Solution Domain Boundary Analysis Method and Its Application in Parameter Spaces of Nonlinear Gear System

Mastering the influence laws of parameters on the solution structure of nonlinear systems is the basis of carrying out vibration isolation and control.Many researches on solution structure and bifurcation phenomenon in parameter spaces are carried out broadly in many fields,and the research on nonlinear gear systems has attracted the attention of many scholars.But there is little study on the solution domain boundary of nonlinear gear systems.For a periodic non-autonomous nonlinear dynamic system with several control parameters,a solution domain boundary analysis method of nonlinear systems in parameter spaces is proposed,which combines the cell mapping method based on Poincaré point mapping in phase spaces with the domain decomposition technique of parameter spaces.The cell mapping is known as a global analysis method to analyze the global behavior of a nonlinear dynamic system with finite dimensions,and the basic idea of domain decomposition techniques is to divide and rule.The method is applied to analyze the solution domain boundaries in parameter spaces of a nonlinear gear system.The distribution of different period domains,chaos domain and the domain boundaries between different period domains and chaotic domain are obtained in control parameter spaces constituted by meshing damping ratio with excitation frequency,fluctuation coefficient of meshing stiffness and average exciting force respectively by calculation.The calculation results show that as the meshing damping increases,the responses of the system change towards a single motion,while the variations of the excitation frequency,meshing stiffness and exciting force make the solution domain presenting diversity.The proposed research contribution provides evidence for vibration control and parameter design of the gear system,and confirms the validity of the solution domain boundary analysis method.

Improved control for distributed parameter systems with time-dependent spatial domains utilizing mobile sensor-actuator networks

A guidance policy for controller performance enhancement utilizing mobile sensor-actuator networks （MSANs） is proposed for a class of distributed parameter systems （DPSs）, which are governed by diffusion partial differential equations （PDEs） with time-dependent spatial domains. Several sufficient conditions for controller performance enhancement are presented. First, the infinite dimensional operator theory is used to derive an abstract evolution equation of the systems under some rational assumptions on the operators, and a static output feedback controller is designed to control the spatial process. Then, based on Lyapunov stability arguments, guidance policies for collocated and non-collocated MSANs are provided to enhance the performance of the proposed controller, which show that the time-dependent characteristic of the spatial domains can significantly affect the design of the mobile scheme. Finally, a simulation example illustrates the effectiveness of the proposed policy.

Parameter Optimization of Tuned Mass Damper Inerter via Adaptive Harmony Search

Dynamic impacts such as wind and earthquakes cause loss of life and economic damage.To ensure safety against these effects,various measures have been taken from past to present and solutions have been developed using different technologies.Tall buildings are more susceptible to vibrations such as wind and earthquakes.Therefore,vibration control has become an important issue in civil engineering.This study optimizes tuned mass damper inerter(TMDI)using far-fault ground motion records.This study derives the optimum parameters of TMDI using the Adaptive Harmony Search algorithm.Structure displacement and total acceleration against earthquake load are analyzed to assess the performance of the TMDI system.The effect of the inerter when connected to different floors is observed,and the results are compared to the conventional tuned mass damper(TMD).It is indicated that the case of connecting the inerter force to the 5th floor gives better results.As a result,TMD and TMDI systems reduce the displacement by 21.87%and 25.45%,respectively,and the total acceleration by 25.45%and 19.59%,respectively.These percentage reductions indicated that the structure resilience against dynamic loads can be increased using control systems.

Terahertz Time-Domain Spectroscopy method for optical parameter extraction of plastic materials

A method for extracting optical parameters of plastics materials based on terahertz time domain spectroscopy is presented. The transmission-type Terahertz Time-Domain Spectroscopy(THz TDS) system is adopted to detect the refractive index and extinction coefficient on different plastic materials. Then the corresponding spectral information is obtained by Fourier transform of the terahertz time domain waveform of the sampling points, including the corresponding amplitude and phase information of the waveform. The optical parameter extraction model is built. By using the simplex optimization method, the curves of the refractive index and extinction coefficient for the plastic material are obtained. The experimental samples are made of different plastic parallel plate materials. The experimental results show that the optimization of optical parameters can improve their extraction accuracy, and the error of refractive index is ±0.005. Extraction technology with the simplex optimization method of optical parameter based on THz TDS can help to extract the optical parameters of engineering plastics. It is of great significance for the research of terahertz nondestructive testing.

TIME DOMAIN PARAMETERS IDENTIFICATION OF FOUNDATION-STRUCTURE INTERACTION SYSTEM

The time domain parameter laenuncauon memoa oi me iounuauon-structure interaction system is presented. On the basis of building the computation mode and the motion equation of the foundation-structure interaction system, the system parameter identification method was established by using the extended Kalman filter （EKF） technique and taking the unknown parameters in the system as the augment state variables. And the time parameter identification process of the foundation-structure interaction system was implemented by using the data of the layer foundation-storehouse interaction system model test on the large vibration platform. The computation result shows that the established parameter identification method can induce good parameter estimation.

Parameter identification algorithm for fault location using one terminal data based on frequency domain

This paper presents a novel algorithm of fault location for transmission line.Solving the network spectrum equations for different frequencies the fault can be located accurately by this algorithm with one terminal data of voltage and current,and the identified parameters,such as fault distance, fault resistance,and opposite terminal system resistance and inductance.The algorithm eliminates the influence of the opposite system impedance on the fault location accuracy,which causes the main error in traditional fault location methods using one terminal data.A method of calculating spectrum from sampled data is also proposed.EMTP simulations show the validity and higher accuracy of the fault location algorithm compared to the existing ones based on one terminal data.

Human Brain Microwave Imaging Signal Processing: Frequency Domain (S-parameters) to Time Domain Conversion

The paper presents the microwave signal processing method using MATLAB based on the result of microwave imaging system simulation developed using Computer Simulation Technology (CST). The simulation system contains a transmitting/receiving antenna, human brain and a tumor inside the brain model. The source signal, microwave signal operates from 1 to 10 GHz. The generated scattering parameters (S-parameters) are in frequency domain form. This paper describes in detail regarding the signal conversion from frequency domain to time domain through proposed Inverse Fast Fourier Transform (IFFT) method as well as the noise filtering process. Peaks detection process was performed in order to identify the time delay of the reflection points at different Y-axis

The Complex Analysis Method of Numerical Identification of Parameters of Quasiideals Processes in Doubly-Connected Nonlinear-Layered Curvilinear Domains

The method of numerical solving of nonlinear model problems of theory of a complex quasi-potential in doubly-connected nonlinear-layered curvilinear domains considering inverse influence function of flow on a conductivity coefficient of medium was developed on the basis of synthesis of numerical methods of the quasi-conformal mappings and summary representations in conjunction with domain decomposition by method Schwartz. The proposed algorithm allows finding the potential of the quasiideals field, construction a motion grid （fluid-flow grid） simultaneously defining the flow lines that separate of sub-domains constancy of coefficient conductivity and identification the piecewise-constant values of coefficient conductivity, the local flows for the known measurements on boundary of domain.

Modeling river water quality parameters using modified adaptive neuro fuzzy inference system

Water quality is always one of the most important factors in human health. Artificial intelligence models are respected methods for modeling water quality. The evolutionary algorithm (EA) is a new technique for improving the performance of artificial intelligence models such as the adaptive neuro fuzzy inference system (ANFIS) and artificial neural networks (ANN). Attempts have been made to make the models more suitable and accurate with the replacement of other training methods that do not suffer from some shortcomings, including a tendency to being trapped in local optima or voluminous computations. This study investigated the applicability of ANFIS with particle swarm optimization (PSO) and ant colony optimization for continuous domains (ACOR) in estimating water quality parameters at three stations along the Zayandehrood River, in Iran. The ANFIS-PSO and ANFIS-ACOR methods were also compared with the classic ANFIS method, which uses least squares and gradient descent as training algorithms. The estimated water quality parameters in this study were electrical conductivity (EC), total dissolved solids (TDS), the sodium adsorption ratio (SAR), carbonate hardness (CH), and total hardness (TH). Correlation analysis was performed using SPSS software to determine the optimal inputs to the models. The analysis showed that ANFIS-PSO was the better model compared with ANFIS-ACOR. It is noteworthy that EA models can improve ANFIS' performance at all three stations for different water quality parameters.

MODAL PARAMETERS EXTRACTION WITH CROSS CORRELATION FUNCTION AND CROSS POWER SPECTRUM UNDER UNKNOWN EXCITATION

In most of real operational conditions only response data are measurable while the actual excitations are unknown, so modal parameter must be extracted only from responses. This paper gives a theoretical formulation for the cross-correlation functions and cross-power spectra between the outputs under the assumption of white-noise excitation. It widens the field of modal analysis under ambient excitation because many classical methods by impulse response functions or frequency response functions can be used easily for modal analysis under unknown excitation. The Polyreference Complex Exponential method and Eigensystem Realization Algorithm using cross-correlation functions in time domain and Orthogonal Polynomial method using cross-power spectra in frequency domain are applied to a steel frame to extract modal parameters under operational conditions. The modal properties of the steel frame from these three methods are compared with those from frequency response functions analysis. The results show that the modal analysis method using cross-correlation functions or cross-power spectra presented in this paper can extract modal parameters efficiently under unknown excitation.

Fifth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (5th-CASAM-N): II. Paradigm Application to a Bernoulli Model Comprising Uncertain Parameters

This work presents the application of the recently developed “Fifth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (5th-CASAM-N)” to a simplified Bernoulli model. The 5th-CASAM-N builds upon and incorporates all of the lower-order (i.e., the first-, second-, third-, and fourth-order) adjoint sensitivities analysis methodologies. The Bernoulli model comprises a nonlinear model response, uncertain model parameters, uncertain model domain boundaries and uncertain model boundary conditions, admitting closed-form explicit expressions for the response sensitivities of all orders. Illustrating the specific mechanisms and advantages of applying the 5th-CASAM-N for the computation of the response sensitivities with respect to the uncertain parameters and boundaries reveals that the 5th-CASAM-N provides a fundamental step towards overcoming the curse of dimensionality in sensitivity and uncertainty analysis.

The Initial Parameters Design of the Voltage Source Converter Fed SMES

The initial parameters of the superconducting magnetic energy storage (SMES) fed by a voltage source converter (VSMES) are studied and the setting rules are designed in this paper. A time-domain simulation model is established by using the software PSCAD/EMTDC. Based on this model, the application of the VSMES in the power system is used to test the designed rules. The simulation results are valuable for the further research of the initial parameters design of the VSMES.

Solution and Analysis of Chatter Stability for End Milling in the Time-domain

In this paper, the instantaneous undeformed chip thickness is modeled to include the dynamic modulation caused by the tool vibration while the dynamic regenerative effects are taken into account. The numerical method is used to solve the differential equations goveming the dynamics of the milling system. Several chatter detection criteria are applied synthetically to the simulated signals and the stability diagram is obtained in time-domain. The simulation results in time-domain show a good agreement with the analytical prediction, which is validated by the cutting experiments. By simulating the chatter stability lobes in the time-domain and analyzing the influences of different spindle speeds on the vibration amplitudes of the tool under a Fixed chip-load condition, conclusions could be drawn as follows： In rough milling, higher machining efficiency can be achieved by selecting a spindle speed corresponding to the axial depth of cut in accordance with the simulated chatter stability lobes, and in Fmish milling, lower surface roughness can be achieved by selecting a spindle speed well beyond the resonant frequency of machining system.

An operational modal analysis method in frequency and spatial domain

A frequency and spatial domain decomposition method （FSDD） for operational modal analysis （OMA） is presented in this paper, which is an extension of the complex mode indicator function （CMIF） method for experimental modal analysis （EMA）. The theoretical background of the FSDD method is clarified, Singular value decomposition is adopted to separate the signal space from the noise space. Finally, an enhanced power spectrum density （PSD） is proposed to obtain more accurate modal parameters by curve fitting in the frequency domain. Moreover, a simulation case and an application case are used to validate this method.

Joint AVO inversion in the time and frequency domain with Bayesian interference

Amplitude variations with offset or incident angle （AVO/AVA） inversion are typically combined with statistical methods, such as Bayesian inference or deterministic inversion. We propose a joint elastic inversion method in the time and frequency domain based on Bayesian inversion theory to improve the resolution of the estimated P- and S-wave velocities and density. We initially construct the objective function using Bayesian inference by combining seismic data in the time and frequency domain. We use Cauchy and Gaussian probability distribution density functions to obtain the prior information for the model parameters and the likelihood function, respectively. We estimate the elastic parameters by solving the initial objective function with added model constraints to improve the inversion robustness. The results of the synthetic data suggest that the frequency spectra of the estimated parameters are wider than those obtained with conventional elastic inversion in the time domain. In addition, the proposed inversion approach offers stronger antinoising compared to the inversion approach in the frequency domain. Furthermore, results from synthetic examples with added Gaussian noise demonstrate the robustness of the proposed approach. From the real data, we infer that more model parameter details can be reproduced with the proposed joint elastic inversion.

Time-domain compressive dictionary of attributed scattering center model for sparse representation

Parameter estimation of the attributed scattering center(ASC) model is significant for automatic target recognition(ATR). Sparse representation based parameter estimation methods have developed rapidly. Construction of the separable dictionary is a key issue for sparse representation technology. A compressive time-domain dictionary(TD) for ASC model is presented. Two-dimensional frequency domain responses of the ASC are produced and transformed into the time domain. Then these time domain responses are cutoff and stacked into vectors. These vectored time-domain responses are amalgamated to form the TD. Compared with the traditional frequency-domain dictionary(FD), the TD is a matrix that is quite spare and can markedly reduce the data size of the dictionary. Based on the basic TD construction method, we present four extended TD construction methods, which are available for different applications. In the experiments, the performance of the TD, including the basic model and the extended models, has been firstly analyzed in comparison with the FD. Secondly, an example of parameter estimation from SAR synthetic aperture radar(SAR) measurements of a target collected in an anechoic room is exhibited. Finally, a sparse image reconstruction example is from two apart apertures. Experimental results demonstrate the effectiveness and efficiency of the proposed TD.

异构平台要素协同理论方法研究

要素协同是协同作战发展的必经之路,杀伤链的动态重构是其典型特征.本文针对平台协同难以满足复杂作战任务需求的问题,提出了异构平台要素协同的解决思路和理论方法.首先分析了要素协同关系复杂性、协同能力不确定性两个难点问题;其次基于反馈机制的可重构架构对复杂作战网络进行建模,提出了杀伤链算子的要素动态重构、协同序参量的效能定量评估方法;最后基于仿真场景实现杀伤链的动态构建与重构,可指导要素协同的算法设计与工程实践.

改进势场蚁群算法优化路径自动规划

针对势场与蚁群联合的自主路径规划存在局部最优解、初始路径选择随机导致效率不高及环境适应性差等问题,提出了基于自适应域和参数自适应设置的改进算法。算法首先基于自适应域改进势场目标不可达问题,并过滤震荡点以平滑路径;其次,通过状态转移函数和信息素更新等相关参数的自适应设置,提高算法在收敛效率和搜索能力上的平衡性,进而提高对障碍环境的适应性。实验结果表明,所提算法能够有效避免局部最优、目标不可达和复杂环境的适应性问题,在路径长度和效率上优于实验采用的已有算法,从而验证了算法的有效性。

基于计算机视觉的公路边坡裂缝监测方法

为及时发现裂缝问题并减少潜在的危害,提出一种公路边坡裂缝的自动监测方法。以公路边坡裂缝为研究对象,针对裂缝图像形态不规则、周边环境干扰大的特点,设计了公路边坡裂缝分割网络(slope cracks segmentation network,SCSNet)和公路边坡裂缝几何参数计算方法。该网络首先采用编码器逐渐捕获更高层次的语义特征,其次采用解码器通过逐渐恢复空间信息并结合跳跃连接融合不同尺度间的信息,然后利用通道注意力机制,学习每个通道间的特征,增强裂缝的特征表达。另外,提出参数计算方法,基于连通域分析得到裂缝连通域,并计算裂缝长度、宽度、面积几何参数。实验结果表明:裂缝分割网络的平均交并比达87.86%,该网络能较好地提取公路边坡裂缝特征;裂缝几何参数计算方法能较准确地测算裂缝的当前状态。

计及线路分布参数的新能源场站谐波不稳定源头定位

现有新能源场站谐波不稳定分析大多采用线路集总参数模型,会遗漏高频固有模式,导致稳定性分析不准确;当计及线路分布参数后,难以直接求解系统固有模式,导致谐波不稳定分析困难且不稳定源头难以有效定位。基于此,提出基于泰勒逼近的计及线路分布参数的新能源场站谐波稳定性频域模态分析方法,通过泰勒逼近求解系统固有模式获得系统阻尼判定系统稳定性,并定义节点参与因子定位新能源场站谐波不稳定源头。分析结果表明:线路分布参数是诱发高频谐波放大的主导因素,忽略线路分布参数会遗漏高频谐波放大点并导致稳定性误判。所提方法可准确判定系统稳定性,并可定位谐波不稳定源头。仿真验证了所提方法的有效性和准确性。