Novosibirsk State Technical University (NSTU) is developing a hardware and software complex for measuring residual technological stresses in metal products. The speckle interferometry method is at the heart of the equipment, and the processing of the received data will be performed by a program written in Python.
Konstantin Nikitin, a graduate student of the Department of Optical Information Technologies at the Faculty of Physics and Technology of NSTU-NETI, proposed his own way of detecting defects in metal products after changing their shape and state of aggregation. The proposed method is based on the analysis of the deformation field around non-penetrating technological holes that are drilled in a controlled sample using speckle interferometry, an optical technology that allows accurate detection of surface changes.
"Residual technological stresses are internal forces that accumulate during 3D printing of metal products, welding, rolling, and laser thermal hardening. It is important that the structures remain durable. The hardware and software complex allows performing a complete stress analysis," Konstantin Nikitin said.
The work on defect detection begins with irradiation of metal surfaces with a semiconductor laser, which creates a speckle pattern - a characteristic granular structure before and after creating a non—penetrating hole. As a result, a number of images are obtained, analyzing which with the help of software it is possible to see changes in speckles, calculate a deformation map and determine residual stresses from it.
According to the graduate student of the ICU Department, the speckle interferometry-based method for monitoring residual stresses is superior to ultrasound and strain measurement due to non-contact, high sensitivity (nanometer level) and the ability to create a complete map of deformation fields in real time. Unlike point strain gauges, it provides visualization of the entire surface, and unlike ultrasound, it is easier to interpret data without complex calibration," said Konstantin Nikitin.
The first results on the development of a device for measuring residual technological stresses in metal products are expected by the end of 2026.
It should be recalled that NSTU-NETI is also conducting proactive work to create a stand for automatic diamond sorting using unique machine learning algorithms, thanks to which it will be possible to accurately classify natural minerals by color.