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Faulty diagnostics model for wind power plant application using AI

Measurement: Sensors 2023年 25卷

作者： Sudhakar, Puladasu Kamble, Nitin K. K, Geetha Turukmane, Anil V. Perli, Suresh Babu P, Jayaraman Department of Electrical and Electronics Engineering Sree Visvesvaraya Institute of Technology and Science Telangana Mahabubnagar509204 India Department of Robotics and Automation D. Y. Patil College of Engineering Pradhikaran Akurdi Pune411044 India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Chengalpattu District Kattankulathur603203 India Department of Computer Science & Engineering VIT- AP University AmaravatiVijaywada India Department of Electrical Engineering NIT Warangal Telangana WARANGAL506004 India Department of Mechanical Engineering Prathyusha Engineering College Aranvoyalkuppam Tiruvallur Tamil Nadu Chennai602025 India

researchers desperately ought to build an efficient turbine problem detection & simulation environment given the quick increase in wind energy capacity and the steadily rising operational cost duration of wind generators. The two aspects of fault identification & fault prediction are employed to describe the primary problem features of wind generators. We examine and synthesize the studies on fault detection techniques that rely on vibrating, electrical impulse evaluation, and pattern matching to address the challenging difficulties of defect detection. During the same period, we highlight the computationally efficient, constraints, and potential directions of distinct approaches. We review recent study developments & suggest a defect forecasting model that utilizes a physical breakdown prototype with data analysis theory fused depending on the mechanics and electronic subsystem degradation features of wind energy. In this study, we employ the Internet of Things (IoT) on Deep Learning (DL) architecture to forecast and identify wind energy generation issues. The testing findings demonstrate the method's ability to diagnose faults logically and forecast their types. © 2022 The Authors

关键词： Pattern matching

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Machine Vision Applications in robotics and automation

Machine Vision Applications in Robotics and Automation

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International Conference on Science Technology engineering and Management (ICONSTEM)

作者： Bharathi GP Kavitha P Laxman Baburao Abhang G. Rathinasabapathi Vipin Sharma T. Sathish Department of Computer and Communication Engineering Sri Sai Ram Institute of Technology Chennai Tamil Nadu India Department of Electrical and Electronics Engineering R.M.K Engineering College Kavaraipettai Tamil Nadu India Department of Automation and Robotics Pravara Rural Engineering College Loni Maharashtra India Department of Mechanical Engineering Panimalar Engineering College Chennai Tamil Nadu India Department of Mechanical Engineering Medi-Caps University Indore Madhya Pradesh Department of Mechanical Engineering Saveetha School of Engineering SIMATS Chennai Tamil Nadu India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

The extensive incorporation of machine vision into the fields of robotics and automation in a variety of different ways. The various uses of machine vision and the revolutionary impact it has on the capabilities of robotic systems. This investigation is fueled by improvements in imaging technology and artificial intelligence. In the abstract, major features such as object detection, navigation, and human-robot interaction are discussed in depth. The abstract also demonstrates how machine vision algorithms contribute to enhanced precision, efficiency, and adaptability in automation processes. The purpose of thisis to shed light on the role that machine vision plays in revolutionising industrial automation, collaborative robotics, and autonomous systems by conducting an examination of real-world implementations and case studies. This all-encompassing investigation not only highlights the current status of machine vision applications but also forecasts the future trajectory of this technology, thereby establishing it as a foundational component for the development of robotics and automation in a variety of fields.

关键词： automation Service robots Navigation Machine vision Imaging Human-robot interaction Object detection

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Grasp Stability Prediction with Sim-to-Real Transfer from Tactile Sensing

arXiv

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arXiv 2022年

作者： Si, Zilin Zhu, Zirui Agarwal, Arpit Anderson, Stuart Yuan, Wenzhen The Robotics Institute Carnegie Mellon University United States The Department of Electrical Engineering Tsinghua University China Meta Reality Labs Research

Robot simulation has been an essential tool for data-driven manipulation tasks. However, most existing simulation frameworks lack either efficient and accurate models of physical interactions with tactile sensors or realistic tactile simulation. This makes the sim-to-real transfer for tactile-based manipulation tasks still challenging. In this work, we integrate simulation of robot dynamics and vision-based tactile sensors by modeling the physics of contact. This contact model uses simulated contact forces at the robot’s end-effector to inform the generation of realistic tactile outputs. To eliminate the simto-real transfer gap, we calibrate our physics simulator of robot dynamics, contact model, and tactile optical simulator with real-world data, and then we demonstrate the effectiveness of our system on a zero-shot sim-to-real grasp stability prediction task where we achieve an average accuracy of 90.7% on various objects. Experiments reveal the potential of applying our simulation framework to more complicated manipulation tasks. We open-source our simulation framework at https://***/CMURoboTouch/Taxim/tree/taxim-robot. © 2022, CC BY-NC-SA.

关键词： End effectors

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Short-Term Photovoltaic Power Forecasting-Based Kernel Ridge Regression

Short-Term Photovoltaic Power Forecasting-Based Kernel Ridge...

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Artificial Intelligence, Applications, Innovation and Ethics (AI2E), International Conference for

作者： Manel Marweni Majdi Mansouri Mansour Hajji Mohamed Faouzi Mimouni Research Laboratory of Automation Signal Processing and Image National Engineering School of Monastir Tunisia Department of Electrical and Computer Engineering College of Engineering Sultan Qaboos University Muscat Oman Laboratory of Advanced Materials and Nanotechnologies Higher Institute of Applied Sciences and Technology of Kasserine Kairouan University Kasserine Tunisia

ISBN: (数字)9798331513733

ISBN: (纸本)9798331513740

The modern energy landscape is undergoing a seismic change from traditional, finite energy sources and toward cleaner, renewable alternatives. The restrictions faced by traditional sources, which are not only finite but increasingly shrink in the face of burgeoning global energy demands driven by population increase and industrial expansion, are driving this change. Although promising, renewable energy poses complications, particularly the reliance on climatic conditions. An important aspect of addressing these difficulties is effective energy management within distribution systems, which includes forecasting and optimization phases. This research focuses on forecasting using an advanced machine learning (ML) approach. Accurately forecasting renewable energy generation over time is critical for improving energy management. This technique is evaluated using a variety of performance indicators, including Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and the Coefficient of Determination (R 2 ). Empirical studies support the method's usefulness, demonstrating noteworthy performance with low error rates.

关键词： Photovoltaic systems Renewable energy sources Technological innovation Accuracy Machine learning Predictive models Forecasting Kernel Energy management Optimization

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The Effective Solar Panel Tracker to Obtain Maximum Energy Optimization by Using Innovative Machine Learning

The Effective Solar Panel Tracker to Obtain Maximum Energy O...

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Artificial Intelligence and Knowledge Discovery in Concurrent engineering (ICECONF), International Conference on

作者： Rajanish Kumar Kaushal V. Velmurugan S. Mahendran Arul Prakash M Balvender Singh Joshuva Arockia Dhanraj Department of Electrical Engineering Chandigarh University Mohali Punjab India Department of Electronics and Communication Engineering Vel Tech Rangarajan and Dr. Sagunthala R and D Institute of Science and Technology Chennai Tamil Nadu India Department of Electrical and Electronics Engineering Er. Perumal Manimekalai College of Engineering Hosur India Department of Mechanical Engineering Sri Sairam Engineering College Chennai Tamil Nadu India Department of Electrical Engineering Government Women Engineering College Ajmer Rajasthan India Department of Mechatronics Engineering Centre for Automation and Robotics (ANRO) Hindustan Institute of Technology and Science Chennai Tamil Nadu India

The heat from solar energy can be used to heat the air and use that heat for drying. Solar trackers are used to effectively track the solar collector to heat the air through a solar thermal collector. The drying hot air can be arranged as layer type trackers as per our requirement.A geo thermal heat pump uses geothermal energy to heat your home in winter and cool it in summer in a cost-effective and renewable way. A mini-split heat pump is the second best way to heat or cool your home or commercial space. In this paper an innovative machine learning model was proposed to enhance the tracking of solar panels. The main objective is to obtain the maximum energy of the solar thermal collector. A tracker uses many times more energy than a washing machine. So the efficiency of both can be improved by researching and selecting more energy efficient machines.A portable solar powered cooling unit uses a solar panel and inverter to provide relief from overheating by converting the DC power provided by the panel into 3-phase AC power. In a saturation point the proposed model achieved 87.20% of integrated tracking, 91.59% of distributed tracking, 90.20% of combined tracking, 89.11% of heat based tracking and 93.77% of high power solar tracking. The proposed model achieved higher level of energy optimization. This will possible because the proposed model monitor and generate the high level of energy because of the machine monitoring model.

关键词： Integrated optics Heat pumps Cogeneration Optical saturation Adaptive optics Solar panels Solar heating

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research on Health Management of IGBT Based on Mechanism Model

Research on Health Management of IGBT Based on Mechanism Mod...

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2022 International Conference on Power Energy Systems and Applications, ICoPESA 2022

作者： Xu, Guoqing Li, Shen Zheng, Luhai Pan, Zhengyun She, Chen Zhao, Hui Shao, Lingfeng Shanghai University School of Mechanical and Electrical Engineering and Automation Shanghai China Co. Ltd Inspection Department Shanghai China Hefei Design and Research Institute of Coal Industry Co. Ltd Inspection Department Anhui China Electronics Technology Co. Ltd Shanghai China

ISBN: (纸本)9781665410977

Temperature sensitive electrical parameter method is widely used in junction temperature detection of power devices because of its non-contact and high sensitivity. However, the junction temperature model based on the least square method or neural network may deviate from the semiconductor physics of the device. In this paper, a "voltage rise time - collector current -junction temperature"detection model based on the switching process mechanism model of power devices is discussed. Based on semiconductor physics, the monotonic relationship between collector current and voltage rise time is analyzed and discussed, and its mechanism model is determined at different temperatures. Finally, a junction temperature model based on the mechanism model is established by using the high-power IGBT H-bridge inverter circuit test platform to verify the theoretical analysis. At the same time, it is verified that the aging analysis of power devices can also be discussed by mechanism model. The experimental results show that the relationship between IGBT collector current and voltage rise time is hyperbolic, and the rise time of collector current and voltage is unique and definite at each junction temperature. When IGBT aging occurs, the curve deviates from that of normal IGBT. And the IGBT junction temperature test results will produce a large error. © 2022 IEEE.

关键词： Junction temperature

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Data Resolution and Future Challenges in Automated Undersea Cable System Design

引用

IEEE Network 2025年

作者： Wang, Tianjiao Wang, Xinyu Moran, Bill Wang, Zengfu Zukerman, Moshe Hong Kong Science Park Center for Intelligent Multidimensional Data Analysis Hong Kong Hong Kong The University of Melbourne Department of Electrical and Electronic Engineering MelbourneVIC3010 Australia Research & Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen518057 China Northwestern Polytechnical University School of Automation Xi’an710072 China City University of Hong Kong Department of Electrical Engineering Kowloon Hong Kong

Undersea optical cables form the backbone of global Internet infrastructure, carrying nearly 99% of international Internet data. As demand for high-speed and reliable connectivity continues to grow, optimizing undersea cable path planning has become essential for reducing costs, mitigating risks, and ensuring high-quality service delivery. While traditional manual planning methods remain widely used by cable system designers, surveyors, and planners, the increasing complexity of cable deployment necessitates the integration of automated methods that leverage advanced computational techniques to enhance efficiency and decision-making. This paper reviews the state-of-the-art in cable path planning and system design, emphasizing the important role of data density in achieving optimal cable paths. In particular, we present realistic path-planning scenarios on the Earth’s surface and describe the Fast Marching Method (FMM), a computational approach that efficiently determines optimal routing based on available data. Simulation results show that increasing map resolution, along with accompanying data at the higher resolution, significantly enhances path planning accuracy, reduces deployment costs, and improves risk assessment, underscoring the importance of acquiring and utilizing high-density data. This understanding leads to a discussion of the challenges of data acquisition and computational scalability in processing large-scale datasets, and the importance of collaboration between cable system engineers, geospatial data scientists, and software developers. This paper proposes a collaborative framework in which automated algorithms complement traditional planning methods, enabling cost-effective solutions that continually adapt and become more effective through expert feedback. This research contributes to a more resilient, efficient, and adaptive global undersea communication network, paving the way for the next generation of intelligent, optimized cable infrastructur

关键词： Risk assessment

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A Target-based Calibration Method for LiDAR-Visual-Thermal Multi-Sensor System

A Target-based Calibration Method for LiDAR-Visual-Thermal M...

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IEEE International Conference on robotics and Biomimetics

作者： Songyu Yuan Tian Xie Shiqiang Zhu Yeheng Chen Yuehua Li Tao Zheng Jason Gu Zhejiang Lab Research Center for Intelligent Robotics Research Institute of Interdis-ciplinary Innovation Hangzhou China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China Department of Electrical and Computer Engineering Dalhousie University Halifax NS Canada

ISBN: (纸本)9781665481106

As the basis of multi-sensor fusion, accurate extrinsic calibration among multi-sensors is vital for hetero-geneous information fusion. However, most existing methods only focus on the calibration between two specific heteroge-neous sensors, such as camera-LiDAR, LiDAR-thermal, and etc. which may cause inevitable accumulation when applied to a multi-sensor system. To address this problem, a novel calibration target and a high-accuracy method are proposed to simultaneously calibrate the intrinsic and extrinsic of a 3D LiDAR, a thermal camera and a visible camera without any user intervention. The proposed method only relies on one calibration board, to calibrate all the intrinsic and extrinsic parameters in one-step, without any strict pose requirement or long-time optimization. Furthermore, 2D-3D corresponding features can be extracted with higher precision by considering sensor model, comparing to the common feature extraction methods. Experiments with Velodyne VLP-16 LiDAR, ZED camera and D843NT thermal camera demonstrate that the proposed method can complete calibration among three of them automatically. Finally, this paper also presents a target-based method of uniformly expressing the calibration errors among multi-sensor system, with a competitive performance against most state-of-the-art methods.

关键词： Laser radar Three-dimensional displays Sensor phenomena and characterization Cameras Feature extraction Sensor systems Robustness

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Wind Farm Short-Term Power Prediction Based on Multiple Intelligent Algorithms 1

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9th Frontier Academic Forum of electrical engineering, FAFEE 2020

作者： Liu, Xuan Zheng, Lu Su, Ke Hu, Jun Zhao, Jianli Hu, Yaodong Inner Mongolia Electric Power Science & Research Institute Hohhot Inner Mongolia China Electrical Engineering and Automation Department Tsinghua University Haidian District Beijing China

ISBN: (数字)9789813366091

ISBN: (纸本)9789813366084

This paper illustrates several intelligent algorithms to build a short-term wind power forecasting model using data of a particular Wind Farm in Inner Mongolia. Advantages and backwards of the four different neural network models have been carefully discussed. Calculation methods and formulas are provided to prove the result. A combination prediction method is proposed in order to make a more accurate distribution power prediction by optimizing the information of multiple single models. Therefore, after analyzing the actual wind power data, the most accurate forecasting model is selected to provide an effective reference for power dispatching, operation and equipment maintenance. In order to integrate theory with practice, a wind farm in Inner Mongolia is chosen to make the short-term power prediction using the different intelligent method discussed in this paper. The most accurate prediction algorithm has been proved by real-time data. © 2021, Beijing Oriental Sun Cult. Comm. CO Ltd.

关键词： Electric load dispatching

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Automatic Saline Monitoring System Using IoT

Automatic Saline Monitoring System Using IoT

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International Carnahan Conference on Security Technology

作者： Raju Patel Manoj Singh Adhikari Manoj Kumar Shukla Mohit Payal Palvai Manoj Kumar Yogesh Kumar Verma School of Electronics Engineering SENSE Vellore Institute of Technology Chennai India School of Electronics and Electrical Engineering Lovely Professional University Punjab India Department of Robotics and Automation Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune India Electronic and Communication Engineering Graphic Era Hill University Dehradun India

The need for health prevention is raising every day as the earth's population rises. Thus, everyone in our planet must take adequate care of their health. Due to technical breakthroughs in the domains medical treatment has improved fast in recent years, using sensors, microcontrollers, and computers to ensure quick patient recovery in hospitals. Every patient should receive better care, better monitoring, and the proper amount of essential nutrients at the proper time. By using an Internet of Things (IoT) to remotely monitor the saline system, the suggested method makes it possible to regulate saline drip rate using an improved technique. The suggested system includes a sensor for determining when the saline liquid level in the saline container has decreased to a risky level and a mechanism for stopping the saline flow automatically once the saline bottle is fully empty or at a specific level. The patients will benefit much from this, especially at night. Additionally, because air bubbles in blood may instantly kill a patient, this technique eliminates the deadly chance of their getting into their circulation. Such a gadget will guarantee that patients won't suffer any damage.

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