Parametric study on contact sensors for MASW measurement-based interfacial debonding detection for SCCS

Steel-concrete composite structures(SCCS)have been widely used as primary load-bearing components in large-scale civil infrastructures.As the basis of the co-working ability of steel plate and concrete,the bonding status plays an essential role in guaranteeing the structural performance of SCCS.Accordingly,efficient non-destructive testing(NDT)on interfacial debondings in SCCS has become a prominent research area.Multi-channel analysis of surface waves(MASW)has been validated as an effective NDT technique for interfacial debonding detection for SCCS.However,the feasibility of MASW must be validated using experimental measurements.This study establishes a high-frequency data synchronous acquisition system with 32 channels to perform comparative verification experiments in depth.First,the current sensing approaches for high-frequency vibration and stress waves are summarized.Secondly,three types of contact sensors,namely,piezoelectric lead-zirconate-titanate(PZT)patches,accelerometers,and ultrasonic transducers,are selected for MASW measurement.Then,the selection and optimization of the force hammer head are performed.Comparative experiments are carried out for the optimal selection of ultrasonic transducers,PZT patches,and accelerometers for MASW measurement.In addition,the influence of different pasting methods on the output signal of the sensor array is discussed.Experimental results indicate that optimized PZT patches,acceleration sensors,and ultrasonic transducers can provide efficient data acquisition for MASW-based non-destructive experiments.The research findings in this study lay a solid foundation for analyzing the recognition accuracy of contact MASW measurement using different sensor arrays.

Design of Cold-Junction Compensation and Disconnection Detection Circuits of Various Thermocouples and Implementation of Multi-Channel Interfaces Using Them-A Secondary Publication

Cold-junction compensation(CJC)and disconnection detection circuit design of various thermocouples(TC)and multi-channel TC interface circuits were designed.The CJC and disconnection detection circuit consists of a CJC semiconductor device,an instrumentation amplifier(IA),two resistors,and a diode for disconnection detection.Based on the basic circuit,a multi-channel interface circuit was also implemented.The CJC was implemented using compensation semiconductor and IA,and disconnection detection was detected by using two resistors and a diode so that IA input voltage became-0.42 V.As a result of the experiment using R-type TC,the error of the designed circuit was reduced from 0.14 mV to 3μV after CJC in the temperature range of 0°C to 1400°C.In addition,it was confirmed that the output voltage of IA was saturated from 88 mV to-14.2 V when TC was disconnected from normal.The output voltage of the designed circuit was 0 V to 10 V in the temperature range of 0°C to 1400°C.The results of the 4-channel interface experiment using R-type TC were almost identical to the CJC and disconnection detection results for each channel.The implemented multi-channel interface has a feature that can be applied equally to E,J,K,T,R,and S-type TCs by changing the terminals of CJC semiconductor devices and adjusting the IA gain.

A multi-channel chemical sensor and its application in detecting hydrothermal vents

There are well-established chemical and turbidity anomalies in the plumes occurring vicinity of hydrothermal vents, which are used to indicate their existence and locations. We here develop a small, accurate multi-channel chemical sensor to detect such anomalies which can be used in deep-sea at depths of more than 4 000 m. The design allowed five all-solid-state electrodes to be mounted on it and each (apart from one reference electrode) could be changed according to chemicals to be measured. Two experiments were conducted using the chemical sensors. The first was a shallow-sea trial which included sample measurements and in situ monitoring. pH, Eh, CO3^2- and SO4^2- electrodes were utilized to demonstrate that the chemical sensor was accurate and stable outside the laboratory. In the second experiment, the chemical sensor was integrated with pH, Eh, CO3^2- and H2S electrodes, and was used in 29 scans of the seabed along the Southwest Indian Ridge (SWIR) to detect hydrothermal vents, from which 27 sets of valid data were obtained. Hydrothermal vents were identified by analyzing the chemical anomalies, the primary judging criteria were decreasing voltages of Eh and H2S, matched by increasing voltages of pH and CO3^2- . We proposed that simultaneous detection of changes in these parameters will indicate a hydrothermal vent. Amongst the 27 valid sets of data, five potential hydrothermal vents were targeted using the proposed method. We suggest that our sensors could be widely employed by marine scientists.

Simple method for extracting the seasonal signals of photochemical reflectance index and normalized difference vegetation index measured using a spectral reflectance sensor

A spectral reflectance sensor(SRS)fixed on the near-surface ground was developed to support the continuous monitoring of vegetation indices such as the normalized difference vegetation index(NDVI)and photochemical reflectance index(PRI).NDVI is useful for indicating crop growth/phenology,whereas PRI was developed for observing physiological conditions.Thus,the seasonal change patterns of NDVI and PRI are two valuable pieces of information in a crop-monitoring system.However,capturing the seasonal patterns is considered challenging because the vegetation index values estimated by the reflection from vegetation are often governed by meteorological conditions,such as solar irradiance and precipitation.Further,unlike growth/phenology,the physiological condition has diurnal changes as well as seasonal characteristics.This study proposed a novel filtering method for extracting the seasonal signals of SRS-based NDVI and PRI in paddy rice,barley,and garlic.First,the measurement accuracy of SRSs was compared with handheld spectrometers,and the R^(2)values between the two devices were 0.96 and 0.81 for NDVI and PRI,respectively.Second,the experimental study of threshold criteria with respect to meteorological variables(i.e.,insolation,cloudiness,sunshine duration,and precipitation)was conducted,and sunshine duration was the most useful one for excluding distorted values of the vegetation indices.After data processing based on sunshine duration,the R^(2)values between the measured vegetation indices and the extracted seasonal signals of vegetation indices increased by approximately 0.002–0.004(NDVI)and 0.065–0.298(PRI)on the three crops,and the seasonal signals of vegetation indices became noticeably improved.This method will contribute to an agricultural monitoring system by identifying the seasonal changes in crop growth and physiological conditions.

ANALYSIS OF SPECTRAL CHARACTERISTICS AMONG DIFFERENT SENSORS BY USE OF SIMULATED RS IMAGES

This research,by use of RS image_simulating method,simulated apparent reflectance images at sensor level and ground_reflectance images of SPOT_HRV,CBERS_CCD,Landsat_TM and NOAA14_AVHRR’s corresponding bands.These images were used to analyze sensor’s differences caused by spectral sensitivity and atmospheric impacts.The differences were analyzed on Normalized Difference Vegetation Index(NDVI).The results showed that the differences of sensors’ spectral characteristics cause changes of their NDVI and reflectance.When multiple sensors’ data are applied to digital analysis,the error should be taken into account.Atmospheric effect makes NDVI smaller,and atmospheric correction has the tendency of increasing NDVI values.The reflectance and their NDVIs of different sensors can be used to analyze the differences among sensor’s features.The spectral analysis method based on RS simulated images can provide a new way to design the spectral characteristics of new sensors.

Clustering in Wireless Multimedia Sensor Networks Using Spectral Graph Partitioning

Wireless multimedia sensor network (WMSN) consists of sensors that can monitor multimedia data from its surrounding, such as capturing image, video and audio. To transmit multimedia information, large energy is required which decreases the lifetime of the network. In this paper we present a clustering approach based on spectral graph partitioning (SGP) for WMSN that increases the lifetime of the network. The efficient strategies for cluster head selection and rotation are also proposed.

Spectral Correction Method of Multi-Channels Near-Infrared Spectrometer and Applications

Near-infrared (NIR) spectrometer based on semiconductor lasers can combine light source and splitter into one, which is an important direction for development of miniature instruments. In order to avoid random interference caused by inconsistency between light sources, the novel evaluation indicators for global stability of multi-channels spectral system were proposed based on the correlation between dynamic deviation spectra of any two channels. The NIR analysis of moisture for corn powder samples based on the partial least squares combined with Savitzky-Golay (SG) smoothing was taken as an example, and a spectral correction method for enhancing prediction performance of multi-channels spectral system was further provided using above evaluation indicators. The experiment results showed that the global stability evaluation indicators significantly increased after SG smoothing correction. Meanwhile, the root-mean-square errors of prediction for corn moisture reduced from 0.373 to 0.283 (%), and the correlation coefficient between predicted and actual values was improved from 0.702 to 0.855. The above results indicated that by improving global stability indicators, the prediction ability of multi-channels spectral system can be improved. The proposed method provided a valuable reference for designing multi-channels diminutive spectrometer with high prediction performance, which had significance for large-scale application of NIR technology.

Turbidity measurement based on a multi-wavelength spectral sensor

A method of measuring turbidity based on a multi-wavelength spectral sensor is proposed by using SFH4737 broad-band infrared LED,a multi-wavelength spectral sensor and independently developed data processing software.Combining multiple wavelength data from the sensor,the unitary and multivariate fitting models were constructed to investigate the relationship among light intensity information,absorbance and turbidity,respectively.The turbidity of the actual water bodies was measured separately by using proposed method and a commercially visible spectrophotometer.The independent-samples T test(p>0.05)showed that there was no significant difference between the method in this paper and the standard assay method.The method is simple and inexpensive,and can be applied to the rapid detection of water turbidity,providing a new way of industrial online measurement.

Network-Wide Time Synchronization in Multi-Channel Wireless Sensor Networks

Recent advances in wireless sensor technology have enabled simultaneous exploitation of multiple channels in wireless sensor systems. In this paper, a novel time synchronization algorithm is proposed for multi- channel Wireless Sensor Networks (WSNs) called Multi-Channel Time Synchronization (MCTS) protocol. Time synchronization is critical for many WSN applications and enables efficient communications between sensor nodes along with intelligent spectrum access. Contrary to many existing protocols that do not exploit multi-channel communications, the protocol takes advantage of potential multiple channels and distributes the synchronization of different nodes to distinct channels and thus, reduces the convergence time of synchronization processes significantly.

Time Series-, Time-Frequency- and Spectral Analyses of Sensor Measurements in an Offshore Wave Energy Converter Based on Linear Generator Technology

Inside the second experimental wave energy converter (WEC) launched at the Lysekil research site on the Swedish west coast in March 2009 a number of sensor systems were installed for measuring the mechanical performance of the WEC and its mechanical subsystems. One of the measurement systems was a set-up of 7 laser triangulation sensors for measuring relative displacement of the piston rod mechanical lead-through transmission in the direct drive. Two measurement periods, separated by 2.5 month, are presented in this paper. One measurement is made two weeks after launch and another 3 months after launch. Comparisons and correlations are made between different sensors measuring simultaneously. Noise levels are investigated. Filtering is discussed for further refinement of the laser triangulation sensor signals in order to separate noise from actual physical displacement and vibration. Measurements are presented from the relative displacement of the piston rod mechanical lead-through, from magnetic flux in the air gap, mechanical strain in the WEC structure, translator position and piston rod axial displacement and active AC power. Investigation into the measurements in the time domain with close-ups, in the frequency domain with Fast Fourier transform (FFT) and with time-frequency analysis with short time Fourier transform (STFT) is carried out to map the spectral content in the measurements. End stop impact is clearly visible in the time-frequency analysis. The FFT magnitude spectra are investigated for identifying the cogging bandwidth among other vibrations. Generator cogging, fluctuations in the damping force and in the Lorenz forces in the stator are distinguished and varies depending on translator speed. Vibrations from cogging seem to be present in the early measurement period while not so prominent in the late measurement period. Vibration frequencies due to wear are recognized by comparing with the noise at generator standstill and the vibration sources in the generator. It is concluded that a moving average is a sufficient filter in the time domain for further analysis of the relative displacement of the piston rod mechanical lead-through transmission.

Universal Spectral Modulation Sensors:(Ⅰ)Theory and Structure

A universal spectral modulation sensor with low cost,stable,reliable and accurate performances is presented.The optical measuring device using a universal spectral modulation sensor is immune to change the intensities of the light source and light transmission due to optical fiber bending and optical fiber connector loss.The spectral modulation sensor system can detect and measure various physical parameters such as pressure,temperature,gas density,and various chemical species.

基于PVDF柔性传感器的不同介质中冲击波波源测量与频谱分析

目的明确体外冲击波系统冲击头在不同介质界面产生的冲击波波源特征。方法采用冲击气压可调的体外冲击波产生与信号采集实验系统,结合聚偏二氟乙烯(PVDF)柔性传感器,通过实验测量方法研究冲击头在不同介质(仿体组织、水和空气)界面产生的冲击波形,分析波源的时域特征和频谱特性。结果在相同气压冲击下,冲击头在仿体界面和水界面产生的冲击波波形相似,二者与空气界面产生的冲击波波形存在较大差异,空气界面的正负压绝对值明显减小;不同介质中产生的冲击波频谱特性相似,都存在3个明显的峰值频率,仿体、水和空气中调制频率分别为12.2、8.5、7.2 kHz,载波频率基本无变化(82~83 kHz)。不同气压冲击下,冲击头在同一介质界面产生的冲击脉冲波波形差异不大,冲击气压仅影响冲击波幅度,不影响峰值频率。随着冲击气压的增大,介质界面正负压绝对值增大,变化基本呈线性。结论PVDF柔性传感器可以有效测量冲击波波源,不同介质界面产生的冲击波在时域和频域都存在一定差异,不能简单以空气或水中的冲击波传播特性代替生物组织中的传播特性。研究结果可以为冲击波设备的评估和临床冲击波治疗方案的制定提供重要信息。

多级冗余强干扰下医用三维力传感器数据的自动挖掘方法

针对医用三维力传感器容易受电磁场等外部环境的影响,产生大量相似特征数据,导致其输出紊乱信号,降低传感器控制精度和测量速度的问题,提出一种多级冗余强干扰下三维力传感器数据挖掘方法。根据角度标定理论采集三维力传感器冗余数据;引入相似度指数函数计算冗余因子,获取三维力传感器冗余数据活跃度,完成数据冗余分类;通过差值去噪算法高性能过滤三维力传感器冗余数据;利用谱聚类算法构建拉普拉斯矩阵,剔除冗余数据,实现三维力传感器数据自动挖掘。仿真结果表明,所提方法在多级冗余强干扰下的三维力传感器控制精度为96.54%,测量速度为0.61 ms,能量消耗为0.26 kcal。由此证明,所提方法的控制精度高、测量速度快、传输效果优,能够满足机器人辅助手术过程中的力反馈控制需求。

多光谱星敏感器的辐射定标与光谱反演

为实现星敏感器对未知空间光环境的测量,提出一种将宽谱段多光谱滤光片装置于星敏感器中的设计,所采集的星图可覆盖星点信息与空间光环境光谱信息,并以此为基础设计了光谱响应定标、辐射定标的实验方案与空间光环境辐亮度分布反演算法。实验结果表明,反演的光环境辐亮度与实测值较为符合,该方法能根据单张星图实时便捷地估算星敏感器应用空间的光环境,可为后续星敏感器的设计优化和观星窗口的选择提供依据。

光谱共焦传感器多参数高准确度校准

针对高准确度光谱共焦传感器缺乏相应校准装置及方法的问题,提出了一种基于激光干涉测量的校准方法,并研制了相应的校准装置。一方面,提出了一种波长倍数间隔测量法,通过位移反馈控制将位移间隔设置为激光波长的整数倍,以减小激光干涉仪非线性误差对测量的影响;另一方面,提出了测点修正算法,消除了受检点处位移标准值因校准装置定位准确度限制不重合对测量的影响。实验结果表明:在0~100μm的测量范围内,示值误差为±23 nm,重复性为5 nm,示值误差测量结果的扩展不确定度U_(2)=7.0 nm(k=2)。构建的校准装置在0~50 mm的测量范围内的示值误差测量结果不确定度为U_(1)=3.0 nm+2×10^(-7)L(k=2)。

基于聚类算法的城市供排水水质检测系统

城市供排水水质检测需要使用多种仪器、步骤繁杂,设计一种基于聚类算法的城市供排水水质自动检测系统。硬件设计方面,设计多参数水质检测仪,在传感器检测模块中,应用传感器实施城市供排水水质中余氯、pH值、TDS值以及温度的检测。设计控制单片机用于系统检测控制。软件设计方面,基于自适应密度峰值聚类算法实施光谱信号数据挖掘,在水质检测融合模块中,设计水质检测融合模型,输出各项目对应的检测结果。测试结果表明,通过设计系统能够实现供水水质与排水水质的自动检测,说明该系统有一定应用前景。

便携式光谱仪检测白酒中乙偶姻含量

目的建立一种便携式光谱仪快速检测白酒中乙偶姻含量的分析方法。方法首先利用AS7341光谱传感器搭建便携式光谱仪,结合肌酸比色法,构建一种检测白酒中乙偶姻含量的即时检测方法。接下来对肌酸比色法反应的温度和时间条件进行优化,反应结果与酶标仪进行对比。最后通过检测7种白酒样本中乙偶姻的含量,来评价本装置的准确性和实用性。结果优化后肌酸比色法的最佳反应条件为40℃反应30min,利用该装置检测到乙偶姻在510nm波长下吸光度与其浓度呈正相关关系。乙偶姻的线性检测范围为0.25~20.00mg/L,检出限为0.049mg/L。该装置检测结果与酶标仪检测结果具有很好的一致性,相关系数为0.9899。最后利用该装置对7种白酒样本中乙偶姻含量进行检测,加标回收率为96.90%~103.32%。结论该装置具有准确、快速、便捷等特点,适用于白酒中乙偶姻含量的即时检测。

基于无线传感器的大气污染物排放浓度远程监测方法研究

为解决人工抽样检测大气污染物的局限性和高误差问题,文章提出基于无线传感器的大气污染物排放浓度远程监测方法。首先,利用DV-Hop定位算法确定传感器最佳安装位置,构建污染监测网络。然后,通过分析光谱数据与气体分子间的关系,检测大气中的异常物质颗粒。结合光谱吸收原理和谐波检测技术,准确计算污染物排放浓度。最后,根据空气质量指数AQI,确定污染排放等级。经实验验证,该方法对某工厂的VOCs排放浓度的监测结果RMSE值低于0.1,有效反映大气污染状况。此方法降低了监测误差,提高大气污染监测的准确性和效率。

非接触式活塞环梯形角测量系统的设计与验证

活塞环梯形角是评价活塞环加工质量的关键参数,随着技术与工艺的进步,传统的接触式梯形角测量方案已不能满足现代的生产需求。分析接触式梯形角测量方案存在的问题,提出了基于光谱共焦位移传感器的非接触梯形角测量方案,并从传感器的选型、组合测量头的设计和夹紧机构的设计3个方面展现了全新的测量系统设计方案。通过对测量系统进行误差分析和可行性验证,证明了新的设计方案具有可行性,为研制新型非接触式活塞环梯形角测量仪提供了全新、有效的思路。

基于C^(#)的光伏压花玻璃厚度在线检测仪设计

该文针对光伏压花玻璃设计并制作了一款在线厚度检测仪器。该仪器使用光谱共焦传感器,采用C^(#)上位机进行核心的交互控制以及数据处理,组合利用可编程逻辑控制器(PLC)和伺服电机控制测量位置。经测试,该仪器操作便捷、测量高效准确,可以取代传统压花玻璃生产过程中繁琐的人工厚度检测。