The use of an artificial neural network in the problem of ultrasonic diagnostics of defects in printed circuit boards of electronic devices

Modern electronic devices are complex technical systems, the functioning of which is accompanied by various physical processes occurring in their nodes and blocks. The combination of circuitry, structural and technological complexity of radio-electronic devices is the cause of various defects in them including hidden ones with a long latency period. This, in turn, imposes higher requirements for the diagnosis and control of the technical condition of electronic devices. The relevance of the research presented in this article is due to the need to increase the reliability and accuracy of defect identification in nodes and blocks of electronic devices, the development of new methods and means of technical diagnostics combining traditional approaches with actively developing technologies of artificial neural networks, big data processing, computational experiment. The article presents a study on ultrasound diagnostics of internal defects in the delamination of printed circuit boards. The method of modeling various defects using specialized software ABAQUS is described. The features of the subsequent processing of experimental data – amplitude-time, amplitude-frequency characteristics, the formation of numerical arrays of the parameters under study – are defined. The structure of an artificial neural network for diagnosing and identifying defects of printed circuit boards is given and the technology of its training and testing is defined. The materials of the article are of practical value for design engineers, circuit and system engineers of electronic systems as well as developers of complex technical complexes.

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