Maintenance of power distribution facilities is a significant subject in the power supplies. Fault caused by deterioration in power distribution facilities may damage the entire power distribution system. However, current methods of diagnosing power distribution facilities have been manually diagnosed by the human inspector, resulting in continuous pole accidents. In order to improve the existing diagnostic methods, a thermal image analysis model is proposed in this work. Using a thermal image technique in diagnosis field is emerging in the various engineering field due to its non-contact, safe, and highly reliable energy detection technology. Deep learning object detection algorithms are trained with thermal images of a power distribution facility in order to automatically analyze its irregular energy status, hereby efficiently preventing fault of the system. The detected object is diagnosed through a thermal intensity area analysis. The proposed model in this work resulted 82% of accuracy of detecting an actual distribution system by analyzing more than 16,000 images of its thermal images.
Artificial intelligence (AI) has been applied to most industries by enhancing automation and contributing greatly to efficient processes and high-quality production. This research analyzes the applications of AI-based automobile accident prevention systems. It deals with AI-based collision prevention systems that learn information from various sensors attached to cars and AI-based accident detection systems that automatically report accidents to the control center in the event of a collision. Based on the literature review, technological and institutional changes are taking place at the national levels, which recognize the effectiveness of the systems. In addition, start-ups at home and abroad as well as major car manufacturers are in the process of commercializing auto parts equipped with AI-based collision prevention technology.
Industrial Motors diagnostic equipment is highly dependent on the automation system, so if there are defects in the automation equipment, it can only rely on the operator’s intuitive judgment.To help with intuitive judgment, Park’s Vactor Approach(PVA) represents the current signal as a pattern of circles, so it can tell if a fault occurs when the circle is distorted. However, the failure to judge the degree of distortion of the circle pattern is the basis of the fault, so it will face difficulties. In this paper, in order to compare the faults of PVA, the period of d-axis current of PVA pulsation was mastered, so that two phase differences occurred in the same signal source. Through experiments, it is confirmed that this is a 90 degree cross formation of PVA, which is convenient for judging from the vision that there is no fault, thus helping the operator to make intuitive judgment.
There has been a significant decline in the number of rail accidents in Korea since system safety management activities were introduced. Nonetheless, analyzing and preventing human error-related accidents is still an important issue in railway industry. As a railway system is increasingly automated and intelligent, the mechanism and process of an accident occurrence are more and more complicated. It is now essential to consider a variety of factors and their intricate interactions in the analysis of rail accidents. However, it has proved that traditional accident models and methods based on a linear cause-effect relationship are inadequate to analyze and to assess accidents in complex systems such as railway systems. In order to supplement the limitations of traditional safety methods, recently some systemic safety models and methods have been developed. Of those, FRAM(Functional Resonance Analysis Method) has been recognized as one of the most useful methods for analyzing accidents in complex systems. It reflects the concepts of performance adjustment and performance variability in a system, which are fundamental to understanding the processes of an accident in complex systems. This study aims to apply FRAM to the analysis of a rail accident involving human errors, which occurred recently in South Korea. Through the application of FRAM, we found that it can be a useful alternative to traditional methods in the analysis and assessment of accidents in complex systems. In addition, it was also found that FRAM can help analysts understand the interactions between functional elements of a system in a systematic manner.
This study analyzed how the installation of a pressure gauge in the indoor fire hydrant of an apartment building affected identifying pressurized water in the pipe, making it easier to conduct internal inspection on the fire suppression system, and ensuring reliability of fire suppression. The following are the study’s results: First, identifying pressurized water in the indoor firefighting pipe had a positive effect on the installation of a pressure gauge in the indoor fire hydrant. This implies that a higher level of identification of pressurized water in the indoor firefighting pipe had a positive impact on improving the installation and use of a pressure gauge in the indoor fire hydrant. Second, making it easier for the fire safety officer to inspect the fire suppression system had a positive effect on the installation of a pressure gauge in the indoor fire hydrant. This suggests that if it becomes easier for the apartment building’s stakeholder to conduct internal inspection or the firefighting facility manager to carry out inspection on the fire suppression system, it would have a positive effect on the installation of a pressure gauge in the indoor fire hydrant. Finally, ensuring reliability in fire suppression had a positive effect on the installation of a pressure gauge in the indoor fire hydrant. This implies that if it becomes easier to identify pressurized water in the indoor firefighting pipe, for the fire safety officer to conduct internal inspection, or for the firefighting facility manager to carry out inspection in accordance with the fire suppression system’s internal inspection requirements, it would increase reliability in fire suppression, making it more necessary to install a pressure gauge in the indoor fire hydrant.
The number of elevators in Korea has surpassed 700,000 units in 2019, which is the 8th in the world by number of installed units and 3rd in the world by new units. The word 'lift' is a representative word, and the category includes elevators, escalators, dumb waiters, and moving walks. Those who live in the city will experience using elevators once or twice a day, and these elevators are becoming an indispensable means of transportation when using high-rise apartments or subways.
However, such a convenient elevator also has a lot of risks that threaten the safety of the user and actually cause many accidents every year. In particular, escalators (including moving walks), which account for as little as 5% of all elevators, account for 70% of all elevator accidents. According to Heinrich's chain of thought theory, accidents are caused by a combination of factors, which are divided into five stages: Stage 1: Genetic Factors and Social Environment, Stage 2: Individual Defects, Stage 3: Unsafe behavior and Unsafe conditions, Stage 4: Accident, Stage 5: Injury. Heinrich said that three of these five phases, unsafe behavior and unsafe conditions, require safety management and efforts to prevent accidents. In escalator accidents, the analysis of accident cases that have occurred so far will be related to unsafe behaviors and unsafe conditions, and the effective management of these causes of accidents will enable safer and more convenient use of escalators.
This study analyzed accident cases of elevator users, focusing on escalator accidents over the last 10 years (2010 ~ 2019), and safety management to prevent safety accidents of elevator users by analyzing the behavior of actual users and questionnaires of experts in related fields. The method was studied.
The importance of innovative capability, the driving force behind innovation as a company’s intangible resources, is increasing. In general, companies with high innovation capability are more likely to be successful in innovation, which can be expected to have a positive impact on corporate performance. The innovation capacity of SMEs considered in this study is R&D capability and manufacturing capability. The reason for this is that not only the continuous efforts to strengthen the competitiveness of SMEs are focused on stabilizing manufacturing capability, but also considering the situation in which governmental support for SMEs’ R&D capability has been actively developed. This study examines whether R&D capability and manufacturing capability have a significant influence on corporate performance and securing competitive advantage, and analyzes whether competitive advantage acts as a mediator between innovation capability and corporate performance through regression analysis. SPSS 23.0 software was used for the empirical analysis of the data obtained through the survey. The research results are as follows. First, both R&D and manufacturing capabilities of SMEs were found to have a significant positive effect on corporate performance. Second, manufacturing capability had a significant effect on securing competitive advantage of SMEs, but R&D capability was not significant. Third, the competitive advantage of SMEs was found to play a mediating role between manufacturing capability and corporate performance.
The purpose of this study was to measure the job aspiration and examine the relationship between that and job satisfaction for wage-earners using the fourth Korean Working Conditions Survey(KWCS). We use the stochastic frontier model for measuring the job aspiration and testing its effect on the job satisfaction. Fstochastic frontier model is introduced to explain that each company potentially produces less than it might due to a degree of job aspiration, measured by decomposing the residuals. In this model framework, it can be regard that the upper bound of the job satisfaction is the ideal frontier, and the bias between the ideal condition and the reality is the job aspiration. If this concept is applicable to the job aspiration, we can measure this bias and investigate a relationship with the job satisfaction. We find that there exists the job aspiration, and it is significantly negatively correlated with the job satisfaction. This result supports that if job aspiration increases, job satisfaction level decreases.