• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권8호
• /
• pp.2718-2731
• /
• 2021

In the structural health monitoring of composite materials, in order to solve the ill-posed problem of impact force reconstruction, regularization techniques are often used to deal with it. Due to the poor convergence of the traditional Tikhonov regularization method, in order to accurately reconstruct the time history of the impact force, this paper improves Tikhonov regularization method and constructs homotopy function with strong convergence. Since the optimal regularization parameters need to be found in the homotopy function, the Newton downhill method is used to find the optimal parameters and the homotopy function can be calculated, which can accurately reconstruct the time history of the impact force. In order to verify the universality of the method in this paper, impact hammers of different materials were used in the experiment in this paper to study and compare the reconstruction effect of impact time history of different impact hammers.

• 전기전자학회논문지
• /
• 제19권1호
• /
• pp.33-40
• /
• 2015

전기 임피던스 단층촬영법(EIT)에서 역문제는 매우 높은 비정치성이므로 이것을 완화시키기 위해서 사전정보가 사용되고 EIT 역문제를 푸는 과정에서 만족스러운 복원성능을 갖기 위해 조정 기법은 적용된다. 반복적 Gauss-Newton 방법은 정확성과 빠른 수렴속도로 인해서 일반적으로 역문제를 푸는데 사용되지만 항상 좋은 성능을 내는 것은 아니며 조정 인자 선택에 따라 성능이 좌지우지된다. 비록 L-곡선과 같이 조정 인자를 결정하는데 이용할 수 있는 여러 가지 방법들이 존재하지만 이러한 방법들이 모든 경우에 적용할 수 있는 것은 아니다. 게다가 조정 인자는 스칼라이고 반복 연산동안 변하지 않는다. 그러므로 이 논문에서는 복원 성능을 향상시키기 위해서 조정 인자를 결정해주는 새로운 방법을 사용하였다. 각각의 반복 연산과정에서 도전율의 norm을 구하고 이것을 대각 행렬형태인 조정 인자를 구하는데 사용한다. 제안한 방법을 인체 흉부 영상 복원에 적용하였고, 기존의 방법들과 복원 성능을 비교하였다. 모의실험 결과, 기존의 방법들과 비교해서 개선된 성능을 확인할 수 있었다.

• Structural Engineering and Mechanics
• /
• 제55권6호
• /
• pp.1157-1176
• /
• 2015

This study presents optimizing structural topology patterns using regularization of Heaviside function. The present method needs not filtering process to typical SIMP method. Using the penalty formulation of the SIMP approach, a topology optimization problem is formulated in co-operation, i.e., couple-signals, with design variable values of discrete elements and a regularized Heaviside step function. The regularization of discontinuous material distributions is a key scheme in order to improve the numerical problems of material topology optimization with 0 (void)-1 (solid) solutions. The weak forms of an equilibrium equation are expressed using a coupled regularized Heaviside function to evaluate sensitivity analysis. Numerical results show that the incorporation of the regularized Heaviside function and the SIMP leads to convergent solutions. This method is tested using several examples of a linear elastostatic structure. It demonstrates that improved optimal solutions can be obtained without the additional use of sensitivity filtering to improve the discontinuous 0-1 solutions, which have generally been used in material topology optimization problems.

• 한국농공학회논문집
• /
• 제61권6호
• /
• pp.9-19
• /
• 2019

Vegetative Filter Strip (VFS) is the best management practice which has been widely used to mitigate water pollutants from agricultural fields by alleviating runoff and sediment. This study was conducted to improve an equation for estimating sediment trapping efficiency of VFS using several different regularization methods (i.e., ordinary least squares analysis, LASSO, ridge regression analysis and elastic net). The four different regularization methods were employed to develop the sediment trapping efficiency equation of VFS. Each regularization method indicated high accuracy in estimating the sediment trapping efficiency of VFS. Among the four regularization methods, the ridge method showed the most accurate results according to $R^2$, RMSE and MAPE which were 0.94, 7.31% and 14.63%, respectively. The equation developed in this study can be applied in watershed-scale hydrological models in order to estimate the sediment trapping efficiency of VFS in agricultural fields for an effective watershed management in Korea.

• 한국음향학회지
• /
• 제42권4호
• /
• pp.364-369
• /
• 2023

두 개 수신기에 들어오는 신호 간의 시간 지연 추정 기술은 수중 음향 뿐만 아니라 실내 음향 및 로보틱스에 이르기까지 다양한 분야에서 응용되고 있는 기술이다. 시간 지연 추정 기술에는 수신기 사이 상호 상관으로부터 시간 지연량을 추정하는 방법이 한 기술 부류이고, 수신기 사이의 시간 지연을 파라메트릭 모델링을 하여 그 파라미터를 시스템 인식의 방법으로 추정하는 기술 부류가 있다. 두 부류 중 후자의 경우 시스템의 파라미터 중에서 지연과 직접 관련 있는 파라미터는 전체 중 극히 일부라는 특성이 있다. 이 특성을 이용하여 Lasso 정규화 같은 방법으로 추정 정확도를 높이기도 한다. 그러나 Lasso 정규화의 경우 필요한 정보가 소실되는 경우가 발생한다. 본 논문에서는 이를 보완하기 위해서 Lasso 정규화에 Ridge 정규화를 덧붙인 Elastic Net을 사용한 방법을 제안한다. 제안한 방법을 기존의 일반 상호 상관(Generalized Cross Correlation, GCC) 방법 및 Lasso 정규화를 사용한 방법과 비교하여, 백색 가우시안 신호원 및 유색 신호원에서도 추정 오차가 매우 적음을 보인다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권11호
• /
• pp.5481-5495
• /
• 2018

Single pixel imaging technology has developed for years, however the video acquisition on the single pixel camera is not a well-studied problem in computer vision. This work proposes a new scheme for single pixel camera to acquire video data and a new regularization for robust signal recovery algorithm. The method establishes a single pixel video compressive sensing scheme to reconstruct the video clips in spatial domain by recovering the difference of the consecutive frames. Different from traditional data acquisition method works in transform domain, the proposed scheme reconstructs the video frames directly in spatial domain. At the same time, a new regularization called spatial cluster is introduced to improve the performance of signal reconstruction. The regularization derives from the observation that the nonzero coefficients often tend to be clustered in the difference of the consecutive video frames. We implement an experiment platform to illustrate the effectiveness of the proposed algorithm. Numerous experiments show the well performance of video acquisition and frame reconstruction on single pixel camera.

• Structural Engineering and Mechanics
• /
• 제82권6호
• /
• pp.771-783
• /
• 2022

Structural damage identification (SDI) methods have been proposed to monitor the safety of structures. However, the traditional SDI methods using modal parameters, such as natural frequencies and mode shapes, are not sensitive enough to structural damage. To tackle this problem, this paper proposes a new SDI method based on transmissibility assurance criterion (TAC) and weighted Schatten-p norm regularization. Firstly, the transmissibility function (TF) has been proved a useful damage index, which can effectively detect structural damage under unknown excitations. Inspired by the modal assurance criterion (MAC), TF and MAC are combined to construct a new damage index, so called as TAC, which is introduced into the objective function together with modal parameters. In addition, the weighted Schatten-p norm regularization method is adopted to improve the ill-posedness of the SDI inverse problem. To evaluate the effectiveness of the proposed method, some numerical simulations and experimental studies in laboratory are carried out. The results show that the proposed method has a high SDI accuracy, especially for weak damages of structures, it can precisely achieve damage locations and quantifications with a good robustness.

• 전기전자학회논문지
• /
• 제18권2호
• /
• pp.272-281
• /
• 2014

전기 임피던스 단층촬영법을 이용한 정적 영상 복원에서 대표적으로 사용되고 있는 복원 알고리즘은 modified Newton-Raphson(mNR) 알고리즘으로 수렴 속도 및 추정 정확도 측면에서 비교적 다른 알고리즘들에 비해 좋은 성능을 나타낸다. mNR 알고리즘에서는 측정 전압과 계산 전압과의 차이, 즉 잔류오차를 최소화하도록 목적함수를 설정하고 이를 반복 연산하여 내부의 저항률 분포를 추정한다. 이때 EIT 역문제의 비정치성을 완화시키기 위해 조정방법을 사용하며 조정인자에 따라 서로 다른 영상 복원 성능을 나타낸다. 기존 기법에서는 반복 연산마다 일정한 상수 값의 조정인자를 사용하기 때문에 대상 물체의 내부 상태가 변하거나 측정 잡음 등이 있는 경우 때때로 조정인자에 따라 영상 복원이 수렴되지 않는다. 따라서 본 논문에서는 영상 복원 수렴 및 성능을 개선하기 위하여 잔류오차에 기반하여 반복 연산마다 자동적으로 조정인자를 수정하는 기법을 제안하였다. 시뮬레이션과 실험을 수행하여 제안된 기법의 영상 복원성능을 평가한 결과 비교적 양호한 성능을 나타내었다.

• Smart Structures and Systems
• /
• 제31권3호
• /
• pp.229-245
• /
• 2023

The absence of excitation measurements may pose a big challenge in the application of structural damage identification owing to the fact that substantial effort is needed to reconstruct or identify unknown input force. To address this issue, in this paper, an iterative strategy, a synergy of Tikhonov regularization method for force identification and modified Jaya algorithm (M-Jaya) for stiffness parameter identification, is developed for damage identification with partial output-only responses. On the one hand, the probabilistic clustering learning technique and nonlinear updating equation are introduced to improve the performance of standard Jaya algorithm. On the other hand, to deal with the difficulty of selection the appropriate regularization parameters in traditional Tikhonov regularization, an improved L-curve method based on B-spline interpolation function is presented. The applicability and effectiveness of the iterative strategy for simultaneous identification of structural damages and unknown input excitation is validated by numerical simulation on a 21-bar truss structure subjected to ambient excitation under noise free and contaminated measurements cases, as well as a series of experimental tests on a five-floor steel frame structure excited by sinusoidal force. The results from these numerical and experimental studies demonstrate that the proposed identification strategy can accurately and effectively identify damage locations and extents without the requirement of force measurements. The proposed M-Jaya algorithm provides more satisfactory performance than genetic algorithm, Gaussian bare-bones artificial bee colony and Jaya algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권3호
• /
• pp.1403-1417
• /
• 2019

With the rapid growth of multimedia data, research on cross-media feature learning has significance in many applications, such as multimedia search and recommendation. Existing methods are sensitive to noise and edge information in multimedia data. In this paper, we propose a semi-supervised method for cross-media feature learning by means of $L_{2,q}$ norm to improve the performance of cross-media retrieval, which is more robust and efficient than the previous ones. In our method, noise and edge information have less effect on the results of cross-media retrieval and the dynamic patch information of multimedia data is employed to increase the accuracy of cross-media retrieval. Our method can reduce the interference of noise and edge information and achieve fast convergence. Extensive experiments on the XMedia dataset illustrate that our method has better performance than the state-of-the-art methods.