• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.6
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• pp.81-86
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• 2017

The high-pressure resin transfer molding (HP-RTM) process has a very effective for the mass production of carbon fiber reinforced plastic (CFRP) for light weight in the automotive industry. In developing robust equipment, new process and fast cure matrix systems reduces significantly the cycle time less than 5 minutes in recent years. This paper describes the cavity pressure, temperature and molding characteristics of the HP-RTM process. The HP-RTM mold was equipped with two cavity pressure sensors and three temperature sensors. The cavity pressure characteristics of the HP-RTM injection, pressurization, and curing processes were studied. This experiment was conducted with selected process parameters such as mold cap size, maximum press force, and injection volume. Consequently, this monitoring method provides correlations between the selected process parameters and final forming characteristics in this work.

• Journal of the Korean Society of Visualization
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• v.18 no.1
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• pp.11-17
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• 2020

The reduction of CO2 emissions has been a key target in the marine industry since the IMO's MEPC published its findings in 2009. Air lubrication method is one of the mature technologies for commercialization to reduce the frictional resistance and enhance fuel efficiency of ships. Since the air lubrication pattern varies according to the ship's standing position and injection flow rate, in order to effectively control the air lubrication system, it is necessary to be able to judge the air layer development state based on the information collected from the monitoring sensor. In this study, we performed the air lubrication ship simulation experiment to measure the void fraction and the frictional resistance. The void fraction was measured to confirm the behavior of the air. Through the measurement of the frictional resistance, the change in frictional resistance reduction rate from the injection point to the longitudinal direction of the ship was confirmed. Based on the measurement results, correlation analysis was performed on void fraction and frictional resistance reduction rate.

• Geomechanics and Engineering
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• v.24 no.1
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• pp.1-14
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• 2021

In this study, a new approach using electrical resistivity measurement was proposed to detect grout penetration and to evaluate the grouting performance for such as waterproof efficiency in single rock fracture. For this purpose, an electrical resistivity monitoring system was designed to collect multi-channel data in real time. This was applied to a system for grout injection/penetration using a transparent fracture replica with various aperture sizes and water-cement mix ratio. The electrical resistivity was measured under various grout penetration conditions in real time, which results were directly compared to the visual observation images of grout penetration/distribution. Moreover, the grouting success status after the curing process was evaluated by measuring the electrical resistivity in relation to changes in frequency in fracture cells where grout injection and penetration were completed. Consequently, it was determined that the electrical resistivity monitoring system could be applied effectively to the detection of successful penetration of grouting into a target area and to actual field evaluation of the grouting performance and long-term stability of underground rock structures.

• Smart Structures and Systems
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• v.29 no.6
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• pp.785-790
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• 2022

Condition monitoring of permanent magnet synchronous motors (PMSMs) and detecting faults such as eccentricity and demagnetization are essential for ensuring system reliability. Motor current signal analysis is the most commonly used precursor for detecting faults in the PMSM drive system. However, the current signature responds sensitively to the load and temperature of the motor, thereby making it difficult to monitor faults in real- applications. Therefore, in this study, a condition monitoring methodology that detects motor faults, including their classification with standstill conditions, is proposed. The objective is to detect and classify faults of PMSMs by using programmable inverter without additional sensors and systems for detection. Both DC and AC were applied through the d-axis of a three-phase motor, and the change in incremental inductance was investigated to detect and classify faults. Simulation with finite element analysis and experiments were performed on PMSMs in healthy conditions as well as with eccentricity and demagnetization faults. Based on the results obtained from experiments, the proposed method was confirmed to detect and classify types of faults, including their severity.

• Korea-Australia Rheology Journal
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• v.16 no.4
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• pp.163-168
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• 2004

In this study, an ultrasonic technique was employed to obtain pressure-volume-temperature (PVT) rela­tionship of polymer melt by measuring ultrasonic velocities under various temperatures and pressures. The proposed technique was applied to on-line monitoring of injection molding process as an attempt to predict quality of molded parts. From the comparison based on Tait equation, it was confirmed that the PVT behav­ior of a polymer is well described by the variation of ultrasonic velocities measured within the polymer medium. In addition, the changes in part weight and moduli were successfully predicted by combining the data collected from ultrasonic technique and artificial neural network algorithm. The results found from this study suggest that the proposed technique can be effectively utilized to monitor the evolution of solid­ification within the mold by measuring ultrasonic responses of various polymers during injection molding process. Such data are expected to provide a critical basis for the accurate prediction of final performance of molded parts.

• Journal of Sensor Science and Technology
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• v.22 no.5
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• pp.309-314
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• 2013

Glass micropipettes are widely used for drug injection in neurological studies. To enable these devices to monitor neural activity simultaneously with drug injection, an electrode such as Ag/AgCl must be located near or inserted into the glass micropipette to detect electrical signals in vivo. Here, we report carbon-nanotube-modified glass micropipettes (CNGs), which have excellent electrochemical properties such as low impedance and large electrochemical surface area suited for neural recording. In addition, using a standard pressure pump, CNGs can deliver drugs to the target region without bending. Because they are based on standard glass micropipettes, CNGs can readily be applied to traditional equipment, creating opportunities to monitor precisely the drug-injected area.

• Journal of IKEEE
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• v.26 no.3
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• pp.389-395
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• 2022

With the evolution of technology, cyber physical systems (CPSs) are being upgraded, and new types of cyber attacks are being discovered accordingly. There are many forms of cyber attack, and all cyber attacks are made to manipulate the target systems. A representative system among cyber physical systems is a cyber physical power system (CPPS), that is, a smart grid. Smart grid is a new type of power system that provides reliable, safe, and efficient energy transmission and distribution. In this paper, specific types of cyber attacks well known as false data injection attacks targeting state estimation and energy distribution of smart grid, and protection strategies for defense of these attacks and dynamic monitoring for detection are described.

• Design & Manufacturing
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• v.17 no.3
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• pp.34-40
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• 2023

In this study, real-time collection of mold vibration signals during injection molding processes was achieved through IoT devices installed on the mold surface. To analyze changes in the collected vibration signals, injection molding was performed under six different process conditions. Analysis of the mold vibration signals according to process conditions revealed distinct trends and patterns. Based on this result, cosine similarity was applied to compare pattern changes in the mold vibration signals. The similarity in time and acceleration vector space between the collected data was analyzed. The results showed that under identical conditions for all six process settings, the cosine similarity remained around 0.92±0.07. However, when different process conditions were applied, the cosine similarity decreased to the range of 0.47±0.07. Based on these results, a cosine similarity threshold of 0.60~0.70 was established. When applied to the analysis of mold vibration signals, it was possible to determine whether the molding process was stable or whether variations had occurred due to changes in process conditions. This establishes the potential use of cosine similarity based on mold vibration signals in future applications for real-time monitoring of molding process changes and anomaly detection.

• Journal of Biosystems Engineering
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• v.21 no.3
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• pp.306-314
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• 1996

A seeder monitoring system was developed to solve the problems of mis-sowing and tube clogging in direct seeding machines, which have been one of the factors that reduce the performance of sowing operations. The system consisted of photo sensors, air nozzles, an air compressor, and a one-chip micro-computer based controller. The system was also equipped with the devices that perform the functions of self-checking and intermittent air injection for cleaning seed tubes. The performance of the system was tested in the laboratory and field. Using the well-cleaned rice seed, the average time for checking the mis-sowing was 1.37 seconds in the field and 1.2 seconds in the laboratory without any malfunction. Overall evaluation of the system indicated that the system can be utilized for seeding machines not only for paddies but beans and corns.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.73-78
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• 2016

In wireless sensor networks, sensors have capabilities of sensing and wireless communication, computing power and collect data such as sound, movement, vibration. Sensors need to communicate wirelessly to send their sensing data to other sensors or the base station and so they are vulnerable to many attacks like garbage packet injection that cannot be prevented by using traditional cryptographic mechanisms. To defend against such attacks, a behavior-based attack detection is used in which some specialized monitoring nodes overhear the communications of their neighbors(normal nodes) to detect illegitimate behaviors. It is desirable that the total sensing area of normal nodes covered by monitoring nodes is as large as possible. The previous researches have focused on selecting the monitoring nodes so as to maximize the number of normal nodes(node coverage), which does not guarantee that the area sensed by the selected normal nodes is maximized. In this study, we have developed an algorithm for selecting the monitoring nodes needed to cover the maximum sensing area. We also have compared experimentally the covered sensing areas computed by our algorithm and the node coverage algorithm.