• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.28 no.10
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• pp.670-675
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• 2015

Degradation diagnosis of cable is one of major issues for operation and maintenance in overhead distribution power lines. The diagnostic system for overhead power lines is composed of three parts in functional aspect - a travelling unit, a sensing unit and a communication unit. Among them, sensor detects the defects such as corrosion and disconnecting of power lines. Performance of sensor is very important, and besides, the size and structure of sensor is restricted for installation to small and lightweight diagnostic system. This paper suggests an optimal eddy current sensor best suit for small and lightweight diagnostic system in consideration of detecting performance, size and ease of installation and so on. Proposed sensor has been designed by Drum core structure and can be applied to the all domestic overhead power lines regardless of the cross-sectional areas. Also, it is showed that results of mock environmental test are satisfied.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.95-113
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• 1997

This paper outlines a framework for a diagnosis of a complex system with uncertain information. Sensor validation ploys a vital role in the ability of the overall system to correctly determine the state of a system monitored by imperfect sensors. Here, emphases are put on the heuristic technology and post-processor for reasoning. Heuristic Sensor Validation (HSV) exploits deeper knowledge about parameter interaction within the plant to cull sensor faults from the data stream. Finally the modified probability distributions and validated data are used as input to the reasoning scheme which is the runtime version of the influence diagram. The output of the influence diagram is a diagnostic mapping from the symptoms or sensor readings to a determination of likely failure modes. Once likely failure modes are identified, a detailed diagnostic knowledge base suggests corrective actions to improve performance. This framework for a diagnostic expert system with sensor validation and reasoning under uncertainty applies in $HEATXPRT^{TM}$ a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants [1].

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.1
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• pp.37-43
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• 2015

Structural health monitoring (SHM) techniques based on the use of active-sensing piezoelectric (PZT) materials have received considerable attention. The validation of the PZT functionality during SHM operation is critical to successfully implementing a reliable SHM system. In this study, we investigated several parameters that affect the admittance-based sensor diagnostic process. We experimentally identified the temperature dependency of the active-sensor diagnostic process. We found that the admittance-based sensor diagnostic process can differentiate the adhesion conditions of bonding materials that are used to install a PZT on a structure, which is important when designing a sensor diagnostic process for an SHM system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1042-1045
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• 2003

In this paper, we present a new method for the monitoring of Electric Control Unit's(ECU) self-diagnostic and the sensor signals of vehicle through Web. In order to measure the ECU's self-diagnostic and sensor signals, the interfaced circuit is designed to communicate ECU and terminal according to the ISO, SAE regulation of communication protocol standard. Microprocessor 80C196KC is used for communicating ECU's self-diagnostic signals and the results are sent to the Embedded Linux System(ELS) through RF module. ELS is developed by SA1110, RF module, Embedded Linux. All commands related in ECU communication are executed through Web. The CGI program composed in web server is executed by user and will return sensor signals from ECU Software on Embedded Linux system is developed to monitor the ECU's sensor signals using the arm compiler tool chain in which RS232 port is programmed by half duplex method. The possibility for remote measurement of ECU sensor signal through Web is verified through the developed systems and algorithms.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.2
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• pp.323-338
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• 1994

This paper outlines a framework for performing intelligent sensor validation for a diagnostic expert system while reasoning under uncertainty. The emphasis is on the algorithmic preprocess technique. A companion paper focusses on heuristic post-processing. Sensor validation plays a vital role in the ability of the overall system to correctly detemine the state of a plant monitored by imperfect sensors. Especially, several theoretical developments were made in understanding uncertain sensory data in statistical aspect. Uncertain information in sensory values is represented through probability assignments on three discrete states, "high", "normal", and "low", and additional sensor confidence measures in Algorithmic Sv.Upper and lower warning limits are generated from the historical learning sets, which represents the borderlines for heat rate degradation generated in the Algorithmic SV initiates a historic data base for better reference in future use. All the information generated in the Algorithmic SV initiate a session to differentiate the sensor fault from the process fault and to make an inference on the system performance. This framework for a diagnostic expert system with sensor validation and reasonig under uncertainty applies in HEATXPRT$^{TM}$, a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants.

• Journal of Sensor Science and Technology
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• v.27 no.6
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• pp.407-413
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• 2018

Most sleep apnea patients exhibit severe snoring, and long-lasting sleep apnea may cause insomnia, hypertension, cardiovascular diseases, stroke, and other diseases. Although polysomnography is the typical sleep diagnostic method to accurately diagnose sleep apnea by measuring a variety of bio-signals that occur during sleep, it is inconvenient as the patient has to sleep with attached electrodes at the hospital for the diagnosis. In this study, a diagnostic pillow is designed to measure respiration, heart rate, and snoring during sleep, using only one polyvinylidene fluoride (PVDF) sensor. A PVDF sensor with piezoelectric properties was inserted into a specially made instrument to extract accurate signals regardless of the posture during sleep. Wavelet analysis was used to identify the extractability and frequency domain signals of respiration, heart rate, and snoring from the signals generated by the PVDF sensor. In particular, to separate the respiratory signal in the 0.2~0.5 Hz frequency region, wavelet analysis was performed after removing 1~2 Hz frequency components. In addition, signals for respiration, heart rate, and snoring were separated from the PVDF sensor signal through a Butterworth filter and median filter based on the information obtained from the wavelet analysis. Moreover, the possibility of measuring sleep apnea from these separated signals was confirmed. To verify the usefulness of this study, data obtained during sleeping was used.

• Journal of the Korean Applied Science and Technology
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• v.30 no.2
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• pp.197-203
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• 2013

The diagnostic assay of calcium ion was sought using a modified sensor with square-wave stripping voltammetry (SWSV) and cyclic voltammetry (CV). In this study, simple graphite pencil was used as working, reference, and auxiliary electrodes. By coating the working electrodes with DNA, their sensitivity was very much improved, and good results were yielded. Moreover, clean seawater was used as an electrolyte solution instead of acid and base electrolytes to lessen the expenses involved in the experiment. The analytical optimum conditions were also examined. These conditions were attained at the low detection limit of $0.6ugL^1$. After that, the results were applied to drinking water of milk contain.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.301-308
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• 2009

In the modern life, machines are used for various areas in industries as the advance of science and industrial development has proceeded. In many machines, the rotating machines play an important role in many processes. Therefore, the development of fault diagnosis and monitoring system for rotating machines is required. An ubiquitous sensor network (USN) is a combination of the key computer science and engineering area technology including the wireless network, embedded system hardware and software, communication, real-time system, etc. It collects environmental information to realize a variety of functions. In this work, a data reduction algorithm for USN based remote fault diagnostic system which can be easily applied to previously built factories is proposed. To verify the feasibility of the proposed scheme, some simulations and experiments are executed.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.161-166
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• 2021

To prevent accidents caused by changes in the surrounding environment or other factors, various protection facilities are installed at the photovoltaic connection module. The main causes of fire are sparks due to foreign substances inside the photovoltaic connection module through high temperature rise and dew condensation in the photovoltaic connection module, and fire due to heat from the power diode. The proposed method can predict the fire by measuring flame, carbon dioxide, carbon monoxide, temperature, humidity, input voltage, and current on the photovoltaic connection module, and when the fire conditions are reached, fire alarm and power off can be sent to managers and users in real time to prevent fire in advance.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.87-91
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• 2019

The diagnosis of the failure for the existing electrical facilities was based on regular preventive maintenance, but this preventive maintenance was limited in preventing a lot of cost loss and sudden system failure. To overcome these shortcomings, fault prediction and diagnostic techniques are critical to increasing system reliability by monitoring electrical installations in real time and detecting abnormal conditions in the facility early. As the performance and quality deterioration problem occurs frequently due to the increase in the number of users of the motor pump, the purpose is to build an intelligent control system that can control the motor pump to maximize the performance and to improve the quality and reliability. To this end, a vibration sensor, temperature sensor, pressure sensor, and low water level sensor are used to detect vibrations, temperatures, pressures, and low water levels that can occur in the motor pump, and to build a system that can identify and diagnose information to users in real time.