CAJ | 학술논문

总体平均经验模态分解（EEMD）可以在噪声环境下对信号进行准确的分解，克服了EMD分解过程中产生频率混叠和虚假模态的缺陷。总体最小二成旋转不变技术（TLS-ESPRIT）算法本身具有很好的消噪能力，用 TLS-ESPRIT 算法可以准确地辨识出信号的参数。结合两者的优点，提出了基于EEMD和TLS-ESPRIT的谐波、间谐波检测方法，结合EEMD分解后的各阶分量的能量来确定电网中真实的谐波、间谐波分量。仿真结果验证了所提方法的可行性和有效性。
총체평균경험모태분해（EEMD）가이재조성배경하대신호진행준학적분해，극복료EMD분해과정중산생빈솔혼첩화허가모태적결함。총체최소이성선전불변기술（TLS-ESPRIT）산법본신구유흔호적소조능력，용 TLS-ESPRIT 산법가이준학지변식출신호적삼수。결합량자적우점，제출료기우EEMD화TLS-ESPRIT적해파、간해파검측방법，결합EEMD분해후적각계분량적능량래학정전망중진실적해파、간해파분량。방진결과험증료소제방법적가행성화유효성。
Ensemble empirical mode decomposition (EEMD) can accurately decompose the signal with noise. It overcomes the shortcomings of empirical mode decomposition (EMD) which can cause the frequency aliasing and false mode in decomposing the signal. TLS-ESPRIT algorithm itself has good noise cancellation capability and can accurately identify the parameters of the signal. A good method is proposed to detect harmonic and inter-harmonic through the use of the advantages of EEMD and TLS-ESPRIT. It determines the real harmonic and inter-harmonic by energy of each order component decomposed by EEMD. Simulation results show the feasibility and effectiveness of the method.