Abstract
According to the consistency between multi-scale decompositions and self-similarity in both wavelet transform and fractal theory, a new method has been developed to extract the feature parameter of wear particle group on the ferrographic image for diesel engine lubricants. The algorithm of minutiae extraction have been carried out by wavelet transform approach and the fractal dimension, and then the feature parameter can be obtained for the wear particle group on the ferrographic image. The fractal dimension D reflects the ferrographic image character in the scale and the amount of wear particle group, which can be used as a comprehensive feature parameter. The metal-ceramic nano-lubricant, which has been applied in the wear test of cylinder and piston-ring material from MAN B&WS50MC marine diesel engine, represent that the wear is speedup suitably, and then the fractal dimension D has consistency with the results of ferrographic analysis.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
