本文選題：變流器 + 壓縮感知�。� 參考：《蘭州交通大學(xué)》2017年碩士論文

【摘要】：目前,風(fēng)電變流器檢測(cè)信號(hào)處理方法均建立在奈奎斯特采樣定理的基礎(chǔ)上,這將產(chǎn)生巨大的采樣數(shù)據(jù),使得數(shù)據(jù)的存儲(chǔ)或者傳輸引起“空間災(zāi)難性”后果。壓縮感知(compressed sensing,CS)理論以遠(yuǎn)低于奈奎斯特采樣頻率采集信號(hào),且信號(hào)的采樣和壓縮同時(shí)進(jìn)行,以信號(hào)的非自適應(yīng)投影來保留原始信號(hào)的關(guān)鍵信息,通過數(shù)學(xué)方法來準(zhǔn)確重構(gòu)原始信號(hào)。針對(duì)以上研究背景,本文緊緊圍繞壓縮感知理論對(duì)風(fēng)電變流器檢測(cè)信號(hào)進(jìn)行處理,該方法既具有壓縮感知的壓縮采樣特性,又具有準(zhǔn)確恢復(fù)重構(gòu)的能力,因此具有重要的研究?jī)r(jià)值。首先,研究了壓縮感知理論,搭建了變流器仿真模型,分析了變流器原始電壓檢測(cè)信號(hào)的稀疏性。由稀疏性信息,研究電壓信號(hào)稀疏變換基與投影矩陣之間的關(guān)系,由優(yōu)化投影理論,降低互相關(guān)性來優(yōu)化投影矩陣,該方法使得投影矩陣的壓縮性能提升。其次,為了解決直接利用CS理論對(duì)變流器輸出端三相電壓檢測(cè)數(shù)據(jù)存儲(chǔ)空間浪費(fèi)以及重構(gòu)性能差等問題,利用三相電壓的關(guān)系,研究了基于坐標(biāo)變換的三相電壓檢測(cè)信號(hào)CS處理方法。先對(duì)輸出端三相電壓檢測(cè)數(shù)據(jù)采用坐標(biāo)變換后轉(zhuǎn)化為一維信號(hào),再利用CS理論對(duì)其進(jìn)行壓縮重構(gòu),重構(gòu)的信號(hào)將其轉(zhuǎn)化為兩相信號(hào)并作坐標(biāo)反變換,即得到重構(gòu)的三相電壓信號(hào)。實(shí)驗(yàn)表明,該方法處理變流器電壓檢測(cè)信號(hào)時(shí),可有效壓縮原始三相電壓數(shù)據(jù),使得運(yùn)行時(shí)間更低、重構(gòu)誤差更小,且節(jié)約了測(cè)量數(shù)據(jù)的存儲(chǔ)空間。然后,對(duì)比研究了五種典型的貪婪重構(gòu)算法。針對(duì)原始信號(hào)重構(gòu)性能差的問題,研究了基于廣義Jaccard系數(shù)的廣義正交匹配追蹤算法,即就是利用廣義Jaccard系數(shù)相似性準(zhǔn)則去替換內(nèi)積相似性準(zhǔn)則來對(duì)支撐集進(jìn)行優(yōu)化。在相同條件下與其它的重構(gòu)算法相比較,改進(jìn)的算法所具有的重構(gòu)性能更優(yōu)。最后,考慮到電壓檢測(cè)信號(hào)所蘊(yùn)含的深層信息等問題,研究了基于本征時(shí)間尺度分解(intrinsic time-scale decomposition,ITD)與改進(jìn)內(nèi)積的壓縮感知重構(gòu)算法相結(jié)合的風(fēng)電變流器電壓信號(hào)重建方法。基于ITD把變流器電壓檢測(cè)信號(hào)處理成互不影響的合理旋轉(zhuǎn)分量和余量,進(jìn)而利用基于廣義Jaccard系數(shù)的廣義正交匹配追蹤算法對(duì)每個(gè)分量進(jìn)行處理,重構(gòu)合并得到變流器原始電壓檢測(cè)信號(hào)。該方法降低了計(jì)算復(fù)雜度和重構(gòu)誤差。
[Abstract]:At present, the detection signal processing methods of wind power converter are based on Nyquist sampling theorem, which will produce huge sampling data, which makes the storage or transmission of data cause "space catastrophic" consequences. Compressed sensing theory collects signals at a much lower sampling frequency than Nyquist, and the sampling and compression of signals are performed simultaneously. The key information of the original signal is preserved by the non-adaptive projection of the signal. The original signal is reconstructed by mathematical method. In view of the above research background, this paper focuses on the compression sensing theory to process the detection signal of wind power converter. This method not only has the compression sensing characteristic of compression sampling, but also has the ability of accurate recovery and reconstruction. Therefore, it has important research value. Firstly, the compression sensing theory is studied, the converter simulation model is built, and the sparsity of the original voltage detection signal is analyzed. Based on the sparse information, the relationship between the sparse transformation basis of voltage signal and the projection matrix is studied. The projection matrix is optimized by optimizing the projection theory and reducing the mutual correlation. The compression performance of the projection matrix is improved by this method. Secondly, in order to solve the problem of waste of data storage space and poor reconfiguration performance of three-phase voltage detection of converter output by using CS theory directly, the relationship of three-phase voltage is used. The CS processing method of three-phase voltage detection signal based on coordinate transformation is studied. The three-phase voltage detection data at the output end are transformed into one-dimensional signal by coordinate transformation, then compressed and reconstructed by CS theory. The reconstructed signal transforms the signal into two-phase signal and makes coordinate inverse transformation. The reconstructed three-phase voltage signal is obtained. The experimental results show that this method can effectively compress the original three-phase voltage data, make the running time lower, the reconstruction error smaller, and save the storage space of the measurement data. Then, five typical greedy reconstruction algorithms are compared. Aiming at the poor performance of the original signal reconstruction, the generalized orthogonal matching tracking algorithm based on generalized Jaccard coefficients is studied, that is, the generalized Jaccard coefficient similarity criterion is used to replace the inner product similarity criterion to optimize the support set. Compared with other reconstruction algorithms under the same conditions, the improved algorithm has better reconfiguration performance. Finally, considering the deep information contained in the voltage detection signal, the voltage signal reconstruction method of wind power converter based on intrinsic time scale decomposition intrinsics time-scale decompositionITD and improved internal product compression sensing reconstruction algorithm is studied. Based on ITD, the voltage detection signal of converter is processed into reasonable rotation component and residual, and then each component is processed by generalized orthogonal matching tracing algorithm based on generalized Jaccard coefficient. The original voltage detection signal of the converter is obtained by reconstructing and merging. This method reduces computational complexity and reconstruction error.
【學(xué)位授予單位】：蘭州交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM614;TM46

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

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2 張曉東;董唯光;郭俊鋒;湯e，

本文編號(hào)：1796538