Laser opto-ultrasonic dual detection for simultaneous compositional, structural, and stress analyses for wire + arc additive manufacturing

Abstract

The complex, nonequilibrium physical, chemical, and metallurgical nature of additive manufacturing (AM) tends to lead to uncontrollable and unpredictable material and structural properties. Therefore, real-time monitoring of AM is of great significance. However, current AM relies on separate postprocess analyses, which are usually destructive, costly, and time-consuming. In this study, we investigated a laser opto-ultrasonic dual (LOUD) detection approach for simultaneous and real-time detection of elemental compositions, structural defects, and residual stress in aluminium (Al) alloy components during wire + arc additive manufacturing (WAAM) processes. In this approach, a pulsed-laser beam was used to excite the surfaces of Al alloy samples to generate ultrasound and optical spectra. As a result, the compositional information can be obtained from the optical spectra, while the structural defects and residual stress distributions can be extracted from the ultrasonic signals. The silicon (Si) and copper (Cu) compositions obtained from optical spectral analyses are consistent with those obtained from the electron-probe microanalyses (EPMA). The 1 mm blowhole and the residual stress distribution of the sample were detected by the ultrasonic signals in the LOUD detection, which shows consistency with the conventional ultrasonic testing (UT). Both results indicate that the LOUD detection holds the promising of becoming an effective testing method for AM processes to ensure quality control and process feedback.

Introduction

Additive manufacturing (AM) is a potentially disruptive technology across multiple industries [1], such as the aerospace, precision manufacturing, and metal [[2], [3], [4], [5]]. Different from conventional material removal methods, AM is based on layer-by-layer shaping and consolidation of feedstock to arbitrary configurations. However, AM generally has a complex nonequilibrium physical and chemical metallurgical nature, leading to unstable manufacturing quality [6,7]. Therefore, the chemical compositions, structural information, and mechanical properties of AM components need to be detected. Up to now, the detection of elemental compositions, structural defects, and residual stress are the most urgently required.

The compositions of metallic materials play significant roles in the mechanical properties of the materials [[8], [9], [10]], such as the silicon (Si) or copper (Cu) elements in aluminum (Al) alloys that can change the sensitivity for hot cracking [11]. Some researchers have carried out extensive work on element detection. For example, Gu et al. [12] studied the key alloying/additive elements in laser melting and laser metal deposition using electron microscopy. It was found that the compositions affected the metallurgical, thermodynamic, and kinetic behaviors of the melt in the nonequilibrium molten pool. Ma et al. [13] studied the composition segregation in the pulsed-laser welding joint using scanning electron microscopy (SEM), energy-dispersive X-ray spectrometry (EDS), and electron-probe micro-analysis (EPMA). The results showed that the segregation degree of laser welding was weaker than that of conventional welding. Wang et al. [14] analyzed the common elements in steels using laser-induced breakdown spectroscopy (LIBS). The average absolute measurement errors were less than 0.04, which showed that LIBS was a potential technology in metal analyses.

Meanwhile, some extensive work in structural defects and residual stress detection has been conducted. For example, Hönnige et al. [15] studied the residual stress of the Wire + Arc Additive Manufacture (WAAM) samples by neutron diffraction measurements. Zhou et al. [16,17] reported the detection of preset defects in three dimensional (3D)-printed titanium alloy samples using phased array ultrasonic testing. Carroll et al. [18] detected internal defects in Ti–6Al–4 V components by X-ray computed tomography. The results showed that the defects could influence ductility in the directed energy deposition additive manufacturing process. Ding et al. [19]. simulated the residual stress of Wire-and-Arc Additive Layer Manufacturing components by finite element analysis (FEA) and then verified the FEA results by neutron diffraction strain. Karabutov et al. [20] detected the residual stress in the welding seam of nickel-titanium alloy arc welding by Laser ultrasonic testing (Laser UT). The results were in close agreement with the conventional testing. Lopez et al. [21] reported that Electro Magnetic Acoustic Transducer (EMAT) or Laser UT can be good approach in online monitoring of WAAM.

However, the current detection of components fabricated by AM are almost performed sequentially, which is time-consuming, costly, and destructive to the samples. In this work, we investigated laser opto-ultrasonic dual (LOUD) detection for the first time to detect elemental compositions, structural defects, and residual stress simultaneously for monitoring component quality during the AM process [22]. The optical emission and ultrasound wave were generated when the laser ablated the surface of the samples under microdestructive (micron-scale ablation) or even nondestructive conditions. After the laser ablation, the element analysis can be obtained from the optical spectra, and the defects and residual stress can be detected and analyzed via the ultrasonic signals.

The WAAM process is a direct-feed process which uses an arc as the heat source and a metallic wire as the feed material. Compared with the powder-feed/bed AM, WAAM has a higher efficiency of material usage and deposition rates with lower capital investment to equipment [23]. More importantly, the welding technology has been well studied and has similarity with the WAAM, which can help understand the complex processes involved in WAAM. Therefore, we used LOUD detection to study both the laser welding and WAAM processes in this study.