CWレーザ溶接におけるハブラニアンプロットと線形重回帰分析を用いた溶込み深さの予測の比較

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2020/07/01

タイトル(英語): Prediction of Penetration Depth by Laser Welding Using Hablanian Plot Method and Linear Multiple Regression Analysis

著者名: 部谷　学（大阪産業大学工学部），舟山　博人（光産業創成大学院大学），坪井　昭彦（光産業創成大学院大学），田川　正雄（（株）レーザックス）

著者名(英語): Manabu Heya (Faculty of Engineering, Osaka Sangyo University), Hiroto Funayama (The Graduate School for the Creation of New Photonics Industries), Akihiko Tsuboi (The Graduate School for the Creation of New Photonics Industries), Masao Tagawa (Laserx Co., Ltd)

キーワード: SUS304，無次元パラメータ，溶接速度，レーザ出力，スポット直径，近似誤差　　SUS304，dimensionless parameter，welding speed，laser power，spot diameter，fitting difference

要約(英語): In order to prove the validity of prediction of penetration depth using Hablanian plot, we have compared experimentally-obtained penetration depths with those predicted by Hablanian plot and linear multiple regression analysis. The experimental results with ~1200 data points were obtained from bead-on-plate welding tests by the laser job shop. Stainless steel plates and four types of industrial CW lasers were used in these tests. From linear multiple regression analysis, it was found that dominating factors were laser power, welding speed, and spot diameter. On the other hand, we can predict the penetration depth using the 3th-degree polynomial fitting curve (standard curve) expressed by Hablanian plot with two dimensionless parameters. The fitting difference between the standard curve and a data point results in the error of prediction. From Hablanian plot, it showed (1) that this fitting difference was dependent on some factors (such as laser power, welding speed, power density, and penetration depth), (2) that the fitting difference was, respectively, negative and positive in the lower and middle welding speed ranges, and (3) that the penetration depth could be precisely predicted by correcting the fitting difference in welding speed from the standard curve compared to the results predicted by linear multiple regression analysis.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.140 No.7 （2020） 特集：2019年電子・情報・システム部門大会

本誌掲載ページ: 675-681 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/140/7/140_675/_article/-char/ja/