Non-contact measurements of machining temperatures were performed with optical pyrometer when drilling particle（B4C） reinforced metal matrix composites（MMCs） with different drills. The effect of particle content, ...Non-contact measurements of machining temperatures were performed with optical pyrometer when drilling particle（B4C） reinforced metal matrix composites（MMCs） with different drills. The effect of particle content, cutting speed, feed rate and tool material on the maximum drilling temperature was investigated. The drilling parameters were optimized based on multiple performance characteristics in terms of the maximum cutting temperature and tool wear. According to the results, the most influential control factors on the cutting temperatures are found to be particle fraction, feed rate and interaction between the cutting speed and particle content, respectively. The influences of the cutting speed and drill material on the drilling temperature are found to be relatively lower for the used range of parameters. Minimum cutting temperatures are obtained with lower particle fraction and cutting speed, with relatively higher feed rates and carbide tools. The results reveal that optimal combination of the drilling parameters can be used to obtain both minimum cutting temperature and tool wear.展开更多
To evaluate measurement uncertainty for small sample size and measurement data from an unknown distribution, we propose a grey evaluation method of measurement uncertainty based on the grey relation coefficient. The u...To evaluate measurement uncertainty for small sample size and measurement data from an unknown distribution, we propose a grey evaluation method of measurement uncertainty based on the grey relation coefficient. The uncertainty of measurement is analyzed using grey system theory, and the defects of the grey evaluation model of measurement uncertainty (GEMU) are studied. We then establish an improved grey evaluation model of measurement uncertainty (IGEMU). Simulations show that the precision of IGEMU is greater than that of GEMU, and that sample size has only a small effect on the precision of IGEVU. In particular, IGEMU is applied to evaluating measurement uncertainty for small sample size and measurement data from an unknown distribution. The measurement uncertainty of total profile deviation, which is measured by the CNC gear measuring center, can be evaluated by a combination of IGEMU and the Monte Carlo method.展开更多
文摘Non-contact measurements of machining temperatures were performed with optical pyrometer when drilling particle（B4C） reinforced metal matrix composites（MMCs） with different drills. The effect of particle content, cutting speed, feed rate and tool material on the maximum drilling temperature was investigated. The drilling parameters were optimized based on multiple performance characteristics in terms of the maximum cutting temperature and tool wear. According to the results, the most influential control factors on the cutting temperatures are found to be particle fraction, feed rate and interaction between the cutting speed and particle content, respectively. The influences of the cutting speed and drill material on the drilling temperature are found to be relatively lower for the used range of parameters. Minimum cutting temperatures are obtained with lower particle fraction and cutting speed, with relatively higher feed rates and carbide tools. The results reveal that optimal combination of the drilling parameters can be used to obtain both minimum cutting temperature and tool wear.
基金supported by the National Natural Science Foundation of China (Grant Nos. 61108052 and 61108073)the Technology Program of the Educational Office of Hei Longjiang Province in China (Grant No.11553016)
文摘To evaluate measurement uncertainty for small sample size and measurement data from an unknown distribution, we propose a grey evaluation method of measurement uncertainty based on the grey relation coefficient. The uncertainty of measurement is analyzed using grey system theory, and the defects of the grey evaluation model of measurement uncertainty (GEMU) are studied. We then establish an improved grey evaluation model of measurement uncertainty (IGEMU). Simulations show that the precision of IGEMU is greater than that of GEMU, and that sample size has only a small effect on the precision of IGEVU. In particular, IGEMU is applied to evaluating measurement uncertainty for small sample size and measurement data from an unknown distribution. The measurement uncertainty of total profile deviation, which is measured by the CNC gear measuring center, can be evaluated by a combination of IGEMU and the Monte Carlo method.
