Real-Time Monitoring of Air Discharge in a Switchgear by an Intelligent NO2 Sensor Module

An air-insulated power equipment adopts air as the insulating medium and is widely implemented in power systems. When discharge faults occur, the air produces decomposition products represented by NO2. The efficient NO2 sensor enables the identification of electrical equipment faults. However, single-sensor-dependent NO2 detection is vulnerable to interfering gases. Implementing the sensor array could reduce the interference and improve detection efficiency. In the field of NO2 detection, In2O3 sensors have exhibited tremendous advantages. In our work, four composites based on In2O3 are integrated into sensor arrays, which could detect 250 ppb of NO2 and exhibit excellent selectivity when simultaneously exposed to CO. To further reduce the impact of humidity on gas-sensing performance, a convolutional neural network and a long short-term memory model equipped with an attention mechanism are proposed to evaluate NO2 concentration within 1 ppm, and the detection error is 63.69 ppb. In addition, the NO2 concentration estimation platform based on a microgas sensor is established to detect air discharge faults. The average concentration of NO2 generated by 10 consecutive discharge faults at 15 kV is 726.58 ppb, which indicates severe discharge in the switchgear. Our NO2 estimation method has great potential for large-scale deployment in low- and medium-voltage switchgears.

Structural and Functional Changes in Soybean Protein via Remote Plasma Treatments

To the best of our knowledge, few studies have utilized cold plasma to improve soybean protein extraction yield and the functional properties of soybean protein. In this study, we aimed to assess the benefits of remote plasma treatments on soybean with respect to the utilization of soybean protein. This study involved two different sample forms (whole and crushed beans), two different plasma chemistry modes (ozone and nitrogen oxides [NO_x = NO + NO₂]), and a novel pressure-swing reactor. Crushed soybeans were significantly affected by NO_x-mode plasma treatment. Crushed soybeans treated with NO_x-mode plasma had the best outcomes, wherein the protein extraction yield increased from 31.64% in the control to 37.90% after plasma treatment. The water binding capacity (205.50%) and oil absorption capacity (267.67%) of plasma-treated soybeans increased to 190.88% and 246.23 % of the control, respectively. The emulsifying activity and emulsion stability slightly increased compared to those of the control. The secondary structure and surface hydrophobicity were altered. The remote plasma treatment of crushed soybeans increased soybean protein extraction yield compared to plasma-treated whole beans as well as untreated beans and altered the structural and physicochemical properties of soybean proteins.