2024
DOI: 10.1088/1361-6501/ad45f4
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Tool wear monitoring based on scSE-ResNet-50-TSCNN model integrating machine vision and force signals

Peng Nie,
Yongxi Guo,
Bixuan Lou
et al.

Abstract: In the realm of mechanical machining, tool wear is an unavoidable phenomenon. Monitoring the condition of tool wear is crucial for enhancing machining quality and advancing automation in the manufacturing process. This paper investigates an innovative approach to tool wear monitoring that integrates machine vision with force signal analysis. It relies on a deep residual two-stream convolutional model optimized with the scSE(Concurrent Spatial and Channel Squeeze and Excitation) attention mechanism (scSE-ResNet… Show more

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Cited by 3 publications
(1 citation statement)
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“…Previous studies have found that wavelet transform can effectively utilize hyperspectral reflectance data by preserving both global and local spectral information, facilitating a better analysis and interpretation of the data. Additionally, wavelet transform exhibits remarkable denoising capabilities as it can separate noise from signals at different scales or frequencies, effectively reducing the distortions caused by noise to enhance the accuracy of hyperspectral reflectance [19]. Liu et al [20] used hyperspectral data, coupled continuous wavelet transform with the RF method, to construct a model for estimating the nitrogen content in summer corn, achieving remote sensing estimation of the nitrogen content and improving the modeling accuracy.…”
Section: Introductionmentioning
confidence: 99%
“…Previous studies have found that wavelet transform can effectively utilize hyperspectral reflectance data by preserving both global and local spectral information, facilitating a better analysis and interpretation of the data. Additionally, wavelet transform exhibits remarkable denoising capabilities as it can separate noise from signals at different scales or frequencies, effectively reducing the distortions caused by noise to enhance the accuracy of hyperspectral reflectance [19]. Liu et al [20] used hyperspectral data, coupled continuous wavelet transform with the RF method, to construct a model for estimating the nitrogen content in summer corn, achieving remote sensing estimation of the nitrogen content and improving the modeling accuracy.…”
Section: Introductionmentioning
confidence: 99%