• International journal of advanced smart convergence
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• v.12 no.3
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• pp.221-232
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• 2023

Recently, due to the expansion of the logistics industry, demand for logistics automation equipment is increasing. The modern logistics industry is a high-tech industry that combines various technologies. In general, as various technologies are grafted, the complexity of the system increases, and the occurrence rate of defects and failures also increases. As such, it is time for a predictive maintenance model specialized for logistics automation equipment. In this paper, in order to secure the operational reliability of the ICT/Cold-Chain Unmanned Storage, a predictive maintenance system was implemented based on the LSTM model. In this paper, a server for data management, such as collection and monitoring, and an analysis server that notifies the monitoring server through data-based failure and defect analysis are separately distinguished. The predictive maintenance platform presented in this paper works by collecting data and receiving data based on RabbitMQ, loading data in an InMemory method using Redis, and managing snapshot data DB in real time. The predictive maintenance platform can contribute to securing reliability by identifying potential failures and defects that may occur in the operation of the ICT/Cold-Chain Unmanned Storage in the future.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3587-3594
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• 2022

A distributed high-speed data acquisition and monitoring system for the RF negative ion source at Huazhong University of Science and Technology (HUST) is developed, which consists of data acquisition, data forwarding and data processing. Firstly, the data acquisition modules sample physical signals at high speed and upload the sampling data with corresponding absolute-time labels over UDP, which builds the time correlation among different signals. And a special data packet format is proposed for the data upload, which is convenient for packing or parsing a fixed-length packet, especially when the span of the time labels in a packet crosses an absolute second. The data forwarding modules then receive the UDP messages and distribute their data packets to the real-time display module and the data storage modules by PUB/SUB-pattern message queue of ZeroMQ. As for the data storage, a scheme combining the file server and MySQL database is adopted to increase the storage rate and facilitate the data query. The test results show that the loss rate of the data packets is within the range of 0-5% and the storage rate is higher than 20 Mbps, both acceptable for the HUST RF negative ion source.

• Environmental Engineering Research
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• v.20 no.4
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• pp.397-402
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• 2015

SCR has been popularly approved as one of the most effective means for NOx emission control in heavy-duty and medium-duty vehicles currently. However, high urea dosing would lead to ammonia slip. And $NH_3$ sensor for vehicle emission applications has not been popularly used in real applications. This paper presents experimental studies on the diesel engine urea-SCR system by using a double NOx sensor system that is arranged in the downstream of the SCR catalyst based on ammonia cross-sensitivity. It was shown that the NOx conversion efficiency rised as $NH_3/NOx$ increases and the ammonia slip started from the $NH_3/NOx$ equal to 1.4. The increase of temperature caused high improvement of the SCR reaction rate while the space velocity had no obvious change. The ammonia slip was in advance as catalyst temperature or space velocity increase and the ammonia storage reduced as catalyst temperature or space velocity increase. The NOx real-time conversion efficiency rised as the ammonia accumulative storage increase and reached the maximum value gradually.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.12
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• pp.638-644
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• 2017

Optimal cooling operation algorithm was developed based on a simulation case of a single family house model equipped with renewable energy facility. EnergyPlus simulation results were used as virtual test data. The model contained three energy storage elements: thermal heat capacity of the living room, chilled water storage tank, and battery. Their charging and discharging schedules were optimized so that daily electricity bill became minimal. As an optimization tool, linear programming was considered because it was possible to obtain results in real time. For its adoption, EnergyPlus-based house model had to be linearly approximated. Results of this study revealed that dynamic cooling load of the living room could be approximated by a linear RC model. Scheduling based on the linear programming was then compared to that by a nonlinear optimization algorithm which was made using GenOpt developed by a national lab in USA. They showed quite similar performances. Therefore, linear programming can be a practical solution to optimal operation scheduling if linear dynamic models are tuned to simulate their real equivalents with reasonable accuracy.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.640-643
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• 2003

A Walsh function based associative memory is capable of storing m patterns in a single pattern storage space with Walsh encoding of each pattern. Furthermore, each stored pattern can be matched against the stored patterns extremely fast using algorithmic parallel processing. As such, this special type of memory is ideal for real-time processing of large scale information. However this incredible efficiency generates large amount of crosstalk between stored patterns that incurs mis-recognition. This crosstalk is a function of the set of different sequencies [number of zero crossings] of the Walsh function associated with each pattern to be stored. This sequency set is thus optimized in this paper to minimize mis-recognition, as well as to maximize memory saying. In this paper, this Walsh memory has been applied to the problem of face recognition, where PCA is applied to dimensionality reduction. The maximum Walsh spectral component and genetic algorithm (GA) are applied to determine the optimal Walsh function set to be associated with the data to be stored. The experimental results indicate that the proposed methods provide a novel and robust technology to achieve an error-free, real-time, and memory-saving recognition of large scale patterns.

• Journal of Broadcast Engineering
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• v.8 no.2
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• pp.126-135
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• 2003

To investigate the DTV coverage especially in downtown areas and improve the performance of DTV receivers, it is necessary to capture the receiving DTV signals that contain the complex characteristics of the real-world RF environments and regenerate them in a laboratory without the performance degradation. In this paper, we developed a DTV RF capture and regeneration system adapting digital signal processing and high speed hard disk storage techniques and analyze its characteristics. The system can capture and replay the DTV RF signals based on a real-time condition in a hard disk. There Is no time limit for capturing RF data within the installed storage capacity. We can expect various Possible applications for this system such as a tool for the development of the receiver performance analysis, design and analysis for the DTV coverage areas, etc.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.712-718
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• 2013

With the development of industry and the improvement of living standards, better quality in power electric service is required more than ever before. This paper deals with the optimal algorithms for voltage regulation in the case where Distributed Storage and Generation (DSG) systems are operated in distribution systems. It is very difficult to handle the interconnection issues for proper voltage managements, because the randomness of the load variations and the irregular operation of DSG should be considered. This paper proposes the optimal on-line real time voltage regulation methods in power distribution systems interconnected with the DSG systems. In order to deliver suitable voltage to as many customers as possible, the optimal sending voltage should be decided by the effective voltage regulation method by using artificial neural networks to consider the rapid load variation and random operation characteristics of DSG systems. The simulation results from a case study show that the proposed method can be a practical tool for the voltage regulation in distribution systems including many DSG systems.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.667-674
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• 2013

Wind power producers face many regulation costs in deregulated environment, which remarkably lowers the value of wind power in comparison with conventional sources. One of these costs is associated with the real-time variation of power output and being paid in frequency control market according to the variation band. This paper presents a new approach to coordination of battery energy storage in wind generation system for reducing the payment in frequency control market. The approach depends on the statistic data of wind generation and the prediction of frequency control market price to determine the optimal variation band which is then kept by the real-time charging and discharging of batteries, ultimately the minimum cost of frequency regulation can be obtained. The optimization problem is formulated as trade-off between the decrease in the regulation payment and the increase in the cost of using battery, and vice versus. The approach is applied to a study case and the results of simulation show its effectiveness.

• ETRI Journal
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• v.45 no.4
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• pp.650-665
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• 2023

A novel smart metering technique capable of anomaly detection was proposed for real-time home power management system. Smart meter data generated in real-time were obtained from 900 households of single apartments. To detect outliers and missing values in smart meter data, a deep learning model, the autoencoder, consisting of a graph convolutional network and bidirectional long short-term memory network, was applied to the smart metering technique. Power management based on the smart metering technique was executed by multi-objective optimization in the presence of a battery storage system and an electric vehicle. The results of the power management employing the proposed smart metering technique indicate a reduction in electricity cost and amount of power supplied by the grid compared to the results of power management without anomaly detection.

• Journal of Satellite, Information and Communications
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• v.8 no.4
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• pp.111-116
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• 2013

Because LEO (Low Earth Orbit) satellite has very limited contact time between satellite and ground station, all telemetry data generated on satellite are stored in a mass memory and transmitted to the ground during the contact time. There are two downlink modes, real-time mode and playback mode. Only real-time data frames are transmitted to the ground in real-time mode, real-time and playback data frames stored into mass memory are transmitted to the ground in playback mode. In accordance with the data transmission rate, there are two downlink rates, low downlink rate and high downlink rate. This paper briefly introduces downlink interfaces and flight software of a LEO satellite developed in KARI. And it presents the telemetry storage method, real-time and playback downlink management method, and downlink channel and rate control method.