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A combined CWT-DWT method using model-based design simulator for partial discharges online detection

机译:基于模型的设计仿真器的联合CWT-DWT方法用于局部放电在线检测

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The suppression of noises is fundamental in onsite Partial Discharge (PD) measurements. For this purpose, the wavelet transform analysis method has been developed and it is a powerful tool for processing the transient and suddenly changing signals. As the wavelet transform possesses the properties of multi-scale analysis and time-frequency domain localization, it is also particularly suitable to process the suddenly changing signals of the partial discharge pulse (PD). In this paper, an improved Wavelet denoising method developed by a model-based design software is presented. Simulations are provided as well as some results obtained during laboratory experiment and on-line PD measurements. The new method efficiency of reducing noises is evaluated by comparing the frequency spectrum before and after filtering processes with other software and hardware methods.
机译:噪声抑制是现场局部放电(PD)测量的基础。为此,已经开发了小波变换分析方法,它是处理瞬态和突然变化信号的强大工具。由于小波变换具有多尺度分析和时频域定位的特性,因此它也特别适合处理局部放电脉冲(PD)突然变化的信号。本文提出了一种基于模型的设计软件开发的改进的小波去噪方法。提供了仿真以及在实验室实验和在线PD测量过程中获得的一些结果。通过将滤波过程前后的频谱与其他软件和硬件方法进行比较,可以评估降低噪声的新方法的效率。

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