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모드 확장법을 이용한 유도 전동기의 진동 및 방사소음 예측
황창주,서왕기,송경준 한국음향학회 2026 한국음향학회지 Vol.45 No.3
본 연구에서는 운전 중인 유도 전동기의 진동 및 방사소음 특성을 규명하기 위해, 실험 데이터와 해석 모델을결합한 모드 확장법(Modal Expansion Method, MEM) 기반의 예측 기법을 제안하고 그 유효성을 검증하였다. 먼저, 신뢰성 있는 모드 선정을 위해 실험 모드 해석을 수행하였으며, 실험과 해석 간의 모드 상관 계수(Modal Assurance Criterion, MAC) 비교를 통해 해석 모델의 타당성을 검토하였다. 이후, 선정된 모드 형상과 운전 변형 형상(Operational Deflection Shape, ODS)을 활용한 계측 가속도로부터 각 절점의 기여도를 산정하였고, 이를 바탕으로미계측 지점을 포함한 전동기 표면 전체의 진동 거동을 예측하였다. 예측된 진동장을 음원으로 적용하여 유한요소법(Finite Element Method, FEM) 기반 구조·음향 연성 해석을 수행하였으며, 이를 통해 방사소음을 예측하였다. 최종적으로 예측과 실험 결과 간의 상관성 분석을 통해 제안한 기법의 정확성을 검증하였다. 본 연구 결과는 유도 전동기의 저진동·저소음 설계를 위한 정량적 설계 기반 자료로 활용될 수 있을 것으로 기대된다. This study proposes and validates a Modal Expansion Method (MEM) based prediction approach for estimating the vibration and radiated noise characteristics of an induction motor under operating conditions. The proposed method combines experimentally measured vibration responses with a finite element model. Experimental Modal Analysis (EMA) was first conducted to identify reliable structural modes, and the finite element model was validated by comparing experimental and numerical mode shapes using the Modal Assurance Criterion (MAC). The selected mode shapes and Operational Deflection Shape (ODS) data measured during motor operation were then used to estimate the Modal Participation Factor (MPF) from measured acceleration responses. Using the estimated modal contributions, the vibration response over the entire motor surface, including unmeasured regions, was reconstructed. The reconstructed surface vibration field was applied as an acoustic excitation source in a finite element–based structural·acoustic coupled analysis to predict the radiated noise. Finally, the predicted vibration and noise results were compared with experimental measurements to verify the accuracy of the proposed method. The results indicate that the MEM-based approach can effectively predict the vibration and radiated noise of an operating induction motor and can be used as a quantitative tool for low-vibration and low-noise motor design.
장거리 공대공 유도탄 동적 신뢰성 예측 모델 구축에 대한 연구
이민형,이종홍,권병기,이철,방성일 항공우주시스템공학회 2025 항공우주시스템공학회지 Vol.19 No.6
This paper outlines the research process for developing a reliability prediction model to better understand the dynamic characteristics of long-range air-to-air missiles. A dummy missile was designed and manufactured to meet established performance targets, and a finite element analysis (FEA) model was created for it. The dynamic characteristics of the manufactured dummy missile were tested, and the results were compared with those from the FEA model. Based on this comparison, the finite element model was updated to finalize the analysis.
기여도 분석법을 이용한 자동차 브레이크 시스템의 스퀼 소음 예측
이종기(Jong Ghi Lee),임현석(Hyun Seok Lim),김희용(Hee Yong Kim),백재욱(Jae Wook Baek) 대한기계학회 2009 大韓機械學會論文集A Vol.33 No.10
A method for determining the geometric stability characteristics of a brake corner module (BCM) is presented. Since disc brake “squeal” noise typically occurs at unstable resonant frequencies of a system, the likelihood of disc brake squeal for a particular design can be determined. Finite element methods are used to derive complex eigenvalue for a brake corner module. Some unstable modes calculated by finite element methods correspond to squeal noise data. Through kinetic energy participation analysis for each part of BCM, we can efficiently predict squeal noise data.
기여도 분석법을 이용한 자동차 브레이크 시스템의 스퀼 소음 예측
이종기(Jong Ghi Lee),임현석(Hyun Seok Lim),김희용(Hee Yong Kim),백재욱(Jae Wook Baek) 대한기계학회 2009 대한기계학회 춘추학술대회 Vol.2009 No.5
A method for determining the geometric stability characteristics of a brake comer module(BCM) is presented. Since disc brake squeal noise typically occurs at unstable resonant frequencies of a system, the likelihood of disc brake squeal for a particular design can be determined. Finite element methods are used to derive complex eigenvalue about a brake comer module. Some unstable modes calculated by finite element methods correspond to squeal noise data. Through kinetic energy participation analysis for each parts of BCM, we can efficiently predict about squeal noise data.