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FBG Sensors in Composite Airframes SHM — PatSnap Eureka

FBG Sensors in Composite Airframes SHM — PatSnap Eureka
Aerospace SHM · Patent Intelligence

Structural Health Monitoring with Fiber Bragg Grating Sensors in Composite Airframes

Fiber Bragg grating (FBG) sensors embedded in composite laminates provide spatially resolved, multi-directional strain data from within load-bearing plies — enabling real-time damage detection across fuselage panels, wing skins, and composite stringers. Over 30 patent records across multiple jurisdictions map the state of the art.

FBG Structural Health Monitoring Workflow in Composite Airframes Four-stage workflow showing how embedded fiber Bragg grating sensors in composite airframes convert strain data into probabilistic damage state estimates via Bayesian data fusion. STEP 1 Composite Laminate Embedded FBG sensor array STEP 2 Wavelength Shift Bragg λ shift = strain signal STEP 3 Bayesian Fusion DI + load cycles → crack estimate STEP 4 Damage State Probabilistic prognostics
30+
Patent records reviewed across jurisdictions
15
Patent families directly addressing aerospace SHM
6+
Jurisdictions covered by Boeing SHM filings
2006–2025
Span of key SHM patent innovations analysed
Field Overview

What Is Structural Health Monitoring for Composite Airframes?

Structural health monitoring (SHM) for composite airframes is a discipline concerned with embedding sensing systems directly into — or onto — primary structural elements such as fuselage panels, wing skins, and composite stringers, enabling continuous or on-demand assessment of structural integrity without disassembly. According to FAA guidance on advanced composite structures, in-service damage detection is one of the most critical certification challenges for composite primary structures.

The patent dataset reviewed covers SHM technologies across civil infrastructure, aerospace, and transportation domains, with the most technically dense cluster centering on composite airframe monitoring. Approximately 15 patent families directly address aerospace structural health monitoring, with The Boeing Company appearing as the single most prolific assignee — filing patents in the US, EP, CA, GB, SG, and JP jurisdictions on closely related SHM architectures.

Fiber Bragg grating (FBG) sensors emerge as a core sensing modality across the dataset. Supporting technical themes include ultrasonic guided wave propagation, Bayesian data fusion analysable via PatSnap Analytics, phased array transducers, compressed sensing, and AI-assisted load estimation. The composite material integration challenge — specifically embedding sensors without compromising laminate integrity — is a unifying design constraint addressed across multiple assignees. Learn more about how PatSnap supports advanced engineering R&D across sectors.

FBG
Core sensing modality across the patent dataset
Boeing
Single most prolific SHM assignee in dataset
6
Jurisdictions: US, EP, CA, GB, SG, JP — Boeing filings
2025
Most recent filings: TUSAS (WO) and 미래엔지니어링 (KR)
  • Co-cured FBG arrays within prepreg lay-ups
  • Bayesian network probabilistic damage estimation
  • Dedicated SHM processor separate from flight computer
  • Hybrid FBG-BOCDA on a single optical fiber
  • Compressed sensing for bandwidth-constrained networks
  • AI/neural network load estimation from strain readings
Sensing Physics & Integration

FBG Sensor Integration in Composite Laminates

Embedding geometry, dual-use monitoring capability, and high-stress zone coverage are the three design dimensions that define effective FBG integration in composite airframe structures.

Operating Principle

Bragg Wavelength Shift as Strain Transducer

FBG sensors operate by reflecting a characteristic Bragg wavelength from a periodic refractive index modulation inscribed in the fiber core; mechanical strain or thermal loading shifts this wavelength in a measurable and reversible manner. Optical fibers can be co-cured directly within prepreg lay-ups, providing intrinsic strain data from within the load-bearing plies rather than from the surface. SHM methods build deformation field maps — capturing both amplitude and phase relative to excitation — across the monitored surface using a network of FBG strain measurements, enabling spatially resolved structural diagnostics rather than point measurements alone.

LOUZADA, 2018 — Frequency Synchronization SHM
Embedding Geometry

Double-Helix Configuration for Multi-Axis Capture

Arranging strain sensors in a double-helix configuration within carbon-fiber-reinforced plastic (CFRP) enables strain measurement in multiple directions simultaneously. The embedding within the composite itself eliminates susceptibility to external environmental influences such as wind, precipitation, or wave loading that would degrade surface-bonded instrumentation — directly relevant to aircraft structures subject to turbulence and thermal gradients. This approach was demonstrated by 유한회사 미래엔지니어링 in their 2025 AI-assisted structural stability monitoring patent.

미래엔지니어링, 2025 — CFRP double-helix
Dual-Use Capability

Tilted FBG for Process Qualification and In-Service Monitoring

Tilted (oblique-type) FBG sensors introduced into the composite during molding allow transmission spectrum monitoring for physical property values during and after cure — providing both process qualification and in-service health data from a single embedded element. This dual-use capability is highly valuable for certifying composite airframe components where as-manufactured state directly affects structural margins, as demonstrated by Tokyo University of Agriculture and Technology's 2019 fiber-reinforced plastic monitoring system.

Tokyo Univ. Ag. & Tech., 2019 — cure + in-service
Priority Zone

Composite Stringer Noodles — High-Stress Embedded Sensing

TUSAS-Turk Havacilik ve Uzay Sanayii's 2025 WO filing positions a fiber optic sensor with reference wavelength characteristics inside the filler material of composite stringers — the structurally critical fillets between laminate plies in stiffened panels — allowing real-time monitoring of those high-stress zones that are inherently difficult to inspect with external methods. The reference wavelength or signal characteristic values are calibrated against the strength values of the stringer during its operational state.

TUSAS, 2025 — stringer noodle FBG
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Patent Landscape Data

SHM Innovation by Assignee and Signal Processing Approach

Derived from analysis of 30+ patent records via PatSnap Eureka, these charts map the key innovators and dominant technical approaches in composite airframe SHM.

SHM Patent Families by Key Assignee

Boeing dominates with 15+ aerospace SHM patent families across 6 jurisdictions; other assignees contribute targeted innovations in sensing physics and deployment.

SHM Patent Families by Key Assignee: Boeing 15+, LORD Corp 2, Airbus Deutschland 2, Spirit AeroSystems 1, TUSAS 1, Xiamen Univ 1 Horizontal bar chart showing patent family counts for top SHM assignees derived from PatSnap Eureka analysis of 30+ patent records. Boeing leads with 15+ families across US, EP, CA, GB, SG, and JP jurisdictions. 0 5 10 15 20 Boeing 15+ LORD Corp 2 Airbus Deutschland 2 Spirit AeroSystems 1 TUSAS 1 Xiamen Univ. 1

SHM Signal Processing Approaches in Patent Literature

Bayesian and probabilistic methods account for the largest share of processing approaches, reflecting Boeing's dominant portfolio and the field's shift toward probabilistic prognostics.

SHM Signal Processing Approaches: Bayesian/Probabilistic 30%, Frequency-Domain/Resonance 25%, Ultrasonic Guided Wave 20%, AI/Neural Network 15%, Compressed Sensing 10% Donut chart showing distribution of signal processing methodologies across composite airframe SHM patents analysed via PatSnap Eureka. Bayesian fusion leads at 30%, followed by frequency-domain methods at 25% and ultrasonic guided waves at 20%. 5 approaches Bayesian / Probabilistic — 30% Frequency-Domain — 25% Ultrasonic Guided Wave — 20% AI / Neural Network — 15% Compressed Sensing — 10%

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Signal Processing & Data Fusion

Damage Detection Architectures: From Raw Wavelength to Probabilistic Prognostics

Multi-layer processing converts FBG wavelength shift data into actionable structural damage state estimates — distinguishing damage signatures from operational noise, temperature drift, and load-path variations.

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Bayesian Network Data Fusion (Boeing, 2014)

Boeing's Bayesian Network-based data fusion technique combines environmental information — specifically load cycles induced on the structure — with a damage index (DI) to produce crack detection outputs and crack length estimates. This represents a statistically rigorous departure from simple threshold-crossing approaches. The same patent family introduces a finite element modeling approach for determining optimal excitation frequencies and time windows for sensed signals.

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Frequency-Domain Resonance Mapping (FACULDADES CATÓLICAS, 2021)

Strain field maps are built based on amplitude and phase at different frequencies near structural resonances — scanning a frequency range and evaluating amplitude (or RMS and peak-to-peak values) of different sensors near resonance, then comparing those maps against a known healthy baseline signature. This approach is particularly powerful for detecting delaminations or disbonds in composite laminates, where damage alters local stiffness and thus shifts resonant frequencies measurably.

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Unlock 2 Additional Processing Architectures
See how dedicated SHM processors and hybrid FBG-BOCDA sensing extend damage detection capability in confined composite structures.
Dedicated SHM processor design FBG-BOCDA two-stage interrogation + Boeing 2006 architecture
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Competitive Landscape

Key Players and Their SHM Innovation Focus Areas

Drawn from the 30+ patent records reviewed via PatSnap Eureka, this table maps each major assignee to their primary technical contribution in composite airframe SHM.

Assignee Jurisdiction(s) Core SHM Innovation Latest Filing
The Boeing Company US, EP, CA, GB, SG, JP Bayesian data fusion, ultrasonic guided waves for curved composites, dedicated SHM processor architecture, Bayesian crack length estimation 2024 (SG — curved composites)
Airbus Deutschland CN Lithiated carbon fiber strain-sensing elements co-cured in multi-ply laminates; fracture-sensing fibers with electrically insulating coatings for delamination onset detection 2020
Spirit AeroSystems US Wireless self-contained sensor wafer architecture with fault-tolerant hierarchical network reconfiguration for composite structures 2009
LORD Corporation US, EP SHM sensor outputs integrated with active vibration cancellation force generators for rotary-wing aircraft — closed-loop structural management 2018 (US)
TUSAS-Turk Havacilik WO FBG sensor inside composite stringer noodle filler material; reference wavelength calibrated against stringer strength values 2025
Korea Institute of Civil Engineering KR Hybrid FBG-BOCDA on single optical fiber: FBG for dynamic response, BOCDA for quasi-static high-resolution strain mapping triggered by impact events 2021
Tokyo Univ. Ag. & Tech. JP Tilted FBG sensors introduced during composite molding for transmission spectrum monitoring — dual process-qualification and in-service health data 2019
Xiamen University CN Compressed sensing algorithms for sparse signal reconstruction from sub-Nyquist sampling — addresses data bandwidth constraints in large aviation SHM sensor networks 2016
유한회사 미래엔지니어링 KR Double-helix CFRP-embedded sensor arrangement with AI neural network for actual structural load estimation from embedded sensor strain readings 2025
LOUZADA / FACULDADES CATÓLICAS BR Frequency-synchronised deformation field mapping using FBG networks; amplitude and phase evaluation near structural resonances vs. healthy baseline 2021
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Aerospace Application Domains

Primary Structural Elements and Deployment Strategies

The primary use case for embedded FBG SHM in the patent literature is the monitoring of primary structural elements in aircraft and spacecraft: fuselage panels, wing skins, composite stringers, and curved laminate sections. Airbus Deutschland's filing directly addresses the challenge of integrating health monitoring into fiber composite airframe components by embedding at least two parallel strain-sensing fibers — specifically lithiated carbon fibers with piezoelectric properties — within the fiber plies of the component. According to EASA's composite structure certification framework, demonstrating in-service damage detectability is a central airworthiness requirement.

Boeing addresses the challenge of curved composite structures — which are abundant in modern airframes — through ultrasonic guided wave systems. The 2024 SG patent provides a repeatable nondestructive technique for monitoring noodle areas in adhesively bonded curved composite laminates, comparing interface-guided wave detection data against simulation-derived prediction data. The time-of-flight of interface guided waves through the noodle allows damage size estimation — critical for composite radii where fiber bridging and through-thickness tension can initiate delamination.

Spirit AeroSystems addresses deployment practicality through wireless, self-contained sensor wafers bonded to aircraft component surfaces communicating in a hierarchical network with a central data acquisition module. If any sensor wafer fails, the central module reconfigures the hierarchical communication order to exclude the malfunctioning node — providing fault tolerance essential for airworthy systems. For API-based integration of SHM data pipelines, PatSnap's open developer platform enables programmatic access to patent and innovation data. The PatSnap materials science intelligence suite also supports composite material innovation teams tracking advanced fibre and resin developments relevant to SHM integration.

Xiamen University's compressed sensing approach addresses data bandwidth constraints inherent in large sensor networks by applying sparse signal reconstruction from sub-Nyquist sampling — enabling rapid reliable detection across complex composite structures without transmitting full-bandwidth data streams from every sensor node. The NIST Non-Destructive Evaluation programme identifies bandwidth-efficient sensing as a key enabler for scalable aerospace SHM deployment.

Monitoring Zone Priority
Composite Stringer Noodles
High-stress fillets between laminate plies — TUSAS 2025 FBG approach
Curved Composite Laminates
Adhesively bonded radii — Boeing SG 2024 guided wave ToF approach
Fuselage & Wing Skin Panels
Large-area FBG networks and wireless wafer arrays — Spirit, Airbus
Rotary-Wing Structures
SHM + active vibration cancellation — LORD Corporation 2018
Innovation Trend

A cross-cutting trend is the integration of AI and machine learning into the SHM pipeline. The 미래엔지니어링 2025 patent employs artificial neural networks to estimate actual structural loads from embedded sensor strain readings, while Boeing's Bayesian network fusion methods perform probabilistic damage state estimation — both representing a shift from deterministic threshold monitoring to probabilistic structural prognostics.

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Structural Health Monitoring with FBG Sensors — Key Questions Answered

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References

  1. Method and System for Structural Health Monitoring with Frequency Synchronization — LOUZADA, DANIEL RAMOS, 2018
  2. Method for Monitoring Structural Stability Using Artificial Intelligence — 유한회사 미래엔지니어링, 2025
  3. Composite Structure with a Structural Health Monitoring Sensor — TUSAS-Turk Havacilik ve Uzay Sanayii, 2025
  4. Methods and Systems for Structural Health Monitoring — The Boeing Company, 2014
  5. Methods and Systems for Structural Health Monitoring — The Boeing Company, 2017
  6. Methods and Systems for Structural Health Monitoring — The Boeing Company, 2021
  7. Structural Health Management Architecture Using Sensor Technology — ANDERSON, DAVID M., 2006
  8. Structural Health Management Architecture Using Sensor Technology — The Boeing Company (EP), 2007
  9. Structural Health Management with Active Control Using Integrated Elasticity Measurement — The Boeing Company, 2015
  10. Structural Health Monitoring of Curved Composite Structures Using Ultrasonic Guided Waves — The Boeing Company (SG), 2024
  11. Method and System for Structural Health Monitoring with Frequency Synchronization — FACULDADES CATÓLICAS (BR), 2021
  12. Structure Health Monitoring System Using Optic Fiber-Based Hybrid Nerve Network Sensor — Korea Institute of Civil Engineering and Building Technology (KR), 2021
  13. Fiber-Reinforced Plastic Composite Material Monitoring System — Tokyo University of Agriculture and Technology (JP), 2019
  14. System and Method for Self-Contained Structural Health Monitoring for Composite Structures — Spirit AeroSystems, Inc., 2009
  15. Systems and Methods for Structural Health Monitoring and Protection — LORD Corporation (US), 2018
  16. Fiber Composite Component with Integrated Structural Health Sensor Device — Airbus Deutschland Operations GmbH (CN), 2020
  17. Fiber Composite Component, Component System, Aircraft and Use — Airbus Deutschland Operations GmbH (CN), 2020
  18. Compressed Sensing System for Aviation Structural Health Monitoring — Xiamen University, 2016
  19. FAA — Advanced Composite Structure Airworthiness Guidance
  20. EASA — Composite Structure Certification Framework
  21. NIST — Non-Destructive Evaluation Programme: Bandwidth-Efficient Sensing for Aerospace SHM

All data and statistics on this page are sourced from the references above and from PatSnap's proprietary innovation intelligence platform. Patent analysis was conducted via PatSnap Eureka.

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