Dissolved gas analysis (DGA) is attracting greater and greater interest from researchers as a fault diagnostic tool for power transformers filled with vegetable insulating oils. This paper presents experimental results of dissolved gases in insulating oils under typical electrical and thermal faults in transformers. The tests covered three types of insulating oils, including two types of vegetable oil, which are camellia insulating oil, Envirotemp FR3, and a type of mineral insulating oil, to simulate thermal faults in oils from 90 °C to 800 °C and electrical faults including breakdown and partial discharges in oils. The experimental results reveal that the content and proportion of dissolved gases in different types of insulating oils under the same fault condition are different, especially under thermal faults due to the obvious differences of their chemical compositions. Four different classic diagnosis methods were applied: ratio method, graphic method, and Duval’s triangle and Duval’s pentagon method. These confirmed that the diagnosis methods developed for mineral oil were not fully appropriate for diagnosis of electrical and thermal faults in vegetable insulating oils and needs some modification. Therefore, some modification aiming at different types of vegetable oils based on Duval Triangle 3 were proposed in this paper and obtained a good diagnostic result. Furthermore, gas formation mechanisms of different types of vegetable insulating oils under thermal stress are interpreted by means of unimolecular pyrolysis simulation and reaction enthalpies calculation.

Transformer winding turn-to-turn fault is the prominent cause of transformer total failure, so detecting the winding fault in real time to stop the failure development in advance is imperative. However, existing techniques entailing periodic offline inspections fail to continuously monitor transformer winding states while causing extra costs due to the outage during inspections. This has driven researchers to consider effective continuous online monitoring methods from several technical perspectives, including typically port voltage current analysis, online frequency response analysis, and vibration analysis. Since these methods are conventionally evaluated with qualitative comparisons focusing only on feasibility, quantitative assessments indispensable for the targeted improvement of the methods and the most suitable method decision in specific scenarios are still missing. To this end, we conduct a comprehensive evaluation on the three methods by leveraging both experiment and theoretical analysis. Specifically, a customized experiment platform has been designed to support data acquisition under different operating conditions. As conventional feature mining algorithms cannot process the monitoring data produced by different methods in a uniform manner, a feature extraction algorithm leveraging image mining is proposed to extract data features after mapping the test data into a high-dimensional image. This novel algorithm allows us to fully assess several fundamental aspects (i.e., sensitivity, repeatability, and antiinterference capability) of these monitoring methods.

The construction of large-scale wind farms results in a dramatic increase of wind turbine (WT) faults. The failure mode is also becoming increasingly complex. This study proposes a new model for early warning and diagnosis of WT faults to solve the problem of Supervisory Control And Data Acquisition (SCADA) systems, given that the traditional threshold method cannot provide timely warning. First, the characteristic quantity of fault early warning and diagnosis analyzed by clustering analysis can obtain in advance abnormal data in the normal threshold range by considering the effects of wind speed. Based on domain knowledge, Adaptive Neuro-fuzzy Inference System (ANFIS) is then modified to establish the fault early warning and diagnosis model. This approach improves the accuracy of the model under the condition of absent and sparse training data. Case analysis shows that the effect of the early warning and diagnosis model in this study is better than that of the traditional threshold method.

Power transformer, as a crucial equipment for power transmission, frequently suffers winding deformation defects, owing to the impact of huge external short-circuit current in actual operation. To resist the rapid deterioration of the defects, online monitoring for winding states is imperative, depending on a thorough understanding of the deformation defects. Unfortunately, there are not much related research on the deformation form and location, as two key objects online diagnosed. In this paper, we concentrate on the analysis of winding deformation and investigation of its high-probability location to deeply understand the winding deformation. For the form of the deformation, a three-dimensional finite element model of the transformer is established to obtain the form and extent of the short-circuit impact force, and a buckling model of the low-voltage winding is designed to analyze the mechanism and form of winding deformation under the impact of huge force induced by short-circuit current. For the location of the deformation, the three-dimensional simulation models are established to analyze the force characteristics of different winding structures in three locations (the conductor transposition area, the area with imbalanced amp-turns and the area with uneven circumferential distribution of force). Then we clarify the possibility of winding deformation in these areas, defined as high-probability locations. Finally, the analyzed results are found to be highly consistent with the actual winding deformation, demonstrating the correctness of the research methods and conclusions. Next stage, the results will provide effective theoretical support for online diagnosis of winding deformation and optimal design of winding structure.

The widely distributed interconnects in printed circuit boards (PCBs) easily couple with high voltage under the action of electromagnetic pulses, which leads to insulation failure. In this study, the dielectric breakdown characteristics of four typical PCBs are studied under continuous square impulse voltage conditions. First, the electric field distribution in the four electrode models is simulated with the ANSYS software (ANSYS Maxwell 17.0). Electric field simulation results show the weak area of electric field distribution. On this basis, the possible breakdown patterns of PCB are analyzed. Second, the influence of factors, such as temperature, pulse duty ratio, interconnect insulation distance, and air pressure, on PCB breakdown voltage is studied through a breakdown test on the PCBs. Results show that the discharge between the single-layer electrodes of the PCBs is surface discharge, and the breakdown is that of a “gas–solid composite medium”. Meanwhile, the breakdown of a double-layer PCB is solid breakdown. Finally, scanning electron microscopy (SEM) produced by Tescan (Brno, Czech Republic) is performed to study the carbonization channel after PCB breakdown. SEM results reveal that the PCB carbonization channel is influenced by temperature and pressure in varying degrees.

Irreversible electroporation (IRE) has emerged as a promising modality for tumor ablation, leveraging the controlled application of electrical pulses to induce cell death. However, the associated muscle contractions during the procedure pose challenges. This study introduces a novel approach, termed Synergistic Bipolar Irreversible Electroporation (SBIRE), aimed at achieving tumor ablation without the undesirable side effect of muscle contraction. SBIRE involves the simultaneous application of nanosecond bipolar electrical pulses (±1600 V per 0.2 cm or ±8000 V per 1 cm, ±500 ns, “+” to “-” delay 1 μs, “-” to “+” delay 200 μs, 5 cycles) and microsecond bipolar electrical pulses (±300 V per 0.2 cm or ±1500 V per 1 cm, ±2 μs, “+” to “-” delay 2 μs, “-” to “+” delay 1000 μs, 25 cycles), strategically designed to synergistically target tumor cells while minimizing the impact on adjacent muscle tissue. The experimental setup includes in vitro and in vivo studies utilizing tumor cells and animal models to assess the efficacy of SBIRE. Preliminary results demonstrate the effectiveness of SBIRE in inducing irreversible electroporation within the tumor, leading to cell death, and the ablation effect is better than other parameter forms (24.41±0.23 mm2 (SBIRE group) vs 12.93±0.31 mm2 (ns group), 6.55±0.23 mm2 (μs group), 19.54±0.25 mm2 (ns+μs group), p<0.0001). Notably, muscle contraction is significantly reduced compared to traditional IRE procedures, highlighting the potential of SBIRE to enhance patient comfort and procedural success. The development of SBIRE represents a significant advancement in the field of tumor ablation, addressing a fundamental limitation associated with muscle contraction during IRE. This technique not only offers a valuable and promising approach to tumor treatment but also holds promise for minimizing procedural side effects.