• Journal of Sensor Science and Technology
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• v.4 no.2
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• pp.14-21
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• 1995

This paper deals with the active magnetic field measuring system which can measure the time-varying magnetic fields generated by power installations and lightning discharges. The magnetic field measuring system consists of the loop-type magnetic field sensor and the active integrator operated by a differential amplifier. The theoretical principle and design rule of the time-varying magnetic field measuring device and the calibration apparatus are introduced. From the calibration experiments, the frequency bandwidth of the full measuring system ranges from 270 Hz to about 2.3 MHz and the response sensitivity for magentic field strength is 128 $mV/{\mu}T$, respectively, and the calculated B-field values in the center of the loop-type sensor versus the the applied current made with a region of ${\pm}3\;%$error. The actual survey experiments by using lightning impulse current and oscillating impulse current were performed, the results of comparision between the input current waveforms and the magnetic field waveforms are a good agreement with each others and their deviations are less than 0.5 %.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.9
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• pp.778-786
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• 2012

Sensors that are used on wireless sensor networks can be divided into two types: directional sensors, such as PIR, image, and electromagnetic sensors; and non-directional sensors, such as seismic, acoustic and magnetic sensors. In order to guarantee the line-of-sight of a directional sensor, the installation location of the sensor must be higher than ground level. Among non-directional sensors, seismic sensors should be installed on the ground in order to ensure the maximal performance. As a result, seismic sensors may have network connectivity problems due to communication failure. In this paper, we propose a 3D node deployment method to maximize the coverage and the network connectivity considering the sensor-specific properties. The proposed method is for non-directional sensors to be placed on the ground, while the directional sensor is installed above the ground, using trees or poles, to maximize the coverage. As a result, through the topology that the detection data from non-directional sensors are transmitted to the directional sensor, we can maximize the network connectivity. Simulation results show that our strategy improves sensor coverage and network connectivity.

• Progress in Superconductivity
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• v.4 no.1
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• pp.42-47
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• 2002

Measuring magnetic fields with a SQUID sensor always requires preliminary adjustments such as optimum bas current determination and flux-locking point search. A conventional magnetoencephalography (MEG) system consists of several dozens of sensors and we should condition each sensor one by one for an experiment. This timeconsuming job is not only cumbersome but also impractical for the common use in hospital. We had developed a serial port communication protocol between SQUID sensor controllers and a personal computer in order to control the sensors. However, theserial-bus-based control is too slow for adjusting all the sensors with a sufficient accuracy in a reasonable time. In this work, we introduce programmatic control sequence that saves the number of the control pulse arrays. The sequence separates into two stages. The first stage is a function for searching flux-locking points of the sensors and the other stage is for determining the optimum bias current that operates a sensor in a minimum noise level Generally, the optimum bias current for a SQUID sensor depends on the manufactured structure, so that it will not easily change about. Therefore, we can reduce the time for the optimum bias current determination by using the saved values that have been measured once by the second stage sequence. Applying the first stage sequence to a practical use, it has taken about 2-3 minutes to perform the flux-locking for our 37-channel SQUID magnetometer system.

• Journal of Sensor Science and Technology
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• v.29 no.5
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• pp.283-292
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• 2020

Current sensors that use a Hall element and Hall IC to measure the magnetic fields generated in steel silicon core gaps do not distinguish between direct and alternating currents. Thus, they are primarily used to measure direct current (DC) in industrial equipment. Although such sensors can measure the DC when installed in expensive equipment, ascertaining problems becomes difficult if the equipment is set up in an unexposed space. The control box is only opened during scheduled maintenance or when anomalies occur. Therefore, in this paper, a method is proposed for facilitating the safety management and maintenance of equipment when necessary, instead of waiting for anomalies or scheduled maintenance. A Bluetooth 4.0 low-energy current-sensor system based on near-field communication is used, which compensates for the nonlinearity of the current-sensor output signal using a piecewise linear model. The sensor is controlled using its generic attribute profile. Sensor nodes and cell phones used to check the signals obtained from the sensor at 50-A input currents showed an accuracy of ±1%, exhibiting linearity in all communications within the range of 0 to 50 A, with a stable output voltage for each communication segment.

• Journal of Multimedia Information System
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• v.2 no.2
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• pp.233-240
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• 2015

Mobile devices are becoming increasingly sophisticated and the latest generation of smartphones now incorporates many diverse and powerful sensors. These sensors include acceleration sensor, magnetic field sensor, light sensor, proximity sensor, gyroscope sensor, pressure sensor, rotation vector sensor, gravity sensor and orientation sensor. The availability of these sensors in mass-marketed communication devices creates exciting new opportunities for data mining and data mining applications. In this paper, we describe and evaluate a system that uses phone-based accelerometers to perform activity recognition, a task which involves identifying the physical activity that a user is performing. To implement our system, we collected labeled accelerometer data from 10 users as they performed daily activities such as "phone detached", "idle", "walking", "running", and "jumping", and then aggregated this time series data into examples that summarize the user activity 5-minute intervals. We then used the resulting training data to induce a predictive model for activity recognition. This work is significant because the activity recognition model permits us to gain useful knowledge about the habits of millions of users-just by having them carry cell phones in their pockets.

• Journal of Korea Multimedia Society
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• v.18 no.3
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• pp.401-407
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• 2015

In this paper, we propose the method to eliminate EMI (Electro-Magnetic Interference) in ELF (Extremely Low Frequency) band below 2 KHz for extending the gesture-recognition distance of smart TVs to more than 3m using electric potential sensor. First, we measure the electric field generated from the back panel of a TV and propose the effective arrangement of two sets of differential sensors as well as the shielding method using metal fiber. Also, we eliminate the PLN (Power Line Noise) and other noise generated from the TV and sensors as well as surrounding environments using filters. Using the proposed EMI eliminating methods, we evaluate displacement ratio on measured signals according to distance between sensors and a moving hand. Experiment results show that our proposed method can extend the hand-gesture sensing distance using EPS (Electric Potential Sensor) up to more than 3m, which is enough to satisfy applicability of EPS based remote control to Smart TVs.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.7
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• pp.643-651
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• 2015

Multi-axis magnetic and accelerometer sensor are widely used in consumer product such as smart phones. The vector output of multi-axis sensors have errors on each axis such as offset error, scale error, non-orthogonality. These errors cause many problems on the performance of the applications. In this paper, we designed the effective inline compensation algorithm for calibrating of 3 axis sensors using ellipsoid for mass production of multi-axis sensors. The outputs with those kinds of errors can be modeled by ellipsoid, and the proposed algorithm makes sequential mappings of the virtual ellipsoid to perfect sphere which is calibrated function of the sensor on three-dimensional space. The proposed calibrating process composed of four main stages and is very straightforward and effective. In addition, another imperfection of the sensor such as the drift from temperature can be easily inserted in each mapping stage. Numerical simulation and experimental results shows great performance of the proposed compensation algorithm.

• Nuclear Engineering and Technology
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• v.36 no.6
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• pp.540-548
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• 2004

Check valve failure is one of the worst problems in nuclear power plants. Recently, many researches have been based on new technology using accelerometers and ultrasonic and magnetic flux detection have been carried out. Here, we have suggested a method that uses acoustic emission sensors for detecting the failures of check valves through measuring and analyzing backward leakage flow, a system that works without disassembling the check valve. For validating the suggested acoustic emission sensor methodology, we designed a hydraulic test loop with a check valve. We have assumed in this study that check valve failure is caused by disk wear or by the insertion of a foreign object. In addition, we have developed diagnostic algorithms by using a neural network model to identify the type and size of the failure in the check valve. Our results show that the proposed diagnostic algorithm with acoustic emission sensors is a good solution for identifying check valve failure without necessitating any disassembly work.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1986-1991
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• 2007

In this paper, we discussed, intelligent soft filter for MR(magnetoresistive) sensor. Most navigation systems today use some type of compass to determine heading direction. Using the earth's magnetic field, electronic compass based on MR(magnetoresistive) sensors can electrically resolve better then 0.1 degree rotation. Intelligent methode for soft building a one degree compass using MR(magnetoresistive) sensors will also be discussed. Compensation techniques are shown to correct for compass tilt angels and nearby ferrous material disturbances. we proved the fuzzy logic that based on the way the ham deals with inexact information is useful for MR sensors.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.538-540
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• 2004

Electrical currents generated by human heart activities create magnetic fields represented by MCG(MagnetoCardioGram). Since an MCG signal acquisition system requires precise and stable operation, the system adopts hundreds of SQUID(Superconducting QUantum Interface Device) sensors for signal acquisition. Such a system requires fast real-time data acquisition in a required sampling interval, i.e., 1 mili-second for each sensor. This paper presents designed hardware to acquire data from 256-channel analog signal with 1 ksamples/sec speed, using 12-bit 8-channel ADC devices, SPI interfaces, parallel interfaces, 8-bit microprocessors, and a DSP processor. We implemented SPI interface between ADCs and a microprocessor, parallel interfaces between microprocessors. Our result concludes that the data collection can be done in $168{\mu}sec$ time-interval for 256 SQUID sensors, which can be interpreted to 6 ksamples/sec speed.