高超,王生,王会,刘广照,吴国荣.砂带磨削表面粗糙度理论预测及灵敏度分析[J].表面技术,2018,47(11):295-305.
GAO Chao,WANG Sheng,WANG Hui,LIU Guang-zhao,WU Guo-rong.Theoretical Prediction and Sensitivity Analysis of Surface Roughness of Abrasive Belt Grinding[J].Surface Technology,2018,47(11):295-305 |
| 砂带磨削表面粗糙度理论预测及灵敏度分析 |
| Theoretical Prediction and Sensitivity Analysis of Surface Roughness of Abrasive Belt Grinding |
| 投稿时间：2018-02-13 修订日期：2018-11-20 |
| DOI：10.16490/j.cnki.issn.1001-3660.2018.11.042 |
| 中文关键词: 电镀金刚石砂带 钢化玻璃 磨削 粗糙度 理论模型 灵敏度 |
| 英文关键词:electroplated diamond belt tempered glass grinding roughness theoretical model sensitivity |
| 基金项目: |
| 作者 | 单位 |
| 高超 | 1.江苏科技大学 机械工程学院，江苏 镇江 212003 |
| 王生 | 1.江苏科技大学 机械工程学院，江苏 镇江 212003 |
| 王会 | 1.江苏科技大学 机械工程学院，江苏 镇江 212003 |
| 刘广照 | 1.江苏科技大学 机械工程学院，江苏 镇江 212003 |
| 吴国荣 | 2.东南大学 机械工程学院，南京 210000 |
|
| Author | Institution |
| GAO Chao | 1.School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China |
| WANG Sheng | 1.School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China |
| WANG Hui | 1.School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China |
| LIU Guang-zhao | 1.School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China |
| WU Guo-rong | 2.School of Mechanical Engineering, Southeast University, Nanjing 210000, China |
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| 中文摘要: |
| 目的 以钢化玻璃磨边为研究对象，建立金刚石砂带磨削表面粗糙度理论预测模型，并分析粗糙度对各工艺因素的灵敏度。方法 首先，采用多因素线性回归分析建立了关于磨削工艺参数的粗糙度理论预测模型；其次，通过正交试验研究了磨削压力、砂带线速度和砂带张紧力对粗糙度和材料去除率的影响大小，并得到了工艺参数的优水平组合；再次，根据正交试验结果计算了粗糙度理论预测模型的数学表达式，同时，建立了灵敏度模型来进行工艺因素的灵敏度分析和工艺参数的区间优化；最后，利用随机试验验证了粗糙度理论预测模型的准确性。结果 极差分析可知，RA（0.137）?RC（0.068）?RB（0.016），MC（6.828）?MA（5.228）?MB（1.784），磨削工艺参数的优水平组合为A2B3C3。电镀金刚石砂带磨削表面粗糙度理论预测模型的表达式为 。各工艺参数的优选区间为：磨削压力10~20 N，线速度15~30 m/s，张紧力40~60 N。随机试验可得，粗糙度理论预测模型的相对误差大小维持在5.5%~10%。结论 关于工艺因素对磨削质量的影响，磨削压力最大，砂带张紧力次之，砂带线速度最小。关于工艺因素对材料去除率的影响，砂带张紧力最大，磨削压力次之，砂带线速度最小。磨削压力为18 N、砂带线速度为30 m/s、砂带张紧力为55 N时，磨削表面质量最好，且材料去除率较高。试验参数范围内，粗糙度对磨削压力的灵敏度随磨削压力的增加而下降，对砂带线速度和砂带张紧力的灵敏度随着二者的增加而增加。15组随机试验表明，粗糙度理论预测模型具有较高的可靠性和准确性。 |
| 英文摘要: |
| The work aims to adopt the edge-grinding of tempered glass as the research object to establish the theoretical prediction model of the surface roughness of diamond abrasive belt grinding and analyze the sensitivity of the roughness to the process factors. Firstly, the theoretical prediction model of roughness for grinding process parameters was established by multi factor linear regression analysis. Secondly, the influences of grinding pressure, line speed and tensioning force of abrasive belt on the roughness and material removal rate were studied by orthogonal test, and the optimum combination of process parameters was obtained. Thirdly, the mathematical expression for theory prediction model of roughness was calculated according to the orthogonal test results. Meanwhile, the sensitivity models were established for sensitivity analysis of process factors and optimization of process parameters. Finally, the accuracy of the roughness theory prediction model was verified by random experiments. From the range analysis, RA(0.137)?RC(0.068)?RB(0.016) and MC(6.828)?MA(5.228)?MB(1.784) and the excellent level combination of grinding process parameters was A2B3C3. The expression of the theoretical prediction model for surface roughness of electroplated diamond abrasive belt grinding was described as and the optimum selection interval of each process parameter was grinding pressure of 10~20 N, linear velocity of 15~30 m/s and tensioning force of 40~60 N. From the random tests, relative error of roughness theory prediction model was maintained at 5.5%~10%. The influence of process factors on roughness is significantly contributed by grinding pressure and then slightly caused by tensioning force, while line speed has the least influence. The influence of process factors on material removal rate is seriously caused by tensioning force and then slightly contributed by grinding pressure, while line speed still has the least influence. The grinding quality is the best and the material removal rate is the highest when the grinding pressure is 18 N, the belt line speed is 30 m/s, and the belt tensioning force is 55 N. In the range of test parameters, the sensitivity of roughness to grinding pressure decreases with the increase of grinding pressure, and the sensitivity to linear velocity and tensioning force increases with the increase of the two factors. The 15 sets of random tests show that the roughness theory prediction model has high reliability and accuracy. |
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