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Fault Detection and Identification Using Deep Learning Algorithms in Induction Motors

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Computer Modeling in Engineering & Sciences 2022年第11期133卷 435-470页

作者： Majid Hussain Tayab din Memon Imtiaz Hussain Zubair Ahmed Memon Dileep kumar Department of Electronic Engineering Quaid-e-Awam University of Engineering Science and TechnologyNawabshah67480Pakistan NCRA Condition Monitoring Systems Lab Mehran University of Engineering and TechnologyJamshoro76062Pakistan Department of Electronic Engineering Mehran University of Engineering and TechnologyJamshoro76062Pakistan Design and Creative Technology Torrens University AustraliaMelbourneAustralia Department of Electronics and Power Engineering Pakistan Navy Engineering College NUSTKarachi75350Pakistan

Owing to the 4.0 industrial revolution condition monitoring maintenance is widely accepted as a useful approach to avoiding plant disturbances and ***,Motor Current Signature Analysis(MCSA)is widely reported as a condition monitoring technique in the detection and identification of individual andmultiple Induction Motor(IM)***,checking the fault detection and classification with deep learning models and its comparison among them selves or conventional approaches is rarely reported in the ***,in this work,wepresent the detection and identification of induction motor faults with MCSA and three Deep Learning(DL)models namely MLP,LSTM,and ***,we have developed the model of Squirrel Cage induction motor in MATLAB and simulated it for single phasing and stator winding faults(SWF)using Fast Fourier Transform(FFT),short Time Fourier Transform(STFT),and Continuous Wavelet Transform(CWT)to detect and identify the healthy and unhealthy conditions with phase to ground,single phasing and in multiple fault conditions using Motor Current Signature *** faults impact on stator current is presented in the time and frequency domain(i.e.,power spectrum).The simulation results show that the scalogram has shown good results in time-frequency analysis for fault and showing its impact on the energy of current during individual fault and multiple fault *** is further investigated with three deep learning models(i.e.,MLP,LSTM,and 1D-CNN)for checking the fault detection and identification(i.e.,classification)improvement in a three-phase induction *** simulating the three-phase induction motor in various healthy and unhealthy conditions in MATLAB,we have collected current signature data in the time domain,labeled them accordingly and created the 50 thousand samples dataset for DL *** the DL models are trained and validated with a suitable number of architecture *** simulation,the multiclass confusion

关键词： Condition monitoring motor fault diagnosis stator winding faults deep learning signal processing

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

Optimal Location to Use Solar Energy in an Urban Situation

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Computers, Materials & Continua 2023年第4期75卷 815-829页

作者： Ngakan Ketut Acwin Dwijendra Indrajit Patra N.Bharath kumar Iskandar Muda Elsayed M.Tag El din Faculty of Engineering Udayana UniversityBali80361Indonesia An Independent Researcher NIT DurgapurWest Bengal700027India Department of Electrical and Electronics Engineering Vignan’s Foundation for Science Technology and ResearchGuntur522001India Department of Doctoral Program Faculty Economic and BusinessUniversitas Sumatera UtaraMedan20222Indonesia Electrical Engineering Department Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11835Egypt

This study conducted in Lima, Peru, a combination of spatial decisionmaking system and machine learning was utilized to identify potentialsolar power plant construction sites within the city. Sundial measurementsof solar radiation, precipitation, temperature, and altitude were collectedfor the study. Gene Expression Programming (GEP), which is based on theevolution of intelligent models, and Artificial Neural Networks (ANN) wereboth utilized in this investigation, and the results obtained from each werecompared. Eighty percent of the data was utilized during the training phase,while the remaining twenty percent was utilized during the testing phase. Onthe basis of the findings, it was determined that the GEP is the most suitablenetwork for predicting the location. The test state’s Nash-Sutcliffe efficiency(NSE) was 0.90, and its root-mean-square error (RMSE) was 0.04. Followingthe generation of the final map based on the results of the GEP model, itwas determined that 9.2% of the province’s study area is suitable for theconstruction of photovoltaic solar power plants, while 53.5% is acceptable and37.3% is unsuitable. The ANN model reveals that only 1.7% of the study areais suitable for the construction of photovoltaic solar power plants, while 66.8%is acceptable and 31.5% is unsuitable.

关键词： Solar energy renewable energy machine learning

Design and Analysis of Graphene Based Tunnel Field Effect Transistor with Various Ambipolar Reducing Techniques

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Computers, Materials & Continua 2023年第7期76卷 1309-1320页

作者： Puneet kumar Mishra Amrita Rai Nitin sharma Kanika sharma Nitin Mittal Mohd Anul Haq Ilyas Khan ElSayed M.Tag El din Department of Electronics and Communication Engineering G L Bajaj Institute of Technology and ManegmentGretear NoidaIndia Department of Electronics and Communication Engineering Chandigarh UnievrsityMohaliPunjabIndia Department of Electronics and Communication Engineering NITTTRChandigarhIndia University Center of Research&Development Chandigarh UniversityMohali121102India Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Mathematics College of Science Al-ZulfiMajmaah University11952Al-MajmaahSaudi Arabia Electrical Engineering Department Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11835Egypt

The fundamental advantages of carbon-based graphene material,such as its high tunnelling probability,symmetric band structure(linear dependence of the energy band on the wave direction),low effective mass,and characteristics of its 2D atomic layers,are the main focus of this research *** impact of channel thickness,gate under-lap,asymmetric source/drain doping method,workfunction of gate contact,and High-K material on Graphene-based Tunnel Field Effect Transistor(TFET)is analyzed with 20 nm *** modelling and electrical characteristic performance have been simulated using the Atlas device simulator of SILVACO TCAD with user-defined material syntax for the newly included graphene material in comparison to silicon carbide(SiC).The simulation results in significant suppression of ambipolar current to voltage characteristics of TFET and modelled device exhibits a significant improvement in subthreshold swing(0.0159 V/decade),the ratio of Ion/Ioff(1000),and threshold voltage(-0.2 V with highly doped p-type source and 0.2 V with highly doped n-type drain)with power supply of 0.5 V,which make it useful for low power digital applications.

关键词： Graphene tunnel field effect transistor(TFET) band to band tunnelling subthreshold swing

A comparative analysis of radon (^(222)Rn) concentration in the different water sources of Ganderbal, Jammu and Kashmir

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Radiation Detection Technology and Methods 2023年第4期7卷 627-635页

作者： Mehak Mohi u din.shakeel Simnani Salik Nazir Sajad Masood Mohammad Rafiq Chakan Supriya Rani Amit kumar Singla shahid Saleem Department of Physics University of KashmirSrinagarJ&K190006India Department of Physics Maharaja Ranjit Singh Punjab Technical UniversityBathindaPunjab151001India Department of Geography and Disaster Management University of KashmirSrinagarJ&K190006India

Introduction Radon,a known carcinogen,is the second largest cause of lung carcinoma as per the World Health *** primary purpose of the present research is to examine and compare the concentrations of radon gas(^(222)Rn)in different sources of water in the Lar and Ganderbal tehsils of the district of Ganderbal,Jammu and *** groundwater ^(222)Rn concentrations indicate higher indoor radon concentrations and long-term radon exposure is extremely harmful to human health as it increases the risk of developing lung *** A scintillation-based radon monitor called the smart RnDuo was used to quantify the amount of radon activity present in water samples collected from different locations of Lar and Ganderbal regions of district *** Average radon(^(222)Rn)concentration of 1.84 BqL^(−1) was found in tap waters,3.73 BqL^(−1) in surface waters,16.56 BqL^(−1) in borewells,and 20.82 BqL^(−1) in *** higher radon concentration in groundwater is because of the direct and prolonged interaction of uranium-rich rocks and soil with the ***,monitoring and regulating radon levels in these water sources is crucial to ensure public health and safety.

关键词： Groundwater quality Ganderbal ^(222)Rn detection Scintilation detector

Influence of scattering of sh-waves in dynamic interaction of shear wall with soil layers

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Earthquake Engineering and Engineering Vibration 2020年第3期19卷 583-595页

作者： shashi kumar Swapan kumar Chakraborty Department of Mathematics Sarala Birla UniversityRanchi 835103India Department of Applied Mathematics Cambridge Institute of TechnologyRanchi 835103India Department of Mathematics Birla Institute of TechnologyMesraRanchi 835215India

The dynamic soil-structure interaction of a shear wall embedded in elastic isotropic and homogeneous soil layers underlain by bedrock,subjected to sh waves,is modeled in the present *** soil layers consist of irregular interfaces and it has been shown that the scattering due to the roughness of the layers has significant effect on the displacement of both the foundation and the shear *** demonstrate the phenomena indirect boundary element method(IBEM)has been used on the basis of its validation in previous problems of similar *** system response is compared with the analytical solution of the same type of model for vertically propagating incident sh *** is observed that for the low frequency of wave,displacement is abruptly high,and as a result the combination of shear wall and foundation perceives *** thickness of the soil layer,mass of the shear wall,stiffness of the bedrock and the soil layers all affects the system frequency and displacement.

关键词： soil dynamic interaction

Varied presentations, magnitude, and outcome of traumatic neck injuries at a level I trauma center

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Emergency and Critical Care Medicine 2022年第2期2卷 45-49页

作者： Parvez Mohi Ud din Dar Jogendra Boddeda Supreet Kaur Pratyusha Priyadarshini Abhinav kumar din.sh Bagaria Narendra Choudhary Junaid Alam Sushma Sagar Subodh kumar Amit Gupta Biplab Mishra Division of Trauma Surgery and Critical Care Jai Prakash Narayan Apex Trauma CentreAll India Institute of Medical Sciences(AIIMS)New DelhiIndia Department of General Surgery All India Institute of Medical Sciences(AIIMS)JodhpurRajasthanIndia

Introduction:Traumatic neck injuries(TNIs)constitute 5%–10%of all trauma *** injuries can be caused by either penetrating or blunt *** can have a varied presentation like cut injury over the neck,bleeding,neck swelling,breathing difficulty,dysphagia,***:This was a retrospective observational study conducted at a level I trauma center in India from January 2016 to March *** hundred thirty patients who required admission and intervention due to TNIs were included in this ***:One hundred thirty patients with neck injuries were included in this *** were predominant(91.5%)with the age ranging from 10 to *** most common mechanism of injury was physical assault(40.7%),followed by road traffic injury(23.8%)and self-inflicted injuries(18.4%).Penetrating trauma was *** neck wound with bleeding was the most common presenting *** II injuries were more common(83.8%)followed by zone I(12.3%)and zone III(3.8%).Soft tissue injury including skin,platysma breach,and strap muscle injury was present in 46.9% of *** injury was present in 13.8%,tracheal injury in 28.5%,vascular injury in 13.8%,and esophageal injury in 4.6% of ***:Penetrating neck trauma is more common than blunt in developing countries like *** Trauma Life Support(ATLS)protocol guides the initial *** definitive management depends on the type and mechanism of injury,anatomical level,severity,and the organ injured.

关键词： Bleeding Neck trauma Resuscitation Trachea Vascular injury

Clinical efficacy of direct-acting antiviral therapy for recurrent hepatitis C virus infection after liver transplantation in patients with hepatocellular carcinoma

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World Journal of Hepatology 2020年第9期12卷 628-640页

作者： Mohamed Saleh Ismail Manal Hassan Saira Aijaz Khaderi Wael Ahmed Yousry Maha Mohsen Kamal El-din Mohamed Mohamed Bahaa El-din Osama Aboelfotoh El Sayed Ahmed Omar Kaseb John Alan Goss FasihaKanwal Prasun kumar Jalal Division of Gastroenterology Baylor College of MedicineHoustonTX 77030United States Department of Internal medicine Gastroenterology and HepatologyAin Shams UniversityCairo 11566Egypt Department of Surgery Division of Abdominal TransplantationBaylor College of MedicineHoustonTX 77030United States Department of Epidemiology the University of Texas MD Anderson Cancer CenterHoustonTX 77030United States Department of Surgery Ain Shams UniversityCairo 11566Egypt Department of Gastrointestinal Medical Oncology the University of Texas MD Anderson Cancer CenterHoustonTX 77030United States

BACKGROUND Recurrent hepatitis C virus(HCV)infection of transplanted liver allografts is universal in patients with detectable HCV viremia at the time of ***-acting antiviral(DAA)therapy has been adopted as the standard of care for recurrent HCV infection in the post-transplant ***,there are insufficient data regarding its efficacy in liver transplant(LT)recipients with a history of hepatocellular carcinoma(HCC),and the risk of HCC recurrence after DAA therapy is *** of DAA treatment failure and HCC recurrence in LT *** A total of 106 LT recipients given DAAs for recurrent HCV infection from 2015 to 2019 were identified(68 with and 38 without HCC).Descriptive statistics and logistic regression models were used to estimate the multivariate odds ratios and respective 95%confidence intervals for predictors of treatment failure and HCC *** Six patients(6%)experienced DAA therapy failure post-LT and 100(94%)had a sustained virologic response at follow-up week 12.A high alanine transaminase level>35 U/L at treatment week 4 was a significant predictor of treatment *** to pre-LT DAA therapy is a predictor of post-LT HCC recurrence,P=*** relapse post-LT was also associated with post-transplantation HCC recurrence,P=*** DAAs are effective and safe in the treatment of recurrent HCV infection in LT recipients with history of *** to pre-and post-LT DAA therapy is associated with post-transplantation HCC recurrence.

关键词： Direct-acting antiviral Liver transplant Hepatocellular carcinoma Recurrence

Optimization of the Voltage Doubler Stages in an RF-DC Convertor Module for Energy Harvesting

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Circuits and Systems 2012年第3期3卷 216-222页

作者： Kavuri Kasi Annapurna Devi Norashidah Md. din Chandan kumar Chakrabarty Department of Electrical and Electronic Engineering INTI International University Nilai Malaysia Department of Electronics and Communication Engineering Universiti Tenega Nasional Kajang Malaysia

This paper presents an optimization of the voltage doubler stages in an energy conversion module for Radio Frequency (RF) energy harvesting system at 900 MHz band. The function of the energy conversion module is to convert the (RF) signals into direct-current (DC) voltage at the given frequency band to power the low power devices/circuits. The design is based on the Villard voltage doubler circuit. A 7 stage Schottky diode voltage doubler circuit is designed, modeled, simulated, fabricated and tested in this work. Multisim was used for the modeling and simulation work. Simulation and measurement were carried out for various input power levels at the specified frequency band. For an equivalent incident signal of –40 dBm, the circuit can produce 3mV across a 100 k? load. The results also show that there is a multiplication factor of 22 at 0 dBm and produces DC output voltage of 5.0 V in measurement. This voltage can be used to power low power sensors in sensor networks ultimately in place of batteries.

关键词： Energy Conversion RF Schottky Diode Villard Energy Harvesting