RTSMFFDE-HKRR: a fault diagnosis method for train bearing in noise environment
The bearings have been exposed to a noisy environment for an extended period, making it
challenging to identify fault characteristics accurately and resulting in low accuracy. In this …
challenging to identify fault characteristics accurately and resulting in low accuracy. In this …
Leveraging artificial intelligence for real-time indirect tool condition monitoring: From theoretical and technological progress to industrial applications
Tool condition monitoring (TCM) during mechanical cutting is critical for maximising the
utilisation of cutting tools and minimising the risk of equipment damage and personnel …
utilisation of cutting tools and minimising the risk of equipment damage and personnel …
ACWGAN-GP for milling tool breakage monitoring with imbalanced data
Tool breakage monitoring (TBM) during milling operations is crucial for ensuring workpiece
quality and minimizing economic losses. Under the premise of sufficient training data with a …
quality and minimizing economic losses. Under the premise of sufficient training data with a …
An interpretable anti-noise convolutional neural network for online chatter detection in thin-walled parts milling
Chatter is a notoriously unstable phenomenon that can adversely affect both surface quality
and machining efficiency. To achieve high-performance machining, the development of …
and machining efficiency. To achieve high-performance machining, the development of …
A tool wear condition monitoring method for non-specific sensing signals
Real-time and accurate monitoring of tool wear conditions is crucial to achieving double
optimization of production cost and product quality. However, the differences in the …
optimization of production cost and product quality. However, the differences in the …
Ex-ante market power evaluation and mitigation in day-ahead electricity market considering market maturity levels
Market power is detrimental to the fair operation of the spot market, thus many market power
evaluation and mitigation approaches have been put forward. However, due to the market …
evaluation and mitigation approaches have been put forward. However, due to the market …
Use of machine learning models in condition monitoring of abrasive belt in robotic arm grinding process
Although the aspects that affect the performance and the deterioration of abrasive belt
grinding are known, wear prediction of abrasive belts in the robotic arm grinding process is …
grinding are known, wear prediction of abrasive belts in the robotic arm grinding process is …
How to mine the abnormal information of power transformers: An efficient tool for quantifying the fault characteristics via multi-vibration signals
The new power system puts forward higher requirements for the reliability of power
equipment. Mining the intrinsic information of equipment operation from massive data is the …
equipment. Mining the intrinsic information of equipment operation from massive data is the …
A novel cross-domain tool breakage monitoring method based on locality preserving joint transfer with intra-class compactness
Abstract—Tool breakage monitoring (TBM) during milling is vital for improving production
efficiency and ensuring product quality. The tool breakage monitoring model under the …
efficiency and ensuring product quality. The tool breakage monitoring model under the …
Tool breakage monitoring driven by the real-time predicted spindle cutting torque using spindle servo signals
Monitoring tool breakage during computer numerical control machining is essential to
ensure machining quality and equipment safety. In consideration of the low cost in long-term …
ensure machining quality and equipment safety. In consideration of the low cost in long-term …