Search Results - "Sun Chuang, Sun Chuang"

Knowledge Transfer for Rotary Machine Fault Diagnosis by Yan, Ruqiang, Shen, Fei, Sun, Chuang, Chen, Xuefeng

“…This paper intends to provide an overview on recent development of knowledge transfer for rotary machine fault diagnosis (RMFD) by using different transfer…”
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Multireceptive Field Graph Convolutional Networks for Machine Fault Diagnosis by Li, Tianfu, Zhao, Zhibin, Sun, Chuang, Yan, Ruqiang, Chen, Xuefeng

“…Deep learning (DL) based methods have swept the field of mechanical fault diagnosis, because of the powerful ability of feature representation. However, many…”
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Joint Learning of Degradation Assessment and RUL Prediction for Aeroengines via Dual-Task Deep LSTM Networks by Miao, Huihui, Li, Bing, Sun, Chuang, Liu, Jie

“…Health assessment and prognostics are two key tasks within the prognostics and health management frame of equipment. However, existing works are performing…”
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Deep Coupling Autoencoder for Fault Diagnosis With Multimodal Sensory Data by Ma, Meng, Sun, Chuang, Chen, Xuefeng

“…Effective fault diagnosis of rotating machinery has multifarious benefits, such as improved safety, enhanced reliability, and reduced maintenance cost, for…”
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Applications of Unsupervised Deep Transfer Learning to Intelligent Fault Diagnosis: A Survey and Comparative Study by Zhao, Zhibin, Zhang, Qiyang, Yu, Xiaolei, Sun, Chuang, Wang, Shibin, Yan, Ruqiang, Chen, Xuefeng

“…Recent progress on intelligent fault diagnosis (IFD) has greatly depended on deep representation learning and plenty of labeled data. However, machines often…”
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Sparse Deep Stacking Network for Fault Diagnosis of Motor by Sun, Chuang, Ma, Meng, Zhao, Zhibin, Chen, Xuefeng

“…A sparse deep learning method is proposed to overcome overfitting risk of deep networks with a large number of nodes and layers. Deep stacking network (DSN) is…”
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Deep Transfer Learning Based on Sparse Autoencoder for Remaining Useful Life Prediction of Tool in Manufacturing by Sun, Chuang, Ma, Meng, Zhao, Zhibin, Tian, Shaohua, Yan, Ruqiang, Chen, Xuefeng

“…Deep learning with ability to feature learning and nonlinear function approximation has shown its effectiveness for machine fault prediction. While, how to…”
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Discriminative Deep Belief Networks with Ant Colony Optimization for Health Status Assessment of Machine by Ma, Meng, Sun, Chuang, Chen, Xuefeng

“…On-line health status monitoring, a key part of prognostics and health management, provides various benefits, such as preventing unexpected failure and…”
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Active Disturbance Rejection Control of Bearingless Permanent Magnet Slice Motor Based on RPROP Neural Network Optimized by Improved Differential Evolution Algorithm by Sun, Chuang, Zhu, Huangqiu

“…In order to realize the strong anti-disturbance capability and the precise control of suspension forces in a bearingless permanent magnet slice motor (BPMSM),…”
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Domain Adversarial Graph Convolutional Network for Fault Diagnosis Under Variable Working Conditions by Li, Tianfu, Zhao, Zhibin, Sun, Chuang, Yan, Ruqiang, Chen, Xuefeng

“…Unsupervised domain adaptation (UDA)-based methods have made great progress in mechanical fault diagnosis under variable working conditions. In UDA, three…”
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Variational Attention-Based Interpretable Transformer Network for Rotary Machine Fault Diagnosis by Li, Yasong, Zhou, Zheng, Sun, Chuang, Chen, Xuefeng, Yan, Ruqiang

“…Deep learning technology provides a promising approach for rotary machine fault diagnosis (RMFD), where vibration signals are commonly utilized as input of a…”
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Dislocated Time Series Convolutional Neural Architecture: An Intelligent Fault Diagnosis Approach for Electric Machine by Liu, Ruonan, Meng, Guotao, Yang, Boyuan, Sun, Chuang, Chen, Xuefeng

“…In most current intelligent diagnosis methods, fault classifiers of electric machine are built based on complex handcrafted features extractor from raw…”
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A Hierarchical Silver‐Nanowire–Graphene Host Enabling Ultrahigh Rates and Superior Long‐Term Cycling of Lithium‐Metal Composite Anodes by Xue, Pan, Liu, Shuiren, Shi, Xinlei, Sun, Chuang, Lai, Chao, Zhou, Ying, Sui, Dong, Chen, Yongsheng, Liang, Jiajie

“…Metallic lithium (Li) is a promising anode for next‐generation high‐energy‐density batteries, but its applications are still hampered due to the limited…”
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Deep-Learning-Based Open Set Fault Diagnosis by Extreme Value Theory by Yu, Xiaolei, Zhao, Zhibin, Zhang, Xingwu, Zhang, Qiyang, Liu, Yilong, Sun, Chuang, Chen, Xuefeng

“…Existing data-driven fault diagnosis methods assume that the label sets of the training data and test data are consistent, which is usually not applicable for…”
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Explainable Graph Wavelet Denoising Network for Intelligent Fault Diagnosis by Li, Tianfu, Sun, Chuang, Li, Sinan, Wang, Zhiying, Chen, Xuefeng, Yan, Ruqiang

“…Deep learning (DL)-based intelligent fault diagnosis methods have greatly promoted the development of the field of fault diagnosis due to their powerful…”
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Interface Engineering via Ti3C2Tx MXene Electrolyte Additive toward Dendrite-Free Zinc Deposition by Sun, Chuang, Wu, Cuiping, Gu, Xingxing, Wang, Chao, Wang, Qinghong

“…Highlights Well-dispersed MXene nanosheets in the electrolyte dramatically shorten Zn 2+ diffusion pathways and facilitate their migration. MXene interfacial…”
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Intelligent Fault Diagnosis for Planetary Gearbox Using Time-Frequency Representation and Deep Reinforcement Learning by Wang, Hui, Xu, Jiawen, Sun, Chuang, Yan, Ruqiang, Chen, Xuefeng

“…Accurately and intelligently identifying faults of the planetary gearbox is essential in the safe and reliable operation and maintenance of the mechanical…”
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WaveletKernelNet: An Interpretable Deep Neural Network for Industrial Intelligent Diagnosis by Li, Tianfu, Zhao, Zhibin, Sun, Chuang, Cheng, Li, Chen, Xuefeng, Yan, Ruqiang, Gao, Robert X.

“…Convolutional neural network (CNN), with the ability of feature learning and nonlinear mapping, has demonstrated its effectiveness in prognostics and health…”
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Fault-Attention Generative Probabilistic Adversarial Autoencoder for Machine Anomaly Detection by Wu, Jingyao, Zhao, Zhibin, Sun, Chuang, Yan, Ruqiang, Chen, Xuefeng

“…Anomaly detection is one of the most fundamental and indispensable components in predictive maintenance. In this article, anomaly detection is modeled as a…”
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Conditional Adversarial Domain Adaptation With Discrimination Embedding for Locomotive Fault Diagnosis by Yu, Xiaolei, Zhao, Zhibin, Zhang, Xingwu, Sun, Chuang, Gong, Baogui, Yan, Ruqiang, Chen, Xuefeng

“…Deep-learning-based methods have been widely applied to fault diagnosis for its capability of automatically extracting features from massive data. However,…”
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