{"title":"A Frequency Characteristics Modelling Method for Current Sensors Based on the Electromagnetic Induction Principle","authors":"Yang Jiao, Hongbin Li, Hui Gong","doi":"10.1109/I2MTC43012.2020.9129127","DOIUrl":"https://doi.org/10.1109/I2MTC43012.2020.9129127","url":null,"abstract":"Along with the development of metallurgy, electric power, military industry, etc., the sensors for high-frequency current signals are required to have better frequency characteristics, achieving the precise measuring and controlling. However, there exists no method to accurately calculate a sensor’s frequency characteristics at the designing stage, which creates a huge obstacle to manufacturing sensors. To address the issue, a frequency characteristics modelling method based on the electrical parameters is proposed in this paper and it consists of three phases: developing the relationship within a micro-unit, modelling with the recursive calculation and calculating the transfer function. With this method, the common-used simulation based on the software is transformed into a totally mathematical recursive calculation, which is quite different from the model based on the circuit topology and could avoids the overwhelming modelling workload. Moreover, an application is conducted to indicate the method’s superiority and validity.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133514463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"All-ConvNet: A Lightweight All CNN for Neuromuscular Activity Recognition Using Instantaneous High-Density Surface EMG Images","authors":"M. Islam, D. Massicotte, Weiping Zhu","doi":"10.1109/I2MTC43012.2020.9129362","DOIUrl":"https://doi.org/10.1109/I2MTC43012.2020.9129362","url":null,"abstract":"Neuromuscular activity recognition using low- resolution instantaneous high-density surface electromyography (HD-sEMG) images present a great challenge. The recent result shows the high potentiality and hence opens up new avenues for the development of more fluid and natural muscle-computer interfaces. However, the existing approaches employed a very large deep ConvNet, which requires learning >5.63 million training parameters only during fine-tuning and pre-trained on a very large-scale labeled HD-sEMG training datasets, as a result, it makes high-end resource bounded and computationally expensive. To overcome this problem, we propose a lightweight All-ConvNet model that consists solely of convolutional layers, a simple yet efficient framework for learning instantaneous HD-sEMG images from scratch through random initialization. Without using any pre-trained models, our proposed lightweight All-ConvNet demonstrate very competitive or even state of the art performance on a current benchmarks HD-sEMG dataset, while requires learning only ~460k training parameters and using ~12xsmaller dataset. The experimental results proved that the proposed lightweight All-ConvNet is highly effective for learning discriminative features for low-resolution instantaneous HD-sEMG image recognition and low-latency processing especially in the data and high-end resource constrained scenarios.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133605826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Separation of Overlapping Reflected Signals in Stepped-Frequency Waveform Reflectometry","authors":"N. Giaquinto, M. Scarpetta, M. Spadavecchia","doi":"10.1109/I2MTC43012.2020.9128537","DOIUrl":"https://doi.org/10.1109/I2MTC43012.2020.9128537","url":null,"abstract":"The aim of this paper is to further develop Stepped Frequency Waveform Reflectometry (SFWR) algorithms for the case of overlapping reflected signals. SFWR is a novel reflectometry technique, primarily developed for localization and characterization of cable faults, which makes use of a sequence of sinusoidal bursts as reference signal. When reflected signals overlaps with the transmitted one or with each other, it is not possible to use the standard technique and a modified procedure is required. A novel technique for localizing overlapping reflected signals is presented and integrated with the fault characterization procedure. Experimental results, obtained from tests on coaxial cables, are reported to prove the effectiveness of the proposed algorithm.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127810237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Performance Comparison of FIR Low-Pass Digital Differentiators for Measurement Applications","authors":"D. Macii, D. Petri","doi":"10.1109/I2MTC43012.2020.9128688","DOIUrl":"https://doi.org/10.1109/I2MTC43012.2020.9128688","url":null,"abstract":"Low-pass Digital Differentiators (LPDs) are adopted in a variety of measurement and testing applications. However, a clear performance analysis of different solutions is seldom reported in the scientific literature. Maybe this is due to the lack of criteria to analyze their behavior on a common basis. In this paper, the passband and stopband features of two families of Finite Impulse Response (FIR) LPDs (namely those resulting from the classic windowing design method and the so-called maximally-flat differentiators) are purposely analyzed under comparable conditions. In particular, starting from a revised definition of Equivalent Noise Bandwidth (ENBW) adapted to the LPD case, a criterion to compare both types of digital differentiators is proposed for common settings of ENBW and impulse response length. The reported analysis shows that, even if the maximally-flat LPDs exhibit a smoother frequency response within the passband, a negligible magnitude error around DC and the possibility to compute the coefficients using recursive analytical expressions, they are less selective than the corresponding windowing-based differentiators. Moreover, while the stopband attenuation of maximally-flat LPDs is higher, their Root Mean Square (RMS) magnitude response errors within the passband are significantly higher. Last but not least, the maximally-flat LPDs suffer from two crucial problems, i.e. finite (and potentially coarse) bandwidth resolution and poor numerical stability, as the filter order grows.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133809751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evaluation of the Applicability of BLE-Based Wireless Sensor Networks for Operational Modal Analysis","authors":"Alvaro di Zeo, R. Taherkhani, S. Nihtianov","doi":"10.1109/I2MTC43012.2020.9129492","DOIUrl":"https://doi.org/10.1109/I2MTC43012.2020.9129492","url":null,"abstract":"This work evaluates experimentally the applicability of wireless sensors networks (WSNs) based on Bluetooth Low Energy (BLE) for operational modal analysis (OMA) in machine diagnostics. OMA enables the dynamic properties of a mechanical system to be determined based on vibration measurements. A WSN for collecting such measurements requires precise synchronization, the transfer of relatively large volumes of data, and a lifetime of several days or weeks. The higher data rate of BLE 5 (2 Mbps), compared to other prominent radio technologies used in WSNs, offers several advantages, e.g. it could allow a reduction in the overall radio utilization, which generally contributes the most to the power consumption of a sensor node. However, the reliability of BLE 5 links in a machine environment must be assessed to determine the applicability of this radio technology in OMA. This work presents experimental results on the quality of BLE 5 links operating inside an industrial machine which indicate that such links can operate reliably when using a relatively high transmission power (above 0 dBm).","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124138139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qian Zhang, Z. Cui, Zihan Xia, Long Yan, Huaxiang Wang
{"title":"Numerical Simulation of Effective Medium Approximation Using Monte Carlo Method and Its Experimental Evaluation","authors":"Qian Zhang, Z. Cui, Zihan Xia, Long Yan, Huaxiang Wang","doi":"10.1109/I2MTC43012.2020.9128767","DOIUrl":"https://doi.org/10.1109/I2MTC43012.2020.9128767","url":null,"abstract":"The phase fraction in the industrial multi-phase flows is a key factor affecting the process efficiency and safety. The capacitance and other impedance based sensors can be employed to estimate this parameter by resorting to the effective medium approximation (EMA) method, which describes the macroscopic properties of composite materials with analytical or theoretical modeling. The EMAs have been paid increasingly attentions in determining the phase fraction in the multi-phase flow. There exist several different EMA models that can be utilized for phase fraction measurement, i.e., Maxwell-Garnett, Bruggeman and Böttcher models. It is essential to evaluate feasibility of these EMA models in gas-solid two-phase flows with different flow regimes, i.e., the homogenous and laminar flows. A four-electrode capacitance sensor is evaluated to validate multiple EMA models for estimating the solid fraction by numerical simulations and static experiments. The numerical simulation work focuses on comparing the solid fraction results obtained from different EMA models by Monte Carlo method.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"222 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124393682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Model-Based Filtering of EEG Alpha Waves for Enhanced Accuracy in Dynamic Conditions and Artifact Detection","authors":"Valentina Casadei, R. Ferrero, Christopher Brown","doi":"10.1109/I2MTC43012.2020.9128381","DOIUrl":"https://doi.org/10.1109/I2MTC43012.2020.9128381","url":null,"abstract":"Electroencephalography (EEG) is the recording of brain electrophysiological activity, usually by electrodes placed on the scalp. The EEG signals contain useful information about the brain state, with specific states being associated with oscillations at specific frequencies (the so-called brain waves); hence, EEG signals are usually analyzed in terms of their frequency content. A notable example is the amplitude estimation of alpha waves (8-14 Hz). This paper proposes a model-based estimation approach, based on known physical properties of alpha waves, which allows enhanced robustness in presence of fast amplitude dynamics, as well as an automatic identification of possible artifacts or discontinuities in the alpha wave. The proposed method is illustrated in this paper with application to a clinical EEG signal, but it is particularly promising for wearable EEG applications, such as brain-computer interface (BCI), to name one, where no expert human supervision is available.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124411094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design and Development of a Mobile e-nose platform for Real Time Victim Localization in Confined Spaces During USaR Operations","authors":"A. Anyfantis, S. Blionas","doi":"10.1109/I2MTC43012.2020.9129247","DOIUrl":"https://doi.org/10.1109/I2MTC43012.2020.9129247","url":null,"abstract":"An electronic nose gas sensor based system for the identification of human presence in confined spaces during Urban Search and Rescue (USaR) operations is presented. The system is intended to be used during the Assessment, Search and Rescue (ASR) level 4 of a USaR operation and is part of the sensor payload of a remotely controlled robot that enters the rubble of collapsed structures searching for trapped victims. The field of operation for the electronic nose from a gas/compounds availability and detectability perspective is investigated to identify candidate detection target chemicals with regard to commercially available sensing solutions and implementation constraints. The e-nose system design and testing cycles are presented, including end user validation.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114993460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Metshein, P. Annus, R. Land, M. Rist, M. Min, Olev Märtens
{"title":"Correlation Between Electrical Bioimpedance and Pressure Waveform in Radial Artery and in Mechanical Pulsating Pipe System","authors":"M. Metshein, P. Annus, R. Land, M. Rist, M. Min, Olev Märtens","doi":"10.1109/I2MTC43012.2020.9128972","DOIUrl":"https://doi.org/10.1109/I2MTC43012.2020.9128972","url":null,"abstract":"The approach of comparing the effect of externally applied pressure onto radial artery in wrist and similarly also onto flexible pipe in artificial on-desk model of cardiovascular system on simultaneously measured electrical bioimpedance and pressure waveform is presented in this paper. Correlation between the measured impedance and simultaneous pressure waveforms in pipe of pulsating saline solution and the same measured parameters of pulsating blood in radial artery was performed. Results showed the correlation between the detected time varying impedance and pressure in artificial cardiovascular system – the presence of increasing trend appears while increasing the squeezing level of the pipe. The contrary result in the case of time varying impedance and pressure in radial artery reveal the complexity of the cardiovascular system of a man with its compensation mechanisms and possible targeting pathway through ulnar artery. However, the outcome also refers to notion of the source of impedance signal – the main contribution from the pulsating volume of blood can be expected. If the agreeable trend of time varying pressure denotes the effect of externally increased inherent pressure in the system and the comparability of developed artificial cardiovascular system, then the decreasing trend of time varying impedance of blood in radial artery refers to the need for modifications on the mechanical system. The convergency of time varying impedance of pulse wave above the externally applied pressure of weight 400 g was verified.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122095038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Knudsen, J. Perchoux, T. Mazoyer, F. Jayat, C. Tronche, T. Bosch
{"title":"Lower detection limit of the acousto-optic effect using Optical Feedback Interferometry","authors":"E. Knudsen, J. Perchoux, T. Mazoyer, F. Jayat, C. Tronche, T. Bosch","doi":"10.1109/I2MTC43012.2020.9128405","DOIUrl":"https://doi.org/10.1109/I2MTC43012.2020.9128405","url":null,"abstract":"Measurement and 3D imaging of acoustic waves through the acousto-optic effect has recently been demonstrated by means of Optical Feedback Interferometry (OFI). In this paper we study experimentally the lower limits of detection of an acoustic wave using an OFI sensor. We show that the OFI sensor exhibits a linear response to acoustic power variations, and we obtain a lower limit of detection of 83 dB rms for a planar acoustic wave at 3 kHz. We also determine the equivalent displacement, that is seen by the OFI sensor at this pressure level, to be 96 pm. A deeper understanding of the limits of the technology and the quantification of the acousto-optic effect shall help improve the applications already created for the measurement of acoustic pressure waves using OFI.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122112195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}