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Defect detection in laser powder deposition components by laser thermography and laser ultrasonic inspections

机译:通过激光热成像和激光超声检查发现激光粉末沉积成分中的缺陷

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摘要

Laser Powder Deposition (LDP) techniques are being adopted within aerospace and automotive manufacturing to produce innovative precision components. Non-destructive techniques (NDT) for detecting and quantifying flaws within these components enables performance and acceptance criteria to be verified, improving product safety and reducing ongoing maintenance and product repair costs. In this work, software enabled techniques are presented for in-process analysis of NDT laser ultrasonic signals and pulsed laser thermography images of sequential metallic LPD layers. LPD tracks can be as thin as 200um while deposited at a rate of 500 mm/min, requiring ultrafast inspection and processing times. The research developed analysis algorithms that allow senior engineers to develop inspection templates and profiles for in-process inspection, as well as an end-to-end, user friendly interface for engineers to perform complete manual Laser Ultrasonic or Laser Thermographic inspections. Several algorithms are offered to quantify the flaw size. location and severity. The identified defects can be imported into a sentencing engine which then automatically compares analysis results against the user defined acceptance criteria so that the manufacturing products can be verified. Where both laser ultrasonic and laser thermographic NDT data is available further statistical tools could increase the confidence level of the inspection decision.
机译:激光粉末沉积(LDP)技术正在航空航天和汽车制造业中采用,以生产创新的精密零件。用于检测和量化这些组件中的缺陷的非破坏性技术(NDT)使性能和验收标准得到验证,从而提高了产品安全性并减少了日常维护和产品维修成本。在这项工作中,提供了软件支持的技术,用于对连续金属LPD层的NDT激光超声信号和脉冲激光热成像图像进行过程中分析。 LPD轨道以500 mm / min的速度沉积时,可以薄至200um,需要超快的检查和处理时间。该研究开发了分析算法,使高级工程师可以开发用于过程中检查的检查模板和配置文件,以及端到端,用户友好的界面,以使工程师可以执行完整的手动激光超声或激光热成像检查。提供了几种算法来量化缺陷大小。位置和严重性。可以将识别出的缺陷导入量刑引擎,然后由量刑引擎自动将分析结果与用户定义的接受标准进行比较,以便可以验证制造产品。在可以获得激光超声和激光热成像NDT数据的地方,进一步的统计工具可以提高检查决策的置信度。

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