融合加速度的桥梁位移响应倾斜摄影监测方法

桥梁的位移响应是结构健康监测和安全状态评估的基础数据。 为充分发挥计算机视觉测量结构位移的优势,并提高实 测位移的精度,本文提出了一种利用加速度与倾斜拍摄的视觉位移进行数据融合的高精度结构位移监测方法。 一方面,通过加 速度重构结构动位移,补充结构高频位移分量;另一方面,通过同频带加速度重构位移与视觉位移计算比例因子,减小像素坐标 向真实坐标转换的误差。 通过室内悬索桥模型实验和室外简支梁现场试验探索了本文方法的有效性。 在室内实验中,与线性 可变差动变压器位移计测量结果相比,本文方法的归一化均方根误差最大为 2. 70% ,比传统视觉测量方法降低约 60% 。 所提 出方法可推进计算机视觉在桥梁健康监测领域的进一步应用。     

基于机器视觉的大柔性结构振动位移测量

针对空间大柔性结构受到扰动后所产生的低频率、大幅值振动变形难以测量的问题,利用基于机器视觉的结构振动位移测量方法对此类结构的振动位移进行了测量,并识别了结构的动态特性。首先,理论分析了传统的对加速度信号直接积分获得位移的方法存在低频噪声被放大的问题并进行了实验论证;然后,研究了基于机器视觉的结构振动位移测量方法,进行了方法精确度与有效性的实验验证。实验中采用数码相机作为视觉传感器,对采集的结构振动视频进行图像处理,采用数字图像相关方法提取每帧图像特征点的位置信息,应用亚像素定位方法改进测量精度。将视觉位移测量方法获得的结构固有频率与加速度数据求得的结构固有频率进行比较,验证了基于机器视觉的振动位移测量方法在大柔性结构振动位移测量和动态特性识别方面的应用有效性。     

基于积分滤波器的位移信息获取

利用积分滤波器对加速度信号进行二次积分,从而获得物体的运动位移信息;为提高系统的稳定性和抗噪性,在积分前分别采用减平均值法和小波变换对加速度信号进行去直流量及去噪处理;通过仿真信号验证算法的正确性,降低了实验成本;最后利用采用XW-IMU5250惯性测量单元实测一个物体的运动,得到了物体精确的运动轨迹。     

Random displacement and acceleration responses of vehicles with uncertainty

Dynamic displacement and acceleration responses of cars with uncertain parameters under random road input excitations are investigated by using a quarter-car model. Based on the theory of random vibration, the vehicle’s random displacement and acceleration responses are developed in time domain and frequency domain. The sprung mass, unsprung mass, suspension damping, suspension and tire stiffness are considered as random variables. The mean value, standard deviation and variation coefficient of the vehicle’s natural frequencies and mode shapes are obtained by using the Monte-Carlo simulation method. The computational expressions for the numerical characteristics of the root mean square value of vehicle’s random displacement and acceleration responses in the frequency domain are developed by means of the random variable’s functional moment method and algebra synthesis method. The influences of the uncertainty of the vehicle’s parameters on the vehicle’s random responses are investigated in detail using a practical example, and some useful conclusions are obtained.     

Full-field dynamic strain reconstruction of an aero-engine blade from limited displacement responses

Blade strain distribution and its change with time are crucial for reliability analysis and residual life evaluation in blade vibration tests. Traditional strain measurements are achieved by strain gauges (SGs) in a contact manner at discrete positions on the blades. This study proposes a method of full-field and real-time strain reconstruction of an aero-engine blade based on limited displacement responses. Limited optical measured displacement responses are utilized to reconstruct the full-field strain. The full-field strain distribution is in-time visualized. A displacement-to-strain transformation matrix is derived on the basis of the blade mode shapes in the modal coordinate. The proposed method is validated on an aero-engine blade in numerical and experimental cases. Three discrete vibrational displacement responses measured by laser triangulation sensors are used to reconstruct the full-field strain over the whole operating time. The reconstructed strain responses are compared with the results measured by SGs and numerical simulation. The high consistency between the reconstructed and measured results demonstrates the accurate strain reconstructed by the method. This paper provides a low-cost, real-time, and visualized measurement of blade full-field dynamic strain using displacement response, where the traditional SGs would fail.     

基于 AKF 滤波器的时栅角位移动态误差抑制方法

动态测量下的谐波误差成分是制约高精度、高分辨率的时栅角位移传感器在动态测量领域运用的主要原因之一。针对动态测量下时栅角位移传感器中的谐波抑制难题,首先简述了时栅角位移传感器的系统模型,其次建立了时栅角位移传感器的动态误差数学模型,之后解释了传感器的动态误差产生机理,阐述了自适应卡尔曼滤波的基本原理,最后构建了基于自适应卡尔曼滤波的时栅角位移传感器的动态误差抑制模型。通过仿真分析证明了时栅角位移传感器在匀速和变速运行情况下,经自适应卡尔曼滤波后,动态误差均降低了约70%,且随着传感器转速的提高,对谐波误差的抑制效果越明显。在实验运用中,该滤波算法对时栅角位移传感器的测量值有很好的实时预测性,传感器能够更快速且稳定运行,在100 r/min的转速下测量误差降低约80%。结果证实了自适应卡尔曼滤波在时栅角位移传感器的动态谐波误差抑制中有着显著的作用,能极大地提高传感器的动态测量精度。     

Multi-rate Kalman filtering for the data fusion of displacement and acceleration response measurements in dynamic system monitoring

Many damage detection and system identification approaches benefit from the availability of both acceleration and displacement measurements. This is particularly true in the case of suspected non-linear behavior and permanent deformations. In civil and mechanical structural modeling accelerometers are most often used, however displacement sensors, such as non-contact optical techniques as well as GPS-based methods for civil structures are becoming more common. It is suggested, where possible, to exploit the inherent redundancy in the sensor information and combine the collocated acceleration and displacement measurements in a manner which yields highly accurate motion data. This circumvents problematic integration of accelerometer data that causes low-frequency noise amplification, and potentially more problematic differentiation of displacement measurements which amplify high-frequency noise. Another common feature of displacement-based sensing is that the high-frequency resolution is limited, and often relatively low sampling rates are used. In contrast, accelerometers are often more accurate for higher frequencies and higher sampling rates are often available. The fusion of these two data types must, therefore, combine data sampled at different frequencies. A multi-rate Kalman filtering approach is proposed to solve this problem. In addition, a smoothing step is introduced to obtain improved accuracy in the displacement estimate when it is sampled at lower rates than the corresponding acceleration measurement. Through trials with simulated data the procedure's effectiveness is shown to be quite robust at a variety of noise levels and relative sample rates for this practical problem.     

位移响应优化设计方法及工程应用

通过研究在动力激励下结构响应的物理量位移为目标或约束的结构动力学优化设计,利用解析的方法,推导出动力位移响应灵敏度计算公式,并成功地移植到有限元程序中.在计算包括杆、梁、板、二维、三维单元在内的所有例子中,用该程序计算出的动力位移响应的灵敏度精度可达到97%以上,并且迭代次数少,求解效率高.     

Retrieving the time history of displacement from measured acceleration signal

It is intended to retrieve the time history of displacement from measured acceleration signal. In this study, the word retrieving means reconstructing the time history of original displacement signal from already measured acceleration signal not just extracting various information using relevant signal processing techniques. Unlike extracting required information from the signal, there are not many options to apply to retrieve the time history of displacement signal, once the acceleration signal is measured and recorded with given sampling rate. There are two methods, in general, to convert measured acceleration signal into displacement signal. One is directly integrating the acceleration signal in time domain. The other is dividing the Fourier transformed acceleration signal by the scale factor of -ω² and taking the inverse Fourier transform of it. It turned out both the methods produced a significant amount of errors depending on the sampling resolution in time and frequency domain when digitizing the acceleration signals. A simple and effective way to convert the time history of acceleration signal into the time history of displacement signal without significant errors is studied here with the analysis on the errors involved in the conversion process.     

Vision-based structural displacement measurement: System performance evaluation and influence factor analysis

In the past decade, the emerging machine vision-based measurement technology has gained great concerns among civil engineers due to its overwhelming merits of non-contact, long-distance, and high-resolution. A critical issue regarding to the measurement performance and accuracy of the vision-based system is how to identify and eliminate the systematic and unsystematic error sources. In this paper, a vision-based structural displacement measurement system integrated with a digital image processing approach is developed. The performance of the developed vision-based system is evaluated by comparing the results simultaneously obtained by the vision-based system and those measured by the magnetostrictive displacement sensor (MDS). A series of experiments are conducted on a shaking table to examine the influence factors which will affect the accuracy and stability of the vision-based system. It is demonstrated that illumination and vapor have a critical effect on the measurement results of the vision-based system.     

一种新型的基于PSoC3的高精度位移测量仪

为降低基于线性可调差动变压器(LVDT)的高精度位移测量仪的生产成本,并减小其产品体积,使产品更具市场竞争力,在分析其工作原理基础上,结合PSoC3"相比于传统单片机,更具系统单片化"的特点,提出了以CY8C3866AXI为核心的新型位移测量系统设计方案。该方案通过运用PSoC3内部的数字模块(DMA和LCD)与模拟模块(AD、DA、PGA等),自行设计了由整流电路、滤波电路和减法电路组成的信号调制电路,完全替代了目前市场上常用的AD698信号调制芯片和ARM控制器的产品组合结构,实现了位移高精度测量,测量精度可达到0.2μm。研究结果表明,该方案具有集成度高、线性度好、成本低廉等优点。     

基于时间参考点的差动式线阵CCD位移传感器

为了将线阵CCD应用于实际工程的大尺寸位移测量,利用线阵CCD像元空间与输出时间的对应关系,提出了一种差动式测量的线阵CCD位移传感器测量系统。分析了线阵CCD位移测量存在的问题,结合线阵CCD中像元空间与驱动脉冲之间的对应关系,提出一种以时间为参考点的差动式测量方法。该方法用两个空间上对齐、时间上错开半个积分周期的线阵CCD检测透光挡板上等间距分布的透光光线的位置变化;通过计算两个CCD上输出光信号的时间差,用匀速扫描测量原理实现对空间位移的测量。用雷尼绍激光干涉仪对所研制的线阵CCD位移传感器进行了校准,结果显示：在有效测量范围（600.05 mm）内,经过修正后的测量误差可控制在±2 μm以内,验证了用差动法实现线阵CCD大尺寸精密位移测量的可行性。     

基于模板匹配算法的压电微位移器位移量原位测量技术

针对压电微位移器的位移量高精度测量需要,基于模板匹配算法提出了一种新颖的位移量原位测量方法。利用改进型的Twyman-Green干涉系统对压电微位移器的电压——位移特性曲线进行原位测量,根据模板匹配算法实时计算干涉条纹的移动量,进而得到对应的压电微位移量,并对相关实验测量结果进行了分析与验证。结果表明,该测量技术具有较高的测量效率以及较好的随机噪声抑制能力,其测量精度和分辨率均可达到纳米量级。该方法属于非接触式测量,具有较高的可靠性,在微位移的高精度原位自动测量中具有较好的实用性。     

Measuring displacement signal with an accelerometer

An effective and simple way to reconstruct displacement signal from a measured acceleration signal is proposed in this paper. To reconstruct displacement signal by means of double-integrating the time domain acceleration signal, the Nyquist frequency of the digital sampling of the acceleration signal should be much higher than the highest frequency component of the signal. On the other hand, to reconstruct displacement signal by taking the inverse Fourier transform, the magnitude of the significant frequency components of the Fourier transform of the acceleration signal should be greater than the 6 dB increment line along the frequency axis. With a predetermined resolution in time and frequency domain, determined by the sampling rate to measure and record the original signal, reconstructing high-frequency signals in the time domain and reconstructing low-frequency signals in the frequency domain will produce biased errors. Furthermore, because of the DC components inevitably included in the sampling process, low-frequency components of the signals are overestimated when displacement signals are reconstructed from the Fourier transform of the acceleration signal. The proposed method utilizes curve-fitting around the significant frequency components of the Fourier transform of the acceleration signal before it is inverse-Fourier transformed. Curve-fitting around the dominant frequency components provides much better results than simply ignoring the insignificant frequency components of the signal.     

Study on out-off-plane displacement measurement using DSPI under impact loading

In this paper, the measuring technique of out-off-plane displacement under impact loading using DSPI is presented. In order to capture the speckle field produced by a Ruby laser, an instantaneous digital image capturing system is introduced. The dynamic speckle images are able to be recorded and stored directly in a digital frame store. Thus digital speckle pattern interferometry (DSPI) is achieved for dynamic measurement. As an example, the measurement of out-off-plane displacement field of circular fixed plate with a concentrative impact loading is completed. The results of the dynamic finite element method show agreement with those of experiments.     

基于支持向量机时栅数控转台时序预测研究

时栅代替光栅等传统位移传感器运用到全闭环数控转台做角位移检测部件,需采用时空变换算法将时栅的时域信息转换到空域信息。运用时间序列分析出时栅数控转台的测试数据依存特性,采用支持向量机建立起未来测试数据和历史样本的映射关系,从而得到测试数据中隐含的规律。依据过去相关测量值采用支持向量机回归预测下一采样时刻角位移,将原本等时采样的绝对式角位移转换为全闭合数控系统需要的等空间增量式连续脉冲。并且在误差控制方面,采用当前预测值对上一次预测误差进行实时修正,消除累计误差保证测量精度。实验证明支持向量回归的时间序列预测算法能有效保证动态数控角位移测量误差控制在±2.5″以内,实现精密全闭环角位移测量。     

Normal displacement and dynamic friction characteristics in a stick-slip process

The dynamic friction-velocity relationship in the slip stage of stick-slip vibration was investigated with a pin-on-flat apparatus. A reasonable relationship was derived from the measured displacement and acceleration of the sliding element, using a computing technique which provided smooth, reliable curves. It was found, from an examination of the effect of data smoothing on computed friction characteristics, that the moving average method can be recommended. Variation of normal displacement of the sliding body during the slip period was examined together with tangential displacement and electrical contact resistance. The friction-velocity relationship was well explained by an assumption that the instantaneous friction variation results from the change in real area of contact resulting from normal displacement occuring in an elastic contact.     

基于时间序列的时栅数控转台动态建模研究

时栅运用到全闭环数控转台作位置检测传感器时,需采用时空变换算法将时栅的时域信息转换成空域信息。利用时间序列对时栅数控转台的动态特性进行建模,依据一系列过去测量值预测下一采样时刻角位移,将原本等时采样的绝对式角位移转换为全闭合数控系统需求的等空间增量式连续脉冲。介绍了动态模型选择标准、参数估计、模型检验的原理和算法。采用当前预测值对上一次预测误差进行实时修正,以消除累计误差保证测量精度。实验证明了采用动态模型预测算法能保证动态数控角位移测量误差控制在±3″以内,实现了精密动态全闭环角位移测量。     

交通荷载作用下桥梁结构参数识别方法

应用动力节点加载法,将作用在桥梁上的交通荷载转化为等效节点荷载,再用两步构造法识别结构物理参数.第1步,用Newmark-β方法变换结构运动方程,并用结构的加速度响应求得变换空间内的位移、速度和加速度响应;第2步,基于最小二乘原理,构造出变换空间内求解结构参数的递推式,进行结构物理参数识别.数值模拟结果表明,在交通荷载作用下,该方法能够快速、准确地进行桥梁结构参数识别.     

振动信号频域积分的滤波修正算法

机械故障诊断中,通过振动信号的软件积分可以实现振动加速度、速度信号向位移信号的转换。为了消除信号中噪声对软件积分结果的影响,分析了软件积分在振动信号积分中趋势项产生的原因,提出了基于传感器低频滤波与阀值滤波修正的频域积分算法。方法简单实用,消除了软件积分结果中的摆动趋势。数值仿真结果与实测结果表明,方法抗噪声能力强,具有很好的精度和通用性,目前已经应用于旋转机械状态监测与故障诊断系统中,为判断机组运行状态提供了很好的依据。