Classification of Features of Pavement Profiles Using Empirical Mode Decomposition

Franta, Daniel P.; Wojtkiewicz, Steven F.; Khazanovich, Lev; United States. Federal Highway Administration; United States. Department of Transportation. Federal Highway Administration. Turner-Fairbank Highway Research Center; Long-Term Pavement Performance Program (U.S.)

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Classification of Features of Pavement Profiles Using Empirical Mode Decomposition

2014-12-01
By Franta, Daniel P. ; Wojtkiewicz, Steven F. ; Khazanovich, Lev

[PDF-2.09 MB]

English

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Alternative Title:

Classification of Features of Pavement Profiles Using Empirical Mode Decomposition [TechBrief]
Creators:

Franta, Daniel P. ; Wojtkiewicz, Steven F. ; Khazanovich, Lev

Franta, Daniel P. ; Wojtkiewicz, Steven F. ; Khazanovich, Lev Less -
Corporate Creators:

United States. Federal Highway Administration ; United States. Department of Transportation. Federal Highway Administration. Turner-Fairbank Highway Research Center ; Long-Term Pavement Performance Program (U.S.)

United States. Federal Highway Administration ; United States. Department of Transportation. Federal Highway Administration. Turner-Fairbank Highway Research Center ; Long-Term Pavement Performance Program (U.S.) Less -
Subject/TRT Terms:

[+]

Algorithms Built-in Curl Classification Concrete Pavements Curling Deflection Empirical Mode Decomposition Hilbert-Huang Intrinsic Mode Function LTPP Pavement Performance
Publication/ Report Number:

FHWA-HRT-13-093;HRDI-30/12-14(250)E
Resource Type:

Tech Report
Geographical Coverage:

United States
Corporate Publisher:

United States. Federal Highway Administration
Abstract:

The Long-Term Pavement Performance (LTPP) database contains surface profile data for numerous pavements that are used mainly for computing International Roughness Index (IRI).(2) In order to obtain more information from these surface profiles, a Hilbert-Huang Transform (HHT) based surface profile algorithm was developed to analyze LTPP field road profile data in order to extract smoothed, consistent profiles from noise-filled data sets using empirical mode decomposition (EMD). The application of this algorithm to concrete surface profiles resulted in the successful separation of the intrinsic mode functions contained within the profile data for several LTPP pavement test sections from Wisconsin, Arizona, and Utah. Arizona was the only test section where the profiles showed consistent “curl” deflections for the same slab over a 20-month timespan and during both winter and early fall seasons. The consistent slab shape is likely due to built-in curl. Built-in curl is defined as permanent concrete slab deformation that occurs early in the life of the pavement. By categorizing and separating intrinsic mode functions contained within LTPP profile data, the results can be used to analyze specific portions of LTPP surface profile data in order to improve concrete pavement models in the future. Currently, no comprehensive procedure exists to model or estimate long-term, effective built-in curling. The developed surface profile algorithm that has proven to be universal can be applied to any LTPP profile data for analysis.
Format:

PDF
Collection(s):

Federal Highway Administration
Main Document Checksum:

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urn:sha-512:91deb09d256d3392adf392796a09da4f427a51caff49fff03df81a75d28e6b249788fa70ea207e9a27193711d0e81b7a472c1762f999fcf41a611fad3b968eaf
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https://rosap.ntl.bts.gov/view/dot/35825/dot_35825_DS1.pdf
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Classification of Features of Pavement Profiles Using Empirical Mode Decomposition

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