• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.537-543
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• 2003

Condition monitoring and fault diagnosis of machines are gaining importance in the industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. By comparing the vibration signals of a machine running in normal and faulty conditions, detection of faults like mass unbalance, shaft misalignment and bearing defects is possible. This paper presents a novel approach for applying the fault diagnosis of rotating machinery. To detect multiple faults in rotating machinery, a feature selection method and support vector machine (SVM) based multi-class classifier are constructed and used in the faults diagnosis. The results in experiments prove that fault types can be diagnosed by the above method.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.5 no.1
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• pp.108-115
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• 2005

Inherited metabolic diseases (IMD) comprise a large class of genetic diseases involving disorders of metabolism. The majorities are due to defects of single genes that code for enzymes that facilitate conversion of various substances into others. Because of the multiplicity of conditions, many different diagnostic tests are used for screening of IMD. Molecular genetic diagnosis is the detection of pathogenic mutations in DNA and/or RNA samples and is becoming a much more common practice in medicine today. The purpose of molecular genetic testing in IMD includes diagnostic testing, pre-symptomatic testing, carrier screening, prenatal diagnosis, preimplantation testing, and population screening. However, because of the complexity, difficulty in interpreting the result, and the ethical considerations, an understanding of technical, conceptual, and practical aspects of molecular genetic diagnosis is mandatory.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.57-64
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• 2024

In the industrial field, robots are used to increase productivity by replacing labors with dangerous, difficult, and hard tasks. However, failures of individual industrial robots in the entire production process may cause product defects or malfunctions, and may cause dangerous disasters in the case of manufacturing parts used in automobiles and aircrafts. Although requirements for early diagnosis of industrial robot failures are steadily increasing, there are many limitations in early detection. This paper introduces methods for diagnosing robot failures using sound-based data and deep learning. This paper also analyzes, compares, and evaluates the performance of failure diagnosis using various deep learning technologies. Furthermore, in order to improve the performance of the fault diagnosis system using deep learning technology, we propose a method to increase the accuracy of fault diagnosis based on an inference window. When adopting the inference window of deep learning, the accuracy of the failure diagnosis was increased up to 94%.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.1
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• pp.1-29
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• 2019

Related to the previous paper on the typical crack pattern of tunnel lining with NATM, the characteristic defects in reinforced cement concrete lining of NATM tunnel have analyzed with the precise inspection with safety and diagnosis (PISD) by KISTEC. Depending on the reinforcing materials, steel rebar, steel fiber, and glass fiber have been implemented to reinforcing lining in various NATM tunnel constructions. Reinforcing lining with rebar are prevailed on NATM tunnel to countermeasure the weak geological circumstances, to pursuit the economical tunnel sections, and to resist the risk of tunnel deterioration. By the special act on the safety control of public facilities, the reinforced NATM tunnels for more than 1 km length are scrutinized closely to characterize defects; crack, reinforcement exposure, and lack of lining. Crack resistance by reinforcing is shown in comparison with the normalized crack to the length of tunnel. Typical exposed reinforcements in lining have exemplified with various sections. The lack of lining due to the mal-construction, spalling, fire, earthquake and leaching has been analyzed. The cause and mechanism with the field inspections and other studies has also been verified. Detailed cases are selected by the above concerns as well as the basic information from FMS (Facilities Management System). Likewise the previous paper, this study provides specialized defects in reinforced lining of NATM and it can be widely used in spreading the essential technics and reporting skills. Furthermore, it would be advised and amended for the detail guideline of Safety Diagnosis and PISD (tunnel).

• Aerospace Engineering and Technology
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• v.11 no.2
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• pp.182-194
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• 2012

To develop a liquid rocket engine with high reliability and safety under constraints of limited time and budget an optimal diagnosis system for the engine needs to be developed in parallel with the development of the engine. This paper is intended to set a development direction of the diagnosis system for the liquid rocket engine through the literature survey and addresses possible engine defects, characteristics of parameters for diagnosis and diagnostic methods including real-time diagnosis, post-test/post-flight diagnosis, fault detection method, parameter circuit method and test diagnosis. In addition tasks to be performed in the design and operation phases of the engine and foreign application case of engine diagnosis are presented.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.301-307
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• 1995

A monitoring technique of spindle fairure should be investirated prior to researcs of fairure diagnosis. This work is about monitoring of unbalanced shaft and defected bearings. The major work is done via experiments and the vibration signal is analysed means of power spectrum technique, and root mean squqre, peak-to-peak. Relationship is quantitatively investigated between defects and these monitoring paramenters.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.161-166
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• 2003

The purpose Performance degradation of concrete structures is generally caused by the deteriorations, such as surface collapse, pop-out, crack, and so on. It may result in serious defects of the concrete structures. Thus it is very important to detect and repair the defects of concrete structures within a proper time to assure the structural safety. However, the defects due to the deteriorations are usually difficult to find by visual inspection. A sensor is developed in this study, which may give early indications for degradation of concrete structures and show the locations of the demage. Cracks can be defected by the liquid in a small glass capsules which are embedded in the concrete structures. This paper discusses the applicability of that was developed smart concrete.

• Nuclear Engineering and Technology
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• v.36 no.3
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• pp.210-218
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• 2004

In the interest of nuclear power plant safety, a self-diagnostic monitoring system (SDMS) is needed to monitor defects in safety-related components. An air-operated valve (AOV) is one of the components to be monitored since the failure of its operation could potentially have catastrophic consequences. In this paper, a model of the AOV is developed with the parameters that affect the operational characteristics. The model is useful for both understanding the operation and correlating parameters and defects. Various defects are introduced in the experiments to construct a fault library, which will be used in a pattern recognition approach. Finally, the validity of the fault library is examined.

• KIEAE Journal
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• v.12 no.3
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• pp.11-18
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• 2012

The purpose of this study is to contribute to solution of the defect dispute in apartment house in advance. We want to propose the improved devices in defect problems by investigating the money that exacted from the practical business of the inspection company and the money that a judge gave a decision in a civil court in 50 cases of the lawsuit to requesting the guarantee against defects and the improved schemes of the applied rate by analyzing the diagnosis money of each applied years about the term of warranty liability in 40 cases of the lawsuit separately from that. As the result, we have to reflect the defect of non construction and error construction on apartment building defects, which recognizes very important factor when we compute the defect repair warranty money and it needs to be rearranged the applied ratio in guarantee peried of housing law practically.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.33-37
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• 2002

Insulation aging diagnosis system provides early warning regarding electrical equipment defects. Early warning is very important in that it can avoid great losses resulting from unexpected shutdown of the production line. Since relations of insulation aging and partial discharge dynamics are non-linear. it is very difficult to provide early warning in an electrical equipment. In this paper, we propose the design method of insulation aging diagnosis system that use a electromagnetic wave and acoustic signal to diagnose an electrical equipment. Proposed system measures the partial discharge on-line from DAS(Data Acquisition System and acquires 2D patterns from analyzing it. For filtering the noise contained in sensor signals we used ICA algorithms. Using this data, we design of the neuro-fuzzy model that diagnoses an electrical equipment and is investigated in this paper. Validity of the new method is asserted by numerical simulation.