基于灰色关联分析法的辽宁省厂拌冷再生路面使用性能指数影响因素
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摘要
目的探究厂拌冷再生技术应用于道路下面层累计当量轴次Ne、年平均气温和年平均降雨量对路面使用性能指数PQI的影响程度,为厂拌冷再生路面养护对策的制订提供参考依据.方法采用《辽宁省普通公路沥青路面厂拌再生技术后评价研究》提供的路面损坏状况指数、路面行驶状况指数,根据《公路技术状况评定标准》(JTG H20—2007)及《高速公路养护质量检评方法》的计算方法获得PQI值.运用M ATLAB软件,基于灰色关联分析法,对辽宁省5个气候区内的典型乳化沥青厂拌冷再生干线公路的路面使用性能指数PQI进行相关因素影响分析.结果 PQI与每条车道累计当量轴次Ne,年平均气温和年平均降雨量之间的灰关联度分别为:气候Ⅰ区0. 578 0,0. 731 2,0. 553 6;气候Ⅱ区0. 638 4,0. 730 3,0. 556 0;气候Ⅲ区0. 619 5,0. 772 2,0. 584 6;气候Ⅳ区0. 710 1,0. 699 4,0. 538 9;气候Ⅴ区0. 814 7,0. 857 6,0. 710 7.结论年平均气温对PQI的影响最大,累计当量轴次Ne次之,年平均降雨对PQI的影响最小.
In the situation that the central plant cold recycling technology is applied to the underlying layer of the road,in order to explore the influence of the cumulative equivalent single axle lode Ne,the annual average temperature and the annual average rainfall on the pavement performance index PQI of the central plant cold recycling and to provide reference for the formulation of main-tenance countermeasures of central plant cold recycling pavement. Based on the Highway Performance Assessment Standards and Expressway Maintenance Quality Evaluation Standards,the PQI value was calculated by using the "Pavement Damage Status Index and Road Driving Status Index"provided by the Research and Research on the Post-Evaluation Research of the Common Road Asphalt Pavement Plant Mixing Technology in Liaoning Province. Based on the gray correlation analysis,the relevant factors of the pavement performance index PQI of the typical emulsified asphalt plant mixed cold reclaimed trunk road in five climate regions of Liaoning Province was analyzed by MATLAB software. Results showthat the grey correlation between PQI and cumulative equivalent single axle lode Ne,annual mean temperature and annual average rainfall are: climate zone I 0. 578 0,0. 731 2,0. 553 6,climate zone II 0. 638 4,0. 730 3,0. 556 0,climate zone III0. 619 5,0. 772 2,0. 584 6,climate IV area 0. 710 1,0. 699 4,0. 538 9,climate V area 0. 814 7,0. 857 6,0. 710 7. The annual average temperature has the greatest impact on PQI,followed by the cumulative equivalent axis Ne,and the annual average rainfall has the least effect on PQI.
In the situation that the central plant cold recycling technology is applied to the underlying layer of the road,in order to explore the influence of the cumulative equivalent single axle lode Ne,the annual average temperature and the annual average rainfall on the pavement performance index PQI of the central plant cold recycling and to provide reference for the formulation of main-tenance countermeasures of central plant cold recycling pavement. Based on the Highway Performance Assessment Standards and Expressway Maintenance Quality Evaluation Standards,the PQI value was calculated by using the "Pavement Damage Status Index and Road Driving Status Index"provided by the Research and Research on the Post-Evaluation Research of the Common Road Asphalt Pavement Plant Mixing Technology in Liaoning Province. Based on the gray correlation analysis,the relevant factors of the pavement performance index PQI of the typical emulsified asphalt plant mixed cold reclaimed trunk road in five climate regions of Liaoning Province was analyzed by MATLAB software. Results showthat the grey correlation between PQI and cumulative equivalent single axle lode Ne,annual mean temperature and annual average rainfall are: climate zone I 0. 578 0,0. 731 2,0. 553 6,climate zone II 0. 638 4,0. 730 3,0. 556 0,climate zone III0. 619 5,0. 772 2,0. 584 6,climate IV area 0. 710 1,0. 699 4,0. 538 9,climate V area 0. 814 7,0. 857 6,0. 710 7. The annual average temperature has the greatest impact on PQI,followed by the cumulative equivalent axis Ne,and the annual average rainfall has the least effect on PQI.
引文
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[16]杨海猛.普通公路沥青路面预防性养护管理决策研究[D].大连:大连理工大学,2014.(YANGHaimeng. Ordinary highway asphalt pavement preventive maintenance management decision-making research[D]. Dalian:Dalian University of Technology,2014.)
[17]张国梁.预防性养护最佳时机的确定方法研究[D].哈尔滨:哈尔滨工业大学,2007.(ZHANGGuoliang. Study on the method of determinating optimal timing of preventive maintenance[D]. Harbin:Harbin Institute of Technology,2007.)
[18]侯博.基于气候分区的辽宁省沥青路面典型结构研究[D].沈阳:沈阳建筑大学,2017.(HOU Bo. Study on the typical structure of asphalt pavement in Liaoning province based on climate zoning[D]. Shenyang:Shenyang Jianzhu University,2017.)
[19]刘寅立. MATLAB数值计算案例分析[M].北京:北京航空航天大学出版社,2011.(LIU Yinli. Case study of MATLAB numerical calculation[M]. Beijing:Beihang University Press,2011.)
[2]苗英豪,王秉纲.中国沥青路面气候影响分区方案[J].交通运输工程学报,2007,7(6):64-69.(MIAO Yinghao,WANGBinggang. Zoning scheme of climatic influence for asphalt pavement in China[J]. Journal of traffic and transportation engineering,2007,7(6):64-69.)
[3]聂鹏.辽宁省沥青路面合理结构类型与区划原理的研究[D].哈尔滨:哈尔滨工业大学,2007.(NIE Peng. Study on regionalization principle and rational structure of asphalt concrete pavement in Liaoning province[D]. Haerbin:Harbin Institute of Technology,2007.)
[4]杨彦海,侯博,姜宏宇.基于空间插值方法的路面结构设计年平均降水量指标精度研究[J].沈阳建筑大学学报(自然科学版),2016(4):643-650.(YANGYauhai,HOU Bo,JLANGHougyu.Study on the accuracy of pavement structure designbased on spatial interpolation methods[J]. Journal of Shenyang jianzhu university(natural science),2016(4):643-650.)
[5]李昌洲,何晓鸣,李文文.灰色系统理论在沥青路面使用性能预测中的应用[J].武汉轻工大学学报,2010,29(1):70-73.(LI Changzhou,HE Xiaoming,LI Wenwen.Application of gray system theory in forecasting the functional performance of biteminous pavement[J]. Journal of Wuhan polytechnic university,2010,29(1):70-73.)
[6]胡群芳,刘文,李清富.公路沥青路面使用性能灰色综合评估[J].公路交通科技,2006,23(1):16-19.(HU Qunfang,LIU Wen,LI Qingfu. Synthetical gray evaluation of asphalt pavement performance[J]. Journal of highway and transportation research and development,2006,23(1):16-19.)
[7]邓聚龙.灰色系统理论教程[M].武汉:华中理工大学出版社,1990.(DENGJulong. Grey system theory tutorial[M]. Wuhan:Huazhong University of Science and Technology Press,1990.)
[8]刘震.灰色关联与预测建模技术及其应用研究[D].南京:南京航空航天大学,2016.(LIU Zhen. Grey incidence and grey forecasting models with their application[D]. Nanjing:Nanjing University of Aeronautics and Astronautics,2016.)
[9] WONGC,LIN B,CHENGC. Fuzzytracking method with a switching grey prediction for mobile robot[J]. IEEE international conference on fuzzy systems,2001,1:103-106.
[10] JIANGY,LI S. Gray system model for estimating the pavement international roughness index[J]. Journal of performance of constructed facilities,2005,19(1):62-68.
[11]华涛.高温多雨山区公路沥青路面使用性能评价研究[D].重庆:重庆交通大学,2013.(HUA Tao. Research on evaluation of asphalt pavement performance in megathermal and rainy mountainous are as[D]. Chongqing:Chongqing Jiaotong University,2013.)
[12]李金龙.重庆高速公路沥青路面使用性能评价预测及养护决策优化研究[D].重庆:重庆交通大学,2012.(LI Jinlong. Research on the evaluation and prediction and maintenance optimizatio decision of expressway asphalt pavement performance in Chongqing[D]. Chongqing:Chongqing Jiaotong University,2012.)
[13]侯超平.高等级沥青路面使用性能预测模型及预防护性养护措施研究[D].重庆:重庆交通大学,2015.(HOU Chaoping. Prediction model of high grade asphaltpavement performance and research onpreventive maintenance measures[D]. Chongqing:Chongqing Jiaotong University,2015.)
[14]胡苏娜.高速公路沥青路面使用性能预测研究[D].重庆:重庆交通大学,2015.(HU Suna. Research on the prediction of highwaypavement performance[D]. Chongqing:Chongqing Jiaotong University,2015.)
[15]齐明.辽宁省路面预防性养护决策分析与典型技术试验验证[D].哈尔滨:哈尔滨工业大学,2015.(QI Ming. Analysis on preventive maintenance decision and testing validation on typilcal techniques for pavements in Liaoning province[D]. Harbin:Harbin Institute of Technology,2015.)
[16]杨海猛.普通公路沥青路面预防性养护管理决策研究[D].大连:大连理工大学,2014.(YANGHaimeng. Ordinary highway asphalt pavement preventive maintenance management decision-making research[D]. Dalian:Dalian University of Technology,2014.)
[17]张国梁.预防性养护最佳时机的确定方法研究[D].哈尔滨:哈尔滨工业大学,2007.(ZHANGGuoliang. Study on the method of determinating optimal timing of preventive maintenance[D]. Harbin:Harbin Institute of Technology,2007.)
[18]侯博.基于气候分区的辽宁省沥青路面典型结构研究[D].沈阳:沈阳建筑大学,2017.(HOU Bo. Study on the typical structure of asphalt pavement in Liaoning province based on climate zoning[D]. Shenyang:Shenyang Jianzhu University,2017.)
[19]刘寅立. MATLAB数值计算案例分析[M].北京:北京航空航天大学出版社,2011.(LIU Yinli. Case study of MATLAB numerical calculation[M]. Beijing:Beihang University Press,2011.)
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