Luiz Fernando Freitas-Gutierres

High-frequency current transformers (HFCTs) are widely used for online partial discharge (PD) monitoring in rotating machines due to their non-intrusive nature and high sensitivity to fast current transients. Unfortunately, the scientific literature often lacks detailed descriptions of the physical principles governing HFCT operation and the influence of sensor design parameters on PD detection are considered insufficiently. This paper presents a focused review of HFCT operating principles and their use in PD monitoring of rotating machines. The electromagnetic behavior of the sensor is revisited, highlighting the role of core geometry, material properties, air-gap configuration, and transfer impedance on the frequency response. In addition, the propagation of PD pulses along power cables is discussed to clarify the combined effects of signal attenuation and sensor bandwidth. The analysis contributes to a clearer understanding of HFCT behavior and supports more informed application of this technique in online PD diagnostics in rotating machines.

In this work, a new methodology is proposed for the online and non-invasive extraction of partial discharge (PD) pulses from raw measurement data obtained using a simplified setup. This method enables the creation of sub-windows with optimized size, each containing a single candidate PD pulse. The proposed approach integrates mathematical morphological filtering (MMF) with kurtosis, a first-order Savitzky-Golay smoothing filter, the Otsu method for thresholding, and a specific technique to associate each sub-window with the phase angle of the applied voltage waveform, enabling the construction of phase-resolved PD (PRPD) patterns. The methodology was validated against a commercial PD detection device adhering to the IEC (International Electrotechnical Commission) standard. Experimental results demonstrated that the proposed method, utilizing an off-the-shelf 8-bit resolution data acquisition system and a low-cost high-frequency current transformer (HFCT) sensor, effectively diagnoses and characterizes PD activity in high-voltage equipment, such as surge arresters and instrument transformers, even in noisy environments. It was able to characterize PD activity using only a few cycles of the applied voltage waveform and identify low amplitude PD pulses with low signal-to-noise ratio signals. Other contribution of this work is the diagnosis and fault signature obtained from a real surge arrester (SA) with a nominal voltage of 192 kV, corroborated by destructive disassembly and internal inspection of the tested equipment. This work provides a cost-effective and accurate tool for real-time PD monitoring, which can be embedded in hardware for continuous evaluation of electrical equipment integrity.

Acoustic inspection of distribution networks is seen as one of the main tools for identifying problems in electrical equipment at an early stage. As is often the case with predictive methods, the analysis of detected phenomena can reveal valuable information about the integrity of the equipment. Therefore, this article aims to evaluate the phenomena detected in a distribution network, with a primary focus on the occurrence of partial discharges identified through ultrasonic inspection. A digital ultrasonic testing device was used to detect acoustic signals emitted from an overhead distribution system, thereby gaining more experience in electrical equipment inspection and in the identification of partial discharges.

Acoustic inspection is a valuable technique that can detect early stage defects in equipment, thereby facilitating predictive maintenance. In recent times, ultrasonic sensors have made detecting partial discharges through acoustic sensing increasingly feasible. However, interpreting the acoustic signals can pose challenges, as it requires extensive expertise and knowledge of equipment configuration. To address this issue, a technique based on zero-crossing rate and fundamental frequency estimation has been proposed to standardize insulator diagnosis. In an experiment involving a database of 72 raw acoustic signals with frequencies ranging from 0 to 128 kHz, various types of pollution and defects were introduced to a chain of insulators. By employing the proposed technique, the occurrence of partial discharges can be detected and classified according to type, such as corona or surface discharges. This advanced approach to diagnosis simplifies the process while providing valuable insights into the severity of observed phenomena in the field.

Este trabalho discute o uso da prototipagem rápida no Curso de Graduação em Engenharia de Energia da Universidade Federal do Pampa, Campus Bagé. As atividades basearam-se na estratégia de aprendizagem ativa e foram desenvolvidas por meio de projetos em um componente curricular optativo do Curso. O desafio principal foi apresentar e fazer uso da prototipagem rápida para incentivar nos discentes a busca pela resolução de problemas de Engenharia. Desenvolveu-se um planejamento para a elaboração de projetos, almejando explorar a criatividade, a dinamicidade e o protagonismo dos discentes. Eles foram estimulados a planejar, projetar, fabricar e a acompanhar o processo de impressão 3D até o estágio final de desenvolvimento do projeto. Dentre os resultados, verificou-se a viabilidade de implantação da aprendizagem ativa no componente curricular do curso. Além disso, constatou-se que o amplo envolvimento dos discentes despertou interesse sobre prototipagem rápida também em colegas que não cursaram a disciplina. Palavras-chave: Aprendizagem ativa; prototipagem rápida; Engenharia.

The evaluation of the operating condition of medium and high voltage equipment based on diagnosis of Partial Discharges (PDs), obtained from the measurement of ultrasonic acoustic emissions, has been the object of analysis of many works available in the technical literature. In this sense, this work presents a practical investigation of the occurrence of PDs, detected through acoustic and electrical methods, in a point-flat system subjected to different voltage levels, gaps and environmental conditions. This methodology is adopted to correlate the measured data with the acoustic (unconventional) and electrical (conventional) methods, in order to demonstrate the effectiveness of the former and contribute to obtaining diagnoses with high precision and reliability. The occurrence of PDs signatures, in the time domain for the acoustic and electrical methods, were obtained for the scenarios under analysis, both indicating, with good approximation, the incidence of the phenomenon. The analysis in the frequency domain of the results acquired with the acoustic method also corroborated the diagnosis of PDs in the evaluated scenarios.