IDENTIFICATION OF NONLINEAR DYNAMIC SYSTEMS:TIME-FREQUENCY FILTERING AND SKELETON CURVES

The nonlinear behavior varying with the instantaneous response was analyzed through the joint time-frequency analysis method for a class of S. D. O. F nonlinear system. A masking operator an definite regions is defined and two theorems are presented. Based on these, the nonlinear system is modeled with a special time-varying linear one, called the generalized skeleton linear system (GSLS). The frequency skeleton curve and the damping skeleton curve are defined to describe the main feature of the non-linearity as well. Moreover, an identification method is proposed through the skeleton curves and the time-frequency filtering technique.

A NEW SYSTEM DYNAMIC EXTREMUM SELF-SEARCHING METHOD BASED ON CORRELATION ANALYSIS

Objective To propose a new dynamic extremum self searching method, which can be used in industrial processes extremum optimum control systems, to overcome the disadvantages of traditional method. Methods This algorithm is based on correlation analysis. A pseudo random binary signal m sequence u(t) is added as probe signal in system input, construct cross correlation function between system input and output, the next step hunting direction is judged by the differential sign. Results Compared with traditional algorithm such as step forward hunting method, the iterative efficient, hunting precision and anti interference ability of the correlation analysis method is obvious over the traditional algorithm. The computer simulation experimental given illustrate these viewpoints. Conclusion The correlation analysis method can settle the optimum state point of device operating process. It has the advantage of easy condition , simple calculate process.

Loss-of-Main Monitoring and Detection for Distributed Generations Using Dynamic Principal Component Analysis

In this paper, our previous work on Principal Component Analysis (PCA) based fault detection method is extended to the dynamic monitoring and detection of loss-of-main in power systems using wide-area synchrophasor measurements. In the previous work, a static PCA model was built and verified to be capable of detecting and extracting system faulty events;however the false alarm rate is high. To address this problem, this paper uses a well-known ‘time lag shift’ method to include dynamic behavior of the PCA model based on the synchronized measurements from Phasor Measurement Units (PMU), which is named as the Dynamic Principal Component Analysis (DPCA). Compared with the static PCA approach as well as the traditional passive mechanisms of loss-of-main detection, the proposed DPCA procedure describes how the synchrophasors are linearly auto- and cross-correlated, based on conducting the singular value decomposition on the augmented time lagged synchrophasor matrix. Similar to the static PCA method, two statistics, namely T2 and Q with confidence limits are calculated to form intuitive charts for engineers or operators to monitor the loss-of-main situation in real time. The effectiveness of the proposed methodology is evaluated on the loss-of-main monitoring of a real system, where the historic data are recorded from PMUs installed in several locations in the UK/Ireland power system.

Dynamics modeling and electromechanical coupling characteristics analysis of cage induction motors

Induction motors, as typical electromechanical energy conversion devices, have received limited attention in previous studies on electromechanical coupling vibrations, precise modeling, and the use of electromechanical coupling effects for fault diagnosis and condition assessment in motor drive systems. This study proposes a comprehensive model of cage induction motors that integrates the multiple coupled circuit model with a rotor-bearing dynamics model. The model accounts for the linear increase in the magnetomotive force across the slot and incorporates the skidding characteristics of bearings in the rotor-bearing system. By calculating the time-varying mutual inductance parameters based on the air-gap distribution in the vibration environment, the electromechanical coupling vibration of the cage motor is investigated. Furthermore, this study examines the electromechanical coupling vibration characteristics influenced by various factors, including bearing clearances, radial loads, and the vertical excitation frequencies of the stators. The results show that the proposed model improves the excitation inputs for the electrical and mechanical systems of the motor compared with conventional models. Increased bearing clearance and radial load affect the current and torque similarly but have opposite effects on the slip ratio. This study provides a deeper understanding of electromechanical coupling mechanisms and facilitates the use of such phenomena for fault diagnosis and condition assessment in motor-driven systems.

Correlation study between ground motion intensity measure parameters and deformation demands for bilinear SDOF systems

The correlation between ground motion intensity measures （IM） and single-degree-of-freedom （SDOF） deformation demands is described in this study. Peak ground acceleration （APG）, peak ground velocity （VPG）, peak ground displacement （DPG）, spectral acceleration at the first-mode period of vibration [As（T1）] and ratio of VPG to APG are used as IM parameters, and the correlation is characterized by correlation coefficients p. The numerical results obtained by nonlinear dynamic analyses have shown good correlation between As（T1） or VPG and deformation demands. Furthermore, the effect of As（T1） and VPG as IM on the dispersion of the mean value of deformation demands is also investigated for SDOF systems with three different periods T=0.3 s, 1.0 s, 3.0 s respectively.

Importance Measure Analysis for Use in Dynamic Performance Design of a Co-cured Composite Damping Instrument Panel

For the best dynamic performance of a co-cured composite damping instrument panel with light weight and high strength,a multilayer sandwich structure with polymethacrylimide( PMI) foam combined with embedded and co-cured composite damping structure is proposed. The structue can maintain the excellent mechanical properties of composite materials,and achieve the damping and light effect at the same time. Input variables which may affect the dynamic performance of the instrument panel were selected and variance based importance measure was analyzed through multifinite element method( FEM) analysis. Using the results of the importance measure analysis,with other design requirements,the important design variable was optimized and an instrument panel with the best dynamic performance under the requirements of light weight and high strength was obtained. The structure of the instrument panel can provide reference for the design of precision,high speed,and dynamic composite component. The importance measure analysis of dynamic performance of the instrument panel can provide a reference for relative design.

Quantitative modeling of bacterial quorum sensing dynamics in time and space

Quorum sensing (QS) refers to the cell communication through signaling molecules that regulate many important biological functions of bacteria by monitoring their population density. Although a wide spectrum of studies on the QS system mechanisms have been carried out in experiments, mathematical modeling to explore the QS system has become a powerful approach as well. In this paper, we review the research progress of network modeling in bacterial QS to capture the system's underlying mechanisms. There are four types of QS system models for bacteria: the Gram-negative QS system model, the Gram-positive QS system model, the model for both Gram-negative and Gram-positive QS system, and the synthetic QS system model. These QS system models are mostly described by the ordinary differential equations (ODE) or partial differential equations (PDE) to study the changes of signaling molecule dynamics in time and space and the cell population density variations. Besides the deterministic simulations, the stochastic modeling approaches have also been introduced to discuss the noise effects on kinetics in QS systems. Taken together, these current modeling efforts advance our understanding of the QS system by providing systematic and quantitative dynamics description, which can hardly be obtained in experiments.

Characteristic Analysis of DS18B20 Temperature Sensor in the High-voltage Transmission Lines’ Dynamic Capacity Increase

Dynamic capacity increase in high voltage electric power transmission line is currently the most economical method for solving electric power transmission bottleneck nowadays. DS18B20 temperature sensor is applied to the dynamic capacity increase of high voltage transmission lines to measure the conductor temperature and ambient temperature. The paper is focused on the experiment of DS18B20 both in the laboratory and outside. From the result of the lab temperature measurement data analysis, using 4 DS18B20’s is the most suitable plan, considering both accuracy and economical efficiency. In the experiment outside, we get four groups of conductor (uncharged) temperature and four groups of ambient temperature. The data proved that DS18B20 has good stability, and small measurement error. It is suitable for measuring the temperature of conductor and ambient in dynamic capacity increase, and helpful to improve the accuracy of the calculation of capacity increasing.

Comparative Analysis of EEG Signals Based on Complexity Measure

The aim of this study is to identify the functions and states of the brains according to the values of the complexity measure of the EEG signals. The EEG signals of 30 normal samples and 30 patient samples are collected. Based on the preprocessing for the raw data, a computational program for complexity measure is compiled and the complexity measures of all samples are calculated. The mean value and standard error of complexity measure of control group is as 0.33 and 0.10, and the normal group is as 0.53 and 0.08. When the confidence degree is 0.05, the confidence interval of the normal population mean of complexity measures for the control group is (0.2871,0.3652), and (0.4944,0.5552) for the normal group. The statistic results show that the normal samples and patient samples can be clearly distinguished by the value of measures. In clinical medicine, the results can be used to be a reference to evaluate the function or state, to diagnose disease, to monitor the rehabilitation progress of the brain.

Power-V诱导的钻柱黏滑振动特征分析

黏滑是石油钻井过程中影响钻井效率和井下钻柱安全的一种振动形式.垂直钻井系统Power-V在提供有效控斜力的同时,还会诱导钻柱黏滑振动.通过研究垂直钻井系统Power-V与井壁的接触作用及钻头与地层的相互作用模型,基于钻柱动力学有限元方法,深入分析Power-V的作用机理,研究其对扭转振动的影响,指出Power-V和井壁间的相互作用会导致钻柱与井壁的摩阻显著增加,进而引起摩阻扭矩的增大,诱导井下黏滑振动.实测振动数据证实,Power-V与井壁间的相互作用是引起钻柱黏滑振动的关键因素.这对于揭示黏滑振动的成因和更好地发挥Power-V的作用具有重要意义.

盾构直削始发方案研究

随着盾构施工工艺的发展,越来越多的工程开始采用盾构直削始发.盾构法施工中,始发是易发生事故的重要环节.相对于传统的人工凿除洞门,直削始发时刀盘直接切割洞门,避免了掌子面土体形成临空面,从而降低了施工风险.以郑州某地铁区间隧道工程盾构直削始发为例,采用Midas GTS NX有限元软件,考虑洞门破除及盾构动态掘进的影响,对盾构直削始发时围护结构变形、土体变形和周围管线变形等进行了计算分析,验证了盾构端头直削始发方案的合理性.为验证数值模拟的可靠性,将数值计算结果和现场监测结果进行了对比分析,对比结果显示二者的变化规律一致,表明数值模拟结果合理.

复杂电能信号谐波时频域特征分析及其对电能计量影响

为准确分析复杂电能信号谐波时频域特性对电能计量的影响,提出了一种零值搜索-短时傅里叶变换时频域电压、电流信号幅度和相位分析算法,利用信号波形过零特征,自适应调整短窗傅里叶变换的时域窗宽,解决了电网频率波动导致的相位累积效应对相位分析的影响,算法的幅值分析误差为10-3、相位分析误差小于1°;建立了复杂电能信号时频域数据表征模型和4类时频域全局化特征矩阵提取算法,解决了时频域特性表征与提取的问题;以典型非线性动态负荷中频炉为分析案例,分析给出了其4类时频域全局化特征,并建立了畸变波形动态电能测试信号特征模型,通过辅助实验验证了4个时频域全局化特征对电能表动态超差的影响,提出了对国际和国内标准修改的建议。

基于手机信令数据的城市居民动态OD矩阵提取方法

现有的城市居民出行调查周期较长,交通小区划分粒度粗糙,导致调查不能及时准确地获取居民出行信息。针对该问题,提出了一种基于手机信令数据的城市居民动态OD矩阵提取方法。首先,针对信令数据中的两种复杂噪声:乒乓切换和漂移数据,提出了基于窗口阈值的检测与等效位置替换方法,以及复杂漂移点的检测和标记处理方法;然后,提出一种改进的ST-DBSCAN聚类方法,引入一种等时化方法将时间信息与空间信息相结合,识别出行过程中的驻留点;最后,基于地理信息系统构建含有道路关键节点的路网,将居民出行OD与路网节点相匹配,有效推导出城市居民动态OD矩阵。实验结果表明:与ST-DBSCAN算法相比,所提改进的ST-DBSCAN算法在聚类效果和识别速度上分别提升了6.10%和5.26%;与统计方法和二阶统计量方法相比,基于改进的ST-DBSCAN算法的动态OD矩阵提取方法在均方误差(MSE)上分别降低了16.98%和21.55%。以北京市为例,运用提出的动态OD矩阵提取方法,能够及时有效地分析城市居民日常与高峰时段的出行特征。

基于地下结构整体损伤表征的复合地震动参数构造及其性能验证

在地下结构抗震设计中,不同的输入地震动引起的地下结构响应有显著差异,因此,合理通过地震动参数选择输入地震动是正确开展地下结构抗震设计的重要前提。针对单一地震动参数难以表征地下结构地震动潜在破坏势问题,文章构造了能更好表征地下结构损伤破坏的复合地震动参数。具体开展了以下工作:提出基于变形与滞回耗能的地下结构整体损伤指标作为结构需求参数,以定量化评估地下结构的整体破坏状态。选取64条真实地震动记录作为输入地震动,开展四层三跨地铁车站地震弹塑性动力时程分析。基于分析结果提供的数据样本,采用偏最小二乘法从统计角度构造复合地震动参数。最后,选用100条真实地震动记录开展两层三跨地铁车站弹塑性动力时程分析,对文章所构造的复合地震动参数进行验证。对比分析复合地震动参数、12个常用地震动参数与地下结构整体损伤指数的回归统计特征。结果表明:复合地震动参数与结构需求数之间具有更好拟合优度值,其Pearson相关性、有效性也优于单一地震动参数。

基于振动信号PSD-SVM方法的不定负荷下柴油机气阀间隙异常故障诊断

针对许多基于振动信号的故障诊断方法在不同负荷下的诊断不全面的问题。提出了一种基于功率谱密度(power spectral density,PSD)与支持向量机(support vector machine,SVM)的故障诊断方法。该方法将振动信号功率经过滑动平均滤波(moving average filter,MAF)处理,计算样本中每个周期的标准化信号的功率谱特征,再使用核方法SVM进行特征分类,从而实现故障诊断。经过柴油机实机测试,该方法对于不同负荷下的故障识别率达到96.72%,能有效识别不同负荷下的柴油机进排气阀间隙增大故障。

行星传动系统均载与动载系数试验测量改进设计

试验测量行星传动系统均载与动载系数的精准度是评价系统动态性能的基础。针对现有行星传动系统均载与动载系数测量方法存在灵敏度与精度欠佳、系数测试算法缺失、测试应力点存误等问题,本文提出了一种方便、实用且具有高精度的行星传动系统均载与动载系数测试方法,定义了系统系数的测试算法与概念,明确了精确应力测试位置点及不同位置间差异性,采用应变片电桥传感器串并联设计,实现了拉压应力叠加、温度补偿以及繁琐标定免除等优点,为精准测取行星传动系统均载与动载性能提供了重要的理论基础和技术手段。

基于矢量IMs的浅埋偏压黄土隧道地震易损性

为从概率角度对浅埋偏压黄土隧道的地震易损性进行定量评价,采用基于黏弹性边界的波动输入方法,并通过增量动力分析对土-结构相互作用有限元模型进行大量非线性动力时程计算,评估20个地震动强度参数(IMs),然后基于标量IM和矢量IMs分别对浅埋偏压黄土隧道展开地震易损性分析.结果表明:地表峰值速度(效益性指标ζ=0.15)是最适合的IM,其次是速度谱强度(ζ=0.20)和谱速度峰值(ζ=0.22);相比于标量IM,基于矢量IMs的拟合效果更好,可降低结构损伤预测的离散性;在建立地震易损性曲面时需考虑2个IMs之间相关性的影响以确定曲面的有效取值范围;采用标量IM会低估或高估隧道实际的损伤概率.基于矢量IMs可对隧道的地震易损性作出更准确的评估.

某离心压气机转子叶尖流场测试及可视化分析

对壁面动态压力传感器阵列测试技术进行了研究,并将该技术应用于某离心压气机转子叶尖的动态流场测试中,获取了大量的动态流场测试数据。采用锁相技术和线性插值方法对测试数据进行了处理和分析,并采用数据可视化技术将动态数据转化成压力分布云图,从云图中可以清楚看出离心压气机不同工作状态下转子叶尖的压力变化,有助于分析转子叶尖处泄漏流、前缘溢流以及泄漏流和分流叶片前缘的相互作用。转子叶尖流场测试及可视化分析结果可以为压气机性能验证和数值模拟方法的修正提供重要的技术支撑。

基于PMU梯度动态偏差的新型电力系统快速稳定性

在能源转型和科技进步双重推动下,高比例可再生能源和高比例电力电子设备正成为电力系统发展重要趋势和关键特征.新型电力系统动态行为随之发生重大变化,传统小干扰稳定性分析方法满足使用需要,在应对运行工况快速变化场合时尚存在亟需解决问题.提出基于同步相量测量装置(PMU)数据梯度动态偏差李雅普诺夫直接分析法对新型电力系统小干扰稳定性进行分析,利用PMU数据矩阵降维得到低维矩阵,代入含双馈异步风力发电机组的电力系统矩阵模型,求解李雅普诺夫方程式得到对角矩阵,通过判定矩阵正定性对系统稳定性作出判断.利用求解后得到的对角矩阵计算相应状态变量动态偏差值,对相应状态变量曲线使用梯度下降法迭代计算该曲线极值点数值,时间加权计算整个振荡过程时间加权动态偏差量,为阻尼稳定控制器配置位置提供指导.利用含风力发电新英格兰10机39节点系统仿真验证方法可以达到改善系统小干扰稳定性以及对新型电力系统快速稳定性分析的有效性.

新型电力系统动态电能测量技术及其标准化研究

以新能源为主体的新型电力系统是促进现代电力系统低碳转型发展的重要前提与必然趋势。在新型电力系统中,新能源占比提高,非线性电力电子设备大量应用,使得电力系统的动态复杂性日益凸显。电网波形失真、可再生能源双向测量等新型运行工况对电能动态测量技术提出了更高要求。针对新型电力系统中动态电能测量面临的问题和挑战,首先分析了典型业务场景下动态电能测量技术特征与标准化需求,然后综述了动态电能信号构建、动态电能测量、动态电能测量评价等关键技术现状及其在新型电力系统场景下面临的核心问题,然后总结了动态电能测量关键技术及其标准化发展趋势,提出了新型电力系统场景下动态电能测量标准体系框架。相关研究为新型电力系统建设和动态测量技术发展及标准体系完善提供方向指引。