Ultrasound Automation for High Volume, Long Term Measurements

Overview

Ultrasonic testing is crucial for the nondestructive evaluation of structural integrity, materials characterization, and quality control. However, continuous manual operation of ultrasound equipment is labor intensive and requires skilled oversight. This paper presents a cost-effective approach to automate an ultrasound system using open-source technologies. The automation enhances efficiency by enabling precise and continuous long-term measurements without external intervention. By synchronizing and autonomously controlling an oscilloscope, waveform generator, and pulser-receiver, the system acquires ultrasound data. The oscilloscope is configured with pyVISA using SCPI commands, setting key parameters for the ultrasound reading. The waveform generator, controlled with pySerial, provides trigger signals to simultaneously control pulser activation and oscilloscope triggering. Timing consistency between physical excitation and waveform capture enables accurate ultrasonic measurements. Acquired waveforms are then processed and saved for analysis. Key parameters like amplitude, rise time, and time-of-flight can be extracted from the data. The modular automation scripts allow users to adjust settings like number of data points and vertical scale between measurements for optimal data resolution. A graphical user interface (GUI) enables configuration adjustability for long-term operations. This flexible framework coordinates multiple instruments without proprietary software or hardware lock-in thereby democratizing the ability to conduct research. Results validate accuracy against manual operation, with a mean squared error of 4.299 × 10-6. By eliminating repetitive manual tasks, the automation system significantly enhances productivity and enables new ultrasonic testing capabilities. Remote nondestructive testing and long-duration characterization experiments can be performed hands-free with high accuracy at a low cost.

Competition history

• AJAS 2024 Category not listed

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