Continuous wavelet analysis of pavement profiles

Alhasan, Ahmad; White, David; Brabanterb, Kris De

doi:10.1016/j.autcon.2015.12.013

Cited by 22 publications

(12 citation statements)

References 27 publications

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“…The Continuous Wavelet Transform (CWT) is one of the several variants of the Wavelet Transform that is commonly considered for pattern/frequency detection in a signal (the pattern/frequency being that of the selected wavelet). As previously shown by the authors in [8] and also [3], the CWT is well-suited to the problem of surface waviness characterization. An interesting property of the CWT (WT in general) is that it is applicable not just to a 1D signal, but also to 2D signals (and signals of higher dimension) [13].…”

Section: D Continuous Wavelet Transform For Surface Flatness Analysismentioning

confidence: 72%

“…The Waviness Index method is thus the one that currently covers the frequency domain the best, albeit for only 5 spatial wavelengths. It should be noted though that these wavelengths were selected specifically to cover the range of wavelengths from 60cm to 300cm that are most likely to impact the operation of forklifts typically used in warehouses (the range is selected to correspond to 50% to 200% of their wheelbase length) [3]. The Waviness Index method was therefore designed to control a range of distances not covered by the F-Numbers method.…”

Section: Traditional Flatness Control Methodsmentioning

confidence: 99%

“…Local planarity is also an important requirement of road surface to ensure comfortable driving [3]. And the requirements for flatness can be even greater in contexts such as television studies (where the travelling motion of cameras must be as smooth as possible) or warehouses where forklifts (now increasingly robotic ones) must travel fast and safely, without the risk of losing their loads due to vertical vibrations resulting from uneven floors [4].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Automatic Surface Flatness Control using Terrestrial Laser Scanning Data and the 2D Continuous Wavelet Transform

Valero¹,

Bosché²

2016

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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-Evaluating flatness defects in surfaces during the construction of a building can prevent problems during subsequent construction tasks or the operation phase. An area of particular interest is that of the flatness of warehouse slabs on which pallettransporting equipment is operated (nowadays including robots). Flatness control has typically been done with extensively manual methods, such as the Straightedge, F-Numbers or Waviness Index methods. However, these are time-consuming, based on very sparse measurements, and conduct assessment in linear ways only (i.e. in 1D along survey lines, as opposed in 2D on the entire surface), which can lead to inaccurate assessment. This paper presents a novel approach that takes advantage of (1) Terrestrial Laser Scanners (TLS) to speed up data acquisition and provide precise and dense 3D measurements of surfaces; and (2) the 2D Continuous Wavelet Transform (CWT) to deliver a 2D wavelength analysis of surface data with high resolution both spatially and in the frequency domain. The value of the proposed method over existing approaches is discussed and demonstrated with a first experiment conducted with a real concrete slab.

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Section: D Continuous Wavelet Transform For Surface Flatness Analysismentioning

confidence: 72%

Section: Traditional Flatness Control Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Automatic Surface Flatness Control using Terrestrial Laser Scanning Data and the 2D Continuous Wavelet Transform

Valero¹,

Bosché²

2016

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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“…For a number of industry applications, a low cost yet accurate 3D surface profiling system is required [1]. A 3D map can easily be achieved through the use of a 3D Terrestrial Laser Scanner (TLS) [2][3][4], however, these can be costly, and therefore may not be practical for some applications. In addition, these applications can often require large areas to be scanned and processed.…”

Section: Introductionmentioning

confidence: 99%

“…Gao et al [7] investigated two methods to minimize the errors due to vibration when using interferometry as a method to map the surface of a shop floor. 3D Terrestrial Laser Scanners have been able to provide high density point cloud surfaces, such as pavement and asphalt, that can then be processed into useful information [2][3][4]. These scanners are typically used as stationary measurement machines, however, Chow et al [8] investigated fusing an inertial Measurement Unit (IMU) with an RGB-D Camera for assisting localization of a Stop and Go scanning solution.…”

Section: Introductionmentioning

confidence: 99%

Robot-Assisted Floor Surface Profiling Using Low-Cost Sensors

2019

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Low cost and accurate 3D surface profiling can help in numerous industry applications including inspection tasks, cleaning, minimizing bumps in navigation of non-uniform terrain, aid navigation, and road/pavement condition analysis. However, most of the available systems are costly or inaccessible for widespread use. This research presents investigation into the capability of cheap and accessible sensors to capture the floor surface profile information. A differential drive robotic platform has been developed to perform testing and conduct the research. 2D localization methods are extrapolated into 3D for the floor capturing process. Two different types of sensors, a 2D laser scanner and an RGB-D camera, are used for comparison of the floor profile capture ability. The robotic system is able to successfully capture the floor surface profile of a number of different type floors such as carpet, asphalt, and a coated floor. A key finding is that the surface itself is a significant factor on the measured profile, i.e. dirt or differing materials can cause false height measurements. Overall the methodology has proved a successful real time solution for creating a point cloud of the floor surface.

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Research on Vibration Index of IRI Detection Based on Smart Phone

Zeng

Zhang

Cao

et al. 2022

Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications

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With the development of science and technology, intelligent pavement smoothness detection becomes possible. Intelligent IRI (International Roughness Index) detection is one of the important development directions of pavement performance detection. Different from traditional IRI detection, intelligent IRI detection uses smart phones to collect traffic vibration data. There are many vibration indexes in IRI evaluation unit of driving vibration data, and IRI evaluation can be realized by extracting vibration indexes. In this study, the corresponding relationship between pavement vibration data and IRI is preliminarily proved by driving test. The synthetic vibration acceleration index can reflect the change of IRI. The length of IRI evaluation unit reflects different significance of pavement performance, and the evaluation vibration index extracted is different. When the evaluation unit is short, IRI reflects the local pavement performance of the evaluation unit, and the correlation between the minimum value of vehicle synthetic vibration acceleration and IRI is the best. When the evaluation unit is long, IRI reflects the overall pavement performance of the evaluation unit, and the correlation between the average value of the absolute value of the vehicle synthetic vibration acceleration and IRI is the best.

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Continuous wavelet analysis of pavement profiles

Cited by 22 publications

References 27 publications

Automatic Surface Flatness Control using Terrestrial Laser Scanning Data and the 2D Continuous Wavelet Transform

Automatic Surface Flatness Control using Terrestrial Laser Scanning Data and the 2D Continuous Wavelet Transform

Robot-Assisted Floor Surface Profiling Using Low-Cost Sensors

Research on Vibration Index of IRI Detection Based on Smart Phone

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