CAJ | 학술논문

针对电能质量暂态扰动信号时频局部化信息量较广难以简洁灵活提取有效细微特征以及匹配追踪算法计算量大的问题，提出一种应用于电能质量扰动特征参量提取及压缩重构的匹配时频原子框架及其遗传优化改进算法。在Gabor过完备时频原子库离散基础上，采用匹配追踪方法(matching pursuit，MP)对扰动信号进行时频原子自适应分解，并通过遗传算法(genetic algorithm，GA)对时频原子参量进行优化计算，从而降低匹配追踪搜索过程的复杂度，获得最佳匹配电能质量扰动信号特征的时频原子参量化解析表示以及匹配特征重压缩构波形。算例仿真表明，该框架重构信噪比高达50 dB，均方误差数量级为0.001，能量恢复系数达到0.99以上，与小波(包)相比，具有更优良的压缩重构性能及多分辨能力，遗传优化时频参量的改进算法，基本保持了 MP 优良的压缩重构性能，计算复杂度缩减率为95.8%，算法收敛性得到提高，匹配扰动信号计算效率提高80~100倍，满足电能质量扰动分析要求。
침대전능질량잠태우동신호시빈국부화신식량교엄난이간길령활제취유효세미특정이급필배추종산법계산량대적문제，제출일충응용우전능질량우동특정삼량제취급압축중구적필배시빈원자광가급기유전우화개진산법。재Gabor과완비시빈원자고리산기출상，채용필배추종방법(matching pursuit，MP)대우동신호진행시빈원자자괄응분해，병통과유전산법(genetic algorithm，GA)대시빈원자삼량진행우화계산，종이강저필배추종수색과정적복잡도，획득최가필배전능질량우동신호특정적시빈원자삼양화해석표시이급필배특정중압축구파형。산례방진표명，해광가중구신조비고체50 dB，균방오차수량급위0.001，능량회복계수체도0.99이상，여소파(포)상비，구유경우량적압축중구성능급다분변능력，유전우화시빈삼량적개진산법，기본보지료 MP 우량적압축중구성능，계산복잡도축감솔위95.8%，산법수렴성득도제고，필배우동신호계산효솔제고80~100배，만족전능질량우동분석요구。
A novel framework using Time-frequency Atom Decomposition, as well as its improved method optimized by genetic algorithm is proposed to decompose and reconstruct power quality disturbances and extract feature parameters of disturbances in this paper, In allusion to the problems that transitory power quality power quality disturbances is high in local time-frequency domain and is difficult to be extracted effective and fine features of the signals flexibly and sententiously,as well as the computation of matching pursuit is huge. Given a redundant Gabor dictionary of time-frequency atoms, we decompose a power disturbance signal into dominant atoms in the frequency-time distribution by Matching Pursuit, which are selected in order to best match the signal structure. In particular, the time-frequency atoms parameters are optimized by Genetic Algorithm to reduce the complex rate of finding the best atoms. And thus some best time-frequency atoms matching features of disturbance signals, and also its reconstruction waveform, which can be described in parametric analysis, are obtained. The simulation results show that using such a framework the signal to noise ratio (SNR) of reconstruction of matching feature of single disturbance can reach up to 50 dB, the order of magnitude of mean square error is 0.001, and energy recovery coefficient is up to 0.99. Relative to the decomposition based on wavelet package, such method is with more excellent signal reconstruction compression and multi-resolution analysis performance. Using the improved method optimized by genetic algorithm, the Computational complexity reduction rate is up to 95.8%, thus the efficiency of matched disturbance feature and convergence performance are improved further to meet the demand of power quality analysis.