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14th International Conference on the Properties and Applications of Dielectric Materials, ICPADM 2024

作者： Aiamrungruang, Phitthaya Pannil, Pittaya Dorkmai, Kritsada Maneerot, Sakda Jeenmuang, Siwakorn Pattanadech, Norasage School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Electrical Engineering Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Instrumentation and Control Engineering Bangkok Thailand

ISBN: (纸本)9798350374605

Dry-type cast resin transformers, utilizing epoxy resin insulation instead of traditional liquid insulation like mineral oil, are designed to prioritize safety, avoid fire hazards, be environmentally compatible, and endure short circuits well. Limitations of dry-type transformers are the installation area by which it should be dry, free from dust, excessive moisture, fertilizers, chemicals, and other corrosive fumes or fumes. This paper investigates the Partial Discharge (PD) phenomena occurring on a 12 kV dry-type transformer surface using HighFrequency Current Transformers (HFCT) with 100 kHz -20 MHz bandwidth as a PD detection device. The simulated PD sources were made from the conductive wire. Moreover, the scheme of winding connections in the dry-type transformer related to cross-talk phenomena between transformer coils is also reported. The recorded Phase-resolved PD (PRPD) and the PD Inception Voltage (PDIV) have been summarized and compared, as described in this paper. © 2024 IEEE.

关键词： Fire hazards

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Intelligent Agricultural Drones Utilizing Nano-Fertilizer Dispensation for Precision Farming

Intelligent Agricultural Drones Utilizing Nano-Fertilizer Di...

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2024 International Conference on Communication, Computing and Internet of Things, IC3IoT 2024

作者： Jayanthi, G. Nancy, W. Umamaheswari, B. Chithrakkannan, R. Sujith, R. Sathya Prasanna, S. Sri Sairam Engineering College Department Of Instrumentation And Control Engineering India Jeppiaar Institute Of Technology Department Of Electronics And Communication Engineering India Sri Sairam Engineering College Department Of Electronics And Communication Engineering India

ISBN: (纸本)9798350352689

An innovative approach to precision agriculture through the integration of artificial intelligence (AI) and nano-fertilizer technology in an agricultural drone system. The proposed system aims to optimize crop yield, reduce environmental impact, and enhance resource efficiency by employing advanced AI algorithms for crop health assessment and nano-fertilizers for targeted nutrient delivery. The drone's real-time decision-making capabilities, coupled with precise dispensation of nano-sized fertilizers, contribute to sustainable farming practices. Field trials demonstrate promising results in terms of improved crop productivity, resource utilization, and minimized environmental footprint. © 2024 IEEE.

关键词： Crops

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A Review of Evaluation Metrics Algorithmic Used in Scholarly Research Recommender System 4

A Review of Evaluation Metrics Algorithmic Used in Scholarly...

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4th International Multidisciplinary Information technology and engineering Conference, IMITEC 2024

作者： Ovono, Gerald Zuva, Travos Otunniyi, Temidayo Faculty of Applied and Computer Sciences Department of Computer South Africa VaalUniversity of Technology Faculty of Engineering and Technology Department of Process Control and Computer Systems South Africa

ISBN: (纸本)9798350387988

The exponential growth of academic publications has made scholarly research recommender systems indispensable tools for researchers. These systems rely on diverse evaluation metrics to assess their effectiveness and relevance. This paper provides a comprehensive review and analysis of these metrics, categorizing them into accuracy, ranking, diversity, user-centric, coverage, temporal, and computational metrics. By employing a mixed-methods approach, combining systematic literature review and empirical analysis, we identify the prevalence and application of these metrics across various scholarly domains such as literature, conferences, and reviewers. Our findings highlight the widespread use of traditional metrics like precision, recall, and Fl-score, while emphasizing the growing importance of novel metrics such as unexpectedness and serendipity, especially in literature and conference recommendations. We also underscore the domain-specific nature of metric selection, with user-centric evaluations more prominent in literature recommendations, and ranking-focused metrics dominant in conference and reviewer recommendations. Furthermore, the study reveals a significant gap in the use of temporal and computational metrics, suggesting key areas for future research. This review offers valuable insights for researchers and practitioners, guiding them in metric selection and highlighting potential directions for enhancing the effectiveness, adaptability, and user satisfaction of scholarly recommender systems. © 2024 IEEE.

关键词： Algorithms Evaluation Metrics Novelty Recommender Systems Scholarly Research Serendipity

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Partial Discharge Characteristics of a Defective MV XLPE Cable 14

Partial Discharge Characteristics of a Defective MV XLPE Cab...

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14th International Conference on the Properties and Applications of Dielectric Materials, ICPADM 2024

作者： Ekasittiphong, Woraphat Smerpitak, Krit Tangthanam, Worasak Jeenmuang, Siwakorn Pattanadech, Norasage Pongswatd, Sawai School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Electrical Engineering Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Instrumentation and Control Engineering Bangkok Thailand

ISBN: (纸本)9798350374605

This paper presents the partial discharge (PD) test on a 22 kV underground cable having a simulated defect within the XLPE insulation. The defects were simulated using the nail, as the drill bits with a different drill diameter. The defect was created into the XLPE insulation layers of the underground cable. Besides, both end sides of the cable were electric field controlled. To simulate the defects for the experiment, the jacket in the middle of the cable was partially trimmed out, and the drill bits was driven through the insulation screen to the insulation layer. The diameter of the drill bits was controlled for each experiment. The PD experiment was conducted using high frequency current transformer (HFCT) sensor as an unconventional PD detection instrument. From analyzing the PD test results, a defect in the XLPE insulation causes vividly the PD inside the XLPE insulation. Consequently, the insulation gradually deteriorates undergoing the PD events. Moreover, the PD test results indicate that the larger diameter of the nail tip radius results in a higher PD magnitude than that generated by a smaller diameter. © 2024 IEEE.

关键词： Partial discharges

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Detection of Fuel Adulteration Using Wave Optical with Machine Learning Algorithms

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Computer Systems Science & engineering 2022年第4期41卷 19-33页

作者： S.Dilip Kumar T.V.Sivasubramonia Pillai Department of Instrumentation and Control Engineering Sri Krishna College of TechnologyCoimbatore641105TamilnaduIndia Department of Physics University College of EngineeringNagercoil629004TamilnaduIndia

Fuel is a very important factor and has considerable inﬂuence on the air quality in the environment,which is the heart of the *** increase of vehi-cles in lived-in areas results in greater emission of carbon particles in the *** fuel causes more contaminated particles to mix with breathing air and becomes the main source of dangerous *** is the mixing of foreign substances in fuel,which damages vehicles and causes more health problems in living beings such as humans,birds,aquatic life,and even water resources by emitting high levels of hydrocarbons,nitrogen oxides,and carbon *** frequent blending liquids are lubricants and kerosene in the petrol,and its adulteration is a considerable problem that adds to environ-mental *** study focuses on detecting the adulteration in petrol using sensors and machine learning algorithms.A modiﬁed evanescent wave opticalﬁber sensor with discrete wavelet transform is proposed for classiﬁcation of adult-erated data from the ***,support vector machine classiﬁer is used for accurate *** sensor isﬁrst tested with fuel and numerical data is classiﬁed based on machine learning ***,the result is eval-uated with less error and high accuracy of 99.9%,which is higher than all existing techniques.

关键词： Petrol adulteration discrete wavelet transform modiﬁed evanescent wave opticalﬁber SVM classiﬁer

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The Experiment of Dielectric Frequency Response of Serviced Aged Distribution Transformer 14

The Experiment of Dielectric Frequency Response of Serviced ...

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14th International Conference on the Properties and Applications of Dielectric Materials, ICPADM 2024

作者： Posrimahapoch, Purichaya Maneerat, Noppadol Daengdee, Danaiwat Jeenmuang, Siwakorn Pannil, Pittaya Pattanadech, Norasage School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Electrical Engineering Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Instrumentation and Control Engineering Bangkok Thailand

ISBN: (纸本)9798350374605

Outdoor Distribution Transformers typically encounter random environments and affect moisture in any ingress ways, e.g., defective breathing, oil leakage, or human error during internal inspection, etc. Such moisture is a very important enemy of the insulation integrity of the transformer. It may cause the failure of the transformer eventually. Therefore, the condition of the transformer insulation needs to be monitored. Dielectric Frequency Response (DFR), also known as Frequency Domain Spectroscopy (FDS), and Polarization and Depolarization Current (PDC) are nondestructive tests providing efficient diagnostic for transformer insulation. The test results can be used to estimate moisture content and oil conductivity. In this paper, the dielectric investigation of a 315 kVA, 22 kV serviced aged distribution transformers, which have been retired for 6 months after being utilized for more than 20 years, was conducted. The experiment results of the DFR and the PDC tests including the investigated mineral oil characteristics (i.e., oil breakdown voltage, moisture content, and tan delta) are reported and analyzed. They should be useful to understand the condition of the transformers. © 2024 IEEE.

关键词： Depolarization

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Partial Discharge Investigation of 22kV Distribution Transformer 14

Partial Discharge Investigation of 22kV Distribution Transfo...

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14th International Conference on the Properties and Applications of Dielectric Materials, ICPADM 2024

作者： Dechothamsathit, Vorawut Pannil, Pittaya Yamsiri, Thummanoon Chumpiboon, Komin Jeenmuang, Siwakorn Pattanadech, Norasage School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Electrical Engineering Bangkong Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Instrumentation and Control Engineering Bangkong Thailand

ISBN: (纸本)9798350374605

This paper presents an off-line partial discharge (PD) experiment conducted on a 22 kV/400 V distribution transformer, which was decommissioned after 20 years of service. The study investigates the impact of reduced oil levels within the transformer on PD characteristics that are expected to facilitate PD activity within the transformer. The experiments were performed with reduced oil levels below the top clamp and using both single-phase and three-phase voltage excitations, with PD measurements recorded for each case. The PD signals were measured using High-Frequency Current Transformers (HFCTs) and capturing current pulses of PD in the frequency range of 100 kHz to 20 MHz. Additionally, transformer oil tests were performed, including moisture content, oil breakdown voltage, and oil conductivity. The results of the PD measurements and oil tests are introduced and discussed in this paper. © 2024 IEEE.

关键词： Distribution transformers

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Relief Facility Locations Using Expected Regret Model

Relief Facility Locations Using Expected Regret Model

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2023 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2023

作者： Na Ayudhya, Wichitsawat Suksawat School of Engineering King Mongkut's Institute of Technology Instrumentation and Control Engineering Department Ladkrabang Bangkok10250 Thailand

ISBN: (纸本)9798350323153

Chiang Rai, Nan, and Phayao, located in the provinces of northern part of Thailand, encountered flood, landslide, river overflow during raining season. Floods in this area are so difficult to predict. Flood mitigation plan is a critical key for relief and recovery. We focus on the preparedness plan for locating relief facilities. Our method to locate the optimal relief facility location is based on the expected regret P-median model with historical data for both populations and transportation routes. We conduct two experiments when the district is served by one relief facility and when the is served by the number of facilities following by the heuristic rule. Numerical results show that Muean Chiang Rai, Wiang Chai, Chiang Khong, Mae Chan, Mae Suai, Mueang Nan and Pua are suitable for locating relief facilities. © 2023 IEEE.

关键词： Decision Analysis Facility location P-Median

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Real-Time Bus Driver Monitoring System Using Machine Learning 2

Real-Time Bus Driver Monitoring System Using Machine Learnin...

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2nd International Conference on Advanced Computing and Communication Technologies, ICACCTech 2024

作者： Kadu, Anil Dharashive, Rajnandini Nimje, Rachit Rajvaidya, Arya Palkar, Sanket Gaikwad, Vijay Vishwakarma Institute of Technology Department of Instrumentation and Control Pune India Vishwakarma Institute of Technology Department of Computer Engineering Pune India Vishwakarma Institute of Technology Department of Electronics and Telecommunication Pune India

ISBN: (纸本)9798331519056

In recent years, the importance of ensuring road safety has intensified, prompting the development of advanced driver monitoring systems. This paper presents a real-time bus driver monitoring system utilizing a Raspberry Pi, OpenCV, a RaspiCam and machine learning techniques. The system aims to enhance passenger safety by detecting driver fatigue and distraction, which are major contributors to road accidents. The proposed solution leverages the Raspberry Pi's processing capabilities and the RaspiCam's imaging features to continuously capture and analyze the driver's facial expressions and eye movements. OpenCV's robust image processing algorithms are employed to identify signs of drowsiness and inattentiveness. The innovative aspects of the proposed solution include the use of Eye Aspect Ratio (EAR) for drowsiness detection and Mouth Aspect Ratio (MAR) for detecting yawning. Both the EAR and MAR are calculated through real-time facial landmark analysis. The system issues alerts when unsafe driving behavior is detected, thereby allowing for timely intervention. The proposed monitoring system is cost-effective and scalable. It offers a promising approach to improving public transportation safety by mitigating the risks associated with driver fatigue and distraction. Experimental results showed an accuracy of 92% for fatigue detection and 88% for distraction detection. This demonstrates the system's effectiveness in real-time detection and its potential for deployment in commercial bus fleets. © 2024 IEEE.

关键词： Bus drivers

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An NFNet-Based Approach for Enhanced Bearing Fault Classification Using Vibrational Signal Analysis 14

An NFNet-Based Approach for Enhanced Bearing Fault Classific...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Jain, Vidhi Dixit, Mayank Misra, Vihaan Bhutani, Geetansh Singh, Vijander Netaji Subhas University of Technology Department of Electrical Engineering Delhi India Netaji Subhas University of Technology Department of Instrumentation and Control Engineering Delhi India

ISBN: (纸本)9798350335095

The present work proposes a novel approach for detecting bearing faults in induction motors using vibrational signals. The proposed method employs a Normalizer-Free ResNet (NFNet) architecture to extract relevant features from 2D image representations of raw vibration data and a classification model to identify the presence of a fault. We convert the vibrational signals into 2D images by applying the Short-Time Fourier Transform (STFT) technique, which offers a time-frequency analysis of the signals. The proposed method improves accuracy over conventional approaches along with reduced computational overhead by using high-performance NFNet architecture for classification. The effectiveness of the proposed method is evaluated on the Case Western Reserve University (CWRU) and Intelligent Maintenance Systems (IMS) datasets of vibration signals from induction motors, experiencing various bearing faults. The results indicate that the suggested framework outperforms the existing methods in terms of accuracy and efficiency, achieving state-of-the-art results. This method can be used for real-time monitoring of induction motors to detect bearing faults and prevent potential equipment failures, making it highly useful for industrial applications. © 2023 IEEE.

关键词： Computer vision

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