CAJ | 학술논문

电网基波是电能计量和电能质量评估的重要指标，提出了基于前馈神经网络的电网基波频率和幅值的高精度检测方法。根据数学推导得出：正弦信号过零点与其两侧对称两点的连线与时间轴交点的时间差，同频率满足单调关系，但并非严格的线性关系，而且与幅值无关，据此用前馈神经网络建立该时间差与频率的映射关系。Matlab仿真表明，提出的算法对频率的检测精度达到10^-4级，幅值的检测精度高达10^-5级，远远高于快速傅里叶变换和Harming窗的插值算法；随机噪声和谐波对前馈神经网络测量精度的影响很小，该算法具有较强的抗干扰能力。
전망기파시전능계량화전능질량평고적중요지표，제출료기우전궤신경망락적전망기파빈솔화폭치적고정도검측방법。근거수학추도득출：정현신호과영점여기량측대칭량점적련선여시간축교점적시간차，동빈솔만족단조관계，단병비엄격적선성관계，이차여폭치무관，거차용전궤신경망락건립해시간차여빈솔적영사관계。Matlab방진표명，제출적산법대빈솔적검측정도체도10^-4급，폭치적검측정도고체10^-5급，원원고우쾌속부리협변환화Harming창적삽치산법；수궤조성화해파대전궤신경망락측량정도적영향흔소，해산법구유교강적항간우능력。
Fundamental of power grid is an important index for electric energy metering and power quality evaluation. A high-precision detection approach, which is based on back propagation neural network （BPNN）, for the frequency and amplitude of power grid fundamental is proposed. It is derived mathematically that the relationship of the time difference, which is between zero-crossing point of sinusoidal signal and the intersection point of time axis and the line connecting two symmetric points on signal curve at both sides of the zero-crossing point, to signal frequency is not strictly linear but monotonous, and the relationship is independent of the amplitude of the signal. Accordingly, the mapping relation between the time difference and fundamental frequency is built by BPNN. Results of simulation by Matlab show that using the proposed algorithm the detection accuracy of fundamental frequency is 10-4 and the detection accuracy of fundamental amplitude is as high as 10-5, and these detection results are sharply higher than those by interpolation algorithms based on fast Fourier transform （FFT） and Hamming window; random noise and harmonics slightly influence the measuring accuracy by BPNN, so the proposed algorithm possesses strong anti-interference capability.