Literature DB >> 32106391

Stabilization of a p-u Sensor Mounted on a Vehicle for Measuring the Acoustic Impedance of Road Surfaces.

Francesco Bianco1, Luca Fredianelli2, Fabio Lo Castro3, Paolo Gagliardi2, Francesco Fidecaro2, Gaetano Licitra4.   

Abstract

The knowledge of the acoustic impedance of a material allows for the calculation of its acoustic absorption. Impedance can also be linked to structural and physical proprieties of materials. However, while the impedance of pavement samples in laboratory conditions can usually be measured with high accuracy using devices such as the impedance tube, complete in-situ evaluation results are less accurate than the laboratory results and is so time consuming that a full scale implementation of in-situ evaluations is practically impossible. Such a system could provide information on the homogeneity and the correct laying of an installation, which is proven to be directly linked to its acoustic emission properties. The present work studies the development of a measurement instrument which can be fastened through holding elements to a moving laboratory (i.e., a vehicle). This device overcomes the issues that afflict traditional in-situ measurements, such as the impossibility to perform a continuous spatial characterization of a given pavement in order to yield a direct evaluation of the surface's quality. The instrumentation has been uncoupled from the vehicle's frame with a system including a Proportional Integral Derivative (PID) controller, studied to maintain the system at a fixed distance from the ground and to reduce damping. The stabilization of this device and the measurement system itself are evaluated and compared to the traditional one.

Entities:  

Keywords:  Adrienne; acoustic impedance; damping; noise; p-p sensor; p-u sensor; road surfaces; stabilization

Year:  2020        PMID: 32106391     DOI: 10.3390/s20051239

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  2 in total

1.  A Conceptual Framework Proposal for a Noise Modelling Service for Drones in U-Space Architecture.

Authors:  Tommy Langen; Vimala Nunavath; Ole Henrik Dahle
Journal:  Int J Environ Res Public Health       Date:  2021-12-25       Impact factor: 3.390

2.  Traffic Flow Detection Using Camera Images and Machine Learning Methods in ITS for Noise Map and Action Plan Optimization.

Authors:  Luca Fredianelli; Stefano Carpita; Marco Bernardini; Lara Ginevra Del Pizzo; Fabio Brocchi; Francesco Bianco; Gaetano Licitra
Journal:  Sensors (Basel)       Date:  2022-03-01       Impact factor: 3.576

  2 in total

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