Interpretation of Partial-Discharge-Activated Frequency Response Analysis for Transformer Diagnostics

Machines, Journal Year: 2025, Volume and Issue: 13(4), P. 300 - 300

Published: April 4, 2025

This paper introduces a novel diagnostic approach called partial-discharge-activated impulse frequency response analysis (PD-IFRA), developed to overcome the limitations of conventional (FRA) in detecting partial discharges (PDs) power transformers. While traditional FRA with low-impulse-voltage excitation (LIVE) effectively identifies mechanical deformations, inter-turn shorts, and insulation faults, it fails detect incipient PD activity since phenomena require beyond inception voltage (PDIV) initiate. study proposes, for first time, extension IFRA moderate levels—without exceeding limits—enabling early non-destructive detection PDs. Experimental validation on 315 kVA, 11 kV/420 V Dyn11 transformer shows that PD-IFRA PD-related impedance deviations within 10 kHz–2 MHz range, especially sources associated floating metal parts. Furthermore, comparative between normal, short-circuited, PD-induced conditions demonstrates significantly enhances precursory diagnosis PDs where fails. contribution advances condition assessment by integrating sensitivity into FRA-based methods without compromising equipment safety.

Language: Английский

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Diagnosis of Stator Inter-Turn Short Circuit Faults in Synchronous Machines Based on SFRA and MTST

Energies, Journal Year: 2025, Volume and Issue: 18(8), P. 2142 - 2142

Published: April 21, 2025

As a key component of the power system, good or bad conditions synchronous machines will directly affect stable supply electric energy. The inter-turn short fault stator is one main dangers to machine and difficult diagnose. Frequency response analysis has recently been introduced used for detecting this type fault; however, degrees locations cannot be recognized by traditional frequency analysis. Therefore, study improves combining it with deep learning model multivariate time series transformer. First, principle introduced. Second, data circuit faults are obtained using an artificially simulated experimental platform machine. then well-trained. Finally, performance proposed method tested verified. It concludes that potential classifying diagnosing stators in machines.

Language: Английский

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Autonomous numerical methods for solving electrical circuits, a taylor series-based approach

i-manager s Journal on Circuits and Systems, Journal Year: 2024, Volume and Issue: 12(2), P. 1 - 1

Published: Jan. 1, 2024

Electrical circuit analysis is a fundamental aspect of engineering, requiring accurate and efficient computational methods for solving differential equations governing behaviour. Traditional numerical methods, such as Euler's Runge-Kutta approaches, have limitations in accuracy efficiency. This paper explores an autonomous approach using the Taylor Series Method, implemented TKSL simulation system. The study compares Method with conventional techniques, evaluating accuracy, complexity, stability. results indicate that expansion method enhances precision while reducing overhead. work contributes to development tools, potential applications power systems, embedded electronics, real-time analysis. Future studies will focus on extending this nonlinear systems optimizing performance.

Language: Английский

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