A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges
Abstract 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, but also …
not only leverage the advantages of Deep Learning (DL) in feature representation, but also …
A review of vibration-based gear wear monitoring and prediction techniques
Gearbox plays a vital role in a wide range of mechanical power transmission systems in
many industrial applications, including wind turbines, vehicles, mining and material handling …
many industrial applications, including wind turbines, vehicles, mining and material handling …
[PDF][PDF] 大数据下机械智能故障诊断的机遇与挑战
雷亚国， 贾峰， 孔德同， 林京， 邢赛博 - 机械工程学报, 2018 - qikan.cmes.org
机械故障是风力发电设备, 航空发动机, 高档数控机床等大型机械装备安全可靠运行的“潜在杀手”
. 故障诊断是保障机械装备安全运行的“杀手锏”. 由于诊断的装备量大面广, 每台装备测点多 …
. 故障诊断是保障机械装备安全运行的“杀手锏”. 由于诊断的装备量大面广, 每台装备测点多 …
Digital twin paradigm: A systematic literature review
Manufacturing enterprises are facing the need to align themselves to the new information
technologies (IT) and respond to the new challenges of variable market demand. One of the …
technologies (IT) and respond to the new challenges of variable market demand. One of the …
Prognostics and health management of Lithium-ion battery using deep learning methods: A review
Y Zhang, YF Li - Renewable and sustainable energy reviews, 2022 - Elsevier
Prognostics and health management (PHM) is developed to guarantee the safety and
reliability of Lithium-ion (Li-ion) battery during operations. Due to the advantages of deep …
reliability of Lithium-ion (Li-ion) battery during operations. Due to the advantages of deep …
A comprehensive review of digital twin—part 1: modeling and twinning enabling technologies
As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented
attention because of its promise to further optimize process design, quality control, health …
attention because of its promise to further optimize process design, quality control, health …
Machine learning in predictive maintenance towards sustainable smart manufacturing in industry 4.0
Recently, with the emergence of Industry 4.0 (I4. 0), smart systems, machine learning (ML)
within artificial intelligence (AI), predictive maintenance (PdM) approaches have been …
within artificial intelligence (AI), predictive maintenance (PdM) approaches have been …
Transfer learning algorithms for bearing remaining useful life prediction: A comprehensive review from an industrial application perspective
Accurate remaining useful life (RUL) prediction for rolling bearings encounters many
challenges such as complex degradation processes, varying working conditions, and …
challenges such as complex degradation processes, varying working conditions, and …
Wavelet transform for rotary machine fault diagnosis: 10 years revisited
As a multi-resolution analysis method rooted rigorously in mathematics, wavelet transform
(WT) has shown its great potential in rotary machine fault diagnosis, characterized by …
(WT) has shown its great potential in rotary machine fault diagnosis, characterized by …