發(fā)布時間：2018-02-09 14:27

  本文關(guān)鍵詞： 經(jīng)驗?zāi)B(tài)分解(EMD) 頻譜質(zhì)心 奇異值分解(SVD) 安全防范系統(tǒng) 信號重構(gòu) 頻譜分析　出處：《光電子·激光》2017年08期 　論文類型：期刊論文

【摘要】：在輸油管道的安全防范系統(tǒng)應(yīng)用背景下,針對傳統(tǒng)方法診斷光纖采集到的入侵信號準(zhǔn)確率不高的問題,提出一種基于經(jīng)驗?zāi)B(tài)分解(EMD)算法和頻譜質(zhì)心(SC)的入侵信號診斷方法。首先將采集到的原始入侵信號通過EMD進(jìn)行分解,分離含噪最多的特征模態(tài)函數(shù)(IMF)分量,再組合剩余的IMF分量形成重構(gòu)信號,對重構(gòu)信號進(jìn)行希爾伯特變換(HT)得到希爾伯特譜,計算它的SC,進(jìn)一步識別入侵信號和干擾信號。通過對油管振動信號進(jìn)行實驗,本文方法對于每種入侵信號和干擾信號的診斷準(zhǔn)確率均在90.00%以上,整體的診斷準(zhǔn)確率達(dá)到97.17%。對于該組油管振動信號,同時運(yùn)用奇異值分解(SVD)法進(jìn)行診斷并將其結(jié)果與本文方法的診斷結(jié)果進(jìn)行對比,整體上本文方法的診斷準(zhǔn)確率比SVD法高出19.00%。仿真實驗結(jié)果表明,本文方法能有效診斷入侵信號,并且診斷效果明顯優(yōu)于奇異值分解法。
[Abstract]:Under the background of the application of oil pipeline security prevention system, aiming at the problem that the traditional method of diagnosing the intrusion signal acquired by optical fiber is not accurate enough, An intrusion signal diagnosis method based on empirical mode decomposition (EMD) algorithm and spectral centroid (SCC) is proposed. Firstly, the original intrusion signal is decomposed by EMD to separate the most noise-containing characteristic mode function (IMF) component. The reconstructed signal is formed by combining the remaining IMF components, and the Hilbert spectrum is obtained by Hilbert transform. The Hilbert spectrum is calculated, and the intrusion signal and the interference signal are further recognized. The experiment is carried out on the vibration signal of the tubing. The diagnostic accuracy of this method for each intrusion signal and interference signal is more than 90.00%, and the overall diagnostic accuracy is 97.17. At the same time, the singular value decomposition (SVD) method is used to diagnose and compare the results with the results of this method. The diagnostic accuracy of this method is 19.00 higher than that of SVD method. The simulation results show that the proposed method can effectively diagnose the intrusion signal. And the diagnostic effect is obviously better than the singular value decomposition method.
【作者單位】： 浙江理工大學(xué)機(jī)械與自動控制學(xué)院;
【基金】：國家自然科學(xué)基金(61503341)資助項目
【分類號】：TE973

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本文編號：1498138