On-linediscrimination of diamond roller profile state
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摘要: 金刚石滚轮形面修形技术是制金刚石滚轮的关键技术之一,目前常采用金刚石砂轮磨削法对金刚石滚轮进行精密修形。金刚石滚轮在精密修形过程中,其表面轮廓Pv值是考量滚轮修形的重要指标,在目前的加工检测中,常是工人停机取下滚轮并放置于轮廓仪上检测,极大的增加了滚轮制作的时间和成本,为此,对在五轴加工机床上的金刚石滚轮沿轮廓面纵向磨削修整过程所产生的振动信号,提出一种基于小波包系数和随机森林的在线检测方法。此方法在进行状态识别时的准确率在92%,具有实际应用价值。Abstract: Diamond roller profile grinding is one of the key technologies for manufacturing diamond rollers. Currently, diamond grinding wheels are commonly used for precision profile grinding of diamond rollers. The surface contour Pv value of the diamond roller is an important indicator for assessing the profile grinding process. In current machining inspections, workers often need to stop the machine, remove the roller, and place it on a contour gauge for measurement, which significantly increases the time and cost of roller production. Therefore, this paper proposes an online detection method based on wavelet packet coefficients and random forest for the vibration signals generated during the longitudinal grinding and trimming process of diamond rollers on a five-axis machining center. The accuracy of the proposed method in state recognition is 92%, indicating its practical application value.
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Key words:
- diamond roller /
- vibration signal /
- wavelet packet coefficients /
- online detection /
- random forest
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