Article
Energy & Fuels
Ashish Doorwar, Bhavesh R. Bhalja, Om P. Malik
Summary: A new stator fault detection and classification scheme for synchronous generators (SGs) is proposed, based on an amplified discrete Teager-kaiser energy operator (ADTKEO) of a new differential component (DCSI). The scheme achieves 100% winding coverage against phase-to-ground faults and can detect other phase faults within a quarter cycle for low-resistance grounded SGs. It is also stable for external faults, even with errors in CT and its saturation.
IEEE TRANSACTIONS ON ENERGY CONVERSION
(2023)
Article
Engineering, Electrical & Electronic
Md. Shamim Reza, Md Maruf Hossain, Mihai Ciobotaru
Summary: The proposed technique for fundamental frequency estimation in three-phase voltage systems under unbalanced and harmonic conditions is efficient, simple, and low-cost, with immunity to various voltage harmonics. It provides quick transient response with a time of less than 75% of one fundamental period, outperforming competing techniques under dynamic conditions.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Engineering, Electrical & Electronic
Maanvi Bhatnagar, Anamika Yadav, Aleena Swetapadma
Summary: The study aims to reduce relaying time for fault detection and classification, as well as accurate fault location estimation using the TKEO and XGBoost algorithm. The analysis was conducted on the IEEE 14 Bus transmission network, developing modules for fault detection, classification, and location estimation. The proposed methodology successfully determines, locates, and identifies faulty phases, with a focus on high impedance faults.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Automation & Control Systems
D. P. S. Gomes, C. Ozansoy
Summary: This paper provides a historical narrative of the progress and developments in the field of high-impedance faults in power distribution systems. It covers seminal papers to contemporary methods and technology, along with quantitative figures on survey methods and knowledge gaps. The comprehensive review serves as a valuable reference for researchers in the field.
Article
Computer Science, Artificial Intelligence
Vasileios Charisis, Stelios Hadjidimitriou, Leontios J. Hadjileontiadis
Summary: Efficient project evaluation is vital for the successful realization of a project, and FISEVAL, a fuzzy inference-based evaluation method, provides tangible evaluation metrics at different levels. It shows promising performance and adaptivity, making it suitable for various project developmental settings.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Maanvi Bhatnagar, Anamika Yadav, Aleena Swetapadma
Summary: A method combining discrete wavelet transforms and fuzzy inference system has been proposed for high impedance fault detection and classification. Testing under different operating conditions showed 100% accuracy in detecting and classifying faults in all cases.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Automation & Control Systems
Seyed Hossein Razavi Hajiagha, Jalil Heidary Dahooie, Niloofar Ahmadzadeh Kandi, Edmundas Kazimieras Zavadskas, Zeshui Xu
Summary: This study proposes an extended hybrid fuzzy multi-criteria model for selecting a sustainable process portfolio. By considering the effects of processes on sustainability and the strength of their relationship, and incorporating economic, social, and environmental criteria, the proposed model provides a comprehensive framework for process selection.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Animesh Sahoo, Khizir Mahmud, Jayashri Ravishankar
Summary: The article introduces a PLL independent frequency estimation technique that utilizes Teager energy operation and third-order polynomial approximated arctangent function to estimate frequency and phase-angle, avoiding trigonometric operations and PLL gain tuning. The grid synchronization technique presented in the work effectively handles grid transients and steady-state disturbances, demonstrating strong performance robustness.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Acoustics
Weidong Jiao, Tianyu Yan, Huilin Pan, Attiq Ur Rehman, Jianfeng Sun
Summary: This study proposes a three-stage defect detection system combining adaptive chirp mode decomposition, improved maximum correlation kurtosis deconvolution, and 1.5-dimensional Teager energy cyclo-stationary spectrum. The system successfully extracts higher order harmonics of bearing defect characteristic frequency, suppresses noise, and highlights fault impact.
JOURNAL OF VIBRATION AND CONTROL
(2022)
Article
Acoustics
Hao Zhou, Jianzhong Yang, Hua Xiang, Jihong Chen
Summary: The weak vibration energy in spindle motor is caused by unbalanced electromagnetic force and unqualified assembly, resulting in different fault features in different life cycles and bearing individuals. Diagnosing compound faults in the spindle motor is challenging. To solve this problem, an improved filtering and feature enhancement method combining AMF and TEO is proposed. The effectiveness of the method is verified through simulation and fault motor experiments, showing better performance in actual engineering scenarios compared to traditional methods.
Article
Engineering, Multidisciplinary
Tian Han, Lingjie Ding, Dandan Qi, Chao Li, Zhi Fu, Weidong Chen
Summary: A fault diagnosis method based on Teager energy operator and second-order stochastic resonance (TSSR) is proposed for wind turbine mainshaft bearing, and its superiority and effectiveness are verified through experiments.
Article
Computer Science, Artificial Intelligence
Xiaowei Gu, Plamen P. Angelov
Summary: This article introduces a novel multiclass fuzzily weighted AdaBoost-based ensemble system using a self-organizing fuzzy inference system as the ensemble component. By utilizing confidence scores from the SOFIS for sample weight updating and ensemble output generation, the proposed FWAdaBoost system achieves more accurate classification boundaries and greater prediction precision, demonstrating effectiveness in various benchmark classification problems.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Fuming Qu, Jinhai Liu, Hongfei Zhu, Huaguang Zhang
Summary: This article proposes an interpretable method based on fuzzy inference system, which can effectively interpret machine learning models in complex applications through reverse construction and optimization.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Computer Science, Artificial Intelligence
Dengxiu Yu, Ming Yang, Yan-Jun Liu, Zhen Wang, C. L. Philip Chen
Summary: This article investigates the problem of adaptive fuzzy tracking control for uncertain nonlinear systems with multiple actuators and sensors faults. The challenge of designing the control scheme arises from the fact that all states of the system cannot be accurately measured due to the presence of multiple sensor faults. Additionally, the design of the controller is complicated by multiple actuator faults and external disturbance. To address these issues, different adaptive update laws are designed to mitigate the effects of unknown actuator faults, sensor faults, and external disturbance. The actual states are estimated by combining sensor outputs with adaptive parameters, and the unknown nonlinear functions are approximated using a combination of fuzzy logic systems and state estimation. A novel adaptive fuzzy tracking control algorithm is then developed using the backstepping method. The proposed fault-tolerant control algorithm ensures bounded signals of the system despite the occurrence of multiple faults by employing the Lyapunov function. The effectiveness of the novel algorithm is verified by comparing its control performance to that of another algorithm.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Green & Sustainable Science & Technology
Kh Md Nahiduzzaman, Tiziana Campisi, Amin Mohammadpour Shotorbani, Khaled Assi, Kasun Hewage, Rehan Sadiq
Summary: This study examines social and cultural stigma in public transport, finding that privacy concerns are the primary cause of stigma, with people from high-income classes more likely to stigmatize certain ridership patterns. The study also uses a fuzzy inference system (FIS) model to analyze survey responses and identify key variables impacting stigma in public bus services.
Article
Engineering, Electrical & Electronic
Maanvi Bhatnagar, Anamika Yadav, Aleena Swetapadma
Summary: A method combining discrete wavelet transforms and fuzzy inference system has been proposed for high impedance fault detection and classification. Testing under different operating conditions showed 100% accuracy in detecting and classifying faults in all cases.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Maanvi Bhatnagar, Anamika Yadav, Aleena Swetapadma
Summary: The study aims to reduce relaying time for fault detection and classification, as well as accurate fault location estimation using the TKEO and XGBoost algorithm. The analysis was conducted on the IEEE 14 Bus transmission network, developing modules for fault detection, classification, and location estimation. The proposed methodology successfully determines, locates, and identifies faulty phases, with a focus on high impedance faults.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Saswati Mishra, Shubhrata Gupta, Anamika Yadav
Summary: In this paper, a Teager energy assisted variational mode decomposition (VMD) based traveling wave fault location technique (FLT) is developed for transmission lines with STATCOM, which can quickly and accurately locate the fault position.
INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS
(2023)
Article
Multidisciplinary Sciences
Upma Sahu, Anamika Yadav, Mohammad Pazoki
Summary: This paper presents a Fuzzy Inference System (FIS)-based method for fault detection, fault section identification, and faulty pole recognition in the MT-HVDC system. The method only utilizes rectifier end measurements of voltage and current signals. Three separate frameworks of FIS modules are developed for complete protection. The proposed method provides rapid fault detection without the need for communication.
Article
Engineering, Electrical & Electronic
Mohammad Pazoki, Bokka Krishna Chaitanya, Anamika Yadav
Summary: This paper introduces a new fault detection scheme for power swing using the Intrinsic Time-scale Decomposition (ITD) method. The ITD decomposes the input signal into rotation and monotonic signals to compute the fault index (FI). The proposed scheme is independent of fault parameters and relies on the morphological features of the input waveform. Experimental results show the superiority of this scheme in detecting faults in various scenarios.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Saswati Mishra, Shubhrata Gupta, Anamika Yadav
Summary: This paper proposes a traveling wave-based fault location estimation algorithm using the short-time matrix pencil method (STMPM) to accurately estimate the fault location in shunt-compensated systems. The algorithm decomposes the windowed signal into time-indexed complex frequencies and estimates the arrival time of waves to obtain the fault location. The proposed algorithm is compared with existing methods and found to be more robust and reliable.
ELECTRICAL ENGINEERING
(2023)
Article
Energy & Fuels
Saswati Mishra, Shubhrata Gupta, Anamika Yadav, Almoataz Y. Abdelaziz
Summary: Modern power systems are complex and susceptible to faults. Accurate fault location is crucial for system restoration and reliability. Fault location methods are used for quick identification, but their accuracy is affected by FACTS devices. This study compares four signal decomposition techniques for fault location in FACTS-compensated systems, and finds that EMD and ESPRIT-based methods are more accurate.
Article
Microbiology
Anamika Yadav, Peeyush Jain, Kusum Jain, Yue Wang, Aditi Singh, Ashutosh Singh, Jianping Xu, Anuradha Chowdhary
Summary: This article reports an outbreak of fungemia caused by Lodderomyces elongisporus in a neonatal intensive care unit (NICU) in Delhi, India. The outbreak affected 10 preterm, low-birthweight neonates, with nine of them surviving after treatment. Whole-genome sequencing showed that patient isolates grouped into two clusters, one from stored apples and the other from patients, clinical environments, and stored apples. Recombination was found in all samples, and there was significant genome divergence between the clinical and apple surface strains. The study highlights the diversity, recombination, and evolution of L. elongisporus in the hospital setting.
Article
Engineering, Electrical & Electronic
Anamika Yadav, Rashmi Bareth, Matushree Kochar, Mohammad Pazoki, Ragab A. El Sehiemy
Summary: This paper proposes Gaussian Process Regression (GPR)-based models for regression analysis problems like load forecasting. The GPR model is a non-parametric kernel-based learning method that can provide accurate predictions with uncertainty. The proposed model is applied to forecast load demand in an Australian city and four Indian cities in Maharashtra state.
IET GENERATION TRANSMISSION & DISTRIBUTION
(2023)
Proceedings Paper
Green & Sustainable Science & Technology
Rashmi Bareth, Matushree Kochar, Anamika Yadav
Summary: Load forecasting is important for utility companies to make decisions regarding load scheduling and load shedding. This paper presents a comparative analysis of 19 machine learning models and finds that Exponential Gaussian Process Regression performs the best in load prediction.
2023 IEEE IAS GLOBAL CONFERENCE ON RENEWABLE ENERGY AND HYDROGEN TECHNOLOGIES, GLOBCONHT
(2023)
Article
Multidisciplinary Sciences
Saswati Mishra, Shubhrata Gupta, Anamika Yadav
Summary: This article presents a literature review on traveling wave-based fault location estimation in FACTS compensated transmission system. It provides an overview of the current state-of-the-art in fault location methods, discusses the importance of these techniques and their classification, and presents the basic theory behind traveling-wave based fault location methods. The review also highlights the challenges in developing efficient fault location methods for FACTS compensated transmission systems and reviews recent advancements in the field, identifying future research directions.
Article
Engineering, Electrical & Electronic
Saswati Mishra, Shubhrata Gupta, Anamika Yadav
Summary: This paper proposes a matching pursuits algorithm-based traveling wave detection technique for fault distance estimation in transmission lines with a thyristor controlled series compensator. The effectiveness of the technique is validated through simulation and comparative assessment.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Maanvi Bhatnagar, Anamika Yadav, Aleena Swetapadma
Summary: The location of faults is crucial in electric power systems, and this paper presents a fault location scheme using random forest and Teager-Kaiser energy operator. The proposed scheme has been tested and proven to accurately determine fault locations, including high impedance faults.
SMART TECHNOLOGIES FOR POWER AND GREEN ENERGY, STPGE 2022
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Jangili Rajashekar, Anamika Yadav
Summary: With the advancements in artificial intelligence techniques, deep learning has attracted international attention. This paper presents a fault detection and classification method based on Long Short-Term Memory networks, which can classify raw process data directly without feature extraction or classifier design and has shown satisfactory results.
2022 SECOND INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRICAL, COMPUTING, COMMUNICATION AND SUSTAINABLE TECHNOLOGIES (ICAECT)
(2022)
Article
Computer Science, Artificial Intelligence
Anamika Yadav, Valabhoju Ashok, Mohammad Pazoki
Summary: This paper presents a fuzzy inference system and microcontroller-based protection scheme for a combined underground cable and overhead transmission line system. The proposed scheme accurately detects, classifies, and locates faults, and identifies the faulty section. The simulation and hardware results validate the effectiveness of the scheme.
EVOLUTIONARY INTELLIGENCE
(2022)
Article
Computer Science, Hardware & Architecture
Jia Ke, Ying Wang, Mingyue Fan, Xiaojun Chen, Wenlong Zhang, Jianping Gou
Summary: This study integrates the emotional correlation analysis model and Self-organizing Map (SOM) to construct fine-grained user emotion vector based on review text and perform visual cluster analysis, which helps platform merchants quickly mine user clustering and characteristics.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
Article
Computer Science, Hardware & Architecture
Shi Qiu, Huping Ye, Xiaohan Liao, Benyue Zhang, Miao Zhang, Zimu Zeng
Summary: This paper proposes a multilevel-based algorithm for hyperspectral image interpretation, which achieves semantic segmentation through multidimensional information fusion, and introduces a context interpretation module to improve detection performance.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
Article
Computer Science, Hardware & Architecture
Jianteng Xu, Qingguo Bai, Zhiwen Li, Lili Zhao
Summary: This study constructs two optimization models for the omnichannel closed-loop supply chain by leveraging the combined power of leader-follower game and mean-variance theories. The focus is on analyzing the performance of manufacturers who distribute products through physical stores. The results show that the risk-averse attitude of the physical store has a positive impact on the overall system profitability, but if the introduced physical store belongs to another firm, total profit experiences a decline.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
Article
Computer Science, Hardware & Architecture
Jiahao Xiong, Weihua Ou, Zhonghua Liu, Jianping Gou, Wenjun Xiao, Haitao Liu
Summary: This paper proposes a novel remote photoplethysmography framework, named GraphPhys, which utilizes graph neural network to extract physiological signals and introduces Average Relative GraphConv for the task of remote physiological signal measurement. Experimental results show that the methods based on GraphPhys significantly outperform the original methods.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
Article
Computer Science, Hardware & Architecture
Zhiyao Tong, Yiyi Hu, Chi Jiang, Yin Zhang
Summary: The rise of illicit activities involving blockchain digital currencies has become a growing concern. In order to prevent illegal activities, this study combines financial risk control with machine learning to identify and predict the risks of users with poor credit. Experimental results demonstrate high performance in user financial credit analysis.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
