Industrial wastewater containing large amounts of organic pollutants is a severe threat to the environment and human health. Thus, the rapid detection and removal of these pollutants from wastewater are essential to protect public health and the ecological environment. In this study, a multifunctional and reusable surface-enhanced Raman scattering (SERS) substrate by growing Ag nanoparticles (NPs) on ZnO nanorods (NRs) was produced for detecting and degrading Rhodamine B (RhB) dye. The ZnO/Ag substrate exhibited excellent sensitivity, and the limit of detection (LOD) for RhB was as low as 10⁻¹¹ M. Furthermore, the SERS substrate could efficiently degrade RhB, with a degradation efficiency of nearly 100% within 150 min. Moreover, it retained good SERS activity after multiple repeated uses. The interaction between Ag NPs, ZnO, and RhB was further investigated, and the mechanism of SERS and photocatalysis was proposed. The as-prepared ZnO/Ag composite structure could be highly applicable as a multifunctional SERS substrate for the rapid detection and photocatalytic degradation of trace amounts of organic pollutants in water.

Accurately and sensitively detecting and locating the partial discharge (PD) inside transformers is of great significance for ensuring the safe operation of transformers. Due to the obstruction of the ultrasonic signal by the transformer casing and electromagnetic interference in the field, the PD detection accuracy and sensitivity of piezoelectric ultrasonic sensors are limited. This study, based on a real 110 kV transformer, explored the installation method of the fiber-optic Fabry-Perot(F-P) sensor array and the localization method for PD, and compared the detection performance of fiber-optic F-P sensors and piezoelectric sensors. In response to optical and acoustic noise present in the field, an adaptive Wiener filter-based noise reduction method was proposed to enhance the accuracy of arrival time extraction. Based on the TDOA principle, a localization equation considering ultrasonic time delay increment was constructed. A PD localization method based on the SOWGO was introduced, and the localization accuracy and its fluctuations were analyzed under conditions considering and not considering the ultrasonic time delay increment. The research results indicate that fiber-optic F-P sensors have higher sensitivity and better resistance to electromagnetic noise and external acoustic noise interference. The solid structure inside the transformer has a significant impact on ultrasonic localization accuracy. Considering the ultrasonic time delay increment can improve localization accuracy, but it may lead to greater fluctuations in the accuracy. The research findings of this article highlight the advantages of fiber-optic F-P sensors in detecting PD in transformers.

In high voltage direct current (HVDC) cable systems, study of electric field distortion created by space charge accumulation is very important for examining insulation performance. Therefore, in this paper the influence of space charge on short-time breakdown characteristics of cross-linked polyethylene (XLPE) are studied. Trap energy distribution is an important factor affecting space charge behavior in dielectrics. Dielectrics with various thicknesses exhibit different space charge phenomena due to various trap distribution characteristics, which regulate the injection, migration and accumulation processes of charges. Consequently, trap characteristics can affect many parameters, such as charge accumulation depth and injection barrier. XLPE with thickness less than 100 μm show lower density of deep traps which can accumulate homogeneous bulk charges as compared to thick XLPE with thickness greater than 100 μm. This phenomenon determines the internal field strength distortion rate which is 20% larger for thin XLPE and it is much higher than that for thick XLPE. The external factor which is considered for analysis is applied field strength and it shows a linear proportional affect on the electric field distortion. A quantitative relationship model between applied field strength and distortion field strength of XLPE with different thicknesses was established. Linear extrapolation was used to obtain the trend of applied, distortion, and actual field strengths at different XLPE thicknesses when breakdown occurred. When the thickness of XLPE is less than 100 μm, distortion field strengths is higher than 50kV/mm and increases with decreasing thickness, resulting in a significant effect on the breakdown phenomenon and breakdown strength increases with increasing thickness. And when the thickness of XLPE is greater than 100 μm, the distortion field strengths is less than 50 kV/mm which also confirms the volume effect on breakdown phenomenon and breakdown strength decreases with increasing thickness.

Transformers play a crucial role in power systems. In this respect, fault diagnosis and aging state assessment have garnered significant attention from researchers. Herein, accelerated thermal aging and Raman scattering experiments are conducted on oil–paper insulation samples to accurately detect aging states. The samples are categorized into different aging stages based on the polymerization degree of the insulating paper. Principal component analysis (PCA), multi-dimensional scale change method (MDS), and isometric mapping algorithm (Isomap) are employed to extract features from the Raman spectra. Subsequently, the XGBoost strong classifier, optimized through Bayesian hyperparameter optimization (BO-XGBoost), is utilized to distinguish between four and ten states among 175 groups of samples after feature extraction. The subsequent classification results of the three feature-extraction methods are compared. The results indicate that Isoamp, which pertains to the manifold dimension transformation, achieves the highest average discriminative accuracy after feature extraction. The discriminative accuracies for aging states four and ten are 97.0% and 95.1% respectively, demonstrating that Raman spectroscopy manifold dimension transformation enhances the distinctiveness between samples of different aging states in the feature-extraction process. The diagnostic model constructed with Isomap and BO-XGBoost enables accurate discrimination of the aging states of oil–paper insulation.

Solder layer voids have a significant impact on the thermal performance of a device, which is a key cause of the thermal failure of the device. In this paper, the area and location of solder layer voids are calculated by combining finite element modeling and experimental measurements. Specifically, by analyzing the path of heat dissipation in the device, an equivalent thermal resistance network is constructed to calculate the area and location of the solder layer voids, and the calculation results show that the increment of the path thermal resistance depends on the void area; almost independently of the location, the temperature distribution of the device changes due to the phenomenon of heat accumulation in the voids. Further, in order to calculate the position of the solder layer voids, a point thermal resistance network matrix model is proposed based on the temperature distribution characteristics of the device surface. The validity of the proposed model is verified by comparing the calculation results of the junction temperature, void area, and location with the measurement results based on experimental platforms.