A Dual-Dip Heterogeneous LPFG Sensing System via Annealing under Bending with Temperature and Humidity Compensation

TL;DR

This paper introduces a dual-dip heterogeneous LPFG sensing system with enhanced sensitivity and multi-parameter capabilities, achieved through bending-assisted annealing and polymer-encapsulated architecture, enabling simultaneous temperature, bending, and humidity sensing.

Contribution

It presents a novel dual-dip heterogeneous LPFG platform with intrinsic spectral heterogeneity and multi-parameter sensing ability, overcoming cross-sensitivity issues in fiber-optic sensing.

Findings

Bending sensitivity increased from -3.44 to -8.97 nm/cm.

Detection limit improved from 0.017 to 0.006 cm.

Achieved simultaneous temperature, bending, and humidity sensing.

Abstract

Optical fiber multi parameter sensing is fundamentally constrained by cross-sensitivity and the complexity of multi sensor integration. Here, we present a dual-dip heterogeneous long-period fiber grating (LPFG) sensing platform enabled by bending assisted annealing, which introduces anisotropic refractive index redistribution and mode dependent coupling enhancement. This process yields enhanced sensitivity, improved dip contrast, and opposite spectral responses between dual resonance dips, providing intrinsic spectral heterogeneity. To overcome temperature cross sensitivity, a polymer-encapsulated cascaded LPFG-FBG architecture is developed, where the LPFG serves as the microbending sensitive element and the FBG acts as a reference channel. PDMS encapsulation enhances stress transfer and suppresses interfacial slippage, improving linearity and repeatability. As a result, the bending sensitivity increases from -3.44 to -8.97 nm per cm, and the detection limit improves from 0.017 to 0.006 cm. Building on this, a multi parameter sensing paradigm is established by integrating dual dip heterogeneity with LPFGFBG spectral orthogonality. With PAAm functionalization, the platform enables simultaneous and decoupled sensing of temperature, bending, and humidity, demonstrating scalable and versatile multi parameter capability. Overall, this work establishes a minimalistic yet robust paradigm for multi-parameter fiber-optic sensing, offering a scalable strategy for high-performance sensing in structural health monitoring and harsh environments.