Design and validation of wireless acceleration sensor network for structural health monitoring

A wireless sensor network is proposed to monitor the acceleration of structures for the purpose of structural health monitoring of civil engineering structures. Using commercially available parts, several modules are constructed and integrated into complete wireless sensors and base stations. The communication protocol is designed and the fusion arithmetic of the temperature and acceleration is embedded in the wireless sensor node so that the measured acceleration values are more accurate. Measures are adopted to finish energy optimization, which is an important issue for a wireless sensor network. The test is perfonned on an offshore platform model, and the experimental results are given to show the feasibility of the designed wireless sensor network .

Design and Fabrication of a Bio-inspired Acceleration Sensor Using Liquid Mass Blocks

A linear acceleration sensor,which is inspired by the human balance organ,is designed and prepared. It uses a liquid mass-block and a symmetrical-electrodes metal-core polyvinylidene fluoride fiber(SMPF)as the sensor element. The output signal of the sensor has an exponential relationship with the excitation amplitude of the impacting vibration. It is capable of detecting the amplitude and the correct frequency for sinusoidal excitations using an exponential correlation. The experiments indicate that both the output signal of the sensor and the resonance frequency increase substantially with increasing diameter of the metal core. The first-order resonance frequencies of the sensors with 40,60,and 80 μm diameter metal wires are below 10 Hz,which is near the range of human body motion frequencies.

Accelerated Particle Swarm Optimization Algorithm for Efficient Cluster Head Selection in WSN

Numerous wireless networks have emerged that can be used for short communication ranges where the infrastructure-based networks may fail because of their installation and cost.One of them is a sensor network with embedded sensors working as the primary nodes,termed Wireless Sensor Networks(WSNs),in which numerous sensors are connected to at least one Base Station(BS).These sensors gather information from the environment and transmit it to a BS or gathering location.WSNs have several challenges,including throughput,energy usage,and network lifetime concerns.Different strategies have been applied to get over these restrictions.Clustering may,therefore,be thought of as the best way to solve such issues.Consequently,it is crucial to analyze effective Cluster Head(CH)selection to maximize efficiency throughput,extend the network lifetime,and minimize energy consumption.This paper proposed an Accelerated Particle Swarm Optimization(APSO)algorithm based on the Low Energy Adaptive Clustering Hierarchy(LEACH),Neighboring Based Energy Efficient Routing(NBEER),Cooperative Energy Efficient Routing(CEER),and Cooperative Relay Neighboring Based Energy Efficient Routing(CR-NBEER)techniques.With the help of APSO in the implementation of the WSN,the main methodology of this article has taken place.The simulation findings in this study demonstrated that the suggested approach uses less energy,with respective energy consumption ranges of 0.1441 to 0.013 for 5 CH,1.003 to 0.0521 for 10 CH,and 0.1734 to 0.0911 for 15 CH.The sending packets ratio was also raised for all three CH selection scenarios,increasing from 659 to 1730.The number of dead nodes likewise dropped for the given combination,falling between 71 and 66.The network lifetime was deemed to have risen based on the results found.A hybrid with a few valuable parameters can further improve the suggested APSO-based protocol.Similar to underwater,WSN can make use of the proposed protocol.The overall results have been evaluated and compared with the existing approaches of sensor networks.

Experimental study on the accumulative effect of multiple pulses on acceleration sensor

Intentional electromagnetic interference is a serious threat to the safety of electronic devices. Multiple electromagnetic pulses will be coupled and transmitted to electronic devices through the cables.Accumulative effects are generated, which make it easier for damage to occur in the electronic devices. In this article, the working principle of micro-silicon acceleration sensors is introduced. The accumulative effects of multiple pulses on acceleration sensors is studied by a large number of injection experiments.The accumulation trends of multiple pulses with different pulse numbers and intervals are analyzed. The damaged structures inside abnormal sensor amplifiers were observed via optical microscopy and scanning electron microscopy. The experimental results show that the accumulative effect is strengthened with increased pulse number or decreased pulse interval, and the threshold voltage for multiple pulses on the acceleration sensor decreases. The threshold voltage for a single pulse is 321.57 V. When the pulse interval is 1 μs and the pulse number is 5, the threshold voltage for multiple pulses is 163.42 V,which is reduced by 49.12% compared with a single pulse. These results provide a reference for the damage design of electromagnetic pulse weapons.

Field Investigation of Vehicle Acceleration at the Stop Line with a Dynamic Vision Sensor

This article presents a study of vehicle acceleration distribution at a traffic signal stop line in an urban environment. Accurate representation of vehicle acceleration behavior provides important inputs to traffic simulation models especially when traffic related emissions need to be estimated. A smart eye TDS （traffic data sensor） system was used to record vehicle trajectories, which were extracted to calculate vehicle acceleration profiles. This paper presents the acceleration distributions obtained from over 300 passenger-car acceleration cycles observed on site from the stop line up to a maximum speed of 40 km/h. These distributions are compared with the outputs from a traffic micro simulation tool modeling a similar stop line scenario. The comparison shows that measured accelerations present wider distribution and lower values than the micro simulation. This result highlights the importance of using acceleration distribution calibrated with real-world measured data rather than default values in order to estimate accurate emission levels.

Acceleration sensing based on piezoresistive effect of carbon nanotube films

Based on piezoresistive effect, the acceleration sensitivity of multi-walled canbon nanotube (MWNT) films was investigated. A three-point bending technique was presented to measure the piezoresistivity, which used a bending stress applied to the samples while making MWNT films wheeling with a rotational machine. The experimental results showed that the fractional increase in resistance increases linearly versus the increase of centripetal acceleration, and there is a linear relationship between the acceleration and the strain. These shed light on using carbon nanotube films as acceleration sensors for many potential applications.

Visualization of real-time displacement time history superimposed with dynamic experiments using wireless smart sensors and augmented reality

Wireless smart sensors(WSS)process field data and inform inspectors about the infrastructure health and safety.In bridge engineering,inspectors need reliable data about changes in displacements under loads to make correct decisions about repairs and replacements.Access to displacement information in the field and in real-time remains a challenge as inspectors do not see the data in real time.Displacement data from WSS in the field undergoes additional processing and is seen at a different location.If inspectors were able to see structural displacements in real-time at the locations of interest,they could conduct additional observations,creating a new,information-based,decision-making reality in the field.This paper develops a new,human-centered interface that provides inspectors with real-time access to actionable structural data during inspection and monitoring enhanced by augmented reality(AR).It summarizes and evaluates the development and validation of the new human-infrastructure interface in laboratory experiments.The experiments demonstrate that the interface that processes all calculations in the AR device accurately estimates dynamic displacements in comparison with the laser.Using this new AR interface tool,inspectors can observe and compare displacement data,share it across space and time,visualize displacements in time history,and understand structural deflection more accurately through a displacement time history visualization.

Wireless Self-Powered Vibration Sensor System for Intelligent Spindle Monitoring

In recent years,high-end equipment is widely used in industry and the accuracy requirements of the equipment have been risen year by year.During the machining process,the high-end equipment failure may have a great impact on the product quality.It is necessary to monitor the status of equipment and to predict fault diagnosis.At present,most of the condition monitoring devices for mechanical equipment have problems of large size,low precision and low energy utilization.A wireless self-powered intelligent spindle vibration acceleration sensor system based on piezoelectric energy harvesting is proposed.Based on rotor sensing technology,a sensor is made to mount on the tool holder and build the related circuit.Firstly,the energy management module collects the mechanical energy in the environment and converts the piezoelectric vibration energy into electric energy to provide 3.3 Vfor the subsequent circuit.The lithium battery supplies the system with additional power and monitors’the power of the energy storage circuit in real-time.Secondly,a three-axis acceleration sensor is used to collect,analyze and filter a series of signal processing operations of the vibration signal in the environment.The signal is sent to the upper computer by wireless transmission.The host computer outputs the corresponding X,Y,and Z channel waveforms and data under the condition of the spindle speed of 50∼2500 r/min with real-time monitoring.The KEIL5 platform is used to develop the system software.The small-size piezoelectric vibration sensor with high-speed,high-energy utilization,high accuracy,and easy installation is used for spindle monitoring.The experiment results show that the sensor system is available and practical.

挤密砂桩振动沉桩可打性分析中必要振幅的试验研究

击振力和振幅是挤密砂桩振动沉桩可打性分析中2个最重要的参数,其中工作振幅与机械设备能力及土性相关,而必要振幅主要与土性相关。现有的振动沉桩可打性分析理论在必要振幅的认识方面存在较大的差异。为了更好解决振动沉桩必要振幅预测问题,依托港珠澳桥隧人工岛工程挤密砂桩可打性分析课题,通过在砂桩管上安装加速度传感器对挤密砂桩沉桩过程进行全程监测,并通过二次积分得到振幅-时程曲线,将各个土质条件下实测振幅与目前常用的日本建调神户株式会社法、美国ICE沉桩理论以及法国PTC沉桩理论进行对比分析,根据实测结果,对上述振动沉桩理论的适用性及优缺点进行了对比分析并给出了必要振幅取值方法的建议。研究结果表明,在采用电动振动锤沉桩的条件下,日本建调神户株式会社法必要振幅的取值偏大,法国PTC法的必要振幅偏小,美国ICE法必要振幅的取值规律性与实测结果吻合良好,但是取值方法不够具体。建议在美国ICE法的基础上结合工程经验进一步细化和完善振动沉桩必要振幅取值。

球体质量块型六维加速度传感器的最大工作频率

工作频带是加速度传感器的重要性能指标之一,但六维加速度传感器的最大工作频率目前尚不明确。鉴于此,分别以实心球体质量块型和空心球体质量块型六维加速度传感器为研究对象,构建了系统最大工作频率的数学模型。首先,通过虚拟实验,获得了传感器基频及最大工作频率与质量块直径和支链刚度之间的数据对。接着,分别绘制了基频和最大工作频率的性能图谱,并运用多元线性回归理论拟合了数据对。最后,运用线性包络原理建立了2个频率之间的映射关系。结果表明,最大工作频率始终介于基频的1/35~1/30区间内。

基于傅里叶变换的振动切削刀具振幅测量方法

振动切削在当今时代的制造业越来越普遍,而振动切削的关键参数刀具振幅又因能量损失而无法避免,为了能保证良好的切削效果,需要知道实际切削过程中的刀具振幅。目前普遍使用激光测振仪测量振动切削的刀具振幅,但设备较为昂贵。为了实现对振动切削刀具振幅经济有效的测量,提出了一种利用加速度传感器测量振动切削刀具振幅的测量方法。利用加速度传感器获得刀具振动方向的加速度,通过傅里叶变换和频域二次积分以及傅里叶反变换,将加速度信号积分为振幅信号。根据实验结果可知,本测量系统的测量误差低于0.8%。

精准温度控制半导体激光治疗仪及其可靠性分析

目的探究影响基于保偏光纤温度传感器的半导体激光治疗仪功率稳定输出的关键因素,探索实用化的激光治疗系统光电子器件可靠性分析方法。方法基于可靠性框图法,对系统光电子器件及其外围电路建立可靠度(RSL)、失效率(λSL)和平均寿命(LSL)分析模型,分析使用环境、运行时间(t)和工作温度(T)对系统运行可靠性的影响。基于加速寿命模型分别在室温大驱动电流(T=25℃、I=2.5 A)、高温工作电流(T=50℃、I=1.5 A)和高温大驱动电流(T=50℃、I=2.5 A)条件下,测试LSL与T、I以及T和I相互作用条件下的关系。结果仿真结果表明,λSL随T的增加而增加,LSL随T的增加而降低,RSL随T和t的增加而降低,在I为1.5 A、T为50℃的条件下,λSL、LSL、RSL估计值分别为5.229×10-51/h、17824.500 h、0.11418。实验结果显示,LSL分别为22873、17693和4780 h,实验测试结果与仿真结果吻合。结论基于本研究所提方法,可结合系统架构、设计方法、使用环境,分析计算出设备的λSL是否满足使用规范,进而预测出设备的RSL与LSL,为设计制造与临床使用提供数据支撑。

完全各向同性的Stewart型六维加速度感知机构构型综合

各向同性是六维加速度感知机构的重要性能指标之一,决定了传感器的测量精度。为获得感知机构的完全各向同性,提出了一种新的构型综合方法。首先,运用Newton⁃Euler法并基于支链之间固有的尺度约束关系,构建了Stewart型六维加速度感知机构的正向解耦方程。其次,剖析了感知机构的各向同性与正向解耦方程中输入矩阵条件数的关联,以及支链位姿与输入矩阵的映射关系。创建了完全各向同性感知机构的构型综合步骤。最后,遵循该步骤,综合出“12⁃6”式Stewart型六维加速度感知机构,并开展了虚拟实验。将添加0.100%随机扰动和零扰动这两种情况相比较,结果显示,六维加速度的最大引用误差为0.169%,也即输入、输出误差的放大倍数仅为1.69。这表明,新构型具有优异的各向同性性能。

加速度传感器的振动筛螺栓松动故障诊断系统

针对GLS10型直线振动筛弹簧紧固螺栓松动故障,结合软件LABVIEW和NIUSB-6363数据采集卡,构建一种基于加速度传感器的振动筛螺栓松动故障诊断系统。通过拧松固定螺栓个数的方法,模拟振动筛弹簧悬臂梁固定端松动故障。结果表明:当振动筛悬梁臂固定端松动时,其最大振幅明显减小,其幅度为原先幅值的53%,可以有效判断故障类型;当故障类型相同、故障程度不同时,分析得到的加速度信号图谱互不相同,且振幅差异明显,可根据振幅的阈值来判断螺栓松动的故障程度。

基于多模态数据的智慧化平衡功能评估系统应用研究

随着人口老龄化的加剧,平衡功能障碍已成为影响老年人生活质量和健康的重大问题。本文提出了一种基于多模态数据的智能化平衡功能评估系统,通过佩戴在身体不同部位的MPU6050加速度传感器和薄膜压阻式足底压力传感器,系统能够实时采集和处理站立和动态行走时的下肢信号,并提供左倾、右倾、平衡稳定、前倾和后倾5种平衡功能评估结果。该系统集成了数据采集、处理、评估和反馈功能,最终可通过用户界面实时查看评估结果,了解自身平衡功能状况并制定相应的干预措施。实验结果表明:该系统的跌倒判断参数指标平均达到85.8%,能够为个体提供精准评估和干预,识别平衡问题并预警失衡风险,具有重要理论意义和应用价值。

基于压电能量收集技术的自供电系统设计

为了降低对传统电池的依赖,同时收集和利用汽车发动机的振动能量,设计了一种二自由度压电能量收集器和基于压电能量收集技术的自供电系统。系统主要由压电能量收集器、电源管理模块和加速度传感器组成。对压电能量收集器进行了建模、仿真和测试,得到了压电能量收集器的谐振频率和输出电压,测试结果表明该压电能量收集器前两阶谐振频率分别为105.5和124.6 Hz,并且在95~128 Hz频率范围内输出电压均在2.7 V以上,频率带宽为33 Hz。测试系统的整体功能,测试结果表明电源管理模块LTC3588-1输出3.34 V的直流电压,加速度传感器ADXL335能够正常工作。实验验证了压电能量收集技术在汽车电子领域中的潜力和可行性,为汽车电子设备提供可持续的自供电解决方案。

基于LSTM的智能手机3D手写识别

针对传统传感器需要在特定的空间区域内才能进行人机交互,极易受到外部环境因素干扰的问题,提出一种新的基于长短时记忆神经网络(LSTM)的智能手机3D空间手写识别方法,用于非特定三维空间中实现的人机交互.首先,利用智能手机内置三轴加速度传感器,采集手部运动数据,并将采集的数据进行预处理操作,构建3D手写识别数据集;然后,基于LSTM构建3D手写识别模型,并利用构建的数据集进行训练;最后,利用训练后的模型实现智能手机的3D手写分类识别.通过在本文自建的非依赖用户数据集上进行测试,实验结果表明,该识别方法可以实现86.4%的准确率,88.1%的召回率,88.4%的精准率和88.0%的F_(1)分数.

轴承端面振动信号原位无线无源测量方法

为解决轴承端面加速度信号的原位测量问题,设计了一种用于轴承端面原位测量的无线无源振动加速度计。采用丝网印刷技术在轴承端面集成电感线圈,利用射频反射原理,通过改变电感线圈与接收天线的距离测量轴承端面的振动信号。搭建试验平台并进行传感器性能验证的结果表明,在20~180 m/s^(2)加速度输入信号的激励下,所设计轴承端面无线无源振动传感器的输出信号与输入信号呈线性关系,传感器的灵敏度为0.120 7 mV/(m·s^(-2)),最大重复性误差不超过0.018%,可在高温高旋环境下进行陶瓷轴承外圈原位振动信号的测量。

基于ADAMS二次开发的六维加速度感知机构的性能优化

构建了六维加速度感知机构的二次开发系统,可实现不同构型和不同尺寸间的转换。给出了基频和灵敏度的计算结果,并以灵敏度为主要性能指标,提出了9-3、12-6和6-6构型的一种参数优化方法。结果显示:6-6构型的线加速度灵敏度和角加速度灵敏度分别提升了2.4倍和4.1倍;9-3构型、12-6构型的线加速度灵敏度均提升了2.4倍,角加速度灵敏度均提升了3.6倍。

GIS缺陷检测用低功耗智能无线振动加速度-声发射融合传感器

针对气体绝缘组合电器(GIS)机械和绝缘缺陷的同时同地感知,本文提出一种低功耗智能无线振动加速度-声发射融合传感器。进行了传感器融合结构设计和仿真验证,使用蓝牙低功耗(BLE)实现传感器与客户端通信。首次将伪随机M序列应用于压电传感器的阻抗响应自校准,单次校准仅需数毫秒和数毫瓦。测试结果表明,传感器100 Hz~2 kHz内平均振动灵敏度为511 mV/g, 20~100 kHz内超声灵敏度稳定在70~90 dB之间,相对不确定度小于2%;工作距离小于8 m时,数据传输速率在1 Mbps以上。在设置金属颗粒缺陷的实际GIS设备上开展机械振动-局部放电联合试验,结果表明传感器可实现设备机械振动和超声波信号的同时同地测量,为电力设备运行状态的分布式检测提供了新型有效的方法和手段。