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FPGA Implementation of Extended Kalman Filter for Parameters Estimation of Railway Wheelset

Computers, Materials & Continua 2023年第2期74卷 3351-3370页

作者： Khakoo Mal Tayab Din Memon Imtiaz Hussain Kalwar bhawani shankar chowdhry Department of Electronic Engineering Mehran University of Engineering&TechnologyJamshoro76062Pakistan Sukkur IBA University Sukkur65200Pakistan Design and Creative Technology Torrens University Australia196 Flinders StreetMelbourne3000VICAustralia Department of Electronics and Power Engineering Pakistan Navy Engineering College NUSTKarachi75350Pakistan NCRA-Condition Monitoring Systems Lab Mehran University of Engineering&TechnologyJamshoro76062Pakistan

It is necessary to know the status of adhesion conditions between wheel and rail for efficient accelerating and decelerating of railroad *** proper estimation of adhesion conditions and their real-time implementation is considered a challenge for *** this paper,the development of simulation model of extended Kalman filter(EKF)in MATLAB/Simulink is presented to estimate various railway wheelset parameters in different contact conditions of *** to concurrent in nature,the Xilinx®System-on-Chip Zynq Field Programmable Gate Array(FPGA)device is chosen to check the onboard estimation ofwheel-rail interaction parameters by using the National Instruments(NI)myRIO®development *** NImyRIO®development board is flexible to deal with nonlinearities,uncertain changes,and fastchanging dynamics in real-time occurring in wheel-rail contact conditions during vehicle *** simulated dataset of the railway nonlinear wheelsetmodel is tested on FPGA-based EKF with different track conditions and with accelerating and decelerating operations of the *** proposed model-based estimation of railway wheelset parameters is synthesized on FPGA and its simulation is carried out for functional verification on *** obtained simulation results are aligned with the simulation results obtained through *** the best of our knowledge,this is the first time study that presents the implementation of a model-based estimation of railway wheelset parameters on FPGA and its functional *** functional behavior of the FPGA-based estimator shows that these results are the addition of current knowledge in the field of the railway.

关键词： Adhesion force extended kalman filter FPGA implementation railway wheelset real-time estimation wheel-rail interaction

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Embedded System Development for Detection of Railway Track Surface Deformation Using Contour Feature Algorithm

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Computers, Materials & Continua 2023年第5期75卷 2461-2477页

作者： Tarique Rafique Memon Tayab Din Memon Imtiaz Hussain Kalwar bhawani shankar chowdhry NCRA-HHCMS Lab Mehran University of Engineering&Technology Jamshoro76062Pakistan Department of Electronic Engineering Quaid-e-Awam University of EngineeringScience&Technology Nawabshah67480Pakistan Design and Creative Technology Torrens University Australia196 Flinders StreetMelbourneVIC 3000Australia Department of Electronic Engineering Mehran University of Engineering and TechnologyJamshoro76062Pakistan Department of Electronics and Power Engineering Pakistan Navy Engineering CollegeNUST Karachi75350Pakistan

Derailment of trains is not unusual all around the world,especially in developing countries,due to unidentified track or rolling stock faults that cause massive casualties each *** this purpose,a proper condition monitoring system is essential to avoid accidents and heavy ***,the detection and classification of railway track surface faults in real-time requires massive computational processing and memory resources and is prone to a noisy ***,in this paper,we present the development of a novel embedded system prototype for condition monitoring of railway *** proposed prototype system works in real-time by acquiring railway track surface images and performing two tasks a)detect deformation(i.e.,faults)like squats,shelling,and spalling using the contour feature algorithm and b)the vibration signature on that faulty spot by synchronizing acceleration and image data.A new illumination scheme is also proposed to avoid the sunlight reflection that badly affects the image acquisition *** contour detection algorithm is applied here to detect the uneven shapes and discontinuities in the geometrical structure of the railway track surface,which ultimately detects unhealthy *** works by converting Red,Green,and Blue(RGB)images into binary images,which distinguishes the unhealthy regions by making them white color while the healthy regions in black *** have used the multiprocessing technique to overcome the massive processing and memory *** embedded system is developed on Raspberry Pi by interfacing a vision camera,an accelerometer,a proximity sensor,and a Global Positioning System(GPS)sensors(i.e.,multi-sensors).The developed embedded system prototype is tested in real-time onsite by installing it on a Railway Inspection Trolley(RIT),which runs at an average speed of 15 km/*** functional verification of the proposed system is done successfully by detecting and recording the various railway track surface faul

关键词： Railway track surface faults condition monitoring system fault detection contour detection deep learning image processing rail wheel impact

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A Novel Method Based on UNET for Bearing Fault Diagnosis

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Computers, Materials & Continua 2021年第10期69卷 393-408页

作者： Dileep Kumar Soother Imtiaz Hussain Kalwar Tanweer Hussain bhawani shankar chowdhry Sanaullah Mehran Ujjan Tayab Din Memon National Centre of Robotics and Automation HHCMS LabMehran University of Engineering&TechnologyJamshoro76020SindhPakistan Department of Electrical Engineering DHA SUFFA UniversityKarachiSindhPakistan Department of Electronic Engineering Mehran University of Engineering and TechnologyJamshoro76020SindhPakistan

Reliability of rotating machines is highly dependent on the smooth rolling of ***,it is very essential for reliable operation of rotating machines to monitor the working condition of bearings using suitable fault diagnosis and condition monitoring *** the recent past,Deep Learning(DL)has become applicable in condition monitoring of rotating machines owing to its *** paper proposes a novel bearing fault diagnosis method based on the processing and analysis of the vibration *** proposed method is the UNET model that is a recent development in DL *** model is applied to the 2D vibration images obtained by transforming normalized amplitudes of the time-series vibration data samples into the corresponding vibration *** UNET model performs pixel-level feature learning using the vibration images owing to its unique *** results demonstrate that the model can perform dense predictions without any loss of label information,generally caused by the sliding window labelling *** comparative analysis with other DL models confirmed the superiority of the UNET model which has achieved maximum accuracy of 98.91%and F1-Score of 99%.

关键词： Condition monitoring deep learning fault diagnosis rotating machines vibration

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Automated Controller Placement for Software-Defined Networks to Resist DDoS Attacks

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Computers, Materials & Continua 2021年第9期68卷 3147-3165页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Lee Ching Kwang Rizaludin Kaspin bhawani shankar chowdhry Rajkumar Buyya Satya Prasad Majumder Manoj Gupta Shuaib Memon Faculty of Computing&Informatics Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation CentreCyberjaya63000SelangorMalaysia National Center of Robotics and Automation Mehran University of Engineering&TechnologyJamshoroPakistan Department of Computer Science and Engineering Hanyang UniversitySeoul04763South Korea School of Electrical and Electronic Engineering Nanyang Technological University639798Singapore Cloud Computing and Distributed Systems Laboratory The University of MelbourneMelbourneVIC 3053Australia Department of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology(BUET)Dhaka1205Bangladesh Department of Electronics and Communication Engineering JECRC UniversityVidhaniJaipur303905India Auckland Institute of Studies Mt AlbertAucklandNew Zealand

In software-defined networks(SDNs),controller placement is a critical factor in the design and planning for the future Internet of Things(IoT),telecommunication,and satellite communication *** research has concentrated largely on factors such as reliability,latency,controller capacity,propagation delay,and energy ***,SDNs are vulnerable to distributed denial of service(DDoS)attacks that interfere with legitimate use of the *** ever-increasing frequency of DDoS attacks has made it necessary to consider them in network design,especially in critical applications such as military,health care,and financial services networks requiring high *** propose a mathematical model for planning the deployment of SDN smart backup controllers(SBCs)to preserve service in the presence of DDoS *** a number of input parameters,our model has two distinct ***,it determines the optimal number of primary controllers to place at specific locations or nodes under normal operating ***,it recommends an optimal number of smart backup controllers for use with different levels of DDoS *** goal of the model is to improve resistance to DDoS attacks while optimizing the overall cost based on the *** simulated results demonstrate that the model is useful in planning for SDN reliability in the presence of DDoS attacks while managing the overall cost.

关键词： SDN automated controller placement SBC ILP DDoS attack

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Unprecedented Smart Algorithm for Uninterrupted SDN Services During DDoS Attack

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Computers, Materials & Continua 2022年第1期70卷 875-894页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Rizaludin Kaspin Iram Haider Sana Nisar J.P.C.Rodrigues bhawani shankar chowdhry Muhammad AslamUqaili Satya Prasad Majumder Danda B.Rawat Richard Etengu Rajkumar Buyya Faculty of Computing&Informatics Multimedia UniversityPersiaranMultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation Centre63000CyberjayaSelangorMalaysia Federal University of Piauí(UFPI) TeresinaPIBrazil Instituto de Telecomunica珲es 6201-001Covilh?Portugal National Center of Robotics and Automation-Condition Monitoring Systems Lab MUETJamshoroPakistan Department of Electrical and Electronic Engineering BUETDhaka1205Bangladesh Department of Electrical Engineering and Computer Science Data Science and Cybersecurity CenterHoward UniversityWashingtonDCUSA Cloud Computing and Distributed Systems(CLOUDS)Laboratory School of Computing and Information SystemsThe University of MelbourneMelbourneVIC 3053Australia

In the design and planning of next-generation Internet of Things(IoT),telecommunication,and satellite communication systems,controller placement is crucial in software-defined networking(SDN).The programmability of the SDN controller is sophisticated for the centralized control system of the entire ***,it creates a significant loophole for the manifestation of a distributed denial of service(DDoS)attack ***,recently a Distributed Reflected Denial of Service(DRDoS)attack,an unusual DDoS attack,has been ***,minimal deliberation has given to this forthcoming single point of SDN infrastructure failure ***,recently the high frequencies of DDoS attacks have increased *** this paper,a smart algorithm for planning SDN smart backup controllers under DDoS attack scenarios has *** proposed smart algorithm can recommend single or multiple smart backup controllers in the event of DDoS *** obtained simulated results demonstrate that the validation of the proposed algorithm and the performance analysis achieved 99.99%accuracy in placing the smart backup controller under DDoS attacks within 0.125 to 46508.7 s in SDN.

关键词： SDN smart algorithm RTZLK-DAASCP DDoS attack DRDoS

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