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作者： Windish, John Joseph PennState University Libraries

学位级别：Master of Science

Synchronization in wireless communications is an important problem. Good synchronization is critical to reliable signal detection and estimation. In this thesis, the concept of synchronization is presented as well as several specific examples of wireless synchronization. An overview of the current state of the art in synchronization, including different techniques and implementations, is *** Time Offset Robust Modulation (STORM) is a waveform design technique involving the simultaneous transmission of a base waveform as well as a time-scaled and time- delayed copy of that waveform. For some applications this technique is attractive as a possible candidate to enhance synchronization performance, due to the different tradeoffs of its performance properties. This thesis presents background for the STORM technique. From there, a theoretical analysis of the performance of STORM as a possible timing synchronization mechanism is ***, this thesis performs a number of simulations showing the performance of STORM synchronization and timing under a variety of different channel conditions. The simulation results are compared to the theoretical analysis. Finally, conclusions from these STORM synchronization and timing simulations and the analyses are presented. Based on these conclusions, potential future work to develop STORM as a timing synchronization scheme is presented.

关键词： timing signal processing algorithm maximum likelihood detection correlation synchronization

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Bearing Defect Diagnosis Based on Harmonic Wavelet Transform and Singular Value Ratio Spectrum

Bearing Defect Diagnosis Based on Harmonic Wavelet Transform...

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5th International Conference on Intelligent Control and Information processing (ICICP)

作者： Hou Zhefei Wang YunPeng Kang Yong Dalian Air Force Commun NCO Acad Dalian Peoples R China

ISBN: (纸本)9781479936502

A novel signal processing algorithm was proposed here for vibration signal analysis in condition monitoring and health diagnosis of rolling bearings. Such technique required an envelope being extracted from vibration signal with Harmonic Wavelet Transform. The principal periodic component in the envelope was subsequently detected, enhanced and reconstructed with sweep frequency method based on singular value ratio (SVR) spectrum. Such signal processing approach was experimentally evaluated by using vibration signals measured on rolling element bearings that contained localized structural defects with proved validity and efficiency.

关键词： condition monitoring rolling bearings signal reconstruction vibrational signal processing vibrations wavelet transforms SVR spectrum envelope extraction harmonic wavelet transform health diagnosis localized structural defects principal periodic component detection principal periodic component enhancement principal periodic component reconstruction rolling bearing defect diagnosis rolling element bearings signal processing algorithm singular value ratio spectrum sweep frequency method vibration signal analysis Harmonic analysis Time-frequency analysis Vibrations Wavelet analysis Wavelet transforms wavelet transforms rolling bearings Condition monitoring Vibration signal processing algorithms signal reconstruction Fourier analysis Time frequency analysis Wavelet Analysis signal analysis defect diagnosis

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Rapid and robust radioisotopes identification algorithms of X-Ray and gamma spectra

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MEASUREMENT 2021年 168卷 108456-108456页

作者： El-Tokhy, Mohamed S. Egyptian Atom Energy Author Engn Dept Nucl Res Ctr P 13759 Inshas Egypt

Fast nuclide identification with higher accuracy rate is a significant requirement within nuclear applications. So effective spectrum identification algorithms are developed for low resolution spectra of NaI(TI) scintillator and Si (Li) detectors. Identification of X-ray and gamma complex spectra is the main objective of current research. So the experimental gamma and X-ray data are trained and tested using artificial neural network (ANN), support vector machine (SVM) and similarity classifiers. The features of acquired X-ray and gamma spectra are extracted using eight algorithms. These algorithms depend on fusion of time-domain descriptors (FTDD), electromyography (EMG), multiscale wavelet packet (MWP), multiscale wavelet packet with statistics (MWPS), principle component analysis (PCA), multi-dimensional scale, the preserved linear projection (LPP) and diffusion map. Robustness of these algorithms is investigated in terms of noise degradations such as Gaussian, Rician, Rayleigh and other complex degradations. Classification accuracy is investigated with the source name. The recognized spectrum is analyzed from view of peak width calibration, efficiency calibration, sum peak analysis, peak-to-Compton ratio (PCR). The rapid identification process is conducted with the algorithm based on electromyography method for both gamma and X-ray spectra. However, the algorithm based on diffusion map realizes the slowest spectrum identification. It is concluded that, for gamma and X-ray spectra, the SVM classifier achieves the fastest identification with maximum rate of 99%. Finally, the ANN is observed to achieve better rate of 100% with slower identification process depending on FTDD, EMG, LPP methods. The proposed approach helps the realization of fastest spectrum identification and classification of gamma and X-ray spectra within nuclear applications with higher robustness and accuracy.

关键词： Spectrum identification Nuclear security Medical and industrial applications signal processing algorithm

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A novel algorithm for highly sensitive and rapid hotspot detection in HTS magnets using quasi-continuous fiber Bragg gratings

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MEASUREMENT 2023年第1期214卷

作者： Huang, Xiyong Gonzales, Jofferson T. Badcock, Rodney A. Victoria Univ Wellington Paihau Robinson Res Inst Wellington New Zealand

Most optical fiber sensors based on Brillouin/Rayleigh scattering, and discrete fiber Bragg gratings (FBGs) cannot offer the speed and distributed sensing with operation in a cryogenic environment < 80 K necessary for superconducting magnet protection. An ultra-long fiber Bragg grating (ULFBG) comprised of quasi-continuous FBGs has the potential to rapidly detect the occurrence of a thermal hot spot in high-temperature super-conducting magnets. However, processing the data for detection purpose is challenging. This is because the spectrum of an ULFBG is complex, and the hotspot induced spectral changes are difficult to identify. In this paper, we present the novel Spectral Intensity Change (SIC) algorithm to 1) extract the region of interest within the spectrum based on unique change patterns, 2) identify the direction of temperature change, and 3) process the isolated spectral data to signal hotspot events. To demonstrate the effectiveness of the algorithm, three ULFBGs with sensing lengths of 0.2, 0.5 and 1.9 m are used to detect events of temperature variations. Using the algorithm, ULFBG sensors not only can identify a hot spot event rapidly and accurately but also achieve a significantly enhanced signal to noise ratio (SNR) at 80 K. The SIC algorithm has the potential to be implemented for real-time hotspot and quench detection in superconducting magnets.

关键词： Distributed sensing Fiber optic sensor Fiber Bragg grating signal processing algorithm Pattern recognition Feature extraction Region of interest Real-time monitoring Cryogenics

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Material classification through distance aware multispectral data fusion

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MEASUREMENT SCIENCE AND TECHNOLOGY 2013年第4期24卷 045001-045001页

作者： Schwaneberg, O. Koeckemann, U. K. Steiner, H. Sporrer, S. Kolb, A. Jung, N. Bonn Rhein Sieg Univ Appl Sci Dept Comp Sci D-53757 St Augustin Germany Univ Siegen Inst Vis & Graph Comp Graph & Multimedia Syst Grp D-57076 Siegen Germany

Safety applications require fast, precise and highly reliable sensors at low costs. This paper presents signal processing methods for an active multispectral optical point sensor instrumentation for which a first technical implementation exists. Due to the very demanding requirements for safeguarding equipment, these processing methods are targeted to run on a small embedded system with a guaranteed reaction time T < 2ms and a sufficiently low failure rate according to applicable safety standards, e.g., ISO-13849. The proposed data processing concept includes a novel technique for distance-aided fusion of multispectral data in order to compensate for displacement-related alteration of the measured signal. The distance measuring is based on triangulation with precise results even for low-resolution detectors, thus strengthening the practical applicability. Furthermore, standard components, such as support vector machines (SVMs), are used for reliable material classification. All methods have been evaluated for variants of the underlying sensor principle. Therefore, the results of the evaluation are independent of any specific hardware.

关键词： displacement measurement optical sensor optical triangulation signal processing algorithm detection and estimation opto-electronic protective device

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Adaptive Phase Detrending for GNSS Scintillation Detection: A Case Study Over Antarctica

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IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 2022年 19卷

作者： Spogli, Luca Ghobadi, Hossein Cicone, Antonio Alfonsi, Lucilla Cesaroni, Claudio Linty, Nicola Romano, Vincenzo Cafaro, Massimo Ist Nazl Geofis & Vulcanol I-00143 Rome Italy SpacEarth Technol I-00143 Rome Italy Univ Aquila Dept Informat Engn Comp Sci & Math I-67100 Laquila Italy Finnish Geospatial Res Inst FI-02430 Masala Finland Univ Salento Dept Engn Innovat I-73100 Lecce Italy

We aim at contributing to the reliability of the phase scintillation index on Global Navigation Satellite System (GNSS) signals at high-latitude. To the scope, we leverage on a recently introduced detrending scheme based on the signal decomposition provided by the fast iterative filtering (FIF) technique. This detrending scheme has been demonstrated to enable a fine-tuning of the cutoff frequency for phase detrending used in the phase scintillation index definition. In a single case study based on Galileo data taken by a GNSS ionospheric scintillation monitor receiver (ISMR) in Concordia Station (Antarctica), we investigate how to step ahead of the cutoff frequency optimization. We show how the FIF-based detrending allows deriving adaptive cutoff frequencies, whose value changes minute-by-minute. They are found to range between 0.4 and 1.2 Hz. This allows better accounting for diffractive effects in phase scintillation index calculation and provides a GNSS-based estimation of the relative velocity between satellite and ionospheric irregularities.

关键词： Cutoff frequency Global navigation satellite system Indexes Ionosphere Receivers Standards Monitoring Galileo Global Navigation Satellite Systems (GNSSs) ionosphere ionospheric irregularities iterative filtering modal analysis signal processing algorithm transform

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Safety in e-Scooters: a Machine-Learning Approach for Online Second Passenger Detection

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IFAC-PapersOnLine 2024年第10期58卷 14-21页

作者： Jessica Leoni Mara Tanelli Silvia Carla Strada Sergio Savaresi Politecnico di Milano Dipartimento di Elettronica Informazione e Bioingegneria (DEIB) Milan Italy

Electric scooters are pivotal for urban mobility, yet safety concerns still prevent widespread adoption. Research identifes rider negligence, such as carrying a second passenger, as a major risk. To address this issue, we propose an autonomous system for real-time detection of second passengers. By analyzing vehicle dynamics through minimal sensors and employing an interpretable machine learning approach, our solution ensures accuracy and interpretability. Rigorous testing with diverse users validates its effectiveness, showcasing adaptability to user characteristics and road conditions, proving the potential of this approach to foster safer electric scooter usage.

关键词： Electric scooter risk detection machine-learning signal processing algorithm smart mobility

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Low power millimeter wave radar system for the visually impaired

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JOURNAL OF ENGINEERING-JOE 2019年第19期2019卷 6034-6038页

作者： Long, Ningbo Wang, Kaiwei Cheng, Ruiqi Hu, Weijian Yang, Kailun Zhejiang Univ Coll Opt Sci & Engn Hangzhou Zhejiang Peoples R China

In order to help visually impaired people to avoid obstacles, a K-band millimetre wave (MMW) radar system based on the principle of frequency-modulated continuous wave (FMCW) is proposed in this study. The FMCW basic principle and the signal processing algorithm are elaborated in detail. The prototype of the radar system has been designed and manufactured. The experiment results show the qualified detection accuracy in view of low deviation. The maximum deviations from the range measurement experiments for a person and a car are 0.14 and 0.47m, respectively. As a wearable system, the radar system has the characteristics of low power and small size, which is very suitable for blind navigation application. In addition, the MMW radar has broad application prospects in the field of automotive blind spot detection and small robots.

关键词： handicapped aids FM radar CW radar millimetre wave radar radar detection radionavigation medical signal detection visually impaired people signal processing algorithm wearable system low power K-band millimetre wave radar system low power K-band MMW radar system frequency-modulated continuous wave radar system FMCW radar system radar detection blind navigation application automotive blind spot detection

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algorithm for recognizing arousals related to breathing event on the micro-movement sensitive mattress monitoring system

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Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument 2008年第SUPPL.期29卷 367-370页

作者： Cao, Zhengtao Yang, Jun Zhu, Yingying Zhang, Hongjin Yu, Mengsun The Fourth Military Medical University Xi'an 710032 China Institute of Aviation Medicine Air Force Beijing 100036 China School of Control Science and Engineering Shandong University Jinan 250061 China

A new algorithm for recognizing arousals related to breathing event that can be used on the micro-movement sensitive mattress monitoring system was presented. Firstly, the method included pre-processing the heart rate to get rid of the rapid-changing element and the slow-changing element in it. Following, the heart rate was processed using the wavelet analysis to make arousals more obvious. Finally, arousals were detected using the algorithm based on the characteristics of heart rate element that was related those. The contrast between our method and manual method on the polysomnography showed that the former can detect typical arousals and was consistent with the latter in most cases.

关键词： Arousals related to breathing event Non-invasive recognization signal processing algorithm

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