Key technologies of intelligentized welding manufacturing : welding arc acoustic sensing and monitoring technology / / Na Lv, Shanben Chen

• Autore: Lv Na
• Pubblicazione: Singapore, : Springer, 2020
• Descrizione fisica: 1 online resource (129 pages)
• Disciplina: 671.5/2
• Soggetto topico: Welding; Welding industry
• Altri autori: ChenShanben
• Note generali: 8 Microphone Array Technology in Welding Dynamic Process Monitoring
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Intro -- Acknowledgements -- Contents -- 1 Multi-source Information of Arc Welding Dynamic Process -- 1.1 Introduction -- 1.2 Acoustic Signal of Welding Dynamic Process -- 1.3 Classification of Welding Acoustic Signal -- 1.4 Feature and Application Value of Arc Sound Signal -- 1.5 Influencing Factor of Arc Sound Signal -- 1.6 Microphone Array Measurement of Arc Sound -- 2 Acoustic Mechanism and Arc Sound Source Modeling for GTAW Welding -- 2.1 Basic Arc Sound Source Model -- 2.1.1 Weld Pool Oscillation Model of Arc Sound -- 2.1.2 Analysis and Validation of Sound Source for GTAW ; 2.1.3 Influence of Welding Parameters on Arc Sound Signal During Dynamic Welding -- 3 Feature Extraction and Analysis of Arc Sound Signal with Dynamic Welding Process -- 3.1 Welding Operation System Setup -- 3.2 Arc Sound Signal Preprocessing Method -- 3.2.1 Removal of DC Component -- 3.2.2 Noise-Removal Process -- 3.2.3 Region of Interest (ROI) Selected -- 3.2.4 Window Function Addition -- 3.2.5 Analysis of Arc Sound Signal in Short Time Domain -- 3.2.6 Frequency-Domain Analysis of Arc Sound Signal -- 3.2.7 Time-Frequency Analysis of Arc Sound Signal ; 3.2.8 Relationship Between Sound Feature and Penetration of Weld Pool -- 4 Channel Generation Mechanism and Modeling for Arc Sound Signal During GTAW -- 4.1 Generation Mechanism of Arc Sound Channel -- 4.2 Arc Sound Channel Modeling Based on Cepstrum Coefficient -- 4.2.1 A Mathematical Model Based on Cepstrum Analysis -- 4.2.2 Cepstrum Coefficients Model of the Arc Sound Signal -- 4.3 Arc Sound Channel Modeling Based on Linear Predictive Analysis -- 5 Prediction Model Establishment Based on Arc Sound Feature Array -- 5.1 Welding Penetration Recognition Analysis Using Arc Sound Signal ; 5.2 Prediction Model Using BPAdaBoost Neural Network for GATW Welding -- 5.3 Classification Model Using Hidden Markov Model -- 5.3.1 Wavelet Analysis -- 5.3.2 Modeling Based on Hidden Markov Model -- 5.3.3 Comparing with Traditional Model -- 6 Relationship Modeling Between Weld Pool Collapse and Welding Penetration Based on Analyzing Arc Sound Features -- 6.1 Welding Experimental Design and Arc Sound Signal Collection -- 6.2 Processing of Arc Sound Signal for Weld Pool Collapse -- 6.2.1 De-DC Component Processing -- 6.2.2 Denoising ; 6.3 Accuracy Verification Test for Prediction Model Based on Arc Sound Feature -- 6.3.1 The Piecewise Linear Fitting for Arc Length -- 6.3.2 Validation of Arc Length Prediction Model -- 6.4 Prediction Experiment of Welding Pool Collapse -- 7 Real-Time Control of Welding Penetration via Arc Sound Signal for GTAW Welding -- 7.1 Design of Real-Time Processing Software for Arc Sound Signal During GTAW Welding -- 7.2 Arc Height Tracking Control Experiment via Arc Sound Signal of GTAW Welding -- 7.3 Welding Penetration Control Experiment via Arc Sound Signal of GTAW Welding
• Sommario/riassunto: This book gives a full picture of the welding quality real-time control via arc sound information. This book presents all aspects of acoustic signal research during the welding dynamic process from the last five years. It also offers valuable and practical strategies for achieving the real-time control of welding quality via arc sound signal. Researchers, scientists, and engineers who have interests in intelligent welding could acquire intensive view and experiment procedures from the book.
• Titolo autorizzato: Key technologies of intelligentized welding manufacturing
• ISBN: 981-15-2002-X
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910483952203321
• Lo trovi qui: Univ. Federico II