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Academic Journal

Acoustic emission monitoring of aspherical lens diffraction in single-point diamond turning process.

Authors : Weng, Chi-Yu¹ (AUTHOR); Shiu, Shiau-Cheng¹ (AUTHOR); Cheng, Yuan-Chieh² (AUTHOR)

Source: International Journal of Advanced Manufacturing Technology. Jan2024, Vol. 130 Issue 1/2, p973-983. 11p.

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Academic Journal

Effects of machining parameters on spectral entropy of acoustic emission signals in the electro erosion.

Authors : Ferreira, Samuel Soares¹ (AUTHOR) ; Maia, Luís Henrique Andrade¹ (AUTHOR); Amorim, Fred Lacerda² (AUTHOR)

Source: International Journal of Advanced Manufacturing Technology. Mar2024, Vol. 131 Issue 1, p289-299. 11p.

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Academic Journal

Tool condition monitoring of diamond-coated burrs with acoustic emission utilising machine learning methods.

Authors : Jessel, Thomas¹ (AUTHOR) ; Byrne, Carl¹ (AUTHOR); Eaton, Mark¹ (AUTHOR)

Source: International Journal of Advanced Manufacturing Technology. Jan2024, Vol. 130 Issue 3/4, p1107-1124. 18p.

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Academic Journal

The use of wavelet transform to evaluate the sensitivity of acoustic emission signals attributes to variation of cutting parameters in milling aluminum alloys.

Authors : Asadi, Reza¹ (AUTHOR); Niknam, Seyed Ali² (AUTHOR) ; Anahid, Mohamad Javad² (AUTHOR)

Source: International Journal of Advanced Manufacturing Technology. Jun2023, Vol. 126 Issue 7/8, p3039-3052. 14p. 4 Diagrams, 7 Charts, 4 Graphs.

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Academic Journal

Acoustic emission for in situ process monitoring of selective laser melting additive manufacturing based on machine learning and improved variational modal decomposition.

Authors : Wang, Haijie¹ (AUTHOR); Li, Bo¹ (AUTHOR) ; Xuan, Fu-Zhen^1,2,3 (AUTHOR)

Source: International Journal of Advanced Manufacturing Technology. Sep2022, Vol. 122 Issue 5/6, p2277-2292. 16p. 2 Color Photographs, 2 Diagrams, 3 Charts, 13

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Academic Journal

The wear detection of mill-grinding tool based on acoustic emission sensor.

Authors : Huang, Wuzhen¹ (AUTHOR); Li, Yuan¹ (AUTHOR) ; Wu, Xian¹ (AUTHOR)

Source: International Journal of Advanced Manufacturing Technology. Feb2023, Vol. 124 Issue 11/12, p4121-4130. 10p.

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Academic Journal

Crack detection in upsetting of aluminum alloy using acoustic emission monitoring technology.

Authors : Ha, Mingyu¹ (AUTHOR); Kim, Ji Hoon² (AUTHOR); Kim, Sangwoo¹ (AUTHOR)

Source: International Journal of Advanced Manufacturing Technology. Feb2023, Vol. 124 Issue 7/8, p2823-2834. 12p.

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Academic Journal

In-process chatter detection in micro-milling using acoustic emission via machine learning classifiers.

Authors : Sestito, Guilherme Serpa¹ (AUTHOR); Venter, Giuliana Sardi² (AUTHOR); Ribeiro, Kandice Suane Barros¹ (AUTHOR)

Source: International Journal of Advanced Manufacturing Technology. Jun2022, Vol. 120 Issue 11/12, p7293-7303. 11p.

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Academic Journal

Tool wear monitoring based on the combination of machine vision and acoustic emission.

Authors : Chen, Meiliang¹ (AUTHOR); Li, Mengdan¹ (AUTHOR) ; Zhao, Linfeng¹ (AUTHOR)

Source: International Journal of Advanced Manufacturing Technology. Apr2023, Vol. 125 Issue 7/8, p3881-3897. 17p.

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Academic Journal

Sensitivity of acoustic emission signals features to cutting parameters in time domain: case of milling aeronautical aluminium alloys.

Authors : Anahid, Mohamad Javad¹ (AUTHOR); Niknam, Seyed Ali¹ (AUTHOR)

Source: International Journal of Advanced Manufacturing Technology. May2024, Vol. 132 Issue 1/2, p265-275. 11p.

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Acoustic emission monitoring of aspherical lens diffraction in single-point diamond turning process.

Effects of machining parameters on spectral entropy of acoustic emission signals in the electro erosion.

Tool condition monitoring of diamond-coated burrs with acoustic emission utilising machine learning methods.

The use of wavelet transform to evaluate the sensitivity of acoustic emission signals attributes to variation of cutting parameters in milling aluminum alloys.

Acoustic emission for in situ process monitoring of selective laser melting additive manufacturing based on machine learning and improved variational modal decomposition.

The wear detection of mill-grinding tool based on acoustic emission sensor.

Crack detection in upsetting of aluminum alloy using acoustic emission monitoring technology.

In-process chatter detection in micro-milling using acoustic emission via machine learning classifiers.

Tool wear monitoring based on the combination of machine vision and acoustic emission.

Sensitivity of acoustic emission signals features to cutting parameters in time domain: case of milling aeronautical aluminium alloys.

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