• Journal of Electrical Engineering and information Science
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• 제3권1호
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• pp.86-93
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• 1998

In this paper, we propose an effective on-line identification method for rotor resistance, which is useful in making speed control of induction motors without rotational transducers robust with respect to the variation in rotor resistance. Our identification method for rotor resistance is based on the linearly perturbed equations of the closed-loop system for sensorless speed control about th operating point. Our identification method for rotor resistance uses only the information of stator currents and voltages. In can provide fairly good identification accuracy regardless of load conditions. Some experimental results are presented to demonstrate the practical use of our identification method. For our experimental work, we have built a sensorless control system, in which all algorithms are implemented on a DSP. Our experimental results confirm that our on-line identification method allows for high precision speed control of commercially available induction motors without rotational transducers.

• Smart Structures and Systems
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• 제30권3호
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• pp.273-286
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• 2022

In recent years, vision-based monitoring has received great attention. However, structural identification using vision-based displacement measurements is far less established. Especially, simultaneous identification of structural systems and unknown excitation using vision-based displacement measurements is still a challenging task since the unknown excitations do not appear directly in the observation equations. Moreover, measurement accuracy deteriorates over a wider field of view by vision-based monitoring, so, only a portion of the structure is measured instead of targeting a whole structure when using monocular vision. In this paper, the identification of structural system and excitations using vision-based displacement measurements is investigated. It is based on substructure identification approach to treat of problem of limited field of view of vision-based monitoring. For the identification of a target substructure, substructure interaction forces are treated as unknown inputs. A smoothing extended Kalman filter with unknown inputs without direct feedthrough is proposed for the simultaneous identification of substructure and unknown inputs using vision-based displacement measurements. The smoothing makes the identification robust to measurement noises. The proposed algorithm is first validated by the identification of a three-span continuous beam bridge under an impact load. Then, it is investigated by the more difficult identification of a frame and unknown wind excitation. Both examples validate the good performances of the proposed method.

• Wind and Structures
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• 제24권5호
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• pp.481-500
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• 2017

A novel three-degree-of-freedom (DOF) forced vibration system has been developed for identification of aeroelastic (self-excited) load parameters used in time-domain response analysis of wind-excited flexible structures. This system is capable of forcing sinusoidal motions on a section model of a structure that is used in wind tunnel aeroelastic studies along all three degrees of freedom - along-wind, cross-wind, and torsional - simultaneously or in any combination thereof. It utilizes three linear actuators to force vibrations at a consistent frequency but varying amplitudes between the three. This system was designed to identify all the parameters, namely, aeroelastic- damping and stiffness that appear in self-excited (motion-dependent) load formulation either in time-domain (rational functions) or frequency-domain (flutter derivatives). Relatively large displacements (at low frequencies) can be generated by the system, if required. Results from three experiments, airfoil, streamlined bridge deck and a bluff-shaped bridge deck, are presented to demonstrate the functionality and robustness of the system and its applicability to multiple cross-section types. The system will allow routine identification of aeroelastic parameters through wind tunnel tests that can be used to predict response of flexible structures in extreme and transient wind conditions.

• 한국인터넷방송통신학회논문지
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• 제17권2호
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• pp.199-204
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• 2017

본 연구는 가정 내에서 사용하는 가전 기기의 사용 에너지를 효율적으로 관리하기 위한 비접촉 가전 기기 식별 기법을 제시한다. 제안하는 기법은 총 전력 사용량 정보를 이용한 기존의 가전 기기 식별 기법을 개선하기 위해서 복합 센서 정보를 종합적으로 활용한다. 이를 위해서 기기 상태와 측정된 센서 값 간의 영향도를 그래프 형태로 정의한다. 기기 상태에 영향을 미치는 복합 센서를 표현하는 영향도 그래프를 통해 기기 식별 예측 결과를 계산하기 위해 총 전력 사용량 기반 예측값과 센서 데이터 처리 알고리즘 예측값의 가중치 합을 사용한다. 시뮬레이션 실험을 통한 성능 분석으로 기존 비접촉 가전 기기 식별 기법의 기기 식별 정확도와 비교한다.

• 한국구조물진단유지관리공학회 논문집
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• 제18권2호
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• pp.64-73
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• 2014

본 연구에서는 철골 골조 구조물의 안전성 모니터링을 위하여 계측한 변형률을 통해 구조물에 작용한 하중을 식별하는 알고리즘을 제안한다. 기존의 시스템 식별 연구에서 구조물의 강성 등을 변수화한 것과는 다르게, 본 연구에서는 구조물에 작용한 하중과 이로 인해 구조물에 발생하는 변형률 간의 관계를 행렬로 정의하고, 이 행렬 및 작용한 하중을 변수화 한다. 계측한 변형률과 변수를 통해 추정한 변형률 사이의 차이를 오차함수로 설정하고 이를 최소화시키기 위해 최적화 알고리즘 중 하나인 유전자 알고리즘을 적용한다. 구해진 변수와 계측 변형률을 통해 작용한 하중을 식별하고 구조물의 하중 변화 시 미계측 지점의 응답을 추정한다. 본 연구에서 제안하는 하중 식별 알고리즘을 검증하기 위해 3차원 철골 골조 구조물의 정적 가력 실험을 수행하였고, 계측한 변형률을 통해 가해진 하중을 낮은 오차 수준으로 식별할 수 있었다. 또한, 하중 조건 변화 시, 계측한 변형률을 통해 모니터링 대상이 되는 미계측 지점의 변형률을 0.17~3.13%의 오차 범위로 추정하였다. 본 연구가 제안하는 식별법이 철골 구조물의 보다 현실적인 안전성 모니터링에 효과적으로 적용될 것으로 기대된다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2002년도 추계학술대회 논문집(II)
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• pp.1065-1073
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• 2002

A new damage identification technique using static displacement data is developed to assess the structural integrity of bridge structures. In the conventional damage assessment techniques using dynamic response, it is usually difficult to obtain a significant natural frequencies variation from the measured data because the natural frequencies variation is intrinsically not sensitive to the damage of a bridge. In this proposed identification method, the stiffness reduction of the bridges can be estimated using the static displacement data measured periodically and a specific loading test is not required. The static displacement data due to the dead load of the bridge structure can be measured by devices such as a laser displacement sensor. In this study, structural damage is represented by the reduction in the elastic modulus of the element. The damage factor of the element is introduced to estimate the stiffness reduction of the bridge under consideration. Finally, the proposed algorithm is verified using various numerical simulation and compared with other damage identification method. Also, the effect of noise and number of damaged elements on the identification are investigated. The results show that the proposed algorithm is efficient for damage identification of the bridges.

• Structural Engineering and Mechanics
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• 제50권1호
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• pp.105-119
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• 2014

This study presents a steel container crane movement analysis and assessment based on structural health monitoring (SHM). The accelerometers are used to monitor the dynamic crane behavior and a 3-D finite element model (FEM) was designed to express the static displacement of the crane under the different load cases. The multi-input single-output nonlinear autoregressive neural network with external input (NNARX) model is used to identify the crane dynamic displacements. The FEM analysis and the identification model are used to investigate the safety and the vibration state of the crane in both time and frequency domains. Moreover, the SHM system is used based on the FEM analysis to assess the crane behavior. The analysis results indicate that: (1) the mean relative dynamic displacement can reveal the relative static movement of structures under environmental load; (2) the environmental load conditions clearly affect the crane deformations in different load cases; (3) the crane deformations are shown within the safe limits under different loads.

• Smart Structures and Systems
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• 제21권1호
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• pp.53-64
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• 2018

Nondestructive testing methods are required to assess the condition of civil structures and formulate their maintenance programs. Axial force identification is required for several structural members of truss bridges, pipe racks, and space roof trusses. An accurate evaluation of in situ axial forces supports the safety assessment of the entire truss. A considerable redistribution of internal forces may indicate structural damage. In this paper, a novel compressive force identification method for prismatic members implemented using static deflections is applied to steel beams. The procedure uses the Euler-Bernoulli beam model and estimates the compressive load by using the measured displacement along the beam's length. Knowledge of flexural rigidity of the member under investigation is required. In this study, the deflected shape of a compressed steel beam is subjected to an additional vertical load that was short-term measured in several laboratory tests by using fiber Bragg grating-differential settlement measurement (FBG-DSM) sensors at specific cross sections along the beam's length. The accuracy of midspan deflections offered by the FBG-DSM sensors provided excellent force estimations. Compressive load detection accuracy can be improved if substantial second-order effects are induced in the tests. In conclusion, the proposed method can be successfully applied to steel beams with low slenderness under real conditions.

• 대한의용생체공학회:의공학회지
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• 제24권6호
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• pp.501-507
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• 2003

환자의 재활을 돕는 보조기 및 의지와 같은 의료기기의 기본 요건 중의 하나는 충분한 강도를 가지도록 설계해야 하는 것이다. 강도설계를 위해서는 먼저 기구에 작용하는 부하를 파악하여야 하는데, 인체에 직접 착용하거나, 인체의 운동을 돕도록 고안된 의료기구의 특성상 정하중 보다는 동하중 형태의 부하를 받는 경우가 많으며, 때때로 충격하중을 받는 경우도 있다. 이같은 형태의 부하를 직접적으로 파악하기 위해서는 구조물에 계측용 센서를 직접 설치하여야 하나, 이럴 경우 센서의 설치로 인한 구조 변경으로 인해 계의 고유 특성을 유지할 수 없는 경우가 흔히 발생하다. 따라서, 이와 같은 경우에는 작용 부하를 간접적으로 즉, 진동 등의 출력으로부터 역으로 구해내는 수 밖에는 없다. 본 논문에서는 이와 같은 동하중 형태의 부하 즉, 작동부하를 구하는 데 있어서 기존 방법인 전달률 방법의 문제점 및 한계점을 살펴보고, 다수개의 기준점을 사용하여 다입력 환경하에서도 적용이 가능한 주성분 분석을 이용한 새로운 방법을 제시하였으며, 실험을 통해 이의 타당성을 검증하였다.

• International Journal of Contents
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• 제6권3호
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• pp.5-9
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• 2010

To manage large database system with video, effective video indexing and retrieval are required. A large number of video retrieval algorithms have been presented for frame-wise user query or video content query, whereas a few video identification algorithms have been proposed for video sequence query. In this paper, we propose an effective video identification algorithm for video sequence query that employs the Cauchy function of histograms between successive frames and the modified Hausdorff distance. To effectively match the video sequences with a low computational load, we make use of the key frames extracted by the cumulative Cauchy function and compare the set of key frames using the modified Hausdorff distance. Experimental results with several color video sequences show that the proposed algorithm for video identification yields remarkably higher performance than conventional algorithms such as Euclidean metric, and directed divergence methods.