Search
Search Results
-
Random forests based classification of tool wear using vibration signals and wear area estimation from tool image data
In precision manufacturing, tool condition monitoring is critical for improving surface finish, increasing efficiency, and lowering manufacturing...
-
Tool wear classification based on maximal overlap discrete wavelet transform and hybrid deep learning model
A precise tool wear monitoring model is essential for manufacturing to ensure reliability and efficiency. This study aims to analyze and monitor the...
-
NJUST-CCTD: An Image Database for Milling Tool Wear Classification with Deep Learning
Deep learning has gained popularity in the task of tool wear identification recently. As an important application of deep learning, however, there...
-
Research on tool wear classification of milling 508III steel based on chip spectrum feature
In the milling process of high-strength steel, the tool and the chip produce severe contact and friction, resulting in severe tool failure. Tools...
-
Tool wear classification in milling for varied cutting conditions: with emphasis on data pre-processing
Insufficient data is always a challenge for develo** an accurate machine learning or deep learning model in manufacturing processes, especially in...
-
An end-to-end deep learning approach for tool wear condition monitoring
It is important to establish a real-time and accurate tool wear monitoring system for improving machining quality, tool utilization, and reducing...
-
Intelligent milling tool wear estimation based on machine learning algorithms
This study introduces an innovative approach to estimate tool wear in milling operations across diverse operational settings, employing a...
-
Study of an ISSA-XGBoost model for milling tool wear prediction under variable working conditions
A tool wear prediction method based on the improved sparrow search algorithm (ISSA) optimized XGBoost model is proposed to enhance the tool wear...
-
Tool wear status monitoring under laser-ultrasonic compound cutting based on acoustic emission and deep learning
In order to solve the problem of untimely monitoring of tool wear status during laser-ultrasonic compound cutting (LUCC), which leads to the...
-
An experimental study of multi-sensor tool wear monitoring and its application to predictive maintenance
Wear in cutting tools is a critical issue that can lead to reduced product quality, increased production costs, and unexpected downtime. To mitigate...
-
Tool wear condition monitoring method based on relevance vector machine
During the machining process, the tool wear state is closely related to the quality of the workpiece, which will directly affect the performance of...
-
Tool wear intelligent monitoring techniques in cutting: a review
Tool wear is inevitable in cutting process. If tool wear failure is not detected in time, it will lead to abnormal cutting process and affect the...
-
Tool wear monitoring based on an improved convolutional neural network
Tool condition is the key factor affecting the quality and efficiency of precision cutting of parts. As tool wear is inevitable during machining,...
-
Research on tool wear modeling of superalloy based on evolutionary cluster analysis
The utilization of the nickel-based superalloy GH4169 in the manufacturing of heat-resistant parts, such as aero-engine casings, blades and blisks,...
-
A new method for tool wear monitoring based on small sample size
Existing online monitoring methods for tool wear require a large number of samples, which presents difficulties in obtaining tool samples, high...
-
Improved depth residual network based tool wear prediction for cavity milling process
The parts with integrated design technology are widely used in aerospace field because of their advantages such as high strength and high reliability...
-
Neural-Network Prediction of Tool Wear
AbstractThe potential of neural networks in predicting the wear resistance of cutting tools when machining workpieces with standard elements is...
-
Workpiece image-based tool wear classification in blanking processes using deep convolutional neural networks
Blanking processes belong to the most widely used manufacturing techniques due to their economic efficiency. Their economic viability depends to a...
-
Research on reconstruction and high-precision detection of tool wear edges under complex lighting environmental influences
On account of the complex lighting environmental impact of the machine tool, the tool body and wear boundary cannot be accurately extracted, which...
-
Machine Learning as an Enabler for Automated Assistance Systems for the Classification of Tool Wear on Milling Tools
Tool wear and the decision when to replace tools is a universal challenge in the metal cutting industry. While the tool wear state can be accurately...