Yongjian Wang

An FFT-LPS–MSDRNet-1D–DAN Framework for Three-Phase Stator Current-Based Cross-Speed Fault Diagnosis of Induction Motors

Manqiang Liu, Yongjian Wang

To address weak fault signatures, unavailable target-speed sample labels, and spectral distribution shifts between source- and target-speed domains in current-only cross-speed fault diagnosis of induction motors, this paper proposes an unsupervised domain adaptation method integrating FFT-LPS, MSDRNet-1D, and DAN. First, three-phase stator-current …

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Anomaly diagnosis of crude oil online near-infrared spectroscopy analysis system with ensemble ICSSOA-SVM

Xiaojie Gu, Yongjian Wang, Xisong Chen

This paper presents an anomaly diagnosis framework for the Crude Oil Online Near-Infrared Spectroscopy Analysis System (CO-NIRS), addressing challenges such as high-dimensional features, susceptibility to local optima, and insufficient diagnostic accuracy. The framework ensembles an Improved Chaos Sparrow Search Optimization Algorithm-enhanced Support …

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A Cross-Domain Deep Adaptive Measurement approach for industrial equipment fault monitoring

Yongjian Wang, Cheng Qian, Shihua Li, Lang Yang et autres

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Enhanced capillary performance of Chemically-corroded laser-ablated wick with nanowire-pore structure for copper vapor chamber

Shuang Liu, Yu Zhang, Yongjian Wang, Wenjie Miao et autres

CineFault-DG: Domain-Generalized Multimodal Fault Diagnosis for Quality Control in Virtual Film Production

Yining Xu, Fang Wang, Yajie Cao, Yongjian Wang

Virtual production has become a central workflow in contemporary film and television making, combining LED volume stages, real-time rendering, camera tracking, color management, and post-production tools into a tightly coupled creative-technical pipeline. However, the same coupling that enables in-camera visual effects also …

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Interactive Transformer with Adaptive Feature Optimization for Fault Diagnosis from Incomplete Signals

Yongjian Wang, Cheng Qian, Shihua Li

An incremental intelligent fault diagnosis method for marine diesel engines based on CNN-Transformer and cosine similarity

Yingying Wu, Yongjian Wang, Hangxi Cai, Guoqiang Li et autres

This paper proposes an incremental intelligent fault diagnosis method for marine diesel engines based on a Convolutional Neural Network (CNN)-Transformer architecture and cosine similarity. The method is designed to address critical limitations of conventional supervised diagnostic frameworks, including heavy reliance on labeled …

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An Ensemble Detector with Probability Transformation for Incipient Faults in Dynamic Process

Shuai Zheng, Yongjian Wang, Xisong Chen, Mengze Gao

Incipient fault detection (IFD) is crucial for secure and reliable operation in industrial processes, aiming to detect incipient faults as early as possible and to protect the safety of operators. In recent years, multivariate statistical methods have been widely used in incipient …

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An enhanced algorithm for cell-level anomaly segmentation in photovoltaic solar panels using electroluminescence imaging

Yongjian Wang, Xisong Chen, Shihua Li

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Experimental and simulation insights into series-to-parallel transition: Exploring critical speed for optimizing energy utilization efficiency in PHEV

Yongchang Zhong, Yuan Yan, Xiaofei Wang, Yongjian Wang et autres

Plug-in hybrid electric vehicles (PHEVs) have emerged as a promising solution to reduce fuel consumption and emissions in the transportation sector. However, optimizing the energy management strategy, particularly the transition between series and parallel modes, remains a critical challenge for maximizing energy …

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A novel BDPCA-SMLSTM algorithm for fault diagnosis of industrial process

Shuai Zheng, Shihua Li, Yongjian Wang

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The Influence of Ti Coating on the Mechanical Properties of Additively Manufactured Diamond Tools with Lattice Structure

Yongjian Wang, Chi Chen, Chenchen Tian, Yi Wan

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