The performance enhancement of an inverter-based grid-connected system necessitates a fast and accurate dynamic response in terms of estimating three-phase grid voltage attributes. The synchronous reference frame phase-locked loop (PLL) and/or the frequency-locking (i.e., frequency-locked loop) approaches are widely used in practical applications. However, due to the phase/frequency feedback loops, the aforementioned parameter estimation schemes may experience instability and provide a slow dynamic response. This work presents a PLL-less grid synchronization solution for three-phase applications to counter the slower dynamic response and demonstrate better immunity against the nonideality of a three-phase grid. In order to remove even and odd-order harmonics and extract the fundamental frequency positive sequence (FFPS), the proposed method employs a combination of band pass filters (CBPFs). Additionally, a novel frequency estimation algorithm is developed, which accurately estimates the angular three-phase grid frequency. Furthermore, the phase angle and amplitude are adaptively estimated using an off-line error-resolving approach, which is derived from the transfer function of the proposed prefiltering solution. Finally, the experimental findings validate the robustness of the current proposal.
{"title":"Robust Band-Pass Filter-Based PLL-Less Approach for Three-Phase Nonsinusoidal Grid Conditions","authors":"Manish Kumar;Anant Kumar Verma;Claudio Burgos-Mellado;Raj Kumar Jarial;Ravinder Nath;Bhumaiah Jula;Diego Muñoz-Carpintero;Catalina González-Castaño;Pedro Roncero-Sánchez","doi":"10.1109/OJIM.2024.3399250","DOIUrl":"https://doi.org/10.1109/OJIM.2024.3399250","url":null,"abstract":"The performance enhancement of an inverter-based grid-connected system necessitates a fast and accurate dynamic response in terms of estimating three-phase grid voltage attributes. The synchronous reference frame phase-locked loop (PLL) and/or the frequency-locking (i.e., frequency-locked loop) approaches are widely used in practical applications. However, due to the phase/frequency feedback loops, the aforementioned parameter estimation schemes may experience instability and provide a slow dynamic response. This work presents a PLL-less grid synchronization solution for three-phase applications to counter the slower dynamic response and demonstrate better immunity against the nonideality of a three-phase grid. In order to remove even and odd-order harmonics and extract the fundamental frequency positive sequence (FFPS), the proposed method employs a combination of band pass filters (CBPFs). Additionally, a novel frequency estimation algorithm is developed, which accurately estimates the angular three-phase grid frequency. Furthermore, the phase angle and amplitude are adaptively estimated using an off-line error-resolving approach, which is derived from the transfer function of the proposed prefiltering solution. Finally, the experimental findings validate the robustness of the current proposal.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"3 ","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2024-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10529140","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-06DOI: 10.1109/OJIM.2024.3396829
Magnus Wangensteen;Tonni Franke Johansen;Ali Fatemi;Erlend Magnus Viggen;Lars Eidissen Haugan
Pitting corrosion, a localized form of corrosion leading to cavities and structural failure in metallic materials, requires early detection for effective mitigation. While ultrasonic inspection techniques can readily detect uniform wall thinning, they often struggle to identify pitting corrosion. This study proposes a time-lapse ultrasound inspection method to detect early-stage pitting using pulse-echo sensors. By recording multiple ultrasonic traces over time, 2-D timelapse images of ultrasonic reflectivity can be generated and fed into a trained neural network for pitting diagnostics. In general, training a machine-learning model requires a large training dataset. This work used data from a drilling experiment to generate a suitable dataset. Dataset construction by random time-ordered combinations of ultrasonic measurements was conducted to create a diverse set of time-lapse image samples to generalize the resulting machine-learning model adequately. A classification neural network was trained to detect the presence of drilled holes, and a separate regression network was trained to estimate the hole depth. Based on drilling data from an independently acquired test dataset, results demonstrate a mean absolute error of 0.163 mm for hole depth estimations. All holes are successfully detected when 0.1 mm deeper than the defined pitting threshold of 0.5 mm. This suggests that the proposed method generalizes well and can be deployed to any similar acquisition system.
{"title":"Pitting Detection and Characterization From Ultrasound Timelapse Images Using Convolutional Neural Networks","authors":"Magnus Wangensteen;Tonni Franke Johansen;Ali Fatemi;Erlend Magnus Viggen;Lars Eidissen Haugan","doi":"10.1109/OJIM.2024.3396829","DOIUrl":"https://doi.org/10.1109/OJIM.2024.3396829","url":null,"abstract":"Pitting corrosion, a localized form of corrosion leading to cavities and structural failure in metallic materials, requires early detection for effective mitigation. While ultrasonic inspection techniques can readily detect uniform wall thinning, they often struggle to identify pitting corrosion. This study proposes a time-lapse ultrasound inspection method to detect early-stage pitting using pulse-echo sensors. By recording multiple ultrasonic traces over time, 2-D timelapse images of ultrasonic reflectivity can be generated and fed into a trained neural network for pitting diagnostics. In general, training a machine-learning model requires a large training dataset. This work used data from a drilling experiment to generate a suitable dataset. Dataset construction by random time-ordered combinations of ultrasonic measurements was conducted to create a diverse set of time-lapse image samples to generalize the resulting machine-learning model adequately. A classification neural network was trained to detect the presence of drilled holes, and a separate regression network was trained to estimate the hole depth. Based on drilling data from an independently acquired test dataset, results demonstrate a mean absolute error of 0.163 mm for hole depth estimations. All holes are successfully detected when 0.1 mm deeper than the defined pitting threshold of 0.5 mm. This suggests that the proposed method generalizes well and can be deployed to any similar acquisition system.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"3 ","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520720","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142452679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tunable diode-laser absorption spectroscopy (TDLAS) sensors have shown to be applicable to, e.g., temperature and pressure measurements in gases. These parameters are indispensable in modern avionics. Even though these systems performed well in laboratory or closed environments, the harsh conditions of avionic flight introduce sources of error. To cope with these challenges, altered variants of the classical direct TDLAS may be taken into consideration. Here, we investigate the differences between an all fiber direct TDLAS and a Mach-Zehnder-based amplitude modulated TDLAS variant. We are able to demonstrate the increased noise immunity of the amplitude modulated system as well as the use of the oxygen A-band for the use as an optical pressure detector.
可调谐二极管激光吸收光谱（TDLAS）传感器已被证明适用于气体温度和压力测量等。这些参数在现代航空电子设备中不可或缺。尽管这些系统在实验室或封闭环境中表现良好，但航空飞行的恶劣条件还是会带来误差。为了应对这些挑战，可以考虑对经典的直接 TDLAS 进行改动。在这里，我们研究了全光纤直接 TDLAS 与基于马赫-泽恩德调幅 TDLAS 变体之间的差异。我们能够证明振幅调制系统具有更强的抗噪能力，并能将氧气 A 波段用作光学压力探测器。
{"title":"Pressure Detection With Mach–Zehnder Linearized Tunable Diode-Laser Absorption Spectroscopy","authors":"Raoul-Amadeus Lorbeer;Matthias Bittner;Oliver Kliebisch;Peter Mahnke","doi":"10.1109/OJIM.2024.3396843","DOIUrl":"https://doi.org/10.1109/OJIM.2024.3396843","url":null,"abstract":"Tunable diode-laser absorption spectroscopy (TDLAS) sensors have shown to be applicable to, e.g., temperature and pressure measurements in gases. These parameters are indispensable in modern avionics. Even though these systems performed well in laboratory or closed environments, the harsh conditions of avionic flight introduce sources of error. To cope with these challenges, altered variants of the classical direct TDLAS may be taken into consideration. Here, we investigate the differences between an all fiber direct TDLAS and a Mach-Zehnder-based amplitude modulated TDLAS variant. We are able to demonstrate the increased noise immunity of the amplitude modulated system as well as the use of the oxygen A-band for the use as an optical pressure detector.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"3 ","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520663","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141308717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-06DOI: 10.1109/OJIM.2024.3390197
Siyuan Bai;Yitong Guo;Weichen Li;Lei Wang;Xuetao Shi
3-D brain electrical impedance tomography (EIT) holds great promise for real-time noninvasive imaging of various brain injuries. However, a reference method for selecting high-performance electrode configurations has not been proposed. In this article, the optimization of electrode layout, stimulation and measurement protocols, and the number of electrodes are sequentially performed. The signal quality and image reconstruction performance of simulated perturbations in four cortical regions are evaluated with various levels of noise taken into consideration. The results showed that, considering cost and convenience, the best number of electrodes is 20, which should be placed in the suboccipital and central vertex regions as needed. Electrodes with large spacing at different heights are mainly the driving electrodes, and the potential is collected in the appropriate adjacent channels. These principles are expected to provide general guidance for the electrode configuration methods of 3-D brain EIT in clinical applications.
三维脑电阻抗断层成像（EIT）在对各种脑损伤进行实时无创成像方面前景广阔。然而，目前尚未提出选择高性能电极配置的参考方法。本文依次对电极布局、刺激和测量方案以及电极数量进行了优化。评估了四个皮层区域模拟扰动的信号质量和图像重建性能，并考虑了不同程度的噪声。结果表明，考虑到成本和便利性，最佳电极数量为 20 个，应根据需要放置在枕下和中央顶点区域。不同高度的大间距电极主要是驱动电极，电位收集在适当的相邻通道中。这些原则有望为三维脑 EIT 的电极配置方法在临床应用中提供普遍指导。
{"title":"Optimization of Electrode Configuration for 3-D Brain EIT","authors":"Siyuan Bai;Yitong Guo;Weichen Li;Lei Wang;Xuetao Shi","doi":"10.1109/OJIM.2024.3390197","DOIUrl":"https://doi.org/10.1109/OJIM.2024.3390197","url":null,"abstract":"3-D brain electrical impedance tomography (EIT) holds great promise for real-time noninvasive imaging of various brain injuries. However, a reference method for selecting high-performance electrode configurations has not been proposed. In this article, the optimization of electrode layout, stimulation and measurement protocols, and the number of electrodes are sequentially performed. The signal quality and image reconstruction performance of simulated perturbations in four cortical regions are evaluated with various levels of noise taken into consideration. The results showed that, considering cost and convenience, the best number of electrodes is 20, which should be placed in the suboccipital and central vertex regions as needed. Electrodes with large spacing at different heights are mainly the driving electrodes, and the potential is collected in the appropriate adjacent channels. These principles are expected to provide general guidance for the electrode configuration methods of 3-D brain EIT in clinical applications.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"3 ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10521592","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141084886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-03DOI: 10.1109/OJIM.2024.3396226
Joseph Filbert;Aaron Barvincak;Mohammad Tayeb Al Qaseer;Reza Zoughi
Common additive manufacturing (AM) methods use metal powder feedstock. The properties of the metal powder, such as particle size distribution (PSD), morphology, and presence of surface oxides or other contaminants, significantly impact the quality of the built part. Microwave materials characterization techniques potentially offer effective means by which to evaluate such metal properties. To assess sensitivity of microwave signals to the properties of metal powder used in AM, different types of metal powder were incorporated into resin composite samples, whose dielectric and magnetic properties were then measured using the well-known completely filled-waveguide technique at the Ka-band (26.5–40 GHz) and V-band (50–67 GHz). These measurements revealed that microwave signals are sensitive to small (~0.5%) changes in the metal powder volume fraction. It was also found that the resin powder composites exhibited diamagnetic properties and could be accurately modeled using effective media theories which consider both the dielectric and magnetic properties. The findings open the door for future investigations by which optimized techniques can be devised to do the same in an in-line manner during the AM process.
常见的增材制造（AM）方法使用金属粉末原料。金属粉末的特性，如粒度分布 (PSD)、形态、表面氧化物或其他污染物的存在，都会对制造部件的质量产生重大影响。微波材料表征技术为评估此类金属特性提供了有效手段。为了评估微波信号对 AM 中使用的金属粉末特性的敏感性，将不同类型的金属粉末加入树脂复合材料样品中，然后使用著名的完全填充波导技术在 Ka 波段（26.5-40 GHz）和 V 波段（50-67 GHz）测量样品的介电和磁特性。这些测量结果表明，微波信号对金属粉末体积分数的微小变化（约 0.5%）非常敏感。研究还发现，树脂粉末复合材料具有双磁性能，可以使用同时考虑介电和磁性能的有效介质理论进行精确建模。这些发现为今后的研究打开了大门，通过这些研究，可以设计出优化的技术，在 AM 过程中以在线方式实现同样的效果。
{"title":"Microwave Characterization of Metal Powder in Additive Manufacturing (AM)","authors":"Joseph Filbert;Aaron Barvincak;Mohammad Tayeb Al Qaseer;Reza Zoughi","doi":"10.1109/OJIM.2024.3396226","DOIUrl":"https://doi.org/10.1109/OJIM.2024.3396226","url":null,"abstract":"Common additive manufacturing (AM) methods use metal powder feedstock. The properties of the metal powder, such as particle size distribution (PSD), morphology, and presence of surface oxides or other contaminants, significantly impact the quality of the built part. Microwave materials characterization techniques potentially offer effective means by which to evaluate such metal properties. To assess sensitivity of microwave signals to the properties of metal powder used in AM, different types of metal powder were incorporated into resin composite samples, whose dielectric and magnetic properties were then measured using the well-known completely filled-waveguide technique at the Ka-band (26.5–40 GHz) and V-band (50–67 GHz). These measurements revealed that microwave signals are sensitive to small (~0.5%) changes in the metal powder volume fraction. It was also found that the resin powder composites exhibited diamagnetic properties and could be accurately modeled using effective media theories which consider both the dielectric and magnetic properties. The findings open the door for future investigations by which optimized techniques can be devised to do the same in an in-line manner during the AM process.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"3 ","pages":"1-13"},"PeriodicalIF":0.0,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10517939","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141164692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abnormal fluid buildup in the lungs, termed pulmonary edema (PE), is a result of congestive heart failure. It is a life-threatening condition, and early detection and prompt treatment can help save lives. In this article, we demonstrate the feasibility of using a microwave sensor to monitor changes in lung water content and hence detect PE. The research paper utilizes a combination of the Debye and Maxwell models, along with the Cole–Cole equation, to evaluate alterations in the dielectric properties and conductivity of lung tissue. By incorporating elements such as air and water found within the tissue, this dielectric model has been employed to foresee how lung tissues behave when subjected to different levels of hydration and inflation. A printed antenna resonating at 2.4 GHz was designed to work as a sensor. The static dielectric parameters of lung tissue at various water volume fractions were calculated at 2.4 GHz using the Debye–Maxwell model. These parameters were substituted in the Cole–Cole equation to calculate the dielectric constant of lung tissue for different levels of water in the lungs. These values were then substituted in the simulation environment, where the sensor is placed on blocks modeling the human thorax. This work is a first of its kind where the dielectric parameters at different levels of hydration have been previously estimated using mathematical models and substituted accordingly in the modeling environment to test the possibility of detection of PE with high precision. It was observed that the magnitude of the reflection coefficient values changes with increasing water volume fraction, making the microwave method of detection of PE feasible and a reliable technique.
肺部异常积液，即肺水肿（PE），是充血性心力衰竭的结果。肺水肿危及生命，早期发现和及时治疗有助于挽救生命。在本文中，我们展示了使用微波传感器监测肺水含量变化从而检测肺水肿的可行性。研究论文结合使用了德拜模型和麦克斯韦模型以及科尔-科尔方程，以评估肺组织介电性质和电导率的变化。通过结合组织内的空气和水等元素，该介电模型可用于预测肺组织在不同程度的水合和充气情况下的表现。设计了一个共振频率为 2.4 GHz 的印刷天线作为传感器。在 2.4 GHz 频率下，使用 Debye-Maxwell 模型计算了肺组织在不同水体积分数下的静态介电参数。将这些参数代入科尔-科尔方程，即可计算出肺部不同水含量下肺组织的介电常数。然后将这些值代入仿真环境，在仿真环境中，传感器被放置在模拟人体胸腔的块上。这项工作是首次使用数学模型估算不同水化水平下的介电参数，并在建模环境中进行相应替换，以测试高精度检测 PE 的可能性。据观察，反射系数值的大小随水体积分数的增加而变化，这使得微波法检测 PE 成为一种可行和可靠的技术。
{"title":"Modeling and Analysis of Lung Water Content Using RF Sensor","authors":"Prapti Ganguly;Shreyasi Das;Amlan Chakrabarti;Jawad Yaseen Siddiqui","doi":"10.1109/OJIM.2023.3348904","DOIUrl":"https://doi.org/10.1109/OJIM.2023.3348904","url":null,"abstract":"Abnormal fluid buildup in the lungs, termed pulmonary edema (PE), is a result of congestive heart failure. It is a life-threatening condition, and early detection and prompt treatment can help save lives. In this article, we demonstrate the feasibility of using a microwave sensor to monitor changes in lung water content and hence detect PE. The research paper utilizes a combination of the Debye and Maxwell models, along with the Cole–Cole equation, to evaluate alterations in the dielectric properties and conductivity of lung tissue. By incorporating elements such as air and water found within the tissue, this dielectric model has been employed to foresee how lung tissues behave when subjected to different levels of hydration and inflation. A printed antenna resonating at 2.4 GHz was designed to work as a sensor. The static dielectric parameters of lung tissue at various water volume fractions were calculated at 2.4 GHz using the Debye–Maxwell model. These parameters were substituted in the Cole–Cole equation to calculate the dielectric constant of lung tissue for different levels of water in the lungs. These values were then substituted in the simulation environment, where the sensor is placed on blocks modeling the human thorax. This work is a first of its kind where the dielectric parameters at different levels of hydration have been previously estimated using mathematical models and substituted accordingly in the modeling environment to test the possibility of detection of PE with high precision. It was observed that the magnitude of the reflection coefficient values changes with increasing water volume fraction, making the microwave method of detection of PE feasible and a reliable technique.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"3 ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10380229","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139572859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-26DOI: 10.1109/OJIM.2023.3347268
Sivagunalan Sivanathan;Mohammed Ali Roula;Kang Li;Dun Qiao;Nigel Joseph Copner
Frequency scanning interferometry (FSI) has become a popular method for long-range, targetbased, distance measurements. However, the cost of developing such systems, particularly the electronic components required for high-speed data acquisition (DAQ), remains a significant concern. In this article, we present a cost-effective, FPGA-based real-time DAQ system specifically designed for FSI, with a focus on long absolute distance measurements. Our design minimizes the use of third-party intellectual property (IP) and is fully compatible with the Xilinx FPGA 7 series families. The hardware employs a 160-MS/s, 16-bit dual-channel ADC interfaced to the FPGA via a low-voltage differential signaling (LVDS). The proposed system incorporates an external sampling clock, referred to as the K-clock, which linearizes the laser’s tuning rate, enabling optical measurements to be sampled at equal optical frequency intervals rather than equal time intervals. Additionally, we present the design of a high-speed, 160-MS/s ADC module for the front-end analog signal interface and the LVDS connection to the chosen FPGA. We demonstrate that the digitized data samples can be efficiently transmitted to a polarization controller (PC) application via a USB interface for further processing.
{"title":"Design of an FPGA-Based High-Speed Data Acquisition System for Frequency Scanning Interferometry Long-Range Measurement","authors":"Sivagunalan Sivanathan;Mohammed Ali Roula;Kang Li;Dun Qiao;Nigel Joseph Copner","doi":"10.1109/OJIM.2023.3347268","DOIUrl":"https://doi.org/10.1109/OJIM.2023.3347268","url":null,"abstract":"Frequency scanning interferometry (FSI) has become a popular method for long-range, targetbased, distance measurements. However, the cost of developing such systems, particularly the electronic components required for high-speed data acquisition (DAQ), remains a significant concern. In this article, we present a cost-effective, FPGA-based real-time DAQ system specifically designed for FSI, with a focus on long absolute distance measurements. Our design minimizes the use of third-party intellectual property (IP) and is fully compatible with the Xilinx FPGA 7 series families. The hardware employs a 160-MS/s, 16-bit dual-channel ADC interfaced to the FPGA via a low-voltage differential signaling (LVDS). The proposed system incorporates an external sampling clock, referred to as the K-clock, which linearizes the laser’s tuning rate, enabling optical measurements to be sampled at equal optical frequency intervals rather than equal time intervals. Additionally, we present the design of a high-speed, 160-MS/s ADC module for the front-end analog signal interface and the LVDS connection to the chosen FPGA. We demonstrate that the digitized data samples can be efficiently transmitted to a polarization controller (PC) application via a USB interface for further processing.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"3 ","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10374215","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139572860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-12DOI: 10.1109/OJIM.2023.3336150
Reza Zoughi
Dear IEEE Open Journal of Instrumentation and Measurement (OJIM) contributors, associate editors, journal administrators, and readers:
尊敬的IEEE仪器与测量开放期刊(OJIM)撰稿人、副编辑、期刊管理员和读者:
{"title":"Message From the Incoming Editor-in-Chief","authors":"Reza Zoughi","doi":"10.1109/OJIM.2023.3336150","DOIUrl":"https://doi.org/10.1109/OJIM.2023.3336150","url":null,"abstract":"Dear IEEE Open Journal of Instrumentation and Measurement (OJIM) contributors, associate editors, journal administrators, and readers:","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"2 ","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10355536","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138633868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There has been tremendous interest in the development and deployment of Signal Processing and Machine Learning algorithms for almost all areas of instrumentation and measurement systems, starting from power systems, transportation, biomedical and healthcare, industrial measurements and automation, robotics and mechatronics, smart infrastructure, and facility management to aerospace and navigation. Their combination, signal processing and machine learning, is expected to dominate the next decade industrial developments. In order to embed the “intelligence” into the measurement, signal processing has been one of the ubiquitous techniques for quite some time. Machine learning methods make these intelligent methods “experienced.” Because machine learning has been around in recent years, signal processing software–hardware systems equipped with machine learning are relatively mature. In this Special Section, a call for paper included (but were not limited to) the following areas.
{"title":"Guest Editorial Special Section on Signal Processing and Machine Learning in Intelligent Instrumentation, IEEE Open Journal of Instrumentation and Measurement","authors":"Anirban Mukherjee;Rajarshi Gupta;Amitava Chatterjee","doi":"10.1109/OJIM.2023.3334827","DOIUrl":"https://doi.org/10.1109/OJIM.2023.3334827","url":null,"abstract":"There has been tremendous interest in the development and deployment of Signal Processing and Machine Learning algorithms for almost all areas of instrumentation and measurement systems, starting from power systems, transportation, biomedical and healthcare, industrial measurements and automation, robotics and mechatronics, smart infrastructure, and facility management to aerospace and navigation. Their combination, signal processing and machine learning, is expected to dominate the next decade industrial developments. In order to embed the “intelligence” into the measurement, signal processing has been one of the ubiquitous techniques for quite some time. Machine learning methods make these intelligent methods “experienced.” Because machine learning has been around in recent years, signal processing software–hardware systems equipped with machine learning are relatively mature. In this Special Section, a call for paper included (but were not limited to) the following areas.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"2 ","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10352322","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138558056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-08DOI: 10.1109/OJIM.2023.3333608
Shervin Shirmohammadi
As the Founding Editor-in-Chief of the IEEE Open Journal of Instrumentation and Measurement (OJIM), it is my pleasure to write this Year-End Message for OJIM’s second year of operations. As you may know by now, OJIM is the Gold Open Access publication of the IEEE Instrumentation and Measurement Society (IMS). All articles are Open Access and available for free to all readers. OJIM is also an online-only and Volume-only journal, meaning that papers are published online continuously as they are accepted. Since there is very little waiting time for a paper to be assigned to the current Volume, OJIM is a rapid-publication and competitive journal by today’s publishing standards. The year 2023 saw OJIM’s second Volume successfully published, so let us take a look at some specifics.
作为 IEEE Open Journal of Instrument and Measurement (OJIM) 的创刊主编，我很高兴能为 OJIM 的第二年运营撰写这篇年终致辞。如您所知，OJIM 是 IEEE 仪器仪表与测量学会 (IMS) 的金牌开放存取刊物。所有文章均为开放获取，免费提供给所有读者。OJIM 还是一本只在线和只出卷的期刊，这意味着论文一经录用就会在网上连续发表。由于论文几乎不需要等待就能被分配到当前卷，因此按照当今的出版标准，OJIM 是一份出版迅速、竞争激烈的期刊。2023 年，OJIM 的第二卷成功出版，让我们来看看一些具体情况。
{"title":"Year-End Message by the Outgoing Editor-in-Chief","authors":"Shervin Shirmohammadi","doi":"10.1109/OJIM.2023.3333608","DOIUrl":"https://doi.org/10.1109/OJIM.2023.3333608","url":null,"abstract":"<graphic>\u0000As the Founding Editor-in-Chief of the IEEE Open Journal of Instrumentation and Measurement (OJIM), it is my pleasure to write this Year-End Message for OJIM’s second year of operations. As you may know by now, OJIM is the Gold Open Access publication of the IEEE Instrumentation and Measurement Society (IMS). All articles are Open Access and available for free to all readers. OJIM is also an online-only and Volume-only journal, meaning that papers are published online continuously as they are accepted. Since there is very little waiting time for a paper to be assigned to the current Volume, OJIM is a rapid-publication and competitive journal by today’s publishing standards. The year 2023 saw OJIM’s second Volume successfully published, so let us take a look at some specifics.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"2 ","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10352324","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138558042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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