Results 31 to 40 of about 5,074,594 (286)
Chaotic Characteristics and the Application of SVM in the Tool Wear State Recognition
MATEC Web of Conferences, 2016 Metal cutting process is a nonlinear system to obtain the tool wear state and chaos theory are introduced tool wear and feature extraction of acoustic emission signal analysis and classification of tool wear state and wear prediction based on support ...
Guan Shan, Pang Hongyang, Kang Zhenxing
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A Comparative Study of CNN, LSTM, BiLSTM, and GRU Architectures for Tool Wear Prediction in Milling Processes [PDF]
, 2023 Accurately predicting machine tool wear requires models capable of capturing complex, nonlinear interactions in multivariate time series inputs. Recurrent neural networks (RNNs) are well-suited to this task, owing to their memory mechanisms and capacity ...
Alberto M. Coronado +5 more
core +1 more source
Development of ANN and ANFIS Models for Prediction of Tool Wear in High-Speed Milling
Journal of Manufacturing and Materials ProcessingIn precision machining, tool wear is one of the primary factors affecting machining quality and production efficiency. This study developed intelligent prediction models for tool wear in the high-speed milling (HSM) of AISI 1045 medium-carbon steel by ...
Wei Tai Huang, Yi Cheng Pan
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A geometry independent integrated method to predict erosion wear rates in a slurry environment [PDF]
, 2010 Material wear due to erosion-corrosion in slurry transport equipment is prevalent in process industries such as the oilsands industry. Damage to equipment can cost a typical oilsands industry nearly £200 million annually, along with an associated health
Gnanavelu, Abinesh Balasubramaniam
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SensorsTool wear prediction is of great significance in industrial production. Current tool wear prediction methods mainly rely on the indirect estimation of machine learning, which focuses more on estimating the current tool wear state and lacks effective ...
Zhiming Rong +4 more
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ConvLSTM-Att: An Attention-Based Composite Deep Neural Network for Tool Wear Prediction
Machines, 2023 In order to improve the accuracy of tool wear prediction, an attention-based composite neural network, referred to as the ConvLSTM-Att model (1DCNN-LSTM-Attention), is proposed.
Renwang Li +3 more
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Cutting Tool Wear Prediction in Machining Operations, A Review
, 2022 In the machining process, tool wear is an unavoidable reason for tool failure. Tool wear has an impact on not just tool life but also the quality of the finished product in terms of dimensional accuracy and surface integrity. Tool wear is a significant element in the annual cost of machining.
Soori, Mohsen, Arezoo, Behrooz
openaire +3 more sources
Wear prediction of micro-grinding tool based on GA-BP neural network
Jin'gangshi yu moliao moju gongchengAn intelligent tool wear prediction model has been proposed for the micro-grinding tool, optimized using a genetic algorithm (GA) based BP neural network.
Miao TIAN +4 more
doaj +3 more sources
FEBS Open Bio, EarlyView.The presence of biotin‐binding avidin proteins in fish and their biological significance are poorly characterized. We cataloged fish avidins and demonstrate that they are widely present and evolutionarily conserved. We created avd knockout zebrafish and show that zebavidin is dispensable for development and that resistance of avd knockout embryos in ...
Anni K. Saralahti +5 more
wiley +1 more source
Tool wear monitoring and hole surface quality during CFRP drilling [PDF]
, 2014 The present investigation focuses on the evaluation of tool wear and surface integrity in the context of CFRP cutting. Series of drilling experiments were performed on CFRP plates using cemented carbide solid drills with the aim to investigate ...
RAMIREZ, Christophe +3 more
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