• Journal of the Korean Society for Nondestructive Testing
• /
• v.29 no.1
• /
• pp.36-42
• /
• 2009

We have developed software for converting the volumetric voxel data obtained from X-ray computed tomography(CT) into computer-aided design(CAD) data. The developed software can used for non-destructive testing and evaluation, reverse engineering, and rapid prototyping, etc. The main algorithms employed in the software are image reconstruction, volume rendering, segmentation, and mesh data generation. The feasibility of the developed software is demonstrated with the CT data of human maxilla and mandible bones.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.31 no.1
• /
• pp.32-39
• /
• 2011

The object of this study is to evaluate and discriminate nondestructively the dislocation substructures of Cu and Cu-Zn alloy subjected to the low-cycle-fatigue. The ultrasonic wave velocity, electrical resistivity and positron annhilation lifetime(PAL) were measured to the nondestructive testing. Cyclic fatigue test of Cu and Cu-Zn alloy with much different stacking fault energies was conducted and the correlations between dislocation behavior and nondestructive parameters were studied. Dislocation cell substructure was developed in Cu, while planar array of dislocation structure was developed in Cu-35Zn alloy only increasing dislocation density with fatigue cycles. Decrease in ultrasonic wave velocity, increase in electrical resistivity and PAL were shown because of the development of lattice defects, dislocations and vacancies, by cyclic fatigue at room temperature. In contrast to Cu-Zn alloy of the planar-array dislocation substructure showing continuous changes in the nondestructive parameters, it does not make any noticeable changes in the nondestructive parameters after the evolution of dislocation cell substructure in Cu.

• Korean System Dynamics Review
• /
• v.16 no.3
• /
• pp.5-29
• /
• 2015

The importance of the concept of safety culture has increased in the security of high-risk facility after Chernobyl accident in 1986. This paper elaborated the concept of safety culture and its main factors by Causal Loop Diagram. Due to the decline of safety culture, the occurrence of incidents and accidents require more and more corrective actions to the members of high-risk facilities and thereby increasing their workloads. Employees who must complete the task within the given time have to have time pressures and don't comply with the rules and procedures. Also, a schedule pressure is a big stress for employees, causing mistakes in precision work. In order to improve these problems, CLD of the safety culture in this paper suggests hiring more workers, re-allocation of given workloads and strengthen the learning, communication capabilities and safety leadership. In addition, the two real accident cases were analyzed to test the feasibility of the System Dynamic simulation model through the process of structuring the fault trees on the stationary black out accident in Kori unit 1 in South Korea and Kleen Energy power station explosion in US. The simulation results show that the various safety factors cause the serious accident combined with mechanical failure and safety culture will reduce the possibility of the accidents in these high-risk organizations. This simulation model can contribute to analyzing the impact of the organizational and human factors of safety culture and can provide the alternatives in high-risk facilities.

• Journal of the Korean Society for Heat Treatment
• /
• v.6 no.4
• /
• pp.237-242
• /
• 1993

The fatigue behaviors of mechanically alloyed Al-4Mg alloys dispersed with either $Al_2O_3$ or $MgAl_2O_4$ oxide particles were investigated. This study maily concerned with the role of coherency of dispersed particles with the matrix on the fatigue behavior of the alloys. The $MgAl_2O_4$ which has a spinel structure with the lattice parameter of exactly the twice of Al showed the habit relation with the matrix. The mechanically alloyed Al-4Mg alloys showed stable stress responses with fatigue cycles from start to failure regadless of strain amplitudes and of existence of dispersoids. The Al-4Mg alloy dispersed with $MgAl_2O_4$ showed not only the better static mechanical properties but also the better low cycle fatigue resistance than that with $Al_2O_3$, i.e., much higher plastic strain energy dissipated to failure, at low strain amplitude. However, this alloy showed inferior fatigue resistance to that dispersed with $Al_2O_3$ or that without dispersion at high strain amplitude. These results imply that $MgAl_2O_4$ may promote lowering the stacking fault energy of the alloy inherited from the coherency with the matrix so that dislocations shuttle back and forth on the same slip plane without cross slipping to other planes during fatigue at low strain amplitude resulting in long fatigue life.

• Plant Journal
• /
• v.8 no.3
• /
• pp.49-54
• /
• 2012

In this study, the way how we can find the defects of motor windings in advance will be discussed. The magnetic flux spectrum in the high frequency region of the large motor was analyzed based on the actual fault practices related with motor windings. In case of defective motor relative amplitude ratio of the stator slot frequency to its sideband was very high compared to that of healthy motor. And the defective signal related with motor windings was indicated in advance in the magnetic flux spectrum prior to over 1 month before failure. Considering this aspect it can be estimated that magnetic flux spectrum in the high frequency region has the excellent predictive diagnostic capability.

• Journal of the Korea Convergence Society
• /
• v.8 no.3
• /
• pp.191-197
• /
• 2017

This development is for non-destructive machine using X-Ray source about detecting outline faults of below middle size products. The differentiation is product of research and development unspecialized small and medium-sized products using X-Ray light sources can check real time if the surface of an external fault of radiation dose reference, within the leakage. The speed control is possible by software solution. In addition, we're working on possibly block doors for worker safety and equipment at the same time that inner drive can be identified in the image. These principles, as a key enabler of the current inspection system such as the container is small to medium-sized parts - a long way from utilization level is possible. This research will give rise to major effects for other various non-destructive market industries except car-industry. The most important fact is that this developed non-destructive machine is controlled below $0.2micro-S{\mu}v$.

• Journal of Aerospace System Engineering
• /
• v.11 no.5
• /
• pp.28-35
• /
• 2017

Magnetic Suspension and Balance System (MSBS) demonstrates the capacity to levitate an experimental model absent any mechanical contact using magnetic forces and moments. It allows precise control of position and attitude of the model, and measures external forces and moments acting on the model. For the purpose of acquisition of reliable experimental results under stable and safe conditions, the performance and robustness of the position and attitude control system of MSBS needs to be improved. To this end, Iterative Feedback Tuning (IFT) and L1 adaptive output feedback algorithm were employed to automatically increase command following performance and to ensure robust operation of MSBS with failure of electric power supply. The applicability was validated using computational simulation.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.10
• /
• pp.5899-5905
• /
• 2014

Faults in electric power system can be a critical problem for vehicles. The system durability is determined mainly by the durability of their components and operating conditions. Monitoring the conditions of the electric power system may be necessary because it is very difficult to predict precisely when it will fail. Therefore, the aim of this study was to develop a diagnosis system for an electric power system of a vehicle. The alternator voltage, excitation voltage, lamp voltage, battery voltage, and engine rpm from a crank angle sensor are monitored continuously and the system fault can be then detected in real time. NI USB- 9201 DAQ and LabVIEW SW have been used to measure the voltages and analyze the data. Compared to conventional measurements for only each component, an integrated and portable measurement method was developed. In addition to the monitoring the electric power system in real time, the saved data from the measurement also provides valuable information to improve the durability of the components.

• Journal of the Korea Society for Simulation
• /
• v.29 no.3
• /
• pp.9-18
• /
• 2020

The development of a large-scale thermal power plant control simulator consists of water/steam systems, air/combustion systems, pulverizer systems and turbine/generator systems. Modeling is possible for all systems except mechanical turbines/generators. Currently, there have been attempts to develop neural network simulators for some systems of a boiler, but the development of simulator for the whole system has never been completed. In particular, autoTuning, one of the key technology developments of all power generation companies, is a technology that can be achieved only when modeling for all systems with high accuracy is completed. The simulation results show accuracy of 95 to 99% or more of the actual boiler system, so if the field PID controller is fitted to this simulator, it will be available for fault diagnosis or auto-tuning.

• Smart Structures and Systems
• /
• v.30 no.6
• /
• pp.613-626
• /
• 2022

Guaranteeing the quality and integrity of structural health monitoring (SHM) data is very important for an effective assessment of structural condition. However, sensory system may malfunction due to sensor fault or harsh operational environment, resulting in multiple types of data anomaly existing in the measured data. Efficiently and automatically identifying anomalies from the vast amounts of measured data is significant for assessing the structural conditions and early warning for structural failure in SHM. The major challenges of current automated data anomaly detection methods are the imbalance of dataset categories. In terms of the feature of actual anomalous data, this paper proposes a data anomaly detection method based on data-level and deep learning technique for SHM of civil engineering structures. The proposed method consists of a data balancing phase to prepare a comprehensive training dataset based on data-level technique, and an anomaly detection phase based on a sophisticatedly designed network. The advanced densely connected convolutional network (DenseNet) and Transformer encoder are embedded in the specific network to facilitate extraction of both detail and global features of response data, and to establish the mapping between the highest level of abstractive features and data anomaly class. Numerical studies on a steel frame model are conducted to evaluate the performance and noise immunity of using the proposed network for data anomaly detection. The applicability of the proposed method for data anomaly classification is validated with the measured data of a practical supertall structure. The proposed method presents a remarkable performance on data anomaly detection, which reaches a 95.7% overall accuracy with practical engineering structural monitoring data, which demonstrates the effectiveness of data balancing and the robust classification capability of the proposed network.