• Corrosion Science and Technology
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• 제7권4호
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• pp.208-211
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• 2008

Safety operation of main pipelines is primarily provided by anticorrosive monitoring. Anticorrosive monitoring of oil pipeline transportation objects is based on results of complex corrosion inspections, analysis of basic data including design data, definition of a corrosion residual rate and diagnostic of general equipment's technical condition. All the abovementioned arrangements are regulated by normative documents. For diagnostics of corrosion-technical condition of oil pipeline transportation objects one presently uses different methods such as in-line inspection using devices with ultrasonic, magnetic or another detector, acoustic-emission diagnostics, electrometric survey, general external corrosion diagnostics and cameral processing of obtained data. Results of a complex of diagnostics give a possibility: $\cdot$ to arrange a pipeline's sectors according to a degree of corrosion danger; $\cdot$ to check up true condition of pipeline's metal; $\cdot$ to estimate technical condition and working ability of a system of anticorrosive protection. However such a control of corrosion technical condition of a main pipeline creates the appearance of estimation of a true degree of protection of an object if values of protective potential with resistive component are taken into consideration only. So in addition to corrosive technical diagnostics one must define a true residual corrosion rate taking into account protective action of electrochemical protection and true protection of a pipeline one must at times. Realized anticorrosive monitoring enables to take a reasonable decision about further operation of objects according to objects' residual life, variation of operation parameters, repair and dismantlement of objects.

• Nuclear Engineering and Technology
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• 제43권4호
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• pp.343-354
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• 2011

It is critically important to identify unexpected loose parts in a nuclear reactor pressure vessel, since they may collide with and cause damage to internal structures. Mass estimation can provide key information regarding the kind as well as the location of loose parts. This study proposes a mass estimation method based on an artificial neural network (ANN), which can overcome several unresolved issues involved in other conventional methods. In the ANN model, input parameters are the discrete cosine transform (DCT) coefficients of the auto-power spectrum density (APSD) of the measured impact acceleration signal. The performance of the proposed method is then evaluated through application to a large-sized plate and a 1/8-scaled mockup of a reactor pressure vessel. The results are compared with those obtained using a conventional method, the frequency ratio (FR) method. It is shown that the proposed method is capable of estimating the impact mass with 30% lower relative error than the FR method, thus improving the estimation performance.

• Nuclear Engineering and Technology
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• 제49권7호
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• pp.1555-1562
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• 2017

A loose part monitoring system is used to identify unexpected loose parts in a nuclear reactor vessel or steam generator. It is still necessary for the mass estimation of loose parts, one function of a loose part monitoring system, to develop a new method due to the high estimation error of conventional methods such as Hertz's impact theory and the frequency ratio method. The purpose of this study is to propose a mass estimation method using a Markov decision process and compare its performance with a method using an artificial neural network model proposed in a previous study. First, how to extract feature vectors using discrete cosine transform was explained. Second, Markov chains were designed with codebooks obtained from the feature vector. A 1/8-scaled mockup of the reactor vessel for OPR1000 was employed, and all used signals were obtained by impacting its surface with several solid spherical masses. Next, the performance of mass estimation by the proposed Markov model was compared with that of the artificial neural network model. Finally, it was investigated that the proposed Markov model had matching error below 20% in mass estimation. That was a similar performance to the method using an artificial neural network model and considerably improved in comparison with the conventional methods.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1990년도 제11회 학술강연회초록집
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• pp.7-31
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• 1990

Tribologicsl diagnostics as the ensemble of means and methods of continuous monitoring of the state of friction characteristics of moving junctions is playing an ever important part in the development of friction, lubrication, and wear theory end practice. The scheme presenting the main areas of tribological diagnostics is given in Fig. I. This growing part of TD is determined by the general tendency of modern technology, expressed in an attempt to organically combine the functions of measuring, evaluating,and predicting the parameters and characteristics of the processee taking place in the operating device. The logical result of this integration in future is the closed system correcting its operation in accordance with sn established program. Unfortunately, tribotechnicsl devices are still very far from such an ideal system at the present time. While in the friction assemblies with hydrodynamic lubrication it is possible in the first approximation to realize feed-backs in the lubricant circulation system with the aid of monitoring of the pressure, temperature and filtration, in the systems operating without lubrication and with boundary lubricetion even the process of selection of the diagnostic parameters has not been completed.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.1182-1185
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• 1995

This paper presents a novel technology for unattented continuous monitoring of radioactive material in hot cell environments. In this monitoring system, the surveillance camera data and NDA data are time synchronized and integrated into the same dimension through data processing. The integrated information is then fed into a neural network to generate diagnostics through data processing. the integrated information of the concept is tested for a spent nuclear fuel transprotation in an operational hot cell at KAERI. The presented integral part of the multi-sensory system and the analytical paradigm may provide an effective technologyical alternative for safeguarding new conceptual hot cell facilities, namely the Dupic facility.

• International Journal of Naval Architecture and Ocean Engineering
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• 제10권5호
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• pp.617-628
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• 2018

Several techniques have been developed in the last years for energy conversion and aeronautic propulsion plants monitoring and diagnostics, to ensure non-stop availability and safety, mainly based on machine learning and pattern recognition methods, which need large databases of measures. This paper aims to describe a simulation based monitoring and diagnostic method to overcome the lack of data. An application on a gas turbine powered frigate is shown. A MATLAB-SIMULINK(R) model of the frigate propulsion system has been used to generate a database of different faulty conditions of the plant. A monitoring and diagnostic system, based on Mahalanobis distance and artificial neural networks have been developed. Experimental data measured during the sea trials have been used for model calibration and validation. Test runs of the procedure have been carried out in a number of simulated degradation cases: in all the considered cases, malfunctions have been successfully detected by the developed model.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2005년도 제24회 춘계학술대회논문집
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• pp.248-251
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• 2005

본 연구에서는 가스 터빈 엔진의 결함에 의해 나타나는 엔진의 성능 저하를 진단하는 기법을 연구하였다. 대상 엔진을 모델화하기 위해 상용 프로그램 GSP를 이용하여 저하된 성능 진단을 위한 변수들을 추출하였으며 이를 바탕으로 Health Monitoring을 위한 Virtual Sensor Model을 구축하였다. 단일 결함과 복합 결함을 예측하기 위한 방법으로 Multiple Linear Regression기법과 가중치를 이용한 기법을 도입하여 엔진 구성품의 결함 위치 및 결함 정도를 예측하였다.

• Smart Structures and Systems
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• 제6권5_6호
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• pp.661-673
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• 2010

This paper presents recent developments in an extremely compact, wireless impedance sensor node (the WID3, $\underline{W}$ireless $\underline{I}$mpedance $\underline{D}$evice) for use in high-frequency impedance-based structural health monitoring (SHM), sensor diagnostics and validation, and low-frequency (< ~1 kHz) vibration data acquisition. The WID3 is equipped with an impedance chip that can resolve measurements up to 100 kHz, a frequency range ideal for many SHM applications. An integrated set of multiplexers allows the end user to monitor seven piezoelectric sensors from a single sensor node. The WID3 combines on-board processing using a microcontroller, data storage using flash memory, wireless communications capabilities, and a series of internal and external triggering options into a single package to realize a truly comprehensive, self-contained wireless active-sensor node for SHM applications. Furthermore, we recently extended the capability of this device by implementing low-frequency analog-to-digital and digital-to-analog converters so that the same device can measure structural vibration data. The compact sensor node collects relatively low-frequency acceleration measurements to estimate natural frequencies and operational deflection shapes, as well as relatively high-frequency impedance measurements to detect structural damage. Experimental results with application to SHM, sensor diagnostics and low-frequency vibration data acquisition are presented.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2008년도 춘계학술대회 논문집 센서 박막재료연구회 및 광주 전남지부
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• pp.111-114
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• 2008

The paper considers the relation between on-line monitoring and diagnostics on the one hand and high-voltage (HV) withstand and partial discharge (PD) on-site testing on the other. HV testing supplies the basic data (fingerprints) for diagnostics. In case of warnings by on-line diagnostic systems, off-line withstand and PD testing delivers the best possible information about defects and enables the classification of the risk. Because alternating voltage (AC) is the most important test voltage, the AC generation on site is considered. Frequency tuned resonant (ACRF) test systems are best adapted to on-site conditions. They can be simply combined with PD measuring equipment. The available ACRF test systems and their application to electric power equipment -from cable systems to power transformers - is described.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2008년도 춘계학술대회 논문집 센서 박막재료연구회 및 광주 전남지부
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• pp.103-105
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• 2008

In, this paper, we consider the relation between on-line monitoring and diagnostics on the one hand and high-voltage (HV) withstand and partial discharge (PO) on-site testing on the other. HV testing supplies the basic data (fingerprints) for diagnostics. In case of warnings by on-line diagnostic systems, off-line withstand and PO testing delivers the best possible information about defects and enables the classification of the risk. Because alternating voltage (AC) is the most important test voltage, the AC generation on site is considered. Frequency tuned resonant (ACRF) test systems are best adapted to on-site conditions. They can be simply combined with PO measuring equipment. The available ACRF test systems and their application to electric power equipment -from cable systems to power transformers - is described.