Applied Sciences

Phase-sensitive optical time domain reflectometry (Φ-OTDR) is a highly sensitive distributed vibration sensing technology crucial for pipeline safety monitoring. However, its sensitivity makes it susceptible to environmental interference, leading to frequent false alarms by misclassifying routine activities as threats. To enable accurate threat identification and rapid response, this study proposes a lightweight LightPatch Vision Transformer (LP-ViT) model suitable for edge deployment. We establish a mapping between excavator-pipeline distance and threat levels: “direct intrusion” (within 5 m), “high-risk operation” (within 10 m), and “background construction” (beyond 15 m). The LP-ViT model is developed through structural optimization and parameter compression of the standard Vision Transformer, achieving a 96.6% reduction in parameter count while maintaining a high classification accuracy of 89.9%. Furthermore, via knowledge distillation, we derive an ultra-lightweight student model with merely 0.37 M parameters, which achieves an inference latency of 5.5 ms per sample, enabling millisecond-level threat detection and response. The proposed solution effectively enhances both the classification accuracy and real-time performance of Φ-OTDR systems in complex environments, providing a practical pathway for implementing edge intelligence in pipeline safety monitoring.

For battery-powered Smart Road components deployed in locations without access to the electrical grid, limited energy availability represents a major challenge to long-term autonomous operation. While photovoltaic panels are the most commonly used energy-harvesting solution, their effectiveness depends strongly on environmental and climatic conditions and may be insufficient in shaded areas or in highly dynamic road environments. Road infrastructure, however, inherently provides additional and largely underutilized energy sources, among which thermoelectric energy generated by temperature gradients within the road structure is particularly promising. This review addresses the problem of identifying viable alternatives or complements to photovoltaic energy harvesting by focusing on thermoelectric transducers as a potential power source for Smart Road applications. The objective of the article is to provide a comprehensive overview of the physical principles underlying thermoelectric transducers, the different architectures of thermoelectric modules, and their practical applicability in road transportation systems. Particular attention is devoted to implementation approaches that do not interfere with traffic flow or compromise road safety, as well as to existing applications of thermoelectric energy harvesting in transportation infrastructure. In addition, the review discusses the potential and limitations of concentrated thermoelectric transducers for increasing power density. By synthesizing current research results, this work evaluates the feasibility, advantages, and challenges of thermoelectric energy harvesting to extend the operational lifetime of autonomous Smart Road components and identifies directions for future research.

Transformers are critical components in power systems, and their functionality must be maintained during seismic events. This study conducted multi-directional shaking table tests on a full-scale 154 kV transformer to investigate the seismic response and failure mechanisms of radiator and conservator connections. Measurements of relative displacement, acceleration, and test response spectra (TRS) indicated stable responses of 0.5–1.2 g for the transformer body, whereas the bushings and radiators exhibited amplified accelerations of up to 4 g and 2 g, respectively, along with relative displacements exceeding 20 mm. Under the 500-year return period input motion, leakage was observed at the lower radiator elbow, which is attributed to the combined effects of concentrated relative displacement, acceleration amplification, frequency-dependent energy concentration, and local structural discontinuities. The observed damage patterns were consistent with leakage incidents reported during the 2024 Noto earthquake in Japan. Based on the experimental findings, this study discusses seismic performance enhancement measures for radiator connections and provides experimental evidence to support the seismic safety evaluation of transformers with similar configurations.