Quantitative imaging of printed circuit board (PCB) delamination defects using laser-induced ultrasound scanning imaging

Laser-induced ultrasound scanning imaging is proposed and utilized for the detection of the printed circuit board (PCB) delamination defect in this present study. Initially, based on the principle of laser-induced ultrasound scanning imaging, a three-dimensional mathematical model of the ultrasonic excitation by pulsed laser acting on the surface of PCB is established and analyzed. Furthermore, based on the established laser ultrasonic nondestructive testing system, single-point testing is investigated on the PCB specimen. A-scan experiments were carried out by transmission and reflection approaches, respectively. Moreover, the influence of the signal receiving position on the discrimination of defective signals and the effect of wavelet transform denoising parameters on the signal-to-noise ratio were investigated. Eventually, based on the laser-induced ultrasound scanning imaging inspection system, the defects of simulated debonding flat bottom holes are detected and studied. The different algorithms or parameters (Fast Fourier Transform, variance, extremum, and principal component analysis, etc.) are employed to extract the characteristic information are analyzed. The experimental results are compared with the traditional infrared thermal wave imaging (lock-in thermography). The experimental results indicate that laser-induced ultrasound scanning imaging has the advantages of high-resolution imaging for the defect with a small diameter. Therefore, it is of great significance to study a set of feasible laser-induced ultrasound scanning imaging for PCB delamination defect detection.

Automated summary

Laser-induced ultrasound scanning imaging is proposed and applied for detecting delamination defects in printed circuit boards (PCBs). A mathematical model is established to analyze the excitation of ultrasonic waves by pulsed lasers on the surface of PCBs. Experimental results show that this imaging technique has high-resolution capabilities and can extract characteristic information for defect discrimination.