Towards CyberSHM: autonomous acousto-ultrasonic health monitoring of operational composite structures
Lead Research Organisation:
CARDIFF UNIVERSITY
Department Name: Sch of Engineering
Abstract
Continuous monitoring of in-service safety-critical structures for real-time assessment of their operational health is receiving significant attention and is a highly topical area of research. This is can be attributed, among others, to the following two factors.
i) The rapid evolution of next-generation complex composite structures and their ubiquitous use as lightweight structures in several industries ranging from aerospace to offshore/onshore energy infrastructure, automotive and nuclear industry.
ii) The significant advancement of automation within a data-rich environment and the immense appetite of industries to leverage its benefits for transforming their traditional, often interventionist, practices.
Significant research investment into next-generation complex composite structures (such as the ongoing EPSRC grant EP/T011653/1) and their rapid uptake in industrial usage has brought to the fore concerns and challenges around monitoring of these structures. Investigations into the susceptibility of these structures to subtle, barely visible damages (like hidden debonding, fibre/matrix-cracking) reveal that the latter can significantly jeopardize the structural integrity and can lead to catastrophic failures. The recent multiple catastrophic accidents in the passenger flights involving aeroplanes manufactured by the world's erstwhile largest planemaker has rightly enhanced the scrutiny on the safety, serviceability and suitability of such structures for public use. This is coupled with objectives for employing greener and sustainable structures (to meet the global emissions target as pledged in the Paris Climate Agreement 2016) and reducing operational costs associated with their inspection and maintenance without compromising on safety.
Concurrently, with a paradigmatic shift towards industrial internet of things within Industry4.0 with ubiquitous, pervasive computing coupled with advanced sensing and communication technologies, it has become a necessity to develop structural health monitoring (SHM) solutions of safety-critical engineering structures which are abreast of, can reap the benefits of and are able to fit seamlessly into this intelligent, data-rich environment of automation.
The proposal is aimed at fundamental scientific investigation into and the technological implementation of monitoring of lightweight composite structures to bridge the gap between the conceived futuristic vision of SHM and the existing interventionist practices of evaluating structural health. The objective of this project is to address the challenge of real-time acousto-ultrasonic monitoring (akin to "listening for damages" and/or changes in structural response) and online damage identification of operational structures using a multi-pronged approach with the key components being -
a) physics-driven underlying model or digital equivalent of structural ultrasonic waveguides behaviour under various operational/ambient conditions,
b) the extraction, synchronization and utilization of structural acoustic fingerprints of damage events (such as tool drop, delamination, cracks) as collected by the onboard sensory network for data-driven training and classification of damage events and
c) a real-time damage identification toolbox (identifying the location, type and severity) which is both data-driven (in-situ sensor data) and model-informed (physics-based understanding of structural waveguides) to give quantified metrics of incipient damage along with their estimated confidence.
The project takes the novel approach of assimilating physics-based characterization structural acoustic characteristics with data from hybrid passive-active acousto-ultrasonic monitoring and interrogation of the monitored structures for a cyberphysical monitoring or CyberSHM of in-service structures.
i) The rapid evolution of next-generation complex composite structures and their ubiquitous use as lightweight structures in several industries ranging from aerospace to offshore/onshore energy infrastructure, automotive and nuclear industry.
ii) The significant advancement of automation within a data-rich environment and the immense appetite of industries to leverage its benefits for transforming their traditional, often interventionist, practices.
Significant research investment into next-generation complex composite structures (such as the ongoing EPSRC grant EP/T011653/1) and their rapid uptake in industrial usage has brought to the fore concerns and challenges around monitoring of these structures. Investigations into the susceptibility of these structures to subtle, barely visible damages (like hidden debonding, fibre/matrix-cracking) reveal that the latter can significantly jeopardize the structural integrity and can lead to catastrophic failures. The recent multiple catastrophic accidents in the passenger flights involving aeroplanes manufactured by the world's erstwhile largest planemaker has rightly enhanced the scrutiny on the safety, serviceability and suitability of such structures for public use. This is coupled with objectives for employing greener and sustainable structures (to meet the global emissions target as pledged in the Paris Climate Agreement 2016) and reducing operational costs associated with their inspection and maintenance without compromising on safety.
Concurrently, with a paradigmatic shift towards industrial internet of things within Industry4.0 with ubiquitous, pervasive computing coupled with advanced sensing and communication technologies, it has become a necessity to develop structural health monitoring (SHM) solutions of safety-critical engineering structures which are abreast of, can reap the benefits of and are able to fit seamlessly into this intelligent, data-rich environment of automation.
The proposal is aimed at fundamental scientific investigation into and the technological implementation of monitoring of lightweight composite structures to bridge the gap between the conceived futuristic vision of SHM and the existing interventionist practices of evaluating structural health. The objective of this project is to address the challenge of real-time acousto-ultrasonic monitoring (akin to "listening for damages" and/or changes in structural response) and online damage identification of operational structures using a multi-pronged approach with the key components being -
a) physics-driven underlying model or digital equivalent of structural ultrasonic waveguides behaviour under various operational/ambient conditions,
b) the extraction, synchronization and utilization of structural acoustic fingerprints of damage events (such as tool drop, delamination, cracks) as collected by the onboard sensory network for data-driven training and classification of damage events and
c) a real-time damage identification toolbox (identifying the location, type and severity) which is both data-driven (in-situ sensor data) and model-informed (physics-based understanding of structural waveguides) to give quantified metrics of incipient damage along with their estimated confidence.
The project takes the novel approach of assimilating physics-based characterization structural acoustic characteristics with data from hybrid passive-active acousto-ultrasonic monitoring and interrogation of the monitored structures for a cyberphysical monitoring or CyberSHM of in-service structures.
People |
ORCID iD |
| Abhishek Kundu (Principal Investigator) |
Publications
Sikdar S
(2022)
Acoustic emission data based deep learning approach for classification and detection of damage-sources in a composite panel
in Composites Part B: Engineering
Sikdar S
(2023)
Deep learning for automatic assessment of breathing-debonds in stiffened composite panels using non-linear guided wave signals
in Composite Structures
| Description | The CyberSHM project has a work-package on developing sleek edge computing devices which can work as an integral component of smart structures, collecting processing and transmitting in-situ data on the edge. Traditionally this has required digital signal processing platforms which have large footprint making deploying them in a real-time monitoring challenging. The project has developed a CyberSHM platform whereby PC-on-chip type of devices manage to monitor and interrogate an operational structure with guided waves, process signals on the edge and deploy trained machine learning algorithms on the edge for essential decision making. A demonstrator for this has been developed and will be iteratively improved in the next phase of the project. A toolbox for predicting the dispersion characteristics of thin-walled laminated composite waveguides with elastic and geometrical singularities, representing damage, have been developed which is being validated experimentally. This is being deployed for a physics-informed approach for damage identification whereby the experimental data-driven models for mapping acousto-ultrasonic waves features to damage parameters is complemented by a physics-based predictions of dispersion. |
| Exploitation Route | The project team in conjuction with industry partners involved in this project will aim at implementing the CyberSHM systems for real-time strutural health monitoring environments. |
| Sectors | Aerospace Defence and Marine Construction Digital/Communication/Information Technologies (including Software) |
| Description | The findings of the project has been used for widening participation program of Cardiff University, such as with Community Gateway Partnership, by participating in public engagement events, particularly aimed at encouraging uptake of STEM subjects amongst school students in communities (like Grangetown project) with low representation in UK higher education. • I have delivered a public engagement event under the Museum After Dark banner at the National Museum Cardiff. Here I planned and led a demonstration called Sounds & Bridges where acoustic footprints of structures were demonstrated to members of the public. The big demonstration was made possible with the assistance of my team of PhD students and PDRAs. • I have organised and represented Cardiff School of Engineering in the Grange Careersfair week with a team of academics and student ambassadors to further the equality-diversity-inclusivity objectives of Cardiff School of Engineering in March 2022. I delivered a lecture along with two academic members to facilitate widening participation by showcasing the findings and impact of the CyberSHM project in practical engineering applications. The student ambassadors have highlighted the scope for students to pursue a career in STEM and the opportunities that exist at Cardiff School of Engineering. |
| First Year Of Impact | 2002 |
| Sector | Communities and Social Services/Policy,Education |
| Impact Types | Societal |
| Description | Knowledge Transfer Partnerships |
| Amount | £279,943 (GBP) |
| Funding ID | KTP012935 |
| Organisation | Innovate UK |
| Sector | Public |
| Country | United Kingdom |
| Start | 08/2021 |
| End | 08/2024 |
| Description | SmartExpertise |
| Amount | £111,884 (GBP) |
| Funding ID | 82504 |
| Organisation | Government of Wales |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2022 |
| End | 12/2022 |
| Description | Wales-Quebec joint call for proposals |
| Amount | £4,300 (GBP) |
| Funding ID | RES40869 |
| Organisation | Government of Wales |
| Sector | Public |
| Country | United Kingdom |
| Start | 11/2021 |
| End | 03/2023 |
| Title | A Deep Learning Model For Autonomous Damage Identification/Classification in Composites |
| Description | A Deep Learning Model is developed for autonomous damage (e.g., acoustic emission source, breathing debond) Identification/Classification in Composites |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2023 |
| Provided To Others? | No |
| Impact | A Deep Learning Model is developed for autonomous damage (e.g., acoustic emission source, breathing debond) Identification/Classification in Composites |
| Title | Edge-computing based SHM & NDE Setup |
| Description | Developing an Edge-computing based Structural Health Monitoring Setup for robust and real-time monitoring of aerospace composites using Acoustic Emission and Guided Wave propagation |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2023 |
| Provided To Others? | No |
| Impact | The Structural Health Monitoring Setup will provide robust and real-time monitoring of aerospace composites |
| Title | Semi-analytical Guided Wave Dispersion Model for Damaged Composites |
| Description | Developed a robust Semi-analytical Guided Wave Dispersion Model for Damaged Composites |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2022 |
| Provided To Others? | No |
| Impact | A robust Semi-analytical Guided Wave Dispersion Model is developed for healthy and damaged Composites |
| Title | CyberSHM |
| Description | The CyberSHM project includes a segment dedicated to the creation of sleek edge computing devices that can seamlessly integrate into smart structures. These devices are capable of collecting, processing, and transmitting data on-site, without the need for large digital signal processing platforms. The traditional approach of using such platforms has proven challenging for real-time monitoring due to their bulky nature. To address this, the project has developed the CyberSHM platform, where PC-on-chip devices are able to monitor and analyze operational structures using guided waves. These devices are equipped to process signals on the edge and deploy trained machine learning algorithms for crucial decision-making. A demonstrator for this platform has been created and will undergo further improvements during the next phase of the project. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2024 |
| Provided To Others? | No |
| Impact | The CyberSHM devices has the potential to make a significant impact in the field of structural health monitoring. Real-time monitoring of structures can be done more efficiently and effectively, without the challenges posed by bulky equipment. This technology allows for enhanced data analysis, leading to more accurate and timely decisions regarding the structural health of monitored systems. The ability to collect, process, and transmit data on-site enables quicker response times and improved overall structural safety. This research has the potential to revolutionize the way in which structures are monitored and maintained, ultimately leading to increased efficiency, cost savings, and improved structural integrity. Furthermore, the development of a demonstrator and the planned iterative improvements in the next phase of the project demonstrate the dedication to practical implementation and ensuring real-world impact. |
| Title | Deep Learning for damage identification |
| Description | A fully data-driven deep learning approach for identification of damage based on their acoustic emission characteristics have been developed which is capable of using AI. |
| Type Of Material | Data analysis technique |
| Year Produced | 2023 |
| Provided To Others? | Yes |
| Impact | A paper has been published on this which has already gathered several academic citations since last year. |
| Title | eSAFE model |
| Description | The eSAFE model enables analysis on dispersion of waveguides for any general layup of thinwalled laminated waveguides which has daamges characterised geometrical or elastic property changes across the laminar direction. This is a first of its kind of model which can study the effect of damage and anomalies on the dispersion characteristics of waveguides. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2024 |
| Provided To Others? | No |
| Impact | The academic impact of this model has been realised by two journal papers under preparation. The results have been presented at academic conferences and is being showcased to industry partners in the project. |
| Description | Collaboration with Airbus |
| Organisation | Airbus Group |
| Department | Airbus Operations |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Airbus has participated in joint research meetings and has provided input by steering the direction of the project and providing industrially relevant ideas for the project. |
| Collaborator Contribution | Airbus has participated in a research seminars for discussing the CyberSHM research plan and collaboration paths with the project partners. They are providing in-kind input to the project by steering the research output into industrially relevant outcomes. |
| Impact | Presentations have delivered from both sides (Cardiff & Airbus) for discussing the possible collaboration paths |
| Start Year | 2022 |
| Description | Collaboration with Mistras |
| Organisation | Airbus Group |
| Department | Airbus Operations |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | A close collaboration is being undertaken with Mistras in this CyberSHM project. Mistras is actively involved in sharing knowledge about structural health monitoring trends and requirements from an industry perspective. |
| Collaborator Contribution | Mistras is providing samples of decommissioned wind turbine blade sections which are being used in the research project. The blade sections will be tested for the performance of the CyberSHM toolboxes being developed in the project. Mistras being a leader in the field of SHM is providing inputs on the sensor hardware suitable for field testing. Their contribution to the project is in-kind and they participate in research steering committee meetings. |
| Impact | The collboration with Mistras has resulted in 1 journal article published in Composite Structures. The data collected for this paper were done with the instrumentation supplied by Mistras and used for the CyberSHM toolbox performance testing. |
| Start Year | 2022 |
| Description | Collaboration with Mistras |
| Organisation | Mistras Group Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | A close collaboration is being undertaken with Mistras in this CyberSHM project. Mistras is actively involved in sharing knowledge about structural health monitoring trends and requirements from an industry perspective. |
| Collaborator Contribution | Mistras is providing samples of decommissioned wind turbine blade sections which are being used in the research project. The blade sections will be tested for the performance of the CyberSHM toolboxes being developed in the project. Mistras being a leader in the field of SHM is providing inputs on the sensor hardware suitable for field testing. Their contribution to the project is in-kind and they participate in research steering committee meetings. |
| Impact | The collboration with Mistras has resulted in 1 journal article published in Composite Structures. The data collected for this paper were done with the instrumentation supplied by Mistras and used for the CyberSHM toolbox performance testing. |
| Start Year | 2022 |
| Description | Collaboration with Mistras |
| Organisation | Stanford University |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | A close collaboration is being undertaken with Mistras in this CyberSHM project. Mistras is actively involved in sharing knowledge about structural health monitoring trends and requirements from an industry perspective. |
| Collaborator Contribution | Mistras is providing samples of decommissioned wind turbine blade sections which are being used in the research project. The blade sections will be tested for the performance of the CyberSHM toolboxes being developed in the project. Mistras being a leader in the field of SHM is providing inputs on the sensor hardware suitable for field testing. Their contribution to the project is in-kind and they participate in research steering committee meetings. |
| Impact | The collboration with Mistras has resulted in 1 journal article published in Composite Structures. The data collected for this paper were done with the instrumentation supplied by Mistras and used for the CyberSHM toolbox performance testing. |
| Start Year | 2022 |
| Description | Collaboration with Mistras |
| Organisation | University of Sherbrooke |
| Country | Canada |
| Sector | Academic/University |
| PI Contribution | A close collaboration is being undertaken with Mistras in this CyberSHM project. Mistras is actively involved in sharing knowledge about structural health monitoring trends and requirements from an industry perspective. |
| Collaborator Contribution | Mistras is providing samples of decommissioned wind turbine blade sections which are being used in the research project. The blade sections will be tested for the performance of the CyberSHM toolboxes being developed in the project. Mistras being a leader in the field of SHM is providing inputs on the sensor hardware suitable for field testing. Their contribution to the project is in-kind and they participate in research steering committee meetings. |
| Impact | The collboration with Mistras has resulted in 1 journal article published in Composite Structures. The data collected for this paper were done with the instrumentation supplied by Mistras and used for the CyberSHM toolbox performance testing. |
| Start Year | 2022 |
| Description | Collaboration with Polish Academy of Sciences - IMP PAN |
| Organisation | Institute of Fluid Flow Machinery |
| Country | Poland |
| Sector | Public |
| PI Contribution | We have started a structured collaboration with Prof Wieslaw Ostachowicz and his research team in the Mechanics of Intelligent Structures Department at the Polish Academy of Sciences - IMP PAN, Gdansk, Poland. Through this collaboration, we planned research visits to conduct some specific experiments at IMP PAN using their state of the art environmental chamber, FBG-systems and ultrasonic interrogator. The collaboration is academic in nature and the group is making in-kind contribution to the project. |
| Collaborator Contribution | The academic partnership has been very fruitful for the project to exchange knowledge. Prof Ostachowicz group has collaborated with us for exploring new sensor technologies for CyberSHM. The collaboration has produced joint journal publication in Composite Structures, Conference publication , Conference Presentations, Organised Special Session in the EWSHM 2022 |
| Impact | • The collaboration has resulted in 2 journal publications • Organised Special Session in the EWSHM 2022. EWSHM is amongst the largest structural health monitoring conferences in Europe and our team in collaboration with Prof Ostachowicz organised the largest special session in this conference - "Machine learning and modelling in structural health monitoring" • submitted extended abstract for the IWSHM conference 2023 to take place in Stanford University. |
| Start Year | 2021 |
| Description | Collaboration with Stanford University |
| Organisation | Stanford University |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | We are exploring opportunities for collaboration with Stanford University's Prof F K Chang's research group for collaborative work on SHM in structures under environmentally extreme conditions which has applications in aerospace and renewable sector. The collaboration is academic in nature. We would be participating in the IWSHM 2023 conference organised by Prof FK Chang's group and would deliver talks at the host university. |
| Collaborator Contribution | Towards developing a structured research collaboration, we will be attending the IWSHM 2023 conference organized by Prof F.K. Chang and his team at the University of Stanford and discussing the possible joint research activities. The collaborative work is scheduled to be undertaken towards the latter half of the project. |
| Impact | Submitted an abstract to the IWSHM 2023, will participate in the IWSHM 2023 conference and discuss the possible research collaborations with Stanford |
| Start Year | 2023 |
| Description | Public Engagement - Grange Careers & Role Model Week |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Public/other audiences |
| Results and Impact | Demonstrated the Mechanical Engineering research activities, 'Sound & Bridges' and Inspired school children in Engineering Education |
| Year(s) Of Engagement Activity | 2022 |
| Description | Public Engagement Event - Museum After Dark, Cardiff |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Schools |
| Results and Impact | Demonstrated the CyberSHM team research activities, 'Sound & Structures' with hands-on experiments to 200+ school children and other general public. |
| Year(s) Of Engagement Activity | 2023 |