• 소음진동
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• 제2권1호
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• pp.3-14
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• 1992

음장의 공간적 변환(Spatial Transformation of Sound Field; STSF)기법의 주요 원리를 간단히 소개한 뒤, STSF에서 Reference 신호의 사용을 보다 상세히 취급하고자 한다. Reference의 보통의 형태(표준 Reference)는 음장 모델에 포함될 전체음장의 일부분, 즉 이 Reference의 연관이 있어 포함될 부분을 결정한다. 결국 한 개 의 표준 Reference는 항상 적용되어져야 한다. 2번째 Reference의 형태(삭제용 Reference)는 모델로부터 원치 않는 무관한 음장성분을 제거하는데 적용된다. 이 Reference와 밀접한 음장 부분이 모델로부터 제거될 것이고, 그렇지 않는 경우는 포함된다. 실제 예에서는 삭제용 Reference가 암소음의 억제와, 음원의 어떤 독립 적인 성분의 억제를 위해 어떻게 적용되는가를 보인다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권4호
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• pp.314-320
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• 2006

Navigation in environments that are densely cluttered with obstacles is still a challenge for Autonomous Ground Vehicles (AGVs), especially when the configuration of obstacles is not known a priori. Reactive local navigation schemes that tightly couple the robot actions to the sensor information have proved to be effective in these environments, and because of the environmental uncertainties, STSF(Space and Time Sensor Fusion)-based fuzzy behavior systems have been proposed. Realization of autonomous behavior in mobile robots, using STSF control based on spatial data fusion, requires formulation of rules which are collectively responsible for necessary levels of intelligence. This collection of rules can be conveniently decomposed and efficiently implemented as a hierarchy of fuzzy-behaviors. This paper describes how this can be done using a behavior-based architecture. The approach is motivated by ethological models which suggest hierarchical organizations of behavior. Experimental results show that the proposed method can smoothly and effectively guide a robot through cluttered environments such as dense forests.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 추계학술대회논문집 II
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• pp.1040-1043
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• 2001

This paper describes the principle behind Crank Angle Analysis, as implemented by Bruel ＆ Kjaer in the Non-Stationary Spatial Transformation of Sound Fields (NS-STSF) system. The NS-STSF system combines a Time Domain Holography measurement on for example an engine with two simultaneously recorded Tacho signals. The Tacho signals provide the crankshaft angle and the RPM at the instant of each instantaneous output (snap-shot) from Time Domain Holography. As a result, the system allows precise analysis of the temporal and spatial relation between the acoustical emission (or the vibration pattern) and the mechanical events during an engine cycle. Some results from a measurement on a DaimlerChrysler engine are presented.

• 한국음향학회지
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• 제14권5호
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• pp.11-19
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• 1995

본 논문에서는 불규칙한 노면이 설치된 섀시 동력계(chassis dynamometer)로 부터 가진된 타이어의 구조 진동 소음을 음장의 공간적 변환기법을 이용하여 측정하였다. 음장의 공간적 변환기법은 소음원으로 부터 원거리까지의 전파를 계산하는 기법이다. 즉, 한평면의 음향 측정으로 부터 측정 평면에서 멀리 떨어지거나 더 가까운 평면에서의 음장을 표현하는 변수들인 음압, 음향 인텐시티, 입자속도 등을 계산한다. 측정 평면에서 음원쪽으로 가까운 평면의 계산은 관접음장 홀로그래피를 적용하여 계산하고 먼 쪽은 헬름흘쓰 적분식을 적용한다 측정결과로 부터 타이어 구조 진동 소음의 방사형태와 소음원의 위치를 예측하였다.

• 한국항해항만학회지
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• 제27권3호
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• pp.273-282
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• 2003

This paper proposes a sensor-fusion technique where rho data sets for the previous moments are properly transformed and fused into the current data sets to enable accurate measurement, such as, distance to an obstacle and location of the service robot itself. In the conventional fusion schemes, the measurement is dependent only on the current data sets. As the results, more of sensors are required to measure a certain physical promoter or to improve the accuracy of the measurement. However, in this approach, intend of adding more sensors to the system, the temporal sequence of the data sets are stored and utilized for the measurement improvement. Theoretical basis is illustrated by examples md the effectiveness is proved through the simulation. Finally, the new space and time sensor fusion (STSF) scheme is applied to the control of a mobile robot in the indoor environment and the performance was demonstrated by the real experiments.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.471-475
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• 2003

This paper proposes a sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable accurate measurement, such as, distance to an obstacle and location of the service robot itself. In the conventional fusion schemes, the measurement is dependent on the current data sets. As the results, more of sensors are required to measure a certain physical parameter or to improve the accuracy of the measurement. However, in this approach, instead of adding more sensors to the system, the temporal sequence of the data sets are stored and utilized for the measurement improvement. Theoretical basis is illustrated by examples and the effectiveness is proved through the simulations. Finally, the new space and time sensor fusion (STSF) scheme is applied to the control of a mobile robot in an unstructured environment as well as structured environment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권1호
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• pp.23-28
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• 2004

This paper proposes a sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable accurate measurement, such as, distance to an obstacle and location of the service robot itself. In the conventional fusion schemes, the measurement is dependent on the current data sets. As the results, more of sensors are required to measure a certain physical parameter or to improve the accuracy of the measurement. However, in this approach, instead of adding more sensors to the system, the temporal sequence of the data sets are stored and utilized for the measurement improvement. Theoretical basis is illustrated by examples and the effectiveness is proved through the simulations. Finally, the new space and time sensor fusion(STSF) scheme is applied to the control of a mobile robot in an unstructured environment as well as structured environment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제10권4호
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• pp.281-286
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• 2010

We propose a space and time based sensor fusion method and a robust landmark detecting algorithm based on sensor fusion for mobile robot navigation. To fully utilize the information from the sensors, first, this paper proposes a new sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable an accurate measurement. Exploration of an unknown environment is an important task for the new generation of mobile robots. The mobile robots may navigate by means of a number of monitoring systems such as the sonar-sensing system or the visual-sensing system. The newly proposed, STSF (Space and Time Sensor Fusion) scheme is applied to landmark recognition for mobile robot navigation in an unstructured environment as well as structured environment, and the experimental results demonstrate the performances of the landmark recognition.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 춘계학술대회논문집
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• pp.34-40
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• 2001

Aeroacoustic technology to improve the acoustic comfort in high-speed became a major topic in vehicle development process. Although most of wind noise reduction and sound quality improvements are possible with full vehicle, the countermeasures should be applied at the early design stage. Acoustic holography technology was used to identify the external wind noise sources of a vehicle in Hyundai Aeroacoustic Wind Tunnel. Microphone self-noise reduction techniques and several reference microphone positions are investigated in order to obtain proper results.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.63-63
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• 2004

기계류는 대개 부정형의 형상을 지니고 있으며, 또 표면이 모두 연결되어 있으므로, 진동하는 물체 표면상에서의 소음원 특성을 세밀히 파악하는 일은 매우 어려운 일이다. 음향 인텐시티나 공간 푸리에 변환을 이용하는 홀로그래피 기법 등의 어레이 마이크에 의한 기법들이 제안되었고 또 활용되고 있으나, 이는 어디까지나 음원에서 가까운 음장을 가상적인 음원면이라 보고 재구성하는 것이어서 실제 음원의 특성을 파악하는데 어려움이 있다. 이러한 문제점을 해결하기 위해 음원표면을 경계요소화 모델링을 하고, 어레이 마이크로 측정될 음장의 지점과 표면간의 관계를 수학적으로 정리한 후, 마이크에서 측정된 신호를 이용해 역으로 경계요소해석 계산을 수행하여 음원 특성을 파악하는 기법이 제안되었다. 본 발표에 있어서는 이와 같은 취지에서 ‘개발된 Inverse BEM을 이용한 NAH 기법’에 관한 개괄적인 내용을 설명하고, 그 적용 가능성 및 이 기법의 미래에 대해 설명하며, 다음과 같은 내용의 순서대로 설명된다: $\textbullet$ 각종 음원 파악 기법들의 특성과 이 방법이 필요한 이유 $\textbullet$일반 음향 holography 기법 (STSF)과의 차이점 $\textbullet$ 이론적 배경 개괄 $\textbullet$ 실제 적용 순서에 따른 방법의 설명 $\textbullet$ 후처리 결과물 $\textbullet$ 본 기법의 향후 과제 및 적용 방법의 개선