Research Of Combination Of EMD And Its Improved Methods And Dimensionless Analysis For Bearing Fault Positioning

Equipment diagnostic is a kind of technology that measure equipmentoperation status information and analysis the process to determine whether ornot the device normally operating using the appropriate means of detection. Thetechnology can not only identify the location and cause of the fault as soon aspossible, but also predict the development trend. Informally, equipmentdiagnostic technology is like “doctor”, and the diagnosis object is like “patients”.The doctor for the patient is the most vivid metaphor of the fault diagnosis,which usually covers “monitoring” and “diagnosis” two levels of meaning. Withthe rapid advance of mechanization level, the device diagnostics technologyfaces more severe tests.On the basis of existing research and in combination with related researchbackground of the subject, this paper put forward a simple, quick and practicalbearing fault diagnosis technology using the advanced dimensionless analysismethod, empirical mode decomposition (EMD), local mean decomposition(LMD) and genetic programming. And it is applied to fault diagnosis of rotating machinery bearings. The main content is as follows:(1) In view of the vibration signal itself is more complex and seriouslypolluted by noise and other disturbance signal, thus the vibration signal need tobe pretreated. And the EMD technique has certain advantages to remove noisejamming signal, thus the fusion to the advanced dimensionless analysistechnology to process the bearing fault characteristic information offers anexplanation from the feasibility and validity of this method.(2) As there will be issues such as false component and endpoint effectwhen dealing with the vibration signal, it is necessary to improve the EMD.LMD is a modified form, which is particularly suited to handle multi-componentmodulation signal, effectively suppresses the end effect exists in EMD and theproblem of false weight has also been solved. Based on these advantages, thispaper proposes bearing fault diagnosis method combined LMD withdimensionless analysis. The method shows its performance superior to EMDtechnology both in theory and practical application.(3) In view of the basic dimensionless index for some fault typeclassification defects and poor ability of the small number, in this paper, geneticprogramming (GP) is applied to dimensionless analysis as its certain advantagesin the characteristic structure and the selection. Firstly, EMD is carried out onthe vibration data processing. Then, build the best composite dimensionlessindex for fault status classification taking advantage of the GP. Finally,experiment to verify the classification performance of the new indicators through the bearing failure analysis...