• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.187-196
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• 2011

Induction motors play a vital role in aeronautical and automotive industries so that many researchers have studied on developing a fault detection and classification system of an induction motor to minimize economical damage caused by its fault. With this reason, this paper extracts robust feature vectors from the normal/abnormal vibration signals of the induction motor in noise circumstance: partial autocorrelation (PARCOR) coefficient, log spectrum powers (LSP), cepstrum coefficients mean (CCM), and mel-frequency cepstrum coefficient (MFCC). Then, we classified different types of faults of the induction motor by using the extracted feature vectors as inputs of a neural network. To find optimal feature vectors, this paper evaluated classification performance with 2 to 20 different feature vectors. Experimental results showed that five to six features were good enough to give almost 100% classification accuracy except features by CCM. Furthermore, we considered that vibration signals could include noise components caused by surroundings. Thus, we added white Gaussian noise to original vibration signals, and then evaluated classification performance. The evaluation results yielded that LSP was the most robust in noise circumstance, then PARCOR and MFCC followed by LSP, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.611-617
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• 2018

The application of health monitoring, including a fault detection technique, is needed to secure the structural safety of large structures. A 2-step crack identification method for detecting the crack location and size of the beam structure is presented. First, a crack occurrence region was estimated using the modified Laplacian operator for the strain mode shape obtained from the distributed local strain data. The crack location and size were then identified based on the natural frequencies obtained from the acceleration data and the neural network technique for the pre-estimated crack occurrence region. The natural frequencies of a cracked beam were calculated based on an equivalent bending stiffness induced by the energy method, and used to generate the training patterns of the neural network. An experimental study was carried out on an aluminum cantilever beam to verify the present method for crack identification. Cracks were produced on the beam, and free vibration tests were performed. A crack occurrence region was estimated using the modified Laplacian operator for the strain mode shape, and the crack location and size were assessed using the natural frequencies and neural network technique. The identified crack occurrence region agrees well with the exact one, and the accuracy of the estimation results for the crack location and size could be enhanced considerably for 3 damage cases. The presented method could be applied effectively to the structural health monitoring of large structures.

• Explosives and Blasting
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• v.22 no.3
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• pp.57-64
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• 2004

There are two major types of underwater blasting at Korea, bridges and harbor construction work. Pier blasting for lay the foundation bridges construction is used dry excavation working (drilling and charging) after pump out water and then fire pump in water that is same as bench blasting. In contrast, underwater blasting for harbor construction and increase of harbor load depth is used to barge with digging equipment that is in oder to drilling on the surface and blasting work(charge, hook-up) under water. Thus, there are need to special concern such as charge method and hook-up method different from tunnel blasting work and bench blasting work. If do not use special concern breaks out dead pressure and mis fire because of there are so many difficult condition such as water pressure, obstruct field of vision. In this study underwater blasting at Busan Harbor Construction have consider with special concern that is plastic pipe charge method used to MegaMITE I and specialized buoy hook- up method make far initial system detonate on the surface used to TLD. The results is designed blast pattern charge per delay effect an inspection of verify between predict velocity and measure velocity. minimized break out mis fire consideration charge method, hook up method. According to result best underwater blasting design is 105mm drilling dia, MeGAMITE II, HiNLL Plus(non electric detonator).

• Journal of the Earthquake Engineering Society of Korea
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• v.13 no.4
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• pp.67-76
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• 2009

Recently, the active interaction control (AIC) system was proposed as a semi-active control system. The AIC system consists of a primary structure and an auxiliary structure. The objective of the AIC system is to control the response of the primary structure through engagement and disengagement between the primary and auxiliary structures. Previous switching control algorithms have been shown to be effective in reducing the response of the primary structure. However, they have the main drawback of requiring an excessive engagement-disengagement frequency and high interaction force. In this paper, the regions in which the switching is activated and the regions in which the switching is deactivated are described separately, to effectively determine the engagement or the disengagement. The general relationship between the switching regions and the deactivated switching regions selected according to the engagement-disengagement conditions is described within the newly-developed comprehensive switching framework. The proposed engagement-disengagement conditions are designed within a comprehensive switching framework, to reduce engagement-disengagement frequency and interaction force. Furthermore, the effect of a control sampling period on the AIC system is explained in terms of the engagement-disengagement frequency. The effectiveness of the proposed algorithms and the effect of the control sampling period are considered for a single degree of freedom model under free vibration. It is observed that increasing the duration of stay by using a large control sampling period prevents the AIC system from activating the possible chance of switching. The proposed algorithms are shown to be effective, both in restricting ineffective switching and in reducing interaction force.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.119-119
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• 2009

인버터 DC 저항용접의 적용성 증대 : 인버터 DC 저항용접 공법이 SPOT, PROJECTON, SEAM, BUTT 등의 공정에 다양하게 적용되어 저항용접 현장에서 고효율, 친환경적 용접 환경을 만드는데 일조 하고 있다. 특히 자동차의 경량화, 충돌내성 증대, 진동 및 내구성 증대, 공간활용 극대화, 새로운 Design 개념 적용 등의 산업전반에 걸쳐 나타나는 신 Trends로 고 장력 철재의 적용 범위가 확대되고 HSS(High Strength Steel), EHSS(Extra High Strength Steel), UHSS (Ultra High strength Steel ; Hot - Formed Steel )등 다양한 철판의 SPOT 저항용접이 필요하게 되었다. 기존의 AC 단상용접의 전력 특성 상 통전 중 무 통전 시간 과 높은 PEAK 전력, 단상 대 전력 소모로 인한 전력 DROP 등의 문제로 인하여 신소재의 용접 시 매우 많은 Spatter가 발생하고, 높은 용접품질의 확보가 어려워 지므로 이를 대체하기 위한 공법으로 MFDC ( 인버터 DC 저항용접공법 )이 적용되고 있다. 인버터 DC 저항용접의 적응제어 : MFDC라는 높은 효율의 용접 전력원이 확보 됨에도 불구하고 용접현장에서는 원 자재, 도금 등의 품질 산포, 프레스 물의 가공산포, 공기압 산포, 전극 과열 및 마모 등의 요인에 의하여 저항용접 산포가 발생하고 있다. 이는 인위적인 조작이 어렵고 불규칙적이며, 어디서나 산재하고 있는 문제이다. 이를 용접전력 제어 법으로 개선하여 일정한 용접성을 확보하기 위한 노력이 적응제어 기법이다. 정 전류, 정 전력 제어는 정량 제어로 용접 물을 비롯한 용접부의 변화와는 관계없이 설정된 일정량의 전력을 공급하기만 하는데 반하여 적응제어는 적절한 용접 작업 시의 용접 물의 상태, 전극의 가압, 표면 상태 등에 따른 변화 페턴을 기억하고 이후 진행되는 용접에 대하여 정상 페턴과의 차이를 감지 이를 보상하므로 고품질의 용접성을 보장하는 제어기법이다. 따라서 다양한 용접 산포 유발 요인에 의해 용접부의 변화가 발생한다 하여도 그 변화를 감지 하고 적절한 용접전력을 공급한다면 고품질의 용접성을 확보하는데 유용한 공법이 될 수 있다. 인버터 DC 저항용접의 SPC 관리 : SPOT 용접 시 획득할 수 있는 다양한 파라메터에 대하여 모니터링 하고 이 자료를 data 화 하여 품질 관리에 응용하게 되면 양산라인에서 반복적으로 발생되는 문제점을 확인 할 수 있고 이를 통계적 방법으로 추적 개선해 나간다면 용접 불량 감소 및 생산성 향상에 도움이 되며 작업자의 공정 능력 향상 및 기업의 기술축적에도 높은 기여를 할 수 있을 것이다. 용접 적응제어와 다양한 파라메터 모니터링이 한 system에서 이루어 질 때 높은 용접성 확보와 불량률 감소, 원가절감, 생산성 향상 등의 효과가 극대화 될 것이다.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.5
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• pp.357-371
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• 2023

In cable tunnel construction using TBM, the vertical shaft is an essential structure for entrance and exit of TBM equipment and power lines. Since a shaft penetrates the ground vertically, it often encounters rock mass. Blasting or rock splitting methods, which are mainly used to the rock excavation, cause public complaints due to the noise, vibration and road occupation. Therefore, mechanical excavation using vertical shaft excavation machine are considered as an alternative to the conventional methods. However, at the current level of technology, the vertical excavation machine has limitation in its performance when applied for high strength rock with a compressive strength of more than 120 MPa. In this study, the potential utilization of waterjet technology as an excavation assistance method was investigated to improve mechanical excavation performance in the hard rock formations. Rock cutting experiments were conducted to verify the cutting performance of the abrasive waterjet. Based on the experimental result, it was found that ensuring excavation performance with respect to changing in ground conditions can be achieved by adjusting waterjet parameters such as standoff distance, traverse speed and water pressure. In addition, based on the relationship between excavation performance, uniaxial compressive strength and RQD, it was suggested that excavation performance could be improved by artificially creating joints using the abrasive waterjet. It is expected that these research results can be utilized as fundamental data for the introduction of vertical shaft excavation machines in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.1C
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• pp.45-51
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• 2010

In urban area, design and construction of civil engineering structures such as subway tunnel, underground space and deep excavation is impeded by unreliable site investigation. Variety of embedded objects, electric noises and traffic vibrations degrades the quality of site investigation, whatever the site-investigation technique would be. In this research, a preliminary research was performed to develop a dedicated site investigation technique for urban geotechnical sites, which can overcome the limitations of urban sites. HiRAS (Hybrid Integration of Surface Waves and Resistivity) technique which is the first outcome of the preliminary research was proposed in this paper. The technique combines surface wave as well as electrical resistivity. CapSASW method for surface-wave technique and PDC-R technique for electrical resistivity survey were incorporated to develop HiRAS technique. CapSASW method is a good method for evaluating material stiffness and PDC-R technique is a reliable method for determination of underground stratification even in a site with electrical noise. For the inversion analysis of HiRAS techniuqe, a site-specific relationship between stress-wave velocity and resistivity was employed. As for outgrowth of this research, the 2-D distribution of Poisson's ratio could be also determined.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.16 no.3
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• pp.95-100
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• 2006

Synthesis of the non-swelling property micas was carried out by hydrothermal method. In order to artificially induce the diffusion of ions, a rotating system was attached to the hydrothermal apparatus and by adding 0.7 mm zircon beads, synthesis of the non-swelling property micas could be performed in a low temperature area. The hydrothermal conditions for the preparation of micas were a reaction temperature of $260^{\circ}C$, for 72 hrs, using $1K_2O,\;1Al(OH)_3,\;4Mg(OH)_2\;and\;6SiO_2$ as the starting materials and a 8M-KOH solution as the hydrothermal solvent. The micas obtained under these conditions were a plate shape with a size of $2.89{\mu}m$ and showed a whiteness of over 97 %. Also, through the FT-IR analysis, because the absorption peak of the $Mg_3OH$ vibration was observed at approximately $3700cm^{-1}$, it could be known that it was phlogopite of non-swelling property showing the chemical composition of $KMg_3AlSi_3O_{10}(OH)_2$. This result was very consistent with the EDS analysis where O (41.34 %), Mg (3.88 %), Al (11.45 %), Si (17.62 %) and K (25.71%) elements were detected.

• Tunnel and Underground Space
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• v.23 no.1
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• pp.13-30
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• 2013

Increase of pore fluid pressure resulting from injection of $CO_2$ may reactivate pre-existing faults, and the induced seismic activities can raise the safety issues such as seal integrity, restoration of storage capacity, and, in the worst case, removal of previously injected $CO_2$. Thus, fault stability and potential for $CO_2$ leakage need to be assessed at the stage of site selection and planning of injection pressure, based on the results of large-scale site investigations and numerical modeling for various scenarios. In this report, studies on the assessment of fault stability during injection of $CO_2$ were reviewed. The seismic activities associated with an artificial injection of fluids or a release of naturally trapped high-pressure fluids were first examined, and then site investigation methods for the magnitude and orientation of in situ stresses, the distribution and change of pore fluid pressure, and the location of faults were generally summarized. Recent research cases on possibility estimation of fault reactivation, prediction of seismic magnitude, and modeling of $CO_2$ leakage through a reactivated fault were presented.

• The KIPS Transactions:PartB
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• v.18B no.3
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• pp.147-156
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• 2011

This paper proposes a 3-stage (preprocessing, feature extraction, and classification) fault detection and classification algorithm for induction motors. In the first stage, a low-pass filter is used to remove noise components in the fault signal. In the second stage, a discrete cosine transform (DCT) and a statistical method are used to extract features of the fault signal. Finally, a back propagation neural network (BPNN) method is applied to classify the fault signal. To evaluate the performance of the proposed algorithm, we used one second long normal/abnormal vibration signals of an induction motor sampled at 8kHz. Experimental results showed that the proposed algorithm achieves about 100% accuracy in fault classification, and it provides 50% improved accuracy when compared to the existing fault detection algorithm using a cross-covariance method. In a real-world data acquisition environment, unnecessary noise components are usually included to the real signal. Thus, we conducted an additional simulation to evaluate how well the proposed algorithm classifies the fault signals in a circumstance where a white Gaussian noise is inserted into the fault signals. The simulation results showed that the proposed algorithm achieves over 98% accuracy in fault classification. Moreover, we developed a testbed system including a TI's DSP (digital signal processor) to implement and verify the functionality of the proposed algorithm.