A Study on a PCBA Short Circuit Detection Method Based on the Hall Effect

Artificial intelligence is currently applied extensively across various fields, including healthcare, transportation, and finance. PCBA (Printed Circuit Board Assembly) short circuits can have a broad impact on AI systems, affecting hardware, software, system performance, and reliability. Conventional needle bed ICT technology in PCBA fault diagnostics can detect short circuits but is unable to pinpoint specific short circuit locations, nor does it provide any valuable information for repair personnel. FCT and AOI methods also have limitations and are unable to offer rapid and effective short circuit localization. This study proposes using the Hall effect to detect magnetic field characteristics produced by the PCBA under specific excitation, utilizing the low impedance property of short circuit points. By examining the magnetic field intensity at the short circuit location under specific excitation, this method aims to achieve quick and accurate localization of PCBA short circuit faults.