Page 138 - 无损检测2024年第九期

颜江涛，等：

金属增材制造检测技术与质量控制研究进展

Keyhole threshold and morphology in laser melting laser ultrasonic imaging method for online inspection of
revealed by ultrahigh-speed X-ray imaging[J]. Science， metal additive manufacturing[J]. Optics and Lasers in
2019，363（6429）：849-852． Engineering，2023，160：107244．
[38] ZHAO C，PARAB N D，LI X X，et al．Critical [48] 郭政亚，熊振华. 金属增材制造缺陷检测技术[J]. 哈尔
instability at moving keyhole tip generates porosity in 滨工业大学学报，2020，52（5）：49-57．
laser melting[J]. Science，2020，370（6520）：1080-1086． [49] PANDIYAN V，MASINELLI G，CLAIRE N，et al．
[39] CHEN Y H，CLARK S J，SINCLAIR L，et al． Deep learning-based monitoring of laser powder
Synchrotron X-ray imaging of directed energy bed fusion process on variable time-scales using
deposition additive manufacturing of titanium alloy Ti- heterogeneous sensing and operando X-ray radiography
6242[J]. Additive Manufacturing，2021，41：101969． guidance[J]. Additive Manufacturing，2022，58：103007．
[40] ESCHNER N，WEISER L，HÄFNER B，et al． [50] LI J C，ZHANG X G，ZHOU Q，et al．A feature-level
Classification of specimen density in Laser Powder Bed multi-sensor fusion approach for in situ quality monitoring
Fusion （L-PBF） using in-process structure-borne acoustic of selective laser melting[J]. Journal of Manufacturing
process emissions[J]. Additive Manufacturing，2020，34： Processes，2022，84：913-926．
101324． [51] ZOU Z Y，ZHANG K，ZHU Z G，et al．Multi-sensor
[41] DRISSI-DAOUDI R，PANDIYAN V，LOGÉ R，et al． monitoring of powder melting states via melt pool
Differentiation of materials and laser powder bed fusion optical emission signals during laser-based powder bed
processing regimes from airborne acoustic emission fusion[J]. Optics Laser Technology，2024，169：109880．
combined with machine learning[J]. Virtual and Physical [52] LI Z X，CHANG B H，WANG K M，et al．Closed-loop
Prototyping，2022，17（2）：181-204． control of alternating dual-electron beams for molten pool
[42] YE D S，HONG G S，ZHANG Y J，et al．Defect regulation during in situ additive manufacturing[J]. Journal
detection in selective laser melting technology by acoustic of Materials Processing Technology，2023，319：118087．
signals with deep belief networks[J]. The International [53] XIONG J，YIN Z Q，ZHANG W H．Closed-loop
Journal of Advanced Manufacturing Technology，2018， control of variable layer width for thin-walled parts
96（5）：2791-2801． in wire and arc additive manufacturing[J]. Journal of
[43] KONONENKO D Y，NIKONOVA V，SELEZNEV Materials Processing Technology，2016，233：100-106．
M，et al．An in situ crack detection approach in additive [54] DIAO Z W，YANG F，CHEN L，et al．Effects of
manufacturing based on acoustic emission and machine deposition height stability of CuCrZr alloy based on arc
learning[J]. Additive Manufacturing Letters，2023，5： voltage sensing：nfluence of materials and energy saving
i
100130． on wire arc additive manufacturing[J]. Journal of Cleaner
[44] RAFFESTIN M，DOMASHENKOV A，BERTRAND Production，2023，425：138665．
P，et al．Ultrasonic diagnostic for in situ control in metal [55] XIA C Y，PAN Z X，ZHANG S Y，et al．Model
additive manufacturing[J]. Measurement，2023，206： predictive control of layer width in wire arc additive
112244． manufacturing[J]. Journal of Manufacturing Processes，
[45] RIEDER H，SPIES M，BAMBERG J，et al．On- and 2020，58：179-186．
offline ultrasonic characterization of components built [56] REZAEIFAR H，ELBESTAWI M．Porosity formation
by SLM additive manufacturing[C]//AIP Conference mitigation in laser powder bed fusion process using a
Proceedings．Minneapolis：AIP Publishing LLC，2016： control approach[J]. Optics & Laser Technology，2022，
130002． 147：107611．
[46] 白雪，马健，许万卫，等. 基于激光超声的金属增材制 [57] WANG R X，STANDFIELD B，DOU C R，et al．
造在线检测技术研究[J]. 航空制造技术，2022，65（20）： Real-time process monitoring and closed-loop control
70-82． on laser power via a customized laser powder bed fusion
[47] CHEN Y，JIANG L Z，PENG Y C，et al．Ultra-fast platform[J]. Additive Manufacturing，2023，66：103449．

100
2024 年 第 46 卷 第 9 期
无损检测