The core technology of ultrasonic flaw detector is mainly based on the propagation characteristics of ultrasonic waves in materials and their interaction with defects. Its working principle begins with the piezoelectric effect, which excites piezoelectric crystals through high-frequency electrical signals to generate mechanical waves with frequencies higher than 20kHz. When sound waves propagate in materials, they will reflect, refract, or scatter due to differences in acoustic impedance when encountering internal defects such as cracks, pores, etc. By capturing these echo signals with a receiving probe and analyzing their time difference and amplitude changes, the defect location can be accurately located and the size can be evaluated.

Pulse reflection method is currently a commonly used technological path. Integrated design of transmission and reception through a single probe, utilizing the time difference between defect echoes and bottom echoes to achieve defect localization. The Time of Flight Diffraction (TOFD) method achieves millimeter level quantitative analysis through the time difference of diffraction waves at the defect end, especially suitable for weld seam detection. Phased array technology achieves beam deflection and focusing by electronically controlling the delayed excitation of multi element probes. Combined with full matrix capture (FMC) and full focusing method (TFM), it can generate real-time C-scan images with a signal-to-noise ratio of over 60dB, achieving micrometer level crack detection.

At the imaging technology level, ultrasonic flaw detectors achieve defect visualization through multidimensional imaging methods such as A-scan, B-scan, and C-scan. Type A display presents defect waveform characteristics intuitively with propagation time as the horizontal axis and reflection amplitude as the vertical axis; B-type display generates two-dimensional tomographic images, similar to the principle of medical B-ultrasound; The C-type display maps the probe position to the defect distribution through mechanical scanning. Nonlinear ultrasound technology further breaks through the diffraction limit, combined with digital twin technology to construct a material acoustic property database, which can predict the evolution trend of defects.

The current technological evolution focuses on intelligent detection systems and environmental adaptability. Deep learning algorithms (such as U-Net network) achieve automatic defect classification with an accuracy rate of 98%; The high-temperature ultrasonic probe (temperature resistant to 800 ℃) and liquid immersion detection robot have expanded the application boundaries of special scenarios such as refining equipment and nuclear reactors. In the future, cutting-edge technologies such as quantum sensing ultrasound and self powered sensors are expected to increase sensitivity by three orders of magnitude, driving non-destructive testing into the era of sub wavelength resolution.