Localization of structural defects of printed circuit board assembly by vibration diagnostics

Objectives. Structural defects may arise during the production and operation of printed circuit board assemblies (PCBAs) installed in radio-electronic assemblies (REAs) due to manufacturing imperfections or the influence of external factors. Of particular concern are latent defects that cannot be detected after the PCBA has been manufactured and which may lead to failures during operation. The typical installation in sealed enclosures of modern PCBAs, which are characterized by a high density of electronic components, significantly complicates the use of conventional inspection and diagnostic methods. This study aims to improve the reliability of detecting and classifying latent defects in PCBAs in sealed blocks based on their mechanical amplitude-frequency characteristics (AFCs) using a deep neural network.

Methods. The paper proposes a vibration diagnostics method based on the numerical modeling of mechanical processes, experimental vibration testing, and the application of an artificial neural network for technical condition classification. Diagnostics involves analyzing the obtained mechanical AFCs using an accelerometer mounted on the enclosure and comparing them with a database of calculated AFCs generated for various technical states of the PCBA.

Results. To verify the proposed method experimentally, a PCBA mock-up was fabricated and installed inside an enclosure with various structural defects introduced into its design. A database of calculated mechanical AFCs was formed for both healthy and faulty states. After obtaining experimental AFCs, they were compared with the calculated data, and the introduced defects were identified using a deep neural network.

Conclusions. The developed vibration diagnostics method enables the highly accurate detection and classification of latent defects arising in radio-electronic equipment during production and operation. This improves the reliability of technical condition assessment of PCBAs.

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