Gayan Chanaka Kahandawa

Use of FBG Sensors for SHM in Aerospace Structures

This paper discusses the use of Fibre Bragg grating sensors (FBG) in structural health monitoring (SHM) of Fibre reinforced polymer (FRP) aerospace structures. The diminutive sensor provided the capability of embedding inside FRP structures in order to monitor vital potential locations for damage. Some practical problems associate with manufacturing process of FRP with embedded FBG sensors, interrelation of distortion to FBG spectra with damage, and interpretation of FBG spectral responses for identifying the damage will be discussed.

Estimation of strain of distorted FBG sensor spectra using a fixed FBGfilter circuit and an artificial neural network

Fibre Bragg Grating (FBG) sensors are extremely sensitive to changes of strain, and are therefore an extremely useful candidate for Structural Health Monitoring (SHM) systems of composite structures. Sensitivity of FBGs to strain gradients originating from damage was observed as an indicator of initiation and propagation of damage in composite structures. To date there have been numerous research works done on distorted FBG spectra due to damage accumulation under controlled environments. Unfortunately, a number of related unresolved problems remain in FBG-based SHM systems development, making the present SHM systems unsuitable for real life applications. This paper reveals a novel configuration of FBG sensors to acquire strain reading and an integrated statistical approach to analyse data in real time. The proposed configuration has proven its capability to overcome practical constraints and the engineering challenges associated with FBG-based SHM systems. A fixed filter decoding system and an integrated artificial neural network algorithm for extracting strain from embedded FBG sensor were proposed and experimentally proved. Furthermore, the laboratory level experimental data was used to verify the accuracy of the system and it was found that the error levels were less than 0.3% in strain predictions.

Prediction of obsolete FBG sensor using ANN for efficient and robust operation of SHM systems

ncreased use of FRP composites for critical load bearing components and structures in recent years has raised the alarm for urgent need of a comprehensive health mentoring system to alert users about integrity and the health condition of advanced composite structures. A few decades of research and development work on structural health monitoring systems using Fibre Bragg Grating (FBG) sensors have come to an accelerated phase at the moment to address these demands in advanced composite industries. However, there are many unresolved problems with identification of damage status of composite structures using FBG spectra and many engineering challenges for implementation of such FBG based SHM system in real life situations. This paper details a research work that was conducted to address one of the critical problems of FBG network, the procedures for immediate rehabilitation of FBG sensor networks due to obsolete/broken sensors. In this study an artificial neural network (ANN) was developed and successfully deployed to virtually simulate the broken/obsolete sensors in a FBG sensor network. It has been found that the prediction of ANN network was within 0.1% error levels.

NIR Fibre Bragg Grating as Dynamic Sensor: An Application of 1D Digital Wavelet Analysis for Signal Denoising

During the past decade, many successful studies have evidently shown remarkable capability of Fiber Bragg Gratings (FBG) sensor for dynamic sensing. Most of the research works utilized the 1550 nm wavelength range of FBG sensors. However near infra-red (NIR) FBG sensors can offer the lower cost of Structural health Monitoring (SHM) systems which uses cheaper silicon sources and detectors. Unfortunately, the excessive noise levels that experienced in NIR wavelengths have caused the rejection of sensor that operating in this range of wavelengths for SHM systems. However, with the appropriate use of signal processing tools, these noisy signals can be easily ‘cleaned’. Wavelet analysis is one of the powerful signal processing tools nowadays, not only for time-frequency analysis but also for signal denoising. This present study revealed that the NIR FBG range gave good response to impact signals. Furthermore, these ‘noisy’ signals’ response were successfully filtered using one dimensional wavelet analysis.

Structural health monitoring technologies and next-generation smart composite structures

Over the past few decades there have been many breakthroughs in the development of smart materials and miniaturisation of sensors. Furthermore a number of nano technologies have underpinned the present rapid development of smart structures. The innovations and advancement of micro and nano-scale sensor technologies have brought the development of smart structures closer to reality, attracting enormous research attention. Increased usage of fibre reinforced composites in advanced engineering fields such as Space, Aerospace, Energy, Automobile and Civil infrastructures has created an emerging need for smart/intelligent structures in next generation designs. The focus of this technology is to bring to fruition self-prognosis/diagnosis and self-healing capabilities within composite structures. The complex nature of damage mechanics and unresolved issues, such as progressive damage accumulation durability/residual-life, remain and there has been rising concern with composite material failures, leading to this demand intelligent and live diagnostics within so-called “smart” composite structures. This is especially important for aerospace vehicles such as helicopters that need to perform close to optimum for all its constituent parts. The detection of structural damage such as cracks and delamination in fibre composite structures remains an important issue for damage identification - it is an important, basic building block within the development of smart/intelligent structures in aerospace application. Global awareness of structural health monitoring systems (SHM), smart structures & materials significantly changing design, manufacturing and maintenance management systems of multi billion dollars worth defence and critical infrastructures in the world. Due to this reason, aerospace, defence, chemical, automobile, and civil engineering fields have been engaged in an extremely difficult task of finding SHM systems and smart structure for the new generation products and structures. Each engineering fields have distinct limitations and challenges at various levels of difficulties in adopting principles of SHM and the replacement of traditional materials with smart materials. In this context exchange of specific information related to SHM systems and smart structures seems to be bounded by IP issues and commercially confidential environments. Due to this reason, advancements of SHM systems and smart structures are facing serious drawbacks. Globally SHM systems and smart structures are developed by using fundamental physical phenomenon/properties inherited by the materials. The stress/strain, acoustic emission and wave propagation, vibration and damping of material are some of the physical phenomenon/properties that widely use in SHM field. Furthermore the smart materials developed with the advancement of new materials development field has contributed in development of smart structures. The use of electrically activated polymers and shape memory alloys are good examples of advanced smart materials. Though there has been a significant involvement in smart materials, smart structures are not limited to use of materials and integrated SHM. The smart structures are developed with innovative design concepts using the materials inherent physical and mechanical properties. As such the SHM and smart structures are not only depending on sensors and smart materials along but also innovative design and manufacturing methods. This book mainly intends to collect the advancements of unbound applied research in SHM and smart structures fields. The collection of the advances research work on generic SHM and smart structures will be expanded with the potentially applicable research in the field.

Development of Embedded FBG Sensor Networks for SHM Systems

Comprised of chapters authored by leading researchers in their respective fields, this edited book showcases exciting developments in general embedded sensor technologies, general sensor technologies, sensor response interrogation and data ...

Integrated FBG Sensor Responses and Full Field Thermo-elastic Stress Approach to Monitor Damage Accumulation in Glass Fibre Reinforced Composite Plates

Monitoring internal damage status of advanced composite components with distributed sensor network has shown significant success in recent research works. However, application of such a system in a full scale structure is a critically challenging task and maintaining such a system during life time operations is an extremely difficult. An additional non-contactable full field strain measurement system being used to measure outer surface strain field of a composite sample while an embedded FBG sensor closer to an internal void being used to monitor localized strain variation. Recent developments in miniature low-cost microbolometer technology have paved the way to use full field thermo-elastic stress mapping using relatively inexpensive Infra-Red cameras. This paper details a comparison of strain measurements observed from FBG sensors embedded in a composite plate sample at a closer location to a void and full field thermo-elastic stress map. The test coupons were fabricated with a purposely created delamination and sample was loaded by quasi-static and low cycle fatigue uni-axial loads. The FBG responses and IR images were recorded in frequent intervals in order to track the delamination growth. Further the strain variations were studied using a detailed FEA and compared with experimental strain and full field Thermo-elastic stress map. doi: 10.12783/SHM2015/82

Indexing damage using distortion of embedded FBG sensor response spectra

Structural Health Monitoring Systems based on embedded FBG sensors, to identify damage conditions, are largely dependent on the spectral distortion of the sensors. The uneven stress gradient occurring along the grating of FBG sensors, due to damage inside composite structures can be estimated by analysing significant changes that appear in the FBG response spectra. However, the stochastic nature of the distorted shape of the FBG spectra makes it difficult to interpret and quantify the existing damage at the location of the FBG sensors. There are several indexing methods proposed by researchers. We have previously presented a novel concept of the “Distortion Index (DI)” which is defined using distorted spectra of FBG sensors. It was observed that the DI increases with the increase in damage size. The Distortion Index (DI) is introduced to create a correlation between the damage and the distortion of the response spectra of a FBG sensor. This index provides the ability to generalise the distortion of FBG spectra for a particular structure. The index can be used to quantify the damage in the structure relative to its original condition, which can be the condition of structure during a regulated time, i.e. a month uninterrupted operation or first hours in operation, of a structure can be used as no damage condition. In this paper we discuss the application of distortion index and comparison with available several other indexes.