自由曲面表面加工质量的在线实时检测技术
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摘要
模具技术水平的高低,渐渐成为衡量一个国家制造业水平高低的重要标志,并在很大程度上决定着产品的质量、效益和新产品的开发能力。随着社会的发展,模具型面越来越多的呈现为复杂的自由曲面,其中模具型面加工质量对产品和模具本身质量、寿命都有相当大的影响,是决定零件功能特性的重要因素之一。如果模具表面的粗糙度提高一个等级,其寿命将会得到大大提高。现在,人们日益认识到模具型面表面粗糙度检测的重要性,恰当的测量方法与设备不但可以帮助用户轻而易举地提高产品的质量,更会提高生产效率。为此,对模具型面表面粗糙度的检测就显得尤为重要了。未来中国模具的发展会越来越复杂化,精度要求也越来越高。品种多样化,变化也就更迅速,这就要求检测设备除了精度高、测量准确,也要更加灵活才能跟上发展的脚步。
本设计主要针对机器人在对零件进行抛光研磨加工后工件的表面质量状况及检测的需要,拟设计一套在线实时粗糙度检测系统,可以为机器人下一步的加工控制提供信息。
在本文中,首先简要叙述了当前国内外关于表面粗糙度检测的发展情况;综合考虑各种检测方法的优劣后,针对模具型面等复杂自由曲面自动抛光系统应用的需要,本文设计了一套可实现曲面表面粗糙度在线检测的子系统,测量系统基于嵌入式处理器,使用激光测头,并配套使用高精度的移动控制装置。该设计是综合应用了传感测试技术、图形图像处理、机电控制等技术的嵌入式表面质量检测系统。本论文主要进行了以下研究:
系统利用激光测距的原理,通过精密测距传感器AT-2测量曲面到测头的Z向距离,用ARM芯片处理、计算,可得到曲面加工的表面粗糙度值Ra,ARM系统同时还用来完成对执行机构运动的控制。
详细分析了测头部分的工作原理和设计方法,给出了使用ARM实现控制测头的方法,介绍了驱动装置的选择及工作原理。
简单介绍了本检测系统的开发环境以及Windows CE5.0操作系统的实现。具体介绍了数据采集系统的总体设计和部分子系统的实现。重点介绍了对评定基准线的拟合算法和滤波算法,通过对一组数据的拟合结果证明曲线拟合算法在一定程度上适合于本曲面检测系统;通过对一正弦曲线的滤波结果,证明该滤波算法适合于ARM系统。
The level of mold technology gradually becomes an important symbol to evaluate a country’s manufacturing level, and largely determines the quality, benefit of the products and new product development capability. With the development of society, the die surface more and more appears as complex free curved surface. Machining quality of die surface has considerable influence to the quality and life of product and mold itself, which is one of the important factors in deciding the functional characteristics of components. If the mold surface roughness is increased by one level, its life will be greatly enhanced. Now, there is a growing awareness of the importance of the die surface roughness inspection. The appropriate measuring methods and equipment can not only help users to easily improve product quality, but will also improve production efficiency. To this end, the surface roughness inspection to die surface is particularly more important. The future development of China mold will be more and more complex, and accuracy requirement is also more and more high. Species diversity makes the change become even more rapidly, which requires testing equipment in addition to high precision, accurate measurement, and more flexible to keep up with the pace of development.
For the robot’s next step processing control to provide information, the paper is proposed to design a set of online and real-time roughness inspection system, which is mainly for the workpiece surface quality status and the need for testing after the robot in the polishing and grinding parts
In this paper, it first briefly described the current domestic and international developments on the surface roughness detection. Considering the pros and cons of various detection methods, aimed at application needs of the automatic polishing system about complex free surface such as the die surface, this paper designed a series of subsystem that could be achieved in-process checking of free-form surface roughness. The measurement system was based on the embedded processor using a laser probe, and supporting the use of high-precision mobile control devices. The design is a embedded surface quality inspection system which is comprehensive application of sensing test technology, graphics and video processing, electrical and mechanical control techniques. This thesis conducted the following study:
System is based on the principle of laser rangefinder, through the precise range-finding sensor AT-2 to measure the Z-distance between surface and the probe. The ARM chip processed and calculated the data that could be obtained the machining surface roughness value Ra. The ARM system was also used for the implementing agencies motion control.
Detailed analysis of work principle and design method about the detection head, given the controlling method of detection head using ARM, and introduced the selections and work principles of the driving devices on control part.
It briefly introduced the development environment of the detection system and the implementation of the Windows CE5.0 operating system, also specifically described the general design of the data acquisition system and implementation of some subsystems. Focused on the fitting algorithm and filter algorithm of baseline. To a certain extent, the curve fitting algorithm was proved to be suitable for the surface detection system by fitting a set of data. The filter algorithm was showed to be fit for the ARM system through a sine curve filtering result.
本设计主要针对机器人在对零件进行抛光研磨加工后工件的表面质量状况及检测的需要,拟设计一套在线实时粗糙度检测系统,可以为机器人下一步的加工控制提供信息。
在本文中,首先简要叙述了当前国内外关于表面粗糙度检测的发展情况;综合考虑各种检测方法的优劣后,针对模具型面等复杂自由曲面自动抛光系统应用的需要,本文设计了一套可实现曲面表面粗糙度在线检测的子系统,测量系统基于嵌入式处理器,使用激光测头,并配套使用高精度的移动控制装置。该设计是综合应用了传感测试技术、图形图像处理、机电控制等技术的嵌入式表面质量检测系统。本论文主要进行了以下研究:
系统利用激光测距的原理,通过精密测距传感器AT-2测量曲面到测头的Z向距离,用ARM芯片处理、计算,可得到曲面加工的表面粗糙度值Ra,ARM系统同时还用来完成对执行机构运动的控制。
详细分析了测头部分的工作原理和设计方法,给出了使用ARM实现控制测头的方法,介绍了驱动装置的选择及工作原理。
简单介绍了本检测系统的开发环境以及Windows CE5.0操作系统的实现。具体介绍了数据采集系统的总体设计和部分子系统的实现。重点介绍了对评定基准线的拟合算法和滤波算法,通过对一组数据的拟合结果证明曲线拟合算法在一定程度上适合于本曲面检测系统;通过对一正弦曲线的滤波结果,证明该滤波算法适合于ARM系统。
The level of mold technology gradually becomes an important symbol to evaluate a country’s manufacturing level, and largely determines the quality, benefit of the products and new product development capability. With the development of society, the die surface more and more appears as complex free curved surface. Machining quality of die surface has considerable influence to the quality and life of product and mold itself, which is one of the important factors in deciding the functional characteristics of components. If the mold surface roughness is increased by one level, its life will be greatly enhanced. Now, there is a growing awareness of the importance of the die surface roughness inspection. The appropriate measuring methods and equipment can not only help users to easily improve product quality, but will also improve production efficiency. To this end, the surface roughness inspection to die surface is particularly more important. The future development of China mold will be more and more complex, and accuracy requirement is also more and more high. Species diversity makes the change become even more rapidly, which requires testing equipment in addition to high precision, accurate measurement, and more flexible to keep up with the pace of development.
For the robot’s next step processing control to provide information, the paper is proposed to design a set of online and real-time roughness inspection system, which is mainly for the workpiece surface quality status and the need for testing after the robot in the polishing and grinding parts
In this paper, it first briefly described the current domestic and international developments on the surface roughness detection. Considering the pros and cons of various detection methods, aimed at application needs of the automatic polishing system about complex free surface such as the die surface, this paper designed a series of subsystem that could be achieved in-process checking of free-form surface roughness. The measurement system was based on the embedded processor using a laser probe, and supporting the use of high-precision mobile control devices. The design is a embedded surface quality inspection system which is comprehensive application of sensing test technology, graphics and video processing, electrical and mechanical control techniques. This thesis conducted the following study:
System is based on the principle of laser rangefinder, through the precise range-finding sensor AT-2 to measure the Z-distance between surface and the probe. The ARM chip processed and calculated the data that could be obtained the machining surface roughness value Ra. The ARM system was also used for the implementing agencies motion control.
Detailed analysis of work principle and design method about the detection head, given the controlling method of detection head using ARM, and introduced the selections and work principles of the driving devices on control part.
It briefly introduced the development environment of the detection system and the implementation of the Windows CE5.0 operating system, also specifically described the general design of the data acquisition system and implementation of some subsystems. Focused on the fitting algorithm and filter algorithm of baseline. To a certain extent, the curve fitting algorithm was proved to be suitable for the surface detection system by fitting a set of data. The filter algorithm was showed to be fit for the ARM system through a sine curve filtering result.
引文
[1] http://baike.baidu.com/view/90551.htm
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[4]叶闯.基于ARM系统的表面粗糙度测量仪的设计[D].桂林:桂林理工大学,2009.
[5]屠志恋.基于融合技术的嵌入式表面质量检测系统的研究[D].浙江:浙江工业大学,2006.
[6]杨旭东.表面粗糙度测量仪的工作原理分析及其改进方案[J/OL].贵州工业大学学报(自然科学版), 2001, 30(1):45-48. http://wenku.baidu.com/view/86ceec28bd64783e09122b6b.html.
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[10]高宏,李庆洋等.高分辨率光学激光轮廓仪[J].仪器仪表学报,1995,16(2):135-139.
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[13]丁汉,朱立民,熊振华.复杂曲面快速测量、建模及基于测量点云的RP和NC加工[J].机械工程学报,2003,39(11):28-37.
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[19] F.Forouzbakhsh,J.Rezanejad Gatabi,I. Rezanejad Gatabi. A new measurement method for ultrasonic surface roughness measurements[J]. Measurement, 2009,42:702-705.
[20]关国强.表面粗糙度检测技术发展概述[J].实用工艺技术, http://www.cqvip.com:42-43.
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[25]高紫俊.基于ARM嵌入式系统水泵效率检测仪的研制[D].哈尔滨:哈尔滨理工大学,2009.
[26]张仁杰,汤林,郑哲.基于ARM920T模块的深孔表面多点粗糙度自动检测装置[J].光学精密工程,2008,5(6):912-916.
[27]陈鼐.基于ARM的嵌入式数据采集与处理系统[D].南京:南京航空航天大学,2007.
[28] Zhanhong Li,Jianxin Liu. 2010 International Conference on Computational and Information Sciences, Chengdu, Sichuan, China, 2010[C]. Published by IEEE CPS in the IEEE conference proceedings,2010.
[29] Ghassan A.Al-Kindi,Bijan Shirinzadeh. An evaluation of surface roughness parameters measurement using vision-based data[J]. International Journal of Machine Tools & Manufacture, 2007,47:697-708.
[30]孔庆杰.基于QT/E和Linux的嵌入式工业打标系统设计[D].成都:西华大学,2010.
[31] LAP Laser. Laser distance sensor ATLAS 02-100 User Guide and Operating Manual, Rev.1.0e[S]. 2005,1.
[32] http://www.lap-laser.com/indallzh/products/sensors/atlas.html
[33]程卫民,陈岭丽.工件表面的形貌分析[J].测控技术,2005,24(5):37-39.
[34]周立功等. ARM嵌入式系统基础教程[M].北京:北京航空航天大学出版社,2005.
[35] http://wenku.baidu.com/view/eea7fb8a6529647d272852a9.html
[36] Kinco.步进电机/步进驱动器选型,KO01CN09-1012[P].
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[2] szforee.常见的几种机加工方法[EB/OL]. [2009,9,12]. http://www.szforee.cn/News/139.html
[3]王选逵.机械制造工艺学[M].北京:机械工业出版社,2008,01.
[4]叶闯.基于ARM系统的表面粗糙度测量仪的设计[D].桂林:桂林理工大学,2009.
[5]屠志恋.基于融合技术的嵌入式表面质量检测系统的研究[D].浙江:浙江工业大学,2006.
[6]杨旭东.表面粗糙度测量仪的工作原理分析及其改进方案[J/OL].贵州工业大学学报(自然科学版), 2001, 30(1):45-48. http://wenku.baidu.com/view/86ceec28bd64783e09122b6b.html.
[7] http://www.delcam.com
[8]屠志恋.嵌入式表面质量检测系统的研究[J].中国水运,2008,8(08):138-139.
[9]朱心雄.自由曲线曲面造型技术[M].北京:科学出版社,2000:88-111.
[10]高宏,李庆洋等.高分辨率光学激光轮廓仪[J].仪器仪表学报,1995,16(2):135-139.
[11]余廷浩.超精细表面微观形貌无接触在线检测仪的研制[D].成都:四川大学,2005.
[12]黄伟.基于双纵模同轴差动原理用于超精密加工在线检测的轮廓测量技术[D].成都:四川大学,2006.
[13]丁汉,朱立民,熊振华.复杂曲面快速测量、建模及基于测量点云的RP和NC加工[J].机械工程学报,2003,39(11):28-37.
[14] T.R.Kramer HH,E.Mession,F.M.Proctor,H.Scott. A feature-based inspection and machining system[J]. Computer-Aided Design,2001,33:653-669.
[15]谢金.自由曲面非接触式测量方法研究及系统研制[D].浙江:浙江大学,2003.
[16]付文智,李明哲,邓玉山等.非接触三维曲面测量仪及其在多点成形中的应用[C].第三届锻压装备与制造技术论坛特种加工技术研讨及产品信息交流会议论文集,2007.
[17]夏利民,谷士文,曾三友.基于形变模型由立体序列图像恢复物体的形状[J].计算机工程,2001,27(10):22-23.
[18]成思源,张湘伟.可变形B样条曲线曲面模型及其有限元求解[J].重庆大学学报,2003,26(2):75-77.
[19] F.Forouzbakhsh,J.Rezanejad Gatabi,I. Rezanejad Gatabi. A new measurement method for ultrasonic surface roughness measurements[J]. Measurement, 2009,42:702-705.
[20]关国强.表面粗糙度检测技术发展概述[J].实用工艺技术, http://www.cqvip.com:42-43.
[21] J.M.Richardson and K.A.March. Fusion of Multi-sensor Data[J]. Int. Journal of Robotic Research,1998,7(6).
[22]周玉凤,杜向阳.互换性与技术测量[M].北京:清华大学出版社,2008,12.
[23]董燕.公差配合与测量技术[M].北京:中国人民大学出版社,2008,11.
[24] http://wenku.baidu.com/view/1f1f4c335a8102d276a22f7c.html
[25]高紫俊.基于ARM嵌入式系统水泵效率检测仪的研制[D].哈尔滨:哈尔滨理工大学,2009.
[26]张仁杰,汤林,郑哲.基于ARM920T模块的深孔表面多点粗糙度自动检测装置[J].光学精密工程,2008,5(6):912-916.
[27]陈鼐.基于ARM的嵌入式数据采集与处理系统[D].南京:南京航空航天大学,2007.
[28] Zhanhong Li,Jianxin Liu. 2010 International Conference on Computational and Information Sciences, Chengdu, Sichuan, China, 2010[C]. Published by IEEE CPS in the IEEE conference proceedings,2010.
[29] Ghassan A.Al-Kindi,Bijan Shirinzadeh. An evaluation of surface roughness parameters measurement using vision-based data[J]. International Journal of Machine Tools & Manufacture, 2007,47:697-708.
[30]孔庆杰.基于QT/E和Linux的嵌入式工业打标系统设计[D].成都:西华大学,2010.
[31] LAP Laser. Laser distance sensor ATLAS 02-100 User Guide and Operating Manual, Rev.1.0e[S]. 2005,1.
[32] http://www.lap-laser.com/indallzh/products/sensors/atlas.html
[33]程卫民,陈岭丽.工件表面的形貌分析[J].测控技术,2005,24(5):37-39.
[34]周立功等. ARM嵌入式系统基础教程[M].北京:北京航空航天大学出版社,2005.
[35] http://wenku.baidu.com/view/eea7fb8a6529647d272852a9.html
[36] Kinco.步进电机/步进驱动器选型,KO01CN09-1012[P].
[37]徐欣,于红旗,易凡等.基于FPGA的嵌入式系统设计[M].北京:机械工业出版社,2004,9.
[38]杨宗德.嵌入式ARM系统原理与实例开发[M].北京:北京大学出版社, 2007,9.
[39] CHRIS MUENCH著,精英科技译. Windows CE权威指南[M].北京:中国电力出版社,2001.
[40]周立功等. PXA270&Windows CE5.0实验指导[M].广州:广州致远电子有限公司, 2007,4.
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