• Smart Structures and Systems
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• v.22 no.5
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• pp.631-641
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• 2018

This paper outlines a computational procedure for the effective merging of diverse sensor measurements, displacement and acceleration signals in particular, in order to successfully monitor and simulate the current health condition of civil structures under dynamic loadings. In particular, it investigates a Kalman Filter implementation for the Heterogeneous Data Fusion of displacement and acceleration response signals of a structural system toward dynamic identification purposes. The procedure is perspectively aimed at enhancing extensive remote displacement measurements (commonly affected by high noise), by possibly integrating them with a few standard acceleration measurements (considered instead as noise-free or corrupted by slight noise only). Within the data fusion analysis, a Kalman Filter algorithm is implemented and its effectiveness in improving noise-corrupted displacement measurements is investigated. The performance of the filter is assessed based on the RMS error between the original (noise-free, numerically-determined) displacement signal and the Kalman Filter displacement estimate, and on the structural modal parameters (natural frequencies) that can be extracted from displacement signals, refined through the combined use of displacement and acceleration recordings, through inverse analysis algorithms for output-only modal dynamics identification, based on displacements.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.424-433
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• 2008

An ownship with towed array sonar (TAS) has limited maneuvers due to its dynamic feature, bearing and frequency measurements of a target which are not detected continuously but are often lost in ocean environment. We propose a pre-processing algorithm for the faded bearing and frequency measurements to solve the BFTMA problem of TAS under limited detection conditions. The proposed pre-processing algorithm to restore the faded bearing and frequency measurements is implemented to perform a BFTMA filter even if the measurements of a target are not continuously detected. The Modified Gain Extended Kalman Filter (MGEKF) method based on the Interacting Multiple Model (IMM) structure is applied for a BFTMA filter algorithm to estimate the target. Simulations for the various conditions were carried out to verify the applicability of the proposed algorithms, and confirmed superior estimation performance compared with the existing Bearings-Only TMA (BOTMA).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.12
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• pp.987-995
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• 2020

Accurate alignment between high-performance payloads and attitude control sensors is essential factor to guarantee accurate attitude orientation and high pointing stability of the satellite. Space craft developers often use theodolite measurement system for satellite alignment during ground AIT(Assembly Integration and Test) phase. When measuring theodolite, errors may occur due to line of sight error, tilting axis error, vertical index error, and vertical axis error. In addition, errors that can occur during alignment measurements with multiple theodolites are analyzed through the alignment cube measurements test. Based on the alignment cube measurements test, a technical method that can improve the alignment measurement accuracy was suggested and it's measurements results satisfied the satellite design requirements.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.361-363
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• 2007

Using intelligent systems, many users do effectively their works. In general, the effective usages of the systems have to possess the usability and accuracy. So, we need some measurements for evaluating the performance of the criteria. But, in most cases, objective measurements for the evaluation are not. In this paper, we propose a measurement technique for objective evaluated measuring of intelligent systems using probability measure.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.6
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• pp.877-884
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• 1994

In the power system state estimation, the J(x)-index test and normalized residuals ${\gamma}$S1NT have been the presence of bad measurements and identify their location. But, these methods require the complete re-estimation of system states whenever bad data is identified. This paper presents back-propagation neural network medel using autoregressive filter for identification of bad measurements. The performances of neural network method are compared with those of conventional mehtods and simulation results show the geed performance in the bad data identification based on the neural network under sample power system.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.1355-1357
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• 2008

Reflection measurements are critical to the evaluation of display performance under ambient illumination conditions. Various hemispherical reflection methods are evaluated for their suitability and robustness across display technologies. The standard integrating sphere method is compared to a sampling sphere apparatus.

• Wind and Structures
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• v.4 no.2
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• pp.101-118
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• 2001

This paper reports the field measurements concerning pressure equalization of rainscreen facades carried out at the Technical University of Eindhoven (TUE) in the Netherlands. The field facility including the details of test panel, meteorological tower, instrumentation, data collection and analysis is presented. Results of investigations into cavity response for various leakage and venting configurations are discussed. Frequency domain techniques have been utilized to show the influence of wind as well as facade characteristics on the pressure equalization performance. Further, this paper presents an early attempt to synthesize the experimental results into existing building codes.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.558-563
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• 1992

Bearing information of target is used critically for target tracking in underwater environment. In passive sonar, target bearing measurements are obtained by processing the acoustic signal emanating from the target. PDA tracking algorithm is usually applied in this case since bearing measurements have several peaks due to interference with other acoustic sources or reflections from underwater media. In this paper, we propose a modified PDA algorithm adopting new probabilistic distributions of the number, position, and amplitude of peaks based on the analysis of real data. This algorithm is tested on real and artificially generated data. The computer simulation result shows improvement of the tracking performance.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.556-561
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• 1987

This paper presents a suboptimal Kalman filter design method for the problem of tracking a maneuvering target. The design method is essentially based on linear target dynamics and linear-like structured measurements called pseudomeasurements. The pseudomeasurements are obtained by manipulating the original nonlinear measurements algebraically. The resulting filter has computational advantages over other filters with similar performance. Monte Carlo computer simulation results are included to demonstrate the effectiveness of the proposed suboptimal filter associated with the target acceleration model.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.345-352
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• 1998

Performance measurement is increasingly becoming a vital issue for promoting quality management within an organization. This research proposes a new performance measurement approach, called the Hierarchically Associated Performance Measurement, for the organizations which emphasize long term quality thrust through a balanced interface between the quality efforts of various units. The proposed approach is unique in that it considers relationships between internal quality activities and national quality award criteria and that it identifies and utilizes the quality responsibilities of functional units in order to encompass organizational roles in the evaluation process. The approach is illustrated via a numerical evaluation of a fictitious organization.