Inferring Pavement Properties using an Embedded Accelerometer

Levenberg, Eyal

doi:10.1260/2046-0430.1.3.229

Cited by 28 publications

(15 citation statements)

References 25 publications

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“…Under motion, the mass is accelerated due to the force applied on the spring. The displacement of the mass is then proportional to the acceleration [26].…”

Section: Accelerometersmentioning

confidence: 99%

In Situ Pavement Monitoring: A Review

et al. 2020

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The assessment of pavement conditions and their evolution with time is a crucial component for the establishment of pavement quality management (QM) plans and the implementation of QM practices. An effective pavement management system (PMS) is based on pavement conditions data continuously collected along the lifetime of a road. These data are used to model the pavement response, evaluate its performances, and trigger the necessary maintenance actions when they do not meet previously defined performance indicators. In the last decades, pavement monitoring via embedded sensing technologies has attracted more and more attention. Indeed, the integration of sensors in the road pavement allows the assessment of the complete history of pavement conditions, starting from sensor installation. Once the technologies are stabilized, collecting this information is expected to help road managers to define more effective asset management plans. This paper first proposes an overview of the most used devices for pavement instrumentation, categorized according to the measured parameters. Then a review of some prominent instrumented sections is presented by focusing on the methodology used for data interpretation.

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“…Under motion, the mass is accelerated due to the force applied on the spring. The displacement of the mass is then proportional to the acceleration [26].…”

Section: Accelerometersmentioning

confidence: 99%

In Situ Pavement Monitoring: A Review

et al. 2020

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“…where w(t) is the time domain signal of Gaussian white noise with mean zero; G q is the road roughness coefficient; v is the vehicle speed (m/s); and n 0 is the reference space frequency and n 0 � 0.1 m −1 . According to (1)- (7), the vehicle random dynamic load forcing on the pavement can be calculated as…”

Section: Random Nonuniformmentioning

confidence: 99%

“…Arraigada et al [6] used accelerometers to measure pavement deflections due to traffic loads. Levenberg [7] inferred the pavement layer properties by using an integral electronic piezoelectric accelerometer. Yu and Yu [8] developed a cost-effective vibration-based system for preliminary evaluation of pavement conditions.…”

Section: Introductionmentioning

confidence: 99%

Investigating the Pavement Vibration Response for Roadway Service Condition Evaluation

Wang

2018

Advances in Civil Engineering

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Dynamic response of pavement provides service condition information and helps with damage prediction, while limited research is available with the simulation of pavement vibration response for evaluating roadway service condition. This paper presents a numerical model for the analysis of the pavement vibration due to the dynamic load created by a passing vehicle. A quarter vehicle model was used for the determination of the vehicle moving load. Both random and spatial characteristics of the load were considered. The random nonuniform moving load was then introduced in a 3D finite element model for the determination of the traffic-induced pavement vibration. The validated numerical model was used to assess the effects of dynamic load, material properties, and pavement structures on pavement vibration response. Numerical analyses showed that the vibration modes changed considerably for the different roadway service conditions. The vibration signals reflect the level of road roughness, the stiffness of the pavement materials, and the integrity of pavement structure. The acceleration extrema, the time-domain signal waveform, the frequency distribution, and the sum of squares of Fourier amplitude can be potential indexes for evaluating roadway service condition. This provides recommendations for the application of pavement vibration response in early-warning and timely maintenance of road.

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“…As a means to resolve the issues with double integration of acceleration traces, it was proposed in Levenberg (2012) and in Levenberg (2015) to directly match measured accelerations against computed accelerations. Doing so required, as an added analysis step, the application of a low-pass filter to the measured signals prior to the matching.…”

Section: Introductionmentioning

confidence: 99%

Inference of Pavement Properties with Roadside Accelerometers

Nielsen

Levenberg

Skar

2020

Lecture Notes in Civil Engineering

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An array of four synchronized single-axis accelerometers was fixed to the surface of an asphalt pavement. Vertical acceleration traces resulting from several nearby passes of a truck with known characteristics were recorded. The work focused on presenting and demonstrating an interpretation method for inferring the mechanical properties of the pavement system based on the recorded accelerations. In general terms, the method was based on carefully low-pass filtering the field-measured acceleration traces, and then best-matching them with a corresponding set of calculated acceleration traces. For this purpose, the pavement system was modeled as a two-layered linear elastic half-space, and a model-guided signal filtering approach was devised to ensure that irrelevant signal content is removed prior to the matching. Based on the analysis of six separate truck passes it was noticed that the inferred upper layer modulus exhibited medium variability while the lower (subgrade) modulus showed little variability. The moduli values displayed fair agreement with those independently estimated from non-destructive and semi-destructive tests. By analyzing many more passes inferred moduli are expected to become more representative. Overall, the method seems workable and scalable, with capacity to handle any number of acceleration sensors as well as other sensor types.

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Inferring Pavement Properties using an Embedded Accelerometer

Cited by 28 publications

References 25 publications

In Situ Pavement Monitoring: A Review

In Situ Pavement Monitoring: A Review

Investigating the Pavement Vibration Response for Roadway Service Condition Evaluation

Inference of Pavement Properties with Roadside Accelerometers

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