【摘要】：隨著經(jīng)濟(jì)的發(fā)展和社會(huì)的進(jìn)步，高質(zhì)量的電能成為電力系統(tǒng)和電力用戶的共同需求，這就要求更高效的電能質(zhì)量檢測與分析技術(shù)，而這又以電力數(shù)據(jù)的采集和壓縮為基礎(chǔ)。近年來，研究人員在電力數(shù)據(jù)壓縮方面進(jìn)行了各種方法的研究與嘗試。傳統(tǒng)的有損壓縮方法在電力數(shù)據(jù)量巨大的前提下或多或少會(huì)存在數(shù)據(jù)的損失，往往會(huì)丟失信號(hào)的關(guān)鍵特征；無損壓縮方法能夠保持原始信息完整，，但要求較高的硬件條件，占用更多的資源。 本文深入研究了壓縮感知理論在電能質(zhì)量數(shù)據(jù)壓縮以及重構(gòu)中的應(yīng)用，并引入傳統(tǒng)的電能質(zhì)量無損壓縮算法LZW作為對比。壓縮感知理論不依賴于Nyquist采樣定理，采樣率從信號(hào)本身的結(jié)構(gòu)和特性出發(fā)，遠(yuǎn)低于傳統(tǒng)采樣頻率，在采集端就將傳統(tǒng)的信號(hào)采集與壓縮兩個(gè)步驟合二為一，大大減小了數(shù)據(jù)量的處理。與LZW算法相對比，壓縮感知理論在壓縮比和重構(gòu)誤差兩個(gè)指標(biāo)上面都有不錯(cuò)的表現(xiàn)。 首先，本文分類介紹了數(shù)據(jù)壓縮方法的基本原理以及壓縮感知理論的研究現(xiàn)狀和發(fā)展趨勢，并且參照IEEE電能質(zhì)量有關(guān)標(biāo)準(zhǔn)以及有關(guān)國內(nèi)外文獻(xiàn)對電能質(zhì)量擾動(dòng)信號(hào)進(jìn)行了分類，構(gòu)建了電能質(zhì)量擾動(dòng)信號(hào)的數(shù)學(xué)模型。 其次，本文闡述了LZW無損壓縮算法與壓縮感知方法的基本理論，在兩種方法的理論基礎(chǔ)上分別介紹了信號(hào)壓縮與重構(gòu)的實(shí)現(xiàn)過程，并且在理論上總結(jié)了兩種方法的優(yōu)缺點(diǎn)以及應(yīng)用的必要條件。 最后，本文在電能質(zhì)量擾動(dòng)信號(hào)數(shù)學(xué)模型的基礎(chǔ)上分別對兩種算法進(jìn)行了仿真實(shí)驗(yàn)，并進(jìn)行了重構(gòu)性能分析，以壓縮效果和重構(gòu)誤差這兩個(gè)標(biāo)準(zhǔn)對兩種方法進(jìn)行了評價(jià)與比較，對壓縮感知理論未來的發(fā)展方向提出了自己的見解。
[Abstract]:With the development of economy and the progress of society, high quality electric energy becomes the common demand of power system and power users, which requires more efficient power quality detection and analysis technology, which is based on the collection and compression of power data. In recent years, researchers have studied and tried various methods in power data compression. The traditional lossy compression method can lose the data more or less under the premise of the huge power data, and often lose the key features of the signal. Lossless compression method can maintain the integrity of original information, but requires higher hardware conditions and takes up more resources. In this paper, the application of compression sensing theory in power quality data compression and reconstruction is deeply studied, and the traditional power quality lossless compression algorithm, LZW, is introduced as a comparison. Compression sensing theory does not depend on the Nyquist sampling theorem. The sampling rate is far lower than the traditional sampling frequency from the structure and characteristics of the signal itself. At the acquisition end, the two steps of traditional signal acquisition and compression are combined together. The data processing is greatly reduced. Compared with LZW algorithm, compression sensing theory has good performance on compression ratio and reconstruction error. Firstly, this paper introduces the basic principle of data compression method, the research status and development trend of compression sensing theory, and classifies the power quality disturbance signal with reference to the IEEE power quality standards and related literature at home and abroad. The mathematical model of power quality disturbance signal is constructed. Secondly, the basic theory of LZW lossless compression algorithm and compression sensing method is introduced, and the realization process of signal compression and reconstruction is introduced based on the two methods. The advantages and disadvantages of the two methods and the necessary conditions for their application are summarized theoretically. Finally, on the basis of the mathematical model of power quality disturbance signal, two algorithms are simulated, and the reconstruction performance is analyzed. The two methods are evaluated and compared according to the compression effect and the reconstruction error. The author puts forward his own opinion on the future development of the theory of compressed perception.
【學(xué)位授予單位】：燕山大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM711

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