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首页> 外文期刊>International journal of engineering research and industrial applications >PAVEMENT PERFORMANCE MEASURES USING ANDROID-BASED SMART PHONE APPLICATION
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PAVEMENT PERFORMANCE MEASURES USING ANDROID-BASED SMART PHONE APPLICATION

机译：使用基于ANDROID的智能电话应用的路面性能测量

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Pavement roughness is a phenomenon experienced by the passenger and operator of a vehicle. It continuously deteriorates under the combined actions of traffic loading and the environment. The most common indicators of pavement performance are: fatigue cracking, surface rutting, riding quality, and skid resistance. It is very essential to evaluate the structural and functional condition of pavements to determine the present condition of the pavement. The models predicting pavement performance play an important role in financial planning and budgeting. Therefore it is essential to study the pavement deterioration factors to draw up the suitable maintenance strategies. This paper aims to investigate pavement roughness for improving the performance, using android based smart phone technology. The data on performance of in service flexible and rigid pavements of Hyderabad City were collected. In the study main distresses were identified from the selected road stretches each of 6km and 20km length. Eleven sets of data were already available from previous studies and additional one set is incorporated in this study. The data is analyzed for assessing the cracking progression, deflection growth, pothole progression and roughness index. The device recorded roughness index measure at a time interval of one second, as opposed to distance based. The raw data is presented in which reports a large variance in international roughness index (IRI) along the road length. This detailed low-level data exceeds the detail necessary of IQL-3/4 data, and therefore the raw unfiltered results from each direction were manually averaged over a one kilometer length. It is observed that the average IRI across the road length is similar despite the severe runs. The results thus obtained were compared with the roughness of the main road outside the city area and the roughness within the city. Regression models were then developed using SPSS (Statistical packages for social sciences) package for validation. The researched model if implemented by the construction agencies shall help in predicting pavement performance and help in protecting further deterioration of the roads with premature financial planning and budgeting.
机译：路面粗糙度是车辆的乘客和驾驶员所经历的现象。在交通负荷和环境的共同作用下，它不断恶化。路面性能的最常见指标是：疲劳裂纹，表面车辙，行驶质量和防滑性。评估人行道的结构和功能状况以确定人行道的当前状况非常重要。预测路面性能的模型在财务规划和预算中起着重要作用。因此，研究路面恶化因素以制定适当的维护策略至关重要。本文旨在研究基于Android的智能手机技术，以改善路面的粗糙度。收集了海得拉巴市在役柔性和刚性路面的性能数据。在研究中，从选定的道路长度（分别为6公里和20公里）中识别出主要的困扰。以前的研究已经提供了11组数据，本研究中还纳入了另外一组。分析数据以评估裂纹发展，挠度增长，坑洼发展和粗糙度指数。该设备以一秒的时间间隔记录了粗糙度指数测量值，与基于距离的测量相反。在原始数据中，报告了沿道路长度的国际粗糙度指数（IRI）的巨大差异。该详细的低层数据超出了IQL-3 / 4数据的必要细节，因此，在一个公里的长度上，手动平均了来自每个方向的原始未过滤结果。可以看到，尽管路况严峻，但整个道路上的平均IRI还是相似的。将由此获得的结果与市区以外的主要道路的粗糙度和市区内的粗糙度进行比较。然后使用SPSS（社会科学统计软件包）软件包开发回归模型以进行验证。如果由施工机构实施，则研究模型将有助于预测路面性能，并通过过早的财务规划和预算帮助保护道路的进一步恶化。

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