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공용중인 아스팔트 포장의 아스팔트층 동탄성계수와 FWD 역산 탄성계수의 상관관계 분석
박희문(Park, Hee Mun),박홍준(Park, Hong Joon) 한국도로학회 2015 한국도로학회논문집 Vol.17 No.5
PURPOSES: The objective of this study is to analyze the relationship between the FWD back-calculated modulus and dynamic modulus of asphalt layers for existing asphalt pavements. METHODS: To evaluate the dynamic modulus of the asphalt mixture in the existing and new asphalt layers, the uniaxial direct tension test was conducted on small asphalt specimens obtained from the existing asphalt-covered pavements. A dynamic modulus master curve was estimated by using the uniaxial direct tension test for each asphalt layer. The falling weight deflectometer (FWD) testing was conducted on the test sections, and the modulus values of pavement layers were back-calculated using the genetic algorithm and the finite element method based back-calculation program. The relationship between measured and back-calculated asphalt layer moduli was examined in this study. The normalized dynamic modulus was adopted to predict the stiffness characteristics of asphalt layers more accurately. RESULTS: From this study, we can conclude that there is no close relationship between dynamic modulus of first layer and back-calculated asphalt modulus. The dynamic moduli of second and third asphalt layers have some relation with asphalt stiffness. Test results also showed that the normalized dynamic modulus of the asphalt mixture is closely related to the FWD back-calculated modulus with 0.73 of R square value. CONCLUSIONS: The back-calculated modulus of asphalt layer can be used as an indicator of the stiffness characteristics of asphalt layers in the asphalt-covered pavements.
박희문(Hee-Mun Park),정종대(Jong-Dae Jung) 한국전기전자학회 2019 전기전자학회논문지 Vol.23 No.4
본 논문은 모바일 로봇과 자동제어 시스템에 적용될 수 있는 음원 위치 추적 시스템(Sound Source Localization, SSL)을 보여준다. 대부분 SSL의 기법은 음원 도달 시간차(Interaural Time Difference, ITD)와 음압 레벨의 차이(Interaural Level Difference, ILD)를 구하고, 마이크로폰 배열의 기하학적 원리를 이용하여 위치를 찾게 된다. 하지만 본 논문에서는 음원의 수평 각도를 구하기 위해 깊은 인공 신경망을 기반으로 한 다른 접근법은 제안한다. 인간의 귀를 모방한 로봇의 양쪽 마이크로폰에서 음원의 신호를 채집하여 연구에 사용했다. Network를 학습시키기 위해 양쪽 마이크로폰에서 얻어진 음원의 스펙트럼 분포 차이를 이용하였다. 각 10도 마다 채집한 데이터로 네트워크를 학습시켰고 임의의 각도에서 얻어진 데이터로 결과를 확인했다. 실험 결과 제안한 SSL의 접근 방식은 상당히 가능성이 있는 결과를 보여주었다. In this paper, we describe a sound source localization(SSL) system which can be applied to mobile robot and automatic control systems. Usually the SSL method finds the Interaural Time Difference, the Interaural Level Difference, and uses the geometrical principle of microphone array. But here we proposed another approach based on the deep neural network to obtain the horizontal directional angle(azimuth) of the sound source. We pick up the sound source signals from the two microphones attached symmetrically on both sides of the robot to imitate the human ears. Here, we use difference of spectral distributions of sounds obtained from two microphones to train the network. We train the network with the data obtained at the multiples of 10 degrees and test with several data obtained at the random degrees. The result shows quite promising validity of our approach.
FWD 처짐곡선을 이용한 아스팔트 포장구조체의 탄성계수 추정 모형 개발
박성완(Park Seong Wan),황정준(Hwang Jung Joon),황규영(Hwang Kyu Young),박희문(Park Hee Mun) 대한토목학회 2006 대한토목학회논문집 D Vol.26 No.5D
본 연구에서는 비파괴 시험 장비인 FWD(Falling Weight Deflectometer)에 의한 처짐곡선을 활용하여 아스팔트 포장구조체의 물성을 합리적으로 추정할 수 있는 방법을 개발하였다. 2004년 국도 PMS(pavement Management System)의 FWD 자료로 다층탄성이론에 근거한 역산프로그램을 사용하여 역해석을 실시하였다. 3층 포장구조체로 기반암을 고려하여 역해석을 실시하였으며, 통계분석을 통하여 각 층 탄성계수의 95% 신뢰구간을 선정하였다. 이 신뢰구간의 범위와 기존 문헌상의 범위를 비교한 결과 차이가 없었으며, 그 결과를 바탕으로 회귀분석을 실시하여 탄성계수를 직접 추정할 수 있는 회귀 분석 모델을 제시하였다. 회귀 분석모델의 적합성 및 유의성 검증, 다중공선성 분석, 잔차 분석 그리고 분산 분석을 통하여 본 연구에서 제시한 회귀 분석모델이 유의하며 높은 적합성을 갖고 있음을 증명하였다. 따라서, 본 연구에서 제시한 회귀 분석 모델을 통해 FWD 시험시 현장에서 역해석을 실시하지 않고도 직접 탄성계수를 추정하여 포장구조체의 상태평가를 할 수 있을 것으로 판단된다. 또한, 아스팔트층의 탄성계수는 온도변화에 따라 많은 차이를 나타내므로 기준온도로 온도보정을 실시하였으며 그 결과를 토대로 현재 공용중인 국도 아스팔트 포장구조체 각 층의 탄성계수와 95%신뢰구간의 탄성계수를 제시하였다. A development of regression model for asphalt concrete pavements using Falling Weight Deflectometer deflections is presented in this paper. A backcalculation program based on layered elastic theory was used to generate the synthetic modulus database, which was used to generate 95% confidence intervals of modulus in each layer. Using deflection basins of FWD data used in developing this procedure were collected from Pavement Management System in flexible pavements. Assumptions of back-calculation are that one is 3 layered flexible pavement structure and another is depth to bedrock is finite. It is found that difference of between 95% confidence intervals and modulus ranges of other papers does not exist. So, the data of 95% confidence intervals in each layer was used to develop multiple regression models. Multiple regression equations of each layer were established by SPSS, package of Statics analysis. These models were proved by regression diagnostics, which include case analysis, multi-collinearity analysis, influence diagnostics and analysis of variance. And these models have higher degree of coefficient of determination than 0.75. So this models were applied to predict modulus of domestic asphalt concrete pavement at FWD field test.
지표투과레이더와 적외선카메라를 이용한 아스팔트 포장 시공 관리 방법
백종은,박희문,유평준,임재규,Baek, Jongeun,Park, Hee Mun,Yoo, Pyung Jun,Im, Jae Kyu 한국도로학회 2015 한국도로학회논문집 Vol.17 No.6
PURPOSES : The objective of this study is to propose a quality control and quality assurance method for use during asphalt pavement construction using non-destructive methods, such as ground penetrating radar (GPR) and an infrared (IR) camera. METHODS : A 1.0 GHz air-coupled GPR system was used to measure the thickness and in situ density of asphalt concrete overlay during the placement and compaction of the asphalt layer in two test construction sections. The in situ density of the asphalt layer was estimated based on the dielectric constant of the asphalt concrete, which was measured as the ratio of the amplitude of the surface reflection of the asphalt mat to that of a metal plate. In addition, an IR camera was used to monitor the surface temperature of the asphalt mat to ensure its uniformity, for both conventional asphalt concrete and fiber-reinforced asphalt (FRA) concrete. RESULTS : From the GPR test, the measured in situ air void of the asphalt concrete overlay gradually decreased from 12.6% at placement to 8.1% after five roller passes for conventional asphalt concrete, and from 10.7% to 5.9% for the FRA concrete. The thickness of the asphalt concrete overlay was reduced from 7.0 cm to 6.0 cm for the conventional material, and from 9.2 cm to 6.4 cm for the FRA concrete. From the IR camera measurements, the temperature differences in the asphalt mat ranged from $10^{\circ}C$ to $30^{\circ}C$ in the two test sections. CONCLUSIONS : During asphalt concrete construction, GPR and IR tests can be applicable for monitoring the changes in in situ density, thickness, and temperature differences of the overlay, which are the most important factors for quality control. For easier and more reliable quality control of asphalt overlay construction, it is better to use the thickness measurement from the GPR.