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Supervised Learning Approaches for Vibration Analysis and Anomaly Detection in Rotating Machines 3

Supervised Learning Approaches for Vibration Analysis and An...

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3rd International Conference on Emerging Trends in electrical, Control, and Telecommunication engineering, ETECTE 2024

作者： Ali, Syed Zulfiqar Ali, Syed Hasnat Javeed, Anees Ullah, Ihsan Memon, Sufyan Ali Manzoor, Sajjad Dept. of Electrical and Computer Engineering CUI Abbottabad Campus Abbottabad Pakistan Dept. of Defence Systems Engineering Sejong University Seoul Korea Republic of Dept. of Electrical Engineering MUST AJK Mirpur Pakistan

ISBN: (纸本)9798331504861

Safety and reliability are crucial for modern systems and technologies. This paper presents an approach for real-time anomaly detection in rotating machines using vibration analysis and machine learning algorithms for predictive maintenance. Rotating machines such as motors, engines, gearboxes and turbines are widely used systems and faults in these systems can result in complete shutdowns. Preventing unexpected downtime while ensuring equipment reliability and safety is essential. In this context, anomaly detection plays a vital role in monitoring the healthy operation of rotating machines. A test-bed was designed to generate datasets for both balanced (healthy) and unbalanced (faulty) motor conditions. The experimental setup consists of a three-phase induction motor, a signal acquisition system (Raspberry Pi), a vibration sensor (MPU6050) and a coupling system capable of adjusting motor balance. Supervised machine learning algorithms, Support Vector Machine (SVM) and Random Forest (RF) were applied to classify and detect anomalies in the collected datasets. A grid search algorithm was employed for hyperparameter tuning of the SVM and RF models. The proposed technique achieved a maximum accuracy of approximately 98% using SVM and 100% using the RF algorithm leveraging nine optimally selected temporal features. ©2024 IEEE.

关键词： Rotating machinery

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A Review of Disease Detection in Sugarcane Using Machine Learning and Deep Learning Techniques 15

A Review of Disease Detection in Sugarcane Using Machine Lea...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Pavan, Undavalli Chandra Pateriya, R.K. Tomar, Deepak Singh Singh, Surendra Maulana Azad National Institute of Technology Dept. of computer science & engineering Bhopal India National Institute of Technology Dept. of computer science & engineering Uttarakhand India

ISBN: (纸本)9798350370249

Agriculture has been an active source of food and economic growth, but it faces significant challenges from diseases and climate change. In Indonesia, sugarcane production is severely impacted by viral infections such as Sugarcane mosaic virus (SCMV) and Sugarcane streak mosaic virus (SCSMV). These infectious diseases pose a threat to the world's sugarcane industry, resulting in significant crop losses in nations like Brazil and India, along with other viruses like the Fiji Disease Virus (FDV), and Sugarcane Yellow Leaf Virus (SCYLV). For such diseases to be managed and performance to be maintained, early detection is essential. Disease detection is accomplished by both conventional and cutting-edge approaches, such as molecular, serological, and imaging methods. However, the advancements in Machine learning, Deep learning and computational image processing algorithms have demonstrated significant potential in the early and precise diagnosis of disease. In this study, different methods used for machine learning (ML) and deep learning (DL) for plant disease diagnosis were reviewed and it highlights the need of high-quality datasets, various pre-processing techniques, robust extraction of features, and efficient classification techniques. It also discussed the issues with data collection, symptom variability, over-fitting, and imbalances in classes, along with potential avenues for further advancement in diagnosing diseases systems. © 2024 IEEE.

关键词： challenges deep learning detection hybrid models machine learning Plant diseases

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On the Feasibility of a Direct Injection Probe with a Capacitively Coupled Return and Integrated Voltage Monitor

On the Feasibility of a Direct Injection Probe with a Capaci...

引用

2024 IEEE International Symposium on Electromagnetic Compatibility, Signal and Power Integrity, EMC+SIPI 2024

作者： Harmon, Aaron Szanto, Daniel Khilkevich, Victor Beetner, Daryl Missouri University of Science and Technology Electromagnetic Compatibility Laboratory Dept. of Electrical and Computer Engineering RollaMO United States

ISBN: (纸本)9798350360394

Characterizing the susceptibility of an IC while it is integrated within a system can be challenging. Characterization is even harder if one wants to know the waveform at the target IC pin when injecting a signal on the pin. In this work, the feasibility of a direct injection probe with a capacitively coupled return and integrated voltage monitor is proposed. This probe is advantageous because it does not need to be soldered to the test device and its ability to provide a measurement of the waveform on the target IC pin during the injection. Methods for reconstructing the pin waveform based on probe measurements are discussed. Initial results indicate that the presented probe is generally insensitive to landing position variations and can accurately provide the waveform at the target IC during an injection. Future work is focused on further validation of the presented probe. © 2024 IEEE.

关键词： Probes

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Using Ant Colony Optimised Algorithms for Shortest Path Exploration by Robots 2

Using Ant Colony Optimised Algorithms for Shortest Path Expl...

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2nd IEEE International Conference on Interdisciplinary Approaches in technology and Management for Social Innovation, IATMSI 2024

作者： Singh, Aashdeep Dhawan, Sakshi Verma, Jyoti Singh, Gurpreet Kaur, Amanpreet Dept. of Computer Science & Engineering Punjab Rajpura India Dept. of Computer Application Punjab Rajpura India Chitkara University Institute of Engineering & Technology Dept. of Computer Science & Engineering Punjab Rajpura India

ISBN: (纸本)9798350360523

In the realm of robotics and autonomous systems, efficient path planning is a critical aspect for optimizing resource utilization and achieving mission objectives. This study explores the application of Ant Colony Optimized (ACO) algorithms to enhance the efficiency of robots in navigating and exploring unknown environments. Inspired by the foraging behavior of ants, ACO algorithms are employed to find the shortest paths by leveraging pheromone communication and decentralized decision-making. Ant Colony Optimization is then introduced as a bio-inspired solution to address these challenges. The experimental results demonstrate the capability of the ACO algorithm to efficiently explore complex environments, adapt to changes in the surroundings, and converge to optimal paths. Insights gained from these analyses contribute to the refinement of the ACO algorithm for diverse robotic applications. The findings of this research have practical implications for the development of autonomous robots operating in real-world scenarios, such as search and rescue missions, environmental monitoring, and surveillance. This study provides a valuable foundation for the integration of bio-inspired algorithms in robotics, advancing the state-of-the-art in autonomous exploration and path planning. © 2024 IEEE.

关键词： Motion planning

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Encoding Cyclic Redundancy Checked Sequences 5

Encoding Cyclic Redundancy Checked Sequences

引用

5th IEEE Middle East and North Africa COMMunications Conference, MENACOMM 2025

作者： Abdel-Ghaffar, Khaled A. S. University of California Dept. Electrical and Computer Engineering DavisCA95616 United States

ISBN: (纸本)9798331519957

The undetected error probability of cyclic redundancy checks (CRC) combined with an error-correcting code in a concatenated coding scheme is considered. It is shown that this probability depends very much on the encoding of the cyclic redundancy checked sequences into codewords in the error-correcting code. Furthermore, it is proved that the average undetected error probability of the concatenated code over all linear encoders of the error-correcting code is about 1/2 of that of the error-correcting code, where is the degree of the CRC polynomial. In particular, for any CRC polynomial of degree , there exists an encoding function of the error-correcting code such that the undetected error probability of the concatenated scheme is at most 1/2 of that of the error-correcting code. © 2025 IEEE.

关键词： Concatenated codes

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Computational Web Drug Discovery Application forSARS- Cov-2 Disease Using Predictive and Analytical Approach 10

Computational Web Drug Discovery Application forSARS- Cov-2 ...

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Hemkiran, S. Kartik, R. Aswath, S. Rathan Kabilan, K. Sudha Sadasivam, G. Psg Institute of Technology and Applied Research Dept. of Computer Science and Engineering Coimbatore India Psg College of Technology Dept. of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350384369

In response to the urgent need for coronavirus treatments, this research focuses on leveraging bioactivity data collection and processing for efficient drug discovery, employing computational methods to predict potential antiviral compounds. Exploratory data analysis was performed to identify patterns and trends, and various molecular descriptors were computed for the Mpro inhibitors in the descriptor dataset preparation step. A regression model was trained using the developed random forest algorithm to predict the bioactivity of new compounds against the standard value and compared with other regression models. Additionally, a web-based application was created using the random forest model to allow users to obtain predicted bioactivity values against Mpro by providing information about molecular structures. Machine learning-based bioactivity prediction offers an intriguing plan for drug discovery, and the proposed work provides a comprehensive workflow for COVID- 19 drug discovery. The web application provides a user-friendly interface for drug discovery researchers to evaluate the potential of compounds against the Mpro target quickly. © 2024 IEEE.

关键词： COVID-19

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A Novel UAV-Enabled V2V Mobile Network: A Reinforcement Learning Approach 31

A Novel UAV-Enabled V2V Mobile Network: A Reinforcement Lear...

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31st International Conference on electrical engineering, ICEE 2023

作者： Firozjae, Hosein Mohammadi Moghaddam, Javad Zeraatkar Ardebilipour, Mehrdad K. N. Toosi University of Technology Dept. Electrical Engineering Tehran Iran University of Birjand Dept. Electrical and Computer Engineering Birjand Iran

ISBN: (纸本)9798350312560

While using Unmanned Aerial Vehicles (UAVs) as flying Base Stations (FBSs) to improve the efficiency of mobile networks can be a promising approach, there are some challenges like the limited energy of the UAV. Applying Reinforcement Learning (RL) algorithms can be a practical solution to solve the energy problem. Furthermore, combining the UAV-aided mobile networks with RL algorithms can be a promising tendency to help other terrestrial vehicles to find the best route. A Vehicle-to-Vehicle (V2V) mobile network, which the UAV plays the role of a FBS and harvests energy from terrestrial users is investigated in this paper. Following that, the limited energy problem of the UAV that avoids it to complete its mission, is solved by using RL algorithms. The RL algorithm of this paper is formed by a modified Q-Learning algorithm. The effectiveness of the proposed scenario is indicated in the simulation results. It is shown in the simulation results that our RL-based proposed scenario can mitigate the flight time of the UAV impressively in comparison to the existing scenario that do not use RL algorithms. © 2023 IEEE.

关键词： Reinforcement learning

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Lifetime Extension for Solid-State Circuit Breakers in Motor Control Center Applications

Lifetime Extension for Solid-State Circuit Breakers in Motor...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Zhou, Jiale Zhao, Tiefu Wang, Yao Dept. of Electrical and Computer Engineering CharlotteNC United States Hebei University of Technology School of Electrical Engineering Tianjin China

ISBN: (纸本)9798350316445

Solid-state circuit breakers (SSCBs) are becoming increasingly popular building blocks of direct current (DC) power systems due to their characteristics of fast interruption, arc-less operation, and no moving parts in recent years. However, the application of SSCBs in alternating current (AC) systems has been limited, primarily due to competition from traditional electromechanical circuit breakers commonly used for AC protection. This paper presents a comprehensive approach to integrate multiple functionalities, including soft start, overload relay, circuit breaker, and contactor, into a single three-phase bidirectional SSCB for motor control center (MCC) applications. This integration enhances system integration, intelligence, and significantly reduces the bulk compared to conventional MCC. In this paper, the lifetime performance of the SSCB is investigated, particularly its use as a contactor, and a turn-off solution is proposed to increase the lifetime and reliability of the SSCB without the participation of any voltage overshoot suppression or zero-crossing current detection devices. Furthermore, the proposed turn-off strategy is analyzed, and the design considerations for snubber and metal oxide varistor (MOV) selection are discussed in relation to the contactor function of the SSCB. Finally, simulation and experimental results are provided to verify the effectiveness of the contactor function and the proposed turn-off scheme. © 2023 IEEE.

关键词： contactor metal oxide varistor (MOV) lifetime motor control center (MCC) short current fault protection Solid-state circuit breaker (SSCB)

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Bi-Directional Power Flow Control for Three Phase Grid Tied Converters in Ev Charging Applications

Bi-Directional Power Flow Control for Three Phase Grid Tied ...

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2024 International Conference on Recent Innovation in Smart and Sustainable technology, ICRISST 2024

作者： Prabhakar, B. Kishore, D. Ravi Venkata Srinu, P.Veera Sivaramakrishna, P.M.V. Saiprasad, T. Godavari Institute of Engineering and Technology Dept. Electrical and Electronics Engineering Rajahmundry India

ISBN: (纸本)9798350309140

The expenses associated with conventional energy have increased dramatically in recent times due to factors such as climate change, environmental degradation, and the depletion of fossil resources. Thus, there is an urgent global need to use clean, innovative energy. Worldwide, there is widespread usage of electric cars (EVs) with smart grid technologies. More and more attention has been directed into the Vehicle-to-Grid (V2G) system. The Bi-directional grid-connected AC/DC converter, which enables bilateral power transfer while satisfying grid power quality criteria, is an essential component of the V2G hybrid system. A Bi-directional Power flow control for three phase grid tied converter is presented in this study. It can offer bidirectional power transfer between EVs and the grid in addition to correcting reactive power and lowering power grid volatility. Introducing the V2G system setup and creating the mathematical model for the AC/DC converter are the first tasks. The next step is to propose an analysis of the PI control method and build a controller. D-Q-0 theory finds use in efficiently synchronising the grid and controlling ripple current in the grid current. The basis for the system simulation model is MATLAB/Simulink. © 2024 IEEE.

关键词： Vehicle-to-grid

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Two Stage Solar PV Generation using Fast Terminal Sliding Mode Control Technique 2

Two Stage Solar PV Generation using Fast Terminal Sliding Mo...

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2nd International Conference on Power, electrical, Electronics and Industrial Applications, PEEIACON 2024

作者： Siddique, Saad Md. Abi Wakkas Hasan, Md. Tarek Ratul, Md. Ruhul Amin Rajshahi University of Engineering & Technology Dept. of Electrical & Electronic Engineering Rajshahi Bangladesh

ISBN: (纸本)9798331517984

This paper introduces a Fast Terminal Sliding Mode Control scheme to regulate a photovoltaic generation system's DC-DC boost converter and single-phase inverter under varying conditions. The proposed method addresses chattering, overshoot, and transient response issues in voltage regulation. Mathematical analyses evaluate its impact on settling time, overshoot, and noise reduction. Maximum Power Point Tracking control ensures efficient operation. Comparative analysis with conventional sliding mode and proportional-integral controllers demonstrates superior performance in transient response, overshoot, settling time, and noise rejection. © 2024 IEEE.

关键词： Sliding mode control

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