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An Improved Fault Diagnosis Method of Rolling Bearings Based on Multi-Scale Attention CNN
Rolling bearing fault diagnosis based on convolutional neural network is greatly effective for bearing maintenance, and it is of great significance...
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Rolling Bearing Fault Diagnosis Based on Multi-source Information Fusion
Addressing the issues that single-source information cannot comprehensively reflect the operational status of equipment, redundant features fail to...
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Research on Bearing Variable Condition Fault Diagnosis Based on RDADNN
Due to the influence of working conditions, the data distribution of bearings is challenging to maintain consistency in practical engineering, which...
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Fault Diagnosis of Rolling Element Bearing with Operationally Developed Defects Using Various Convolutional Neural Networks
Rolling element bearings are critical building blocks of any rotating machine. Achieving effective and precise fault diagnosis through various neural...
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Bearing Fault Diagnosis Based on VMD and Improved CNN
The vibration signal of the bearing from a train is non-stationary, nonlinear, and mixed with noise, which makes it challenging to extract the fault...
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Fault Diagnosis for Marine Two-Stroke Diesel Engine Based on CEEMDAN-Swin Transformer Algorithm
The state information of marine diesel engines is strongly time-varying under the interference of multiple internal and external excitations. Fault...
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Fault Diagnosis of Rolling Bearings Based on Spectral Kurtosis Graph and LFMB Network
AbstractRolling bearings usually operate under a time-varying speed. However, most technologies for diagnosing bearing faults are based on a constant...
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A Fault Diagnosis Method for Rolling Bearing Combining Signal Difference and Coarse Graining
To precisely determine the type of bearing fault, the paper has proposed the solution by combining first-order difference of signals and...
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Characteristics of Common-Mode Voltage Offset in Small Sectors and OC Fault Diagnosis Method for Three-Level Inverter
T-type three-level inverters (T 2 3LIs) are widely used in the electric drive system of new energy vehicles. However, the open-circuit (OC) faults of...
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A Novel Lightweight Unsupervised Multi-branch Domain Adaptation Network for Bearing Fault Diagnosis Under Cross-Domain Conditions
Cross-domain fault diagnosis methods have been widely developed to solve domain-shift diagnostic tasks with data distribution discrepancies. However,...
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Investigation of Rolling Bearing Weak Fault Diagnosis Based on CNN with Two-Dimensional Image
AbstractIn this paper, we choose convolutional neural network (CNN) as the method to diagnosis weak fault of rolling bearings. In order to improve...
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An Intelligent Fault Diagnosis Method of Rolling Bearings Based on Short-Time Fourier Transform and Convolutional Neural Network
The rolling bearing is the key component of rotating machinery, and fault diagnosis for rolling bearings can ensure the safe operation of rotating...
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Deep Transfer Learning for Bearing Fault Diagnosis using CWT Time–Frequency Images and Convolutional Neural Networks
Deep transfer learning has evolved into a powerful method for defect identification, particularly in mechanical systems that lack sufficient training...
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Modeling and Diagnosis of Induction Machines Operating under Open-Phase Fault
AbstractThis paper presents a new approach for the modeling and diagnosis of the induction machines (IM) operation under open-phase fault. This fault...
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Induction Motor Fault Diagnosis with Local Ternary Pattern and AI Approaches
Owing to the induction machine's widespread use across most industries, engine failure will be quite expensive. To address this problem, numerous...
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Integration of Discrete Wavelet and Fast Fourier Transforms for Quadcopter Fault Diagnosis
Due to the extensive use of Unmanned Aerial Vehicles (UAVs) and the co-evolution of current technology, a key introduction to fault detection has...
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Time–Frequency Analysis for Planetary Gearbox Fault Diagnosis Based on Improved U-Net++
Planetary gearbox plays an important role in many industrial fields and is also a vulnerable component. It is of great significance to develop the...
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Wind Turbine Gearbox Bearing Fault Diagnosis Method Based on ICEEMDAN and Flexible Wavelet Threshold
Extracting eigenvalues from vibration pulse signals is a crucial aspect of diagnosing faults in wind turbine gearbox bearings. However, the presence...
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Unknown Bearing Fault Recognition in Strong Noise Background
AbstractThe fault pattern of rolling bearing usually is unknown in heavy noise background, which means the bearing has two possibilities of single...
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A Parameter-Adaptive VME Method Based on Particle Swarm Optimization for Bearing Fault Diagnosis
In the decomposition process of variational mode extraction (VME), it is hard to choose the approximate center frequency and the weighting...
