Extracting Power Transformer Vibration Features by a Time-Scale-Frequency Analysis Method

Abstract

In order to take advantage of the merits of WPT and HHT in feature extraction from vibration signals of power transformer, a time-scale-frequency analysis method is developed based on the combination of these two techniques. This method consists of two steps. First, the desirable wavelet packet nodes corresponding to characteristic frequency bands of power transformer are selected through a Correlation Degree Threshold Screening (CDTS) technique for reconstructing a time-domain signal that contains useful information of power transformer. Second, the HHT is then conducted on the reconstructed signal to track the instantaneous frequencies corresponding to natural characteristics of power transformer. Experimental results are provided by analyzing a real power transformer vibration signal. Compared with the features extracted by directly using HHT, the features obtained by the proposed method reveal clearer condition pattern of the transformer, which shows the potential of this method in condition monitoring of power transformer

Distributed Measuring System for Predictive Diagnosis of Uninterruptible Power Supplies in Safety-Critical Applications

“…Recent works [17][18][19][20][21][22][23][24][25] exploit vibration measurements for mechanical fault diagnosis of power transformers, but they use a large set of sensors, e.g., at least 10 in [17][18][19], 15 in [22], or 40 in [21] for each transformer. Recent works on power transformer analysis [17][18][19][20][21][22][23][24][25], and battery analysis [45][46][47], adopt computation intensive probabilistic algorithms, not implementable in low-cost embedded computing systems.…”

“…Recent works on power transformer analysis [17][18][19][20][21][22][23][24][25], and battery analysis [45][46][47], adopt computation intensive probabilistic algorithms, not implementable in low-cost embedded computing systems. Moreover, the above works usually follow a centralised approach instead of a distributed networking approach as in this paper.…”

“…The weight of these power transformers can be up to a thousand of Kg, whereas their voltage and current levels are up to several hundreds of kVA [8,[17][18][19][20][21][22][23][24][25][26][27][28][29][30]. The causes of degradation for high power transformers can be of an electrical nature, such as over-current and over-voltage conditions, or of a thermal nature, over-temperature condition, and of a mechanical nature.…”

Changes to the Vibration Response of a Model Power Transformer with Faults

“…7 To further develop the vibration-based condition monitoring method, efforts were also made in the area of signal processing to extract the vibration features of a damaged transformer by advanced signal processing methods, including the wavelet transform, the Hilbert Huang transform, and their combinations. 10 Although the feasibility of using the vibration method for transformer condition monitoring was verified in these case studies, there is still a gap in understanding the physical correlation between the changes in the vibration response and changes in the transformer's mechanical properties associated with the causes of failures. A better understanding of vibration changes caused by transformer mechanical faults is beneficial to fault allocation, even to the development of novel monitoring strategies, which is the research motivation of this work.…”

“…Previous work has demonstrated that this method provides an option for assessing the mechanical integrity of a transformer. [6][7][8][9][10][11][12] Unlike the DGA and FRA methods, it relies on changes in the vibration response of the transformer under both steady-state and transient processes. For an example, Berler found that looseness in the winding clamping force might cause variations at twice the operating frequency and its harmonics.…”