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Multiple sensing-driven feature extraction and defect detection

Record Type:	Electronic resources : Monograph/item
Title/Author:	Multiple sensing-driven feature extraction and defect detectionby Zhifen Zhang, Guangrui Wen, Wenjing Ren.
Author:	Zhang, Zhifen.
other author:	Wen, Guangrui.
Published:	Singapore :Springer Nature Singapore :2025.
Description:	xi, 169 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Materials.
Online resource:	https://doi.org/10.1007/978-981-96-4808-5
ISBN:	9789819648085$q(electronic bk.)

Multiple sensing-driven feature extraction and defect detection
Zhang, Zhifen.

Multiple sensing-driven feature extraction and defect detection[electronic resource] /by Zhifen Zhang, Guangrui Wen, Wenjing Ren. - Singapore :Springer Nature Singapore :2025. - xi, 169 p. :ill., digital ;24 cm.

1. Introduction -- 2. Arc sound and its application on penetration detection for GTAW -- 3 Optical spectroscopy-based inner porosity monitoring for GTAW -- 4. Optical spectroscopy-based multiple defects detection for GTAW -- 5. Optical spectroscopy-based real-time seam strength prediction for laser beam welding (LBW) -- 6. Optical spectroscopy-based intelligent defect detections for laser AM -- 7. Summary and Conclusions.

This book reports the recent study results in applying online signals and artificial intelligence for welding and laser additive manufacturing (AM). It provides insights on the fundament of quality monitoring and intelligent defect detections for welding and laser AM using arc sound and plasma spectral signals collected during the manufacturing processes. Analyzing respectively from a global and local perspective establishes a knowledge base of features characterizing welding statuses. Researchers, scientists, and engineers in intelligent welding and laser AM can benefit from the book. As such, this book provides valuable knowledge, valuable methods, and practical algorithms that can be considered in real-time defect detection for welding and laser AM.

ISBN: 9789819648085$q(electronic bk.)

Standard No.: 10.1007/978-981-96-4808-5doiSubjects--Topical Terms:

203115
Materials.

LC Class. No.: TA403

Dewey Class. No.: 620.11

Multiple sensing-driven feature extraction and defect detection
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505 0 $a 1. Introduction -- 2. Arc sound and its application on penetration detection for GTAW -- 3 Optical spectroscopy-based inner porosity monitoring for GTAW -- 4. Optical spectroscopy-based multiple defects detection for GTAW -- 5. Optical spectroscopy-based real-time seam strength prediction for laser beam welding (LBW) -- 6. Optical spectroscopy-based intelligent defect detections for laser AM -- 7. Summary and Conclusions.
520 $a This book reports the recent study results in applying online signals and artificial intelligence for welding and laser additive manufacturing (AM). It provides insights on the fundament of quality monitoring and intelligent defect detections for welding and laser AM using arc sound and plasma spectral signals collected during the manufacturing processes. Analyzing respectively from a global and local perspective establishes a knowledge base of features characterizing welding statuses. Researchers, scientists, and engineers in intelligent welding and laser AM can benefit from the book. As such, this book provides valuable knowledge, valuable methods, and practical algorithms that can be considered in real-time defect detection for welding and laser AM.
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