Incremental Pyraformer–Deep Canonical Correlation Analysis: A Novel Framework for Effective Fault Detection in Dynamic Nonlinear Processes by Yucheng Ding, Yingfeng Zhang, Jianfeng Huang, Shitong Peng

“…However, capturing nonlinear and temporal dependencies in dynamic nonlinear industrial processes poses significant challenges for traditional data-driven fault detection methods. …”
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Reliability assessment of elastic distribution network based on fault correlation matrix by LI Ning, HU Jiale, ZHAN Xiaoxuan, SHEN Panpan, JIANG Panyong, ZHUO Chaoran

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Fault Diagnosis of Industrial Process Based on FDKICA-PCA by ZHANG Jing, ZHU Fei-fei, LIU Jia-xing, WANG Jiang-tao

“…Because the dynamic characteristics of autocorrelation and lag correlation in production process are neglected in fault diagnosis,Kernel Independent Component AnalysisPrincipal Component Analysis (KICAPCA) is very poor in detecting small and gradual faults because of lacking available variable contribution analysis.In this paper, a dynamic kernel independent component analysis (KICAPCA) fault diagnosis method based on wavelet packet filtering is proposed.This method integrates wavelet packet filtering theory and AR model prediction data characteristics into KICAPCA to extract the feature information of process variable autocorrelation and lagrelated .In this paper, KICAPCA algorithm is used to extract the independent components and principal components of process variables to determine the control limits of three monitoring indicators T2, SPE,I2.Nonlinear contribution graph is used for fault diagnosis, and the advantage of FDKICAPCA method is verified by simulation results of Tennessee process.…”
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THE EXPERIMENTAL STUDY ON STICK­SLIP PROCESS  OF BENDING FAULTS by Guo Yanshuang, Ma Jin, Yun Long, Sergei A. Bornyakov

“…The stick­slip process of bending faults with one angle change of 5° at the connection location between the two line fault segments is investigated in this paper. …”
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An approach for fault-related monitoring variables selection based on dual-layer correlation networks by Zhenjie Zhang, Xinjiu Chen, Xiaobin Xu, Yi Li, Pingzhi Hou, Zehui Zhang, Haohao Guo

“…Purpose – Fault-related monitoring variables selection is a process of obtaining a subset of variables from the original set, which is of great significance for reducing information redundancy and improving the performance of the fault diagnosis models. …”
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Heuristic localization of faults in power transmission lines with uncertainty in parameters and fault-impedance by Akif Nadeem, Qingyan Zhang, Feng Cao, Arslan A. Rizvi, Salah-ud-din Khokhar

“…Unlike existing stochastic correlation-based methods, this approach improves the fault location accuracy, does not require fault data pre-processing, and effectively quantify the uncertain variations in line parameters and fault-impedance. …”
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Progress in Root Cause and Fault Propagation Analysis of Large-Scale Industrial Processes by Fan Yang, Deyun Xiao

“…In large-scale industrial processes, a fault can easily propagate between process units due to the interconnections of material and information flows. …”
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Development Process and Characteristics Study of Tree Line Discharge in 10 kV Overhead Power Lines by XU Huikai, HUANG Xiaolong, YANG Chunlan, CHEN Tianxiang, YANG Nongchao, CHEN Long

“…In addition, several issues emerged during the experimental process that differ from conventional single-phase grounding faults. …”
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Adaptive Fault Detection for Complex Dynamic Processes Based on JIT Updated Data Set by Jinna Li, Yuan Li, Haibin Yu, Yanhong Xie, Cheng Zhang

“…A novel fault detection technique is proposed to explicitly account for the nonlinear, dynamic, and multimodal problems existed in the practical and complex dynamic processes. …”
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Multiscale Interaction Purification-Based Global Context Network for Industrial Process Fault Diagnosis by Yukun Huang, Jianchang Liu, Peng Xu, Lin Jiang, Xiaoyu Sun, Haotian Tang

“…The application of deep convolutional neural networks (CNNs) has gained popularity in the field of industrial process fault diagnosis. However, conventional CNNs primarily extract local features through convolution operations and have limited receptive fields. …”
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Sequence-Aware Vision Transformer with Feature Fusion for Fault Diagnosis in Complex Industrial Processes by Zhong Zhang, Ming Xu, Song Wang, Xin Guo, Jinfeng Gao, Aiguo Patrick Hu

“…Experimental analyses on data segment length, network depth, feature fusion and attention head receptive field validate the approach, demonstrating that a shallower encoder network is better suited for high-dimensional time-series fault diagnosis in complex industrial processes compared to deeper networks. …”
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A New Evidential Reasoning Rule Considering Evidence Correlation with Maximum Information Coefficient and Application in Fault Diagnosis by Shanshan Liu, Guanyu Hu, Shaohua Du, Hongwei Gao, Liang Chang

“…The evidential reasoning (ER) rule has been widely adopted in engineering fault diagnosis, yet its conventional implementations inherently neglect evidence correlations due to the foundational independence assumption required for Bayesian inference. …”
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A Feature Extraction Algorithm for Rolling Bearing Faults and Its Application by Zhen Zhang, Baoguo Liu, Wenliao Du, Wei Feng

“…Focusing on the difficulty of completely extracting the surface damage caused by rolling bearing lubrication failure, an algorithm for extracting bearing lubrication fault is proposed, which is based on periodic optimum singular value decomposition (O-SVD) cascaded fast spectral correlation (FSC). …”
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Causal discovery and fault diagnosis based on mixed data types for system reliability modeling by Xiaokang Wang, Siqi Jiang, Xinghan Li, Mozhu Wang

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A survey of data-driven fault-diagnosis methods for large-scale industrial production processes by Qianxiang YU, Qing LI, Linlin LI, Yixuan WANG

“…Fault diagnosis for large-scale industrial production systems has attracted considerable research interest in response to the complex, multisource, and precision requirements of these processes. …”
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A Distributed Detection Method for Quality-related Faults in Complex Non-stationary Industrial Processes by Jie DONG, Daye LI, Yanmei WEI, Kaixiang PENG, Hui YANG

“…These non-stationary characteristics can obscure faults in industrial processes. Traditional quality-related fault detection methods cannot detect abnormalities on time, leading to the transfer and evolution of faults between different operational units of industrial processes. …”
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Enhanced Fault Localization in Multi-Terminal HVDC Systems Using Improved Gaussian Process Regression by Abha Pragati, Manohar Mishra, Pritam Bhowmik, Josep M. Guerrero, Debadatta Amaresh Gadanayak

“…This study proposes an improved Gaussian process regression (IGPR)-based fault location method for a multi-terminal high voltage DC (HVDC) system. …”
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Oil and source correlation and its geological significance of Fengcheng 1 well block in Wuxia fault zone, Junggar Basin by Guanbo LIU, Shijia CHEN, Wenjun HE, Yangyang ZHANG

“…As the conventional oil and gas exploration in the Wuxia fault zone of the western uplift of the Junggar Basin enters its later stages, great breakthroughs have been made in shale oil exploration of the Lower Permian Fengcheng Formation in the past two years. …”
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Impact of Optical Imagery and Topography Data Resolution on the Measurement of Surface Fault Displacement Using Sub‐Pixel Image Correlation by Solène L. Antoine, Zhen Liu

“…In this study, we assess the effect of optical imagery and topography data resolution on the measurement of the earthquake surface displacement when using optical image cross‐correlation (OIC) techniques. Results show that the average noise in the output displacement maps linearly increases with decreasing image resolution, resulting in greater uncertainties in mapping surface fault geometry and associated displacement. …”
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Big Earth data processing using machine learning for integrated mapping of the dead sea fault, Jordan by Polina Lemenkova

“…The objective is to analyze a correlation between the factors affecting the geomorphological shape of Jordan with respects to the Dead Sea Fault and geological evolution. …”
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