Bi Wu

A pseudo-labeling training-based progressive multi-scale adaptive network for fault localization of high-speed train bogies

Qingjie Liu, Bi Wu, Na Qin, Deqing Huang et autres

The high-speed train (HST) bogie, as the sole mechanical connection between the train body and the track, endures diverse operational loads and forces, making it crucial to minimize abnormal vibrations and ensure safety. Existing intelligent diagnostic models, typically trained on single-speed datasets, …

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Distribution characteristics of microplastics in wastewater treatment plants in mega cities–the case study of Chengdu City

Jieyu Lv, Tao Huang, Bi Wu, Xinhao Hu et autres

With the increasingly serious problem of microplastic pollution, wastewater treatment plants (WWTPs) have attracted much attention as a key node for intercepting microplastics into the natural environment. In this study, the distribution characteristics of microplastics and their removal efficacy in wastewater treatment …

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Fault Diagnosis of Multi-Railway High-Speed Train Bogies by Improved Federated Learning

Jiahao Du, Yiming Zhang, Deqing Huang, Bi Wu

Bogie is the unique connection unit between the train body and rails, and degenerations of its key elements could seriously threaten train safety. In previous works that address the fault diagnosis of bogie of high-speed train (HST), only a single railway is …

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Stepwise Adaptive Convolutional Network for Fault Diagnosis of High-Speed Train Bogie Under Variant Running Speeds

Bi Wu, Deqing Huang, Yiming Zhang

Fault diagnosis of high-speed train (HST) bogie plays an indispensable role in guaranteeing the safety and stability of the daily operation of HST. Up to now, the well-established fault diagnosis models of HST bogie, which are usually trained by supervised learning mechanism, …

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High-Accuracy and Adaptive Fault Diagnosis of High-Speed Train Bogie Using Dense-Squeeze Network

Yiming Zhang, Deqing Huang, Bi Wu, Ziyi Liu

As one of the most important systems of high-speed train (HST), bogie system matters when it comes to the safety and reliability of HST operation. In order to strengthen feature propagation and alleviate vanishing gradients problems in training deep-learning networks, a novel …

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Topology optimization of damping material layout in coupled vibro-acoustic system using hybrid finite element-wave based method

Bi Wu, Weichun Fan, Zhongming Xu, Zhifei Zhang et autres

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LeanNet: An Efficient Convolutional Neural Network for Digital Number Recognition in Industrial Products

Na Qin, Longkai Liu, Deqing Huang, Bi Wu et autres

The remarkable success of convolutional neural networks (CNNs) in computer vision tasks is shown in large-scale datasets and high-performance computing platforms. However, it is infeasible to deploy large CNNs on resource constrained platforms, such as embedded devices, on account of the huge …

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KCF-Match Target Tracking Algorithm for Tracking Swing Angle of Coupler Based on Video

Jiahao Du, Na Qin, Yiming Zhang, Bi Wu et autres

The coupler is an essential component on the train that has the function of connecting and buffering. The actual dynamic performance of the coupler directly influences the safety and comfort of the vehicle. When the heavy haul train passes through the curve, …

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Structural multi-objective topology optimization and application based on the criteria importance through intercriteria correlation method

Weichun Fan, Zhongming Xu, Bi Wu, Yansong He et autres

A structural multi-objective topology optimization method integrating the solid isotropic material with penalization (SIMP) approach, compromise programming method and criteria importance through intercriteria correlation (CRITIC) method is proposed. The SIMP approach performs topology optimization. The compromise programming method builds a comprehensive objective …

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Optical Flow Based Face Hallucination Via Weightedly-Constrained Representation

Bi Wu, Zhihua Cai, Xiaobo Liu

Face hallucination can improve the resolution of observed low-resolution (LR) face image to predict the high-resolution (HR) face image. In order to achieve good result performance, the training samples and local structure prior of face image are utilized by some approaches including …

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An Event Detection Method for Social Networks Based on Evolution Fluctuations of Nodes

Huan Wang, Wenbin Hu, Zhenyu Qiu, Bi Wu

How can we discover and estimate major events in complex social networks? Event detection and evaluation in social networks provide an effective solution, which has become the critical basis for many real applications, such as crisis management and decision making. However, the …

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Extreme Learning Machine Based on Evolutionary Multi-objective Optimization

Yaoming Cai, Xiaobo Liu, Yu Wu, Peng Hu et autres

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