高電圧絶縁診断のための高いノイズ耐性を有する革新的な広帯域UHFセンサの開発

Partial discharge (PD) is a pre-breakdown phenomenon that can cause the insulation deterioration of HV equipment. Thus, detection of PD signals enables us to evaluate the insulation condition and avoid catastrophic breakdown. This also brings the reliable operation of the electric power system consisting of the HV equipment. The UHF method, one of the PD detection methods on the PD-emitted EM wave in the UHF bands, has been widely used in the electric power system because this method has many advantages, such as a non-direct connection with the HV circuit, high sensitivity, quick response and so on. However, the rapid development of ICT and digital technologies could impact the PD detection by the UHF method in view of the noise interference by the communication waves, consequently reducing the UHF sensor’s sensitivity and detection ability. Thus, eliminating the communication noise is strongly required in parallel with the wideband PD detection in the UHF method. Under this background, this dissertation dealt with the development of the wideband UHF sensor with high noise resistance ability for PD detection under noise conditions. The Multiple Narrow Band (MNB) antenna, a newly proposed and developed wideband UHF sensor with high noise resistance, was designed and optimized based on the theoretical and experimental discussion. The MNB antenna satisfies the main requirements of the UHF sensor and has excellent properties; wideband detection (more than 1 GHz) and high noise resistance for the communication and ISM bands (S11 > -6 dB). The design rule was summarized as a flowchart to develop the MNB antenna with different detection and elimination frequencies depending on the purpose (Chapter 3). The discharge detection property of the MNB antenna was clarified and compared with the HA based on the PD experiments. As a result, it was proved that the MNB antenna could detect different PD signals from the different insulations and discharge types, and the signal intensity, i.e., the peak to peak amplitude of the antenna output, of the MNB antenna showed a good correlation with that of the HA (Chapter 4). The noise resistance ability of the MNB antenna was extracted using the PD in SF6 gas under the noise source experiment. The MNB antenna can detect the PD signal under noise conditions with a higher signal-noise ratio (SNR) than HA under elimination frequency noises. The PD in SF6 gas under drone noise (2.4 GHz, Wi-Fi) experiment was performed to make practical conditions. The 100 times measurement result showed that the PD detection rate under drone noise was 1% and 94% for HA and MNB antenna, respectively. The PD signal and drone noise repetition rates were investigated to understand the advantage of MNB antenna compared with HA. As a result, it was observed that the PD signal repetition was much lower than drone noise repetition for HA, while the drone noise repetition was lower than PD signal repetition for the MNB antenna because of the noise resistance ability (Chapter 5). The communication noise elimination ability of the MNB antenna was further improved by adding the low-pass filtering function without size extension. The Filtered Multiple Narrow Band (FMNB) antenna was designed with higher noise resistance than the MNB antenna. This enhancement increased the Wi-Fi noise resistance ability from 15 dBm to more than 30 dBm. Due to this noise reduction, the FMNB antenna detected the PD signal under drone noise with a noticeable higher SNR than the MNB antenna. In addition, the microstrip filter can be designed for different frequency bands to resist certain noises. Moreover, the MNB antenna can be designed for different PD signals, and different noise condition depends on the purpose by adjusting the detection and elimination frequencies. It means the MNB antenna can be used in all types of HV equipment as a UHF sensor. Also, the noise resistance ability makes the MNB antenna is suitable to cooperate with other ICT and digital technology as a wireless and smart sensor. (Chapter 6).九州工業大学博士学位論文 学位記番号: 工博甲第551号 学位授与年月日: 令和4年3月25日1 Introduction|2 Experimental Setup and Procedure|3 Design of a Novel UHF Sensor for PD Detection|4 Discharge Detection Properties of a Multiple Narrow Band Antenna|5 Noise Resistance Properties of a Multiple Narrow Band antenna|6 Enhanced Filtered Multiple Narrow Band Antenna|7 Conclusions九州工業大学令和3年

MRI Contrast Agent Studies of Compartmental Differentiation, Dose-Dependence, and Tumor Characterization in the Brain: A Dissertation

Magnetic resonance imaging (MRI) has increasingly become the preferred imaging modality in modern day research to study disease. MRI presents an imaging technique that is practically non-invasive and without any ionizing radiation. This dissertation presents the use of contrast agents in MRI studies to differentiate compartments, to study dose dependence of relaxation times, and to characterize tumors using signal amplifying enzymes in the brain. Differentiating compartments in the brain can be useful in diffusion studies to detect stroke at an early stage. Diffusion-weighted NMR techniques have established that the apparent diffusion coefficient (ADC) of cerebral tissue water decreases during ischemia. However, it is unclear whether the ADC change occurs due to changes in the intracellular (IC) space, extracellular (EC) space, or both. To better understand the mechanism of water ADC changes in response to ischemic injury, making IC and EC compartment specific measurements of water diffusion is essential. The first study was done where manganese (Mn2+) was used as an IC contrast agent. Mn2+ uptake by cells causes shortening of the T1 relaxation time of IC water. The relative difference in T1 relaxation times between the IC and EC compartments can be used to discriminate between the MR signals arising from water in the respective compartments. Mn2+ is also widely used in manganese-enhanced MRI (MEMRI) studies to visualize functional neural tracts and anatomy in the brain in vivo. In animal studies, the goal is to use a dose of Mn2+ that will maximize the contrast while minimizing its toxic effects. The goal of dose study was to investigate the MRI dose response of Mn2+ in rat brain following SC administration of Mn2+. The dose dependence and temporal dynamics of Mn2+ after SC injection can prove useful for longitudinal in vivo studies that require brain enhancement to persist for a long period of time to visualize neuroarchitecture like in neurodegenerative disease studies. Contrast agents, in addition to their use in compartmental differentiation and dose studies, can be used for imaging tumors. The last study in this dissertation focuses on imaging EGF receptors in brain tumors. We tested a novel pretargeting imaging approach that includes the administration of humanized monoclonal antibody (anti-EGFR mAb, EMD72000) linked to enzymes with complementing activities that use a low-molecular weight paramagnetic molecule (diTyr-GdDTPA) as a reducing substrate administered following the mAb conjugates. We analyzed the differential MR tumor signal decay in vivo using orthotopic models of human glioma. The patterns of MR signal change following substrate administration revealed differences in elimination patterns that allowed distinguishing between non-specific and specific modes of MR signal decay

MRI Contrast Agent Studies of Compartmental Differentiation, Dose-dependence, and Tumor Characterization in the Brain

Magnetic resonance imaging (MRI) has increasingly become the preferred imaging modality in modern day research to study disease. MRI presents an imaging technique that is practically non-invasive and without any ionizing radiation. This dissertation presents the use of contrast agents in MRI studies to differentiate compartments, to study dose dependence of relaxation times, and to characterize tumors using signal amplifying enzymes in the brain. Differentiating compartments in the brain can be useful in diffusion studies to detect stroke at an early stage. Diffusion-weighted NMR techniques have established that the apparent diffusion coefficient (ADC) of cerebral tissue water decreases during ischemia. However, it is unclear whether the ADC change occurs due to changes in the intracellular (IC) space, extracellular (EC) space, or both. To better understand the mechanism of water ADC changes in response to ischemic injury, making IC and EC compartment specific measurements of water diffusion is essential. The first study was done where manganese (Mn2+) was used as an IC contrast agent. Mn2+ uptake by cells causes shortening of the T1 relaxation time of IC water. The relative difference in T1 relaxation times between the IC and EC compartments can be used to discriminate between the MR signals arising from water in the respective compartments. Mn2+ is also widely used in manganese-enhanced MRI (MEMRI) studies to visualize functional neural tracts and anatomy in the brain in vivo. In animal studies, the goal is to use a dose of Mn2+ that will maximize the contrast while minimizing its toxic effects. The goal of dose study was to investigate the MRI dose response of Mn2+ in rat brain following SC administration of Mn2+. The dose dependence and temporal dynamics of Mn2+ after SC injection can prove useful for longitudinal in vivo studies that require brain enhancement to persist for a long period of time to visualize neuroarchitecture like in neurodegenerative disease studies. Contrast agents, in addition to their use in compartmental differentiation and dose studies, can be used for imaging tumors. The last study in this dissertation focuses on imaging EGF receptors in brain tumors. We tested a novel pretargeting imaging approach that includes the administration of humanized monoclonal antibody (anti-EGFR mAb, EMD72000) linked to enzymes with complementing activities that use a low-molecular weight paramagnetic molecule (diTyr-GdDTPA) as a reducing substrate administered following the mAb conjugates. We analyzed the differential MR tumor signal decay in vivo using orthotopic models of human glioma. The patterns of MR signal change following substrate administration revealed differences in elimination patterns that allowed distinguishing between non-specific and specific modes of MR signal decay

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Application Of Antenna Synthesis And Digital Signal Processing Techniques For Active Millimeter-wave Imaging Systems

Millimeter-wave imaging has gathered attention in recent years for its ability to penetrate clothing, thin layers of soils, and certain construction materials. However, image quality remains a challenge that needs to be addressed. One way of improving image quality is by increasing the dimensions of the collecting aperture. A sparse array can be used to synthesize a larger aperture with a limited set of relatively small detectors. In this research we design, build, and test a test-bed having an active source at 94 GHz and an array of coherent detectors, mounted on arms that extend radially on a rotary table. Using this test bed a circular area with a maximum diameter of 900 mm can be scanned. The signal is down-converted using heterodyne receivers with digital in-phase and quadrature detection. Signal correlation is performed using the digitized data, which is stored for post-processing, electronic focusing, and image reconstruction. Near-field imaging using interferometric reconstructions is achieved using electronic focusing. Imaging tests show the ability of the system to generate imagery of concealed and unconcealed objects at distances between 400 and 700 mm. A study of the effects of redundant and nonredundant configurations on image quality for 4 common detector configurations is presented. In this document we show that an active sparse-aperture imaging system using digital correlators is a viable way to generate millimeter-wave images

First electrostatic probe results from Explorer 17

Electrostatic probe results from ionospheric sounding by Explorer XVII satellit

Diffraction Analysis with UWB Validation for ToA Ranging in the Proximity of Human Body and Metallic Objects

The time-of-arrival (ToA)-based localization technique performs superior in line-of-sight (LoS) conditions, and its accuracy degrades drastically in proximity of micro-metals and human body, when LoS conditions are not met. This calls for modeling and formulation of Direct Path (DP) to help with mitigation of ranging error. However, the current propagation tools and models are mainly designed for telecommunication applications via focus on delay spread of wireless channel profile, whereas ToA-based localization strive for modeling of DP component. This thesis provides a mitigation to the limitation of existing propagation tools and models to computationally capture the effects of micro-metals and human body on ToA-based indoor localization. Solutions for each computational technique are validated by empirical measurements using Ultra-Wide-Band (UWB) signals. Finite- Difference-Time-Domain (FDTD) numerical method is used to estimate the ranging errors, and a combination of Uniform-Theory-of-Diffraction (UTD) ray theory and geometrical ray optics properties are utilized to model the path-loss and the ToA of the DP obstructed by micro- metals. Analytical UTD ray theory and geometrical ray optics properties are exploited to model the path-loss and the ToA of the first path obstructed by the human body for the scattering scenarios. The proposed scattering solution expanded to analytically model the path-loss and ToA of the DP obstructed by human body in angular motion for the radiation scenarios

Sound wave phase processing for precise positioning

Tese de mestrado. Métodos computacionais em Ciências e Engenharia. Faculdade de Engenharia. Universidade do Porto. 200

Advanced photonic and electronic systems - WILGA 2017

WILGA annual symposium on advanced photonic and electronic systems has been organized by young scientist for young scientists since two decades. It traditionally gathers more than 350 young researchers and their tutors. Ph.D students and graduates present their recent achievements during well attended oral sessions. Wilga is a very good digest of Ph.D. works carried out at technical universities in electronics and photonics, as well as information sciences throughout Poland and some neighboring countries. Publishing patronage over Wilga keep Elektronika technical journal by SEP, IJET by PAN and Proceedings of SPIE. The latter world editorial series publishes annually more than 200 papers from Wilga. Wilga 2017 was the XL edition of this meeting. The following topical tracks were distinguished: photonics, electronics, information technologies and system research. The article is a digest of some chosen works presented during Wilga 2017 symposium. WILGA 2017 works were published in Proc. SPIE vol.10445

Model of the propagation of very low-frequency beams in the Earth–ionosphere waveguide: principles of the tensor impedance method in multi-layered gyrotropic waveguides

The modeling of very low-frequency (VLF) electromagnetic (EM) beam propagation in the Earth–ionosphere waveguide (WGEI) is considered. A new tensor impedance method for modeling the propagation of electromagnetic beams in a multi-layered and inhomogeneous waveguide is presented. The waveguide is assumed to possess the gyrotropy and inhomogeneity with a thick cover layer placed above the waveguide. The influence of geomagnetic field inclination and carrier beam frequency on the characteristics of the polarization transformation in the Earth–ionosphere waveguide is determined. The new method for modeling the propagation of electromagnetic beams allows us to study the (i) propagation of the very low-frequency modes in the Earth–ionosphere waveguide and, in perspective, their excitation by the typical Earth–ionosphere waveguide sources, such as radio wave transmitters and lightning discharges, and (ii) leakage of Earth–ionosphere waveguide waves into the upper ionosphere and magnetosphere. The proposed approach can be applied to the variety of problems related to the analysis of the propagation of electromagnetic waves in layered gyrotropic and anisotropic active media in a wide frequency range, e.g., from the Earth–ionosphere waveguide to the optical waveband, for artificial signal propagation such as metamaterial microwave or optical waveguides