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基于正交分解的介质损耗因数数字测量算法 被引量:35

A Novel Algorithm of Dielectric Loss Measurement Based on Orthogonal Decomposition
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摘要 首先概述了过零点电压比较法、谐波分析法等几种现有的介质损耗因数tanδ数字化测量算法的优缺点,分析tanδ的物理意义及其谐波条件下的定义问题。将电压与电流定义为欧氏函数空间的2个向量,利用正交特性将泄漏电流分解为相互正交的有功分量与无功分量,进而提出了基于正交分解的tanδ数字化测量算法及其简化计算公式。最后分别在电压无畸变、电压含谐波、电压频率波动、采样频率以及采样时间长度变化时,对文中提出的介损测量正交分解法进行仿真验证,并与谐波分析法进行比较分析。仿真结果显示,当电压频率波动与采样数据长度变化时,正交分解法的最大测量误差分别为谐波分析法的23.72%与5.35%;采样频率变化对2种方法的影响相同;在电压频率为50.5Hz时,tanδ实时测量值的波动幅度降低了110倍。该算法物理意义明确,计算简单,测量结果精确、稳定,可用于tanδ的离线测量与在线监测。 The advantages and disadvantages of recent digital algorithms of dielectric loss, which include zero cross point voltage comparison, harmonics analysis and so on, are reviewed, Then signification and definition of dielectric loss factor-rand is analyzed under harmonics exist. Further more, voltage and current are defined as vectors in Euclid function space, and according to orthogonal characteristic, the current signal is decomposed to a total of active and reactive current. Subsequently, a novel digital algorithm of tanδmeasurement is presented based on orthogonal decomposition, and this algorithm has properties such as clear physical signification, simple calculation, precise and steady measurement result. At last, the proposed algorithm is simulated under such conditions as sinusoidal voltage, nonsinusoidal voltage, frequency fluctuation, sampling frequency and sampling time length in change. Comparing with harmonics analysis method, simulation results show that the maximal measurement error is reduced to 23.72 percent and 5.35 percent respectively when voltage frequency fluctuates in (50-20.5)Hz, Meanwhile, the fluctuation scope of real-time measurement value of rand is reduced 110 times when frequency is 50.5 Hz. So the proposed method can be used in rand online monitoring and offline measurement.
出处 《中国电机工程学报》 EI CSCD 北大核心 2008年第7期127-133,共7页 Proceedings of the CSEE
关键词 介质损耗因数 数字化测量 正交分解 有功电流分量 有功系数 仿真 dielectric loss factor digital measurement orthogonal decomposition active current active power oefficient simulation
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