• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.4 s.74
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• pp.419-427
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• 2006

In this paper, an experimental real-time hybrid method, which implements the earthquake response control of a building structure with a TLD(Tuned Liquid Damper) by using only a TLD as an experimental part, is proposed and is experimentally verified through a shaking table test. In the proposed methodology, the whole building structure with a TLD is divided into the upper TLD and the lower structural parts as experimental and numerical substructures, respectively. The control force acting between their interface is measured with a shear-type load-cell which is mounted on the shaking table. The shaking table vibrates the upper experimental TLD with the response calculated from the numerical substructure, which is subjected to the excitations of the measured interface control force at its top story and an earthquake input at its base. The experimental results show that the conventional method, in which both a TLD and a building structure model are physically manufactured and are tested, can be replaced by the proposed methodology with a simple experimental installation and a good accuracy for evaluating the control performance of a TLD.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.5
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• pp.494-502
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• 2011

Bimodal tram is designed to run on a dedicated path in automatic mode using a magnetic track system in order to realize a combination of the accessibility of a bus and the constant regularity of a railroad. This paper presents design and test results of the series hybrid propulsion system of the bimodal tram on both test track and public road, which uses CNG (Compressed Natural Gas) engine and Lithium polymer battery pack. This paper describes the real-time data measuring equipment for the series hybrid propulsion system of the bimodal tram. Using this measurement equipment, the performance of the prototype vehicle's driving on test track and public road was verified and the fuel consumption and the efficiency of CNG engine have been investigated.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.527-534
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• 2006

A real-time hybrid method, in which the experimental implementation and the numerical computation of a structure are simultaneously carried out in real-time and combined on-line, has been used as a dynamic testing technique of structure to investigate its dynamic behaviors. In this paper, an experimental hybrid method, which implements the earthquake response control of a building structure with a TLD by using only a TLD as an experimental part, is proposed and is experimentally verified through a shaking table test. In the proposed methodology, the whole building structure with a TLD is divided into the upper TLD and the lower structural parts as experimental and numerical substructures, respectively. At the moment, the control force acting between their interface is measured from the experimental TLD with shear-type load-cell which is mounted on shaking table. Shaking table vibrates the upper experimental TLD with the response calculated from the numerical substructure, which is subjected to the excitations of the measured interface control force at its top story and an earthquake input at its base. The experimental results show that the conventional method, in which both a TLD and a building model are physically manufactured and are tested, can be replaced by the proposed methodology with a simple experimental installation and a good accuracy for evaluating the control performance of a TLD.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3955-3971
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• 2020

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.2
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• pp.217-225
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• 2007

This paper proposes the real-time hybrid shaking table testing methods to simulate the dynamic behavior of a soil-structure interaction system with dynamic soil stiffness by using only a structure model as the physical specimen and verifies their effectiveness for experimental implementation. Experimental methodologies proposed in this paper adopt such a way that absolute accelerations measured from the superstructure and shaking table are feedback to the shaking table controller, and then the shaking table is driven by the calculated motion of the absolute acceleration (acceleration feedback method) or the absolute velocity (velocity feedback method) of foundation that is required to simulate the dynamic behavior of a whole soil-structure interaction system. The shaking table test is implemented by reflecting the dynamic soil stiffness, which are differently approximated from the theoretical one depending on the feedback methods, on the shaking table controller to calculate soil part. The effectiveness of the proposed experimental methods is verified by comparing the response measured from the test on a foundation-fixed structural model and that obtained from the experiment of a soil-interaction system under the consideration in this paper and by matching the dynamic soil stiffness reflected on the shaking table controller with that identified using the experimentally measured data.

• Journal of Power Electronics
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• v.16 no.1
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• pp.217-226
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• 2016

A new method is proposed based on a hidden Markov model (HMM) to estimate and analyze battery states of health. Battery system health states are defined according to the relationship between internal resistance and lifetime of cells. The source data (terminal voltages and currents) can be obtained from vehicular battery models. A characteristic value extraction method is proposed for HMM. A recognition framework and testing datasets are built to test the estimation rates of different states. Test results show that the estimation rates achieved based on this method are above 90% under single conditions. The method achieves the same results under hybrid conditions. We can also use the HMMs that correspond to hybrid conditions to estimate the states under a single condition. Therefore, this method can achieve the purpose of the study in estimating battery life states. Only voltage and current are used in this method, thereby establishing its simplicity compared with other methods. The batteries can also be tested online, and the method can be used for online prediction.

• Journal of Ocean Engineering and Technology
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• v.34 no.6
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• pp.475-480
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• 2020

Underwater operating platforms face difficulties regarding power supply and communications. To overcome these difficulties, this study proposes a hybrid surface and underwater vehicle (HSUV) and presents the development of the platform, control algorithms, and results of field tests. The HSUV is capable of supplying reliable power to the unmanned underwater vehicle (UUV) and obtaining data in real time by using a tether cable between the UUV and the unmanned surface vehicle (USV). The HSUV uses global positioning system (GPS) and ultra-short base line sensors to determine the relative location of the UUV. Way point (WP) and dynamic positioning (DP) algorithms were developed to enable the HSUV to perform unmanned exploration. After reaching the target point using the WP algorithm, the DP algorithm enables USV to maintain position while withstanding environmental disturbances. To ensure the navigation performance at sea, performance tests of GPS, attitude/heading reference system, and side scan sonar were conducted. Based on these results, manual operation, WP, and DP tests were conducted at sea. WP and DP test results and side scan sonar images during the sea trials are presented.

• Journal of Korean Society on Water Environment
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• v.21 no.2
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• pp.132-140
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• 2005

The pilot test of a new alternative for small wastewater treatment system has been conducted for two years. It consists of a hybrid bioreactor and the expert system including the process control logic, PLC system, and HMI for the process automation. In order to monitor and remote control its status, the real-time data was transferred from the on-site control center to the central station via a wireless local area network. More efficient and stable performances were observed at automatic operating mode compared with the manual. On an average, COD, SS, T-N and T-P concentrations in the effluent from the hybrid bioreactor were less than 14, 7, 12 and 0.9 mg/L, respectively. According to the result from pilot tests, the quality of treated wastewater with sand filtration was enough to be utilized again.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

• Progress in Superconductivity and Cryogenics
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• v.11 no.3
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• pp.35-39
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• 2009

The study for a protective relay system is one of the important technical issues on the power system application of Superconducting Fault Current Limiter (SFCL). We used Real Time Digital Simulator(RTDS) to study the true interaction of the protection system with the power system. RTDS modeling of SFCL is necessary to the detailed protective relay tests. In this paper, we developed an analysis model using RTDS for studying the transient behavior of 22.9kV SFCL and carried out closed-loop testing of protective relays in distribution power system with the developed SFCL model. The SFCL model has the operation mechanism of 22.9kV hybrid SFCL being developed by LSIS and KEPRI in Korea. The parameters of the model are based on the test data of the real SFCL. Power system planners and operators can solve the expected problems in power system application of SFCL using protective relay testing results.