Autonomous driving paper index
A dual-FBG Terfenol-D micro-displacement sensor for robust vehicular condition monitoring and intelligent transportation applications
One-line summary
An autonomous driving research paper: A dual-FBG Terfenol-D micro-displacement sensor for robust vehicular condition monitoring and intelligent transportation applications.
Engineering notes
Key topics: autonomous driving, perception. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
<title>Abstract</title> To address the challenge of environmental temperature interference in micro-displacement monitoring within intelligent transportation systems, this study proposes a temperature-insensitive micro-displacement sensor utilizing Terfenol-D giant magnetostrictive material and dual Fiber Bragg Gratings (FBGs). The sensor employs the magnetostrictive effect of Terfenol-D to drive micro-deformation. A differential configuration of two FBGs (FBG1 axially attached, FBG2 attached at a specific angle) eliminates wavelength drift induced by ambient temperature variations, converting the wavelength difference into displacement information. To validate system performance, a co-simulation platform integrating an Intelligent Driver Model (IDM) with the FBG sensor was established. Simulations were conducted under dynamic multi-vehicle scenarios, road slope variations, and coupled temperature-vibration interference. Two demodulation schemes were experimentally evaluated: spectrometer-based demodulation and an integrated demodulation module. Results indicate that within the 0–25μ m measurement range, the integrated demodulation scheme achieved a linearity of 0.493 and a sensitivity of 6.83 pm/μm. The displacement error remained below 6.2% under temperature fluctuations of ± 10◦ C, with a dynamic response time on the millisecond scale, demonstrating excellent real-time performance and robustness. The system also features immunity to electromagnetic interference, high integration, and miniaturization, making it suitable for applications such as electric vehicle chassis deformation monitoring and bridge dynamic load measurement. This research provides a reliable optical sensing solution for constructing the perceptionlayer of Vehicle-to-Everything (V2X) networks.
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