The smart grid was initially developed to facilitate communication between operators of the electric power system (such as power generation companies and transmission system operators) and consumers within the distribution network. To implement the smart grid paradigm, time-synchronized measurement devices were developed and introduced into the electric power system. Phasor measurement units (PMUs) and waveform measurement units (WMUs) were created for wide-area transmission networks (at the high-voltage layer), while micro-PMUs were introduced for real-time state estimation in distribution networks (at the low-voltage layer). These time-synchronized measurement devices allow power system operators to monitor the operational status of power generation, transmission, and distribution infrastructure in real time. In particular, data-driven applications utilizing the measurement data can intelligentize and advance the monitoring, operation, and control of the smart grid. The capabilities of digitized high-resolution measurement and time-synchronization are the key factors that enable these contributions to the smart grid. This paper provides an introduction to time-synchronized measurement devices, outlines their specific capabilities, and explores the data-driven applications that can be implemented for advanced smart grid monitoring systems.

The LIDAR principle is used in a variety of fields, including large-scale pipeline facility management, industrial disaster safety control, and atmospheric environmental monitoring, to employ the remote gas detection technique. In this study, we designed and implemented a remote detection method for N2O gas leaks using absorption spectroscopy based on frequency modulation of a Mid-IR quantum cascade laser (QCL) with a wavelength of 4.5 μm. We direct the frequency-modulated beam, locked to a single absorption line of N2O, to a leak hole on a target surface within a range of approximately 50 m. For area scanning around the leak point, we use a galvano scanner to deflect the probe beam. The back-scattered beam from the diffuse target surface is then collected by a Cassegrain telescope with a diameter of 300 mm and detected by an InSb photo-detector with high photon sensitivity. To process the detected signal, we utilize fundamental and second harmonic detection with a lock-in amplifier, resulting in a relative gas concentration expressed as the second harmonic signal normalized by the fundamental signal. Our test results demonstrate that this proposed method can detect gas leaks as small as 0.005 sccm at a distance of 50 m.

Cavity ring-down spectroscopy (CRDS) is an ultra-sensitive direct absorption technique that offers unique advantages compared to other spectroscopic techniques. It can measure cooperative enhanced absorption for weakly absorbing species at ultra-low concentrations. This is achieved by leveraging the concept of a stable optical cavity, which allows for an effective optical path length of several kilometers within a small physical sample length. One advantage of CRDS technology is that it is unaffected by fluctuations in the intensity of the light source. Another advantage is its applicability to the detection of atoms, molecules, and radicals in the atmosphere. Additionally, the equipment associated with this technology is compact and robust. This paper will first introduce the fundamental principles and setup of CRDS technology. It will then provide an overview of the characteristics of the fabrication equipment and the high reflectivity mirror coating process used in cavity ring-down spectroscopy.

This study investigated the effectiveness of tap water application in reducing nano-sized wear particles at a wheel-rail contact interface and its impact on air quality at different train velocities. Airborne wear particles (AWPs) were simulated using a twin-disk rig at 500, 800, and 1,300 RPM. Mass concentration of nano-sized wear particles was measured using a fast mobility particle sizer (FMPS) at a sampling frequency of 1 Hz. To simulate various vehicle dynamics and contact conditions, the slip rate was incrementally increased from 0 to 3%. During wet conditions, water was applied at a rate of 7 L/min. PM0.1 and PM0.56 under dry and wet conditions were compared to evaluate the method’s effectiveness. The analysis showed that the tap water application method improved the air quality by reducing PM0.56 by at least 74% and PM0.1 by approximately 80%. In conclusion, the water application method can effectively improve air quality by reducing generation of nano-sized wear particles. The train velocity affected the generation of nano-sized wear particles under both conditions.

In this paper, we introduce a new pneumatic temperature control technique and its application to precision thermometry. The method controls temperature by adjusting gas pressure through the unique thermohydraulic linkage of the pressure-controlled loop heat pipe (PCLHP). Due to this temperature-pressure linkage, the PCLHP-based pneumatic temperature control achieves exceptional control speed, stability, and precision. To fully understand this method, we systematically investigated the effects of various influencing parameters, such as heat load, sink temperature, and rate of pressure change, on the stability of temperature control. In addition, we successfully achieved closed-type pneumatic temperature control using a mechanically-driven gas pressure controller. We also developed a hybrid PCLHP that incorporates a heat pipe liner into the isothermal region to further improve the temperature uniformity of the pneumatically-controlled temperature field. With this technique, we significantly improved the accuracy of the fixed point of the International Temperature Scale of 1990 by using inside nucleation of the freezing temperature of tin and determining the liquidus temperature of tin. In this paper, we summarize the results of these diverse efforts in characterizing the pneumatic temperature control technique, along with theoretical analyses.

In this study, to improve the performance of a solid oxide fuel cell based on a porous metal support, a fuel cell using a multi-layered anode functional layer was fabricated and electrochemical performance analysis was performed. Surface and cross-sectional microstructures according to particle size control were confirmed through FE-SEM. The pore size of the multi-layer anode functional layer was gradually reduced compared to that of a single-structure anode functional layer. As a result, it was confirmed that the surface roughness was lower than that of the single structure. This led to a reduction in polarization resistance through smooth transmission of gas generated from the electrode. As a result, it was confirmed that electrochemical performance was improved by more than 1.25 times in fuel cells using a multi-layered anode functional layer compared to that with a single structure.

Parallel robots exhibit superior precision to serial robots. They operate with reduced power consumption due to load distribution among individual motors. However, symmetrical parallel robots employing a 1T2R structure encounter challenges with parasitic movements at the end-effector, leading to control complexities and application limitations. This study aimed to downsize the robot while ensuring its operational range by employing origami techniques. Addressing the inherent weakness of origami’s stiffness, various methods of material stacking and designed joints with diverse materials and thicknesses were proposed to meet specific angle requirements for each component. The developed control model was validated through simulations and experiments, effectively minimizing parasitic movements by verifying the robot"s motion.

Manned water-powered aerial vehicles have been implemented into specialized missions around water bodies, such as firefighting and rescue. However, the dual requirement of vehicle motion control and performing tasks challenges operators. Moreover, in the presence of a low visibility, dense smoke, and extreme temperature, they always face potential risks. Motivated by these difficulties, this paper proposed an unmanned water-powered aerial vehicle using a nozzle rotation mechanism. This mechanism allows the vehicle to have a wide range of forces and torques in multiple directions under constant mass flowrate condition. A simple controller was designed to investigate the fundamental flight motions and verify dynamic properties of the vehicle in practical testing. To come up with the control law, the following steps were taken. Firstly, a mathematical model was derived to reflect the vehicle’s dynamic characteristics. Secondly, a well-known proportional-derivative-integral controller incorporating gravity compensation was deployed to regulate the 3-degree-of-freedom motion system. Thirdly, experiments were conducted to confirm the flight ability of the proposed vehicle. Results demonstrated that the control system preserved stability and the vehicle could fly following the desired altitude.

Inertial navigation technology originally designed for precise guidance of missiles is widely used in weapon systems. Guided missiles have become supersonic and high maneuverability with advancement of science and technology. Antivibration performance against high vibration and shock energy is accordingly required. Sensors of an Inertial Navigation System (INS) have a high sensitivity. Conversion coefficients for acceleration values and bias errors in signals must be minimized. A vibration isolator is generally applied to protect INS by attenuating the vibration and shock energy transmitted from dynamic disturbances. The stiffness and damping are changed using highly damped materials such as elastomers that must be protected from disturbances. A vibration isolator is widely used in various fields. However, it is important to understand characteristics of a vibration isolator composed of elastomer because it has nonlinearities such as hyperelasticity and viscoelastic as well as damping characteristics. In this study, a COTS vibration isolator suitable for INS was selected through theoretical approach. Response characteristics of the system in a vibration and shock environment were analyzed through FEM analysis and vibration and shock test. In addition, through repeated excitation test, reproducibility and structural stability were confirmed when the vibration isolator was installed in the system.

In the semiconductor manufacturing industry, efficient operation of wafer transfer robots has a direct impact on productivity and product quality. Ball screw misalignment anomalies are a critical factor affecting precision transport of robots. Early diagnosis of these anomalies is essential to maintaining system efficiency. This study proposed a method to effectively diagnose ball screw misalignment anomalies using 1D-CNN and 2D-CNN models. This method mainly uses binary classification to distinguish between normal and abnormal states. Additionally, explainable artificial intelligence (XAI) technology was applied to interpret diagnostic decisions of the two deep learning models, allowing users to convince prediction results of the AI model. This study was based on data collected through acceleration sensors and torque sensors. It compared accuracies of 1D-CNN and 2D-CNN models. It presents a method to explain the model"s predictions through XAI. Experimental results showed that the proposed method could diagnose ball screw misalignment anomalies with high accuracy. This is expected to contribute to the establishment of reliable abnormality diagnosis and preventive maintenance strategies in industrial sites.