Method for detecting microstructure of functionally graded material based on digital acousto-optic holography

A method for detecting a microstructure of a functionally graded material based on digital acousto-optic holography, comprising the following steps:

• Step 1:
• excite a sample with an ultrasonic wave
• Use an independent ultrasonic wave to excite a tested functionally graded material, utilize the ultrasonic wave to carry internal gradient information of the material to be propagated and output;
• Step 2:
• record a light wave
• After the ultrasonic wave carries the internal gradient information of the material to be propagated and output, form a reflection wave and a transmission wave, and then use an acousto-optic modulation device to modulate a laser light source of a laser of a laser device to form two light waves of different frequencies, wherein the two light waves of different frequencies record reflection wave information and transmission wave information of the ultrasonic wave through the reflection and the refraction of a reflecting mirror and a spectroscope, respectively;
• Step 3:
• form a single tomographic acousto-optic hologram
• Refract the light wave recorded with the reflection wave by the spectroscope again, and refract the light wave recorded with the transmission wave by the reflecting mirror and the spectroscope again, wherein the light waves are finally combined and recorded in the same hologram in an image collector by the spectroscope to form a single tomographic acousto-optic hologram;
• Step 4:
• perform numerical reconstruction of phase information
• Use different wavelengths and different reconstruction distances in an optic hologram to separate the reflection wave information and the transmission wave information, and realize the demodulation of ultrasonic wave information;
• Step 5:
• perform global detection
• According to demodulated ultrasonic wave information, combine with a sound field theory, perform quantitative mapping to obtain the gradient information of the material, and finally realize the global detection of the microstructure inside the functionally graded material.