• Journal of Korean Society for Quality Management
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• v.49 no.3
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• pp.327-340
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• 2021

Purpose: The purpose of this study is to propose a system predicting whether an electricity distribution system is abnormal by analyzing the temperature of the deteriorated system. Traditional electricity distribution system abnormality diagnosis was mainly limited to post-inspection. This research presents a remote monitoring system for detecting thermal images of the deteriorated electricity distribution system efficiently hereby providing safe and efficient abnormal diagnosis to electricians. Methods: In this study, an object detection algorithm (YOLOv5) is performed using 16,866 thermal images of electricity distribution systems provided by KEPCO(Korea Electric Power Corporation). Abnormality/Normality of the extracted system images from the algorithm are classified via the limit temperature. Each classification model, Random Forest, Support Vector Machine, XGBOOST is performed to explore 463,053 temperature datasets. The process capability index is employed to indicate the quality of the electricity distribution system. Results: This research performs case study with transformers representing the electricity distribution systems. The case study shows the following states: accuracy 100%, precision 100%, recall 100%, F1-score 100%. Also the case study shows the process capability index of the transformers with the following states: steady state 99.47%, caution state 0.16%, and risk state 0.37%. Conclusion: The sum of caution and risk state is 0.53%, which is higher than the actual failure rate. Also most transformer abnormalities can be detected through this monitoring system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.98-105
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• 2021

The sensory stimulation of a cosmetic product has been deemed to be an ancillary aspect until a decade ago. That point of view has drastically changed on different levels in just a decade. Nowadays cosmetic formulators should unavoidably meet the needs of consumers who want sensory satisfaction, although they do not have much time for new product development. The selection of new products from candidate products largely depend on the panel of human sensory experts. As new product development cycle time decreases, the formulators wanted to find systematic tools that are required to filter candidate products into a short list. Traditional statistical analysis on most physical property tests for the products including tribology tests and rheology tests, do not give any sound foundation for filtering candidate products. In this paper, we suggest a deep learning-based analysis method to identify hand cream products by raw electric signals from tribological sliding test. We compare the result of the deep learning-based method using raw data as input with the results of several machine learning-based analysis methods using manually extracted features as input. Among them, ResNet that is a deep learning model proved to be the best method to identify hand cream used in the test. According to our search in the scientific reported papers, this is the first attempt for predicting test cosmetic product with only raw time-series friction data without any manual feature extraction. Automatic product identification capability without manually extracted features can be used to narrow down the list of the newly developed candidate products.

• Fire Science and Engineering
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• v.33 no.2
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• pp.107-113
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• 2019

Recently, due to global warming, the trend shows an increase in number of lightning strikes which increase risk regarding industry infrastructures. Especially in case where the lightning strikes infrastructures including refinery, petorchemical plant facilities or storage tanks, it can cause power failures, electrical machine malfunction and damage which can lead to fire explosion and multiple calamities. Therefore, detailed case studies must be conducted through a systematic research regarding lightning strike accidents in order to understand its mechanism and devise preventive measures. This paper aims to study cases of explosion regarding waste water storage tanks in refineries and petrochemical plants in order to analyze its root cause and provide preventive measures for avoiding lightning related incidents.

• Journal of IKEEE
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• v.24 no.4
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• pp.1004-1010
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• 2020

This paper proposes an initial rotor magnetic pole detection method for single-phase permanent magnet synchronous motors. The target motor cannot obtain position information based on the back emf in the low speed and stop state. Therefore, an open loop starting process is required, and in this process, initial rotor position information for low current and soft start is need. The proposed initial rotor magnetic pole detection algorithm considers the effect of asymmetric air- gap and magnetic flux. In addition, the high-frequency voltage signal injection and the offset voltage for accurate detection is used. As a result, the permanent magnet poles are is determined by acquiring the maximum value of the induced current using the virtual dq-axis.

• Journal of IKEEE
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• v.26 no.2
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• pp.265-270
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• 2022

This paper proposes the detection algorithm for switch open fault of asymmetric 6-phase PMSM based on stationary reference frame dq-axis currents. In this paper, target motor has an asymmetric structure in which two upper three windings have an electrical phase difference of 30° and a neutral point is separated. As a result, dual 3-phase PWM inverters and the detection techniques due to open failures of switch are definitely required. In this paper, the dual dq-axis current control method is used for driving the asymmetric 6-phase PMSM and the open fault switch should be detected by using variable all pass filter and low pass filter in order to detect the current amplitude. The effectiveness and usefulness of the proposed method is verified by several experiments.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.1
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• pp.18-23
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• 2022

Electrohydrodynamic jet (e-jet) printing, a type of direct contactless microfabrication technology, is a versatile fabrication process that enables a wide range of micro/nanopattern arrays by applying a strong electric field between the nozzle and the substrate. In general, the morphology and the thickness of polymers/quantum dot micropatterns show a systematic dependence on the diameter of the nozzle and the ink composition with a fully automated printing machine. The purpose of this report is to provide typical examples of e-jet printed micropatterns of polymers/quantum dots to explain the effect of each process variable on the result of experiments. Here, we demonstrate several operating conditions that allow high-resolution printing of layers of polymers/quantum dots with a precise control over thickness and submicron lateral resolution.

• Tribology and Lubricants
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• v.39 no.4
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• pp.133-138
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• 2023

This paper presents a discussion on lubricating oil filters. The maintenance of lubricating oil filters can improve the performance of mechanical systems and extend the service life of the lubricating oil. Therefore, the effective management of the lubricating oil can extend the service life of the machine and reduce maintenance costs. A representative method for managing lubricating oil is filtering the lubricating oil using a lubricant filter. However, effectively managing a lubricating oil using a lubricant filter requires an understanding of the related knowledge. In this paper, we present the definition, classification, characteristics, specifications, performance, and self-cleaning function of lubricating oil filters. The lubricant filters are classified based on the filter material, filtering method, filtering location, and amount of filtered fluid. Cellulose and glass fiber materials are conventionally used as materials for lubricant filters, and recently, metal materials, which show excellent durability, are being increasingly adopted. The filtering methods can be classified into physical, chemical, magnetic, and electric field methods, and the lubricant filters can be classified according to their location in the lubrication system. The beta ratio and efficiency of the lubricant filter can be determined based on the performance of the filter. Finally, there are many products or technologies that add a self-cleaning function to the filter to remove foreign substances or contaminants for efficient management.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.37-45
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• 2023

In line with the 4th Industrial Revolution, facility maintenance technologies for building smart factories are receiving attention and are being advanced. In addition, technology is being applied to smart farms and smart fisheries following smart factories. Among them, in the case of a recirculating aquaculture system, there is a motor pump that circulates water for a stable quality environment in the tank. Motor pump maintenance activities for recirculating aquaculture system are carried out based on preventive maintenance and data obtained from vibration sensor. Preventive maintenance cannot cope with abnormalities that occur before prior planning, and vibration sensors are affected by the external environment. This paper proposes an anomaly detection algorithm that utilizes ADTK, a Python open source, for motor pump anomaly detection based on data collected through current sensors that are less affected by the external environment than noise, temperature and vibration sensors.

• Korea Trade Review
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• v.45 no.2
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• pp.51-65
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• 2020

According to an analysis of 560 foreign-invested companies investing in South Korea's manufacturing industry, the following three facts were found. First, the proportion of sales by manufacturing foreign-invested companies is divided into 68.5 percent of domestic sales and 31.5 percent of exports. From 68.5 percent of domestic sales, sales to Korean companies are 60.5 percent, including 37.1 percent for large companies and 23.4 percent for small and medium-sized companies, while only 8.0 percent for domestic consumers. Second, the investment sectors of manufacturing foreign-invested enterprises are 'machine and equipment manufacturing', 'chemical and chemical-chemical material manufacturing-excluding pharmaceuticals', 'electronic components, computers, video, sound and communication equipment manufacturing' and 'vehicle and trailer manufacturing'. It overlaps with electric·electronics, petro-chemicals and automobiles, which are Korea's main industries and areas of Korean global companies. Third, 31.5 percent of the sales of foreign-invested companies in the manufacturing sector are exported. Foreign-invested companies export their products to use them for their parents or affiliates or to the third countries. The analysis shows that foreign-invested companies invested in Korea for B2B transactions with Korean companies. The implications are that Korea can attract foreign investments by utilizing Korean companies' demand for intermediate goods. Foreign-invested companies can invest in Korea in order to use Korea, which has signed free trade agreements with the US, the EU and ASEAN, as an export platform.

• Geomechanics and Engineering
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• v.35 no.5
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• pp.487-497
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• 2023

Penetration rate (PR) and penetration depth (Pe) are crucial parameters for estimating the cost and time required in tunnel construction using tunnel boring machines (TBMs). This study focuses on investigating the impact of rock strength on PR and Pe through full-scale experiments. By conducting controlled tests on rock-like specimens, the study aims to understand the contributions of various ground parameters and machine-operating conditions to TBM excavation performance. An earth pressure balanced (EPB) TBM with a sectional diameter of 3.54 m was utilized in the experiments. The TBM excavated rocklike specimens with varying uniaxial compressive strength (UCS), while the thrust and cutterhead rotational speed were controlled. The results highlight the significance of the interplay between thrust, cutterhead speed, and rock strength (UCS) in determining Pe. In high UCS conditions exceeding 70 MPa, thrust plays a vital role in enhancing Pe as hard rock requires a greater thrust force for excavation. Conversely, in medium-to-low UCS conditions less than 50 MPa, thrust has a weak relationship with Pe, and Pe becomes directly proportional to the cutterhead rotational speed. Furthermore, a strong correlation was observed between Pe and cutterhead torque with a determination coefficient of 0.84. Based on these findings, a predictive model for Pe is proposed, incorporating thrust, TBM diameter, number of disc cutters, and UCS. This model offers a practical tool for estimating Pe in different excavation scenarios. The study presents unprecedented full-scale TBM excavation results, with well-controlled experiments, shedding light on the interplay between rock strength, TBM operational variables, and excavation performance. These insights are valuable for optimizing TBM excavation in grounds with varying strengths and operational conditions.