基于路面探测信息的清雪车自动控制研究
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摘要
本文结合国家经贸委“多功能路面清雪车”项目,针对路面探测信息状况,对清雪车雪铲自动控制系统进行研究,实现路面雪层厚度探测及清雪车雪铲自动避障功能。主要工作如下:
1.运用软件GprMaxV2.0建立含障碍物的积雪路面模型。针对探地雷达电磁波在不同介质交界面上的特性,对仿真的回波数据进行分析,说明了探地雷达的回波数据与路面信息之间的关系。通过对积雪路面进行探测试验,采集路面探测数据。利用MATLAB软件对采集数据进行分析,选择合适的控制算法和设定控制门限。
2.介绍了雪层厚度计算的理论基础,采用BP神经网络,计算积雪路面雪层厚度。通过结果对比和误差分析,说明了神经网络在雪层厚度计算中应用的可行性。
3.通过对液压控制系统进行分析比较,综合考虑清雪车清除冰雪的特点、要求及成本等因素,在已选取的控制算法基础上,选择电液开关控制系统作为清雪车工作装置的控制系统。建立清雪车雪铲自动控制系统,分析控制系统的构成。针对工作装置液压控制系统,介绍了对称阀控制非对称液压缸的传递函数,确定液压控制系统各元件参数,利用软件AMESim对液压控制系统进行仿真分析。
The ways to clean heaped snow on speedways, highways and urban streets in winter has been the research focus around the world over the years. Snow-cleaning work bears close relation to a series of issues such as social production, people’s daily lives, traffic safety and environmental protection in northern cities. With social development and the ever-increasing level of mechanical technology, people are pressed for an efficient and roboticized device to sweep snow in place of the conventional snow-cleaning method.
This research was conducted through the multifunction snow remover project sponsored by the State Economic and Trade Commission. Based on the road detection information obtained by GPR(ground penetration radar), the study is carried out on the automatic control system for the snow-remover’s shovel to effect the detecting of road snow thickness and fulfill the shovel’s automatic obstacle-avoiding function. The specific work involves:
(1)The forward model of the snow road with obstacles is established by using GprMaxV2.0 software and applying the basic principles of the electromagnetic wave theory. The detection echo data obtained from the simulated model is calculated. In light of the variant properties of the GPR electromagnetic wave at different medium interfaces, the echo data from the simulation is given a detailed analysis to explore the road surface information pattern from the radar echo data.
(2)The GPR is employed to carry out grouped detection experiments on the snow-heaping road surface to collect the echo data. The collected data are entered into the MATLAB software for analysis; the correlation coefficient method is selected as the control algorithm considering the difference among echo data curves. The existence of obstacles on the road surface is judged through calculating
1.运用软件GprMaxV2.0建立含障碍物的积雪路面模型。针对探地雷达电磁波在不同介质交界面上的特性,对仿真的回波数据进行分析,说明了探地雷达的回波数据与路面信息之间的关系。通过对积雪路面进行探测试验,采集路面探测数据。利用MATLAB软件对采集数据进行分析,选择合适的控制算法和设定控制门限。
2.介绍了雪层厚度计算的理论基础,采用BP神经网络,计算积雪路面雪层厚度。通过结果对比和误差分析,说明了神经网络在雪层厚度计算中应用的可行性。
3.通过对液压控制系统进行分析比较,综合考虑清雪车清除冰雪的特点、要求及成本等因素,在已选取的控制算法基础上,选择电液开关控制系统作为清雪车工作装置的控制系统。建立清雪车雪铲自动控制系统,分析控制系统的构成。针对工作装置液压控制系统,介绍了对称阀控制非对称液压缸的传递函数,确定液压控制系统各元件参数,利用软件AMESim对液压控制系统进行仿真分析。
The ways to clean heaped snow on speedways, highways and urban streets in winter has been the research focus around the world over the years. Snow-cleaning work bears close relation to a series of issues such as social production, people’s daily lives, traffic safety and environmental protection in northern cities. With social development and the ever-increasing level of mechanical technology, people are pressed for an efficient and roboticized device to sweep snow in place of the conventional snow-cleaning method.
This research was conducted through the multifunction snow remover project sponsored by the State Economic and Trade Commission. Based on the road detection information obtained by GPR(ground penetration radar), the study is carried out on the automatic control system for the snow-remover’s shovel to effect the detecting of road snow thickness and fulfill the shovel’s automatic obstacle-avoiding function. The specific work involves:
(1)The forward model of the snow road with obstacles is established by using GprMaxV2.0 software and applying the basic principles of the electromagnetic wave theory. The detection echo data obtained from the simulated model is calculated. In light of the variant properties of the GPR electromagnetic wave at different medium interfaces, the echo data from the simulation is given a detailed analysis to explore the road surface information pattern from the radar echo data.
(2)The GPR is employed to carry out grouped detection experiments on the snow-heaping road surface to collect the echo data. The collected data are entered into the MATLAB software for analysis; the correlation coefficient method is selected as the control algorithm considering the difference among echo data curves. The existence of obstacles on the road surface is judged through calculating
引文
[1] Michael Douglass Heiler. Artificial neural networks for the interpretation of ground penetrating radar data for infrastructure condition assessment [D]. America: Carnegie Mellon University, 1996:12-39.
[2] 倪观军.路用探地雷达数据处理算法研究[D]. 哈尔滨: 哈尔滨工业大学, 2004:1-10.
[3] 刘家学,汪卫民等. 探地雷达中目标的自适应检测与跟踪[J]. 中国民航学院学报, 2003,21(4):5-8.
[4] V. Rampa, U. Spagnolini. Multitarget Detection/tracking of Echoes with Known Waveform: Algorithm and Applications[C]. Proceedings International Conference on Acoustics, Speech, and Signal Processing, Munich. 1997, 1: 487-490.
[5] U. Spagnolini, V. Rampa. Multitarget Detection/tracking for Monostatic Ground Penetrating Radar: Application to Pavement Profiling[C]. IEEE Trans on Geosciences and Remote Sensing. 1999, 37(1):383-394.
[6] J. Li, R. Wu. An Efficient Algorithm for Time Delay Estimation[C]. IEEE Transactions on Signal Processing. 1998, 46(8):2231-2235.
[7] R.W u, X .Li , J. Li. Continuous Pavement Profiling with G round-Penetrating Radar[C]. IEE Proc. Radar Sonar Navigation. 2002, 149(4):183-193.
[8] 韩萍,吴仁彪,苏志刚.超分辨时延估计研究新进展[J] 中国民航学院学报, 2000,18(4):1-9.
[9] R. Wu, J. Li. Novel Time Delay Estimation Methods with Applications to Ultra wideband Ground-Penetrating Radar[C]. SPIE Conference Proceedings on Radar Sensor Technology III, Orlando. 1998, 3395:57-68.
[10] A. J. Wimsat, T. Scullion, etc. Use of Ground Penetrating Radar Data in Pavement Rehabilitation Strategy Selection and Pavement Condition Assessment[C]. SPIE Conference on Structural Material Technology III, San Antonio.1998,3400: 372-383.
[11] J.H .Meloy, C .H. Overman, etc. Ground Penetrating Radar Signal Processing Techniques for Airfield Evaluations [C]. SPIE Conference Peoceedings on Radar Sensor Technology and Data Visualization, Orlando.2002, 4744:37-47.
[12] J. M. Cowdery, J. L. Kurtz. Ground Penetrating Radar Signal Processing Techniques for Road Subsurface Measurements [C]. SPIE Conference Proceedings on Radar Technology IV, Orlando. 1999, 3704:86-94.
[13] S. Lahouar. Development of Data Analysis Algorithms for Interpretation of Ground Penetrating Radar Data [D]. Virginia Polytechnic institute, 2003: 20-50.
[14] 中国电波传播研究所. LTD-2000 探地雷达使用手册,2005,3: 1-31.
[15] 郭成超. 路面结构层材料介电特性反演及路面雷达应用[D]. 郑州:郑州大学,2004:20-40.
[16] A. Giannopoulos Modelling ground penetrating radar by GprMax[J] Construction and Building Materials, 2005 ,(19): 755–762.
[17] Antonis Giannopoulos GprMax2D/3D User's Manual Version 2.0,2005:1-69.
[18] 李大心. 探地雷达方法与应用[M]. 北京: 地质出版社,1994:17-26.
[19] 高文森,张魁元等.概率统计教程[M]. 长春:东北师范大学出版社,1999:155-163.
[20] 飞思科技产品研发中心.神经网络理论与MATLAB7实现[M]. 北京:电子工业出版社,2005:44-52.
[21] 赵永辉,谢雄耀等. 地下管线雷达探测图像处理及解释系统. 同济大学学报(自然科学版), 2005 ,(9):1253-1258.
[22] 王群,何云龙等. 基于神经网络的探地雷达探雷研究. 电波科学学报, 2001, (9):398-403.
[23] 杨天春,吕绍林等. 地质雷达检测道路结构的理论及应用分析[J].中南工业大学学报,2001,32(2):118-121.
[24] 赵刚. 多功能路面清雪车电液比例阀控系统的模糊-PID 控制[D]. 长春:吉林大学,2003:4-30.
[25] 高纪念, 蔚长春. 电液控制技术及其应用[M]. 北京 :石油工业出版社, 1993:207-233.
[26] 徐大成,邹丽新,丁建强. 微型计算机控制技术及应用[M].北京: 高等教育出版社, 2003:169-208.
[27] 王栋梁等. 非对称阀控制非对称缸的分析研究[J]. 山东建材学院学报, 2001,(6):123-127.
[28] 高钦和, 黄先祥. 基于simulink的重物举升液压控制系统建模与仿真[J]. 机床与液压, 2001,(1):61-63.
[29] 付永领,祁晓野. AMESim 系统建模和仿真-从入门到精通[M].北京: 北京航空航天出版社, 2006:32-149.
[30] 郑建荣. ADAMS-虚拟样机技术入门与提高. 北京:机械工业出版社,2002:48-134.
[31] 刘宏友等. MATLAB 6 基础及应用[M].重庆: 重庆大学出版社,2002:10-100.
[32] 陈亚勇等. MTATLAB 信号处理详解[M]. 北京:人民邮电出版社,2002:70-90.
[33] 黄永安等. MTATLAB7.0/SIMULINK6.0 建模仿真开发与高级工程应用[M]. 北京:清华大学出版社,2005:40-60.
[34] 周开利,康耀红. 神经网路模型及其 MATLAB 仿真程序设计[M]. 北京:清华大学出版社,2005:69-90.
[35] 孔令讲. 浅地层探地雷达信号处理算法的研究[D] .成都:电子科技大学, 2003:20-40.
[36] 吴晓莉,林哲辉等. MATLAB 辅助模糊系统设计[M]. 西安: 西安电子科技大学出版社,2002:120-160.
[37] 路甫祥等. 电液比例控制技术[M]. 北京:机械工业出版社,1988:100-150.
[38] 党建武. 神经网络技术及应用[M]. 中国铁道出版社,2000:50-100.
[39] 余琴. C 波段多极化 SAR 反演积雪湿度模型研究[D].北京: 中国科学院遥感应用研究所, 2004:10-50.
[40] 谢庆生等. 机械工程中的神经网络方法[M]. 北京:机械工业出版社,2003: 40-120.
[41] Minior, D. and S.Smith. Neural Networks for Highway Maintenance Investigation Using Ground Penetrating Radar Data[C]. Proceedings of the Symposium on the Application of Geophysics to Engineering and Environmental Problems, San Diego, California, 1993,4: 449-462.
[42] Attoh-Okine, B. Using Neural Networks to Identify Pavement Structure Based on Radar Output[C]. Proceeding of Pacific Rim Trans Tech Conference, VolumeII, Seattle, Washington, 1993,7: 45-456.
[43] 李玉琳.液压元件与系统设计[M]. 北京:北京航空航天大学出版社,1991:101-158.
[44] 邓洪超,马文星. DQX 路面除雪车浮雪铲除雪作业模型[J] 吉林大学学报,2005,(4):381-385.
[45] 张利平. 液压传动系统及设计[M]. 北京:化学工业出版社, 2005:50-150.
[46] 张利平. 液压传动与控制[M]. 西安:西北工业大学出版社, 2005:100-150.
[47] 林崧. 液压系统计算机辅助设计[M]. 西安: 西北工业大学, 1991:7-53.
[48] 胡寿松.自动控制原理(第四版)[M].北京:科学出版社,2001:20-133.
[49] 方慧,肖都. 公路结构检测中探地雷达资料自动解释技术. 物探与化探,2005,29(2)146-152.
[51] 成大先等. 机械设计手册第三版第四卷[M]. 北京: 化学工业出版社, 1993,(12):117-479.
[52] 杨华,任勇等. 以相关系数为特征量的飞机目标识别法[J]. 清华大学学报(自然科学版),2001,41(7):29-31.
[53] 李天云等.变压器故障的相关系数分析法[J]. 变压器,1998,(8):37-39.
[2] 倪观军.路用探地雷达数据处理算法研究[D]. 哈尔滨: 哈尔滨工业大学, 2004:1-10.
[3] 刘家学,汪卫民等. 探地雷达中目标的自适应检测与跟踪[J]. 中国民航学院学报, 2003,21(4):5-8.
[4] V. Rampa, U. Spagnolini. Multitarget Detection/tracking of Echoes with Known Waveform: Algorithm and Applications[C]. Proceedings International Conference on Acoustics, Speech, and Signal Processing, Munich. 1997, 1: 487-490.
[5] U. Spagnolini, V. Rampa. Multitarget Detection/tracking for Monostatic Ground Penetrating Radar: Application to Pavement Profiling[C]. IEEE Trans on Geosciences and Remote Sensing. 1999, 37(1):383-394.
[6] J. Li, R. Wu. An Efficient Algorithm for Time Delay Estimation[C]. IEEE Transactions on Signal Processing. 1998, 46(8):2231-2235.
[7] R.W u, X .Li , J. Li. Continuous Pavement Profiling with G round-Penetrating Radar[C]. IEE Proc. Radar Sonar Navigation. 2002, 149(4):183-193.
[8] 韩萍,吴仁彪,苏志刚.超分辨时延估计研究新进展[J] 中国民航学院学报, 2000,18(4):1-9.
[9] R. Wu, J. Li. Novel Time Delay Estimation Methods with Applications to Ultra wideband Ground-Penetrating Radar[C]. SPIE Conference Proceedings on Radar Sensor Technology III, Orlando. 1998, 3395:57-68.
[10] A. J. Wimsat, T. Scullion, etc. Use of Ground Penetrating Radar Data in Pavement Rehabilitation Strategy Selection and Pavement Condition Assessment[C]. SPIE Conference on Structural Material Technology III, San Antonio.1998,3400: 372-383.
[11] J.H .Meloy, C .H. Overman, etc. Ground Penetrating Radar Signal Processing Techniques for Airfield Evaluations [C]. SPIE Conference Peoceedings on Radar Sensor Technology and Data Visualization, Orlando.2002, 4744:37-47.
[12] J. M. Cowdery, J. L. Kurtz. Ground Penetrating Radar Signal Processing Techniques for Road Subsurface Measurements [C]. SPIE Conference Proceedings on Radar Technology IV, Orlando. 1999, 3704:86-94.
[13] S. Lahouar. Development of Data Analysis Algorithms for Interpretation of Ground Penetrating Radar Data [D]. Virginia Polytechnic institute, 2003: 20-50.
[14] 中国电波传播研究所. LTD-2000 探地雷达使用手册,2005,3: 1-31.
[15] 郭成超. 路面结构层材料介电特性反演及路面雷达应用[D]. 郑州:郑州大学,2004:20-40.
[16] A. Giannopoulos Modelling ground penetrating radar by GprMax[J] Construction and Building Materials, 2005 ,(19): 755–762.
[17] Antonis Giannopoulos GprMax2D/3D User's Manual Version 2.0,2005:1-69.
[18] 李大心. 探地雷达方法与应用[M]. 北京: 地质出版社,1994:17-26.
[19] 高文森,张魁元等.概率统计教程[M]. 长春:东北师范大学出版社,1999:155-163.
[20] 飞思科技产品研发中心.神经网络理论与MATLAB7实现[M]. 北京:电子工业出版社,2005:44-52.
[21] 赵永辉,谢雄耀等. 地下管线雷达探测图像处理及解释系统. 同济大学学报(自然科学版), 2005 ,(9):1253-1258.
[22] 王群,何云龙等. 基于神经网络的探地雷达探雷研究. 电波科学学报, 2001, (9):398-403.
[23] 杨天春,吕绍林等. 地质雷达检测道路结构的理论及应用分析[J].中南工业大学学报,2001,32(2):118-121.
[24] 赵刚. 多功能路面清雪车电液比例阀控系统的模糊-PID 控制[D]. 长春:吉林大学,2003:4-30.
[25] 高纪念, 蔚长春. 电液控制技术及其应用[M]. 北京 :石油工业出版社, 1993:207-233.
[26] 徐大成,邹丽新,丁建强. 微型计算机控制技术及应用[M].北京: 高等教育出版社, 2003:169-208.
[27] 王栋梁等. 非对称阀控制非对称缸的分析研究[J]. 山东建材学院学报, 2001,(6):123-127.
[28] 高钦和, 黄先祥. 基于simulink的重物举升液压控制系统建模与仿真[J]. 机床与液压, 2001,(1):61-63.
[29] 付永领,祁晓野. AMESim 系统建模和仿真-从入门到精通[M].北京: 北京航空航天出版社, 2006:32-149.
[30] 郑建荣. ADAMS-虚拟样机技术入门与提高. 北京:机械工业出版社,2002:48-134.
[31] 刘宏友等. MATLAB 6 基础及应用[M].重庆: 重庆大学出版社,2002:10-100.
[32] 陈亚勇等. MTATLAB 信号处理详解[M]. 北京:人民邮电出版社,2002:70-90.
[33] 黄永安等. MTATLAB7.0/SIMULINK6.0 建模仿真开发与高级工程应用[M]. 北京:清华大学出版社,2005:40-60.
[34] 周开利,康耀红. 神经网路模型及其 MATLAB 仿真程序设计[M]. 北京:清华大学出版社,2005:69-90.
[35] 孔令讲. 浅地层探地雷达信号处理算法的研究[D] .成都:电子科技大学, 2003:20-40.
[36] 吴晓莉,林哲辉等. MATLAB 辅助模糊系统设计[M]. 西安: 西安电子科技大学出版社,2002:120-160.
[37] 路甫祥等. 电液比例控制技术[M]. 北京:机械工业出版社,1988:100-150.
[38] 党建武. 神经网络技术及应用[M]. 中国铁道出版社,2000:50-100.
[39] 余琴. C 波段多极化 SAR 反演积雪湿度模型研究[D].北京: 中国科学院遥感应用研究所, 2004:10-50.
[40] 谢庆生等. 机械工程中的神经网络方法[M]. 北京:机械工业出版社,2003: 40-120.
[41] Minior, D. and S.Smith. Neural Networks for Highway Maintenance Investigation Using Ground Penetrating Radar Data[C]. Proceedings of the Symposium on the Application of Geophysics to Engineering and Environmental Problems, San Diego, California, 1993,4: 449-462.
[42] Attoh-Okine, B. Using Neural Networks to Identify Pavement Structure Based on Radar Output[C]. Proceeding of Pacific Rim Trans Tech Conference, VolumeII, Seattle, Washington, 1993,7: 45-456.
[43] 李玉琳.液压元件与系统设计[M]. 北京:北京航空航天大学出版社,1991:101-158.
[44] 邓洪超,马文星. DQX 路面除雪车浮雪铲除雪作业模型[J] 吉林大学学报,2005,(4):381-385.
[45] 张利平. 液压传动系统及设计[M]. 北京:化学工业出版社, 2005:50-150.
[46] 张利平. 液压传动与控制[M]. 西安:西北工业大学出版社, 2005:100-150.
[47] 林崧. 液压系统计算机辅助设计[M]. 西安: 西北工业大学, 1991:7-53.
[48] 胡寿松.自动控制原理(第四版)[M].北京:科学出版社,2001:20-133.
[49] 方慧,肖都. 公路结构检测中探地雷达资料自动解释技术. 物探与化探,2005,29(2)146-152.
[51] 成大先等. 机械设计手册第三版第四卷[M]. 北京: 化学工业出版社, 1993,(12):117-479.
[52] 杨华,任勇等. 以相关系数为特征量的飞机目标识别法[J]. 清华大学学报(自然科学版),2001,41(7):29-31.
[53] 李天云等.变压器故障的相关系数分析法[J]. 变压器,1998,(8):37-39.