서지주요정보
다입력-단일출력계 모형을 이용한 소음/진동원 규명에 관한 연구 = Source identification methods by multiple-input/single output modeling
서명 / 저자 다입력-단일출력계 모형을 이용한 소음/진동원 규명에 관한 연구 = Source identification methods by multiple-input/single output modeling / 배병국.
저자명 배병국 ; Bae, Byung-Kook
발행사항 [대전 : 한국과학기술원, 1998].
Online Access 원문보기 원문인쇄

소장정보

등록번호

8008316

소장위치/청구기호

학술문화관(문화관) 보존서고

DME 98020

SMS전송

도서상태

이용가능

대출가능

반납예정일

초록정보

Several approaches can be employed to tackle source and path identification problems via multiple-input/single-output modeling. When the inputs are not correlated to each other, contribution of each input can be obtained easily by using the ordinary coherence function between the input and output. However, the independence among the measured inputs is not always warranted in real situations. Partial coherence function approach is one of them especially when the measured inputs are correlated to each other, in which conditioning of the inputs is performed before calculating the contribution of each input. On the other hand, virtual coherence function approach decompose simply the real correlated inputs into virtual independent inputs. The physical meanings, general advantages and limitations of several techniques via multiple-input/single-output modeling were discussed with an acoustical system. It is impractical or impossible to directly measure the physical sources in many experiments. From this difficulty, responses in the vicinities of the real sources are usually employed as inputs for the multiple-inpt/single-output modeling. The measured inputs therefore can be correlated to each other for the reason that physical sources are inherently correlated to each other or input measurements are contaminated by other sources. The linear relationships among the measured inputs can be explained in two ways. One possibility of the input correlation is the case where the inputs cause each other partially and another is the case where the measured inputs do not cause each other although they are correlated. In real situations, it may not be clear whether the linear relationship among the inputs is related with the causality or not. In order to make the conditioning analysis successful, first of all, priorities of the correlated inputs should be correctly decide corresponding to the physical situations in a given model. This problem can be resolved based on the property of transfer function between any pair of correlated inputs. Since the causalities among the inputs are frequency dependent and the conditioning analysis of the correlated inputs is more frequently performed in the frequency domain, Hilbert transform approach is introduced in this thesis to determine such priorities in frequency domain. Theoretical background of the proposed method was introduced and the procedure was illustrated through an application to measurements from an acoustical system. The feasibility of causality checking method and source identification methods have been demonstrated through practical applications.

서지기타정보

서지기타정보
청구기호 {DME 98020
형태사항 xv, 137 p. : 삽도 ; 26 cm
언어 한국어
일반주기 저자명의 영문표기 : Byung-Kook Bae
지도교수의 한글표기 : 김광준
지도교수의 영문표기 : Kwang-Joon Kim
수록잡지명 : "Hilbert transform approach in source identification via multiple-input/single-output modeling for correlated inputs". Mechanical Signature and Signal Processing. Academic Press Limited
학위논문 학위논문(박사) - 한국과학기술원 : 기계공학과,
서지주기 참고문헌 : p. 132-137
주제 다입력/단일출력
소음/진동원 규명
상관관계
우선순위
인과관계
힐버트변환
MISO(Multiple-Input/Single-Output
Source identification
Correlation
Priority
Causality
Hilbert transform
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