基于声学层析成像的炉内温度场重建算法研究

为了获取快速准确的锅炉温度场在线监测信息,提出了一种基于声学层析成像(AT)测量的代数重建-神经网络(ART-NN)温度场重建算法,该算法结合了代数重建方法(ART)和BP神经网络方法的优势.采用该算法对多种典型的温度场模型进行数值仿真,分析了算法的重建结果和稳健性,并利用实验研究进一步评估该算法的性能.结果表明:ART-NN算法的重建质量和稳健性要优于Tikhonov正则法、Landweber迭代法和ART方法,为提高锅炉炉膛温度场重建质量提供了一种有效方法.     

GMRES算法在声学法重建三维温度场中的应用

利用声学测量技术进行锅炉炉膛温度场测量时,重建算法是实现炉膛温度场重建的关键。而在基于像素分割的重建算法中,准确、快速求解飞渡时间矩阵方程是重点及难点。对于求解大型稀疏矩阵方程问题,GMRES(广义极小残差法)效果比较好,尤其是针对大型稀疏非对称矩阵的求解问题。本研究将GMRES算法应用于锅炉炉膛三维温度场重建过程中,并利用MATLAB软件对单峰对称和单峰偏斜两种三维理想温度场模型进行了计算机仿真重建。研究表明:该算法重建精度高、速度快,可用于锅炉炉内三维温度场重建过程。     

考虑声波折射的声学锅炉温度场测量技术的研究

根据炉膛断面理想的温度分布函数,给出了二维单峰圆对称模型温度场,数值计算了声波在模型温度场中沿直线路径的传播时间,用声学CT算法进行了温度场的重建仿真。根据光学Fermat原理和数学变分方法建立的声波传播路径的数学模型,数值计算了声波在模型温度场中的折射传播路径,发现声波在非均匀温度场中不沿直线传播,其传播路径朝向温度较高的区域发生弯曲。利用得到的声波实际传播路径,用声学CT算法重建了温度场,结果表明考虑声波折射后建立的声学法二维温度场精确度得到提高。图5参7     

声学CT算法重建炉内三维温度场的仿真研究

为了实现炉内温度场的实时在线监测,提出了2种声学CT算法:代数重建法(ART)和同步迭代重建法(SIRT).采用2种CT算法分别对炉膛火焰分布的单峰模型、双峰模型和四峰模型进行了温度场重建仿真实验,并对2种算法的仿真结果进行了比较,分析了2种算法的抗噪声能力.结果表明:2种算法均可用于炉膛三维温度场重建且各有优劣,对于燃烧情况复杂的电站锅炉,抗噪声能力更强的SIRT算法具有更好的稳定性.     

声学法锅炉温度场检测技术及应用

声学法锅炉温度场检测技术是近年来发展起来的一项新技术。介绍了声学温度场检测技术的声学原理和通过测量声波传感器间的声波传播时间 ,然后利用最小二乘原理重建温度场的测量方法 ,并进行了炉膛截面二维温度场重建仿真。对声学烟温测量方法在锅炉烟温测量中的应用及存在的问题进行了分析和讨论。     

废热锅炉非对称管板的热-结构耦合有限元分析

本文采用有限元分析方法对废锅的非对称管板进行了9种工况的分析,以图示的形式给出了温度场的分布情况,并对各种工况相应路径上的应力强度进行了评定,计算结果表明在管程压力和温差的共同作用下,应力最大点出现在管箱筒体与管板连接位置,由于布管数量少,设备直径小,由非对称结构引起的管板应力和温度场的非对称分布并不明显。     

声学法重建炉内温度场的算法研究

基于声学测温的基本原理和理想状态下炉内温度场的分布规律,提出了每条声波传播路径上温度的抛物线函数,利用数值计算插值方法中的平方反比法,得出了测量平面上划分的各网格点温度值,从而实现了二维温度场的重建。基于领域经验,借助工程数学软件MATLAB,对本重建算法进行了计算机仿真,得出了二维温度场的网格立体图和等温线图。最后,将仿真出的温度场和理想温度场比较,进行误差分析,验证了本重建算法的正确性和可行性,取得了声学测温图像重建的一定进展。     

基于声学与光学相联合的温度场重建技术数值模拟研究

为了获得较为精确的炉膛燃烧二维温度场,达到实时监测炉膛内火焰温度的目的,分别利用光学法与声学法建立温度场重建模型并推导出较为简便的矩阵反演公式,并结合SVD(奇异值分解)算法对炉膛内二维温度场进行重建。数值研究表明:在测量误差均为0.05和0.1时,光学与声学测量方法分别在高温区域与低温区域有较好的重建效果,据此提出了基于层次分析法的声、光联合温度场重建技术,当采用(声、光)联合技术对炉膛单峰对称、单峰偏置和双峰对称温度场进行二维重建时,反演精度较光学法或声学法均提高0.01左右,表明了此种融合方法的可行性和准确性,对炉膛温度场反演具有重要意义。     

对称与非对称碳氢火焰温度场重建实验研究

为了测量碳氢火焰的截面温度场分布,根据火焰烟黑辐射传递特性,提出了基于火焰发射辐射能图像的温度场重建模型,使用最小二乘QR矩阵分解法（LSQR法）求解该模型。数值模拟重建了轴对称和非对称分布的两类温度场,重建结果精度较高。进而对实验室的甲烷扩散火焰截面二维温度场进行了重建,结果与已有文献相比符合较好,特别是对非对称火焰,能准确还原其温度场分布特征,实验得到了较好的结果。     

基于DenseNet与声学层析成像的温度场高分辨率重建

提出一种虚拟观测结合密集连接网络(DenseNet)的两阶段声学层析成像温度场高分辨率重建算法。以总体最小二乘为目标,采用虚拟观测法对超声飞行时间(TOF)进行重建,得到粗网格下的温度分布;然后利用搭建的DenseNet预测细化网格的温度分布信息,采用双输入模型,同时利用模块化输出方法对典型的温度场模型进行数值仿真。结果表明：该算法的重建质量和抗噪性均优于常用的虚拟观测方法、Landweber迭代法、Tikhonov算法及代数重建(ART)方法。     

On the treatment of non-optimal regularization parameter influence on temperature distribution reconstruction accuracy in participating medium

The choice of the regularization parameter plays a very important role in the inverse radiation problem of temperature distribution in participating medium and in practice the regularization parameter is not easy to determine accurately, which can directly affect the reconstruction accuracy and introduce errors into reconstruction results. This paper presents the alleviation of non-optimal regularization parameter influence on the temperature distribution reconstruction accuracy in participating medium using coupled methods, i.e., two kinds of regularization method (least square QR decomposition (LSQR) method and truncated singular value decomposition (TSVD) method) coupled with genetic algorithm (GA). The radiative heat transfer was described by the backward Monte Carlo method for its efficiency. Two kinds of temperature distributions with one peak and two peaks are considered. The results show that GA can still improve the accuracy of solutions even though the optimal regularization parameters are used in the coupled methods (LSQR-GA and TSVD-GA). GA can also reduce the temperature reconstruction errors due to the non-optimal choice of the regularization parameter and improve the accuracy of the reconstruction results in the coupled methods. Moreover, the coupled methods can even reach the same or better solutions accuracy for some samples with non-optimal regularization parameter, compared with the accuracy of solutions obtained by the single LSQR method or TSVD method with the optimal regularization parameter. This study demonstrates that the coupled method can alleviate non-optimal regularization parameter influence and obtain more accurate results for the inverse radiation problem of temperature distribution in participating medium.     

炉膛中二维温度场与辐射参数的同时重建

辐射逆问题研究受到了广泛的关注。以炉膛为研究对象,开展了二维温度场与辐射参数同时重建的研究。用CCD接收边界辐射强度图像和辐射温度图像,提出用正则化方法从辐射温度图像中重建介质温度场,从辐射强度图像中更新辐射参数,两者交替迭代,直到收敛。模拟计算表明,在测量数据中加入标准方差为0.02,0.05的正态分布的误差后,仍可以较好地重建出介质温度场与辐射参数。图4表4参13     

Inverse analysis applied to retrieval of parameters and reconstruction of temperature field in a transient conduction–radiation heat transfer problem involving mixed boundary conditions

This article deals with the application of the inverse method for simultaneous retrieval of parameters and reconstruction of the temperature field in a transient conduction–radiation problem with mixed boundary conditions. The conducting–radiating medium is absorbing, emitting and isotropically scattering. The boundaries are diffuse gray. One boundary of the planar medium is at a prescribed temperature, while the other boundary is at a prescribed heat flux. A method involving lattice Boltzmann method (LBM), the finite volume method (FVM) is used to obtain the temperature field in the mixed boundary problem which in the present work is termed as the direct method. Next, random perturbations are imposed on this exact temperature field and then simultaneous reconstruction of the same and estimation of properties are accomplished by minimizing the square of the error between the exact and guessed temperature fields. This error, that in the present work is termed as the objective function, is minimized using the genetic algorithm (GA). The impact of different genetic parameters on the accuracy of the estimation is also investigated. It is observed that subject to the proper selection of the genetic parameters, simultaneous reconstruction of the temperature field along with a reasonably good estimation of the unknown parameters can be achieved using the LBM–FVM–GA.     

A Hybrid Method for Reconstructing Temperature Distributions in a Radiant Enclosure

A hybrid method combining Tikhonov regularization and generalized singular value decomposition (TR–GSVD) was proposed to reconstruct temperature distributions in radiant enclosures. The regularization parameter, which is crucial to accurately inverse temperature distributions, could be fast updated in TR–GSVD. Numerical reconstruction of three-dimensional temperature fields in a 10 m × 10 m × 20 m furnace proved TR–GSVD possesses the same computational accuracy but higher efficiency compared with TR. Experimental reconstruction results from practical flames in the furnace also showed the regularization parameter changed significantly in some combustion conditions. It is necessary to update the regularization parameter during the reconstruction.     

Boundary Element Method（BEM） for Solving Normal or Inverse Bio—heat Transfer Problem of Biological Bodies with Complex Shape

Ｂｏｕｎｄａｒｙ　Ｅｌｅｍｅｎｔ　Ｍｅｔｈｏｄ　（ＢＥＭ）　ｆｏｒ　Ｓｏｌｖｉｎｇ　Ｎｏｒｍａｌ　ｏｒ　Ｉｎｖｅｒｓｅ　Ｂｉｏ－ｈｅａｔ　Ｔｒａｎｓｆｅｒ　Ｐｒｏｂｌｅｍ　ｏｆ　Ｂｉｏｌｏｇｉｃａｌ　Ｂｏｄｉｅｓ　ｗｉｔｈ　Ｃｏｍｐｌｅｘ　Ｓｈａｐｅ...     

Simultaneous reconstruction of temperature distribution, absorptivity of wall surface and absorption coefficient of medium in a 2-D furnace system

For a 2-D furnace system filled with a gray medium, surrounded by gray emitting/absorpting and diffusely reflecting wall surfaces, the temperature distribution is reconstructed using an improved Tikhonov regularization method with radiative energy images detected from the boundary of the furnace, uniform absorptivity of both the wall surfaces and the medium being updated from the temperature images grasped from the boundary too. These steps are taken alternately till a convergence is reached. The measurement errors with normal distribution of standard square deviation of 0.01 are taken into consideration for the radiative energy image and temperature image data. The reconstruction errors for radiative properties vary from 1.45% to 10.75%, and for the highest temperature are within 2%. Comparatively, the reconstruction result for the sharper temperature distribution is not as good as that for the smoother temperature distribution. The applicability of the proposed method may be practically valuable.     

An inverse heat transfer problem for restoring the temperature field in a polymer melt flow through a narrow channel

An important problem in polymer processing is to provide suitable thermal conditions for polymer melt flows through narrow channels during extrusion or injection. Due to various thermal effects (e.g., viscous dissipation, chemical reactions) the temperature profile of the melt could be quite sharp. In order to numerically simulate polymer flows and heat transfer through a narrow channel, the inlet boundary conditions, which are generally unknown, have to be specified. For such a creeping flow, the area where the velocity field develops is very short. In contrast, the inlet temperature profile develops quite slowly and affects the temperature field far downstream. An approach is suggested for restoring the inlet temperature profile by solving an inverse heat transfer problem using Cauchy data at the channel wall. The polymer flow is assumed to be a steady, laminar and incompressible flow of a non-Newtonian pseudo-plastic fluid, which is governed by the Navier–Stokes equations and a constitutive “power law” model for viscosity. This non-linear inverse problem is solved by a sequential approximation method combined with Tikhonov's regularization method. Notably, this approach has been found to be efficient for field observation problems, when the magnitude of non-linearity is not too large. The results of numerical simulation are presented and questions regarding accuracy are discussed.     

电站锅炉炉内三维温度场在线检测与分析

在1台670t/h电站锅炉上安装了1套三维温度场可视化监测系统,该系统由炉膛火焰图像探测器、视频分割器及工控机等组成。通过对炉膛火焰辐射图像的处理,采用正则化方法实现了炉膛内三维温度场(沿锅炉高度方向划分为12层横截面)的在线监测。检测结果表明,由于该锅炉掺烧高炉煤气。在沿炉膛高度方向上形成了两个燃烧高温区;炉内平均温度与机组负荷和主汽压力的相关性较好;通过对一次锅炉灭火事件的分析,表明该系统在燃烧诊断方面具有重要作用。     

Inverse analysis for estimating the unsteady inlet temperature distribution for two-phase laminar flow in a channel

An inverse thermal problem was considered for two-phase laminar flow in a parallel plate duct. The inlet temperature, which varies temporally as well as spatially, was estimated when measured temperatures were available at downstream of the duct. In the present study, the problem is solved through a minimization of an objective function by using two regularization methods, i.e., the iterative conjugate gradient method (CGM) and the Tikhonov regularization method (TRM). The effects of the functional form of inlet temperature profile, the number of the measurement points and the measurement errors are investigated and discussed. The computational accuracy and efficiency of these two regularization method are compared and discussed.     

Convection Coefficient Estimation by the Truncated Singular Value Decomposition Method Applied to the Associated Inverse Thermal Problem

This paper presents a regularization technique suited to the inverse problem associated with the reconstruction of the internal convection coefficient from external temperature measurements. More precisely, the error function between measured and prospective temperatures, obtained from a prospective convection coefficient, is minimized by applying the Newton method. The truncated singular value decomposition method is used to regularize the corresponding Hessian matrix. Numerical simulations were performed for three different test cases and three different randomly perturbed initial guesses in order to validate the proposed method. Results confirm that the convection coefficient can be reconstructed within reasonable precision.