Wiley Series in Pure and Applied Optics

This work describes a novel method of embedded damage detection within glass fiber–reinforced polymer composites. Damage detection is achieved by monitoring the spatially distributed electrical conductivity of a strain-sensitive multiwalled carbon nanotube thin film. First, thin films were spray-deposited directly upon glass fiber mats. Second, using electrical impedance tomography, the spatial conductivity distribution of the thin film was determined before and after damage-inducing events. The resolution of the sensor was determined by drilling progressively larger holes in the center of the composite specimens, and the corresponding electrical impedance tomography response was measured by recording the current–voltage data at the periphery of the monitored composite sample. In addition, the sensitivity to damage occurring at different locations in the composite was also investigated by comparing electrical impedance tomography spatial conductivity maps obtained for specimens with sets of holes drilled at different locations in the sensing area. Finally, the location and severity of damage from low-velocity impact events were detected using the electrical impedance tomography method. The work presented in this study indicates a paradigm shift in the available possibilities for structural health monitoring of fiber-reinforced polymer composites.

Detection of Spatially Distributed Damage in Fiber-Reinforced Polymer Composites.

In-flight and wireless damage detection in a UAV composite wing using fiber optic sensors and strain field pattern recognition

This paper presents an aircraft health and usage monitoring system (HUMS) using fiber Bragg grating (FBG) sensors. This study aims to implement and evaluate the HUMS for in-flight strain monitoring of aircraft structures. An optical-fiber-based HUMS was developed and applied to an ultralight aircraft that has a rectangular wing shape with a strut-braced configuration. FBG sensor arrays were embedded into the wing structure during the manufacturing process for effective sensor implementation. Ground and flight tests were conducted to verify the integrity and availability of the installed FBG sensors and HUMS devices. A total of 74 flight tests were conducted using the HUMS implemented testbed aircraft, considering various maneuvers and abnormal conditions. The flight test results revealed that the FBG-based HUMS was successfully implemented on the testbed aircraft and operated normally under the actual flight test environments as well as providing reliable in-flight strain data from the FBG sensors over a long period of time.

https://iopscience.iop.org/article/10.1088/0964-1726/24/10/105003/pdf

Aircraft health and usage monitoring system for in-flight strain measurement of a wing structure

Aircraft industry is continually striving towards reducing the acquisition, operation and maintenance costs. Usage of advanced composite materials in primary aircraft structures have resulted in significant weight savings owing to their higher specific strength and specific stiffness. Composite structures, in spite of their inherent advantages, are prone to various damages. To detect and repair various structural damages that can occur during the service life of the aircraft, a thorough inspection schedule is implemented through conventional visual and Non Destructive Evaluation methods. Such scheduled inspections lead to considerable increase in maintenance cost & down-time of the aircraft. An online structural health monitoring (SHM) system consisting of well-designed sensor networks incorporated in the structure along with necessary hardware and software can provide information about the structure, thereby leading to reporting of flaws or damages in real time. Such a system can provide inputs for condition based maintenance which can result in reduced maintenance cost. This paper presents the work carried out at CSIR-National Aerospace Laboratories towards developing a flight-worthy SHM system and its demonstration on an unmanned aerial vehicle (UAV). Sensor selection, characterization, instrumentation design, algorithm development towards damage detection & load estimation at lab level and implementation of the technology on a UAV are discussed in this paper.

/pdf/structural-health-monitoring-of-composite-aircraft-lwspoc7j9z.pdf

Structural Health Monitoring of Composite Aircraft Structures Using Fiber Bragg Grating Sensors

Detection of hidden damages such as disbonds and delaminations are of relevance to the safety and maintenance of composite airframe structures. This study explores damage identification and load estimation using artificial neural networks (ANNs) on a composite test box. The objective is to detect disbond between spar and skin of the composite box using strain measurements made using fiber optic sensors. A novel approach is devised to create disbonds of various lengths using a non-adhesive insert between top skin and flange of centre spar. Initially a large disbond is created and progressively the disbond size is reduced in stages to obtain a healthy structure. The composite box is loaded at every stage and strains are acquired at various locations in the box using fiber Bragg grating (FBG) sensors. The difference in strains between healthy and unhealthy stages of the box is indicative of the presence of damage, as well as its extent and the loads acting on the structure. ANNs are trained using data generated from numerical models of the composite test box for healthy and disbond cases. These trained ANNs are then used to estimate the applied load, disbond size and disbond location using experimental strain data.

Disbond detection and load estimation on a composite test box using Fiber Bragg grating sensors

This study explores damage identification and load estimation in composite structures using Artificial Neural Networks (ANNs) and its application to a composite test box. The test box contains a debond between its spar and skin. The box was loaded and strains were captured at several locations using Fiber Bragg Grating (FBG) sensors as well as strain gages. The difference in strains between healthy and unhealthy box is indicative of the presence of damage, as well as its extent and the loads seen by the box. ANNs were trained using data generated from finite element (FE) analyses of the test box. These trained ANNs were then used to estimate the applied load, debond size and location on the box. Damage and load predicted by the ANNs were verified using tests on the box.

Debond Detection and Load Estimation Using Fiber Bragg Grating Sensors on a Composite Test Box – Part II (Algorithm Development)

The advent of composite co-cured and co-bonded integrated construction in aircraft structures has led to the replacement of fastened joints with bonded joints between the skins and the stiffeners. Skin-stiffener debonds could occur due to impact or other operational reasons and is usually internal. Structural safety can be impaired if the debond is located in compression/ shear zones and is sufficiently large. This paper presents finite element model of a carbon fibre composite structure with debond. The modeling technique is applied to a composite wing box. A debond was intentionally introduced in the box during fabrication. Various types of tests were performed in presence of debond. Static normal strains were captured during these tests using Fibre Bragg Grating sensors and strain gauges. Finally the strains captured during tests were compared with the strains predicted by the finite element analyses of implemented model of wing box.

Saransh Jain

Papers

Structural Health Monitoring of Composite Aircraft Structures Using Fiber Bragg Grating Sensors

Disbond detection and load estimation on a composite test box using Fiber Bragg grating sensors

Debond Detection and Load Estimation Using Fiber Bragg Grating Sensors on a Composite Test Box – Part II (Algorithm Development)

Prediction of Strains in the Debond Region of a Composite Box Structure