Shape from focus based on 3D structure tensor using optical microscopy

Shape from focus (SFF) is a widely used passive optical method for 3D shape reconstruction. In SFF, a focus measure, which is used to estimate the relative focus level, plays a critical role in depth estimation. In this article, we present a new focus measure for accurate 3D shape estimation in optical microscopy based on the analysis of 3D structure tensor. First, the 3D tensors are computed from the input image sequence for each pixel. Then, each tensor is decomposed into point, curve, and surface tensors by decomposing tensors into eigenvalues and eigenvectors. Finally, the surfaceness is used to measure the quality of sharpness. The proposed focus measure provides accurate focus values and better resistance against noise. The proposed measure is evaluated by conducting experiments using image sequences of simulated and microscopic real objects. The comparative analysis demonstrates the effectiveness of the proposed focus measure in recovering 3D shape.     

A multi-tone central divided difference frequency tracker with adaptive process noise covariance tuning

The problem of real-time frequency estimation of nonstationary multi-harmonic signals is important in many applications. In this paper, we propose a novel multi-frequency tracker based on a state-space representation of the signal with Cartesian filters and the second-order central divided difference filter (CDDF), which improves the performance of the extended Kalman filter (EKF) by using Stirling's interpolation method to approximate the mean and covariance of the state vector. A crucial element of the method is the adaptive scaling of the process noise covariance matrix appearing in the filter equations, as a function of the innovation sequence, which tunes the accuracy-reactivity trade-off of the filter. The proposed solution is evaluated against two approaches from the literature, namely the factorized adaptive notch filter (FANF) and the extended Kalman filter frequency tracker (EKFFT). Several experiments emphasize the estimation accuracy of the proposed method as well as the improved robustness with respect to initial errors and input signal complexity. The presented method appears to be particularly efficient with rapidly varying frequencies, thanks to the update mechanism that adjusts the filter parameters based on the amplitude of the estimation error.     

气候环境实验室地面结冰云雾模拟控制系统设计

飞机结冰会引起飞机气动特性、动力系统性能改变,甚至造成飞行事故。地面结冰云雾模拟设施作为一种模拟飞机飞行结冰条件的重要设备,常用于飞机防除冰系统功能验证。针对气候环境实验室结冰云雾试验条件需要,在对地面结冰云雾模拟系统进行研究的基础上,对适用于气候环境实验室的结冰云雾模拟系统进行了设计。对系统关键设计技术、系统功能及组成进行了分析,并对控制系统方案进行了详细阐述。试验表明,控制系统人机界面友好,运行可靠,能够满足液态水含量、雾滴直径参数的精确调节,产生符合试验所需的结冰环境。     

Structural parameter design method for a fast-steering mirror based on a closed-loop bandwidth

When a fast-steering mirror (FSM) system is designed, satisfying the performance requirements before fabrication and assembly is vital. This study proposes a structural parameter design approach for an FSM system based on the quantitative analysis of the required closed-loop bandwidth. First, the open-loop transfer function of the FSM system is derived. In accordance with the transfer function, the notch filter and proportional-integral (PI) feedback controller are designed as a closed-loop controller. The gains of the PI controller are determined by maximizing the closed-loop bandwidth while ensuring the robustness of the system. Then, the two unknown variables of rotational radius and stiffness in the open-loop transfer function are optimized, considering the bandwidth as a constraint condition. Finally, the structural parameters of the stage are determined on the basis of the optimized results of rotational radius and stiffness. Simulations are conducted to verify the theoretical analysis. A prototype of the FSM system is fabricated, and corresponding experimental tests are conducted. Experimental results indicate that the bandwidth of the proposed FSM system is 117.6 Hz, which satisfies the minimum bandwidth requirement of 100 Hz.     

基于改进交叉熵算法的电力系统随机生产模拟

蒙特卡洛模拟的计算效率与系统的可靠性密切相关，在其用于高可靠性系统的随机模拟时存在计算效率偏低的问题。为此，提出了一种基于多层交叉熵与对偶变数抽样技术相结合的随机模拟算法。首先使用多层交叉熵构造零方差概率密度函数的近似函数，提高小概率失效事件的抽取概率；其次基于已构造的近似概率函数，采用对偶变数抽样法进行抽样，进一步提高抽样的收敛速度。以IEEE RTS修改系统为例进行了算例分析，算例结果验证了所提出的基于改进交叉熵的电力系统随机生产模拟算法的有效性。     

Distributed data-driven observer for linear time invariant systems

This paper is concerned with distributed data-driven observer design problem. The existing data-driven observers rely on a common assumption that all the information about the system, and the calculations based upon this information are centralized. Therefore the resulting algorithms cannot be applied to the distributed systems in which each local observer receives only a part of the output signal. On the other hand, traditional model-based distributed state estimation methods generally assume that the processes are decomposed according to the known process models, while in data-driven approaches there is no such information available. The main goal of this paper is to extend the centralized data-driven observer design approach to the distributed framework. The stability of the proposed data-driven distributed observer is also proved analytically. A quadruple-tank process is simulated to demonstrate the performance of the proposed scheme.     

Outlier accommodation in moving-horizon state estimation: A risk-averse performance-specified approach

This paper presents a novel state estimation approach for linear dynamic systems when measurements are corrupted by outliers. Since outliers can degrade the performance of state estimation, outlier accommodation is critical. The standard approach combines outlier detection utilizing Neyman-Pearson (NP) type tests with a Kalman filter (KF). This approach ignores all residuals greater than a designer-specified threshold. When measurements with outliers are used (ie, missed detections), both the state estimate and the error covariance matrix become corrupted. This corrupted state and covariance estimate are then the basis for all subsequent outlier decisions. When valid measurements are rejected (ie, false alarms), potentially using the corrupted state estimate and error covariance, measurement information is lost. Either using invalid information or discarding too much valid information can result in divergence of the KF. An alternative approach is moving-horizon (MH) state estimation, which maintains all recent measurement data within a moving window with a time horizon of length L. In MH approaches, the number of measurements available for state estimation is affected by both the number of measurements per time step and the number of time steps L over which measurements are retained. Risk-averse performance-specified (RAPS) state estimation works within an optimization setting to choose a set of measurements that achieves a performance specification with minimum risk of outlier inclusion. This paper derives and formulates the MH-RAPS solution for outlier accommodation. The paper also presents implementation results. The MH-RAPS application uses Global Navigation Satellite Systems measurements to estimate the state of a moving platform using a position, velocity, and acceleration model. In this application, MH-RAPS performance is compared with MH-NP state estimation.     

Process noise covariance estimation via stochastic approximation

Kalman filtering for linear systems is known to provide the minimum variance estimation error, under the assumption that the model dynamics is known. While many system identification tools are available for computing the system matrices from experimental data, estimating the statistics of the output and process noises is still an open problem. Correlation-based approaches are very fast and sufficiently accurate, but there are typically restrictions on the number of noise covariance elements that can be estimated. On the other hand, maximum likelihood methods estimate all elements with high accuracy, but they are computationally expensive, and they require the use of external optimization solvers. In this paper, we propose an alternative solution, tailored for process noise covariance estimation and based on stochastic approximation and gradient-free optimization, that provides a good trade-off in terms of performance and computational load, and is also easy to implement. The effectiveness of the method as compared to the state of the art is shown on a number of recently proposed benchmark examples.     

基于多项式变换的参数估计方法

本文给出一种采用DPT估计SNCK信号时宽—带宽积的方法,并通过仿真该估计方法的性能与其它估计方法进行比较.首先给出SNCK信号参数估计的一般过程.为了便于计算和理论推导,根据估计出的中心频率将接收到的SNCK信号搬移到零频,从而进一步估计其它参数,如采用DPT估计SNCK信号时宽带宽积.本文将重点研究采用DPT算法估计SNCK信号值的方法.     

Inhibition of counterflow methane/air diffusion flame by water mist with varying mist diameter

In the present study, the effect of fine water mist on extinguishment of a methane–air counterflow diffusion flame was investigated to understand the underlying physics of fire extinguishment of highly stretched diffusion flame by water mist. Twin-fluid atomizers were used to generate polydisperse water mist of which Sauter mean diameters were 10, 20, 40, and 60 μm. When water mist is not added, the critical stretch rate at extinguishment is 439 s⁻¹ as compared to the theoretical value of 460 s⁻¹. For the case with water mist addition, when the stretch rate is small enough, almost all the water mist evaporates within the flame zone. On the other hand, for high stretch rate case, large mist droplets pass through the flame zone and can reach the stagnation plane. However, no oscillatory motion was found around the stagnation plane. Critical stretch rate at extinguishment decreases monotonously with the mass fraction of water mist independently of the mist diameter within the range of D₃₂ from 10 μm to 60 μm. On the other hand, with increase in the surface area parameter, the critical stretch rate at extinguishment decreases rapidly and becomes less sensitive at large surface area parameter, of which tendency is qualitatively in good agreement with theoretical predictions. For a constant surface area parameter, the critical stretch rate decreases with mist diameter because the mass fraction of water mist should increase in proportion to the mist diameter to keep the surface area parameter constant. When the water mist evaporates completely in the flame zone as in the present study, the mass fraction of the water mist is the dominant factor for fire extinguishment, rather than the surface area parameter. Therefore, an appropriate combination of stretch rate and water mist mass fraction should be provided to suppress effectively a given fire with a small amount of water mist.