3-D underwater object restoration using ultrasonic transducer fabricated with PZT-polymer 3-3 type composite and neural network

In this study, the characteristics of a transducer fabricated with porous PZT-polymer composites with 3-3 connectivity are investigated and 3D underwater object restoration using the self-made ultrasonic transducer and modified SCL (Simple Competitive Learning) neural network is presented. The self-made transducer satisfied requirements of ultrasonic transducers in water, and a modified SCL neural network using the acquired object data 16/spl times/16 low-resolution image was used for underwater object restoration of 32/spl times/32 high-resolution image. The experimental results have shown that the ultrasonic transducer fabricated with porous PZT-polymer composites with 3-3 connectivity could be applied in a sonar system.