A newly developed on-line visual ferrograph(OLVF) gives a new way for engine wear state monitoring. However, the reliability of on-line wear debris image processing is challenged in both monitoring ship engines and the Caterpillar bench test, which weren’t reported in previous studies. Two problems were encountered in monitoring engines and processing images. First, small wear debris becomes hard to be identified from the image background after monitoring for a period of time. Second, the identification accuracy for wear debris is greatly reduced by background noise because of oil getting dark after running a period of time. Therefore, the methods adopted in image processing are examined. Two main reasons for the problems in wear debris identification are generalized as follows. Generally, the binary threshold was determined by global image pixels, and was easily affected by the non-objective zone in the image. The boundary of the objective zone in the binary image was misrecognized because of oil color becoming lighter during monitoring. Accordingly, improvements were made as follows. The objective zone in a global binary image was identified by scanning a column of pixels, and then a secondary binary process confined in the objective zone was carried out to identify small wear debris. Linear filtering with a specific template was used to depress noise in a binary image, and then a low-pass filtering was performed to eliminate the residual noise. Furthermore,the morphology parameters of single wear debris were extracted by separating each wear debris by a gray stack, and two indexes, WRWR (relative wear rate) and WRWS (relative wear severity), were proposed for wear description. New indexes were provided for on-line monitoring of engines.
As one of the most wear monitoring indicator, dimensional feature of individual particles has been studied mostly focusing on off-line analytical ferrograph. Recent development in on-line wear monitoring with wear debris images shows that merely wear debris concentration has been extracted from on-line ferrograph images. It remains a bottleneck of obtaining the dimension of on-line particles due to the low resolution, high contamination and particle's chain pattern of an on-line image sample. In this work, statistical dimension of wear debris in on-line ferrograph images is investigated. A two-step procedure is proposed as follows. First, an on-line ferrograph image is decomposed into four component images with different frequencies. By doing this, the size of each component image is reduced by one fourth, which will increase the efficiency of subsequent processing. The low-frequency image is used for extracting the area of wear debris, and the high-frequency image is adopted for extracting contour. Second, a statistical equivalent circle dimension is constructed by equaling the overall wear debris in the image into equivalent circles referring to the extracted total area and premeter of overall wear debris. The equivalent circle dimension, reflecting the statistical dimension of larger wear debris in an on-line image, is verified by manual measurement. Consequently, two preliminary applications are carried out in gasoline engine bench tests of durability and running-in. Evidently, the equivalent circle dimension, together with the previously developed concentration index, index of particle coverage area(IPCA), show good performances in characterizing engine wear conditions. The proposed dimensional indicator provides a new statistical feature of on-line wear particles for on-line wear monitoring. The new dimensional feature conveys profound information about wear severity.
The roller-scraper tribosystem of automatic teller machine(ATM) plays an important role in reliable cash requests.However,the abrasive wear of the polymer tribosystem becomes a prominent problem when operating in sandy environment.The wear behavior of the tribosystem in a simulated sandy environment has been experimentally studied previously.However the abrasive wear mechanism of roller-scraper tribosystems is still unknown to new design.The wear rates of polymer rollers were examined comprehensively and several jumping variations were found in the full data extent.Three wear stages were classified by the magnitude of wear rates,and different dominant wear mechanisms corresponding with different particle diameter were found by examining the worn surfaces.Accordingly a presumption was proposed that wear mechanisms in different stages were correlated with sand particles of different diameter.In a verification experiment,three typical wear mechanisms including cutting,ploughing,and wedging were found corresponding with different wear stages by scanning electron microscope(SEM) examination.A theoretical analysis was carried out with a simplified sphere particle intrusion model and the transfer conditions for different wear mechanisms were studied referring to the slip-field theory.As a main result,three typical wear models versus friction coefficient of particle/roller,and particle radius were mapped with variant hardness of the polymer roller and ratio of contact shear stress to bulk shear stress.The result illuminated the abrasive wear mechanism during particle intrusion.Particularly,the critical transition conditions gave the basis for improving the wear performance of roller-scraper tribosystems in a sandy environment.
