Gearbox localized fault detection based on meshing frequency modulation analysis
Gearbox fault detection commonly relies on comparing sideband frequencies beside the
meshing frequency of gear, and its harmonics of higher orders in frequency domain between …
meshing frequency of gear, and its harmonics of higher orders in frequency domain between …
Correlation analysis of vibration signal frequency with tool wear during the milling process on martensitic stainless steel material
Martensitic AISI 420 stainless steel is favored for hardness and strength due to the hard
phase of martensite and chromium carbide. However, machining this martensitic steel is …
phase of martensite and chromium carbide. However, machining this martensitic steel is …
Naïve Bayes algorithm for timely fault diagnosis in helical gear transmissions using vibration signal analysis
AG Abdulameer, AS Hammood… - International Journal on …, 2024 - Springer
Vibration signal analysis assumes a critical role in the diagnosis of faults within helical gear
transmissions, facilitating early detection and mitigation of potential failures. This paper is …
transmissions, facilitating early detection and mitigation of potential failures. This paper is …
Multivariate multi-scale cross-fuzzy entropy and SSA-SVM-based fault diagnosis method of gearbox
Fuzzy entropy (FuzzyEn) is widely recognized as a powerful tool for analyzing nonlinear
dynamics and measuring the complexity of time series data. It has been utilized as an …
dynamics and measuring the complexity of time series data. It has been utilized as an …
An envelope time synchronous averaging for wind turbine gearbox fault diagnosis
Purpose Vibration-based condition monitoring techniques are widely used for diagnosing
faults in rotating machines. These techniques are implemented in the time domain, the …
faults in rotating machines. These techniques are implemented in the time domain, the …
[HTML][HTML] Gearbox fault identification using auto-encoder without training data from the damaged machine
Deep learning methods work well in machine diagnostics where operating conditions affect
diagnostic signals. Classifiers are often used for fault identification, but these methods …
diagnostic signals. Classifiers are often used for fault identification, but these methods …
Optimizing Failure Diagnosis in Helical Gear Transmissions with Stochastic Gradient Descent Logistic Regression using Vibration Signal Analysis for Timely Detection
AS Hammood, AG Taki, NS Ibrahim… - Journal of Failure …, 2024 - Springer
Vibration analysis plays a pivotal role in the initial identification and reduction of defects in
helical gear transmissions, underscoring the significance of precise fault detection. This …
helical gear transmissions, underscoring the significance of precise fault detection. This …
Enhancing Turbine Blade Manufacturing through MEMS-Based Milling Monitoring
Manufacturing steam turbine blades with intricate shapes poses a substantial challenge.
These blades significantly impact turbine efficiency, reliability, and productivity. Their precise …
These blades significantly impact turbine efficiency, reliability, and productivity. Their precise …
A gearbox fault diagnosis algorithm based on convolutional neural network and fusion coordinate attention mechanism
H Ni, L Zhang, C Wu - International Conference on Computer …, 2024 - spiedigitallibrary.org
In response to the challenges of low accuracy, difficult feature extraction, and poor real-time
performance in traditional gearbox fault diagnosis algorithms, this paper proposes a …
performance in traditional gearbox fault diagnosis algorithms, this paper proposes a …