• Journal of Korea Multimedia Society
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• v.24 no.9
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• pp.1203-1210
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• 2021

In this paper, we developed the inspection system of electric vehicle pouch battery using image processing. Line scan cameras are used for acquiring the all parts of the pouch battery, and several steps of image processing for extracting significant dimensions(User Required Position) of the battery. In image processing, edge lines, node points, dimension lines, etc. were extracted using Preprocessor, Square Edge Detection, and Size Detection algorithms. This is used to measure the dimensions of the location requested by the user on the pouch battery. For verification of the inspection system, the dimensions of three pouch batteries produced in the same process were measured, and the mean and standard deviation were obtained to confirm the precision.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.275-277
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• 2005

In a lithium-ion battery which is being used in many portable electronic goods, electrolyte is disaggregated and then the gas is happened when electric charging volt is over the 4.5V. So, the pressure on the safety valve is increased and electrolyte is leaked out in the cell. It leads to the risk of explosion. On the other hand, in the case which the battery is discharged excessively, the negative pole is damaged and the performance of the battery is deteriorated. The protection module of a lithium-ion battery is used for preventing such risk and the inspection system is needed to check the performance of such protection module. In this research, a PC-based auto inspection system is developed for the inspection of a battery protection module using Dallas chipset. In the inspection system, AVRl28 chip is used as a controller and the communication protocol is developed for the data communication between the protection module and the AVR128 chip. And GPIB interface is used for the control of measuring devices. Also, MMI environment is developed using LabView for convenient monitoring by the tester.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.1
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• pp.72-79
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• 2016

Uninterruptible power supplies are extensively used as backup power in various applications such as telecommunication systems, Internet data centers, hospitals, and military technologies. Some of these applications require a considerable number of batteries, and the maintenance of such batteries is critical for the reliability of a system. However, batteries are chemical energy storage devices that deteriorate over time and frequently inspecting their performance and suitability is difficult. A real-time remote battery inspection system that applies electrochemical impedance spectroscopy is proposed and implemented in this study. The proposed system consists of a small inspection circuit and software for control. The former is developed to monitor the impedance variation of the battery and to diagnose its state. The validity and feasibility of the proposed system is proven by experimental results.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.147-153
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• 2024

X-rays are extensively employed for non-destructive inspection, applied to packaged food, human anatomy, and industrial products. Recently, this technology has extended to inspecting batteries in electric vehicles. Given the challenge of manual inspection for a substantial volume of batteries, deep learning is leveraged to detect battery defects. However, the effectiveness of deep learning heavily depends upon data size, and acquiring authentic defective images is a difficult and time-consuming task. In this study, we use data augmentation and investigate the impact of data size on battery inspection performance. The results provide valuable insights for enhancing the capabilities of the inspection process.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.909-910
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• 2013

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.6
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• pp.820-826
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• 2012

For the development of reliable thermal batteries, electrolyte is quite important because it is closely related to the performance and stability of thermal batteries. This paper describes general image processing method used for the inspection of molten-salt based electrolyte disk and also describes how we can apply this image processing method to the inspection of thermal battery electrolyte. Moreover we have found optimized image processing conditions to improve the discriminating ability of compaction defects such as non-uniform parts in an electrolyte.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.32-40
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• 2003

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.718-723
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• 2014

In this paper, we developed the inspection system of electric vehicle battery plate using image processing. Four cameras are used for acquiring the principal parts of the plate, and several steps of image processing for extracting significant dimensions of the plate such as widths and lengths. As a preceding step, calibration of four cameras is carried for compensating distorted images using dot-arrayed sheet. Coordinate systems for four cameras are defined where one coordinate system is assigned to the reference coordinate system to which the others are relatively described. Line information of the edge in the windowed image is extracted using elaborate edge-detection algorithm, and finally the intersection points between lines are extracted to calculate widths and lengths of the plate from which the error status of the battery plate is decided.

• Journal of Platform Technology
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• v.11 no.2
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• pp.54-65
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• 2023

Due to the nature of electric vehicles, the batteries used for electric vehicles have a very large rated capacity. If an electric vehicle runs for a long time or an electric vehicle is abandoned due to a traffic accident, the electric vehicle battery becomes a waste battery. Even in vehicles that are being abandoned, the remaining capacity of waste batteries for electric vehicles is sufficient for other purposes. Waste batteries for automobiles are very expensive, so they need to be recycled and reused, but there was a problem that the standards for measuring the performance grade of waste batteries for recycling and reuse were insufficient. As a method for measuring the remaining capacity of waste battery, the most stable and reliable method is to measure the remaining capacity of battery using full charge and discharge. However, the inspection method by the full charging and discharging method varies depending on the capacity of the battery, but it takes more than a day to inspect, and many people are making great efforts to solve this problem. In this paper, an electric vehicle battery residual capacity analysis technique using voltage deviation between cells was studied and analyzed as a method to reduce inspection time for electric vehicle batteries. To this end, a full charging and discharging-based capacity measurement system was constructed, experimental data were collected using a nose or waste battery, and the correlation between the voltage deviation and the remaining capacity of the battery pack was analyzed to verify whether it can be used for battery inspection.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.129-135
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• 2022

Currently, the rapid growth of electric vehicles and the collection and disposal of waste batteries are becoming a social problem. The purpose of this paper is to propose a fast and efficient battery screening method through a safe inspection and storage method according to the collection and storage of waste batteries of electric vehicles. In addition, as the resistance inside the waste battery increases, an instantaneous voltage drop occurs, and there is a risk of overcharging and overdischarging compared to the initial state of the battery. Accordingly, there are great difficulties in operation, so the final goal of this study is to develop a device for diagnosing aging through real-time battery internal resistance measurement. Final result As a result of simulation of the internal resistance measurement test circuit through external impedance (AC), the actual simulation value was 0.05Ω, RS = Vrms / Irms => Vrms = 8.0036mV, Irms = 162.83Ma. Substitute the suggested method. The result was calculated as Rs = 0.0495Ω. It is possible to measure up to 64 impedances inside the aging diagnostic equipment that enables real-time monitoring of the developed battery cells, and the range can be changed according to the application method.