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Unknown working condition fault diagnosis of rotate machine without training sample based on local fault semantic attribute

Advanced Engineering Informatics
Xuejun Liu, Wei Sun, Hongkun Li, Qiang Li, Zhenhui Ma, Chen Yang   +5 more
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Robust fault diagnosis of rolling bearings via entropy-weighted nuisance attribute projection and neural network under various operating conditions

Structural Health Monitoring, 2022
Rolling bearings are crucial components in the fields of mechanical, civil, and aerospace engineering. They sometimes work under various operating conditions, which makes it harder to distinguish faults from normal signals. Nuisance attribute projection (NAP) is a technique that has been widely used in audio and image recognition to eliminate ...
Di Yang, Yong Lv, Rui Yuan, Hewenxuan Li, Weihang Zhu   +4 more
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Hybrid attribute conditional adversarial denoising autoencoder for zero-shot classification of mechanical intelligent fault diagnosis

Applied Soft Computing, 2020
Abstract Data-based intelligent fault diagnosis method is a research hotspot in modern mechanical systems. However, due to practical limitations, fault samples under all working conditions cannot be obtained, which would cause the data-based model lack of particular training data, resulting in unsatisfied testing performance.
Haixin Lv, Jinglong Chen, Tongyang Pan, Zitong Zhou   +3 more
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Rolling bearing fault diagnosis and performance degradation assessment under variable operation conditions based on nuisance attribute projection

Mechanical Systems and Signal Processing, 2019
Abstract The operation conditions are always non-stationary in the operation of rotating machinery. It is the key to realize the fault diagnosis of rotating machinery under different operation conditions by extracting the features which are irrelevant to the operation conditions and contain fault information.
Wenyi Huang, Junsheng Cheng, Yu Yang
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A novel vibro-acoustic fault diagnosis method of rolling bearings via entropy-weighted nuisance attribute projection and orthogonal locality preserving projections under various operating conditions

Applied Acoustics, 2022
Di Yang, Yong Lv, Rui Yuan, Ke Yang, Hongyu Zhong   +4 more
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Improved Workflow for Fault Detection and Extraction Using Seismic Attributes and Orientation Clustering

Applied Sciences (Switzerland), 2021
Jeongmin Yu
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Automated Fault Detection and Extraction under Gas Chimneys Using Hybrid Discontinuity Attributes

Applied Sciences (Switzerland), 2021
Qazi Sohail Imran, Numair Ahmed Siddiqui, Abdul Halim Abdul Latiff   +2 more
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Fault Enhancement in Seismic Images by Introducing a Novel Strategy Integrating Attributes and Image Analysis Techniques

Pure and Applied Geophysics, 2022
Mohammad Radad, Mehrdad Soleimani, Amin Roshandel Kahoo   +2 more
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Federated knowledge amalgamation with unbiased semantic attributes under cloud–edge collaboration for heterogeneous fault diagnosis

Journal of Process Control, 2023
Pengyu Song, Chunhui Zhao, Jinliang Ding   +2 more
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Pyramid-type zero-shot learning model with multi-granularity hierarchical attributes for industrial fault diagnosis

Reliability Engineering and System Safety, 2023
Chunhui Zhao, Jinliang Ding
exaly