Modeling of grinding wheel topography based on a joint method of 3D microscopic observation and embedded grindable thermocouple technique
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The grinding wheel generally has a complicated topography for the irregularity of abrasive grits, which always has an important influence on the final quality of the grinding workpiece. In this paper, a joint method of microscopic observation and grindable thermocouple technique was adopted to model the wheel topography. The grinding wheel topography was first modeled through microscopic observation by an in-position 3D microscope KH-7700 installed on the grinding machine. Based on the measurement of grit sizes, shapes, and distributions through the 3D microscope, a wheel surface model was established and a static grit number model based on Rayleigh distribution was proposed. Moreover, a numerical model was given to validate the proposed Rayleigh distribution model of an active grit number. In order to investigate the real abrasive grit number in a grinding process, an embedded grindable thermocouple was used to detect the dynamic variation of temperature signals, which will reflect the variation of in-process wheel topography under different process parameters, machine status, and even the grit-workpiece interaction status. Through the experimental analysis, it can be concluded that the increase of depth of cut ap could help to greatly increase the active grit number to the grinding process, while the increase of workpiece speed Vw and decrease of wheel speed Vs could lead to a subtle increase of the grit number. Moreover, the active grit number is about one fourth to one third of the static grits. The contact arc length between the wheel (CBN) and the workpiece (Ti-6Al-4V) was calculated by the contact time from the workpiece surface temperature data, and it was found that the actual contact arc length was about 1.5~2 times of the geometric size.
KeywordsWheel topography Active grit number Contact arc length Microscopic observation Grindable thermocouple technique
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This project is supported by National Science and Technology Major Project of China (Grant No.2017ZX04005001).
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