Výsledky vyhľadávania - "Improved stack autoencoder"

Fault Diagnosis of Rolling Bearings Based on an Improved Stack Autoencoder and Support Vector Machine

Autori: Mingliang Cui Youqing Wang Xinshuang Lin a ďalší

Zdroj: IEEE Sensors Journal. 21:4927-4937

Predmety: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 01 natural sciences, 0104 chemical sciences

Prístupová URL adresa: https://ieeexplore.ieee.org/document/9223764/
https://ui.adsabs.harvard.edu/abs/2021ISenJ..21.4927C/abstract

Fault Diagnosis of Rolling Bearings Based on an Improved Stack Autoencoder and Support Vector Machine.

Autori: Cui, Mingliang Wang, Youqing Lin, Xinshuang a ďalší

Zdroj: IEEE Sensors Journal; 2021, Vol. 21 Issue 2, p4927-4937, 11p

Fault Diagnosis of Pitch System of Wind Turbine based on Improved Stacked Auto-Encoder Network.

Autori: Sihua Wang Tian Wang Lijun Zhou a ďalší

Zdroj: Electrotehnica, Electronica, Automatica; Jul-Sep2020, Vol. 68 Issue 3, p47-54, 8p

Predmety: FAULT diagnosis, SUPERVISORY control & data acquisition systems, SUPERVISORY control systems, WEIGHT training, ALGORITHMS, ACQUISITION of data, WIND turbines

Deep Learning Technique-Based Steering of Autonomous Car.

Autori: Yang, Yiqin Wu, Zhe Xu, Qingyang a ďalší

Zdroj: International Journal of Computational Intelligence & Applications; Jun2018, Vol. 17 Issue 2, pN.PAG-N.PAG, 18p

Predmety: NEURAL circuitry, AUTONOMOUS vehicles, RASPBERRY Pi, BIOLOGICAL neural networks, LEARNING

Automatic Recommendation Algorithm for Video Background Music Based on Deep Learning.

Autori: Kai, Hong

Zdroj: Complexity; 2/3/2021, p1-11, 11p

Predmety: ENVIRONMENTAL music, MUSIC videos, DEEP learning, SIGNAL convolution, CONVOLUTIONAL neural networks, MATRIX decomposition, SPARSE matrices

Few-shot fault diagnosis of rolling bearing under variable conditions based on deep meta-transfer learning.

Autori: Zeng, Liang Chang, Xinyu Jian, Junjie a ďalší

Zdroj: Applied Intelligence; Nov2025, Vol. 55 Issue 16, p1-21, 21p

Lightweight bearing fault diagnosis via decoupled distillation and low rank adaptation.

Autori: Petrosian, Ovanes Li, Pengyi He, Yulong a ďalší

Zdroj: Scientific Reports; 10/16/2025, Vol. 15 Issue 1, p1-15, 15p

Predmety: DEEP learning, FAULT diagnosis, SIGNAL processing, KNOWLEDGE transfer, COMPUTER performance, STATISTICAL models

Open-set domain adaptation fusion method based on weighted adversarial learning for machinery fault diagnosis.

Autori: She, Bo Tan, Fangyin Zhao, Yang a ďalší

Zdroj: Journal of Intelligent Manufacturing; Oct2025, Vol. 36 Issue 7, p5067-5086, 20p

Predmety: FAULT diagnosis, DIAGNOSIS, MACHINE learning, DISCRIMINANT analysis

AttenResNet18: A Novel Cross-Domain Fault Diagnosis Model for Rolling Bearings.

Autori: Huang, Gangjin Wu, Shanshan Zhang, Yingxiao a ďalší

Zdroj: Sensors (14248220); Oct2025, Vol. 25 Issue 19, p5958, 25p

Predmety: FAULT diagnosis, ROLLER bearings, ARTIFICIAL neural networks, INTERDISCIPLINARY research, PATTERN recognition systems

A modified transformer based on adaptive frequency enhanced attention, large kernel convolution, and multiscale implementation for bearing fault diagnosis.

Autori: Chang, Xiao Cai, Shaobin Cai, Wanchen a ďalší

Zdroj: Scientific Reports; 9/25/2025, Vol. 15 Issue 1, p1-25, 25p

Predmety: FAULT diagnosis, DEEP learning, SIGNAL filtering, SIGNAL processing, FEATURE extraction, CONVOLUTIONAL neural networks, TRANSFORMER models

A transfer learning-based fault diagnosis method for rolling bearings with variable operating conditions.

Autori: Song, Cunli Yuan, Xiaomeng

Zdroj: Applied Intelligence; Sep2025, Vol. 55 Issue 14, p1-13, 13p

A Robust Rolling Bearing Fault Diagnosis Approach Using Hybrid Red Deer Optimization Based 1D-CNN.

Autori: Joseph, Thomas U., Sudeep K., Keerthi Krishnan a ďalší

Zdroj: International Journal of Acoustics & Vibration; Sep2025, Vol. 30 Issue 3, p272-283, 12p

Predmety: ROLLER bearings, FAULT diagnosis, SIGNAL separation, SIGNAL processing, METAHEURISTIC algorithms, SIGNAL denoising, FRACTAL analysis, CONVOLUTIONAL neural networks

Variable Working Condition Fault Diagnosis Method for Rotating Machinery Based on Dual-Task Cognitive Cost Sensitivity.

Autori: Jiang, Qianwen Xu, Jinghua Zhang, Shuyou a ďalší

Zdroj: Big Data & Cognitive Computing; Sep2025, Vol. 9 Issue 9, p232, 25p

Predmety: FAULT diagnosis, ROTATING machinery, MACHINE learning, COGNITIVE load, CONVOLUTIONAL neural networks, LONG short-term memory, TRANSFER of training, OPTIMIZATION algorithms

A novel approach of fault diagnosis for gearbox based on VMD optimized by SSA and improved RCMDE.

Autori: Cao, Jiahao Zhang, Xiaodong Wang, Hongwei a ďalší

Zdroj: Journal of Vibration & Control; Aug2025, Vol. 31 Issue 15/16, p3282-3294, 13p

Predmety: FAULT diagnosis, GEARBOXES, SUPPORT vector machines, SIGNAL processing, VIBRATION (Mechanics), WIND turbines

A Hybrid Deep Learning Approach for Bearing Fault Diagnosis Using Continuous Wavelet Transform and Attention-Enhanced Spatiotemporal Feature Extraction.

Autori: Siddique, Muhammad Farooq Saleem, Faisal Umar, Muhammad a ďalší

Zdroj: Sensors (14248220); May2025, Vol. 25 Issue 9, p2712, 23p

Predmety: LONG short-term memory, DEEP learning, FAULT diagnosis, TIME-frequency analysis, PLANT maintenance

An adaptive hierarchical hybrid kernel ELM optimized by aquila optimizer algorithm for bearing fault diagnosis.

Autori: Yan, Hao Shang, Liangliang Chen, Wan a ďalší

Zdroj: Scientific Reports; 4/8/2025, Vol. 15 Issue 1, p1-26, 26p

Predmety: EXTREME learning machines, MACHINE learning, ARTIFICIAL intelligence, FAULT diagnosis, AUTOENCODERS

Weaker top-down cognitive control and stronger bottom-up signaling transmission as a pathogenesis of schizophrenia.

Autori: Lyu, Xiaodan Liu, Tiantian Ma, Yunxiao a ďalší

Zdroj: Schizophrenia; 3/5/2025, Vol. 11 Issue 1, p1-12, 12p

Research on the Fault Diagnosis Method of Automotive Charging Pile Based on the Improved MLP with SAE.

Autori: Han, Yuanxun Ren, Mingzhu Ma, Qingliang a ďalší

Zdroj: Journal of Electrical Engineering & Technology (19750102); Mar2025, Vol. 20 Issue 3, p1333-1345, 13p

Intelligent Fault Diagnosis Across Varying Working Conditions Using Triplex Transfer LSTM for Enhanced Generalization.

Autori: Iqbal, Misbah Lee, Carman K. M. Keung, Kin Lok a ďalší

Zdroj: Mathematics (2227-7390); Dec2024, Vol. 12 Issue 23, p3698, 29p

Predmety: LONG short-term memory, MACHINE learning, HILBERT-Huang transform, FAULT diagnosis, INDUSTRIAL efficiency, BOTTLENECKS (Manufacturing), DEEP learning

A One-Dimensional Depthwise Separable Convolutional Neural Network for Bearing Fault Diagnosis Implemented on FPGA.

Autori: Liang, Yu-Pei Chen, Hao Chung, Ching-Che

Zdroj: Sensors (14248220); Dec2024, Vol. 24 Issue 23, p7831, 18p

Predmety: CONVOLUTIONAL neural networks, DIGITAL electronics, FAULT diagnosis, FEATURE extraction, ROLLER bearings