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- W2032165154 abstract "Road roughness is a very important consideration in evaluating the condition of a given way, as it affects vehicles or vehicle passengers, e.g., ride comfort, safety, noise emission, and operating factors. In recent years, the establishment for measuring and evaluating road roughness is requisite issues in various countries. Wavelet Transform (WT) is used as one of the methods that discriminates the local road roughness. One of the advantages of WT is being able to represent the location in both space and frequency simultaneously. In this study, we propose a method for detecting road roughness using the second-generation wavelet transform (SWT). This method is adopted to train free parameters based on some training signals, which contain the localized road distress. Using a free parameter can perform optimization of a basis function comparatively easily. As a result of applying SWT using PIARC EVEN data, when the form of input data and the study waveform of a free parameter were similar, a close-up of an output ingredient was taken. On the other hand, when form differed, it was not detected as a feature point. This is considered to be very important character when designing WT according to the use of road surface management." @default.
- W2032165154 created "2016-06-24" @default.
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- W2032165154 date "2004-01-01" @default.
- W2032165154 modified "2023-09-27" @default.
- W2032165154 title "Basic study on the road roughness detection method using the second-generation wavelet transform" @default.
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