| In China,the construction of transportation infrastructure sustains rapid growth.The mileage of expressway in China ranks first in the world.Pavement engineering directly reflects the quality and driving comfort of the highway.With its good road performance,asphalt becomes the preferred material for high-grade highway pavement.However,highway asphalt pavement has suffered widespread premature failure in China.In addition to inadequate design and construction equipment,some human-related factors are the major causes contributing to poor construction quality.For example,unskilled engineers operate rollers improperly;contractors cut corners for profits.It is insecure to supervise these human factors only by contractors themselves.Entrusting supervisors to monitor construction process is a necessary means to ensure the construction quality of asphalt pavement.From the perspective of the supervisors,this paper develops an asphalt pavement construction quality monitoring system.By analyzing the main acceptance items and influence factors of pavement quality,the key parameters that need to be monitored during the construction process are determined,including asphalt content,gradation,mix temperature and mix time in asphalt production process,as well as operate parameters of constructing machineries in asphalt construction process.The monitoring response range and warning rules of these parameters are determined.The developing process of the system includes the hardware development based on Internet of Things and the software development based on Web programming.The system gives feedback control by Web applications,SMS messages,and warning indicators on site.The system has been implemented successfully in the Zhao Ma Highway construction project in Yunnan Province.The asphalt density and aggregate gradation were improved to a statistically significant level as shown by comparing before and after the monitoring system’s deployment.The implementation of the monitoring system proposed by this paper could improve asphalt pavement construction quality and provides decision support for pavement maintenance in the future.In addition,concerning the problem that GPS will lose efficacy in tunnel,this paper develops an UWB-based positioning subsystem to track construction machineries at tunneling site.Traditional wireless positioning technologies which are based on carrier wave communication are vulnerable to multiple paths effect.On the contrary,UWB technology is suitable for positioning in complex and half-closed tunnel,with its advantages of accuracy and anti-attenuation.For long and straight tunnels which can be simplified as one-dimensional environment,an UWB rough positioning system is proposed based on condition adjustment.The typical precision in Line-of-Sight(LOS)is 10 cm.Regarding the problem of increasing errors in None-Line-of-Sight(NLOS),an UWB/SINS integrated navigation system is proposed.By analyzing the sources and features of noises,an improved simplified Sage-Husa adaptive Kalman filter is applied to UWB/SINS data fusion,on the basis of the loosely-coupled indirectly Kalman filter which gives feedback correction.A threshold method is used to distinguish LOS and NLOS.The results of laboratory experiments suggest that the UWB/SINS system using conventional Kalman filter can decrease 25.43% positioning error compared with UWBonly system.The adaptive filter can decrease 11.39% compared with conventional Kalman filter.The simulation results verify the superiority of adaptive filter as well.Several field tests have been implemented at tunneling site.The system is promising to assist asphalt pavement construction monitoring,with good practicability and stability. |
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