The design and optimization of two types of novel miniature vibrating Electric Field Sensors (EFSs) based on Micro Electro Mechanical Systems (MEMS) technology are presented.They have different structures and vibratin...The design and optimization of two types of novel miniature vibrating Electric Field Sensors (EFSs) based on Micro Electro Mechanical Systems (MEMS) technology are presented.They have different structures and vibrating modes. The volume is much smaller than other types of charge-induced EFSs such as field-mills. As miniaturizing, the induced signal is reduced enormously and a high sensitive circuit is needed to detect it. Elaborately designed electrodes can increase the amplitude of the output current, making the detecting circuit simplified and improving the signal-to-noise ratio. Computer simulations for different structural parameters of the EFSs and vibrating methods have been carried out by Finite Element Method (FEM). It is proved that the new structures are realizable and the output signals are detectable.展开更多
光伏系统逆变器启动时,最大功率点跟踪(maximum power point tracking,MPPT)等内部控制算法会引起电流瞬态变化,从而干扰直流串联电弧故障诊断装置对故障特征的正确识别,造成误动作。为此,针对逆变器启动情况下电弧故障检测装置易出现...光伏系统逆变器启动时,最大功率点跟踪(maximum power point tracking,MPPT)等内部控制算法会引起电流瞬态变化,从而干扰直流串联电弧故障诊断装置对故障特征的正确识别,造成误动作。为此,针对逆变器启动情况下电弧故障检测装置易出现误动作的问题,提出一种基于无量纲特征量和灰色关联度的故障检测方法。首先分析了电弧故障RLC等效振荡模型,得出电弧电流信号在频域具有较宽的频带;然后分别对逆变器工况与电弧故障实测电流的频域特性进行了对比,发现正常工况与故障在1~20 kHz和40~60 kHz范围内的频谱在波峰陡峭度、所处位置等方面存在差别,使用峭度、偏度、峰值因子、冲击因子、裕度因子、波形因子等提取频谱特征,计算灰色关联度并进行故障识别;最后,分别使用模拟平台和实际光伏系统进行了试验验证。结果表明,所提方法可有效避免逆变器启动造成的干扰,提高故障识别的准确度。展开更多
基金Supported by the National Natural Science Foundation of China (No.60172001).
文摘The design and optimization of two types of novel miniature vibrating Electric Field Sensors (EFSs) based on Micro Electro Mechanical Systems (MEMS) technology are presented.They have different structures and vibrating modes. The volume is much smaller than other types of charge-induced EFSs such as field-mills. As miniaturizing, the induced signal is reduced enormously and a high sensitive circuit is needed to detect it. Elaborately designed electrodes can increase the amplitude of the output current, making the detecting circuit simplified and improving the signal-to-noise ratio. Computer simulations for different structural parameters of the EFSs and vibrating methods have been carried out by Finite Element Method (FEM). It is proved that the new structures are realizable and the output signals are detectable.
文摘光伏系统逆变器启动时,最大功率点跟踪(maximum power point tracking,MPPT)等内部控制算法会引起电流瞬态变化,从而干扰直流串联电弧故障诊断装置对故障特征的正确识别,造成误动作。为此,针对逆变器启动情况下电弧故障检测装置易出现误动作的问题,提出一种基于无量纲特征量和灰色关联度的故障检测方法。首先分析了电弧故障RLC等效振荡模型,得出电弧电流信号在频域具有较宽的频带;然后分别对逆变器工况与电弧故障实测电流的频域特性进行了对比,发现正常工况与故障在1~20 kHz和40~60 kHz范围内的频谱在波峰陡峭度、所处位置等方面存在差别,使用峭度、偏度、峰值因子、冲击因子、裕度因子、波形因子等提取频谱特征,计算灰色关联度并进行故障识别;最后,分别使用模拟平台和实际光伏系统进行了试验验证。结果表明,所提方法可有效避免逆变器启动造成的干扰,提高故障识别的准确度。
