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60th IEEE Nuclear Science Symposium (NSS) / Medical Imaging Conference (MIC) / 20th International Workshop on Room-Temperature Semiconductor X-ray and Gamma-ray Detectors

作者： Lu, Yihuan Zhang, Hao Liang, Zhengrong Gindi, Gene SUNY Stony Brook Dept Elect & Comp Engn Stony Brook NY 11794 USA

ISBN: (纸本)9781479905348

We address the problem of optimizing data acquisition for photon-counting CT. We formulate a task-driven approach using a clinically relevant task of detection and localization of a lesion in a search region. The appropriate scalar measure of task performance is ALROC, the area under the LROC curve. For hardware optimization, the observer performing the task should operate on the raw (sinogram) data so that the best possible information, independent of the parameters of any particular reconstruction algorithm, is collected. To carry out the task, we use the ideal observer (IO), a numerical observer that yields the maximal ALROC amongst all observers. This differs from the usual numerical observer that operates on the reconstructed data and is designed so that its performance tracks that of a human observer. So while the optimization is carried out in the sinogram domain, the task definition is in the object domain. In this work, we mathematically specialize a previously developed 10 to the case of photon-counting transmission tomography. We applied the 10 to a 2D simulation of CT with the task of detecting a 3mm lung nodule in a lung region of a 512x512 phantom. The application was to optimize the number of angular acquisitions given a fixed dose. A plot of ALROC vs. angle number peaks at 42 angles. We also plotted ALROC vs. dose (at 105 angles) to characterize the increase in task performance with count level.

关键词： X-ray detection and localization ideal observer system optimization photon-counting

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Review on detection and localization of underwater target

Review on detection and localization of underwater target

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2nd International Conference on Civil Engineering, Architecture and Building Materials (CEABM 2012)

作者： Yang Guang Zheng Yi Wang Shitao Xiang Xu Yu Yanting Shandong Prov Key Lab Ocean Environm Monitoring T Qingdao 266001 Peoples R China Shandong Acad Sci Inst Oceanograph Instrumentat Qingdao 266001 Peoples R China

ISBN: (纸本)9783037854228

Europe, the United States and China have conducted a lot of research on the detection and localization of underwater target. The United States, the typical representative among Europe and America, pays much attention to marine research and has a profound foundation. In China, Harbin Engineering University, Institute of Acoustics of Chinese Academy of Sciences and Northwestern Polytechnical University also have done a lot of research on target detection and localization. Overall, the United States of America and other developed countries temporarily precede China in underwater target detection and localization.

关键词： Underwater Target detection and localization Research Status

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MULTISENSORY SURVEILLANCE DRONE FOR SURVIVOR detection AND GEOlocalization IN COMPLEX POST-DISASTER ENVIRONMENT 39

MULTISENSORY SURVEILLANCE DRONE FOR SURVIVOR DETECTION AND G...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Rohman, Budiman P. A. Andra, M. B. Putra, H. F. Fandiantoro, D. H. Nishimoto, Masahiko Kumamoto Univ Grad Sch Sci & Technol Kumamoto Japan Indonesian Inst Sci Jakarta Indonesia

ISBN: (纸本)9781538691540

The large scale natural disasters often result in a large death victim number and severe damage to buildings. Although some of the impacts can be reduced by the foreseeable future, they cannot be fully eliminated. In order to minimize the victim number, we propose a multisensory surveillance drone system employed an autonomous and robust unmanned aerial vehicle equipped with multiple sensors for specifically enhancing the search and rescue mission to detect the survivors in the post-disaster area. As the main sensors, we employ an ultra-wideband radar;microphone array, camera, and an RFID reader. For making the geolocalization of the detected survivors, we also employ laser range finder and LIDAR. This paper will discuss briefly the system design and the development progress of the project. Besides, the next step of the development is also presented.

关键词： disaster survivor detection and localization ultra-wideband radar microphone array computer vision radio frequency identification

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Sensor fault diagnosis in inland navigation networks based on a grey-box model

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IFAC-PapersOnLine 2018年第24期51卷 742-747页

作者： Segovia, P. Blesa, J. Duviella, E. Rajaoarisoa, L. Nejjari, F. Puig, V. Terrassa Campus Gaia Building Rambla Sant Nebridi 22 Terrassa08222 Spain c/ Llorens i Artigas 4-6 Barcelona08028 Spain IMT Lille Douai Univ. Lille Unité de Recherche Informatique Automatique LilleF-59000 France

Inland navigation networks are equipped with limnimeters to measure and record water level data for the control of water levels and the management of water resources. When faults occur on sensors, corrupted data can be considered as correct, leading to undesirable management actions. Therefore, it is necessary to detect and localize these faults. In this paper, the detection and localization of sensor faults is performed through the analysis of the parameters of a grey-box model, which are obtained from available real data. The parameters are determined with a sliding window, with the exception of the delays, which are considered known a priori. A fault is detected and then localized when there is a change in the value of the parameters. This approach is well suited for constant faults and particularly well adapted for intermittent faults. Data of an inland navigation reach located in the north of France are used to highlight the performance of the proposed approach. © 2018

关键词： Fault detection Air navigation Electric fault currents Failure analysis Information management Inland waterways Large scale systems Navigation Water levels Water management Corrupted data detection and localization Grey box modeling Inland navigation Intermittent fault Sensor fault diagnosis Sliding Window Water level data

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Detecting, locating, and characterizing voids in disaster rubble for search and rescue

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ADVANCED ENGINEERING INFORMATICS 2019年 42卷 100974-000页

作者： Hu, Da Li, Shuai Chen, Junjie Kamat, Vineet R. Univ Tennessee Dept Civil & Environm Engn Knoxville 851 Neyland Dr Knoxville TN 37996 USA Univ Michigan Dept Civil & Environm Engn 2350 Hayward2008 GG Brown Ann Arbor MI 48109 USA

After natural and man-made disasters such as earthquakes, hurricanes, and explosions, victims may survive in voids that are formed naturally in collapsed structures. First responders need to identify and locate these critical voids for rapid search and rescue operations. Due to the complex and unstructured occlusions in disaster areas, visual and manual search is time-consuming and error-prone. In this study, we proposed a novel method to automatically detect, locate, and characterize voids buried in disaster rubble using ground penetrating radar (GPR). After preprocessing the collected radargrams, the boundaries of potential voids are segmented based on radar signal patterns, and the 95% confidence intervals are constructed around the segmented boundaries to account for uncertainties. To improve the detection accuracy, the geometric relations of the detected boundaries and their signal characteristics are examined to confirm the void existence. Then, the void location and dimension are estimated based on calibrated velocity of radar wave and its travel time. The effectiveness and efficiency of the proposed method were manifested by its performance in laboratory and field experiments. The contribution of this study is twofold. First, the feasibility of using GPR to detect, locate, and characterize voids in collapsed structures is experimentally tested, innovatively extending the application of GPR to search and rescue operations. Second, algorithms are developed to process non-intuitive radargrams to provide first responders actionable information.

关键词： First responders Search and rescue Disaster Void Ground penetrating radar detection and localization

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Time Delay Estimation of Ultra High Frequency Signals Radiated from Partial Discharge Sources

Time Delay Estimation of Ultra High Frequency Signals Radiat...

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IEEE Applied Signal Processing Conference (ASPCON)

作者： Anitha, Bhukya Koley, Chiranjib Natl Inst Technol Durgapur Dept Elect Engn Durgapur W Bengal India

ISBN: (纸本)9781538666869

Supply of uninterrupted power is of present need in progressing India. The most of these interruptions occur mainly due to failures in insulations of electrical apparatus. Therefore, the present work aimed at developing an early warning system for electrical distribution substations by predicting insulation breakdown. This paper, focused on time delay estimation in between the UHF signals received at multiple sensors placed around the substation. The delay estimation is most critical and essential part in detection and localization of electrical component having weakness or some defects in insulation and act as PD source. Unfortunately, the radiated UHF signals are highly contaminated with noise, form mobile, TV, and Radio broadcastings. Previous works on time delay estimation in the area mainly depends on time domain based estimation procedures, such as first peak (FP), cumulative energy (CE), and cross correlation (CC). However, recent study reveals that, each PD sources having less variant and almost unique frequency domain based signature. Therefore, in the work, Generalized Cross Correlation (GCC) which is a frequency domain based correlation technique for estimation of time delay has been investigated in details. In the work different weighing functions for the GCC, such as Smoothed Coherence Transform (SCOT), the Phase Transform (PHAT), the Eckart Filter (EF) and the Maximum Likelihood (ML) estimator. The study reveals that the GCC with ML function provide most accurate and precise estimation of time delay.

关键词： detection and localization Distribution Substation Generalized Cross Corelation,. Partial Discharge Time Delay Estimation Ultra High Frequency

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Characterization of dynamic phenomena based on the signal analysis in phase diagram representation domain

Characterization of dynamic phenomena based on the signal an...

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作者： Angela Digulescu University Of Grenoble

学位级别：博士

Signals' deformation along their propagation path is among the most important aspect which has to be taken into account at reception. These effects are caused by phenomena like attenuation, reflection, dispersion and noise. Whereas the first two are rather easy to monitor, because they affect the amplitude, respectively the delay, the latter two are more difficult to control, because they change signals' parameters (amplitude, frequency and phase) in an environment-dependent manner. In this thesis, the main objective is to contribute to the analysis of signals related to different physical phenomena, aiming to better understand them as well as to estimate their parameters that are interesting from application point of view. Different applicative contexts have been investigated in active and passive sensing configurations. For the active part, we mention the monitoring of cavitation phenomena and its characterization for hydraulic system surveillance. The second application of the active sensing is the underwater object detection and tracking without synchronization between sensors. For the passive configuration, we focus on the pressure transient analysis in water pipes investigation with a non- intrusive method and on the surveillance of electrical power systems in the presence of transient phenomena such as electrical arcs. Despite the differences between the physical considerations, we propose a unique mathematical model of the signals issued from the active/passive sensing system used to analyze the considered phenomena. This model is based on the Recurrence Plot Analysis (RPA) and Recurrence Quantification Analysis (RQA) methods. With this concept, we propose the phase-space based waveform design. This waveform design technique presents the interest to conduct to a high speed sensing methods, very useful to monitor dynamic phenomena. Moreover, we propose new tools for the investigation of the signals characteristics. The first one is the TDR* measure (Time Dist

关键词： Signal deformation Phase diagram Recurrence Plot Analysis Phase-space based adaptive waveform detection and localization Signal characterization

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localization and classification of power quality disturbances using maximal overlap discrete wavelet transform and data mining based classifiers

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IFAC-PapersOnLine 2016年第1期49卷 437-442页

作者： Upadhyaya, Swarnabala Mohanty, Sanjeeb Department of Electrical Engineering National Institue of Technology Rourkela769008 India

This paper has proposed the time-series based maximal overlap discrete wavelet transform (MODWT) technique for detection and localization of different types of power quality (PQ) disturbances. Ten types of different PQ events of the voltage signal such as sag, swell, interruption, harmonic, spike, notch etc. are analyzed with the aforementioned wavelet transform (WT). Each of the signal is decomposed up to fourth level with the MODWT. The co-efficients of MODWT decomposition are further used for feature extraction which are the input to the classifiers like Support Vector Machine (SVM) and Decision Tree(DT). For the detection of the disturbances, the signals are decomposed up to four finer levels whereas for the classification, decomposition is carried out up to seventh finer levels. © 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Data mining Decision trees Discrete wavelet transforms Power quality Signal reconstruction Support vector machines Wavelet transforms detection and localization Maximal overlap discrete wavelet transforms Power quality disturbances PQ event Types of power Voltage signals

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A Holistic Vision-based Hazard detection Framework for Asteroid Landings

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IFAC-PapersOnLine 2016年第17期49卷 218-223页

作者： Yan, Yunfeng Qi, Donglian Li, Chaoyong Yu, Miao Chen, Tuo College of Electrical Engineering Zhejiang University Hangzhou China

A holistic vision-based hazard detection framework for asteroid landing is introduced in this paper. The proposed holistic conjecture takes advantage of the Hough Transform method and decision forests, shares the simplicity and wide applicability of the Hough transform but bypasses the problem of obstacle multi-size detection and permits detection of multiple objects. The framework is conducive to hazard avoidance, satisfying the safe bound of the lander and the exploration task, and adaptive to environment, autonomous without additive complex filtering. The results show that the framework provides detection and localization performance close to that of human calibrations and can be further improved when larger and more diverse datasets are available. © 2016

关键词： Landing Asteroids Forestry Hazards Hough transforms Object detection Complex filtering Decision forest detection and localization Exploration tasks Hazard areas Holistic visions Safe landing Transform methods

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Adaptive split spectrum processing for ultrasonic signal in the pulse echo test

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RUSSIAN JOURNAL OF NONDESTRUCTIVE TESTING 2015年第4期51卷 245-257页

作者： Bouden, T. Djerfi, F. Nibouche, M. Jijel Univ Dept Automat LEND Lab Jijel Algeria UWE Univ Bristol Dept Engn Design & Math Bristol Avon England

In this paper, an Adaptive Split Spectrum Processing technique (A-SSP) is proposed, to improve ultrasonic echoes detection. It is an arrangement of conventional Split Spectrum Processing (SSP) with an empirical method of analyzing nonlinear and non-stationary signals, called Empirical Mode Decomposition (EMD). This proposed technique allows breaking up the signal into several bands of frequencies in an adaptive way and intrinsic to the treated signal using EMD. It enables us to know the internal contents and the local changes of the ultrasonic signal and makes the detection of any desired targets more flexible for the coherent noise problem. In the combination phase of A-SSP, a linear operation for selected intrinsic mode functions and a non linear one for non selected intrinsic mode functions are used to reconstruct the signal with separated echoes. To evaluate the proposed techniques (A-SSP with different combination operations), firstly a mortar specimen with artificial defect is used to resolve the defects detection and localization problem. Secondly a paste cement specimen is also used to resolve the materials characterization problem. The signals were obtained using a technique applied in pulse-echo mode, known as the prism technique. Numerical and experimental tests were performed to verify the effectiveness and reliability of the proposed technique and to show its excellent performances.

关键词： Non-Destructive Testing (NDT) paste cement mortar propagation velocity thickness detection and localization Split Spectrum Processing (SSP) Empirical Mode Decomposition (EMD)

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