• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 추계학술대회
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• pp.914-916
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• 2013

재생에너지는 주변 환경으로부터 다양한 방법으로 다양한 형태로 획득 하는 에너지이다. 최근 기능성 고분자 복합물(EAP)을 활용하여 압력이나 진동 등의 물리적 에너지를 전기 에너지로 전환 저장, 활용하는 집전 기술이 주목 받고 있다. EAP의 한 종류인 IPMC(Ionic exchange Polymer Composite)는 친수성 특성을 가지고 있어 해양 발전 플랜트 에너지원으로 연구가 진행중이다. IPMC를 활용한 해양 발전 플랜트 연구는 시간적 제약이 없어 실시간으로 IPMC에서 생성되는 전력을 측정 할 수 있는 시스템이 필요하며, 해상에 떠있는 발전 플랜트 특성상 유선을 통한 전력 측정 시스템 구동 및 데이터 전송이 어려워 자가 발전 및 무선 데이터 전송 시스템이 필요하다. 본 연구에서는 IPMC 해양 발전 플랜트의 모니터링 시스템을 개발하고자 한다. 다수의 IPMC 발전 플랜트에 대한 개별적인 전류/전압 측정 시스템을 구축하고 이를 CAN 통신을 활용하여 메인 시스템에 모든 정보를 수집 및 무선 통신으로 데이터 전송이 이루어지도록 하며, 태양광을 이용하여 자가 발전시스템을 구축하여 외부의 공급전력 없이 실시간으로 측정시스템이 구동 할 수 있는 모니터링 시스템을 개발하고자 한다.

• Nuclear Engineering and Technology
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• 제53권9호
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• pp.3068-3084
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• 2021

Investigations of large commercial aircraft impact effect on nuclear power plant (NPP) buildings have been drawing extensive attentions, particularly after the 9/11 event, and this paper aims to experimentally assess the damage and vibrations of NPP buildings subjected to aircraft crash. In present Part I, two shots of reduce-scaled model test of aircraft impacting on NPP building were carried out. Firstly, the 1:15 aircraft model (weighs 135 kg) and RC NPP model (weighs about 70 t) are designed and prepared. Then, based on the large rocket sled loading test platform, the aircraft models were accelerated to impact perpendicularly on the two sides of NPP model, i.e., containment and auxiliary buildings, with a velocity of about 170 m/s. The strain-time histories of rebars within the impact area and acceleration-time histories of each floor of NPP model are derived from the pre-arranged twenty-one strain gauges and twenty tri-axial accelerometers, and the whole impact processes were recorded by three high-speed cameras. The local penetration and perforation failure modes occurred respectively in the collision scenarios of containment and auxiliary buildings, and some suggestions for the NPP design are given. The maximum acceleration in the 1:15 scaled tests is 1785.73 g, and thus the corresponding maximum resultant acceleration in a prototype impact might be about 119 g, which poses a potential threat to the nuclear equipment. Furthermore, it was found that the nonlinear decrease of vibrations along the height was well reflected by the variations of both the maximum resultant vibrations and Cumulative Absolute Velocity (CAV). The present experimental work on the damage and dynamic responses of NPP structure under aircraft impact is firstly presented, which could provide a benchmark basis for further safety assessments of prototype NPP structure as well as inner systems and components against aircraft crash.

• Structural Engineering and Mechanics
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• 제63권6호
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• pp.779-788
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• 2017

System identification and damage detection for structural health monitoring have received considerable attention. Various time domain analysis methodologies based on measured vibration data of structures have been proposed. Among them, recursive least-squares estimation of structural parameters which is also known as parametric Kalman filter (PKF) approach has been studied. However, the conventional PKF requires that all the external excitations (inputs) be available. On the other hand, structural uncertainties are inevitable for civil infrastructures, it is necessary to develop approaches for probabilistic damage detection of structures. In this paper, a parametric Kalman filter with unknown inputs (PKF-UI) is proposed for the simultaneous identification of structural parameters and the unmeasured external inputs. Analytical recursive formulations of the proposed PKF-UI are derived based on the conventional PKF. Two scenarios of linear observation equations and nonlinear observation equations are discussed, respectively. Such a straightforward derivation of PKF-UI is not available in the literature. Then, the proposed PKF-UI is utilized for probabilistic damage detection of structures by considering the uncertainties of structural parameters. Structural damage index and the damage probability are derived from the statistical values of the identified structural parameters of intact and damaged structure. Some numerical examples are used to validate the proposed method.

• Smart Structures and Systems
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• 제21권6호
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• pp.741-749
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• 2018

Structural health monitoring (SHM) systems are necessary to achieve smart predictive maintenance and repair planning as well as they lead to a safe operation of mechanical structures. In the context of vibration-based SHM the measured structural responses are employed to draw conclusions about the structural integrity. This usually leads to a mathematically illposed inverse problem which needs regularization. The restriction of the solution set of this inverse problem by using prior information about the damage properties is advisable to obtain meaningful solutions. Compared to the undamaged state typically only a few local stiffness changes occur while the other areas remain unchanged. This change can be described by a sparse damage parameter vector. Such a sparse vector can be identified by employing $L_1$-regularization techniques. This paper presents a novel framework for damage parameter identification by combining sparse solution techniques with an Extended Kalman Filter. In order to ensure sparsity of the damage parameter vector the measurement equation is expanded by an additional nonlinear $L_1$-minimizing observation. This fictive measurement equation accomplishes stability of the Extended Kalman Filter and leads to a sparse estimation. For verification, a proof-of-concept example on a quadratic aluminum plate is presented.

• Advances in aircraft and spacecraft science
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• 제4권6호
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• pp.613-637
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• 2017

The development systems for the Structural Health Monitoring has attracted considerable interest from several engineering fields during the last decades and more specifically in the aerospace one. In fact, the introduction of those systems could allow the transition of the maintenance strategy from a scheduled basis to a condition-based approach providing cost benefits for the companies. The research presented in this paper consists of a definition and next comparison of four methods applied to numerical measurements for the extraction of damage features. The first method is based on the determination of the Structural Intensity field at the on-resonance condition in order to acquire information about the dissipation of vibrational energy throughout the structure. The Damage Quantification Indicator and the Average Integrated Global Amplitude Criterion methods need the evaluation of the Frequency Response Function for a healthy plate and a damaged one. The main difference between these two parameters is their mathematical definition and therefore the accuracy of the scalar values provided as output. The fourth and last method is based on the Mode-shape Curvature, a FRF-based technique which requires the application of particular finite-difference schemes for the derivation of the curvature of the plate. All the methods have been assessed for several damage conditions (the shape, the extension and the intensity of the damage) on two test plates: an isotropic (steel) plate and a 4-plies composite plate.

• 한국유체기계학회 논문집
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• 제16권3호
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• pp.32-38
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• 2013

This paper deals with the study on the rotordynamic and experimental analysis of turbine-generator system connected with a magnetic coupling. Although magnetic coupling has been used to torque transmission of chemical processing pump rotating at under 3,600rpm, magnetic coupling in this study is applied to high-speed turbine-generator system using a working fluid that is refrigerant such as ammonia or R-124a. Results of rotordynamic design analysis are as follows. The first, shaft diameter nearest to outer hub of magnetic coupling has a big effect on the $1^{st}$ critical speed of generator rotor. The second, if the $1^{st}$ critical speeds of turbine rotor and generator rotor have enough to separation margin in comparison to rated speed, the $1^{st}$ critical speed of turbine-magnetic coupling-generator rotor train has enough to separation margin regardless of connection stiffness of magnetic coupling. The analytical FE model is guaranteed by impact test on the prototype and condition monitoring such as measurements of vibration and bearing temperature is also performed.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 추계학술대회
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• pp.585-590
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• 2004

Many machine failures are not detected well in advance due to the masking of background noise and attenuation of the source signal through the transmission mediums. Advanced signal processing techniques using adaptive filters and higher order statistics have been attempted to extract the source signal from the measured data at the machine surface. In this paper, blind deconvolution using the eigenvector algorithm (EVA) technique is used to recover a damaged bearing signal using only the measured signal at the machine surface. A damaged bearing signal corrupted by noise with varying signal-to-noise (s/n) was used to determine the effectiveness of the technique in detecting an incipient signal and the optimum choice of filter length. The results show that the technique is effective in detecting the source signal with an s/n ratio as low as 0.21, but requires a relatively large filter length.

• 비파괴검사학회지
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• 제31권2호
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• pp.134-138
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• 2011

회전기기의 고장 탐지에 있어 기존의 진단법과 달리 동적 하중조건 하에서 비접촉, 비파괴의 적외선 열화상 기법이 제안된다. 본 논문에서는 단열 깊은 홈 볼 베어링을 시편으로 하여, 회전기기의 기존의 고장 진단법 대신 수동형 열화상 기법을 이용한 시험을 수행하였다. 추가적으로, 제안된 방법의 효율성을 평가하기 위해 기존의 진동 스펙트럼 분석법을 적용하여 열화상 시험법을 비교하였다. 시혐의 결과로써, 동적 하중조건 하 볼 베어령의 온도분포 특성이 철저히 분석되었다.

• 한국정밀공학회지
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• 제16권12호
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• pp.119-125
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• 1999

This paper gives an overview of the various approaches to designing statistical pattern recognition scheme based on Bayes discrimination rule and the artificial neural networks for rotating machine condition classification. Concerning to Bayes discrimination rule, this paper contains the linear discrimination rule applied to classification into several multivariate normal distributions with common covariance matrices, the quadratic discrimination rule under different covariance matrices. Also we discribes k-nearest neighbor method to directly estimate a posterior probability of each class. Five features are extracted in time domain vibration signals. Employing these five features, statistical pattern classifier and neural networks have been established to detect defects on rotating machine. Four different cases of rotation machine were observed. The effects of k number and neural networks structures on monitoring performance have also been investigated. For the comparison of diagnosis performance of these two method, their recognition success rates are calculated form the test data. The result of experiment which classifies the rotating machine conditions using each method presents that the neural networks shows the highest recognition rate.

• 동력기계공학회지
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• 제7권2호
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• pp.29-35
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• 2003

The monitoring and diagnostics of the rotating machinery have been received considerable attention for many years. The objectives are to classify the machinery condition and to find out the cause of abnormal condition. This paper describes a classification method of diagnosing the small reciprocating compressor for refrigerators using the artificial neural network and the wavelet transform. In order to extract salient features, the wavelet transform are used from primary noise signals. Since the wavelet transform decomposes raw time-waveform signals into two respective parts in the time space and frequency domain, more and better features can be obtained easier than time-waveform analysis. In the training phase for classification, self-organizing feature map(SOFM) and learning vector quantization(LVQ) are applied, and the accuracies of them ate compared with each other. This paper is focused on the development of an advanced signal classifier to automatize the vibration signal pattern recognition. This method is verified by small reciprocating compressors, for refrigerator and normal and abnormal conditions are classified with high flexibility and reliability.