• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.11 no.4
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• pp.92-99
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• 1997

This paper proposed a control method to improve the efficiency of monitoring method by applying the nural network for an alarm processing method(APM)in an elevator facility of apartment complex. This APM is based on the cumulative generalized delta rule of backpropagation in neural network.It was used to infer the minimum alarms among multi-fired alarms, and then the inferred alarm can be dis¬played maintenance information of facility by using a pre-defined troubleshoot knowledge base. For validating the proposed monitoring method of this thesis, simulation results are compared with the operation of existing monitoring system and the way of alarm processing. The simulation method used to the three case of virtual scenario. As comparison results, a proposed method in this paper could be proved the applied possibility of an neural network and the performance in fields of facilities maintenance.

• The KSFM Journal of Fluid Machinery
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• v.12 no.5
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• pp.39-46
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• 2009

This paper outlines how the on-line performance monitoring system can be used to improve the efficiency and maintenance of the equipments. And a method of the heat rate allocation to each equipment was suggested to monitor the performance of combined cycle power plants. This calculates the expected heat rate of current conditions and compares it with actual values. Loss allocation in heat rate is reconciled by calculating the magnitude of the deficiency contributed by major components, such as the gas turbine, heat recovery steam generator, steam turbine and condenser. Expected power output is determined by a detailed model and correction curves of the plant. This simulation models are found to reproduce high accuracy in behavior of the cycle for various operating conditions, both in design and in off-design condition. Errors are lower than 2% in most cases.

• Journal of Welding and Joining
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• v.19 no.4
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• pp.384-390
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• 2001

There have been many problems due to deformation in industry field. Especially, it is severe in parts with small size and thin thickness and in products that must have excellent airtightness and anti-noise. The countermeasures for this deformation in field have mainly been dependent on the rule of trial and error by operator's experience because of productivities. Systematic study about this product with deformation is also insufficient that deformation is complex problem with shape, size, material of product, joining method and conditions, etc.. It is efficient to apply CAE technique without influence on productivity to this problem. There is, however much difference between the result analyzed by CAE and appearances in working field because of the insufficiency of communication between simulator and worker and of sensing data for boundary condition in analysis. In this study, to solve this deformation problem, we intend to make a simulation model that is adapted from working conditions by tuning and feedback between sensing data and simulation results. This paper include temperature monitoring and make a heat transfer model using sensing data in product as previous step for deformation analysis. The heat transfer analysis of shrinkage fit process is considerably difficult due to contact heat transfer between case and core. To solve this contact problem, gap element is used in present study.

• Earthquakes and Structures
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• v.2 no.2
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• pp.189-206
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• 2011

In this study, the subspace stochastic realization theories (SSR model I and SSR model II) have been applied to a real bridge for estimating its dynamic characteristics (natural frequencies, damping constants, and vibration modes) under ambient vibration. A numerical simulation is carried out for an arch-type steel truss bridge using a white noise excitation. The estimates obtained from this simulation are compared with those obtained from the Finite Element (FE) analysis, demonstrating good agreement and clarifying the excellent performance of this method in estimating the structural dynamic characteristics. Subsequently, these methods are applied to the vibration induced by both strong and weak winds as obtained by remote monitoring of the Kabashima bridge (an arch-type steel truss bridge of length 136 m, and situated in Nagasaki city). The results obtained with this experimental data reveal that more accurate estimates are obtained when strong wind vibration data is used. In contrast, the vibration data obtained from weak wind provides accurate estimates at lower frequencies, and inaccurate accuracy for higher modes of vibration that do not get excited by the wind of lower intensity. On the basis of the identified results obtained using both simulated data and monitored data from a real bridge, it is determined that the SSR model II realizes more accurate results than the SSR model I. In general, the approach investigated in this study is found to provide acceptable estimates of the dynamic characteristics of highway bridges as well as for the vibration monitoring of bridges.

• Journal of Power Electronics
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• v.12 no.5
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• pp.778-786
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• 2012

In this paper, a novel scheme for the condition monitoring of lithium polymer batteries is proposed, based on the sigma-point Kalman filter (SPKF) theory. For this, a runtime-based battery model is derived, from which the state-of-charge (SOC) and the capacity of the battery are accurately predicted. By considering the variation of the serial ohmic resistance ($R_o$) in this model, the estimation performance is improved. Furthermore, with the SPKF, the effects of the sensing noise and disturbance can be compensated and the estimation error due to linearization of the nonlinear battery model is decreased. The effectiveness of the proposed method is verified by Matlab/Simulink simulation and experimental results. The results have shown that in the range of a SOC that is higher than 40%, the estimation error is about 1.2% in the simulation and 1.5% in the experiment. In addition, the convergence time in the SPKF algorithm can be as fast as 300 s.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1167-1175
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• 2021

The process of automation and monitoring in industrial control system involves the use of many types of sensors. A programmable logic controller plays an important role in the automation of the different processes in the power plant system. The major control units are boiler for temperature and pressure, turbine for speed of motor, generator for voltage, conveyer belt for fuel. The power plant units are controlled using microcontrollers and PLCs, but FPGA can be the feasible solution. The paper focused on the design and simulation of hardware chip to monitor boiler, turbine, generator and conveyer belt. The hardware chip of the plant is designed in Xilinx Vivado Simulator 17.4 software using VHDL programming. The methodology includes VHDL code design, simulation, verification and testing on Virtex-5 FPGA hardware. The system has four independent buzzers used to indicate the status of the boiler, generator, turbine motor and conveyer belt in on/off conditions respectively. The GSM is used to display corresponding message on the mobile to know the status of the device in on/off condition. The system is very much helpful for the industries working on plant automation with FPGA hardware integration.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.11-17
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• 2008

Typical wireless sensor networks used in structural monitoring are continuous types wherein data transmission is progressive at all time that may include irrelevant and insignificant data and information. Continuous types of wireless monitoring systems often pose problems of handling large-sized data that may deteriorate the performance of the system. The proposed method is to suggest an event-triggered monitoring system that captures and transmits relevant data only. An error signal generated by the Principal Components Analysis (PCA) is utilized as an index for event detection and selective data transmission. With this new monitoring scheme, the remote server is relieved of unwanted data by receiving only relevant information from the wireless sensor networks. The performance of the proposed scheme was verified with simulation studies.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.12
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• pp.60-69
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• 1997

We present an average method based on the multirate signal processing and dynamic allocation average for the purpose of monitoring event-related potentials(ERP) and continuously and dynamically. In the proposed method, first, latency shifts are detected through the cross correlation between a current response and the reference response. Then, the multirate signal processing which is composed of up-sampler, lowpass filter, and down sampler is performed to compensate the latency shifts of the reference response, therefore we obtain the reference response with a peak latencies compenated by those of a current response. Finally, the single response is obtained by averaging the compensated reference response and a current response. In the simulation, the results of quantitative evaluation by simulation and the results using linical data are presented. From the result, the proposed method reflects dynamic time-varying ERP more exactly than previous methods and is also effective in consecutive monitoring of ERP.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.174-181
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• 1999

In this paper the technique to predict tool wear theoretically in shearing process is suggested. The tool wear in the process affects the tolerances of final pans, metal flows and costs of processes. In order to predict the tool wear the deformation of workpiece during the process is analyzed by using non-isothermal finite element program. The ductile fracture criterion and the element kill method are also used to estimate if and where a fracture will occur and to investigate the features of the sheared surface in shearing process. Results obtained from finite element simulation, such as nodal velocities and nodal forces, are transformed into sliding velocity and normal pressure on tool monitoring points respectively. The monitoring points are automatically generated and the wear rates on these points are accumulated during the process. It is assumed that the wear depth on the tool surface is linear function of the lot sizes based upon the known experimental results. The influence of clearance between die and punch upon tool wear is also discussed.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.150-152
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• 2007

The stator faults yield asymmetrical operation of induction machines, such as irregular current, torque pulsation, increased losses and decreased average torque. So it is necessary to detect the stator faults and develope the monitoring system for detecting faults including vibration and noise. This paper describes the method to analysis the induction motors with the stator winding inter-turn short for investigation of the asymmetrical operation during normal and transient states. And a simple method is used for the simulation and analysis of the induction machines with stator asymmetries. Finally, simulation results, finite element analysis and experimental ones are presented. The results can be useful for real-time on-line monitoring of an induction motor.