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Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006. 1st International Symposium on

作者： Kezhao Li Jianping Yuan Xiaokui Yue Qun Fang College of Astronautics Northwestern Polytechnical University Xi'an China Northwestern Polytechnical University China

ISBN: (纸本)0780393953

In this paper a novel algorithm is proposed for the spacecraft detection and relative navigation problems. The main contents of this algorithm are studied as following: (i) detection algorithm by using mathematical morphology (MM). In spacecraft detection and information extraction by using MM transformation, how to design a reasonable structuring element according to the shape of spacecraft entities and its transformation information is very important, (ii) relative navigation algorithm based-on conformal geometric algebra (CGA). CGA allows to higher order entities (lines, planes, circles, spheres) in the same manner as with points. It is a novel way to deal with 2D-3D pose estimation problem. The description of spacecraft entities and its transformation based-on CGA will be studied, (iii) combining detection with relative navigation organically. Using the theory of spacecraft dynamics and spacecraft entities transformation information, we provide a new thought to construct and reconstruct dynamically structuring elements. The reasonable decomposition of structuring element for spacecraft features detection and providing the spacecraft entities transformation information based-on CGA theory can assure relative navigation to be combined with detection organically.

关键词： aerospace computing algebra mathematical morphology navigation 2D pose estimation problem 3D pose estimation problem conformal geometric algebra detection algorithm information extraction mathematical morphology relative navigation algorithm spacecraft d

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A Robust STFT Based algorithm for detection of Symmetrical Fault during Power Swing 7

A Robust STFT Based Algorithm for Detection of Symmetrical F...

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7th IEEE Power India International Conference (PIICON)

作者： Bhattacharjee, Rupanjali De, Abhinandan BBIT Dept Elect Engn Budge Budge 700137 W Bengal India IIEST Shibpur Dept Elect Engn Howrah 711103 W Bengal India

ISBN: (纸本)9781467389624

Effective power swing blocking (PSB) schemes are a crucial component of any power system protection technology. Distance relays act as the primary protection element of the long distance transmission lines. Its operation is based on the impedance trajectory at the relay location. However, apart from faults, there exist multiple power system events that are nonhazardous in nature but has similar impedance trajectories to faults. In order to prevent false triggering of distance relays in such cases, various PSB schemes have been proposed for proper detection and prevention. In the present work a robust STFT based algorithm for detection of symmetrical fault in existance of power swing is proposed. The input attribute of the algorithm is the three phase instantaneous power at the relay location. The 39 bus New England power system model has been utilized as the test environment. Further five diverse power system events simulated in MATLAB-SIMULINK platform have been employed to validate the efficacy of the proposed algorithm.

关键词： detection algorithm fault detection power swing symmetrical fault STFT

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An algorithm for detection of Malicious Messages on CAN Buses

An Algorithm for Detection of Malicious Messages on CAN Buse...

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2012 National Conference on Information Technology and Computer Science

作者： Congli Ling State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control,Zhejiang University Hangzhou,China Dongqin Feng State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control,Zhejiang University Hangzhou,China

Control systems are encountering increasing security threats;as one of the common systems,CAN control system is very facile to be *** at the improvement of CAN control system security,an algorithm for detection of malicious CAN messages is given,and it has been implemented in the CANoe simulation *** result shows that this algorithm has powerful detection function and valuable practice signification.

关键词： CAN bus detection algorithm malicious messages CANoe

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The Application of the detection and Data Mining algorithm Optimization in Honeynet

The Application of the Detection and Data Mining Algorithm O...

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2009 ISECS International Colloquium on Computing, Communication, Control, and Management

作者： Dong Nanping College of Automation of Beijing Union University Beijing, China Zhou Guanling, Wang Yuping College of Automation of Beijing Union University Beijing, China

A technical scheme, which can properly arrange IDS and optimally apply the algorithms of detection and data mining to the Honeynet environment, is proposed in the building automation system completed by the author recently. In this specific environment, the position of IDS is deployed reasonably and the anomaly and misuse detection algorithm of IDS is designed and selected optimally. Meanwhile, the misuse detection rules are updated dynamically with the combination of data-mining association rule algorithm. The design makes the classical and mature algorithms display their technical characteristics and advantages to the largest extent in the project and enable the honeynet to protect the internal control network as expected.

关键词： detection algorithm honeynet association rules optimal design

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Joint assessment of temporal segmentation, time unit and detection algorithms in syndromic surveillance

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PREVENTIVE VETERINARY MEDICINE 2022年 203卷 105619页

作者： Brilleaud, Sophie Durand, Benoit Le Strat, Yann Sala, Carole French Agcy Food Environm & Occupat Hlth & Safety Epidemiol Unit 14 Rue Pierre & Marie Curie F-94706 Maisons Alfort France French Natl Publ Hlth Agcy Sante Publ France 12 Rue Val lOsne F-94415 St Maurice France French Agcy Food Environm & Occupat Hlth & Safety 31 Ave Tony Gamier F-69364 Lyon 07 France Paris Est Creteil Univ Creteil France

The choice of the aggregation that defines the temporal unit of epidemiological surveillance is part of the more theoretical framework of the modifiable temporal unit problem (MTUP). It has been demonstrated that this choice influences temporal cluster detection and may lead to false-positive results and poor estimation of regression model parameters. In syndromic surveillance (SyS), despite the choice of which temporal aggregation to use being crucial, it has not yet been addressed in the literature. In most SyS systems, this choice is driven by the frequency of the data collection and/or human resources available, although neither the temporal unit's influence on the performance of anomaly detection algorithms nor on the efficiency of the SyS are *** main objective of our study was to analyze the influence of the temporal aggregation unit on the performances of SyS detection algorithms used routinely, according to the characteristics of specific syndromes and outbreaks. Simulating daily time series of various syndromes, we tested three different time series aggregation methods. For each of four anomaly detection algorithms and their variants, we calculated seven performance indicators and multi-criteria scores to guide epidemiologists in their choice of which temporal aggregation of surveillance to use. From 19,200 analyzed time series, we observed an effect of temporal aggregation on the performance of the detection algorithms tested. Results also showed that the time aggregation unit was linked to the detection algorithm used, and that strong aggregation-algorithm interactions need to be taken into account when deciding on which aggregation-algorithm pair to use. Using theoretical data, our study also showed that no one ideal aggregation-algorithm pair exists for all contexts when deciding on which temporal unit of surveillance to use, and that the choice depends on several *** results can help public health practitioners choose the most appropr

关键词： Modifiable temporal unit problem Syndromic surveillance detection algorithm One health

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Early detection Technique for Stator Winding Inter-Turn Fault in BLDC Motor Using Input Impedance

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2015年第1期51卷 240-247页

作者： Park, Jun-Kyu Jeong, Chae-Lim Lee, Seung-Tae Hur, Jin Univ Ulsan Dept Elect Engn Ulsan 680749 South Korea

This paper proposes a diagnosis technique algorithm for a brushless dc motors under a stator inter-turn fault (ITF) condition using input impedance. The algorithm has early detection and various speed-range detection advantages. To early and accurately detect the ITF, the rotating speed, input current, voltage, resistance, and inductance must be analyzed. Therefore, we choose the input impedance as the detection factor because it includes all these factors. In this paper, the fault-detection system works without requiring a fast Fourier transform and the calculation of the negative-sequence impedance from the comparison of the measured impedance with the database impedance. The proposed technique was verified by the simulation and experiment.

关键词： Brushless dc (BLDC) motors detection algorithm early detection input impedance inter-turn fault

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3D Camera and Pulse Oximeter for Respiratory Events detection

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IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 2021年第1期25卷 181-188页

作者： Coronel, Carmina Wiesmeyr, Christoph Garn, Heinrich Kohn, Bernhard Wimmer, Markus Mandl, Magdalena Glos, Martin Penzel, Thomas Kloesch, Gerhard Stefanic-Kejik, Andrijana Boeck, Marion Kaniusas, Eugenijus Seidel, Stefan AIT Austrian Inst Technol GmbH A-1210 Vienna Austria Kepler Univ Hosp Dept Neurol 2 A-4020 Linz Austria Oberosttereich Gesundheitsholding Salzkammergut Klinikum Voklabruck A-4840 Vocklabruck 4840 Austria Adv Sleep Res GmbH Berlin Germany Charite Univ Med Berlin Interdisciplinary Sleep Med Ctr D-10117 Berlin Germany Saratov NG Chernyshevskii State Univ Saratov 410012 Russia Med Univ Vienna Dept Neurol A-1090 Vienna Austria Vienna Univ Technol TU Wien Inst Electrodynam Microwave & Circuit Engn A-1040 Vienna Austria

Objective: The purpose of this study was to derive a respiratory movement signal from a 3D time-of-flight camera and to investigate if it can be used in combination with SpO2 to detect respiratory events comparable to polysomnography (PSG) based detection. Methods: We derived a respiratory signal from a 3D camera and developed a new algorithm that detects reduced respiratory movement and SpO2 desaturation to score respiratory events. The method was tested on 61 patients synchronized 3D video and PSG recordings. The predicted apnea-hypopnea index (AHI), calculated based on total sleep time, and predicted severity were compared to manual PSG annotations (manualPSG). Predicted AHI evaluation, measured by intraclass correlation (ICC), and severity classification were performed. Furthermore, the results were evaluated by 30-second epoch analysis, labelled either as respiratory event or normal breathing, wherein the accuracy, sensitivity, specificity and Cohens kappa were calculated. Results: The predicted AHI scored an ICC r 0.94 (0.90 0.96 at 95 confidence interval, p < 0.001) compared to manualPSG. Severity classification scored 80 accuracy, with no misclassification by more than one severity level. Based on 30-second epoch analysis, the method scored a Cohens kappa 0.72, accuracy 0.88, sensitivity 0.80, and specificity 0.91. Conclusion: Our detection method using SpO2 and 3D camera had excellent reliability and substantial agreement with PSG-based scoring. Significance: This method showed the potential to reliably detect respiratory events without airflow and respiratory belt sensors, sensors that can be uncomfortable to patients and susceptible to movement artefacts.

关键词： Cameras Three-dimensional displays Sleep apnea Sensors Biomedical measurement Manuals Biomedical computing detection algorithm biomedical signal processing biomedical monitoring

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Method for Online detection of Arcing in Low-Voltage Distribution Systems

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IEEE TRANSACTIONS ON POWER DELIVERY 2017年第3期32卷 1244-1252页

作者： Mukherjee, Ayan Routray, Aurobinda Samanta, Anik Kumar Indian Inst Technol Adv Technol Dev Ctr Kharagpur 721302 W Bengal India Indian Inst Technol Dept Elect Engn Kharagpur 721302 W Bengal India

This paper presents an algorithm for online detection of arcing in low-voltage (230 V, 50 Hz) distribution systems. Electromagnetic radiation has been used as a feature for discrimination between arc and nonarc signals. The output of the electromagnetic radiation sensor has been analyzed in the spectral domain using the log-spectral distance metric for the detection of arcing. For validation of this method, a testbench comprising an arc generation setup has been developed in the laboratory. The algorithm has been tested against arc and arc-mimicking normal signals using the testbench to validate its effectiveness. Further, the algorithm is implemented online using xPC target (an embedded platform) for studying the feasibility and accuracy of its online implementation. A system based on this method can continuously monitor the health of a distribution network and, thus, can be very helpful in safeguarding against fire hazards due to electric arcing.

关键词： Arc discharges detection algorithm electrical fault detection electrical safety electromagnetic radiation event detection hazards power system protections signal-processing algorithms spectral analysis

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Computer-based detection and analysis of heart sound and murmur

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ANNALS OF BIOMEDICAL ENGINEERING 2005年第7期33卷 937-942页

作者： El-Segaier, M Lilja, O Lukkarinen, S Sörnmo, L Sepponen, R Pesonen, E Univ Lund Hosp Childrens Hosp Dept Paediat Div Paediat Cardiol SE-22185 Lund Sweden Lund Univ Dept Electrosci S-22100 Lund Sweden Helsinki Univ Technol Dept Appl Elect Helsinki Finland

To develop a digital algorithm that detects first and second heart sounds, defines the systole and diastole, and characterises the systolic murmur. Heart sounds were recorded in 300 children with a cardiac murmur, using an electronic stethoscope. A Digital algorithm was developed for detection of first and second heart sounds. R-waves and T-waves in the electrocardiography were used as references for detection. The sound signal analysis was carried out using the short-time Fourier transform. The first heart sound detection rate, with reference to the R-wave, was 100% within 0.05-0.2R-R interval. The second heart sound detection rate between the end of the T-wave and the 0.6R-R interval was 97%. The systolic and diastolic phases of the cardiac cycle could be identified. Because of the overlap between heart sounds and murmur a systolic segment between the first and second heart sounds (20-70%) was selected for murmur analysis. The maximum intensity of the systolic murmur, its average frequency, and the mean spectral power were quantified. The frequency at the point with the highest sound intensity in the spectrum and its time from the first heart sound, the highest frequency, and frequency range were also determined. This method will serve as the foundation for computer-based detection of heart sounds and the characterisation of cardiac murmurs.

关键词： detection algorithm signal analysis short-time Fourier transform systolic murmur

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Robust Data-Driven Adversarial False Data Injection Attack detection Method With Deep Q-Network in Power Systems

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2024年第8期20卷 10405-10418页

作者： Ran, Xiaohong Tay, Wee Peng Lee, Christopher H. T. Nanyang Technol Univ Energy Res Inst Singapore 637141 Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

Electric power systems have been increasingly subjected to false data injection attacks (FDIAs) and adversarial examples, which inject well-designed disturbance signals into the measurements, and thereby generate erroneous state estimation (SE) results. The present work addresses this issue by proposing a robust data-driven attack detection algorithm. We apply a novel metric denoted as Euclidian distance similarity ratio for detecting stealthy attack during the SE process. Second, two different deep Q networks are, respectively, employed for detecting FDIAs and adversarial examples based on their respective inflection points (IPs). We also propose sufficient and necessary conditions for the successful detection of adversarial examples based on the corresponding analyses of IPs. Finally, two networks are trained using deep reinforcement learning. The effectiveness of the proposed robust detection method is demonstrated based on simulations involving IEEE 14, 57, and 118 bus power systems.

关键词： Adversarial examples deep reinforcement learning (DRL) detection algorithm inflection points (IPs)

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