Exploring the essence of compound fault diagnosis: A novel multi-label domain adaptation method and its application to bearings [PDF]
Heliyon, 2023 Compound fault diagnosis in essence is a fundamental but difficult problem to be solved. The separation and extraction of compound fault features remain great challenges in industrial applications due to the lack of labeled fault data.
Liuxing Chu +5 more
doaj +2 more sources
Compound Fault Diagnosis of Aero-Engine Rolling Element Bearing Based on CCA Blind Extraction [PDF]
IEEE Access, 2021 Fault diagnosis of aero-engine spindle bearing is a critical technique of engine prognostics and health management. As is known that the diagnosis of compound fault of aero-engine spindle bearing is very difficult and easily affected by other vibration ...
Wei-Tao Zhang +3 more
doaj +2 more sources
Multi–Output Classification Based on Convolutional Neural Network Model for Untrained Compound Fault Diagnosis of Rotor Systems with Non–Contact Sensors [PDF]
Sensors, 2023 Fault diagnosis is important in rotor systems because severe damage can occur during the operation of systems under harsh conditions. The advancements in machine learning and deep learning have led to enhanced performance of classification. Two important
Taehwan Son, Dongwoo Hong, Byeongil Kim
doaj +2 more sources
Compound Fault Diagnosis of Wind Turbine Gearbox via Modified Signal Quality Coefficient and Versatile Residual Shrinkage Network [PDF]
SensorsWind turbine gearbox fault diagnosis is critical to guarantee working efficiency and operational safety. However, the current diagnostic methods face enormous restrictions in handling nonlinear noise signals and intricate compound fault patterns. Herein,
Weixiong Jiang +4 more
doaj +2 more sources
Compound Fault Diagnosis of Planetary Gearbox Based on Improved LTSS-BoW Model and Capsule Network [PDF]
SensorsThe identification of compound fault components of a planetary gearbox is especially important for keeping the mechanical equipment working safely. However, the recognition performance of existing deep learning-based methods is limited by insufficient ...
Guoyan Li +5 more
doaj +2 more sources
Compound Fault Diagnosis of Rolling Bearing Based on Singular Negentropy Difference Spectrum and Integrated Fast Spectral Correlation [PDF]
Entropy, 2020 Compound fault diagnosis is challenging due to the complexity, diversity and non-stationary characteristics of mechanical complex faults. In this paper, a novel compound fault separation method based on singular negentropy difference spectrum (SNDS) and ...
Guiji Tang, Tian Tian
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Intelligent diagnosis of rolling bearing compound faults based on device state dictionary set sparse decomposition feature extraction–hidden Markov model [PDF]
Advances in Mechanical Engineering, 2020 Identification of rolling bearing fault patterns, especially for the compound faults, has attracted notable attention and is still a challenge in fault diagnosis.
HongChao Wang, WenLiao Du
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Adaptive Label Refinement Network for Domain Generalization in Compound Fault Diagnosis. [PDF]
Sensors (Basel)Domain generalization (DG) aims to develop models that perform robustly on unseen target domains, a critical but challenging objective for real-world fault diagnosis. The challenge is further complicated in compound fault diagnosis, where the rigidity of hard labels and the simplicity of label smoothing under-represent inter-class relations and ...
Du Q, Yao J, Yang J, Tu F, Yang S.
europepmc +4 more sources
Diagnosis of Compound Fault Using Sparsity Promoted-Based Sparse Component Analysis [PDF]
Sensors, 2017 Compound faults often occur in rotating machinery, which increases the difficulty of fault diagnosis. In this case, blind source separation, which usually includes independent component analysis (ICA) and sparse component analysis (SCA), was proposed to ...
Yansong Hao +4 more
doaj +2 more sources
Compound Fault Diagnosis of Rolling Bearing Based on ALIF-KELM [PDF]
Mathematical Problems in Engineering, 2021 Aiming at the shortcomings of difficult classification of rolling bearing compound faults and low recognition accuracy, a composite fault diagnosis method of rolling bearing combined with ALIF and KELM is proposed. First, the basic concepts of ALIF and KELM are introduced, and then ALIF is used to decompose the sample data of vibration signals of ...
Jie Ma +3 more
openalex +2 more sources