Search Results - "Li, Jipu"

Dynamic Distribution Adaptation Based Transfer Network for Cross Domain Bearing Fault Diagnosis by Liao, Yixiao, Huang, Ruyi, Li, Jipu, Chen, Zhuyun, Li, Weihua

“…In machinery fault diagnosis, labeled data are always difficult or even impossible to obtain. Transfer learning can leverage related fault diagnosis knowledge…”
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Correction to: Dynamic Distribution Adaptation Based Transfer Network for Cross Domain Bearing Fault Diagnosis by Liao, Yixiao, Huang, Ruyi, Li, Jipu, Chen, Zhuyun, Li, Weihua

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Clustering Federated Learning for Bearing Fault Diagnosis in Aerospace Applications with a Self-Attention Mechanism by Li, Weihua, Yang, Wansheng, Jin, Gang, Chen, Junbin, Li, Jipu, Huang, Ruyi, Chen, Zhuyun

“…Bearings, as the key mechanical components of rotary machinery, are widely used in modern aerospace equipment, such as helicopters and aero-engines…”
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A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges by Li, Weihua, Huang, Ruyi, Li, Jipu, Liao, Yixiao, Chen, Zhuyun, He, Guolin, Yan, Ruqiang, Gryllias, Konstantinos

“…Deep Transfer Learning (DTL) is a new paradigm of machine learning, which can not only leverage the advantages of Deep Learning (DL) in feature representation,…”
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Deep Semisupervised Domain Generalization Network for Rotary Machinery Fault Diagnosis Under Variable Speed by Liao, Yixiao, Huang, Ruyi, Li, Jipu, Chen, Zhuyun, Li, Weihua

“…In recent years, deep learning has become a promising tool for rotary machinery fault diagnosis, but it works well only when testing samples and training…”
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Domain Adversarial Transfer Network for Cross-Domain Fault Diagnosis of Rotary Machinery by Chen, Zhuyun, He, Guolin, Li, Jipu, Liao, Yixiao, Gryllias, Konstantinos, Li, Weihua

“…Recently, deep learning-based intelligent fault diagnosis techniques have obtained good classification performance with amount of supervised training data…”
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A Robust Weight-Shared Capsule Network for Intelligent Machinery Fault Diagnosis by Huang, Ruyi, Li, Jipu, Wang, Shuhua, Li, Guanghui, Li, Weihua

“…In practical industrial applications, the working conditions of machinery are changing with long-term operation, and the health status is declining with the…”
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A Two-Stage Transfer Adversarial Network for Intelligent Fault Diagnosis of Rotating Machinery With Multiple New Faults by Li, Jipu, Huang, Ruyi, He, Guolin, Liao, Yixiao, Wang, Zhen, Li, Weihua

“…Recently, deep transfer learning based intelligent fault diagnosis has been widely investigated, and the tasks that source and target domains share the same…”
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Deep Ensemble Capsule Network for Intelligent Compound Fault Diagnosis Using Multisensory Data by Huang, Ruyi, Li, Jipu, Li, Weihua, Cui, Lingli

“…With the manufacturing industry stepping into the emerging new era of big data and intelligence, the amount of data collected from perception and monitoring…”
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Deep Adversarial Capsule Network for Compound Fault Diagnosis of Machinery Toward Multidomain Generalization Task by Huang, Ruyi, Li, Jipu, Liao, Yixiao, Chen, Junbin, Wang, Zhen, Li, Weihua

“…With advanced measurement technologies and signal analytics algorithms developed rapidly, the past decades have witnessed large amount of successful…”
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Federated Transfer Learning for Bearing Fault Diagnosis With Discrepancy-Based Weighted Federated Averaging by Chen, Junbin, Li, Jipu, Huang, Ruyi, Yue, Ke, Chen, Zhuyun, Li, Weihua

“…Generally, high performance of deep learning (DL)-based machinery fault diagnosis methods relies on abundant labeled fault samples under various working…”
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Deep Self-Supervised Domain Adaptation Network for Fault Diagnosis of Rotating Machine With Unlabeled Data by Li, Jipu, Huang, Ruyi, Chen, Junbin, Xia, Jingyan, Chen, Zhuyun, Li, Weihua

“…Recently, domain adaptation (DA)-based fault diagnosis (FD) approaches have been receiving increasing attention in intelligent FD of rotating machinery due to…”
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A Multi-Source Weighted Deep Transfer Network for Open-Set Fault Diagnosis of Rotary Machinery by Chen, Zhuyun, Liao, Yixiao, Li, Jipu, Huang, Ruyi, Xu, Lei, Jin, Gang, Li, Weihua

“…In real industries, there often exist application scenarios where the target domain holds fault categories never observed in the source domain, which is an…”
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A Deep Adversarial Transfer Learning Network for Machinery Emerging Fault Detection by Li, Jipu, Huang, Ruyi, He, Guolin, Wang, Shuhua, Li, Guanghui, Li, Weihua

“…Deep transfer learning has attracted many attentions in machine intelligent fault diagnosis. However, most existed deep transfer learning algorithms encounter…”
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Multiscale Wavelet Prototypical Network for Cross-Component Few-Shot Intelligent Fault Diagnosis by Yue, Ke, Li, Jipu, Chen, Junbin, Huang, Ruyi, Li, Weihua

“…The techniques of machine learning, as well as deep learning (DL) methods, have seen a wide application in the intelligent fault diagnosis field these years…”
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Generalized open-set domain adaptation in mechanical fault diagnosis using multiple metric weighting learning network by Chen, Zhuyun, Xia, Jingyan, Li, Jipu, Chen, Junbin, Huang, Ruyi, Jin, Gang, Li, Weihua

“…•A generalized open-set fault diagnosis (OSFD) scenario is defined.•A multiple metric weighting learning network is constructed to address two OSFD issues…”
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Multiple Source-free Domain Adaptation Network based on Knowledge Distillation for Machinery Fault Diagnosis by Yue, Ke, Li, Jipu, Chen, Zhuyun, Huang, Ruyi, Li, Weihua

“…Data privacy protection is a hot-button issue in the field of intelligent fault diagnosis. For this purpose, plenty of methods are recently proposed to adapt a…”
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Digital Twin-Assisted Fault Diagnosis of Rotating Machinery Without Measured Fault Data by Xia, Jingyan, Huang, Ruyi, Li, Jipu, Chen, Zhuyun, Li, Weihua

“…Timely and accurate data-driven fault diagnosis approaches are essential for ensuring the reliable operation and efficient maintenance of rotating machinery…”
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Deep continual transfer learning with dynamic weight aggregation for fault diagnosis of industrial streaming data under varying working conditions by Li, Jipu, Huang, Ruyi, Chen, Zhuyun, He, Guolin, Gryllias, Konstantinos C., Li, Weihua

“…Catastrophic forgetting of learned knowledges and distribution discrepancy of different data are two key problems within fault diagnosis fields of rotating…”
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An auto-regulated universal domain adaptation network for uncertain diagnostic scenarios of rotating machinery by Li, Jipu, Zhang, Xiaoge, Yue, Ke, Chen, Junbin, Chen, Zhuyun, Li, Weihua

“…In recent years, domain adaptation techniques have garnered significant attention in the field of intelligent fault diagnosis for mechanical equipment. Domain…”
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