【摘要】：目前,高壓直流電纜工程空前開展,但電纜及其附件帶電檢測(cè)和模式識(shí)別技術(shù)研究尚處于初級(jí)階段。使用交聯(lián)聚乙烯電纜設(shè)計(jì)制作了絕緣內(nèi)部氣隙、絕緣表面劃傷、外半導(dǎo)電層爬電、高壓端毛刺電暈4種絕緣缺陷模型。提出將基于壓縮感知理論的稀疏表示分類技術(shù)應(yīng)用于直流下局部放電信號(hào)模式識(shí)別。使用放電重復(fù)率圖譜作為分類樣本,將訓(xùn)練樣本集組成過(guò)完備字典,利用測(cè)試樣本在其上投影的稀疏性,通過(guò)1范數(shù)最小進(jìn)行稀疏表示從而實(shí)現(xiàn)分類。在不同樣本維數(shù)下,采用同倫、非負(fù)最小二乘以及正交匹配追蹤3種算法解決1范數(shù)最小問(wèn)題。結(jié)果表明:較低維度(10×10維、15×15維)時(shí),3種方法識(shí)別正確率近似,隨著維度增大,同倫法識(shí)別率明顯優(yōu)于另外兩者,20×20維時(shí)最大識(shí)別率可達(dá)92.31%,非負(fù)最小二乘法識(shí)別率稍次,但運(yùn)算時(shí)間過(guò)長(zhǎng)。綜合比較,同倫法具有識(shí)別率高和運(yùn)算速度快的優(yōu)點(diǎn),取20×20維即可滿足識(shí)別精度和計(jì)算效率的要求。
[Abstract]:At present, HVDC cable engineering has been carried out unprecedented, but the research on live detection and pattern recognition technology of cable and its accessories is still in its infancy. Four kinds of insulation defect models, such as air gap inside insulation, scratch on insulation surface, creeping of outer semiconductive layer and burr corona at high voltage end, were designed and manufactured by using cross-linked polyethylene cable. A sparse representation classification technique based on compression sensing theory is proposed for PD signal pattern recognition under DC conditions. The discharge repetition rate graph is used as the classification sample and the training sample set is formed into an over-complete dictionary. The sparsity of the projection of the test sample on it is used to realize the classification by the sparse representation of the minimum norm of 1 norm. Under different sample dimensions, homotopy, non-negative least squares and orthogonal matching tracking algorithms are used to solve the 1-norm minimum problem. The results show that at the lower dimension (10 脳 10 dimension, 15 脳 15 dimension), the recognition accuracy of the three methods is approximate. With the dimension increasing, the homotopy recognition rate is obviously better than the other two, and the maximum recognition rate can reach 92.31% at 20 脳 20 dimension, and the recognition rate of the homotopy method is better than that of the other two methods. The recognition rate of non-negative least square method is a little lower, but the operation time is too long. Comprehensive comparison shows that homotopy method has the advantages of high recognition rate and fast operation speed, and 20 脳 20 dimension can meet the requirements of recognition precision and calculation efficiency.
【作者單位】： 上海交通大學(xué)電氣工程系;國(guó)網(wǎng)浙江省電力公司舟山供電公司;
【基金】：國(guó)家重點(diǎn)基礎(chǔ)研究發(fā)展計(jì)劃(973計(jì)劃)(2014CB239506) 國(guó)家電網(wǎng)公司科技項(xiàng)目(52110115007J)~~
【分類號(hào)】：TM75

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相關(guān)期刊論文 前7條

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本文編號(hào)：2446527