Lamb-Waves-Based Sparse Distributed Penetrating Communication via Phase-Position Modulation for Enclosed Metal Structures

Xu, Yunfei; Li, Quanchang; Lin, Wanrong; Wu, Qihang; Huang, Wenbin; Ding, Xiaoxi

doi:10.1109/tii.2023.3246524

Cited by 4 publications

(1 citation statement)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Bahouth et al [13] explored the Lamb wave based wireless communication in both healthy and damaged metal plates. Xu et al [14] utilized Lamb waves for communication between internal and external sensor nodes in enclosed metals with a sparsely distributed configuration. In Lamb wave based communication research, the contact between transducers and structures is commonly required to achieve better data transmission of acoustic signals.…”

mentioning

confidence: 99%

Deep Learning Based Non-Contact Communication using Air-Coupled Leaky Lamb Wave

Fan,

Zou,

Ling

2024

Preprint

View full text Add to dashboard Cite

Ultrasound is used as an alternative to conventional communication in scenarios with severe electromagnetic shielding and interference. Ultrasonic guided waves, like Lamb waves, exhibit favorable transmission characteristics in platy structures, enabling long-distance propagation with low energy loss. This paper proposes a non-contact data transmission method using air-coupled leaky Lamb waves. Wave conversion and multipath interference have nonlinear effects on air-coupled leaky Lamb wave communication. To decode received temporal signals, a lightweight deep residual network (ResNet) designed for end-to-end time series classification (TSC) is employed. Real-world transmission experiments on a platy structure with a pitch-catch configuration were conducted, comparing three modulation methods: amplitude shift keying (ASK), frequency shift keying (FSK), and binary phase shift keying (BPSK). The trained ResNet achieved 1 recognition accuracy for each modulation. In bit error rate (BER) experiments, the error rate for each modulation was 0.

show abstract

mentioning

confidence: 99%