• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.9
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• pp.887-895
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• 2017

This paper presents a study on the accelerated life tests of parts that operate during the opening and closing of door frames, particularly door hinges. Hinge theoretical verification and validation of the test equipment in the present study and the different structures and fault mode, depending on the purpose of usage analysis, failure mode for one of the hinges of the switchgear components used for electromagnetic shielding facilities and on-site operating conditions. The accelerated life test was designed for the characteristic lifetime prediction of the components, by estimating the shape parameter and the acceleration factor.

• Korean Journal of Computational Design and Engineering
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• v.21 no.2
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• pp.111-121
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• 2016

The plant equipment usually has a long life cycle. During its O&M (Operation & Maintenance) phase, since the occurrence of an accident of offshore plant equipment causes catastrophic damage, it is necessary to make more efforts for managing critical offshore equipment. Nowadays due to the emerging ICTs (Information Communication Technologies) and sensor technologies, it is possible to gather the health status data of important offshore equipment and their environment data, which leads to much concern on CBM (Condition-Based Maintenance). In this study, we will propose an approach to estimate the remaining lifetime of an offshore plant equipment (pump tower) based on gathered ocean environment data.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.983-989
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• 2015

Power transformer is one of the major and key apparatus in electric power system. Monitoring and diagnosis of transformer fault is necessary for improving the life period of transformer. The failures caused by short circuits are one of the causes of transformer outages. The short circuit currents induce excessive forces in the transformer windings which result in winding deformation affecting the mechanical and electrical characteristics of the winding. In the present work, a transformer producing only the radial flux under short circuit is considered. The corresponding axial displacement profile of the windings is computed using Finite Element Method based transient structural analysis and thus obtained displacements are compared with the experimental result. The change in inter disc capacitance and mutual inductance of the deformed windings due to different short circuit currents are computed using Finite Element Method based field analyses and the corresponding Sweep Frequency Responses are computed using the modified electrical equivalent circuit. From the change in the first resonant frequency, the winding movement can be quantified which will be useful for estimating the mechanical withstand capability of the winding for different short circuit currents in the design stage itself.

• Earthquakes and Structures
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• v.8 no.3
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• pp.681-697
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• 2015

Iran as one of the countries located on the Alpine-Himalayan seismic belt has recently experienced a few number of catastrophic earthquakes. A well-known index of how buildings are affected by earthquakes is through assessment of probable Peak Ground Acceleration (PGA) and structures' response spectra. In this research, active faults around Kerman and Birjand, two major cities in eastern parts of Iran, have been considered. Seismic catalogues are gathered to categorize effects of surrounding faults on seismicity of the region. These catalogues were further refined with respect to time and space based on Knopoff-Gardner algorithm in order to increase statistical independency of events. Probabilistic Seismic Hazard Analysis (PSHA) has been estimated for each of cities regarding 50, 100, 200 and 500 years of structures' effective life-span. These results subsequently have been compared with Deterministic Seismic Hazard Analysis (DSHA). It has been observed that DSHA not necessarily suggests upper bound of PSHA results. Furthermore, based on spectral Ground Motion Prediction Equations (GMPEs), Uniform Hazard Spectra (UHS) and spectral acceleration were provided for 2% and 10% levels of probability of exceedance. The results show that increasing source-to-site distance leads to spectral acceleration reduction regarding each fault. In addition, the spectral acceleration rate of variation would increase if the source-to-site distance decreases.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.751-756
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• 2018

In smart factories and industrial IoT, all facilities in a factory are monitored over the Internet, thereby facility can reduce the downtime and increase the availiability by preventive maintenance before it breaks down. The abnormal conditions of the major facilities in the plant are caused by abnormal temperature rise, vibration, and variations in noise. Consequently, it is critical to develop a very small smart device that is easily installed in a small space to enable real-time monitoring of the vibration status of the facility. In this study, smart devices were developed for smart factory fault prediction and robustness management using ultra small micro-controllers with WiFi capabilities and MEMS acceleration sensors.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.7
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• pp.80-88
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• 2021

The behavior of the injection system was determined through FFT and PSD analysis of the pressure data of the common rail, and when the diesel fuel is mixed with water, the pressure data of the common rail, depending on the water content and engine rotation speed, represent a different frequency component distribution. Recently, a theory has been suggested that mixing diesel fuel with water controls engine overheating, fuel efficiency, NOx, CO, etc., but if water content exceeds 10%, it can have a fatal adverse effect on the engine's injection system. In the future, it is necessary to promote fault diagnosis and prediction studies of diesel engines using FFT and PSD results from common rail pressure data.

• Steel and Composite Structures
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• v.32 no.4
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• pp.467-478
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• 2019

Running safety and ride comfort of high speed railway largely depend on the track geometry that is dependent on the bridge deformation. This study presents a theoretical study on mapping the bridge vertical deformations to the change of track geometry. Analytical formulae are derived through the theoretical analysis to quantify the track geometry change, and validated against the finite element analysis and experimental data. Based on the theoretical formulae, parametric studies are conducted to evaluate the effects of key parameters on the track geometry of a high speed railway. The results show that the derived formulae provide reasonable prediction of the track geometry change under various bridge vertical deformations. The rail deflection increases with the magnitude of bridge pier settlement and vertical girder fault. Increasing the stiffness of the fasteners or mortar layer tends to cause a steep rail deformation curve, which is undesired for the running safety and ride comfort of high-speed railway.

• Geomechanics and Engineering
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• v.18 no.2
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• pp.215-224
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• 2019

Excavation of long tunnels by shielded TBMs is a safe, fast, and efficient method of tunneling that mitigates many risks related to ground conditions. However, long-distance tunneling in great depth through adverse geological conditions brings about limitations in the application of TBMs. Among various harsh geological conditions, squeezing ground as a consequence of tunnel wall and face convergence could lead to cluttered blocking, shield jamming and in some cases failure in the support system. These issues or a combination of them could seriously hinder the performance of TBMs. The technique of excavation has a strong influence on the tunnel response when it is excavated under squeezing conditions. The Golab water conveyance tunnel was excavated by a double-shield TBM. This tunnel passes mainly through metamorphic weak rocks with up to 650 m overburden. These metamorphic rocks (Shales, Slates, Phyllites and Schists) together with some fault zones are incapable of sustaining high tangential stresses. Prediction of the convergence, estimation of the creeping effects and presenting strategies to overcome the squeezing ground are regarded as challenging tasks for the tunneling engineer. In this paper, the squeezing potential of the rock mass is investigated in specific regions by dint of numerical and analytical methods. Subsequently, several operational solutions which were conducted to counteract the challenges are explained in detail.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.75-86
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• 2019

Purpose: It is essential for the steel industry to produce steel products without unexpected downtime to reduce costs and produce high quality products. A hot strip rolling mill consists of many mechanical and electrical units. In condition monitoring and diagnosis, various units could fail for unknown reasons. Methods: In this study, we propose an effective method to detect units with abnormal status early to minimize system downtime. The early warning problem with various units was first defined. An autoencoder was modeled to detect abnormal states. An application of the proposed method was also implemented in a simulated field-data analysis. Results: We can compare images of original data and reconstructed images, as well as visually identify differences between original and reconstruction images. We confirmed that normal and abnormal states can be distinguished by reconstruction error of autoencoder. Experimental results show the possibility of prediction due to the increase of reconstruction error from just before equipment failure. Conclusion: In this paper, hot strip roughing mill monitoring method using autoencoder is proposed and experiments are performed to study the benefit of the autoencoder.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.11
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• pp.94-101
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• 2020

In the age of industry 4.0, artificial intelligence is being widely used to realize machinery condition monitoring. Due to their excellent performance and the ability to handle large volumes of data, machine learning techniques have been applied to realize the fault diagnosis of different equipment. In this study, we performed the failure mode effect analysis (FMEA) of an aluminum electrolytic capacitor by using deep learning and big data. Several tests were performed to identify the main failure mode of the aluminum electrolytic capacitor, and it was noted that the capacitance reduced significantly over time due to overheating. To reflect the capacitance degradation behavior over time, we employed the Vanilla long short-term memory (LSTM) neural network architecture. The LSTM neural network has been demonstrated to achieve excellent long-term predictions. The prediction results and metrics of the LSTM and Vanilla LSTM models were examined and compared. The Vanilla LSTM outperformed the conventional LSTM in terms of the computational resources and time required to predict the capacitance degradation.