Accuracy of Surface Roughness Parameters Determination

Experimental surface roughness research is tightly related with task about choice of measuring trace length on the surface under research. In fact, as the trace length is greater, as precisely parameter values can be obtained. But in practice, amount of measurements are limited, therefore it is necessary chose an optimal trace length. Moreover, accuracy of the parameter depends on profile tracing quality, data processing, and others factors. In our event, the most important output data are parameters Ra (average roughness), amount of zero n(0) and maximums m. For the trace length determining we use probability function theory method. Rough surface profile is described with normal stationary probability process h(x) [1], that has a mathematical expectation E{h(x)} = 0 and correlation function K(t). If is known parameter determination precision e, validity b, and measuring trace length, then can easy determine necessary amount of measurements. Also, as known dispersion and mathematical expectation values, can determine amount of measurements of parameters under research. Researching various processed surfaces, even in one cut-off length limits, amount of measurements fundamentally changes, what indicates onto necessary much carefully apply the methodical leadings