• KIPS Transactions on Computer and Communication Systems
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• v.11 no.6
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• pp.193-204
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• 2022

In a smart factory environment in a small and medium-sized enterprise (SME) environment, sensors and actuators operating on actual manufacturing lines, programmable logic controllers (PLCs) to manage them, human-machine interface (HMI) to control and manage such PLCs, and consists of operational technology server to manage PLCs and HMI again. PLC and HMI, which are in charge of control automation, perform direct connection with OT servers, application systems for factory operation, robots for on-site automation, and production facilities, so the development of security technology in a smart factory environment is demanded. However, smart factories in the SME environment are often composed of systems that used to operate in closed environments in the past, so there exist a vulnerable part to security in the current environment where they operate in conjunction with the outside through the Internet. In order to achieve the internalization of smart factory security in this SME environment, it is necessary to establish a process according to the IEC 62443-4-1 Secure Product Development Life cycle at the stage of smart factory SW and HW development. In addition, it is necessary to introduce a suitable development methodology that considers IEC 62443-4-2 Component security requirements and IEC 62443-3 System security requirements. Therefore, this paper proposes an application plan for the IEC 62443 based development security process to provide security internalization to smart factories in an SME environment.

• Korean Journal of Optics and Photonics
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• v.35 no.1
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• pp.9-17
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• 2024

A plenoptic optical system for microscopy comprises an objective lens, tube lens, microlens array (MLA), and an image sensor. Numerical aperture (NA) matching between the tube lens and MLA is used for optimal performance. This paper extends performance predictions from NA matching to unmatching cases and introduces a computational technique for plenoptic configurations using optical analysis software. Validation by fabricating and experimenting with two sample systems at 10× and 20× magnifications resulted in predicted spatial resolutions of 12.5 ㎛ and 6.2 ㎛ and depth of field (DOF) values of 530 ㎛ and 88 ㎛, respectively. The simulation showed resolutions of 11.5 ㎛ and 5.8 ㎛, with DOF values of 510 ㎛ and 70 ㎛, while experiments confirmed predictions with resolutions of 11.1 ㎛ and 5.8 ㎛ and DOF values of 470 ㎛ and 70 ㎛. Both formula-based prediction and simulations yielded similar results to experiments that were suitable for system design. However, regarding DOF values, simulations were closer to experimental values in accuracy, recommending reliance on simulation-based predictions before fabrication.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.478-488
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• 2023

This paper investigates the naval application of laser communication as a potential replacement for traditional acoustic wave communication in underwater environments. We developed a laser transceiver using Arduino and MATLAB, conducting a water tank experiment to validate communication feasibility across diverse underwater conditions. In the first experiment, when transmitting data through a laser, the desired message was converted into data and transmitted, received, and confirmed to be converted into the correct message. In the second experiment, the operation of communication in underwater situations was confirmed, and in the third experiment, the intensity of light was measured using the CDS illuminance sensor module and the limits of laser communication were measured and confirmed in various underwater situations. Additionally, MATLAB code was employed to gather data on salinity, water temperature, and water depth for calculating turbidity. Optimal wavelength values (532nm, 633nm, 785nm, 1064nm) corresponding to calculated turbidity levels (5, 20, 55, 180) were determined and presented. The study then focuses on analyzing potential applications in naval tactical communication, remote sensing, and underwater drone control. Finally, we propose measures for overcoming current technological limitations and enhancing performance.

• Journal of the Korean Geotechnical Society
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• v.40 no.3
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• pp.41-54
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• 2024

Regular monitoring plays a crucial role in ensuring the safety of geotechnical structures. Currently, nondestructive methods are employed to monitor such structures to minimize the impact, e.g., sensor-based accelerometers, displacement meters, image-based lasers, and drone imaging. These technologies can observe surface changes; however, they frequently suffer difficulties in terms of identifying changes in internal properties. To monitor changes in internal properties, in situ geotechnical investigations can be employed. A nondestructive test that can be used for this purpose is the spectral analysis of surface wave (SASW) test using geophones. The SASW test is a nondestructive method; however, due to the time required for data interpretation and the difficulty in analyzing the data, it is challenging to use the SASW test for monitoring applications that require frequent observations. However, it is possible to apply the first-step analysis, which yields the dispersion curve, for monitoring rather than the complete SASW analysis, which yields the shear wave velocity. Thus, this paper presents a fundamental study on the phase difference that derives the dispersion curve to utilize the SASW test for monitoring. The reliability of each phase difference interval is examined to determine the boundary to the subjected monitor. The study used phase difference data obtained using a geophone from a single-layered, homogeneous ground site to evaluate reliable boundaries. The findings of this study are expected to improve the utility of monitoring by identifying the ideal boundary for phase difference data.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.109-121
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• 2024

In various manufacturing processes such as textiles and automobiles, when equipment breaks down or stops, the machines do not work, which leads to time and financial losses for the company. Therefore, it is important to detect equipment abnormalities in advance so that equipment failures can be predicted and repaired before they occur. Most equipment failures are caused by bearing failures, which are essential parts of equipment, and detection bearing anomaly is the essence of PHM(Prognostics and Health Management) research. In this paper, we propose a preprocessing algorithm called SWT-SVD, which analyzes vibration signals from bearings and apply it to an anomaly transformer, one of the time series anomaly detection model networks, to implement bearing anomaly detection model. Vibration signals from the bearing manufacturing process contain noise due to the real-time generation of sensor values. To reduce noise in vibration signals, we use the Stationary Wavelet Transform to extract frequency components and perform preprocessing to extract meaningful features through the Singular Value Decomposition algorithm. For experimental validation of the proposed SWT-SVD preprocessing method in the bearing anomaly detection model, we utilize the PHM-2012-Challenge dataset provided by the IEEE PHM Conference. The experimental results demonstrate significant performance with an accuracy of 0.98 and an F1-Score of 0.97. Additionally, to substantiate performance improvement, we conduct a comparative analysis with previous studies, confirming that the proposed preprocessing method outperforms previous preprocessing methods in terms of performance.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.147-155
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• 2024

Currently, the 4th Industrial Revolution, like other revolutions, is bringing great change and new life to humanity, and in particular, the demand for and use of drones, which can be applied by combining various technologies such as big data, artificial intelligence, and information and communications technology, is increasing. Recently, it has been widely used to carry out dangerous military operations and missions, such as the Russia-Ukraine war and North Korea's reconnaissance against South Korea, and as the demand for and use of drones increases, concerns about the safety and security of drones are growing. Currently, a variety of research is being conducted, such as detection of wireless communication abnormalities and sensor data abnormalities related to drones, but research on real-time detection of threats using radio frequency characteristic data is insufficient. Therefore, in this paper, we conduct a study to determine whether the characteristic data is normal or abnormal signal data by collecting radio frequency signal characteristic data generated while the drone communicates with the ground control system while performing a mission in a HITL(Hardware In The Loop) simulation environment similar to the real environment. proceeded. In addition, we propose an unsupervised learning-based threat detection system and optimal threshold that can detect threat signals in real time while a drone is performing a mission.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.318-327
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• 2009

In this paper, we propose a 3-D geometric localization method for near-field broadband source in shallow water environments. According to the waveguide invariant theory, slope of the interference pattern which is seen in a sensor spectrogram directly proportional to a range of the source. The relative ratio of the range between source and sensors was estimated by matching of two interference patterns in spectrogram. Then this ratio is applied to the Apollonius's circle which shows the locus of a source whose range ratio from two sensors is constant. Two Apollonius's circles from three sensors make the intersection point that means the horizontal range and the azimuth angle of the source. And this intersection point is constant with source depth. Therefore the source depth can be estimated using 3-D hyperboloid equation whose range difference from two sensors is constant. To evaluate a performance of the proposed localization algorithm, simulation is performed using acoustic propagation program and analysis of localization error is demonstrated. From simulation results, error estimate for range and depth is described within 50 m and 15 m respectively.

• The Journal of the Acoustical Society of Korea
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• v.26 no.4
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• pp.173-181
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• 2007

In this paper, we propose a moving target localization algorithm using acoustic spectrograms. A time-versus-frequency spectrogram provide a information of trajectory of the moving target in underwater. For a source at sufficiently long range from a receiver, broadband striation patterns seen in spectrogram represents the mutual interference between modes which reflected by surface and bottom. The slope of the maximum intensity striation is influenced by waveguide invariant parameter ${\beta}$ and distance between target and sensor. When more than two sensors are applied to measure the moving ship-radited noise, the slope and frequency of the maximum intensity striation are depend on distance between target and receiver. We assumed two sensors to fixed point then form a circle of apollonios which set of all points whose distances from two fixed points are in a constant ratio. In case of three sensors are applied, two circle form an intersection point so coordinates of this point can be estimated as a position of target. To evaluates a performance of the proposed localization algorithm, simulation is performed using acoustic propagation program.

• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.400-405
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• 2024

When cavitation noise occurs in ship propellers, the level of underwater radiated noise abruptly increases, which can be a critical threat factor as it increases the probability of detection, particularly in the case of naval vessels. Therefore, accurately and promptly assessing cavitation signals is crucial for improving the survivability of submarines. Traditionally, techniques for determining cavitation occurrence have mainly relied on assessing acoustic/vibration levels measured by sensors above a certain threshold, or using the Detection of Envelop Modulation On Noise (DEMON) method. However, technologies related to this rely on a physical understanding of cavitation phenomena and subjective criteria based on user experience, involving multiple procedures, thus necessitating the development of techniques for early automatic recognition of cavitation signals. In this paper, we propose an algorithm that automatically detects cavitation occurrence based on simple statistical features reflecting cavitation characteristics extracted from acoustic signals measured by sensors attached to the hull. The performance of the proposed technique is evaluated depending on the number of sensors and model test conditions. It was confirmed that by sufficiently training the characteristics of cavitation reflected in signals measured by a single sensor, the occurrence of cavitation signals can be determined.

• Journal of Platform Technology
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• v.12 no.2
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• pp.34-44
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• 2024

This paper proposes a dynamic clock supply control algorithm and a system load power stabilization algorithm that minimizes the power consumption of the sensing system, which accounts for the largest percentage of power consumption in mobile devices, to extend the usage time of the rechargeable battery mounted on the mobile device. The dynamic clock supply control algorithm can reduce the power consumed by the sensing system by configuring a circuit to cut off the power of the sensing system and by recognizing the state of low sensor change and adjusting the measurement cycle. The system load power stabilization algorithm is an algorithm that controls the power of the surrounding module according to the power consumption state, and when it requires a lot of power, it controls the clock supply to stabilize the operation. The experimental results confirmed that applying only the dynamic clock supply control algorithm reduces the power consumed by the sensing system by 17%, and applying only the system load power stabilization algorithm reduces power consumption by 9.3%, enabling it to operate stably in situations that require a lot of power such as image processing. When both algorithms were applied, the power consumption of the battery was reduced by 67% compared to before applying the algorithm. Through this, the reliability of the proposed method was confirmed.