True-temperature inversion algorithm for a multi-wavelength pyrometer based on fractional-order particle-swarm optimization

Herein,a method of true-temperature inversion for a multi-wavelength pyrometer based on fractional-order particle-swarm optimization is proposed for difficult inversion problems with unknown emissivity.Fractional-order calculus has the inherent advantage of easily jumping out of local extreme values;here,it is introduced into the particle-swarm algorithm to invert the true temperature.An improved adaptive-adjustment mechanism is applied to automatically adjust the current velocity order of the particles and update their velocity and position values,increasing the accuracy of the true temperature values.The results of simulations using the proposed algorithm were compared with three algorithms using typical emissivity models:the internal penalty function algorithm,the optimization function(fmincon)algorithm,and the conventional particle-swarm optimization algorithm.The results show that the proposed algorithm has good accuracy for true-temperature inversion.Actual experimental results from a rocket-motor plume were used to demonstrate that the true-temperature inversion results of this algorithm are in good agreement with the theoretical true-temperature values.

Adaptive Antenna Utilizing Power Inversion and Linearly Constrained Minimum Variance Algorithms

This paper presents a new algorithm based on the power inversion （PI） and the linearly constrained minimum variance （LCMV）. This algorithm is capable of adjusting the weights of the antenna array in real time to respond to and improve the global positioning system （GPS） received signals coming from the desired directions and at the same time to highly suppress the jammers coming from the other directions. The simulation is performed for fixed and moving jammers. It indicates that this structure can give deeper nulls, more than 115 dB depths for fixed jammers and more than 94 dB depths for moving jammers.

DESIGN AND IMPLEMENTATION OF DUAL-FIELD MODULAR INVERSION ALGORITHM

Modular inverse arithmetic plays an important role in elliptic curve cryptography. Based on the analysis of Montgomery modular inversion algorithm, this paper presents a new dual-field modular inversion algorithm, and a novel scalable and unified architecture for Montgomery inverse hardware in finite fields GF(p) and GF(2n) is proposed. Furthermore, this architecture based on the new modular inversion algorithm has been verified by modeling it in Verilog-HDL, and accomplished it under 0.18 μm CMOS technology. The result indicates that our work has better performance and flexibility than other works.

Crustal velocity structure of central Gansu Province from regional seismic waveform inversion using firework algorithm

The firework algorithm（FWA） is a novel swarm intelligence-based method recently proposed for the optimization of multi-parameter, nonlinear functions. Numerical waveform inversion experiments using a synthetic model show that the FWA performs well in both solution quality and efficiency. We apply the FWA in this study to crustal velocity structure inversion using regional seismic waveform data of central Gansu on the northeastern margin of the Qinghai-Tibet plateau. Seismograms recorded from the moment magnitude（MW） 5.4 Minxian earthquake enable obtaining an average crustal velocity model for this region. We initially carried out a series of FWA robustness tests in regional waveform inversion at the same earthquake and station positions across the study region,inverting two velocity structure models, with and without a low-velocity crustal layer; the accuracy of our average inversion results and their standard deviations reveal the advantages of the FWA for the inversion of regional seismic waveforms. We applied the FWA across our study area using three component waveform data recorded by nine broadband permanent seismic stations with epicentral distances ranging between 146 and 437 km. These inversion results show that the average thickness of the crust in this region is 46.75 km, while thicknesses of the sedimentary layer, and the upper, middle, and lower crust are 3.15,15.69, 13.08, and 14.83 km, respectively. Results also show that the P-wave velocities of these layers and the upper mantle are 4.47, 6.07, 6.12, 6.87, and 8.18 km/s,respectively.

Seismic fluid identification using a nonlinear elastic impedance inversion method based on a fast Markov chain Monte Carlo method

Elastic impedance inversion with high efficiency and high stability has become one of the main directions of seismic pre-stack inversion. The nonlinear elastic impedance inversion method based on a fast Markov chain Monte Carlo （MCMC） method is proposed in this paper, combining conventional MCMC method based on global optimization with a preconditioned conjugate gradient （PCG） algorithm based on local optimization, so this method does not depend strongly on the initial model. It converges to the global optimum quickly and efficiently on the condition that effi- ciency and stability of inversion are both taken into consid- eration at the same time. The test data verify the feasibility and robustness of the method, and based on this method, we extract the effective pore-fluid bulk modulus, which is applied to reservoir fluid identification and detection, and consequently, a better result has been achieved.

Nonlinear inversion of ultrasonic guided waves for in vivo evaluation of cortical bone properties

Ultrasonic guided waves(UGWs),which propagate throughout the entire thickness of cortical bone,are attractive for the early diagnosis of osteoporosis.However,this is challenging due to the impact of soft tissue and the inherent difficulties related to multiparametric inversion of cortical bone quality factors,such as cortical thickness and bulk wave velocity.Therefore,in this research,a UGW-based multi-parameter inversion algorithm is developed to predict strength-related factors.In simulation,a free plate(cortical bone)and a bilayer plate(soft tissue and cortical bone)are used to validate the proposed method.The inversed cortical thickness(CTh),longitudinal velocity(V_(L))and transverse velocity(V_(T))are in accordance with the true values.Then four bovine cortical bone plates were used in in vitro experiments.Compared with the reference values,the relative errors for cortical thickness were 3.96%,0.83%,2.87%,and 4.25%,respectively.In the in vivo measurements,UGWs are collected from the tibias of 10 volunteers.The theoretical dispersion curves depicted by the estimated parameters(V_(T),V_(L),CTh)match well with the extracted experimental ones.In comparison with dual-energy x-ray absorptiometry,our results show that the estimated transverse velocity and cortical thickness are highly sensitive to osteoporosis.Therefore,these two parameters(CTh and V_(T))of long bones have potential to be used for diagnosis of bone status in clinical applications.

An improved multi-objective optimization algorithm for solving flexible job shop scheduling problem with variable batches

In order to solve the flexible job shop scheduling problem with variable batches,we propose an improved multiobjective optimization algorithm,which combines the idea of inverse scheduling.First,a flexible job shop problem with the variable batches scheduling model is formulated.Second,we propose a batch optimization algorithm with inverse scheduling in which the batch size is adjusted by the dynamic feedback batch adjusting method.Moreover,in order to increase the diversity of the population,two methods are developed.One is the threshold to control the neighborhood updating,and the other is the dynamic clustering algorithm to update the population.Finally,a group of experiments are carried out.The results show that the improved multi-objective optimization algorithm can ensure the diversity of Pareto solutions effectively,and has effective performance in solving the flexible job shop scheduling problem with variable batches.

Performance of global look-up table strategy in digital image correlation with cubic B-spline interpolation and bicubic interpolation

Global look-up table strategy proposed recently has been proven to be an efficient method to accelerate the interpolation, which is the most time-consuming part in the iterative sub-pixel digital image correlation （DIC） algorithms. In this paper, a global look-up table strategy with cubic B-spline interpolation is developed for the DIC method based on the inverse compositional Gauss-Newton （IC-GN） algorithm. The performance of this strategy, including accuracy, precision, and computation efficiency, is evaluated through a theoretical and experimental study, using the one with widely employed bicubic interpolation as a benchmark. The global look-up table strategy with cubic B-spline interpolation improves significantly the accuracy of the IC-GN algorithm-based DIC method compared with the one using the bicubic interpolation, at a trivial price of computation efficiency.

Inverse kinematics of a heavy duty manipulator with 6-DOF based on dual quaternion

An iterative method is introduced successfully to solve the inverse kinematics of a 6-DOF manipulator of a tunnel drilling rig based on dual quaternion, which is difficult to get the solution by Denavit-Hartenberg(D-H) based methods. By the intuitive expression of dual quaternion to the orientation of rigid body, the coordinate frames assigned to each joint are established all in the same orientation, which does not need to use the D-H procedure. The compact and simple form of kinematic equations, consisting of position equations and orientation equations, is also the consequence of dual quaternion calculations. The iterative process is basically of two steps which are related to solving the position equations and orientation equations correspondingly. First, assume an initial value of the iterative variable; then, the position equations can be solved because of the reduced number of unknown variables in the position equations and the orientation equations can be solved by applying the solution from the position equations, which obtains an updated value for the iterative variable; finally, repeat the procedure by using the updated iterative variable to the position equations till the prescribed accuracy is obtained. The method proposed has a clear geometric meaning, and the algorithm is simple and direct. Simulation for 100 poses of the end frame shows that the average running time of inverse kinematics calculation for each demanded pose of end-effector is 7.2 ms on an ordinary laptop, which is good enough for practical use. The iteration counts 2-4 cycles generally, which is a quick convergence. The method proposed here has been successfully used in the project of automating a hydraulic rig.

A Time-Frequency Associated MUSIC Algorithm Research on Human Target Detection by Through-Wall Radar

In this paper,a time-frequency associated multiple signal classification(MUSIC)al-gorithm which is suitable for through-wall detection is proposed.The technology of detecting hu-man targets by through-wall radar can be used to monitor the status and the location information of human targets behind the wall.However,the detection is out of order when classical MUSIC al-gorithm is applied to estimate the direction of arrival.In order to solve the problem,a time-fre-quency associated MUSIC algorithm suitable for through-wall detection and based on S-band stepped frequency continuous wave(SFCW)radar is researched.By associating inverse fast Fouri-er transform(IFFT)algorithm with MUSIC algorithm,the power enhancement of the target sig-nal is completed according to the distance calculation results in the time domain.Then convert the signal to the frequency domain for direction of arrival(DOA)estimation.The simulations of two-dimensional human target detection in free space and the processing of measured data are com-pleted.By comparing the processing results of the two algorithms on the measured data,accuracy of DOA estimation of proposed algorithm is more than 75%,which is 50%higher than classical MUSIC algorithm.It is verified that the distance and angle of human target can be effectively de-tected via proposed algorithm.

Inverse method for the determination of elastic properties of coating layers by the surface ultrasonic waves

As the coated materials are widely applied in engineering, estimation of the elastic properties of coating layers is of great practical importance. This paper presents an inversion algorithm for determining the elastic properties of coating layers from the given velocity dispersion of surface ultrasonic waves. Based on the dispersive equation of surface waves in layered half space, an objective function dependent on coating material parameters is introduced. The density and wave velocities, which make the object function minimum, are taken as the inversion results. Inverse analyses of two parameters (longitudinal and transverse velocities) and three parameters (the density, longitudinal and transverse velocities) of the coating layer were made.

Delamination Identification for FRP Composites with Emphasis on Frequency-Based Vibration Monitoring-A Review

Fibre reinforced polymer (FRP) composite laminates are now commonly usedin many structural applications, especially in the aerospace industry, where margins ofsafety are kept low in order to minimise weight. Timely detection and assessment ofdamage (in particular delaminations) in composite laminates are therefore critical, as theycan cause loss of structural integrity affecting the safe operation of the composite structures.The current trend is towards implementation of structural health monitoring (SHM)systems which can monitor the structures in situ without down time. In this paper, first, thecurrent available SHM techniques for delamination detection in FRP composites arebriefly reviewed, including acoustic emission, fibre optic sensors, Lamb wave-,impedance- and vibration-based methods. Among different vibration-based methods,frequency monitoring is the simplest to implement, requiring only single pointmeasurement, and is relatively accurate and reliable, thus it becomes the main focus ofpresent paper. A comprehensive review of frequency-based vibration monitoring isconducted in terms of the various aspects of delamination identification in FRPs throughfrequency shifts, including review of theoretical models for free vibration of delaminatedFRP beams, survey of finite element modelling of delaminated composite structures,summary of experimental modal analyses on FRP composites with delaminations, andinverse algorithms for frequency-based delamination assessment. This paper aims to helpthe readers to get an overview of the available SHM techniques for monitoring the integrityof FRP composites, with a special emphasis on delamination assessment throughfrequency-based vibration monitoring.

Modified simulated annealing evolutionary algorithm for fully distributed fiber Bragg grating temperature sensing

In this paper, we present a simple and fast spectra inversion method to reconstruct the temperature distribution along single fiber Bragg grating （FBC） temperature sensor. This is a fully distributed sensing method based on the simulated annealing evolutionary （SAE） algorithm. Several modifications are made to improve the algorithm efficiency, including choosing the most superior chromosome, setting up the boundary of every gene according to the density of resonance peaks of the reflection spectrum, and dynamically modifying the boundary with the algorithm running. Numerical simulation results show that both the convergence rate and the fluctuation are significantly improved. A high spat-ial temperature resolution of 0.25 mm has been achieved at the time cost of 86 s.

Efficient model building in active appearance model for rotated face

This paper proposes the efficient model building in active appearance model(AAM) for the rotated face.Finding an exact region of the face is generally difficult due to different shapes and viewpoints.Unlike many papers about the fitting method of AAM,this paper treats how images are chosen for fitting of the rotated face in modelling process.To solve this problem,databases of facial rotation and expression are selected and models are built using Procrustes method and principal component analysis(PCA).These models are applied in fitting methods like basic AAM fitting,inverse compositional alignment(ICA),project-out ICA,normalization ICA,robust normalization inverse compositional algorithm(RNIC)and efficient robust normalization algorithm(ERN).RNIC and ERN can fit the rotated face in images efficiently.The efficiency of model building is checked using sequence images made by ourselves.

Efficient Generalized Inverse for Solving Simultaneous Linear Equations

Solving large scale system of Simultaneous Linear Equations (SLE) has been (and continue to be) a major challenging problem for many real-world engineering and science applications. Solving SLE with singular coefficient matrices arises from various engineering and sciences applications [1]-[6]. In this paper, efficient numerical procedures for finding the generalized (or pseudo) inverse of a general (square/rectangle, symmetrical/unsymmetrical, non-singular/singular) matrix and solving systems of Simultaneous Linear Equations (SLE) are formulated and explained. The developed procedures and its associated computer software (under MATLAB [7] computer environment) have been based on “special Cholesky factorization schemes” (for a singular matrix). Test matrices from different fields of applications have been chosen, tested and compared with other existing algorithms. The results of the numerical tests have indicated that the developed procedures are far more efficient than the existing algorithms.

Optimization of regularization parameter of inversion in particle sizing using light extinction method

In particle sizing by light extinction method, the regularization parameter plays an important role in applying regularization to find the solution to ill-posed inverse problems. We combine the generalized cross-validation （GCV） and L-curve criteria with the Twomey-NNLS algorithm in parameter optimization. Numerical simulation and experimental validation show that the resistance of the newly developed algorithms to measurement errors can be improved leading to stable inversion results for unimodal particle size distribution.

Verification of the stability criterion of inverse algorithms for layered sea bottom

In this paper, two inverse algorithms were used to infer the impedance profile of the layered bottom in a cooling-water pool. The error by two algorithms increased dramatically and leading to overflow in computation. Both inverse results were quite close to the measured data if the recorded data had been corrected by a stability criterion.

Real-Time Automatic Scaling Method of Oblique Ionogram Parameters Based on Morphological Operator and Inversion Technique

Automatic scaling ionogram can get the parameters of ionogram which are vital to ionosphere detecting. In this paper, a new method is proposed to scale F2 layer trace automatically from oblique ionogram based on morphological operator and inversion technique. This method is verified through the comparison of actual detecting data with statistical analysis. The results show that the proposed automatic scaling method has high acceptable rate and is suitable for scaling oblique ionogram with different high angle wave states. It is fast and precise to fit O-mode echoes in F2 layer without the influence from F1 layer. This method could be applied in real-time ionospheric oblique sounding research with high reliability and versatility.

Estimation of pollutant sources in multi-zone buildings through different deconvolution algorithms

Effective identification of pollution sources is particularly important for indoor air quality.Accurate estimation of source strength is the basis for source effective identification.This paper proposes an optimization method for the deconvolution process in the source strength inverse calculation.In the scheme,the concept of time resolution was defined,and combined with different filtering positions and filtering algorithms.The measures to reduce effects of measurement noise were quantitatively analyzed.Additionally,the performances of nine deconvolution inverse algorithms under experimental and simulated conditions were evaluated and scored.The hybrid algorithms were proposed and compared with single algorithms including Tikhonov regularization and iterative methods.Results showed that for the filtering position and algorithm,Butterworth filtering performed better,and different filtering positions had little effect on the inverse calculation.For the calculation time step,the optimal Tr(time resolution)was 0.667%and 1.33%in the simulation and experiment,respectively.The hybrid algorithms were found to not perform better than the single algorithms,and the SART(simultaneous algebraic reconstruction technique)algorithm from CAT(computer assisted tomography)yielded better performances in the accuracy and stability of source strength identification.The relative errors of the inverse calculation for source strength were typically below 25%using the optimization scheme.

一种用于位移场分析的应变模式频域数字图像相关方法

本文提出了一种在频域中考虑应变对位移影响的频域数字图像相关方法.研究并建立了一个在频域中评价参考图像子区与目标图像子区之间匹配的评价标准,并在此基础之上,提出了可用于位移和应变计算的频域迭代算法,其中,Hessian矩阵在迭代过程中保持不变.在Hessian矩阵的形成过程中,参考图像子区中灰度的梯度可以通过快速傅里叶变换进行计算,具有很高的计算效率和精度.同时,一种离散傅里叶变换重采样技术被用于代替传统的插值方法对变形图像子区中亚像素位置的灰度进行重建和更新.为了验证所提方法的有效性和准确性,使用了国际DIC挑战委员会(IDCC)提供的系列图像(2D-Challenge 1.0,样本6)进行位移分析.分析的误差结果表明,在子区大小为41×41像素的条件下,对变形为50%的模拟实验进行了计算,位移分析结果的精度约为0.0032像素(最大绝对值误差),在精度上优于已发表的文献.最后,对硅橡胶试件进行了14.85%的单轴拉伸试验,通过相关系数分布检验了本文所提方法在实际应用中的有效性,并给出了分析的位移和应变分布.