基于改进频域反射法的三芯海底电缆缺陷定位方法
Defect Location Method of Three-core Submarine Cable Based on Improved Frequency Domain Reflection Method
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摘要: 在三芯海底电缆缺陷发展为故障之前对其进行准确定位,可有效保障海上风电系统的稳定运行。为此,文中提出一种基于改进频域反射法的三芯海底电缆缺陷定位方法。首先,建立考虑海水渗透聚丙烯(polypropylene,PP)外披层的三芯海底电缆多导体耦合模型,并在此基础上计算线芯导体的首端频域反射系数谱;然后,提出基于双谱线校正的无窗全相位快速傅里叶逆变换(inverse fast fourier transform,IFFT)方法,将其作为频域反射法的频时转换算法,对首端频域反射系数谱进行处理,得到定位波形,有效抑制了谱泄漏问题与栅栏效应,提升了频域反射法识别并定位三芯海底电缆缺陷的能力;最后,以长度为1 000 m的220 kV三芯海底电缆为研究对象,对三芯海底电缆的两类典型缺陷进行仿真验证。结果表明,该方法可以较好地识别并定位三芯海底电缆的主绝缘老化缺陷与外部破损缺陷,缺陷定位的平均绝对误差小于0.5 m。在单点缺陷试验中,与传统频域反射法相比,该方法可以更灵敏地识别三芯海底电缆的微弱缺陷,同时将缺陷定位的绝对误差至少减少50%;在多点缺陷试验中,传统频域反射法会遗漏部分外部破损缺陷,而该方法则可以识别信噪比为50 dB噪声环境下的三相全部缺陷,同时定位缺陷的相对误差小于0.1%。Abstract: Accurate localization of defects in three-core submarine cables before fault occurrence is essential for the stable operation of offshore wind power systems. An improved frequency domain reflection–based defect localization method is therefore proposed. A multi-conductor coupling model of a three-core submarine cable considering seawater penetration into the polypropylene outer sheath is established to obtain the sending-end frequency-domain reflection coefficient spectrum. A windowless full-phase inverse fast Fourier transform method based on double-spectrum-line correction is then applied for frequency–time conversion, effectively suppressing spectral leakage and the picket-fence effect and enhancing defect identification and localization capability. Simulation studies on a
1000 m, 220 kV three-core submarine cable demonstrate that the proposed method accurately identifies and locates both main insulation aging and external damage defects, with an average absolute localization error of less than 0.5 m. Compared with the conventional frequency domain reflection method, higher sensitivity to weak defects and more than 50% reduction in localization error are achieved in single-point defect scenarios, while all ABC-phase defects are successfully detected under a 50 dB signal-to-noise ratio in multi-point defect scenarios, with relative localization errors below 0.1%
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