitable systemof DF11oil data, it is to wear the DMUs daily detection of internal combustion engine and theestablishment of LSSVR model and linear regression method to analyze and predict the twotrain datas. It is of great significance to wear of two vehicles and wear comparison of theconclusion of the two cars as well as the other chemical mechanical wear.Firstly we introduced the related knowledge and oil DMUs detection technology athome and abroad， summarize the oil liquid iron spectrum analysis, spectrum and otherequipment and oil physical and chemical progress. Next we get the drawings of thecorresponding spectral trend graph and the regression chart comparison of the direct readingFerrography and spectrometric trend graph of the DMU. We can judge wearing race conditionof each motor car by tracking the spectrometric of the spectral elements of each vehicle of theDMU in the same mileage circumstances. At the same time, we get wearing serious of the twomotor cars by the big and small wear particles trend comparison of the Ferrography in thesame mileage circumstances and analysis DMU two cars wear modeling, and two cars fittingdifference by using the least square support vector regression methods. In the third part wedesign the detection of DMUs oil of the overall system and the system of the DMU oildetection, and can get diesel engine running-in oil basic information, lubricating oil basicinformation, diesel engine performance parameter data information of the two motor cars withthe help of the Delphi7software. In the forth part we analysis and judge something about thedirect reading ferrography, analysis ferrography, spectroscopy, particle counter, surfaceroughness, conventional physicochemical index and other related parameters by computer. Wecan get the information of the total wear, wear severity, severity index, cumulative wear,cumulative wear severity, large particles percentage, small particles percentage, wearrelatively serious degree basing on the large particles percentage and the small particlespercentage of the direct reading Ferrography of the each motor car of the DMU. We also canjudge the oil using state based on the comparison of the viscosity, flash point, petroleum etherinsoluble, alkali, water trace determination of the two vehicles etc. The fifth part we get the information of the wear trend graph and regression comparison chart of the spectrum andmake a quantitative value and quantitative calculation of ratio on the wear rate and wear badlyat a running segment between the two motor cars with the help of the Delphi7through thetracking of the domestic" New Dawn" DMU and "Span" DMU locomotive relevant data formore than years combined with the analysis of ferrography, direct reading ferrography,spectroscopy, physical and chemical index analysis statistically with the help of the Delphi7software. Then this puts forward a comprehensive utilization of information fusiontechnology to improve the diesel engine wearing diagnosis’s reliability method.