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Application of hamming windowed interpolated DFT algorithm based on modified ideal sampling frequency in on-line measuring dielectric loss angle

机译:汉明窗口内插DFT算法在线测量介电损耗角度基于改进的理想采样频率的应用

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To assess the insulation condition of capacitive apparatus, on-line monitoring of dielectric loss angle is an effective measure. Harmonic analysis algorithm is used to calculate dielectric loss angle traditionally, this method can effectively suppress the DC (Direct Current) offset and harmonic interference. However, when the power system frequency fluctuates, the synchronous sampling condition is difficult to meet, so, traditional harmonic analysis method can produce leakage of spectrum and picket-fence effect, which greatly affects the accuracy of dielectric loss angle measurement. In order to reduce this adverse effect, this paper proposes a method called hamming windowed interpolated DFT (Discrete Fourier Transform) algorithm based on modified ideal sampling frequency. Time series analysis based on modified ideal sampling frequency can be used to modify the time series in non-synchronous sampling condition to meet synchronous sampling condition. Hamming windowed interpolated DFT algorithm can inhibit leakage of spectrum and picket-fence effect. Firstly this paper analyzes the principle of traditional DFT algorithm and the reason that causes leakage of spectrum and picket-fence effect in non-synchronous sampling condition. Secondly, the principle of hamming windowed interpolated DFT algorithm based on modified ideal sampling frequency is elaborated. Finally this paper presents the simulation result which shows that the improved approach has higher accuracy.
机译:为了评估电容装置的绝缘条件,介电损耗角的在线监测是有效的措施。谐波分析算法用于传统上计算介电损耗角度,该方法可以有效地抑制DC(直流)偏移和谐波干扰。然而,当电力系统频率波动时,同步采样条件难以满足,因此,传统的谐波分析方法可以产生频谱和剥离件效应的泄漏,这极大地影响了介电损耗角度测量的准确性。为了减少这种不利影响,本文提出了一种基于修改理想采样频率的汉明窗口内插DFT(离散傅里叶变换)算法的方法。基于修改的理想采样频率的时间序列分析可用于修改非同步采样条件的时间序列,以满足同步采样条件。汉明窗口内插DFT算法可以抑制频谱和剥离围栏效应的泄漏。首先,本文分析了传统DFT算法的原理及导致频谱泄漏和剥离围栏效应的原因在非同步采样条件下。其次,阐述了基于改进的理想采样频率的汉明窗口内插DFT算法的原理。最后,本文提出了模拟结果,表明改进的方法具有更高的准确性。

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