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Partial discharge (PD) measurement system based on high frequency current transducer (HFCT) provides a convenient and cost-effective means for online insulation condition monitoring of transformers. However, it is a difficult task to extract PD signals from the measured signals overwhelmed by noise, which consequently leads to ambiguities in the condition assessment of transformers. This paper develops...
Condition monitoring and diagnosis have become an essential part of power transformer asset management. A variety of online and offline measurements have been performed in utilities for evaluating different aspects of transformers’ conditions. However, properly processing measurement data and explicitly correlating these data to transformer condition is not a trivial task. This paper proposes an intelligent...
Measurement of partial discharge (PD) paves a way for transformer insulation diagnosis. However, noise always interferes with PD signals and can jeopardize the diagnostic reliability. Therefore, it is necessary to adopt signal processing techniques to remove noise from collected signals. Among various types of noise, stochastic noise is considerably difficult to remove due to its similarity with PD...
Partial discharge (PD) measurement by using high frequency current transducer (HFCT) provides a means for online monitoring of power transformers. However, extensive interferences and noise can cause difficulties in PD signals interpretation and consequently lead to ambiguity in transformer insulation condition assessment. Therefore, necessary signal processing techniques need to be adopted for PD...
Partial discharge (PD) pattern recognition has been applied for identifying the types of insulation defects in high voltage (HV) equipment. This paper proposes a novel Bayesian neural network (BNN) and discrete wavelet transform (DWT) hybrid algorithm for PD pattern recognition. Laboratory experiments on a number of PD models have been conducted for evaluating the performance of the proposed algorithm.
An accurate interpretation of partial discharge (PD) signals in high voltage (HV) equipment provides crucial information for assessing the insulation conditions. To automate the interpretation process, feature extraction of PD signals and pattern recognition using the extracted features are required. This paper adopts discrete wavelet transform (DWT) and empirical mode decomposition (EMD) for signal...
Partial discharge (PD) measurement provides a means for online monitoring and assessing the insulation condition of a substation transformer. However, the characteristics of PD pulses may vary depending on various factors such as geometry of insulation system, types of PD sources, properties of PD sensors and measurement systems, and sampling rate. Among these factors, sampling rate of PD measurement...
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