Advanced Multi-Scale CNN-BiLSTM for Robust Photovoltaic Fault Detection by Xiaojuan Zhang, Bo Jing, Xiaoxuan Jiao, Ruixu Yao

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DEFORMATION CHANGES IN THE FAMENNIAN-TOURNAISSIAN CARBONATE ROCKS IN THE NORTHWESTERN MARGINAL FAULT ZONE OF THE CASPIAN BASIN by V. V. Korobkin, Zh. S. Tulemissova, A. E. Chaklikov

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Detection of Transformer Faults: AI-Supported Machine Learning Application in Sweep Frequency Response Analysis by Hakan Çuhadaroğlu, Yılmaz Uyaroğlu

“…In this context, Sweep Frequency Response Analysis (SFRA) has emerged as an effective method for detecting potential faults at an early stage by examining the frequency responses of transformers. …”
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Risk Analysis of Underground Tunnel Construction with Tunnel Boring Machine by Using Fault Tree Analysis and Fuzzy Analytic Hierarchy Process by Nitidetch Koohathongsumrit, Wasana Chankham

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Hazard analysis of future surface displacements on active faults based on the recurrence interval of strong earthquakes by Zhou Qingyun, Liu Jingnan, Tian Peng, Luo Weidong, Bai Xianfu, Yang Yue, Zou Zhenyu

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Enhanced Rolling Bearing Fault Diagnosis Using Multimodal Deep Learning and Singular Spectrum Analysis by Yunhang Wang, Hongwei Wang, Ruoyang Bai, Yuxin Shi, Xicong Chen, Qingang Xu

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Condition monitoring and multi-fault classification of hydraulic systems using multivariate functional data analysis by Cevahir Yildirim, Alba M. Franco-Pereira, Rosa E. Lillo

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Overhead Transmission Line Modeling Strategies for EMT-Based Traveling-Wave Analysis and Fault Location by Adrian Wilmer Diaz Sarmiento, Jaimis Sajid Leon Colqui, Jose Pissolato Filho

“…The results show that: 1) uniform soil resistivity assumptions introduce negligible errors in TW arrival times despite minor amplitude variations; 2) shield wires significantly affect modal structure, compromising the effectiveness of Clarke transformation for ground quasi-mode decoupling while preserving aerial quasi-mode reliability; 3) exact eigenvector-based decomposition improves ground mode identification but remains impractical for field applications; 4) the classical two-terminal fault location method maintains high accuracy across all modeling configurations; and 5) simplified OHTL modeling uniformly distributed sections at both terminals achieves an optimal balance between accuracy and computational efficiency for simulating TWs. …”
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Typical Fault Estimation and Dynamic Analysis of a Leader-Follower Unmanned Aerial Vehicle Formation by Jian Shen, Qingyu Zhu, Xiaoguang Wang, Pengyun Chen

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Enhancing Fault Detection and Localization in MT-MVDC Networks Using Advanced Singular Spectrum Analysis by Hossam Sabra, Amr Kassem, Ahmed A. A. Ali, Karam M. Abdel-Latif, Ahmed F. Zobaa

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Assessment of Transformer Fault Severity from Online Dissolved Gas Analysis Using Positive CUSUM by Naris Chattranont, Sakhon Woothipatanapan, Nattachote Rugthaicharoencheep

“…Dissolved gas analysis (DGA) is one of the transformer testing methods that has been widely used for a long time because it does not require the transformer to be offline for testing. …”
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Presaturated iron‐core fault current limiters for MVDC power system applications by Ibrahim A. Metwally, Mohamed Eladawy

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Robust Fractional Low Order Adaptive Linear Chirplet Transform and Its Application to Fault Analysis by Junbo Long, Changshou Deng, Haibin Wang, Youxue Zhou

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Classification Analytics for Wind Turbine Blade Faults: Integrated Signal Analysis and Machine Learning Approach by Waqar Ali, Idriss El-Thalji, Knut Erik Teigen Giljarhus, Andreas Delimitis

“…However, a key gap remains in integrating these methods into a unified framework for fault prediction, which could offer a more comprehensive solution for diagnosing faults. …”
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Analysis and Diagnosis of the Stator Turn-to-Turn Short-Circuit Faults in Wound-Rotor Synchronous Generators by Haotian Mao, Khashayar Khorasani, Yingqing Guo

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Typical Faults Analysis and Troubleshooting of a MetroTrain MVB Communication Network Control System by Zhengwei HU, Yun JI, Fangfang JIAO, Hongxing ZHANG, Rushi LI

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Markov-CVAELabeller: A Deep Learning Approach for the Labelling of Fault Data by Christian Velasco-Gallego, Nieves Cubo-Mateo

“…Markov-CVAELabeller comprises three main phases: (1) image encoding through the application of the first-order Markov chain, (2) latent space representation through the consideration of a convolutional variational autoencoder (CVAE), and (3) clustering analysis through the implementation of <i>k</i>-means. …”
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Russian education faults by Tatyana A. Voronova, Anatoliy I. Gretchenko, Mikhail N. Kulapov, Valeriy M. Zuev, Irina A. Kalinina

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Understanding Discrepancy of Power System Dynamic Security Assessment with Unknown Faults: A Reliable Transfer Learning-based Method by Chao Ren, Han Yu, Yan Xu, Zhao Yang Dong

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Development of fault detection system in irrigation pumping systems using machine learning methods with consideration of energy and water consumption by Gulnar Zholdangarova, Waldemar Wójcik

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