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Research on AI-Based Oil and Gas Pipeline Leak detection and Localization technology 3

Research on AI-Based Oil and Gas Pipeline Leak Detection and...

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3rd international conference on Intelligent Computing, Communication and Convergence, ICI3C 2023

作者： Yong, Guo Tarim Oil&Gas Transportation Branch Company of West Pipeline Co. Ltd China Oil&Gas Pipeline Network Corporation Xinjiang Korla841000 China

ISBN: (纸本)9798350343922

Oil and gas pipelines, as a crucial part of the global energy transmission, play an essential role in ensuring energy security and efficient transportation. However, pipeline leakage is a significant problem that has long plagued the industry, causing not only severe environmental damage but also potentially leading to major safety incidents and resulting in enormous economic losses. Traditional leakage detection methods, such as those based on pressure and flow monitoring, although effective in some cases, are often limited by high false alarm rates and low sensitivity, especially in detecting small-scale or concealed *** recent years, with the rapid development of artificial intelligence technology, its application in oil and gas pipeline leak detection and localization has increasingly gained attention. Artificial intelligence technologies, particularly machine learning and deep learning algorithms, can identify subtle signs of leaks by analyzing large amounts of data, thereby enabling earlier warnings of leaks. These technologies can improve the accuracy and efficiency of detection while reducing false alarm rates, offering a new perspective and method for the safe operation of *** paper aims to explore and analyze the application of artificial intelligence technology in the field of oil and gas pipeline leak detection and localization. We will first analyze the impact of oil and gas pipeline leaks, then review the limitations of traditional detection technologies, and discuss in detail how artificial intelligence can improve existing leak detection methods. Through specific case studies and analysis of experimental data, this paper will demonstrate the significant advantages of artificial intelligence technology in enhancing the accuracy and efficiency of leak detection. Finally, we will discuss the current challenges and potential directions for future development, emphasizing the importance of further research. © 2023 IEEE.

关键词： Energy security

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Multi-strategy Collaborative Optimized YOLOv5s and Its Application in Distance Estimation 3

Multi-strategy Collaborative Optimized YOLOv5s and Its Appli...

引用

2023 IEEE 3rd international conference on Data Science and Computer Application, ICDSCA 2023

作者： Shen, Zijian Mu, Zhenping Li, Xiangxiang The University of Hong Kong Hong Kong The Hong Kong University of Science and Technology Hong Kong

ISBN: (纸本)9798350341546

The increasing accident rate brought about by the explosive growth of automobiles has made the research on active safety systems of automobiles increasingly important. The importance of improving the accuracy of vehicle target detection is self-evident. To achieve the goals of vehicle detection and distance estimation and provide safety warnings, a Distance Estimation Safety Warning system (DESWS) based on a new neural network model (YOLOv5s-SE) by replacing the IoU with DIoU, embedding SE attention module, and a distance estimation method through using the principle of similar triangles was proposed. In addition, a method that can give safety suggestions based on the estimated distance using nonparametric testing was presented in this work. Through the simulation experiment, it was verified that the mAP was improved by 5.5% and the purpose of giving safety suggestions based on the estimated distance information can be achieved. © 2023 IEEE.

关键词： DIoU distance estimation nonparametric testing target detection YOLO

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Ink layer thickness detection based on laser triangulation technology 3

Ink layer thickness detection based on laser triangulation t...

引用

3rd international conference on Laser, Optics, and Optoelectronic technology, LOPET 2023

作者： Zhang, Weipeng Wu, Shuqin Zhuang, Yanyan Chai, Chengwen Li, Jialin School of Electrical and Mechanical Engineering Beijing Institute of Graphic Communication Beijing China

ISBN: (纸本)9781510667624

The problem of the accuracy of some prints in the field of packaging printing technology due to the inability to accurately detect the thickness of the ink layer is studied. For this purpose, a method of detecting the ink layer thickness by combining the laser triangulation technique and the image processing technique is proposed. Firstly, the platform of the ink layer thickness detection system is built. Then the industrial camera acquires images and processes the acquired images. Finally obtains the laser offset using the improved probabilistic Hough transform method to calculate the thickness value. The experiments verified that the method can effectively measure the ink layer thickness of plastic flexible packaging prints. © 2023 SPIE.

关键词： Triangulation

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Abnormal Scene Image Recognition Method for Intelligent Operation and Maintenance of Electrical Equipment in Substations 3

Abnormal Scene Image Recognition Method for Intelligent Oper...

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3rd international conference on Energy Engineering and Power systems, EEPS 2023

作者： Yang, Youhang Wang, Shaorong Ren, Jiaxuan Zhang, Yanyan Huazhong University of Science and Technology School of Electrical and Electronic Engineering Wuhan China China Southern Power Grid Dongguan Power Supply Bureau Dongguan China

ISBN: (纸本)9798350313857

The utilization of robot inspections and accurate, rapid identification of fault targets in images through artificial intelligence technology represents an important research area in the field of intelligent operation and maintenance for substations. To address the issue of massive image data collected by robot inspections, an abnormal scene image recognition method is proposed for intelligent operation and maintenance of electrical equipment in substations, with consideration for both the accuracy and real-time performance of object detection. Firstly, the research status and development trend of intelligent operation and maintenance technology of substation electrical equipment is elaborated. Subsequently, a fault detection model for intelligent operation and maintenance of electrical equipment in substations is proposed based on YOLO v5 deep neural network. To improve the detection speed of the model, Cross Stage Partial (CSP) and Spatial Pyramid Pooling Fast (SPPF) structures are utilised to reduce model parameters. Finally, the effectiveness of the proposed model is validated through two application scenarios: substation foreign object suspension image recognition and thermal defect detection based on infrared images. The experimental results demonstrate that the model achieves a detection accuracy of 99.8% in foreign object suspension detection for electrical equipment, with an average frame rate of 149 frames/s. Moreover, the model has an accuracy of 98.9% for the detection of thermal defects in infrared images of electrical equipment, with an average frame rate of 123 frames/s. These results satisfy the application requirements for real-time monitoring. © 2023 IEEE.

关键词： Object detection

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Automatic detection of Paediatric Congenital Heart Diseases from Phonocardiogram Signals 3

Automatic Detection of Paediatric Congenital Heart Diseases ...

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3rd IEEE international conference on Artificial intelligence, ICAI 2023

作者： Ahmad, Zafar Zeeshan, Muhammad Sohail, Arshad Fazal-E-Haq Haris, Muhammad Khan, Misha Urooj Hussain, Sayed Shahid Khan, Muhammad Salman Department of Electrical Engineering Peshawar Pakistan Lady Reading Hospital MTI Paediatric Cardiology Peshawar Pakistan National Center of Artificial Intelligence Artificial Intelligence in Healthcare IIPL University of Engineering and Technology Peshawar Pakistan Peshawar Pakistan College of Engineering Department of Electrical Engineering Qatar University Doha Qatar

ISBN: (纸本)9798350322125

The World Health Organization (WHO) claims that 0.8% to 1.2% of newborns worldwide are affected by congenital heart diseases (CHDs). There are many methods for CHD identification, and the most prevalent is phonocardiography (PCG). It is a non-invasive method that offers crucial knowledge about the sounds (S1, S2, S3, and S4) and beats of the heart. This research study aims to train a binary categorization system using a deep neural network for CHDs by using a combination of local and public datasets. The local dataset (LD) had 583 signals (normal and abnormal PCG), while the public dataset (PD) taken from Michigan University had 23 PCG recordings. Both datasets were down-sampled to 8 kHz. The band pass filter was designed such that it ensured that any signals outside of the 20-650 Hz range were filtered out, allowing only the desired frequencies to be processed. All signals were chunked at a signal duration of 4 seconds. For data augmentation, pitch-shifting was applied and passed to a 1D convolutional neural network (CNN). The best results were achieved for case C, with an accuracy of 98.56 %, precision of 98.57 %, F1 score of 98.56 %, specificity of 98.0 %, and sensitivity of 99.0%. © 2023 IEEE.

关键词： Deep neural networks

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Geometry-based multi-beam survey line layout problem 3

Geometry-based multi-beam survey line layout problem

引用

2023 3rd international conference on Computational Modeling, Simulation and Data Analysis, CMSDA 2023

作者： Li, Chuangqi Wang, Yuhang Hu, Fan College of Computer and Information Engineering Henan Normal University Xinxiang Henan453007 China College of Physics Henan Normal University Xinxiang Henan453007 China Key Laboratory of Artificial Intelligence and Personalized Learning in Education of Henan Province Henan China Engineering Lab of Intelligence Business and Internet of Things of Henan Province Henan China

The multi-beam measurement system plays a crucial role in ocean mapping and underwater terrain detection. By simultaneously transmitting multiple beams, the system can accurately receive sound waves reflected from the seabed, providing more precise and comprehensive water depth information while effectively revealing the complexity and characteristics of underwater terrain. Under the background and application provided by Question B of the 2023 National Mathematical Contest in Modeling for College Students, this paper investigates the relationship between ocean floor width measurement and factors such as beam position, angle, and slope. Utilizing geometric relations, trigonometric similarity, and sine theorem, a mathematical model is established to determine adjacent strip coverage width and overlap ratio. Furthermore, an optimal strategy is determined by using a greedy algorithm, while binary search backtracking is employed to derive the interval of the next adjacent survey line with the required overlap ratio to obtain an optimal terrain detection strategy. © Published under licence by IOP Publishing Ltd.

关键词： Landforms

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Research and Application of YOLOv3-Based Intelligent Module for Remote Sensing Image Recognition on Satellites 3

Research and Application of YOLOv3-Based Intelligent Module ...

引用

3rd international conference on Artificial intelligence, Automation, and High-Performance Computing, AIAHPC 2023

作者： Tang, Hua Ye, Bingxin Shi, Huajun Wang, He Yu, Tao China Electronics Technology Group Corporation China The 32nd Research Institute of China Electronics Technology Group Corporation China

ISBN: (数字)9781510666580

ISBN: (纸本)9781510666573

With the continuous development of satellite technology, the acquisition and processing of satellite remote sensing data have become increasingly common. However, at present, satellites still use a mode of transmitting data back to the ground and utilizing ground CPU/GPU platforms for intelligent processing, which is inefficient due to the process of data transmission between the satellite and the ground. This article studies the application method and implementation of real-time remote sensing image recognition by integrating the Yulong810 on-board intelligent module on a satellite based on the YOLOv3 object detection *** response to the actual needs of satellite remote sensing image recognition, the algorithm is optimized based on the Yulong810 on-board intelligent module, which improves the recognition efficiency and reduces power consumption while ensuring the accuracy of remote sensing image recognition. By comparing with ground CPU/GPU platforms, the results show that the Yulong810 on-board intelligent module has lower power consumption and higher efficiency, and the recognition accuracy is comparable to that of ground platforms, which can completely replace ground remote sensing image detection equipment when integrated into *** integrating the module into the satellite, real-time intelligent processing can be achieved in orbit, improving the efficiency of satellite remote sensing image recognition. © 2023 SPIE.

关键词： Image recognition

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Innovations in Voice Navigation Using Object detection to Empower the Visually Impaired 3

Innovations in Voice Navigation Using Object Detection to Em...

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Suryawanshi, Ranjeet Arudra, Annepu Dankan Gowda, V. Uthaman, Mathu Swathi Pai, M. Prasad, V.K. Satya Bharati Vidyapeeth's College of Engineering Department of Electronics and Telecommunications Engineering Maharashtra Kolhapur India Rajiv Gandhi Institute of Technology Department of Computer Science & Engineering Cholanagar R T Nagar Karnataka Bangalore India Bms Institute of Technology and Management Department of Electronics & Communication Engineering Karnataka Bangalore India Mahaguru Institute of Technology Department of Computer Science and Engineering Kayamkulam Alappuzha Kattachira India Nmam Institute of Technology Department of Artificial Intelligence and Machine Learning Karnataka Nitte574110 India Symbiosis Institute of Business Management Hyderabad India Pune India

ISBN: (纸本)9798350319125

The project focuses on addressing the challenges faced by visually impaired individuals in navigating environments, especially when encountering obstacles or misplacing essential tools like walking sticks. A novel solution is proposed: a voice-controlled smart stick, designed to enhance the autonomy of visually impaired people in their daily activities without reliance on others. This research introduces a sophisticated walking stick equipped with ultrasonic sensors, operated via voice commands for ease of use and accessibility The voice-controlled smart stick is distinguished by its user-friendly interface, rapid responsiveness, minimal power consumption, lightweight design, and ease of folding and handling. This project not only offers a practical solution for the visually impaired but also signifies a significant advancement in assistive technology, enhancing independence and safety in daily life. © 2023 IEEE.

关键词： Autonomous Navigation Navigation systems Object detection Realtime Obstacle detection Visual Impairment Voice Navigation

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Role of human-centred artificial intelligence in facilitating learning management system 3

Role of human-centred artificial intelligence in facilitatin...

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3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Gowrabhathini, Jitendra Buddhi, Dharam Jyothika, Yedla Sai Mounika, Balla Sai, Palacharla Veera Reddy, Battula Anuhya Kl University Kl Business School Koneru Lakshmaiah Education Foundation India Uttaranchal University Uttaranchal Institute of Technology India Kl University Koneru Lakshmaiah Education Foundation India

ISBN: (纸本)9798350399264

Learning management systems, often known as LMSs, represent the most desirable alternative for the provision of instructional materials in higher education since they make high-quality educational resources available to students from all over the globe. As a bridge, we utilize programs that manage the learning that occurs between students and teachers. This paradigm shift occurs as a result of the presence of intelligent agents who emulate the astute strategies utilized by the instructor and the pupils. The technologies that make up artificial intelligence are based on the reproduction of concepts that are present in human intelligence. This research gives a broad overview of the LMS environments in which AI-based techniques were used. In addition to that, the examples stress more instances of the huge range. Learning management system (LMS) users, including students, professors, and managers, may all benefit from the investigation of AI-related LMS techniques, which have been investigated as potential solutions to a variety of LMS issues. © 2023 IEEE.

关键词： Students

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Intrusion detection system Using Ensemble Techinque 3

Intrusion Detection System Using Ensemble Techinque

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3rd international conference on Innovative Sustainable Computational Technologies, CISCT 2023

作者： Jain, Namo Singh, Mukund Pratap Chaurasia, Kuldeep Ravindran, Gobinath School of Computer Science Engineering and Technology Bennett University Greater Noida India SR University Department of Civil Engineering Telangana Warangal India

ISBN: (纸本)9798350303360

Intrusion detection systems, which inspect and analyze network data for signs of hostile activity, are critical to computer network security. These systems are suggested to distinguish and respond to not permitted access, misuse, and other confidence consequences that could concession the concealment, veracity, and accessibility of network resources. In this research, we give an overview of intrusion detection employed in computer networks, including their classification, architecture, and detection methods. The structure intends to detect both recognized-notorious intrusions and attacks with better detection accuracy and lesser untruthful-probability measures. We look at the challenges of setting up and maintaining IDS with their importance in distinguishing various categories of network infringements. This study indicates that intrusion detection systems are an important part of contemporary network protection and are frequently used in many organizations to defend against cyber-attacks. Voting method to identify the intrusion detection systems representing the best performance scores on the dataset. The performance parameter (accuracy, F1_score, precision, and recall) values of the voting model are 0.998015, 0.998015, 0.998016 and 0.998015. © 2023 IEEE.

关键词： Intrusion detection

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