Compound Fault Diagnosis of a Wind Turbine Gearbox Based on MOMEDA and Parallel Parameter Optimized Resonant Sparse Decomposition [PDF]
Sensors, 2022 Wind turbines usually operate in harsh environments. The gearbox, the key component of the transmission chain in wind turbines, can easily be affected by multiple factors during the operation process and develop compound faults. Different types of faults
Yang Feng +3 more
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Blind Fault Extraction of Rolling-Bearing Compound Fault Based on Improved Morphological Filtering and Sparse Component Analysis. [PDF]
Sensors (Basel), 2022 In order to effectively separate and extract bearing composite faults, in view of the non-linearity, strong interference and unknown number of fault source signals of the measured fault signals, a composite fault-diagnosis blind extraction method based on improved morphological filtering of sinC function (SMF), density peak clustering (DPC) and ...
Xie W, Zhou J, Liu T.
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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
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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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A New Compound Fault Feature Extraction Method Based on Multipoint Kurtosis and Variational Mode Decomposition [PDF]
Entropy, 2018 Due to the weak entropy of the vibration signal in the strong noise environment, it is very difficult to extract compound fault features. EMD (Empirical Mode Decomposition), EEMD (Ensemble Empirical Mode Decomposition) and LMD (Local Mean Decomposition ...
Wenan Cai +3 more
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Diagnosis of Compound Fault Using Sparsity Promoted-Based Sparse Component Analysis. [PDF]
Sensors (Basel), 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 separate mixed signals.
Hao Y, Song L, Ke Y, Wang H, Chen P.
europepmc +5 more sources
Semi-Supervised Informer for the Compound Fault Diagnosis of Industrial Robots [PDF]
Sensors (Basel)The increasing deployment of industrial robots in manufacturing requires accurate fault diagnosis. Online monitoring data typically consist of a large volume of unlabeled data and a small quantity of labeled data. Conventional intelligent diagnosis methods heavily rely on supervised learning with abundant labeled data. To address this issue, this paper
Chuanhua Deng +4 more
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Composite Fault Prediction of Bearing Based on Cascaded Long Short Term Memory Neural Network
Kongzhi Yu Xinxi Jishu, 2022 At present, resonance demodulation and data envelopment analysis, etc are usually used for health evaluation and remaining life prediction of bearings, but there are some problems such as difficulty in extracting health degree, single fault prediction ...
JIANG Xuyao +5 more
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Hybrid Adaptive Fault-Tolerant Control for Compound Faults of Hypersonic Vehicle
IEEE Access, 2021 This study investigates the hybrid fault-tolerant control (FTC) for hypersonic flight vehicles (HFVs) under the rudder structure fault (RSF) and rudder angle deviation fault (RADF). The nonlinear equations of the model are linearised by fuzzy logic, the external nonlinear disturbance is approximated by radial basis functions, which transforms the ...
Kai-Yu Hu, Wenhao Li, Zian Cheng
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Compound Fault Feature Extraction of Wind Power Gearbox Based on DRS and Improved Autogram
Zhongguo dianli, 2023 Compound fault feature extraction is the key to analyzing the root cause of wind power gearbox faults. A compound fault feature extraction method based on DRS and improved Autogram is proposed.
Haifei MA +4 more
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