Improving process monitoring of ultrasonic metal welding using classical machine learning methods and process-informed time series evaluation
出版年份 2022 全文链接
标题
Improving process monitoring of ultrasonic metal welding using classical machine learning methods and process-informed time series evaluation
作者
关键词
Ultrasonic metal welding, Design of experiments, Sensors, Process monitoring, Quality control, Artificial intelligence, Machine learning
出版物
Journal of Manufacturing Processes
Volume 77, Issue -, Pages 54-62
出版商
Elsevier BV
发表日期
2022-03-15
DOI
10.1016/j.jmapro.2022.02.057
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Feature-based quality classification for ultrasonic welding of carbon fiber reinforced polymer through Bayesian regularized neural network
- (2021) Lei Sun et al. JOURNAL OF MANUFACTURING SYSTEMS
- Online tool condition monitoring for ultrasonic metal welding via sensor fusion and machine learning
- (2021) Qasim Nazir et al. Journal of Manufacturing Processes
- Hybrid multi-task learning-based response surface modeling in manufacturing
- (2021) Yuhang Yang et al. JOURNAL OF MANUFACTURING SYSTEMS
- Quality detection and classification for ultrasonic welding of carbon fiber composites using time-series data and neural network methods
- (2021) Lei Sun et al. JOURNAL OF MANUFACTURING SYSTEMS
- Anvil state identification based on acceleration signals in ultrasonic metal welding of lithium batteries
- (2021) Xinhua Shi et al. Journal of Manufacturing Processes
- Quality prediction of ultrasonically welded joints using a hybrid machine learning model
- (2021) Patrick G. Mongan et al. Journal of Manufacturing Processes
- SciPy 1.0: fundamental algorithms for scientific computing in Python
- (2020) Pauli Virtanen et al. NATURE METHODS
- Analysis of the thermo-mechanical mechanism during ultrasonic welding of battery tabs using high-speed image capturing
- (2019) I. Balz et al. Welding in the World
- Ultrasonic spot welding of aluminum-copper dissimilar metals: A study on joint strength by experimentation and machine learning techniques
- (2018) Mantra Prasad Satpathy et al. Journal of Manufacturing Processes
- Effect of the interface characteristics on the joint properties and diffusion mechanisms during ultrasonic metal welding of Al/Cu
- (2017) Jean Pierre Bergmann et al. Welding in the World
- Effect of welding parameters on tensile strength of ultrasonic spot welded joints of aluminum to steel – By experimentation and artificial neural network
- (2017) Dewang Zhao et al. Journal of Manufacturing Processes
- A comparison of machine learning methods for cutting parameters prediction in high speed turning process
- (2016) Zoran Jurkovic et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Online process monitoring with near-zero misdetection for ultrasonic welding of lithium-ion batteries: An integration of univariate and multivariate methods
- (2016) Weihong Guo et al. JOURNAL OF MANUFACTURING SYSTEMS
- In-situ measurement of relative motion during ultrasonic spot welding of aluminum alloy using Photonic Doppler Velocimetry
- (2016) Y. Lu et al. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
- Microstructural and mechanical performance of ultrasonic spot welded Al–Cu joints for various surface conditions
- (2016) Mantra Prasad Satpathy et al. Journal of Manufacturing Processes
- Transient Temperature and Heat Flux Measurement in Ultrasonic Joining of Battery Tabs Using Thin-Film Microsensors
- (2013) Hang Li et al. JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
- Feature selection for manufacturing process monitoring using cross-validation
- (2013) Chenhui Shao et al. JOURNAL OF MANUFACTURING SYSTEMS
- Parametric optimization of ultrasonic metal welding using response surface methodology and genetic algorithm
- (2012) S. Elangovan et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Optimization of ultrasonic welding parameters for copper to copper joints using design of experiments
- (2010) Sooriyamoorthy Elangovan et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
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