Friction Viewed as a Random Process

A stationary cast-iron button sliding against a rotating cast-iron disk generated a time-varying friction signal. The signal was recorded using digital computer data-acquisition techniques. Sixty runs were taken, using different values for various parameters (such as load, velocity, and temperature). The data were analyzed on a digital computer by two different techniques. The first was a time-series analysis: the Fourier transform of each run was taken and the power spectral density of the run was studied. The second technique was a standard statistical analysis using the Kolmogorov-Smirnov goodness-of-fit test. From the two analyses, some interesting conclusions were made: 1 – the friction behaves like a random process, 2 – friction may be treated as a constant signal with superimposed white noise, 3 – the instantaneous coefficient of friction is normally distributed, 4 – friction is influenced by load and velocity, and 5 – the mean value and standard deviation are functionally related.