Condition-based Health Management
A large amount of our engineering infrastructure today is ageing would this be aircraft, ground vehicles, ships or buildings. Damage is a consequence of loads being applied to those engineering structures which has to be tolerated from a design point of view. Maintenance is the action resulting as a consequence and the more a structure ages the more maintenance and specifically inspection is required. Condition-based and structural health monitoring (SHM) and management is an emerging engineering discipline that involves state-of-the-art research developments in sensing technologies, signal processing, diagnostics and prognostics, mechanics and computational modeling, data mining, instrumentation and control. The goal of this multidisciplinary area is the transition from traditional time-based scheduled maintenance schemes to the condition-based maintenance (CBM) and complete life-cycle monitoring and management of mechanical, civil, and aerospace structural systems. Such a transition is paramount for reasons associated with reduced maintenance costs throughout the life cycle of the structure, increased safety, and unprecedented performance leading to resilient and self-sustainable structural systems.
The objective of SHM is to identify the condition of a structure based on in situ measurements obtained via appropriate sensing technologies and analyze the data using advanced signal processing methods, engineering models, and optimal decision making schemes. SHM involves the observation of a structure or mechanical system over time using periodically spaced measurements, the extraction of damage-sensitive features from these measurements and the statistical analysis of these features to determine the current state of system health. In addition, novel SHM approaches involve the integration of data-based with physics-based and computational modeling approaches in order to achieve increased accuracy in the estimation of the structural health via additional physical insight and enable the prognosis of the remaining useful life of the structure.
At FEAC Engineering we have a world-class team working on cutting-edge state-of-the-art SHM technologies, spanning the areas related to novel sensing technologies, structural dynamics and aeroelasticity, real-time SHM diagnostics and prognostics, damage tolerance, high0fidelity multi-physics computational modeling, and structural control.
Engineering structures today are continuously ageing, would those be in civil engineering, energy generation or aeronautics, to just name a few. Civil engineering buildings such as houses or bridges are not truly designed for a finite life, although one is aware that those will not last forever. Almost all private and government industries want to detect damage in their products as well as in their manufacturing infrastructure at the earliest possible time. Such detection requires these industries to perform some form of SHM and is motivated by the potential life-safety and economic impact of this technology. Finally, many portions of the existing technical infrastructure are approaching or exceeding their initial design life. As a result of economic issues, these civil, mechanical and aerospace structures are being used in spite of aging and the associated damage accumulation. Therefore, the ability to monitor the health of these structures is becoming increasingly important.
Most current structural and mechanical system maintenance is done in a time-based mode. SHM is the technology that will allow the current time-based maintenance philosophies to evolve into more cost effective condition-based maintenance philosophies. The concept of condition-based maintenance is that a sensing system on the structure will monitor the system response and notify the operator that damage has been detected. Life-safety and economic benefits associated with such a philosophy will only be realized if the monitoring system provides sufficient warning such that corrective action can be taken before the damage evolves to a failure level. The trade-off associated with implementing such a philosophy is that it requires a more sophisticated monitoring hardware to be deployed on the system and it requires a sophisticated data analysis procedure that can be used to interrogate the measured data.
Finally, many companies that produce high capital expenditure products, such as airframes, jet engines and large construction equipment would like to move to a business model where they lease this equipment as opposed to selling it. With these models the company that manufactures the equipment would take on the responsibilities for maintenance of that equipment. SHM has the potential to extend the maintenance cycles and, hence, keep the equipment out in the field where it can continue to generate revenues for the owner. Also, the equipment owners would like to base their lease fees on the amount of system life used up during the lease time rather than on the current simple time-based lease fee arrangements. Such a business model will not be realized without the ability to monitor the damage initiation and evolution in the rental hardware.
- Development of integrated systems for SHM to enable the transition to condition-based maintenance of mechanical, civil, and aerospace structures. Experience in vibration-based methods, acousto-ultrasonics-based methods, and electromechanical impedance methods for metallic structures and composites.
- Development of complete SHM systems for various industries: Civil Infrastructure (bridges, buildings, roads), renewable energy (wind turbines, off-shore systems, etc., automotive, aerospace, oil and gas (offshore platforms, pipelines), magnets and superconductors, industrial Equipment (rotating machinery, bearings, etc.)
- Experience in detecting various damage types: damage in composites in the form of delamination, matrix cracking, debond, and cracks, adhesively bonded joints, bolted joints, fatigue cracks in metallic and composite structures, cracks in RC structures, etc.
- Design and structural integration of appropriate sensing approaches for SHM based on high-fidelity computational modeling, design optimization, and deep knowledge of state-of-the-art SHM methods. Experience in sensing technologies based on accelerometers, strain gauges, piezoelectric transducers, and fiber optics. Capability for multi-modal sensor networks based on the specific structural challenges and damage modes.
- Development of optimized methods for early damage detection, localization, and quantification for mechanical, civil, and aerospace structures. Capability for real-time analysis and assessment.
- Structural analysis based on integrated data-based and FEM/BEM-based approaches. We build high-fidelity computational models that are updated with measurements obtained from real structures to achieve the highest possible accuracy for complex structures operating in dynamic environments under uncertainty.
- Data analysis based on state-of-the-art system identification, statistical signal processing, and machine learning approaches. Development of integrated systems with data acquisition and analysis capabilities based on custom-designed hardware and software.
- Big Data analysis along with our in-house “Smart Data” analysis techniques based on the correlation of physics-based and data-based approaches.
Advancements in Composite Aero-structures
- Design of composite aerospace structures and structural components (wings, fuselage, primary and secondary structural components) based on high-fidelity computational models and design optimization approaches.
- Design of self-sensing self-diagnostic composite materials: (i) Integration of micro-sensors in the composite layup to enable self-sensing capabilities. (ii) Integration of electronics, micro-controllers and signal processing units for real-time data processing and communications. (iii) Real-time data analysis and assessment. The above procedure results in intelligent structures with high-resolution state-sensing, awareness and self-diagnostic capabilities.
- Static and dynamic simulations based on FEM/BEM modeling approaches. Damage tolerance and fatigue analysis. Failure mode analysis, buckling behavior, crash performance, etc.
- Model updating and calibration based on experimental data obtained from prototype coupons or actual structural components. Validation of simulations and models via experimental results and analysis.