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- W583304830 abstract "Surface distress degrades not only structural but also functional performance of a pavement. Distressed pavements seriously reduce ride quality and safety of road users and also raise vehicle operating costs. Road agencies frequently use response type profilers to monitor their pavements especially for the roughness deteriorations and then maintain acceptable surface conditions to road users. The goal of this study is to introduce the potential application of response type profilers to the distress identification in the roughness profile measurements. In this study, the authors examine a distress identification method based on the lifting wavelet transform (LWT) rather than conventional signal processing using band-pass filters. LWT performs decomposition and reconstruction of a roughness profile by lifting wavelet filters containing controllable free parameters that enable the initial wavelet filters to learn the target distresses that should be identified. For the purpose of this study, a validation experiment by use of the response type profiler introduced to regular monitoring of expressway in Japan identifies severe distresses due to frost heaving that is a good example of the target. As the experimental result, average 77.9% (error of 22.1%) of the target distress can be correctly identified. This satisfies the acceptable error for longitudinal profile measurements within 30% in Japan. Consequently, the proposed method contributes to the distress survey using response type profilers rather than conventional visual-based methods, measuring surface roughness characteristics." @default.
- W583304830 created "2016-06-24" @default.
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- W583304830 date "2014-01-01" @default.
- W583304830 modified "2023-09-23" @default.
- W583304830 title "Lifting Wavelet Transform for Distress Identification Using Response Type Profilers" @default.
- W583304830 hasPublicationYear "2014" @default.
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