Design of a robust SHM system for composite structures

Abstract

Composites are becoming increasingly popular materials used in a wide range of applications on large-scale structures such as windmill blades, rocket motor cases, and aircraft fuselage and wings. For these large structures, using composites greatly enhances the operation and performance of the application, but also introduces extraordinary inspection challenges that push the limits of traditional NDE in terms of time and cost. Recent advances in Structural Health Monitoring (SHM) technologies offer a promising solution to these inspection challenges. But efficient design methodologies and implementation procedures are needed to ensure the reliability and robustness of SHM technologies for use in real-world applications. This paper introduces the essential elements of the design and implementation process by way of example. State-of-the-art techniques to optimize sensor placement, perform self-diagnostics, compensate for environmental conditions, and generate probability of detection (POD) curves for any application are discussed. The techniques are presented in relation to Acellent's recently developed SmartComposite System that is used to monitor the integrity of large composite structures. The system builds on the active sensor network technology of Acellent that is analogous to a built-in acousto-ultrasonic NDE system. Key features of the system include new miniaturized lightweight hardware, self-diagnostics and adaptive algorithm to automatically compensate for damaged sensors, reliable damage detection under different environmental conditions, and generation of POD curves. This paper will provide an overview of the system and demonstrate its key features.

SMART solutions for composite structures

“…Also, measuring the differences between adjacent baseline data sets and using these values as a measure of the environmental noise, automated threshold determination for each path can be achieved. This technique can be used to compensate for global temperature changes in the structure as well as temperature gradients across the structure [18]. When the new set of data is compared against the baseline data after the temperature calibration and there exists significant difference that exceeds the given threshold, then one can determine that there would be damage/defects on the structure.…”

Piezoelectric Transducer-Based Structural Health Monitoring for Aircraft Applications

“…However, traditional POD curves are generated through extensive testing which is not practical for every new structure and sensor configuration. To overcome this difficulty, Acellent has developed a method to compute the POD [14,162]. After a sensor layout has been defined and the operating paths have been determined, the user can select the option to generate POD curves.…”

Probability of detection, localization, and sizing: The evolution of reliability metrics in Structural Health Monitoring

“…Alternatively, performing several inspections on a series of representative damages, it is possible to develop a probability density function relative to the damage severity which is used to obtain an upper bound on the damage size. 196,197…”