Continuous primary dynamic pavement response system using piezoelectric axle sensors

Abstract

Increasing commercial traffic over recent years is inflicting increased damage to roadways. As a result, road engineers are adopting more mechanistic performance-based road-modeling techniques to assist in the design, construction, and preservation of road assets. One such common mechanistic analysis technique is dynamic deflection pavement response induced under typical commercial truck loading. This paper presents an investigation of piezoelectric axle sensors as a possible tool for obtaining dynamic pavement deflection data under commercial truck loadings. One of the primary benefits to using piezoelectric axle sensors is that there are thousands of piezoelectric sensors already installed in roads world wide currently measuring the dynamic weights of commercial vehicles. Specifically, this research investigated the potential to use several different types and orientations of commercially available piezoelectric axle sensors to measure pavement deflection response under heavy truck loading. This research found that data from certain piezoelectric sensors and configurations could potentially predict deflection characteristics of a typical flexible pavement system. Based on these findings, there is the potential to use piezoelectric axle sensors for primary response modeling of road structures.Key words: piezoelectric sensors, deflection bowl, weigh-in-motion, mechanistic road modeling.

Detecting concealed damage in asphalt pavement based on a composite lead zirconate titanate/polyvinylidene fluoride aggregate

“…The relationship between the attenuation coefficient and the crack width w in asphalt pavement was established in Chen et al 38 and is expressed in Equation (8).…”

“…The external evaluation technology cannot monitor microdamage and damage development. On-site sensing technology employs embedded optical fiber sensors, 6,7 pressure sensors, 8 strain gauges, 9 thermocouples, 10 accelerometers, 11 and other sensors. 12 The on-site sensing technology can monitor pavement performance and environmental factors continuously in real time and overcome the shortcomings of external evaluation technology.…”

Toward an Integrated Smart Sensing System and Data Interpretation Techniques for Pavement Fatigue Monitoring

“…As new “smart” structures are being designed, special consideration has been paid toward embedding health monitoring capabilities directly into the construction material during the manufacturing and deployment process (Chen and Liu, 2010; Elvin et al, 2006; Adeli and Saleh, 1997, 1998; Tanner et al, 2002; Kim and Adeli, 2005; Adeli and Jiang, 2009). Currently, pavement instrumentation for condition monitoring is done on a localized and short‐term basis (Timm et al, 2004a, 2004b; Al‐Qadi et al, 2004; Lukanen, 2005; Loulizi et al, 2006; Huff et al, 2005). The available technology does not allow for continuous long‐term monitoring mainly because of the limitations caused by the use of batteries: the life span of a battery is about 1–2 years; in addition, it is impractical to replace batteries for embedded sensors.…”

“…A myriad of potential self‐powering energy sources have been identified (e.g., solar power, thermal gradient, piezoelectric, vibrational); yet few are capable of providing the 100 μW of continuous power widely believed to be the absolute minimum required to operate a single sensor currently available (Warneke and Pister, 2002). Also, the deployment of existing systems on a network level remains unfeasible due to cost, difficulty of installation and data collection techniques (fixed and massive data acquisition systems), and low durability attributed to the required wiring (Huff et al, 2005). Thus, the creation of a low‐cost, autonomous self‐powered usage monitoring sensor would be a significant improvement to the field of pavement monitoring and management.…”

A wavelet interpretation of vehicle-pavement interaction

“…For heavy trucks, the vehicle dynamic response of concern is the axle loads, because they affect both pavement and vehicle damage. There has been a variety of studies involving either measurements or analytical predictions of dynamic axle loads (Whittemore 1969, Papagiannakis 1997, Chatti and Lee 2002, Huff et al 2005. Traditionally, vehicle-pavement interaction in the frequency domain has been studied through Fourier analysis.…”