• Smart Structures and Systems
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• v.15 no.2
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• pp.489-503
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• 2015

Response estimation at unmeasured locations using the limited number of measurements is an attractive topic in the field of structural health monitoring (SHM). Because of increasing complexity and size of civil engineering structures, measuring all structural responses from the entire body is intractable for the SHM purpose; the response estimation can be an effective and practical alternative. This paper investigates a response estimation technique based on the Kalman state estimator to combine multi-sensor data under non-zero mean input excitations. The Kalman state estimator, constructed based on the finite element (FE) model of a structure, can efficiently fuse different types of data of acceleration, strain, and tilt responses, minimizing the intrinsic measurement noise. This study focuses on the effects of (a) FE model error and (b) combinations of multi-sensor data on the estimation accuracy in the case of non-zero mean input excitations. The FE model error is purposefully introduced for more realistic performance evaluation of the response estimation using the Kalman state estimator. In addition, four types of measurement combinations are explored in the response estimation: strain only, acceleration only, acceleration and strain, and acceleration and tilt. The performance of the response estimation approach is verified by numerical and experimental tests on a simply-supported beam, showing that it can successfully estimate strain responses at unmeasured locations with the highest performance in the combination of acceleration and tilt.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1934-1942
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• 2015

An estimation problem in the environment which GPS signals do not reach, should be solved by employing an indoor location estimation scheme. Location estimation schemes for indoor environments generally include the AOA, TOA, RSS, Fingerprint, and TDOA. For a ship environment where there exist many spaces enclosed by iron plates, the TDOA scheme is appropriate because location estimation is usually performed at a closed range. In this paper, we address the problem of estimating the location of a terminal under the ship environment. The problem of location estimation by using the TDOA is presented in detail, and then an algorithm for applying the estimation to the ship environment is proposed. Finally, the proposed algorithm of location estimation in a ship by the TDOA scheme is verified through simulations from three viewpoints.

• Journal of Applied Reliability
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• v.16 no.1
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• pp.32-40
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• 2016

Purpose: The purpose of this study is to analyze the effect of sampling points on accuracy of storage reliability estimation for one-shot systems by assuming a weibull distribution as a storage reliability distribution. Also propose method for determining of sampling points for increase the accuracy of reliability estimation. Methods: Weibull distribution was divided into three sections for confirming the possible to estimate the parameters of the weibull distribution only some section's sample. Generate quantal response data for failure data. And performed parameter estimation with quantal response data. Results: If reduce sample point interval of 1 section, increase the accuracy of reliability estimation although sampling only section 1. Even reduce total number of sampling point, reducing sampling time interval of the 1 zone improve the accuracy of reliability estimation. Conclusion: Method to increase the accuracy of reliability estimation is increasing number of sampling and the sampling points. But apply this method to One-shot system is difficult because test cost of one-shot system is expensive. So propose method of accuracy of storage reliability estimation of one-shot system by adjustment of the sampling point. And by dividing the section it could reduce the total sampling point.

• Journal of Biomedical Engineering Research
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• v.31 no.4
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• pp.285-291
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• 2010

Recently, advance on various modalities of diagnosing, prostate volume estimation became possible not only by the existing two-dimension medical images data but also by the three-dimensional medical images data. In this study, magnetic resonance image (MRI), computer tomography (CT) and ultrasound (US) were employed to evaluate prostate phantom volume measurements for estimation, comparison and analysis. For the prostate phantoms aimed at estimating the volume, total of 17 models were developed by using devils-tongue jelly and changing each of the 5ml of capacity from 20ml to 100ml. For the volume estimation through 2D US, the calculation of the diameter with C9-5Mhz transducer was conducted by ellipsoid formula. For the volume estimation through 3D US, the Qlab software (Philips Medical) was used to calculate the volume data estimated by 3D9-3Mhz transducer. Moreover, the images by 16 channels CT and 1.5 Tesla MRI were added by the method of continuous cross-section addition and each of imaginary prostate model's volume was yielded. In the statistical analysis for comparing the availability of volume estimation, the correlation coefficient (r) was more than 0.9 for all indicating that there were highly correlated, and there were not statistically significant difference between each of the correlation coefficient (p=0.001). Therefore, the estimation of prostate phantom volume using three-dimensional modalities of diagnosing was quite closed to the actual estimation.

• Journal of Korea Society of Waste Management
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• v.35 no.8
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• pp.777-784
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• 2018

Since climate change increases the risk of extreme rainfall events, concerns on flood management have also increased. In order to rapidly recover from flood damages and prevent secondary damages, fast collection and treatment of flood debris are necessary. Therefore, a quick and precise estimation of flood debris generation is a crucial procedure in disaster management. Despite the importance of debris estimation, methodologies have not been well established. Given the intrinsic heterogeneity of flood debris from local conditions, a regional-scale model can increase the accuracy of the estimation. The objectives of this study are 1) to identify significant damage variables to predict the flood debris generation, 2) to ascertain the difference in the coefficients, and 3) to evaluate the accuracy of the debris estimation model. The scope of this work is flood events in Ulsan city region during 2008-2016. According to the correlation test and multicollinearity test, the number of damaged buildings, area of damaged cropland, and length of damaged roads were derived as significant parameters. Key parameters seems to be strongly dependent on regional conditions and not only selected parameters but also coefficients in this study were different from those in previous studies. The debris estimation in this study has better accuracy than previous models in nationwide scale. It can be said that the development of a regional-scale flood debris estimation model will enhance the accuracy of the prediction.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.7
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• pp.1068-1079
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• 2008

Tilt and heading angles information of a remotely operated vehicle (ROV) are very important in underwater navigation. This paper presents a low.cost tilt and heading estimation system. Three single.axis rate gyros, a tri-axis accelerometer, and a tri-axis magnetometer are used. Output signals coming from these sensors are fused by two Kalman filters. The first Kalman filter is used to estimate roll and pitch angles and the other is for heading angle estimation. By using this method, we have obtained tilt (roll and pitch angles) and heading information which are reliable over long period of time. Results from experiments have shown the performance of the presented system.

• Journal of Broadcast Engineering
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• v.6 no.1
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• pp.72-81
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• 2001

An adaptive channel estimation technique for OFDM-based DTV receivers is proposed using a new mobility estimator. Sample mean techniques for channel estimation have displayed good performance in slow fading channels, because averaging reduces noise In channel estimation operation. This paper suggests an algorithm which selects the optimal number of symbols within which the sample mean of consecutive pilot data can be obtained. The designed mobility estimator determines the optimal number by comparing mobility variance and estimated noise valiance. The algorithm using the mobility estimator obtains an optimal channel function under time-invariant or time-variant multipath fading channels, thereby making the best BER performance.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.574-576
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• 2004

Since variance of noise is important parameter for a noise filter to reduce noise in image and the performance of noise filter is dependent on estimated variance. In this paper, we apply additive noise variance estimation method to estimate variance of speckle noise of synthetic aperture radar (SAR) imagery. Generally, speckle noise is in multiplicative model, logarithmic transformation is then used to transform multiplicative model into additive model. Here, speckle noise is generally modeled as Gamma distribution function with different looks. The additive noise variance estimation is processed in log domain. The synthesis image and real image of SAR are implemented to test and confirm results and show that more accurate estimation can be achieved.

• Proceedings of the KSRS Conference
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• v.1
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• pp.239-242
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• 2006

Impervious surface is an important index for the estimation of urbanization and environmental change. In addition, impervious surface has an influence on the parameters of rainfall-runoff model during rainy season. The increase of impervious surface causes peak discharge increasing and fast concentration time in urban area. Accordingly, impervious surface estimation is an important factor of urban rainfall-runoff model development and calibration. In this study, impervious surface estimation is performed by using remote sensing images such as landsat-7 ETM+ and high resolution satellite image and regression tree algorithm based on case study area ? Jungnang-cheon basin in Korea.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2385-2388
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• 2005

In this paper, we propose the estimation method for the image affine information for computer vision. The first estimation method is given based on the XYS image normalization and the second estimation method is based on the image normalization by Pei and Lin. The XYS normalization method turns out to have better performance than the method by Pei and Lin. In addition, we show that rotation and aspect ratio information can be obtained using the central moments of both the original image and the sensed image. Finally, we propose the modified version of the normalization method so that we may control the size of the image.