本文選題：電容層析成像 + COMSOL　； 參考：《中國民航大學》2017年碩士論文

【摘要】：電容層析成像(Electrical Capacitance Tomography,ECT)是一項資源耗費低、快速、安全、廉價的過程層析成像技術(shù),通過對管道中不同物質(zhì)所對應介電常數(shù)的檢測,獲取管道橫截面的相分布狀況。近幾年,ECT已被廣泛應用于氣液兩相流空隙率測量及流型識別、流化床氣固兩相流濃度分布可視化、氣力輸送等多個領(lǐng)域。為了更加全面地學習掌握ECT圖像重建算法,主要做了以下幾方面的工作:1.闡述ECT技術(shù)的基本原理,對正、逆問題進行數(shù)學建模,并通過有限差分法對ECT正問題進行求解。2.深入研究目前存在的幾種傳統(tǒng)圖像重建算法,介紹幾種典型算法的成像理念,對算法求解過程進行推導與驗證,并闡述其優(yōu)缺點,利用圖像評價參數(shù)對圖像重建結(jié)果進行比較。3.針對電容層析成像系統(tǒng)圖像重建過程中Tiknonov正則化解過度光滑引起的圖像細節(jié)信息丟失問題,引入pl,2(?(27)10 p)的混合范數(shù)作為正則化算法的數(shù)據(jù)項和正則化項。該方法利用了歐氏范數(shù)2l的光滑性和分數(shù)范數(shù)pl(?(27)10 p)的稀疏性,不僅比范數(shù)2,1l具有更好的聯(lián)合稀疏性,對噪聲的抗干擾性也更強。4.針對電容層析成像圖像重建中靈敏度矩陣的病態(tài)問題以及消耗主要計算時間的奇異值分解,對部分奇異值分解算法進行改進,該算法在計算大于某一閾值的奇異值及奇異向量時,給出一種新的隱式啟動規(guī)則,提供了一種直接可以調(diào)用的功能,無需對靈敏度矩陣最優(yōu)基向量組的維度進行預先估算。最后針對雅可比部分奇異值分解算法,提出一套修正的預處理和優(yōu)化方案。5.針對電容層析成像系統(tǒng)圖像重建過程中Tiknonov正則化引起的解的過度光滑和奇異值分解算法引起的數(shù)值不穩(wěn)定,提出了一種更為廣義的正則化算法。首先利用正定矩陣對正則化目標函數(shù)的懲罰相修正,使其可以對包含非光滑性信息的圖像進行更準確重構(gòu),進一步在目標函數(shù)求解過程中引入對角權(quán)值矩陣,對基于2l范數(shù)的數(shù)據(jù)項改進。
[Abstract]:Electrical Capacitance tomography (ECT) is a low cost, fast, safe and cheap process tomography technique. The phase distribution of the cross section of the pipeline can be obtained by detecting the permittivity of different materials in the pipeline. In recent years, ECT has been widely used in voidage measurement and flow pattern identification of gas-liquid two-phase flow, visualization of gas-solid two-phase flow concentration distribution in fluidized bed, pneumatic transport and so on. In order to master the ECT image reconstruction algorithm more comprehensively, we mainly do the following work: 1. This paper expounds the basic principle of ECT technology, models the forward and inverse problems, and solves the forward problem of ECT by finite difference method. In this paper, several traditional image reconstruction algorithms are deeply studied, the imaging concepts of several typical algorithms are introduced, the algorithm solution process is deduced and verified, and its advantages and disadvantages are expounded. The image reconstruction results are compared by using image evaluation parameters. In order to solve the problem of loss of image detail information caused by excessive smoothing of Tiknonov regularization in the process of image reconstruction in electrical capacitance tomography system, the mixed norm of plan 2n / 2710 p) is introduced as the data item and regularization item of the regularization algorithm. This method takes advantage of the smoothness of Euclidean norm 2l and the sparsity of fractional norm pl(?(27)10 p. This method not only has better joint sparsity than norm 2l, but also has stronger anti-jamming to noise. Aiming at the ill-conditioned problem of sensitivity matrix and the singular value decomposition which consumes the main computing time in the reconstruction of electrical capacitance tomography image, the algorithm of partial singular value decomposition is improved. When calculating the singular value and singular vector larger than a certain threshold, the algorithm presents a new implicit start rule, which provides a directly callable function without the need to estimate the dimension of the optimal basis vector group of the sensitivity matrix in advance. Finally, for Jacobian partial singular value decomposition algorithm, a set of modified preprocessing and optimization scheme. In view of the excessive smoothness of solution caused by Tiknonov regularization and the numerical instability caused by singular value decomposition algorithm in image reconstruction of electrical capacitance tomography system, a more generalized regularization algorithm is proposed. Firstly, the penalty phase of regularized objective function is modified by positive definite matrix, which can reconstruct the image containing non-smooth information more accurately, and further introduce diagonal weight matrix in the process of solving objective function. The data item based on 2l norm is improved.
【學位授予單位】：中國民航大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41

【參考文獻】

相關(guān)期刊論文 前10條

1 鄭顧平;李強;李剛;;基于遺傳算法的奇異值分解信號去噪算法[J];計算機應用研究;2015年08期

2 LIU Chang;XU Lijun;CAO Zhang;;Measurement of nonuniform temperature distribution by combining line-of-sight TDLAS with regularization methods[J];Instrumentation;2014年03期

3 劉涵;梁莉莉;黃令帥;;基于分塊奇異值分解的兩級圖像去噪算法[J];自動化學報;2015年02期

4 梁旭;樸成日;全應栓;;基于貝葉斯融合的機載電源系統(tǒng)評估方法[J];國外電子測量技術(shù);2014年10期

5 Muhammad Mukhlisin;Marlin Ramadhan Baidillah;Mohd Raihan Taha;;Electrical capacitance volume tomography for measurement soil water infiltration in vessel experiments[J];Journal of Central South University;2014年01期

6 郭志恒;闞哲;邵富群;律德才;;一種非均勻正則化的ECT重建方法[J];儀器儀表學報;2013年12期

7 王郗雨;楊曉梅;胡學姝;;基于奇異值分解的壓縮感知核磁共振圖像重構(gòu)算法[J];計算機應用研究;2013年04期

8 趙玉磊;郭寶龍;閆允一;;電容層析成像技術(shù)的研究進展與分析[J];儀器儀表學報;2012年08期

9 陳德運;鐘陳;王莉莉;盛曉飛;于曉洋;;基于局部能量的電容層析成像圖像融合方法[J];計算機應用研究;2012年05期

10 陳琪;劉石;;介觀尺度多孔介質(zhì)燃燒室內(nèi)火焰分布的電容層析成像(英文)[J];Chinese Journal of Chemical Engineering;2012年02期

相關(guān)博士學位論文 前2條

1 李楠;相鄰電容傳感器設(shè)計及ECT技術(shù)研究[D];西安電子科技大學;2010年

2 雷兢;多相流的電容層析成像圖像重建研究[D];中國科學院研究生院（工程熱物理研究所）;2008年

，

本文編號：1794242