Guided-wave transmission of ultrasonic signals using compressive sensing and time-domain encoding

The increasing deployment of intelligent structures and embedded sensor networks creates a growing demand for reliable transmission of measurement data in environments where conventional wired and wireless communication methods are ineffective. In metallic and enclosed structures, electromagnetic waves are strongly attenuated, while wired solutions increase system complexity and weight. To address these limitations, this study proposes a novel guided-wave-based framework for the transmission of full ultrasonic measurement signals within structural elements. The proposed approach combines compressive sensing with a dual-stage encoding strategy. First, ultrasonic signals acquired by piezoelectric sensors are compressed using the Compressive Sampling Matching Pursuit (CoSaMP) algorithm, enabling efficient representation with a reduced number of samples while preserving essential measurement information. Next, selected amplitude–time pairs are encoded into single integer values and mapped onto a binary representation. This binary data is transmitted through the structure using a pulse position modulation (16-PPM) scheme, where information is encoded in the temporal location of ultrasonic wave packets. The method was validated both numerically, using finite element simulations, and experimentally on an aluminium plate instrumented with piezoelectric transducers. The transmission process was performed in a multi-hop configuration, and the original measurement signals were reconstructed at the final node. The results demonstrate that the proposed framework enables accurate reconstruction of ultrasonic signals from significantly reduced datasets, with only approximately 6% of samples required. Despite the presence of noise and wave dispersion, the reconstructed signals preserved the features necessary for reliable damage detection and localization. The study confirms that guided waves can be used not only for structural diagnostics but also as a medium for robust transmission of measurement data, enabling integrated sensing–communication systems for structural health monitoring applications.