A Simple Calibration Method for a Fringe Projection System Embedded within an Additive Manufacturing Machine

In additive manufacturing (AM), especially for advanced powder fusion machines, it is of high importance to develop an in situ inspection system to monitor the printed surface and pre-print powder bed as the build cycle proceeds. Consequently, high resolution, high precision and fast detection measurement systems need to be investigated, as such optically based measurement systems can provide feedback for manufacturing process optimisation. Fringe projection technology has a great advantage in the measurement of topography in such environments. The implementation of a fringe projection system requires that the system is pre-calibrated in order to obtain high measurement resolution and repeatability. This paper presents a simple calibration method for an AM-based in situ fringe projection system using a phase-depth calibration model. If a calibration plate with certificated marks is used, however, the texture of the plate will affect the measured phase accuracy. A simple calibration method to reduce the calibration plate texture effect in the process of calibration is outlined. Experimental results show that the proposed method can eliminated these effects and improve measurement resolution and repeatability. The proposed in situ/in process inspection technique has been implemented within a commercial electron beam powder bed fusion additive manufacturing machine (EBAM), to demonstrate the capability for effective feedback during the manufacturing process.

[1]  Lei Huang,et al.  Least-squares calibration method for fringe projection profilometry considering camera lens distortion. , 2010, Applied optics.

[2]  Beiwen Li,et al.  Structured Light Techniques and Applications , 2016 .

[3]  Feng Gao,et al.  A simple, flexible and automatic 3D calibration method for a phase calculation-based fringe projection imaging system. , 2013, Optics express.

[4]  Fu-Pen Chiang,et al.  Color-encoded digital fringe projection technique for high-speed three-dimensional surface contouring , 1999 .

[5]  Xiang Peng,et al.  Performance analysis of a 3D full-field sensor based on fringe projection , 2004 .

[6]  Nicola Senin,et al.  Surface texture metrology for metal additive manufacturing: a review , 2016 .

[7]  Chenggen Quan,et al.  Shape measurement of small objects using LCD fringe projection with phase shifting , 2001 .

[8]  High-dynamic-range 3D measurement for E-beam fusion additive manufacturing based on SVM intelligent fringe projection system , 2021, Surface Topography: Metrology and Properties.

[9]  Wang Jianguo,et al.  Complete 3D measurement in reverse engineering using a multi-probe system , 2005 .

[10]  Peisen S. Huang,et al.  Error compensation for a three-dimensional shape measurement system , 2003 .

[11]  Hans J. Tiziani,et al.  Testing micro devices with fringe projection and white-light interferometry , 2001 .

[12]  Tong Guo,et al.  Simple, flexible calibration of phase calculation-based three-dimensional imaging system. , 2011, Optics letters.

[13]  Y. Shin,et al.  Additive manufacturing of Ti6Al4V alloy: A review , 2019, Materials & Design.

[14]  A. Kashani,et al.  Additive manufacturing (3D printing): A review of materials, methods, applications and challenges , 2018, Composites Part B: Engineering.

[15]  Yan Hu,et al.  Calibration of fringe projection profilometry: A comparative review , 2021 .

[16]  Jing Xu,et al.  Status, challenges, and future perspectives of fringe projection profilometry , 2020 .

[17]  J. Kofman,et al.  Comparison of linear and nonlinear calibration methods for phase-measuring profilometry , 2007 .

[18]  Michael A. Sutton,et al.  Development and assessment of a single-image fringe projection method for dynamic applications , 2001 .

[19]  Reinhold Ritter,et al.  3-D shape measurement of complex objects by combining photogrammetry and fringe projection , 2000 .

[20]  Zonghua Zhang,et al.  In-situ areal inspection of powder bed for electron beam fusion system based on fringe projection profilometry , 2020 .

[21]  C Guan,et al.  Composite structured light pattern for three-dimensional video. , 2003, Optics express.