The study presents an underwater acoustic signal processing approach for the identification of the material of an object using wideband chirp pulses. The echo from the target is formed by a number of processes that occur during reflection of the pulse from an object. The timing of these reflected components and geometry of their wave paths determine speed of sound in the wave propagating material. The calculated speed of sound is then used to identify the material. The novel method enables automated material identification without any training data. The object of the material identification is a two-layer metal spherical shell filled with liquid and placed in a fresh water tank. The presented approach identifies the shell and filler materials of the sphere. In this work, the sphere thickness is limited by 2% in relation to the radius. Results are evaluated for the sphere's radius in a range from 0.05 to 0.15 m. The approach yields 83.5% success rate for the shell material identification and 79.9% success rate for the filler material on the synthetic data. For the experimental data, 67.3 and 80% success rates were obtained for shell and filler material identification, respectively.
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- School of Engineering & Physical Sciences - Associate Professor
- School of Engineering & Physical Sciences, Institute of Sensors, Signals & Systems - Associate Professor
- Research Centres and Themes, Energy Academy - Associate Professor
Person: Academic (Research & Teaching)