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.

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.

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.

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 approach for automatic microseismic event association using RANSAC-based Arrival Time Event Clustering(RATEC)

In the presence of background noise,arrival times picked from a surface microseismic data set usually include a number of false picks that can lead to uncertainty in location estimation.To eliminate false picks and improve the accuracy of location estimates,we develop an association algorithm termed RANSAC-based Arrival Time Event Clustering(RATEC)that clusters picked arrival times into event groups based on random sampling and fitting moveout curves that approximate hyperbolas.Arrival times far from the fitted hyperbolas are classified as false picks and removed from the data set prior to location estimation.Simulations of synthetic data for a 1-D linear array show that RATEC is robust under different noise conditions and generally applicable to various types of subsurface structures.By generalizing the underlying moveout model,RATEC is extended to the case of a 2-D surface monitoring array.The effectiveness of event location for the 2-D case is demonstrated using a data set collected by the 5200-element dense Long Beach array.The obtained results suggest that RATEC is effective in removing false picks and hence can be used for phase association before location estimates.

Performance Analysis of Multi-Channel CR Enabled IoT Network with Better Energy Harvesting

Wireless Sensor Networks(WSNs)can be termed as an autoconfigured and infrastructure-less wireless networks to monitor physical or environmental conditions,such as temperature,sound,vibration,pressure and motion etc.WSNs may comprise thousands of Internet of Things(IoT)devices to sense and collect data from its surrounding,process the data and take an automated and mechanized decision.On the other side the proliferation of these devices will soon cause radio spectrum shortage.So,to facilitate these networks,we integrate Cognitive Radio(CR)functionality in these networks.CR can sense the unutilized spectrum of licensed users and then use these empty bands when required.In order to keep the IoT nodes functional all time,continuous energy is required.For this reason the energy harvested techniques are preferred in IoT networks.Mainly it is preferred to harvest Radio Frequency(RF)energy in the network.In this paper a region based multi-channel architecture is proposed.In which the coverage area of primary node is divided as Energy Harvesting Region and Communication Region.The Secondary User(SU)that are the licensed user is IoT enabled with Cognitive Radio(CR)techniques so we call it CR-enabled IoT node/device and is encouraged to harvest energy by utilizing radio frequency energy.To harvest energy efficiently and to reduce the energy consumption during sensing,the concept of overlapping region is given that supports to sense multiple channels simultaneously and help the SU to find best channel for transmitting data or to harvest energy from the ideal channel.From the experimental analysis,it is proved that SU can harvest more energy in overlapping region and this architecture proves to consume less energy during data transmission as compared to single channel.We also show that channel load can be highly reduced and channel utilization is proved to be more proficient.Thus,this proves the proposed architecture cost-effective and energy-efficient.

MODULATION OF FRET THROUGH THE SPECTRAL-OVERLAP STRATEGY

Fluorescence resonance energy transfer(FRET)is an important photophysical mechanism whichfinds many applications in biophotonics,particularly in biological sensing and imaging.It is well known,there are two major factors that determine the efficiency of FRET.One is the distance between the donor and the acceptor,and the other is the overlap of the donor's emission and the acceptor's absorption spectra.However,while the distance-modulation of FRET is very popular,the spectral-overlap-modulation draws much less attention.In this talk,I would like to illustrate the importance of the strategy of spectral-overlapmodulation.The presentation will include our works on the construction of highly efficient FRET systems featuring the short and rigid linker between the donor and acceptor moieties,and several typical examples of spectral-overlap-modulation strategy applied in the development of ratiometric sensors.

Clustering in Wireless Multimedia Sensor Networks

Wireless Multimedia Sensor Networks (WMSNs) are comprised of small embedded audio/video motes capable of extracting the surrounding environmental information, locally processing it and then wirelessly transmitting it to sink/base station. Multimedia data such as image, audio and video is larger in volume than scalar data such as temperature, pressure and humidity. Thus to transmit multimedia information, more energy is required which reduces the lifetime of the network. Limitation of battery energy is a crucial problem in WMSN that needs to be addressed to prolong 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 as part of clustering approach. Simulation results show that our strategy is better than existing strategies.

Utilization of Extrinsic Fabry-Perot Interferometers with Spectral Interferometric Interrogation for Microdisplacement Measurement

The paper presents a number of signal processing approaches for the spectral interferometric interrogation of extrinsic Fabry-Perot interferometers(EFPIs). The analysis of attainable microdisplacement resolution is performed and the analytical equations describing the dependence of resolution on parameters of the interrogation setup are derived. The efficiency of the proposed signal processing approaches and the validity of analytical derivations are supported by experiments. The proposed approaches allow the interrogation of up to four multiplexed sensors with attained resolution between 30 pm and 80 pm, up to three times improvement of microdisplacement resolution of a single sensor by means of using the reference interferometer and noisecompensating approach, and ability to register signals with frequencies up to 1 kHz in the case of 1 Hz spectrum acquisition rate. The proposed approaches can be used for various applications, including biomedical, industrial inspection, and others, amongst the microdisplacement measurement.

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。

大气层内全天时星敏感器成像模型仿真与影响因素分析

全天时星敏感器在大气层内进行观测任务时,难以避免受到大气的影响。为了深入研究全天时星敏感器白昼观星困难的原因,需要对全天时星敏感器在成像过程中所受到的大气影响进行分析。利用MODTRAN软件对大气的干扰进行仿真计算,对不同观测条件下大气的影响进行了研究,并得到大气对全天时星敏感器成像影响的计算模型。研究结果显示,选择合适的光谱范围有利于全天时星敏感器的白昼观星任务。结合黑体辐射定律、恒星星等和恒星光谱型等信息,对恒星辐射的计算进行了修正,建立了恒星目标光谱辐射计算模型。最后,利用得到的大气影响的计算模型和修正后的恒星目标光谱辐射计算模型,并结合相关探测参数,进行仿真信噪比和仿真星图的计算。通过将仿真结果与实际实验结果进行对比,验证了所提出模型的正确性。

环境参数对纸质文物病害作用及其光纤光谱在线检测技术

为了探索光照、湿度、CO_(2)体积分数对纸质文物病害作用,搭建了环境参数病害纸质样品实验系统,构建了光纤光谱传感器及其检测系统。实验研究表明:蓝紫光和红光对纸质文物病害作用强度高于黄光,纸质样品经蓝紫光和红光辐射后由于热效应导致纤维素发生光分解反应;低湿度作用后纤维素收缩,高湿度作用后在样品表面滋生大量霉菌发生腐蚀侵蚀生化反应;高体积分数CO_(2)作用使纤维素发生酸解反应,导致纸质样品形貌特征发生变化、抗张强度降低、热稳定性降低。纸质样品病害发生后,光纤光谱传感器输出信号在275 nm出现了特征吸收峰;当纸质样品表面附着有霉菌微生物时,特征吸收峰漂移至300 nm。26℃、黄光、相对湿度55%和低CO_(2)体积分数的环境有利于保存纸质样品。