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Appending-inspired multivariate time series association fusion for tool condition monitoring
In intelligent machining, tool condition monitoring (TCM) is crucial to improving tool efficiency and machining accuracy, which requires the...
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Tool wear condition monitoring across machining processes based on feature transfer by deep adversarial domain confusion network
Deep learning-based data-driven methods have been successfully developed in tool wear condition monitoring (TWCM), relying on the massive available...
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A novel approach for tool condition monitoring based on transfer learning of deep neural networks using time–frequency images
Traditional tool condition monitoring methods developed in an ideal environment are not universal in multiple working conditions considering...
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A novel approach of tool condition monitoring in sustainable machining of Ni alloy with transfer learning models
Cutting tool condition is crucial in metal cutting. In-process tool failures significantly influences the surface roughness, power consumption, and...
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Artificial intelligence systems for tool condition monitoring in machining: analysis and critical review
The wear of cutting tools, cutting force determination, surface roughness variations and other machining responses are of keen interest to latest...
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An imbalanced data learning approach for tool wear monitoring based on data augmentation
During cutting operations, tool condition monitoring (TCM) is essential for maintaining safety and cost optimization, especially in the accelerated...
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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...
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Partitioned abrasive belt condition monitoring based on a unified coefficient and image processing
Abrasive belt condition (BC) monitoring is significant for achieving profile finishing precision and quality in grinding of difficult-to-machine...
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Deep learning based condition monitoring of road traffic for enhanced transportation routing
The efficient management of road traffic is crucial for enhancing transportation routing and improving overall traffic flow. However, the...
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A Generative AI approach to improve in-situ vision tool wear monitoring with scarce data
Most aerospace turbine casings are mechanised using a vertical lathe. This paper presents a tool wear monitoring system using computer vision that...
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An edge-based algorithm for tool wear monitoring in repetitive milling processes
In the era of Industry 4.0, cloud computing has attracted a lot of attention from industrial organizations in realizing smart manufacturing. However,...
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Tool wear classification in precision machining using distance metrics and unsupervised machine learning
This article reports an unsupervised approach for estimation of the tool condition in precision machining processes. Three campaigns of...
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Tool wear condition monitoring based on a two-layer angle kernel extreme learning machine using sound sensor for milling process
Tool condition monitoring (TCM) in numerical control machines plays an essential role in ensuring high manufacturing quality. The TCM process is...
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Machining accuracy prediction and adaptive compensation method of CNC machine tool under absence of machining process sensing
Spindle axial error is the main factor restricting machining accuracy improvements of machine tools. Monitoring the machining process of computer...
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Decision-Making in Structural Health Monitoring and Predictive Maintenance of Wind Turbines
The fourth stage of the life cycle of a wind farm refers to operation and maintenance activities. This stage includes routine maintenance and repairs...
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Industrial system working condition identification using operation-adjusted hidden Markov model
In this article, the problem of industrial system working condition identification in the context of complex operation modes is considered. The...
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Circular Economy Self-assessment Tool for Hotels
The hotel industry is immersed in a debate about the negative externalities derived from its activity, which makes the effective development of the...
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Evaluation of data augmentation and loss functions in semantic image segmentation for drilling tool wear detection
Tool wear monitoring is crucial for quality control and cost reduction in manufacturing processes, of which drilling applications are one example....
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Identification of cutting tool wear condition in turning using self-organizing map trained with imbalanced data
One of the most important parameters in machining process is tool wear. Thus, monitoring the wear of cutting tools is essential to ensure product...
