A comparison of least squares and maximum likelihood methods using sine fitting in ADC testing

ADC test methods require the best possible reconstruction of the input signal of the ADC under test from the acquired, therefore erroneous, ADC output data. The commonly used least squares (LS) fit and the recently introduced maximum likelihood (ML) estimation are competing methods. This paper presents a simulation-based comparative study of these estimation methods with the goal to investigate the behavior of both methods and to determine their limits. Two alternative algorithms for the calculation of the maximum likelihood fit are considered (gradient-based minimization and differential evolution). The main finding is that while for low-INL (linear) ADCs the two methods (LS and ML) give similar results, for practical (almost always nonlinear) ADCs ML is definitely better.     

Parameter estimation for a dual-rate system with time delay

This paper investigates the parameter estimation problem of the dual-rate system with time delay. The slow-rate model of the dual-rate system with time delay is derived by using the discretization technique. The parameters and states of the system are simultaneously estimated. The states are estimated by using the Kalman filter, and the parameters are estimated based on the stochastic gradient algorithm or the recursive least squares algorithm. When concerning state estimate of the dual-rate system with time delay, the state augmentation method is employed with lower computational load than that of the conventional one. Simulation examples and an experimental study are given to illustrate the proposed algorithm.     

线阵CCD图像两种直线拟合边缘检测方法比较研究

对线阵CCD图像边缘检测的直接直线拟合法和基于梯度算子直线拟合法进行了比较研究。利用线阵CCD对线材目标进行宽度测量,并分别用两种方法对采集目标图像进行边缘位置检测。经检测得到,直接直线拟合法和基于梯度算子直线拟合法的检测精度分别为0.579%和0.039%,标准差分别为0.037mm和0.169mm。结果表明,直接直线拟合法精度较低,但稳定性较好;基于梯度算子直线拟合法精度较高,但结果容易受到随机噪声的影响。     

地下管道泄漏检测定位中的时延估计方法

本文将一种新的自适应无偏时延估计方法用于地下管道的泄漏检测和漏点定位，避免了经典自适应时延估计算法-LMS算法在噪声环境下可能产生有偏时延估计的不足。文章为该方法建立了新的自适应准则，分析了由该准则得到的最优解，并提出相应的算法来实现最优解的搜索，也详细的推导了算法的收敛条件。实验表明，该方法能够有效地消除不相关噪声的干扰，使得估计性能得到显著的改善。     

Reset observers alleviating the peaking and the robustness tradeoffs: A case study on force estimation in teleoperation

The peaking phenomenon is an undesirable effect appearing in observers and destroying controller performance. Several solutions have been proposed to mitigate peaking in state estimation. The literature shows that reset or impulsive observers are superior to linear (Luenberger) observers. However, the comparisons are based on particular choices of linear observers. This paper investigates this issue. First, comparative frameworks are proposed based on two traded-off performance indices: ensemble maximum-peak versus ensemble settling time for nominal conditions, and ensemble settling time versus size of the error asymptotic invariant set for quadratically bounded uncertain plants. Next, performance limitations of linear observers are represented by Pareto-optimal boundaries. In this way, not previously considered in the literature as far as known, the superiority of the chosen reset observer is more rigorously assessed. The framework is finally applied to force estimation in haptic teleoperation.     

A fast iterative recursive least squares algorithm for Wiener model identification of highly nonlinear systems

In this paper, an online identification algorithm is presented for nonlinear systems in the presence of output colored noise. The proposed method is based on extended recursive least squares (ERLS) algorithm, where the identified system is in polynomial Wiener form. To this end, an unknown intermediate signal is estimated by using an inner iterative algorithm. The iterative recursive algorithm adaptively modifies the vector of parameters of the presented Wiener model when the system parameters vary. In addition, to increase the robustness of the proposed method against variations, a robust RLS algorithm is applied to the model. Simulation results are provided to show the effectiveness of the proposed approach. Results confirm that the proposed method has fast convergence rate with robust characteristics, which increases the efficiency of the proposed model and identification approach. For instance, the FIT criterion will be achieved 92% in CSTR process where about 400 data is used.     

Bearing degradation process prediction based on the PCA and optimized LS-SVM model

Bearing degradation process prediction is extremely important in industry. This paper proposed a new method to achieve bearing degradation prediction based on principal component analysis (PCA) and optimized LS-SVM method. Firstly, the time domain, frequency domain, time–frequency domain features extraction methods are employed to extract the original features from the mass vibration signals. However, the extracted original features still with high dimensional and include superfluous information, the multi-features fusion technique PCA is used to merge the original features and reduce the dimension, the typical sensitive features are extracted. Then, based on the extracted features, the LS-SVM model is constructed and trained for bearing degradation process prediction. The pseudo nearest neighbor point method is used to determine the input number of the model. The particle swarm optimization (PSO) is used to selected the LS-SVM parameters. An accelerated bearing run-to-failure experiment was carried out, the results proved the effectiveness of the methodology.     

高速傅里叶红外光谱仪TurboFT的控制及最佳测量温度方法研究

本文介绍了美国D＆P公司生产的高速傅里叶红外光谱仪TurboFT,对该仪器的控制软件进行了二次开发,使其拥有了仪器参数设置,采集光谱,黑体定标等功能。并利用其自带黑体进行多组不同温度下的全波段采样,经过最小二乘拟合法计算出各波段的温度与光谱值的响应函数,利用原光谱数据计算出理论温度值,并与实际温度值进行比较,筛选出均方差最小的前二十组数据,经过统计,总结出在不同光谱叠加数下,温度测试光谱最佳曲线拟合的波段范围,为今后使用该仪器进行物体表面温度测量提供了最佳测量依据。并利用所得温度曲线进行了四组对不同岩石的表面温度测量实验,验证了该方法的可行性。这项研究完成为今后在使用该仪器进行矿物分析的过程中,增添了物体表面温度预测的辅助功能。     

Performance evaluation of outlier detection methods in GNSS vector networks using 1D and 3D component analysis

In most surveying studies, the computation of reference point coordinates in three-dimensional (3D) space has become inevitable with the extensive use of the Global Positioning System (GPS). Such computations are particularly required in the establishment and densification of 3D geodetic networks. In contrast to the classical measurements, GPS vector measurements, resulting from the processing of code and phase observations, are physically correlated. Therefore, in the analysis of observations components of GPS vectors can be considered either individually (i.e. 1D) or a whole (i.e. 3D). In this study, this consideration is applied for outlier detection process in a simulated GPS vector network and the results are compared with the outlier detection method considering each vector component individually. Results showed that using 3D components for outlier search was more effective when the gross error exists in all components of the baseline whereas the outlier search for 1D component was best conducted when an outlier exists in a component. Findings in this study clearly indicated that both methods should be applied to data sets to detect the outliers so as to ensure the elimination of outliers in the network.     

A consensus-based multi-agent approach for estimation in robust fault detection

This paper is devoted to distributed estimation in robust fault detection for sensor networks with networked-induced delays and packet dropouts by using a consensus-based multi-agent approach. Utilizing the information interaction and coordination among the neighboring networks based on multi-agent theory, we design novel and multiple agent-based robust fault detection filters (RFDFs) subject to only partial estimated and measured information. Asymptotically stable sufficient conditions for the innovative constructed filters are derived in the form of linear matrix inequality (LMI) and the threshold fit for each agent-based RFDF is determined. An illustrative example is given to demonstrate the effectiveness of the consensus-based multi-agent approach for the estimation in robust fault detection.     

基于粒子群优化算法的直线拟合及应用

将粒子群优化算法和传统最小二乘法相结合,采用残差平方和准则、绝对残差绝对值和准则、相对残差绝对值和准则建立了一种基于粒子群优化算法的直线拟合方法,获得了比传统最小二乘法拟合要好得多的估计结果,实验证明了该方法的有效性及高精度性。     

基于共面直线迭代加权最小二乘的相机位姿估计

针对相机内参数已标定和未标定情况下的相机位姿求解,提出了基于共面直线迭代加权最小二乘的相机位姿估计算法。推导了关于相机焦距和位姿参数的线性方程,通过4条以上共面直线实现了相机位姿参数的线性解算;对参数线性解进行迭代加权最小二乘优化,得到更高精度的参数估计值和直线权值;最后,利用直线权值和欧式变换的保距性实现相机焦距的解算,得到了相机焦距和位姿参数的估计值。仿真实验表明:提出的算法在相机已标定,直线数为20,像点噪声方差为5pixel的情况下,角度误差小于0.2°,相对平移向量误差小于0.5%,耗时大约为1ms。真实数据实验表明,提出的算法可以获得与棋盘标定结果相近的精度。与现有算法相比,提出的算法抗噪性更好,精度更高,能够实现基于单幅图像的未标定相机的位姿估计。     

Robust state estimation for a class of uncertain nonlinear systems: Comparison of two approaches

In this paper, two approaches for robust state estimation of a class of Lipschitz nonlinear systems are proposed. First, a novel Unknown Input Observer (UIO) is designed without observer matching condition satisfaction. Then, an $H_{\infty }$ observer for approximate disturbance decoupling is proposed. Sufficient conditions for the existence of both proposed observers are derived based on a Lyapunov function. The achieved conditions are formulated in terms of a set of linear matrix inequalities (LMIs) and optimal gain matrices are obtained. The minimum values of the disturbance attenuation levels for both methods are obtained through solving optimization problems. Finally, the proposed approaches are compared by simulation studies of an automated highway system.     

单矢量水听器的几种DOA估计方法

针对单矢量水听器,将旋转不变技术(estimation of signal parameters via rotational invariance techniques,ESPRIT)等参数估计算法用于直方图统计,并提出了基于单矢量水听器的多重信号分类(multiple signal classification,MUSIC)算法,推导出波束形成的功率谱公式和半功率波束宽度公式以及不同声压振速组合情形下定向性能的理论下界,同时也对其他波达方向(direc-tion of arrival,DOA)估计方法进行了总结。理论分析和实验结果表明:ESPRIT等用于直方图统计后能够获取更为全面准确的目标信息;MUSIC算法可获得比最小方差无畸变响应(minimum variance distortionless response,MVDR)更高的分辨率,而且同样满足实时处理要求;MVDR的半功率波束宽度与信噪比大致呈现反比例关系,而常规波束形成(conventional beam-forming,CBF)的半功率波束宽度收敛于131.06°,两者都只与信噪比有关;声能流法等适用于较高信噪比情形,而波束形成和子空间方法的定向精度在较低信噪比情形下仍能接近理论下界,尤其是波束形成具有良好的宽容性;功率谱估计的3种算法具有相同的估计误差边界;各定向算法的时间花销都较小,均可应用于实时系统。     

Nested DE based parameter estimation for multiple vortex ring microburst model

Modelling of microburst is significant for flight simulations. The most widely used model of microburst is the one based on the principle of multiple vortex ring. The characteristics of the microburst are directly determined by the parameters of the model. The conventional method to fix the parameters of multiple vortex ring microburst model is using experiential formula, which is not flexible enough. In this paper, we treat the parameters estimation of multiple vortex ring model as an optimization problem, and introduce the differential evolution algorithm to solve it. In the process of estimating the parameters by the maximum wind velocity, there are two interrelated optimization processes. Therefore, we improved the standard differential evolution algorithm in this paper. A nested differential evolution algorithm is proposed to accomplish the two optimization process, intermediate optimization and objective optimization. The numerical experiments show that this method can flexibly generate microburst with any maximum wind velocity, and the error meet the requirement set by the user.     

基于多直线对应和加权最小二乘的位姿估计

为了求解复杂环境下目标的位姿,提出了基于多直线对应的加权最小二乘位姿估计算法。首先对模型直线进行等间隔采样,并沿采样点投影法线方向搜索图像点对应;然后利用图像点对应局部和全局特性对样本点进行加权;最后通过优化法向距离实现目标位姿的优化求解。为了解决模型-图像对应错误引起的优化失败问题,算法在模型-图像点匹配阶段为每个采样点保留多个图像点对应,通过随机Hough变换(RHT)算法将图像点对应约束在直线上,并为每条模型直线保留多图像直线对应。在对样本点进行加权时,综合考虑了样本点自身的属性和样本点同周围点的关系,有效提高了算法对纹理,背景,噪声等的鲁棒性。实验结果表明:提出的方法能够实现复杂环境下目标位姿的优化求解,其在x方向、y方向和z方向的角度估计误差分别优于0.4,0.3和0.1°;在垂直光轴方向和沿光轴方向的相对位置误差则分别优于0.03%和0.1%。相比单假设方法,提出的方法能够更有效地克服复杂背景干扰,实现特殊视图目标位姿的稳定估计。     

Force estimation and failure detection based on disturbance observer for an ear surgical device

The disturbance observer is one of the useful tools for estimating the contact force between the subject body and the environment in robotic and mechatronic systems. This paper introduced a novel automatic office-based ear surgical device for the treatment of Otitis Media with Effusion (OME) under the guidance of force sensing information. Since the force sensing information must be reliable so as to ensure the safety of the device, a contact force estimation method based on the disturbance observer is proposed. The system model is built and a control strategy is proposed and developed. In the control strategy, a composite motion controller for an ultrasonic motor (USM) stage is presented, and then the design and the stability analysis of an advanced disturbance observer is given. Furthermore, a contact estimator and a failure detector, aiming to enhance the safety and reliability enhancement, are designed. Finally, the proposed control strategy is studied with both simulation and experiment. The experimental results show that the advanced disturbance observer can estimate the actual contact force correctly and precisely, and the disturbance observer based force estimation and failure detection method is feasible which can be used in force sensing, contact detection and fault diagnosis.     

典型软件成本估算方法比较及选择

利用国际软件标杆标准化组织(ISBSG)的标杆数据库,研究了两个最典型的软件成本分析模型--软件生命周期模型和构造性成本模型.通过大量的仿真计算,对不同类型软件项目的成本估算精度进行了全面比较,得出了一组有价值的实验结果.在此基础上,给出一个根据项目的具体情况选择合适的成本估算模型的决策方法.该方法在一个复杂产品多学科设计平台的开发项目中进行了应用,并验证了所提出方法的可行性.     

飞机机电系统部件数据驱动健康状态 在线估计方法综述

飞机机电系统的机电部件(飞机机电系统部件)处于良好的健康状态是飞机机电系统安全运行重要前提,对于保障飞机正常飞行和成员安全具有重要意义。飞机机电系统部件健康状态在线估计可以实现部件健康状态的在线估计,有效支撑部件的视情维修,进而为飞行任务保障提供决策参考。本文以代表性飞机机电系统部件机电作动器和辅助动力装置为具体研究对象,在对该领域健康状态估计方法进行充分调研基础上,阐述飞机机电系统部件健康状态估计基本概念及内涵,并针对飞机机电系统部件数据驱动健康状态在线估计方法体系进行系统地分析,进而归纳总体发展动态并展望未来发展方向,以此为相关研究者提供参考。