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This paper proposes the implementation of a dedicated hardware architecture for structural health monitoring through the generation and acquisition of Lamb ultrasonic waves. The system utilizes an FPGA SoC to control data acquisition from four sensors, and active filters to perform signal conditioning with better resolution. The architecture employs a 12-bit ADC with a sampling rate of 500 kbps. The system allows signal generation and acquisition either through commands sent via a USB connection from a host computer or wirelessly in situations where distance is critical. A Python code was developed to monitor the acquisition data. Additionally, an executable program based on this algorithm was proposed, ensuring that the system can be portable to other computers. The results of tests and trials with composite laminates demonstrate the feasibility of the architecture for use in structural health monitoring (SHM) systems.

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System for Generating and Receiving Lamb Ultrasonic Waves Using FPGA Applied to Fault Detection on Composite Plates

  • 会议论文

  • 发表日期：

    2025年

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  • Orest Kaleniuk Filho,
  • Roberto d’Amore,
  • Osamu Saotome

摘要

This paper proposes the implementation of a dedicated hardware architecture for structural health monitoring through the generation and acquisition of Lamb ultrasonic waves. The system utilizes an FPGA SoC to control data acquisition from four sensors, and active filters to perform signal conditioning with better resolution. The architecture employs a 12-bit ADC with a sampling rate of 500 kbps. The system allows signal generation and acquisition either through commands sent via a USB connection from a host computer or wirelessly in situations where distance is critical. A Python code was developed to monitor the acquisition data. Additionally, an executable program based on this algorithm was proposed, ensuring that the system can be portable to other computers. The results of tests and trials with composite laminates demonstrate the feasibility of the architecture for use in structural health monitoring (SHM) systems.