An effective rough surface model is the foundation for the evaluation of the contact, lubrication, friction and wear behaviors of engineering assemblies. This study first presented an investigation of the time series method, linear transformation method and Johnson transformation system. Then, an improved rough surface modeling method was proposed. The solving of the autocorrelation coefficient matrix was transformed to a nonlinear least squares problem and the analytical gradient formula was derived. The fast Fourier transform (FFT) method was further employed to improve the computational efficiency. Using this approach, rough surfaces with different autocorrelation function (ACF) and statistical parameters were generated and then compared with the prescribed surfaces. It was found that the ACF, areal autocorrelation function (AACF) and statistical parameters of the simulated surfaces were consistent with those of the prescribed surfaces. Moreover, an extremely good agreement was also found between the measured and generated grinding surfaces in terms of ACF, AACF and statistical parameters, which further proved the validity of the proposed method at large autocorrelation length. Therefore, the technique developed in this study may serve as a novel approach to generate rough surfaces with high efficiency and accuracy.
Tribology International – Elsevier
Published: Mar 1, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.
All for just $49/month
Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.
Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.
It’s easy to organize your research with our built-in tools.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera