М.Yu. Reushev – Ph.D. (Phys.-Math.), Associate Professor,

Siberian Federal University (Krasnoyarsk)

E-mail: reuqem@mail.ru

S.L. Nikitin – Junior Research Scientist,

FIC KSC SB RAS (Krasnoyarsk)

N.N. Davletshin – Junior Research Scientist,

FIC KSC SB RAS (Krasnoyarsk)

The paper presents the results of the development of a scanner model for defectoscopy of materials by non-destructive testing in the THz range.

Recently, in addition to widely used methods of flaw detection, such as acoustic, X-ray, and optical, submillimeter (THz) range radiowave defectoscopy is spreading. One of the main advantages of THz flaw detectors is their non-destructive effect. In addition, THz radiation is non-ionizing and the scanning process of the test samples is safe for the user. Recently, it has become possible to visualize THz radiation, which makes it possible to improve the diagnostics and detection of defects, including in semiconductor integrated circuits. The experimental setup of the scanner mockup consisted of a THz radiation source, a motorized platform for attaching samples, and a recording device.

As a source of THz radiation, a molecular gas laser was used with optical pumping by radiation of a frequency-tunable waveguide CO2 laser in the wavelength range from 9,4 to 10,7 μm. The active media of the THz laser was methanol and difluoromethane. The wavelengths and the output power of the THz laser were measured using a Fabry–Perot scanning interferometer (TSFPI) and a Golay optoacoustic detector (GC-1P).

During the experiments, THz laser generation was obtained at 15 wavelengths in the range from 96 to 235 μm with an output power of the order of 1 mW.

For measurements, the following was developed: a model of a motorized platform for scanning the samples under study, as well as a technique and software for automating the process of finding and visualizing defects based on the ArduinoUNO microcontroller. The software is executed in the LABVIEW programming environment using the ArduinoUNO microcontroller. To work with the microcontroller, ArduinoIDE software was used, which allows using ready-made libraries for writing a scanning program and recording a signal. After scanning the sample, an array of data is formed, the values of which are used to build an image with a certain resolution. The image allows you to visually familiarize yourself with the result of the scan, and locally determine the presence of defects, after which you can conduct a more detailed scan, namely to resume shooting at a higher resolution, at the location of the defect.

The results can be useful for defectoscopy of dielectric coatings, semiconductor integrated circuits, and other applications.

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