• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.4
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• pp.129-136
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• 2021

River facilities and port structures require a regular inspection and diagnosis due to obsolescence. Currently, most river facilities are undergoing indirect inspection and diagnosis by divers. The underwater inspections are not feasible due to safety issues of divers and restrictions on working hours and environment. To overcome these issues, it is intended to conduct inspections of river facilities using underwater drones. In this research, an underwater ROV (Remote Operated Vehicle) has been developed, which is a kind of drone with propellers. As a key device of this research, an injection device has been attached to the underwater drone to conduct an operation test, a stable operation test of an underwater drone, and a test of attached sensors. The river facility inspection can be carried out optimally using the hovering control of the drone and injection systems. With the developed ROV system, hovering test and injection test have been performed to verify the feasibility of this development.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.534-539
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• 2007

In this paper, we present the development of an intelligent diagnosis system for detecting faults of the low voltage wires. The wire detecting system based on the Time-Frequency Domain Reflectometry (TFDR) algorithm shows the condition of the wires. We analyze the reflected signal which is sent from the wire detecting system and classify the fault type of the wires by using the intelligent diagnosis system. Through the TFDR, generally, the conditions of the wires are classified into the three types - damage, open and short. In order to classify the fault type efficiently, we use the fuzzy classifier which is represented as IF-THEN rules. Finally, we show the utility of the proposed algorithm by performing the simulation which is based on the data of the coaxial cable.

• Development and Reproduction
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• v.25 no.2
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• pp.113-121
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• 2021

This article aims to introduce German discussion on the approval of the non-invasive prenatal diagnosis (NIPD), which started with the development of PrenaTest^® by LifeCodexx AG. The discussion started with the concern that the non-invasive nature of NIPD, such as PrenaTest^®, may rapidly expand the use and scope of similar tests, thus leading to a new era of eugenics. Based on this concern, the need for clear clinical guidelines on specific indications for NIPD has been suggested. Along the same line, it was discussed whether PrenaTest^® is against the Basic Law prohibiting discrimination on grounds of disability and whether the test is outside the scope of the purpose of gene testing limited by Genetic Diagnosis Act. Through such discussion, the Federal Ministry of Health of Germany established the preconditions for inclusion of NIPD in the German public health insurance system. For this, the German motherhood guideline was amended and the information for the insured persons provided to pregnant women was included in the amended guideline. Such discussion made in Germany provides insight on which points should be considered when various gene testings are accepted in Korea, in which genetic communication has not been systematized yet. In particular, German counseling system for pregnant women will provide valuable insights for Korea where the direction for regulations on abortion has not been established even after the ruling by the Constitutional Court that charges for abortion are against the constitution.

• Fire Science and Engineering
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• v.21 no.2 s.66
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• pp.42-47
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• 2007

This paper presents the development of a case-based system for an electrical fire cause diagnosis system using the entity relation database. The relation database which provides a very simple but powerful way of representing data is widely used. The system focused on database construction and cause diagnosis can diagnose the causes of electrical fires easily and efficiently. In order to store and access to the information concerned with electrical fires, the key index items which identify electrical fires uniquely are derived out. The case-based system consists of a case which contains information from the past fires. The case-based system could present the cause of a newly occurred fire to be diagnosed by searching the case-based database for reasonable matching. The case-based system has not only searching functions with multiple attributes by using the collected various information(such as fire evidence, structure, and weather of a fire scene) but also more improved diagnosis functions which can be easily used for the electrical fire cause diagnosis system.

• Proceedings of the KIEE Conference
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• 2001.11a
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• pp.198-200
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• 2001

In this paper, we describe the developed learning tool of expert system for preventive diagnosis of substation power equipments. The expert system was programmed by using the diagnosis methods as like gas analysis in oil and partial discharge, hottest temperature, the current of OLTC driving meter, the current of fan and pump in MTr and driving coil current in GCB and leakage current in LA. The learning tool is composed of the expert system and the explanation of diagnosed examples and the applied rules and it well worked according to the rule.

• Journal of the Korean Solar Energy Society
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• v.31 no.3
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• pp.17-22
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• 2011

Techniques for mismatch loss minimization to increase the PV system efficiency are under development recently. In this paper, a method to make diagnosis of PV module mismatch is presented, which uses a concept of operating point factor. The method is based on the fact that the ratio of the incremental conductance of a PV module to instantaneous conductance is 1 when the module is operating at its maximum power point. The variations of module voltage and current are taking place by the maximum power point tracker in the power conditioning units of PV system. The effectiveness of the method is verified through an application to a real PV system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.3
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• pp.526-531
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• 2003

In this paper, we implement embedded Linux intelligent controller and remote monitoring system for Bridge Diagnosis. Embedded controller as the hard core is consisted of 32 bit CPU and is designed to have processing of real time monitoring and FFT for Bridge Diagnosis. The prototype monitoring system can operate with world wide web in GUI environment by Java. Detailed design and functional analysis for monitoring system are performed by systems approach.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.4
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• pp.42-49
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• 1998

This wear debris can be harvested from the lubricants of operating machinery and its morphology is directly related to the damage to the interacting surface from which the particles originated. The morphological identification of wear debris can therefore provide very early detection of a fault and can also often facilitate a diagnosis. The purpose of this study is to attempt the developement of intelligent system for moving condition diagnosis of the machine driving system. The four shape parameter(50% volumetric diameter, aspect, roundness and reflectivity) of war debris are used as inputs to the neural network and learned the moving condition of five values(material3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameter learned. The three kinds of the wear debris had a different pattern characteristics and recognized the moving condition and materials very well by neural network.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.11
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• pp.47-54
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• 2009

Spin coaters are the essential instruments in micro-fabrication processes, which apply uniform thin films to flat substrates. In this research, a spin coater diagnosis system is developed to detect the abnormal operation of TFT-LCD process in real time. To facilitate the real-time data acquisition and analysis, the circular-buffered continuous data transfer and the short-time Fourier transform are applied to the fault diagnosis system. To determine whether the system condition is normal or not, a steady-state detection algorithm and a frequency spectrum comparison algorithm using confidence interval are newly devised. Since abnormal condition of a spin coater is rarely encountered, algorithm is tested on a CD-ROM drive and the developed program is verified by a function generator. Actual threshold values for the fault detection are tuned in a spin coater in process.

• Proceedings of the KIEE Conference
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• 1999.11d
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• pp.1025-1027
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• 1999

Recently, many researches on a diagnosis of stator winding insulation of large generators are reported. They mostly utilize a trend analysis of Partial Discharge (PD). In this paper, a novel on-line monitoring system for an insulation diagnosis is proposed. This system obtains the parameters such as Maximum Partial Discharge Magnitude (QM), Normalized Quantity Number (NQN) and Dynamic Stagnation Voltage (DSV) by continuous on-line monitoring of winding insulation. It is capable of diagnosing the insulation condition by analyzing the trend of PD and utilizing the database built by the system.