共查询到19条相似文献,搜索用时 109 毫秒
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针对超精密车削表面,提出一种基于多波长散射光特性的表面粗糙度测量方法,以铝合金为例对该方法进行验证。首先建立超精密车削表面形貌—散射光模型并开展验证实验,定量实验结果证明建立的散射光模型平均误差仅为1%。基于散射光模型研究刀痕纹理方向、刀痕宽度(每转进给量)和刀痕高度(表面粗糙度峰谷值)对镜像光反射率的影响,研究结果证明表面粗糙度是影响镜像光反射率的关键因素。在此基础上进一步建立300~700 nm波长范围内镜像光反射率平均值和表面粗糙度之间的定量关系,基于超精密车削表面的测量结果对该定量关系进行验证。所提出新方法获得的粗糙度测量结果与原子力显微镜测量结果吻合,最大相对误差仅为7.5%。 相似文献
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基于遗传算法的超精密切削表面粗糙度预测模型参数辨识及切削用量优化 总被引:2,自引:0,他引:2
建立易于分析各切削用量对粗糙度影响关系的表面粗糙度预测模型和最优的切削用量组合,是超精密切削加工技术的不断发展的需要。针对最小二乘法和传统优化方法的不足,提出了将遗传算法用于超精密切削表面粗糙度预测模型的参数辨识,并用于求解最优切削用量,给出了金刚石刀具超精密切削铝合金的表面粗糙度预测数学模型和切削用量优化结果,进行了遗传算法和常规优化算法的比较,结果表明遗传算法较最小二乘法和传统的优化方法更适合于粗糙度预测模型的参数辨识及保证切削用量的最优。 相似文献
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精密超精密加工技术综述 总被引:2,自引:0,他引:2
根据未来工艺发展规划要求,积极探索国内外精密超精密加工技术,对该项技术的现状进行了分析,作出综述,并提出了实施该项技术的具体途径及所要考虑的问题. 相似文献
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采用陶瓷刀具进行淬硬轴承钢GCr15的硬车削加工试验,并通过正交试验分析和方差分析给出试验范围内的最优加工参数组合。基于所建立的表面粗糙度经验模型,分析切削速度、进给量和刀尖圆弧半径对表面粗糙度的影响规律。试验与仿真分析表明,增大刀尖圆弧半径可有效降低已加工表面的表面粗糙度,而提高切削速度可使表面粗糙度略有下降;当进给量增大时,表面粗糙度几乎线性增加。同时,进给量对表面粗糙度的影响最大,刀尖圆弧半径次之,而切削速度的影响微弱。 相似文献
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B.Y. Lee H. Juan S.F. Yu 《The International Journal of Advanced Manufacturing Technology》2002,19(4):295-301
The paper presents a system for measuring the surface roughness of turned parts using a computer vision system. The images
of specimens grabbed by the computer vision system are processed to obtain parameters of their grey levels (spatial frequency,
arithmetic mean value, and standard deviation). These parameters are used as input data to a polynomial network. Using the
trained polynomial network, the experimental result shows that the surface roughness of a turned part made of S55C steel,
measured by the computer vision system over a wide range of turning conditions, can be obtained with reasonable accuracy,
compared to that measured by a traditional stylus method. Compared with the stylus method, the computer vision system constructed
is a useful method for measuring the surface roughness of this material faster, at a lower cost, and with lower environmental
noise. 相似文献
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Machining trials were carried out on a G-17 cast iron using round and square-shaped pure oxide (≥99 vol. % Al2O3 + ≤ 1 vol. % ZrO2), mixed oxide (70 vol. % Al2O3 + 30 vol. % TiC) and silicon coarbide whisker-reinforced (75 vol. % Al2O3 + 25 vol. % SiC) ceramic tools in order to study the extent of damage on the machined surfaces. G-17 is a BS 1452 (1977) designation and equivalent to ANSI/ASTM A48-83 grade 40 designation. The test results show that the round-shaped ceramic tools produced better surface finish and less damage than square inserts under the cutting conditions investigated due to their increased nose radius, which increased the tool-workpiece contact area during machining. The surface finish deteriorates with prolonged machining and an increase in the depth of cut. The hardness values of the surface layer were generally above the average hardness value of the base material due to the hardening of the surface layer as a result of the high pressure, compressive stress and temperatures generated at the cutting edge during machining. A higher rate of hardening was observed when machining with the mixed oxide and SiC whisker-reinforced ceramic tools due, perhaps, to the relatively high temperatures generated at the higher cutting speed (500 m/min.) used. 相似文献
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不同的铣削加工工艺参数会影响加工表面形貌和表面粗糙度.考虑灰关联分析与神经网络法的各自优点,提出了一种新的基于灰关联神经网络模型进行表面粗糙度预测的模型.首先利用灰关联分析,将各因子与预测目标作关联性的排序,且把不必要的因子剔除,接着进行神经网络的训练及预测.将所提的预测模型运用到铣削加工的表面粗糙度预测中,构建出表面... 相似文献
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