Research On Surface Morphology Characteristics Of Metal Materials Resist Plant Abrasive Based On The Fractal And Wavelet Theory

Plant Abrasives versus metallic materials wear is a typical soft abrasivewear which widely exists in the agricultural machinery, agricultural andsubsidiary products processing field. The identification of this wearcondition, and an in-depth study of wear mechanism of which depend onthe the surface topography analysis of wear pair. The study found that,after wears the metal surface topography appearance to have randomsequence, the self-similarity and self-affine features. The traditionalcharacterization of worn surface roughness parameters is related to thescales of parameters, restricted by the measuring instrument and thesampling length restriction, its measurement result cannot be truly reflectthe true character of worn surface, while Wavelet and fractal theory ismeasurement tools which have nothing to do with scale make it possibleto study wear surface morphology. In this paper, graphics, fractal andwavelet technology as a means.Plant abrasive wear of metal materialsurface profile curve and surface grayscale images as the object of study,the worn surface morphology were studied, the results are as follows:(1)This article respectively used different calculation method offractal dimension of the surface profile of4kinds of materials, researchresults indicate that the box counting method、 the power spectrum andthe R/S analysis method of fractal dimension calculation error is bigger，but the semi-variance method and variation method of fractal dimensioncalculation error is smaller. So, the semi-variance method and variablemethod can be used to calculation of fractal dimension of plant abrasiveto metallic material wear surface; The study showed that t Study findsmaterial wear worn surface fractal dimension and weight loss are related,ground losses more severe, the fractal dimension is also bigger. (2)The application of b wavelet judgment method to analyze thesurface profile of the worn surface, the study found that There weredifferences in the b wavelet judgment analysis and semi-differencemethod and variation method. the b wavelet judgment have HighPrecision. It Change Law are coincident with the weight loss.(3)Introducing Multifractal Spectra into the metal wear surfacegray-scale image features，the research shows that there was a positivecorrelation between Multifractal Spectra characteristic value and wearweight loss. The greater the wear weight loss, the fractal characteristics ofbody spectral width the greater. The Multifractal Spectra characteristicvalue positive and negative has relation with Shape of the curve in thecoordinates. When the Spectrum Subtraction more than zero was the lefthook-shaped, its surface dominated by peak and is more smooth; Whenthe Spectrum Subtraction less than zero was the right hook-shaped, itsSurface dominated by Valley and more rough.(4)Using wavelet analysis method to extract characteristic parametersof wear surface of metallic materials. Decomposing The SEM mage indifferent directions and seeking energy ratio in different directions. Theanalysis results show that low-frequency energy Equal to low-frequencyenergy, the proportion of the energy distribution in different directionscan be used as characterization parameters of the worn surface features.