Detection and Localization of Partial Discharge in Connectors of Air Power Lines by Means of Ultrasonic Measurements and Artificial Intelligence Models

Noninvasive wearable sensor for the continuous monitoring of human sound and movement signals in real-time

Recently, with the development of non-invasive human health monitoring technology including wearable devices, a flexible sensor that monitors 'human sound and movement signals' such as human voice and muscle movement is attracting attention. In this experiment, electrospun nanofibers were mixed with highly conductive nanoparticles and coated with polyaniline to detect the patient's electrical signals. Due to the high piezoelectric effect, nanofiber-based sensors do not require charging through a separate battery, so they can be used as self-powered devices. In addition, the LCR meter test confirmed that the sensor has a high capacitance due to its high conductivity and high sensitivity to electrical signals. The sensor produced in this study can visually estimate the electrical signal of the actual human body through real-time comparison with electromyography (EMG) measuring equipment, and it was confirmed that the error is small. This sensor is expected to be widely used in the medical field, from simple sound and movement signals to disease monitoring.

Combining Step-Growth and Chain-Growth Polymerizations in One Pot: Light-Induced Fabrication of Conductive Nanoporous PEDOT-PCL Scaffold

A novel method based on light-induced fabrication of a poly (3,4-ethylenedioxythiophene)-polycaprolactone (PEDOT-PCL) scaffold using phenacyl bromide (PAB) as a single-component photoinitiator is presented. HBr released from the step-growth polymerization of EDOT is utilized as an in situ catalyst for the chain-growth polymerization of ε-caprolactone. Detailed investigations disclose the formation of a self-assembled nanoporous electroconductive scaffold (1.2 mS cm-1 ). Fluorescence emission spectra of the fabricated scaffold exhibit a mixed solvatochromic behavior, indicating specific interactions between the self-assembled scaffold and solvents with varying polarities, as evidenced by transmission electron microscopy (TEM). Moreover, the same light-induced technique can also be applied for bulk photopolymerization showcasing the versatility and wide-ranging scope of the originated method. In brief, this study introduces a novel approach for light-induced polymerization reactions that is merging step-growth and chain-growth mechanisms. This innovative approach is promising to facilitate in situ polymerization of monomers possessing diverse functionalities.

Rahman SF, Mohd Yusoff MF, Hamzah A. Hydrogen gas sensing performance of a carbon-doped boron nitride nanoribbon at elevated temperatures

In this study, computational simulations were used to investigate the performance of a carbon-doped boron nitride nanoribbon (BC2NNR) for hydrogen (H2) gas sensing at elevated temperatures. The adsorption energy and charge transfer were calculated when H2 was simultaneously attached to carbon, boron, and both boron and nitrogen atoms. The sensing ability was further analyzed considering the variations in current-voltage (I-V) characteristics. The simulation results indicated that the energy bandgap of H2 on carbon, boron, and both boron and nitrogen exhibited a marginal effect during temperature variations. However, significant differences were observed in terms of adsorption energy at a temperature of 500 K, wherein the adsorption energy was increased by 99.62% of that observed at 298 K. Additionally, the evaluation of charge transfer indicated that the strongest binding site was achieved at high adsorption energies with high charge transfers. Analysis of the I-V characteristics verified that the currents were considerably affected, particularly when a certain concentration of H2 molecules was added at the highest sensitivity of 15.02% with a bias voltage of 3 V. The sensitivity at 298 K was lower than those observed at 500 and 1000 K. The study findings can form the basis for further experimental investigations on BC2NNR as a hydrogen sensor.

Diagnosis of Partial Discharge Based on the Air Components for the 10 kV Air-Insulated Switchgear

Partial discharge (PD) is a common phenomenon of insulation aging in air-insulated switchgear and will change the gas composition in the equipment. However, it is still a challenge to diagnose and identify the defect types of PD. This paper conducts enclosed experiments based on gas sensors to obtain the concentration data of the characteristic gases CO, NO₂, and O₃ under four typical defects. The random forest algorithm with grid search optimization is used for fault identification to explore a method of identifying defect types through gas concentration. The results show that the gases concentration variations do have statistical characteristics, and the RF algorithm can achieve high accuracy in prediction. The combination of a sensor and a machine learning algorithm provides the gas component analysis method a way to diagnose PD in an air-insulated switchgear.

Partial Discharge and Internet of Things: A Switchgear Cell Maintenance Application Using Microclimate Sensors

This paper proposes a solution for the development of microclimate monitoring for Low Voltage/High Voltage switchgear using the PRTG Internet of Things (IoT) platform. This IoT-based real time monitoring system can enable predictive maintenance to reduce the risk of electrical station malfunctions due to unfavorable environmental conditions. The combination of humidity and dust can lead to unplanned electrical discharges along the isolators inside a low or medium voltage electric table. If no predictive measures are taken, the situation may deteriorate and lead to significant damage inside and outside the switchgear cell. Thus, the mentioned situation can lead to unprogrammed maintenance interventions that can conduct to the change of the entire affected switchgear cell. Using a low-cost and efficient system, the climate conditions inside and outside the switchgear are monitored and transmitted remotely to a monitoring center. From the results obtained using a 365-day time interval, we can conclude that the proposed system is integrated successfully in the switchgear maintaining process, having as result the reduction of maintenance costs.