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Increasing the Sensitivity of the Method of Early Detection of Cyber-Attacks in Telecommunication Networks Based on Traffic Analysis by Extreme Filtering

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ENERGIES 2020年第11期13卷 2774页

作者： Privalov, Andrey Lukicheva, Vera Kotenko, Igor Saenko, Igor Emperor Alexander I St Petersburg State Transport 9 Moskovsky Pr St Petersburg 190031 Russia Russian Acad Sci SPIIRAS St Petersburg Inst Informat & Automat 3914 Liniya St Petersburg 199178 Russia

The paper proposes a method for improving the accuracy of early detection of cyber attacks with a small impact, in which the mathematical expectation is a fraction of the total, and the pulse repetition period is quite long. Early detection of attacks against telecommunication networks is based on traffic analysis using extreme filtering. The algorithm of fuzzy logic for deciding on the results of extreme filtering is suggested. The results of an experimental evaluation of the proposed method are presented. They demonstrate that the method is sensitive even with minor effects. In order to eliminate the redundancy of the analyzed parameters, it is enough to use the standard deviation and the correlation interval for decision making.

关键词： detection of cyberattacks extreme filtering traffic decomposition fuzzy logic algorithm

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Research on Robust Control of Automobile Anti-lock Braking System Based on Road Recognition

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JORDAN JOURNAL OF MECHANICAL AND INDUSTRIAL ENGINEERING 2022年第3期16卷 343-352页

作者： Qi, Gengxin Fan, Xiaobin Zhu, Shuaiwei Chen, Xinbo Wang, Pan Li, Hao Henan Polytech Univ Sch Mech & Power Engn Jiaozuo 454000 Henan Peoples R China China North Vehicle Res Inst Beijing 100072 Peoples R China

Automobile anti-lock braking system (ABS) is an important component of vehicle active safety control system and is widely used in various automobiles. In the car braking process, the car equipped with ABS can effectively shorten the braking distance, and avoid vehicle side-slip, etc., ensuring the braking performance and driving safety of the vehicle. In order to further improve the performance and robustness of automobile ABS, a robust ABS control method based on road recognition is proposed for the current ABS control method. Based on the fuzzy logic control method, the road surface adhesion coefficient is estimated to realize the road surface recognition, and the optimal slip rate is dynamically obtained. According to the slip rate, a robust controller of ABS is designed. The simulation results show that the robust controller of ABS has good control effect and robustness and can estimate the road adhesion coefficient in real time. (C) 2022 Jordan Journal of Mechanical and Industrial Engineering. All rights reserved

关键词： Automobile anti-lock braking system vehicle active safety system tire/road adhesion coefficient fuzzy logic algorithm robust controller

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Intelligent automated system based on a fuzzy logic system for plant protection product control in orchards

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International Journal of Agricultural and Biological Engineering 2019年第3期12卷 92-102页

作者： Peter Berk A.Belšak D.Stajnko M.Lakota N.Muškinja M.Hočevar J.Rakun Faculty of Agriculture and Life Sciences University of MariborPivola 102311 HoceSlovenia Faculty of Mechanical Engineering University of MariborSmetanova 172000 MariborSlovenia Faculty of Electrical Engineering and Computer Science University of MariborSmetanova 172000 MariborSlovenia Faculty of Mechanical Engineering University of LjubljanaAskerceva 61000 LjubljanaSlovenia

The spraying of plant protection product(PPP)in orchards is a very hazardous working procedure,owing to the spray drift caused by the uneven operation of conventional axial boom *** research describes an intelligent automated system for precise(PPP)distribution in *** is based on an intelligent decision-making model using ultrasonic measurements of leaf area density under laboratory conditions,which serve to trigger electromagnetic valves(EMV)on the axial boom sprayer.A fuzzy logic algorithm was an integrated part of the intelligent system for controlling the PPP by generating the pulse width modulation signal and applying it through the EMV of the prototype boom *** results showed that by using an intelligent decision-making model,the same efficiency as with conventional methods could be achieved,but with reduced usage of plant protection ***,the intelligent automated system used 4.8 times less spray mixture than the conventional one.

关键词： plant protection product boom sprayer electromagnetic valve fuzzy logic algorithm tree canopy

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Rolling Guide Filtering and Non-subsampled Contourlet Transform for Fusion of Visible and Infrared Images

JOURNAL OF APPLIED SCIENCE AND ENGINEERING

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JOURNAL OF APPLIED SCIENCE AND ENGINEERING 2020年第4期23卷 687-694页

作者： Wang, Xiaodong Chen, Hongyou Zhengzhou Univ Sci & Technol Sch Elect Engn Zhengzhou 450000 Peoples R China

Image fusion is essentially an image enhancement technology, which aims to generate fusion images with richer information and more features by extracting complementary information from images collect-ed by different sensors (such as infrared and visible light) or the same sensor (such as multi-focus image). For the fusion of infrared and visible images, it is easy to produce problems such as missing detail infor-mation and suppressing less noise. In this paper, we propose a Visible and Infrared Images fusion method by combining Non-subsampled Contourlet Transform (NSCT) and rolling guide filtering. First, fuzzy log-ic algorithm is used to enhance the contrast of visible image and highlight the effective information of image. Second, the enhanced visible and infrared images are decomposed by NSCT to obtain the low fre-quency and high frequency sub-bands. The improved rolling guide filter is used to enhance the edge and other details of the high frequency sub-band of infrared image. Third, mean gradient strategy and fuzzy logic strategy are used to fuse high and low frequency sub-bands, respectively. Experiments show that the proposed fusion method has better results than other state-of-the-art methods in terms of information entropy, standard deviation, and mutual information.

关键词： Image fusion NSCT Rolling guide filtering fuzzy logic algorithm

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An experimental method for diagnostic of incipient broken rotor bar fault in induction machines

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HELIYON 2022年第3期8卷 e09136页

作者： Sabir, Hamza Ouassaid, Mohammed Ngote, Nabil Mohammed V Univ Rabat Engn Smart & Sustainable Syst Res Ctr Mohammadia Sch Engineers Rabat Morocco ENSMR Engn Sch Rabat Morocco

Induction Motors (IMs) have multiple advantages, as they are robust and easy to maintain. A small fault in a single rotor bar could cause the break of this bar, subsequently breaking a large adjacent bar number because of the oscillations created by the unbalance of the rotor. For this reason, early detection of any small failure is recommended to remove some posterior damage and the maintenance expenses. This work proposes a new and original method that uses the cyclostationnarity of the electrical signal instead of the vibratory signal to detect the incipient failure. The experimental data has been manipulated. The results prove that this new designed strategy can identify and classify the level of cracking that occurs in a single rotor bar, even under various loads.

关键词： Asynchronous machines Industrial engineering Signal processing Early detection Incipient fault System fault detection Condition monitoring Arti ficial intelligence fuzzy logic algorithm

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Wireless battery charging control for electric vehicles: a user-involved approach

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IET POWER ELECTRONICS 2019年第10期12卷 2688-2696页

作者： Ouyang, Quan Xu, Guotuan Liu, Kailong Wang, Zhisheng Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing Jiangsu Peoples R China Univ Warwick Warwick Mfg Grp Coventry CV4 7AL W Midlands England

This study presents a user-involved wireless battery charging approach for electric vehicles, which enables the battery to reach the user-specified state by regulating the charging current provided by a wireless charger with double-sided inductor-capacitor-capacitor compensation topology. Specifically, an optimal state of charge (SOC) trajectory is first generated through formulating and solving an optimisation issue with the consideration of user demand and operating constraints. Next, a cascade control strategy is proposed to regulate the wireless charger to make the battery track the scheduled charging trajectory. The out loop control designs suitable charging current for SOC trajectory tracking, which can effectively suppress the violation of the charging constraints by on-line compensating the battery model bias. In the inner loop, a fuzzy proportion-integration (PI) algorithm is proposed to control the wireless charger to provide the charging current designed by the out loop, in which fuzzy logic algorithm is utilised to on-line tune the PI gains to improve the control performance. Extensive real-time results demonstrate the effectiveness and promise of the proposed user-involved wireless battery charging control strategy.

关键词： PI control fuzzy control battery powered vehicles control system synthesis optimisation power capacitors cascade control three-term control battery chargers electric vehicles user-involved wireless battery charging approach user-specified state wireless charger double-sided inductor-capacitor-capacitor compensation topology charge trajectory user demand cascade control strategy battery track scheduled charging trajectory SOC trajectory tracking charging constraints battery model bias control performance user-involved wireless battery charging control strategy charging current fuzzy proportion-integration algorithm PI gain fuzzy logic algorithm

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Novel strategies to reduce engine emissions and improve energy efficiency in hybrid vehicles

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CLEANER ENGINEERING AND TECHNOLOGY 2021年 2卷

作者： Sher, Farooq Chen, Sihong Raza, Ali Rasheed, Tahir Razmkhah, Omid Rashid, Tazien Rafi-ul-Shan, Piyya M. Erten, Begum Coventry Univ Sch Mech Aerosp & Automot Engn Fac Engn Environm & Comp Coventry CV1 5FB W Midlands England COMSATS Univ Islamabad Dept Mech Engn Sahiwal Campus Sahiwal Pakistan Int Soc Engn Sci & Technol Coventry W Midlands England Shanghai Jiao Tong Univ Sch Chem & Chem Engn Shanghai 200240 Peoples R China NFC Inst Engn & Fertilizer Res Dept Chem Engn Faisalabad Pakistan Cardiff Metropolitan Univ Cardiff Sch Management Cardiff CF5 2YB Wales Istanbul Gedik Univ Gedik Vocat Sch Dept Occupat Hlth & Safety TR-34876 Istanbul Turkey

Hybrid electric vehicles (HEV) can provide a same power as gasoline and diesel-powered vehicles while also reducing fuel consumption by 40-50%. However, due to a complex system of HEV, the power control strategies are used to improve the work efficiency, fuel economy and to reduce exhaust emissions. In the present work, four parameters are studied with the main focus on the optimization of power system of a parallel hybrid vehicle. These parameters are the influence of fuzzy logic algorithm on hybrid electric vehicle power train that is acceleration performance, climbing performance, engine efficiency and exhaust gas emissions. First, the vehicle's power train is optimized using the Advanced Vehicle Simulator (ADVISOR). Secondly, by ensuring acceleration and climbing performance, the vehicle manufacturing cost is reduced by reducing the weight of the vehicle. Thirdly, two driving road test conditions, Extra-Urban Driving Cycle (EUDC) and Urban Dynamometer Driving Schedule (UDDS) are used to enhance the fuel consumption efficiency of the vehicle. Using a fuzzy logic algorithm for random operations, the operating range of an internal combustion engine is controlled as much as possible in the most efficient range. Through the control of 121 different algorithms, the operating efficiency of the powertrain is optimized to reduce exhaust emissions and improve fuel efficiency. The results showed that the proposed strategy can reduce fuel consumption by 5%, CO by 50% and improved the operating efficiency of engine by 15%. Not only this control strategy optimizes the efficiency of powertrain, but also the efficiency of the internal combustion engine. Moreover, the motor and battery pack itself can be optimized. These hybrid vehicles can minimize the fuel demand and are the best substitute for the classic internal combustion engines.

关键词： Clean energy Parallel hybrid electric vehicles Energy management fuzzy logic algorithm Optimization and CO emissions

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A Glider-Assist Routing Protocol for Underwater Acoustic Networks With Trajectory Prediction Methods

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IEEE ACCESS 2020年 8卷 154560-154572页

作者： Su, Yishan Zhang, Lin Li, Yun Yao, Xing Tianjin Univ Dept Elect & Informat Engn Tianjin 300072 Peoples R China Guilin Univ Aerosp Technol Guilin 541004 Peoples R China

In recent years, marine exploration has become one of the most popular research subjects. At present, gliders in Underwater Acoustic Sensor Networks (UASNs) are equipped with a variety of sensors, which can play an important role in marine detection and monitoring. In addition, gliders also have the ability of data collection and storage. When coexisting with the sensor nodes, they can be regarded as special sensor nodes with semi-determined sawtooth trajectories. In hybrid UASNs including sensor nodes and gliders, a robust routing protocol is required to improve the poor network connectivity caused by long transmission delay, high bit error rate and unreliable transmission links. In this article, the fuzzy logic algorithm (FLA) is used to convert multiple input parameters into one output value, thus reducing the storage burden of the network. Therefore, a glider-assist routing scheme with trajectory prediction is proposed to improve the connectivity of the hybrid network. The simulation results show that our scheme is superior to other protocols in terms of delivery ratio, end-to-end latency and lifetime.

关键词： Routing Routing protocols Trajectory Relays Underwater acoustics Delays Hybrid underwater acoustic sensor network routing protocol fuzzy logic algorithm Kalman filtering

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An approach towards selective harmonic elimination switching pattern of cascade switched capacitor twenty nine-level inverter using artificial bee colony algorithm

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MICROPROCESSORS AND MICROSYSTEMS 2020年 79卷 103292-103292页

作者： Ramesh, A. Sait, H. Habeebullah Dr Pauls Engn Coll Dept Elect & Elect Engn Villupuram Tamil Nadu India Anna Univ Dept Elect & Elect Engn BIT Campus Tiruchirappalli Tamil Nadu India

This paper introduces harmonic removal in a Switched capacitor multilevel inverter utilizing artificial bee colony (ABC) method. The main focus is to neglect lower order harmonics by resolving nonlinear equation. In our paper, ABC algorithm is enforced to a twenty nine level inverter for resolving the equation. Selective Harmonics Elimination PWM is mainly used in lower order harmonics suppression. The MLI gets input from the SEPIC converter that comprises of Photo Voltaic Module as a source of generation. The PV panel output voltage is maintained constantly with a greater gain DC-DC SEPIC converter. Hence to obtain high power from the PV system, gray Wolf Optimization technique and fuzzy logic control is used. The high frequency modulation technique i.e. Multi Carrier modulation technique is too applied in the proposed new topology for reducing the higher order harmonics. The proposed ABC harmonics elimination technique is also compared with genetic algorithm based SHE method. MATLAB simulation platform is utilized to simulate the module. The experimental verification of the proposed work was done using DSPIC30F2010 controller.

关键词： Switched capacitor multi level inverter SEPIC converter Selective harmonics elimination MPPT algorithm GWO algorithm fuzzy logic algorithm ABC algorithm DSPIC controller

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Rolling Guide Filtering and Non-subsampled Contourlet Transform for Fusion of Visible and Infrared Images

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淡江理工学刊 2020年第4期23卷 687-694页

作者： Xiaodong Wang Hongyou Chen

Image fusion is essentially an image enhancement technology, which aims to generate fusion images with richer information and more features by extracting complementary information from images collected by different sensors (such as infrared and visible light) or the same sensor (such as multi-focus image). For the fusion of infrared and visible images, it is easy to produce problems such as missing detail information and suppressing less noise. In this paper, we propose a Visible and Infrared Images fusion method by combining Non-subsampled Contourlet Transform (NSCT) and rolling guide filtering. First, fuzzy logic algorithm is used to enhance the contrast of visible image and highlight the effective information of image. Second, the enhanced visible and infrared images are decomposed by NSCT to obtain the low frequency and high frequency sub-bands. The improved rolling guide filter is used to enhance the edge and other details of the high frequency sub-band of infrared image. Third, mean gradient strategy and fuzzy logic strategy are used to fuse high and low frequency sub-bands, respectively. Experiments show that the proposed fusion method has better results than other state-of-the-art methods in terms of information entropy, standard deviation, and mutual information.

关键词： Image fusion NSCT Rolling guide filtering fuzzy logic algorithm

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