• Environmental Engineering Research
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• v.21 no.1
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• pp.29-35
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• 2016

This study evaluated the fertilizing value of struvite deposit recovered from swine wastewater in cultivating lettuce. Struvite deposit was compared to complex fertilizer, organic fertilizer and compost to evaluate the fertilizing effect of struvite deposit. Laboratory pot test showed that the struvite deposit better enhanced lettuce growth in comparison to commercial fertilizers. It was revealed that the growth rate of lettuce was simultaneously controlled by phosphorus (P) and magnesium (Mg). Moreover, nutrients such as nitrogen (N), P, K, calcium (Ca) and magnesium (Mg) were abundantly observed in the vegetable tissue of struvite pot. Meanwhile, struvite application led to the lower accumulation of mercury (Hg), lead (Pb), chromium ($Cr^{6+}$) and nickel (Ni). In addition, no detection of cadmium (Cd), arsenic (As) and nickel (Ni) in the lettuce tissue was observed in struvite application pots. The experimental results proved that the optimum struvite dosage for lettuce cultivation was 0.5 g struvite/kg soil. The column experiments clearly showed that ammonia nitrogen was more slowly released from struvite deposit than from complex fertilizer. Consequently, it was concluded that the struvite deposits recovered from swine wastewater were effective as a multi-nutrient fertilizer for lettuce cultivation.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.8
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• pp.55-61
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• 2010

In this paper, we proposed selective extraction method of frequency information and PCA-ELM based diagnosis system for three-phase induction motors. As the first step for diagnosis procedure, DFT is performed to transform the acquired current signal into frequency domain. And then, frequency components are selected according to discriminate order calculated by variance As the next step, feature extraction is performed by principal component analysis (PCA). Finally, we used the classifier based on Extreme Learning Machine (ELM) with fast learning procedure. To show the effectiveness, the proposed diagnostic system has been intensively tested with the various data acquired under different electrical and mechanical faults with varying load.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.288-294
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• 2013

The diagnosis of motor failures using an on-line method has been the aim of many researchers and studies. Several spectral analysis techniques have been developed and are used to facilitate on-line diagnosis methods in industry. This paper discusses the first application of a motor flux spectral analysis to the identification of broken rotor bar (BRB) faults in induction motors using a multiple signal classification (MUSIC) technique as an on-line diagnosis method. The proposed method measures the leakage flux in the radial direction using a radial flux sensor which is designed as a search coil and is installed between stator slots. The MUSIC technique, which requires fewer number of data samples and has a higher detection accuracy than the traditional fast Fourier transform (FFT) method, then calculates the motor load condition and extracts any abnormal signals related to motor failures in order to identify BRB faults. Experimental results clearly demonstrate that the proposed method is a promising candidate for an on-line diagnosis method to detect motor failures.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2528-2530
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• 2000

In general, Diode makes a major role in electronic circuit. For example, switching of rectifier, cross current of switching rectifier, energy transfer of electronic element and reverse charge of capacitor, voltage insulation, energy feedback from load to power supply, and such as recovery of storaged energy. Generally, We regard power diode as ideal element, but it has a certain boundary actually, specially, We use diode for detecting circuit peak hold voltage signal. It has cut in voltage. It occurs error of measurement value namely. This error, below in region diode voltage drop (0.7v) measurement value is wholesome signal, Specially, We can not get precision data. Therefore, precision level is low between theoretical and measurement data because of error in actual circuit. Conclusionally, In this paper, We define the error concerning to the power diode characteristics which is used detecting of the minute signal, and recommend the method that minimize measurement error.

• ETRI Journal
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• v.37 no.5
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• pp.961-971
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• 2015

This paper proposes a 250 mV supply voltage digital low-dropout (LDO) regulator. The proposed LDO regulator reduces the supply voltage to 250 mV by implementing with all digital circuits in a$0.11{\mu}m$ CMOS process. The fast current tracking scheme achieves the fast settling time of the output voltage by eliminating the ringing problem. The over-voltage and under-voltage detection circuits decrease the overshoot and undershoot voltages by changing the switch array current rapidly. The switch bias circuit reduces the size of the current switch array to 1/3, which applies a forward body bias voltage at low supply voltage. The fabricated LDO regulator worked at 0.25 V to 1.2 V supply voltage. It achieved 250 mV supply voltage and 220 mV output voltage with 99.5% current efficiency and 8 mV ripple voltage at $20{\mu}A$ to $200{\mu}A$ load current.

• Structural Engineering and Mechanics
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• v.32 no.6
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• pp.787-809
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• 2009

Recent interest in the use of wireless sensor networks for structural health monitoring (SHM) is mainly due to their low implementation costs and potential to measure the responses of a structure at unprecedented spatial resolution. Approaches capable of detecting damage using distributed processing must be developed in parallel with this technology to significantly reduce the power consumption and communication bandwidth requirements of the sensor platforms. In this investigation, a damage detection system based on a distributed processing approach is proposed and experimentally validated using a wireless sensor network deployed on two laboratory structures. In this distributed approach, on-board processing capabilities of the wireless sensor are exploited to significantly reduce the communication load and power consumption. The Damage Location Assurance Criterion (DLAC) is used for localizing damage. Processing of the raw data is conducted at the sensor level, and a reduced data set is transmitted to the base station for decision-making. The results indicate that this distributed implementation can be used to successfully detect and localize regions of damage in a structure. To further support the experimental results obtained, the capabilities of the proposed system were tested through a series of numerical simulations with an expanded set of damage scenarios.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.6
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• pp.99-105
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• 2014

Power transformers are applied throughout the power system to connect systems of different voltage to one another. Since a ratio differential relay offers high sensitivity in detection of internal faults in power transformers, it is widely used in the main protection system. The use of nonlinear devices such as rectifiers and other devices utilizing solid state switching have been increased in industry during recent years. For nonlinear loads, the load current is not proportional to the instantaneous voltage. This situation creates harmonic distortion on the system. The harmonic could differential relay misoperation if not recognized. This paper aims at analyzing and probing into the influences of harmonics on a ratio differential relay for power transformer protection.

• Journal of Power Electronics
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• v.15 no.1
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• pp.131-145
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• 2015

The voltage-source inverters (VSI) supplying a motor drive are prone to open transistor faults. To address this issue in fault-tolerant drives applicable to electric vehicles, a new open transistor fault diagnosis (FD) method is presented in this paper. According to the proposed method, in order to define the FD index, the phase angle of the converter output current is estimated by a simple trigonometric function. The proposed FD method is adaptable, simple, capable of detecting multiple open switch faults and robust to load operational variations. Keeping the FD in mind as a mandatory part of the fault tolerant control algorithm, the FD block is applied to a five-phase converter supplying a multiphase fault-tolerant PM motor drive with non-sinusoidal unbalanced current waveforms. To investigate the performance of the FD technique, the fault-tolerant sliding mode control (SMC) of a five-phase brushless direct current (BLDC) motor is developed in this paper with the embedded FD block. Once the theory is explained, experimental waveforms are obtained from a five-phase BLDC motor to show the effectiveness of the proposed FD method. The FD algorithm is implemented on a field programmable gate array (FPGA).

• Journal of Power Electronics
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• v.12 no.5
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• pp.800-812
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• 2012

This paper analyses the mathematical model and control strategies of a Hybrid Active Power Filter with Injection Circuit (IHAPF). The control strategy based on the load harmonic current detection is selected. A novel control method for a IHAPF, which is based on the analyzed control mathematical model, is proposed. It consists of two closed-control loops. The upper closed-control loop consists of a single fuzzy logic controller and the IHAPF model, while the lower closed-control loop is composed of an Adaptive Network based Fuzzy Inference System (ANFIS) controller, a Neural Generalized Predictive (NGP) regulator and the IHAPF model. The purpose of the lower closed-control loop is to improve the performance of the upper closed-control loop. When compared to other control methods, the simulation and experimental results show that the proposed control method has the advantages of a shorter response time, good online control and very effective harmonics reduction.

• International Journal of Automotive Technology
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• v.8 no.5
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• pp.637-650
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• 2007

A new on-line fault detection and isolation(FDI) scheme has been proposed for engines using an adaptive neural network classifier; this paper investigates the robustness of this scheme by evaluating in a wide range of operational modes. The neural classifier is made adaptive to cope with the significant parameter uncertainty, disturbances, and environmental changes. The developed scheme is capable of diagnosing faults in the on-line mode and can be directly implemented in an on-board diagnosis system(hardware). The robustness of the FDI for the closed-loop system with crankshaft speed feedback is investigated by testing it for a wide range of operational modes, including robustness against fixed and sinusoidal throttle angle inputs, change in load, change in an engine parameter, and all changes occurring simultaneously. The evaluations are performed using a mean value engine model(MVEM), which is a widely used benchmark model for engine control system and FDI system design. The simulation results confirm the robustness of the proposed method for various uncertainties and disturbances.