## 3 LPBF Sensing Techniques
### Acoustic Techniques  
Also referred to as resonance techniques, acoustic techniques detect the excited vibrations in a specimen to assess part quality and detect defects. By collecting the acoustic emissions (AE) generated from the LPBF printing process, the correlation between the anomaly signals and the location can provide insight into the location and size of defects, including internal defects. **Acoustic emission spectroscopy (AES)** measures the continuous release of energy from where transient elastic waves are generated in a material. There are two significant components in AE spectroscopy, namely, a fault that is the cause of energy release in the material (event) and the transducer that gathers the data from the produced event. The fault generated from the AE signal appears in high-frequency sound waves [167]. AE spectroscopy has been mainly used for dynamic damage characterization, specifically for crack propagation monitoring. Other internal structural defects can be detected from acoustic signals. AE spectroscopy is a non-destructive technology that can quickly generate valuable data about the location of defects [167]. However, the description generated from the AE cannot accurately describe the size and shape of defects. [PERSON] et al. [168] used AE to monitor the fatigue crack growth behavior of LPBF-printed Ti6 Al4V components. Two AE broadband \"pico\" type sensors were attached to the side of the printed specimen. The time delay between the two AE signals and the wave velocity of the material simultaneously were used to determine the crack location. A study performed acoustic resonance testing of SS316L and 6802 T6 aluminum alloy samples to measure the modulus of LPBF-printed lattice samples with a high degree of loose powder adhesion [169]. The samples were excited with a small impact, and a microphone was  
Figure 29: Example provided by [75] for an Al-33 Cu LPBF-printed specimen, showing the DSC results identifying the eutectic point of the material. used to record the AE signals. The resulting AR test results were reportedly feasible in providing a metric of loose powder adhesion and other structural characteristics. Multiple studies used AE signals to characterize the corrosion behavior of AlSi10 mg specimens [170] and monitoring techniques to detect crack formation in a high-strength Al92 Mn6 Ce2 alloy LPBF-printed component, as shown in Figure 30 [171]. A combination using laser Doppler vibrometry (LDV) with vibrational resonance spectroscopy to develop a laser acoustic resonance spectroscopy (LARS) system was introduced [172]. The LARS system reportedly identified defects rapidly in LPBF cubic components. Acoustic signals generated during the LPBF printing process of SS304 using an equipped nominal microphone attached to the LPBF were collected [173]. Melting states such as overheating, slight overheating, standard, and slight balling in the LPBF printing process are obtained by the relationship between acoustic signals, energy densities, and track formation. A high-frequency structure-borne sensor was used to detect AE activity associated with cracking. [PERSON] et al. [174] used a microphone to record the AE signals during the LPBF printing process of SS316L cubic samples. After post-processing, spectrograms were created from the extracted AE signals, revealing the location of defects in the samples. [PERSON] et al. [175] collected AE signals during and after the LPBF printing process of Al92 Mn6 Ce2 cylindrical specimens using a high-temperature structure-borne sensor. The processed AE signal data were used to train various ML algorithms to recognize crack signals. **Fiber Bragg grating (FBG)** sensors are one of the most sensitive sensor types for acoustic and pressure wave detection [176]. For FBGs, AE signals are collected through fiber optic sensors, where the strain sensitivity is correlated with the AE measurements.