本文關鍵詞： 泄漏孔徑識別 總體局域均值分解(ELMD) KL散度 稀疏表示分類器 過完備字典　出處：《中國機械工程》2017年10期 　論文類型：期刊論文

【摘要】：針對天然氣管道泄漏受孔徑、傳感器距離、管道內(nèi)壓力等多種因素影響,特征提取及識別算法較為復雜的問題,提出了基于總體局域均值分解-相對熵的特征提取算法并結合稀疏表示分類的泄漏孔徑識別新方法。該方法采用總體局域均值分解方法對泄漏信號進行自適應分解,得到不同孔徑泄漏信號的特征信息,并根據(jù)KL散度選擇包含主要泄漏信息的PF分量,在此基礎上提取多種時頻特征參數(shù),獲取全面準確表征泄漏信號的特征向量;針對小樣本復雜信號的分類,提出稀疏表示分類器實現(xiàn)泄漏孔徑準確分類。該分類器采用過完備字典求得測試信號的最稀疏解,并以此解作為測試信號的稀疏重構系數(shù),以獲取測試信號在不同類別中的重構信號,最終通過判斷測試信號與重構信號的殘差值大小完成泄漏孔徑分類。實驗結果表明,所提出的算法比傳統(tǒng)的SVM及BP分類算法識別準確率高。
[Abstract]:The gas pipeline leakage is affected by many factors, such as aperture, sensor distance, pipeline pressure and so on, so the algorithm of feature extraction and identification is more complex. In this paper, a new method of leak aperture identification based on local mean decomposition and relative entropy is proposed, which combines with sparse representation classification. The method uses the local mean decomposition method to self-adaptively divide the leakage signal. Solution. The characteristic information of different aperture leakage signal is obtained, and the PF component which contains the main leakage information is selected according to the KL divergence. On this basis, a variety of time-frequency characteristic parameters are extracted. Obtain the characteristic vector which can represent the leakage signal completely and accurately; For the classification of small sample complex signals, a sparse representation classifier is proposed to realize accurate classification of leak aperture, which uses an overcomplete dictionary to obtain the most sparse solution of the test signal. The solution is used as the sparse reconstruction coefficient of the test signal to obtain the reconstructed signal of the test signal in different classes. Finally, the leak aperture classification is completed by judging the residual value of the test signal and the reconstructed signal. The experimental results show that the proposed algorithm is more accurate than the traditional SVM and BP classification algorithms.
【作者單位】： 燕山大學信息科學與工程學院;燕山大學河北省測試計量技術及儀器重點實驗室;中國石油天然氣管道通信電力工程有限公司;
【基金】：國家自然科學基金資助項目(51204145) 河北省自然科學基金資助項目(E2013203300,E2016203223)
【分類號】：TE973.6
【正文快照】： 0引言天然氣管道泄漏會造成嚴重后果,微小泄漏是燃氣管道發(fā)生燃爆的主要誘因,泄漏孔徑的不同直接與危險程度相關,當傳感系統(tǒng)檢測到管道發(fā)生泄漏后,盡快估計出不同泄漏孔徑,是快速制定管道搶修計劃、評估泄漏尺度的重要基礎,對燃氣管道的泄漏及識別具有重要意義。天然氣管道泄

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