Adaptive Smoothing Method Based on Fuzzy Theory Study and Realization

In this paper, we study about a method to optimize the fused track quality in intelligence network of radar target fusion system, considering the role of people in the fusion system;we start to find ways to optimize the quality of the fused track, and adaptive smoothing method is proposed based on fuzzy theory. Tests show that this method can greatly improve the quality of the fused track system for battlefield reconnaissance provides high-quality, high-reliability battlefield.

Adaptive smoothing length method based on weighted average of neighboring particle density for SPH fluid simulation

Background In the smoothed particle hydrodynamics(SPH)fluid simulation method,the smoothing length affects not only the process of neighbor search but also the calculation accuracy of the pressure solver.Therefore,it plays a crucial role in ensuring the accuracy and stability of SPH.Methods In this study,an adaptive SPH fluid simulation method with a variable smoothing length is designed.In this method,the smoothing length is adaptively adjusted according to the ratio of the particle density to the weighted average of the density of the neighboring particles.Additionally,a neighbor search scheme and kernel function scheme are designed to solve the asymmetry problems caused by the variable smoothing length.Results The simulation efficiency of the proposed algorithm is comparable to that of some classical methods,and the variance of the number of neighboring particles is reduced.Thus,the visual effect is more similar to the corresponding physical reality.Conclusions The precision of the interpolation calculation performed in the SPH algorithm is improved using the adaptive-smoothing length scheme;thus,the stability of the algorithm is enhanced,and a larger timestep is possible.

Adaptive linear active disturbance-rejection control strategy reduces the impulse current of compressed air energy storage connected to the grid

The merits of compressed air energy storage(CAES)include large power generation capacity,long service life,and environmental safety.When a CAES plant is switched to the grid-connected mode and participates in grid regulation,using the traditional control mode with low accuracy can result in excess grid-connected impulse current and junction voltage.This occurs because the CAES output voltage does not match the frequency,amplitude,and phase of the power grid voltage.Therefore,an adaptive linear active disturbance-rejection control(A-LADRC)strategy was proposed.Based on the LADRC strategy,which is more accurate than the traditional proportional integral controller,the proposed controller is enhanced to allow adaptive adjustment of bandwidth parameters,resulting in improved accuracy and response speed.The problem of large impulse current when CAES is switched to the grid-connected mode is addressed,and the frequency fluctuation is reduced.Finally,the effectiveness of the proposed strategy in reducing the impact of CAES on the grid connection was verified using a hardware-in-the-loop simulation platform.The influence of the k value in the adaptive-adjustment formula on the A-LADRC was analyzed through simulation.The anti-interference performance of the control was verified by increasing and decreasing the load during the presynchronization process.

Adaptive Endpoint Detection Based on Subband Speech

An adaptive endpoint detection algorithm based on band energy and adaptive smoothing algorithm is described. This algorithm utilizes the capability of adaptive smoothing algorithm that intensifies the discontinuity between local areas. The band energy features are selected because of their usefulness in detecting high energy regions (in the incoming signal) and making the distinction between speech and noise. Heuristic 'edge-focusing' is used to endpoint detection to save the time in iteration.

Optimization of buckling load for laminated composite plates using adaptive Kriging-improved PSO:A novel hybrid intelligent method

An effective hybrid optimization method is proposed by integrating an adaptive Kriging(A-Kriging)into an improved partial swarm optimization algorithm(IPSO)to give a so-called A-Kriging-IPSO for maximizing the buckling load of laminated composite plates(LCPs)under uniaxial and biaxial compressions.In this method,a novel iterative adaptive Kriging model,which is structured using two training sample sets as active and adaptive points,is utilized to directly predict the buckling load of the LCPs and to improve the efficiency of the optimization process.The active points are selected from the initial data set while the adaptive points are generated using the radial random-based convex samples.The cell-based smoothed discrete shear gap method(CS-DSG3)is employed to analyze the buckling behavior of the LCPs to provide the response of adaptive and input data sets.The buckling load of the LCPs is maximized by utilizing the IPSO algorithm.To demonstrate the efficiency and accuracy of the proposed methodology,the LCPs with different layers(2,3,4,and 10 layers),boundary conditions,aspect ratios and load patterns(biaxial and uniaxial loads)are investigated.The results obtained by proposed method are in good agreement with the literature results,but with less computational burden.By applying adaptive radial Kriging model,the accurate optimal resultsebased predictions of the buckling load are obtained for the studied LCPs.

Adaptive practical output tracking of a class of nonlinear systems

Focus is laid on the adaptive practical output-tracking problem of a class of nonlinear systems with high-order lower-triangular structure and uncontrollable unstable linearization. Using the modified adaptive addition of a power integrator technique as a basic tool, a new smooth adaptive state feedback controller is designed. This controller can ensure all signals of the closed-loop systems are globally bounded and output tracking error is arbitrary small.

A Parameter Adaptive Method for Image Smoothing

Edge is the key information in the process of image smoothing. Some edges, especially the weak edges, are difficult to maintain, which result in the local area being over-smoothed. For the protection of weak edges, we propose an image smoothing algorithm based on global sparse structure and parameter adaptation. The algorithm decomposes the image into high frequency and low frequency part based on global sparse structure. The low frequency part contains less texture information which is relatively easy to smoothen. The high frequency part is more sensitive to edge information so it is more suitable for the selection of smoothing parameters. To reduce the computational complexity and improve the effect, we propose a bicubic polynomial fitting method to fit all the sample values into a surface. Finally, we use Alternating Direction Method of Multipliers (ADMM) to unify the whole algorithm and obtain the smoothed results by iterative optimization. Compared with traditional methods and deep learning methods, as well as the application tasks of edge extraction, image abstraction, pseudo-boundary removal, and image enhancement, it shows that our algorithm can preserve the local weak edge of the image more effectively, and the visual effect of smoothed results is better.

基于改进迁移学习的红外光谱图像自适应分割研究

为了从红外光谱图像中获取有用信息,设计基于改进迁移学习的红外光谱图像自适应分割方法。采集系统获取红外光谱图像,采用直方图均衡技术对红外光谱图像进行增强处理,依据增强后图像各帧像素的高斯正态分布,重建红外光谱图像,将红外光谱图像重建结果输入双分支卷积神经网络模型,利用迁移学习子网提取红外光谱图像全局特征,结合残差注意力子网提取的图像细小特征;通过集成学习融合差异红外光谱图像特征,输出分割后的红外光谱图像。测试结果表明:该方法可实现红外光谱图像分割,且分割结果清晰,具有显著细节特征。

Smooth pulse recovery based on hybrid wavelet threshold denoising and first derivative adaptive smoothing filter

Based on the pulse-shaping unit in the front end of high-power laser facilities,we propose a new hybrid scheme in a closed-loop control system including wavelet threshold denoising for pretreatment and a first derivative adaptive smoothing filter for smooth pulse recovery,so as to effectively restrain the influence of electrical noise and FM-to-AM modulation in the time–power curve,and enhance the calibration accuracy of the pulse shape in the feedback control system.The related simulation and experiment results show that the proposed scheme can obtain a better shaping effect on the high-contrast temporal shape in comparison with the cumulative average algorithm and orthogonal matching pursuit algorithm combined with a traditional smoothing filter.The implementation of the hybrid scheme mechanism increased the signal-to-noise ratio of the laser pulse from about 11 dB to 30 dB,and the filtered pulse is smooth without modulation,with smoothness of about 98.8%.

Infrared LSS-Target Detection Via Adaptive TCAIE-LGM Smoothing and Pixel-Based Background Subtraction

Infrared small target detection is a significant and challenging topic for daily security. This paper proposes a novel model to detect LSS-target (low altitude, slow speed, and small target) under the complicated background. Firstly, the fundamental constituents of an infrared image including the complexity and entropy are calculated, which are invoked as adaptive control parameters of smoothness. Secondly, the adaptive L0 gradient minimization smoothing based on texture complexity and information entropy (TCAIE-LGM) is proposed in order to remove noises and suppress low-amplitude details in infrared image abstraction. Finally, difference of Gaussian (DoG) map is incorporated into the pixel-based adaptive segmentation (PBAS) background modeling algorithm, which can differ LSS-target from the sophisticated background. Experimental results demonstrate that the proposed novel model has a high detection rate and produces fewer false alarms, which outperforms most state-of-the-art methods.

A novel approach to determine residual stress field during FSW of AZ91 Mg alloy using combined smoothed particle hydrodynamics/neuro-fuzzy computations and ultrasonic testing

The faults in welding design and process every so often yield defective parts during friction stir welding(FSW).The development of numerical approaches including the finite element method(FEM)provides a way to draw a process paradigm before any physical implementation.It is not practical to simulate all possible designs to identify the optimal FSW practice due to the inefficiency associated with concurrent modeling of material flow and heat dissipation throughout the FSW.This study intends to develop a computational workflow based on the mesh-free FEM framework named smoothed particle hydrodynamics(SPH)which was integrated with adaptive neuro-fiizzy inference system(ANFIS)to evaluate the residual stress in the FSW process.An integrated SPH and ANFIS methodology was established and the well-trained ANIS was then used to predict how the FSW process depends on its parameters.To verify the SPH calculation,an itemized FSW case was performed on AZ91 Mg alloy and the induced residual stress was measured by ultrasonic testing.The suggested methodology can efficiently predict the residual stress distribution throughout friction stir welding of AZ91 alloy.

Dark-field detection method of shallow scratches on the super-smooth optical surface based on the technology of adaptive smoothing and morphological differencing

In recent years, modern optical processing technologies, such as single point diamond turning, ion beam etching, and magneto-theological finishing, arc getting break- throughs. Machining precisions of super-smooth optics have also been significantly improved. However, with increasing demands for the optical surface quality,

Robust immersion and invariance adaptive coordinated control for a class of biaxial gantry systems

This paper proposes a robust Immersion and Invariance(I&I)adaptive coordinated controller for a class of uncertain linear-motor-driven biaxial gantry system subject to external disturbances for high-accuracy contour tracking.Firstly,the dynamic model of the gantry system is transformed into task coordinate frame,through which the contour tracking can be regarded as a regulation problem.Based on the transformed system dynamics,an I&I-based adaptation law with smooth projection is proposed to estimate the unknown parameters.Different from traditional adaptive control,the proposed robust I&I adaptive control introduces a new term called tuning function in adaptation law to shape the dynamic behaviour of the estimation vector.Then the stability of the closed-loop system is proved by Lyapunov theory.Finally,comparative experiments are executed on an industrial biaxial gantry system with two different cases to verify the effectiveness of the proposed control law.

A NEW METHOD FOR STRUCTURAL TOPOLOGICAL OPTIMIZATION BASED ON THE CONCEPT OF INDEPENDENT CONTINUOUS VARIABLES AND SMOOTH MODEL

A concept of the independent-continuous topological variable is proposed to establish its corresponding smooth model of structural topological optimization. The method can overcome difficulties that are encountered in conventional models and algorithms for the optimization of the structural topology. Its application to truss topological optimization with stress and displacement constraints is satisfactory, with convergence faster than that of sectional optimizations.

Spatially smoothed quaternion-Capon beamforming in the presence of coherent interferences

The performance the quaternion-Capon（ Q-Capon） beamformer degraded when suppressing the interferences that are coherent with the signal of interest（ SOI）. To tackle the problem,the spatial smoothing technique is adopted in quaternion domain to decorrelate the interferences by using linearly and uniformly spaced two-component electromagnetic vector-sensors. By averaging several translational invariant subarray quaternion covariance matrices,the quaternion spatial smoothing is performed to prevent the SOI cancellation phenomena caused by the presence of coherent interferences. It is demonstrated that the quaternion spatial smoothing Q-Capon beamformer can suppress the coherent interferences remarkably while the computational cost is lower than the complex domain long vector spatial smoothing counterpart. Theoretical analyses and simulation results validate the efficacy of the spatially smoothed Q-Capon beamformer in terms of coherent interference suppression capability.

公铁两用大跨度斜拉桥-无砟轨道体系变形适应性研究

高速铁路大跨度斜拉桥结构变形受其复杂服役环境影响显著,而无砟轨道对工后变形的调整能力有限,因此大跨度斜拉桥的复杂变形条件将直接影响其上无砟轨道结构的适应性。以沪渝蓉高铁长江北支公铁两用大跨度斜拉桥应用无砟轨道为工程背景,建立无砟轨道-大跨度斜拉桥一体化精细空间有限元模型,分析铁路、公路以及温度等多种荷载联合作用下大跨度斜拉桥-无砟轨道体系平顺性、无缝线路稳定性和无砟轨道层间变形协调性,从而对大跨度公铁两用钢桁梁斜拉桥-无砟轨道体系变形适应性开展深入研究。结果表明:在运营荷载及温度荷载最不利组合作用下,大跨度斜拉桥主梁线形平顺,变形平缓,桥梁整体刚度较好,桥上无砟轨道几何形位可以满足静态验收标准;大跨度斜拉桥上无缝线路的强度和稳定性满足要求,扣件工作性能良好,钢轨伸缩调节器的设置可有效释放梁端钢轨的纵向应力;无砟轨道层间设置橡胶隔离层且不跨主梁桁架节间的布置方式可提高大跨度斜拉桥上无砟轨道的变形协调性能,使得桥上无砟轨道层间始终处于受压状态,达到“隔而不离”的桥上轨道层间理想服役状态;大跨度公铁两用钢桁梁斜拉桥-无砟轨道体系变形适应性良好。本文研究成果可为公铁两用大跨度钢桁梁斜拉桥上无砟轨道的应用提供技术参考。

一种适用宽速域冲击的明胶鸟弹数值建模方法

明胶鸟弹在不同撞击速度下表现出不同的响应特性。为解决传统明胶鸟弹本构表征方法在不同速度范围内不能通用的问题,开展了330 g明胶鸟弹以70~190 m/s速度、60°或90°入射刚性铝合金平板试验,记录了冲击力数据及撞击形貌。结果表明,随着撞击速度的提高,鸟弹碎裂得更充分,碎块体积减小。利用LS-DYNA建立了自适应FEM-SPH(finite element method-smoothed particle hydrodynamics)鸟体模型。依据试验结果反演得到一组鸟体本构参数:切线模量为1.33MPa,剪切模量为115.95MPa,Murnaghan状态方程参数γ为10.49,k_(0)为69.77 MPa,体积模量为246.4 MPa,失效塑性应变为1.15,初始屈服应力为0.21 MPa。仿真结果与试验结果具有很好的一致性,冲击力峰值的相对误差在2%以内,冲量的相对误差在10%以内。自适应FEM-SPH鸟体模型具有比SPH模型和拉格朗日模型更高的精度。由自适应模型得到的Hugoniot压强与理论结果具有相同的变化趋势,滞止压强与理论值较接近。

基于权值平滑的自适应调零算法研究与实现

在卫星导航定位系统中,由于导航信号的功率较低,在到达地面时极易受到干扰,导致定位失败。自适应零陷技术可以有效地提高卫星导航接收机的抗干扰能力,然而由于常规的空时联合最小功率响应会时常出现零陷抖动,不能有效的对准干扰来向,从而导致接收机的抗干扰性能下降。对于该情况,本文提出对抗干扰算法中的权值进行平滑滤波处理的方法,并且通过仿真验证、FPGA实现、现场实测等手段验证了该算法的可行性。该方法可有效抑制系统权值以及零陷位置的抖动,从而提高抗干扰算法的稳定性和可靠性,对相关工程领域具有一定的参考价值。

基于自适应平滑死区逆的航天气化炉氧气流量控制

航天气化炉氧气流量对象具有大噪声、非线性和强干扰特性,氧气流量控制系统自动化程度低。由于氧气阀门具有死区非线性,人工操作和常规控制策略常常无法获得理想的控制效果,因此提出了一种自适应平滑死区逆算法,补偿氧气阀门的死区非线性,再引入氧气主管压力的变化速度作为前馈量,补偿氧气压力波动带来的干扰。自适应平滑死区逆与前馈控制成功应用于航天气化炉氧气流量控制系统,控制效果明显改善。

基于ε-level蝙蝠算法的无人机三维航迹规划

针对复杂地形环境、存在各种威胁和约束的无人机航迹规划问题,提出了一种基于ε-level改进蝙蝠算法的航迹规划算法。根据无人机目标函数和约束条件,建立无人机三维航迹规划模型;其次,针对蝙蝠算法处理高维带约束问题存在的早熟现象,设计了自适应权重系数和迭代阈值以平衡算法的探索能力和开发能力,并结合ε-level比较策略提高算法对非凸非线性约束优化问题的处理能力;设计了转弯半径可变的Dubins曲线用来对航迹进行平滑处理并解决2个航迹点连线贯穿地形的问题。通过仿真实验,并与蝙蝠算法、粒子群优化算法、ε-level粒子群优化算法和ε-level差分进化算法相比较,所提算法在开发能力、稳定性和成功率等方面都表现出较优的性能。