Structural Health Monitoring (SHM) denotes the ability to detect and interpret adverse "changes" in a structure in order to improve safety and reduced inspection costs. Essentially overall life-cycle costs can be minimized by mitigating unnecessary maintenance actions and manual non-destructive evaluation (NDE) with automated, built-in systems. In this exciting field, non-invasive detection techniques are integrated into a structure to continuously monitor components for damage such as cracks or delamination or degradation such as corrosion or abrasion. SHM is receiving increasing attention, particularly from the commercial and military aviation community, in order to eliminate scheduled manual inspections in lieu of condition-based maintenance for more efficient design practices and more accurate component repair and replacement decisions. This methodology shift could result in a significant savings in the overall cost of ownership of a vehicle, as well as significant gains in operational safety.

MDC has emerged as an industry leading Structural Health Monitoring company, conducting research in nearly every aspect of this discipline. MDC engineers have achieved significant advancements in the state-of-the-art for SHM architecture, infrastructure, sensors, hardware, packaging, modeling and algorithms, leading to a robust portfolio of patented and patent-pending technologies. SHM investigations at MDC have focused both on the maturation of proven methods for near term deployment as well as pushing the envelope with revolutionary new technologies for future implementation. MDC frequently collaborates with top universities, small businesses, government agencies and major aerospace corporations to maintain superior SHM technology.

The methodology for SHM research at MDC has been Modeling, Evaluation and Distributed Infrastructure Components (MEDIC). MEDIC is not just an acronym, but a powerful set of maturing concepts leading to intelligent and efficient SHM. Modeling is the first important step in implementing any SHM system. In the pre-installation phase, modeling helps facilitate sensor placement and conveys a good understanding of the interaction between the sensors, the material, and any defects that may be present. MDC has also demonstrated the use of models for accurate algorithm development, such as model-augmented pattern recognition, where parametric finite element models are used to generate state dictionaries rather than extensive physical testing. Furthermore, in the post-installation phase models can integrate diagnostic estimations to present prognostic predictions.

Evaluation refers to the NDE methods that are integrated with the structure, such a guided waves (GW), frequency response (FR) or acoustic emission (AE). Selection of the appropriate monitoring method requires a good understanding of the structure and customer requirements. Optimal sensing and/or excitation elements are then chosen and mounted on the structure in appropriate locations. Finally, diagnostic algorithms are developed to translate results into material health. Essentially the structure serves as a transfer function, where excitations are the inputs, sensors signals are the outputs, and the state of the structure dictates specific response characteristics.

Infrastructure components refer to the remaining elements necessary to facilitate damage detection, including: signal conditioning, amplification, data acquisition, function excitation, memory, microprocessing, communication and power. One of the most novel aspects of the MDC SHM methodology, is our patented distributed infrastructure, where each of these elements has been integrated into micro-miniature hardware node local to each sensor rather than accumulating all of the electronics in a single remote location. There are several benefits to distributed acquisition and computation. First, sensor signals are of much higher fidelity since there are no exposed leads for introduction of electrical noise, and there are no cables to attenuate the signals through stray capacitance. Second, by digitizing the analog signals locally, digital data can be placed on a common serial bus (CAN, FireWire, Ethernet, etc), thereby greatly minimizing the weight and complexity of cabling as opposed to individual wires going between each sensor element and central acquisition hardware. Third, since the data has been digitized, local processing can greatly reduce the volume of data that need to be transmitted through the bus by various feature extraction, reduction and compression techniques. Finally, the overall mass of the system is greatly reduced through the elimination of cables, connectors, additional amplifiers, repeaters, and other bulky off-the-shelf hardware. Overall, MDC firmly believes that only through an integrated MEDIC approach can SHM be successfully realized for a commercial application. While this methodology requires a decent amount of up-front effort in modeling and experimental calibration, the resulting payoff will return on the initial investment exponentially.

Click here for a downloadable introduction to SHM presentation and for MDC's SHM capabilities.