Seismic acceleration signal analysis and application

Although various types of geophones are applied in seismic exploration,there are only three common types of signals produced by geophones:displacement,velocity,and acceleration signals.Currently,our understanding of the signal characteristics,such as the generation mechanism,the geophysical properties,and the significance of the corresponding rock physics,remains unclear,which makes it difficult to both scientifically evaluate and take full advantage of the different types of geophones.In this paper,the mechanism by which seismic waves are generated is studied based on the spring–damped vibration theory.The physical characteristics of the three above-mentioned signal types and the relationships among the physical properties of the signals and medium are analyzed,as well as the signalto-noise ratio(SNR),resolution,and spectrum characteristics.Based on laboratory tests,field experiments,and applications,we obtained the following conclusions.The acceleration signal reflects the elastic characteristics of the medium and the change rules,and the signal strength is positively correlated with physical property changes.The acceleration signal has favorable attributes,such as small distortion,high fidelity,strong high-frequency amplitudes,and a wide frequency band.Therefore,the acceleration signal is more suitable for high-precision seismic exploration of complex media.In addition,the P-wave acceleration signal more accurately reflects the elastic Young modulus,shear modulus,and density changes than the velocity signal.However,the sensitivity decreases with increasing shear modulus and density.For the S-wave,the acceleration signal is more sensitive to the shear modulus and density than the velocity signal.

Use of Accelerators for Biomechanical Analysis of Walking Motion Aided by Wheeled Walking Frames

Walkers improve self-reliability. We examined the effectiveness of a newly developed wheeled walking frame for use by physically handicapped persons. Unstable gaits in walker users were analyzed by tri-axial accelerometers and a motion capture system. Several markers were placed on subjects＇ backs and legs. Subjects were requested to walk around a test course at a comfortable speed, while their motion was recorded by two high-speed video cameras. The activities performed on the test course comprised standing, normal walking, fast walking, and walking over a barrier. Any accidental falls were also recorded. We established the characteristic rules of gait motion using a walker. Furthermore, we demonstrated that gait characteristics are more conveniently extracted from acceleration sensors than from motion capture systems, since the sensors can be affixed to subjects for self-monitoring and goal achievements. The methods employing acceleration sensors are considered suitable for determining the average gait motions of elderly persons living in nursing homes, and can be used to evaluate walking motion before and aider rehabilitation.

Experimental study of structural damage identification based on modal parameters and decay ratio of acceleration signals

A novel damage assessment method based on the decay ratio of acceleration signals(DRAS)was proposed.Two experimental tests were used to show the efficiency.Three beams were gradually damaged,and then the changes of dynamic parameters were monitored from initial to failure state.In addition,a new method was compared with the linear modal-based damage assessment using wavelet transform(WT).The results clearly show that DRAS increases in linear elasticity state and microcrack propagation state,while DRAS decreases in macrocrack propagation state.Preliminary analysis was developed considering the beat phenomenon in the nonlinear state to explain the turn point of DRAS.With better sensibility of damage than modal parameters,probably DRAS is a promising damage indicator in damage assessment.

Characterisation of Real-World Bus Acceleration and Deceleration Signals

Public transportation by bus is an essential part of mobility. Braking and starting, e.g., approaching a bus stop, are documented as the main reason for non-collision incidents. These situations are evoked by the acceleration forces leading to perturbations of the passenger’s base of support. In laboratory studies perturbations are applied to getting insight into the postural control system and neuromuscular responses. However, bus perturbations diverge from laboratory ones with respect to duration, maximum and shape, and it was shown recently that these characteristics influence the postural response. Thus, results from posturographic studies cannot be generalised and transferred to bus perturbations. In this study, acceleration (ACC) and deceleration (DEC) signals of real traffic situations were examined. A mathematical approach is proposed in order to identify characteristics of these signals and to quantify their similarity and complexity. Typical characteristics (duration, maximum, and shape) of real-world driving manoeuvres concerning start and stop situations could be identified. A mean duration of 13.6 s for ACC and 9.8 s for DEC signals was found which is clearly longer than laboratory perturbations. ACC and DEC signals are more complex than the used signals for platform displacements in the laboratory. The proposed method enables the reconstruction of bus ACC and DEC signals. The data can be used as input for studies on postural control with high ecological validity.

Research on velocity and acceleration geophones and their acquired information

Based on the research of two geophone types （10 Hz moving-coil velocity and piezoelectric acceleration） and their velocity and acceleration parameters, frequency response functions have been determined, as well as the differences between them. Also, shock- vibration tests have been accomplished, not only to explain the two shock response signal differences, but also to analyze the response signal characteristics and its ability to carry information. In addition, seismic data acquisition experiments have been carried out under comparable conditions in the field. A contrast analysis of shot gathers and stack profiles acquired with the two geophone types is given in this paper. The results show that the acceleration signal from the acceleration geophone has a better advantage in terms of high signal-to-noise ratio, high accuracy, high resolution, and quantity of information to better meet current and future requirements for seismic exploration.

基于概率的步行导致结构振动评估方法

提出一种基于概率的步行导致结构振动评估方法。现有的评估方法大致有三类:简化方法、基于频域的方法和基于时域的方法,都可以得到步行导致结构共振时产生的峰值加速度,但都没有考虑步行频率的概率分布,因此无法给出加速度值对应的超越概率。行人步行频率大部分分布在一个较窄的范围内,而且基本符合正态分布。该评估方法可以在计算结构竖向振动加速度的基础上,计算振动加速度的概率密度函数。从而可以确定各加速度值的超越概率,对结构振动的风险作出更准确的评估。在此基础上,可以选择具有一定保证率的结构振动加速度反应系数来代表结构的振动性能表现,建议办公建筑取95%保证率的反应系数,天桥结构取具有90%保证率的反应系数来代表结构的振动表现。

特种车辆多维载荷谱加速方法及在振动环境模拟试验中的应用

目的 解决车辆多轴轴耦合台架试验耗时长、花费大以及振动环境模拟精度低等问题。方法 将雨流投影方法运用到多维载荷加速处理中,利用传统雨流滤波法和多轴雨流投影滤波方法分别对特种车辆部件实际所受的多轴载荷进行加速处理,对加速后的多维载荷信号开展基于时域波形再现的振动环境模拟,以更有效地利用轮式车多轴轴耦合试验台开展加速疲劳试验。结果 对比加速前后的多维载荷信号,在时域、频域、损伤域基本一致的前提下,多维载荷信号时间压缩了50%,多轴振动环境的模拟精度大于80%。结论 采用该方法开展车轮加速疲劳试验,能够精确再现被试件的实际振动环境。通过实际试验验证,可以很好地再现故障出现的时间和形式,与实际野外路试结果十分吻合。

门槛阈值自匹配的车载呼救系统设计

为了提高车辆碰撞自动呼救系统(Automatic Crash Notification System,ACNS)的抗干扰能力和事故信息的准确性,提出了一种具有自适应门槛阈值的ACNS触发算法。基于门槛阈值与路面国际平整度指数之间的关联模型,设计ACNS触发算法,并实现ACNS门槛阈值随路面状况和车速的动态匹配;基于STM32F103ZET6微控制器,利用加速度信号采集模块、定位模块和通信模块等模块设计一种车辆事故自动呼救系统终端;利用道路实车试验和触发测试试验测试系统性能;结果表明:ACNS终端能够实现门槛阈值根据不同路面状况的动态匹配,并对相关信息进行实时处理及发送呼救信息。

基于线性调频连续波的合作式通信辐射源测距

针对加速运动目标参数估计中,离散多项式变换方法无法进行非整数估计的问题,本文提出基于瑞夫算法的离散多项式变换法和基于Chirp-Z变换的离散多项式变换法2种新型离散多项式变换算法,对加速运动目标速度和加速度进行估计,并对2种算法的估计误差和计算量进行了分析比较。结果表明:2种算法在信噪比-20 dB时均方误差开始接近克拉美罗界。基于瑞夫算法的离散多项式变换法与3次迭代基于Chirp-Z变换的离散多项式变换法均可在较低信噪比下可实现任意频率的有效估计且性能接近,二者均可实现低信噪比下速度、加速度的有效估计,但基于瑞夫算法的离散多项式变换法计算量远小于3次迭代基于Chirp-Z变换的离散多项式变换法。

基于NEON的VSIPL加速技术研究

针对航空及通信领域嵌入式信息处理软件的可移植性和实时性需求,提出了ARM平台下基于NEON的矢量信号图像处理函数库(VSIPL)中间件算法加速优化的方法。VSIPL中间件能够解决信号处理软件在不同平台的复用性问题,通过对VSIPL的数据特性进行分析,然后将NEON技术应用于VSIPL加速设计中,实现数据的并行处理以提高运算速率。最后,对VSIPL中的典型向量算法优化前后进行性能对比测试,并分析了不同因素对加速效果的影响,测试结果验证了加速方法的可行性。提出的基于NEON的VSIPL加速设计方法能有效提高信号处理软件的性能,具有一定的指导意义和工程应用价值。

Method for pedestrian signal timing at signalized intersections

The pedestrian timing at signalized intersections is studied aiming at the problems of the inconsistency of the vehicular and pedestrian timing requirements and the insufficiency of pedestrian clearance. Based on the formulae of WALK and flashing DON＇T WALK （FDW） in the highway capacity manual （HCM）, the relationship between pedestrian signal indications and vehicular signal indications is discussed using the theory of traffic flow. Then, methods of pedestrian timing for different cases are established, particularly the methods of the pedestrian green adjustment. Ways of pedestrian crossing are analyzed for roadways with different forms and widths of the median island. The sampling values of calculation parameters are studied, and the recommended formulae of pedestrian timing for different conditions are presented.

基于振动加速度与声音信号融合的轨道交通列车轴箱轴承故障诊断方法

[目的]轴箱轴承是轨道交通列车转向架的关键零部件,其健康状态直接影响列车的运行安全。需建立更为科学、高效的轴箱轴承故障诊断方法,以有效提取强干扰噪声下的轴承故障特征信息。[方法]以振动加速度及声音信号(以下简称“振声信号”)为研究目标,分析了轴箱轴承振声信号的故障特征,提出了一种最优带通卷积滤波的信号降噪方法。该方法将原始信号在频域内划分为多个分段,确定不同分段的带通滤波参数,构建了多通道带通卷积滤波器组。采用时域指标分段峭度来选择最优滤波信号,并对最优滤波信号进行频率加权能量算子解调,以识别轴承的故障部位。[结果及结论]所提故障诊断方法可以在强干扰噪声下实现对振动加速度信号、声音信号故障特征的提取,仿真结果及现场试验结果均验证了该诊断方法的有效性。振动加速度、声音信号的故障诊断结论可相互补充验证,进一步提高轴箱轴承故障诊断的准确率。

基于奇异值滤波的旋转装备转速提取

课题组针对无硬件测量设备的振动信号转速信息提取算法中存在频带不易确定和运算量大等问题,提出一种奇异值分解滤波的转速估计方法。先将振动加速度信号先作Hankel重构,再奇异值分解,然后利用差分奇异谱确定重构奇异分量,依据连续两个奇异分量确定一个频率成分,重构各频率分量信号,最后对重构分量作频谱分析估计当前转速。实验表明:奇异值分解滤波能有效提取信号中的频率分量,进而从振动加速度信号中提取转速信息。对比实验证明了课题组提出的方法具有频带自适应、易于实现和精度高的优势。

基于功率谱密度的地下水管道漏水点智能检测

为及时发现管道漏水问题,提高检测准确率,提出一种基于水声信号的地下水管道多漏水点检测方法。在地下水管道安装两个电压式加速度传感器,采集漏水信号,根据冲激响应函数、差分方程分析FIR滤波装置去噪原理,结合等波纹逼近、雷米兹算法设计其内部运算,完成漏水信号的去噪处理;使用功率谱密度描述信号频带分布情况,判断水管道是否漏水,若漏水,根据信号时延差及其在管道中的传播速度,确定漏水点位置。仿真结果表明,所提方法去噪效果好,能有效检测出水管道漏水点位置,且检测精度高,用时短,可广泛使用。

参数优化VMD-小波阈值的振动筛加速度信号降噪

为去除振动筛的加速度信号中伴随的噪声,提出一种使用鲸鱼优化算法(Whale Optimization Algorithm,WOA)优化变分模态分解(variational mode decomposition,VMD)-小波阈值的加速度信号降噪方法。使用WOA对VMD的模态分解数k和惩罚因子α进行寻优,将得到的最优参数代入VMD中,并根据设定好的阈值,对含噪有效分量进行降噪处理。经实际运行验证,参数优化VMD-小波阈值降噪方法能有效消除信号噪声。

基于启发式粗化算法的半监督图神经网络的训练加速框架及算法

图神经网络是当前阶段图机器学习的主流工具,发展势头强劲。通过构建抽象图结构,运用图神经网络模型能够高效地处理多种应用场景下的问题,包括节点预测、链接预测和图分类等方向。与之相对应,一直以来,在大规模图上的应用是图神经网络训练中的关键点和难点,如何有效、快速地在大规模图数据上进行图神经网络的训练和部署是阻碍图神经网络进一步工业化应用的一大难题。图神经网络因为能够利用图的网络结构的拓扑信息,所以在如节点预测的赛道上能够取得比一般其他神经网络如多层感知机等更好的效果,但是图的网络结构的节点个数和边的条数的规模增长制约了图神经网络的训练,真实数据集的节点数量规模达到千万级别甚至亿级别,或者是部分稠密的网络结构中边的数量规模亦达到了千万级别,使得传统的图神经网络训练方法均难以直接取得成效。针对以上问题,改进并提出了基于图粗化算法的新型图神经网络训练框架,并在此基础上提出了两种具体的训练算法,同时配合提出了两种简单的启发式图粗化算法。在精度损失可以接受和内存空间消耗大大降低的前提下,所提算法能够进一步显著地降低图神经网络的计算量,缩短训练时间,实验结果表明其在常见数据集上均能取得令人满意的成绩。

瓦里安C系列加速器枪系统与联锁原理分析和典型案例

瓦里安C系列高能直线加速器均采用三极(栅极控制)电子枪系统,其故障率较高、解决难度较大,多表现为剂量率不稳定甚至不能出束,报GFIL枪灯丝联锁。本研究以iX平台的代表——Clinac iX为例,结合典型案例和技术图纸阐述枪控制系统的工作原理,通过分析电源电路和枪驱动等关键模块内部和模块之间的信号处理的流程和方向,发现问题症结并处理元器件解决问题,为工程师安全高效解决C系列乃至电路集成度和数字化程度非常高、以VitalBeam为代表的新一代高端技术平台的加速器的同类问题,提供解决思路和方法借鉴。

基于头部姿态和肌电信号的意识丧失监测与唤醒系统

目的开发一套完整系统以监测飞行员持续性正加速度引发的意识丧失(G-LOC)并及时唤醒,从而缩短飞行员空中失能时间。方法本系统采用MPU6050惯性传感器和无锡市思知瑞科技有限公司生产的肌肉传感器实时获取飞行员所处环境的头部姿态和肌电特征,完成了系统硬件设计、主程序设计、头部姿态监测模块设计、肌电信号采集处理模块和上位机界面显示设计,并进行系统测试和离心机测试。系统测试通过预先采集被试2 min静息状态和肌肉收缩状态下的肌电信号、人体平视前方和极力低头的头部姿态角,个性化设定肌电信号和头部姿态角度的阈值,加速度阈值为测试环境下的重力加速度。离心机测试是通过在动物离心机上摆放姿态角的位置模拟人体抬头与低头的过程,加速度阈值设为3 G,此测试环境的正加速度为4、6、8 G。结果该系统能实时捕捉被测人员的头部姿态和肌电信号的生理特征,并及时发出语音提醒,在规定时间内未得到反馈(抬头、肌电恢复)能立即进入警报唤醒模式,且能在离心机上使用。结论该系统的功能完备、逻辑完整、实用性强,进一步实验完善后有实际应用的可能。

一种高精度测量IEPE加速度传感器的电路设计与应用

随着环境试验设备产业的快速发展,环境振动试验的需求日益增加,其中加速度的测量成为评估振动试验效果的关键参数,为了能精确获取环境振动试验中的加速度值,特别是在使用集成电路式压电传感器(IEPE加速度传感器)时,本文提出了一种针对IEPE加速度传感器的高精度测量电路设计方案。该电路方案旨在解决IEPE加速度传感器在振动试验中信号提前与处理的问题,电路主要包括传感器的恒流供电、信号调理、信号输出、电源管理和噪声抑制等模块。该电路成功实现了对IEPE加速度传感器的精确测量,并应用与环境振动试验箱中,为振动试验、工业监测、机械健康诊断等领域提供了可靠的测量手段。

基于信号捕获算法的非入侵式柔性压感睡眠呼吸检测护理系统

针对睡眠呼吸监测的实际需求,设计一款非侵入式的柔性压感睡眠呼吸检测系统。该系统尤其适用于医院、养老院等需要特殊护理的群体。该系统硬件能够利用高精度传感器在人体睡眠时捕捉细微的呼吸信号变化,并进行噪声消除和去趋势预处理。通过算法识别呼吸信号的周期和幅度特征,从而精准判断呼吸暂停的情况。该系统提供移动端和PC端的呼吸信号波形监测服务,以便全面监测和分析睡眠数据。经过实际应用验证,该系统的检测结果与实际观察结果高度一致,且在同类系统中表现出卓越的检测准确度。