Charles R. Farrar, Los Alamos National Laboratory

The process of implementing a damage detection strategy for aerospace, civil, and mechanical engineering infrastructure is referred to as structural health monitoring (SHM). This process 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. For long-term SHM, the output of this process is periodically updated information regarding the ability of the structure to continue to perform its intended function in light of the inevitable aging and degradation resulting from the operational environments. Under an extreme event, such as an earthquake or unanticipated blast loading, SHM is used for rapid condition screening. This screening is intended to provide, in near real time, reliable information about system performance during such extreme events and the subsequent integrity of the system. Once damage is detected, damage prognosis (DP) is employed to predict the remaining useful life of a system, given some estimate of the future loading conditions that the system will experience. Currently, for most complex engineering systems accurate DP is not feasible with existing engineering capabilities. To date, SHM and DP studies have for the most part been carried out independent of the materials science community.

It is the author’s speculation that damage detection, as determined by changes in the dynamic response of systems, has been practiced in a qualitative manner, using acoustic techniques (e.g., tap tests on train wheels), since modern humans have used tools. More recently, this subject has received considerable attention in the technical literature. However, with the exception of condition monitoring of rotating machinery, there are very few instances in which SHM technology has made the transition from research to practice.

A review of the literature reveals several outstanding challenges for transitioning SHM technology from research to practice. These challenges include the following:

  • Structural monitoring versus structural health monitoring. Many sensor systems currently being deployed on real-world structures are actually structural monitoring systems, as opposed to SHM systems. They are simply sparse arrays of sensors deployed with no a priori definition of the damage to be detected and no definition of the methods for feature extraction and statistical classification that will be used to identify damage.

  • Local versus global damage detection. The most fundamental challenge is the fact that damage is typically a local phenomenon and may not significantly influence the global response of a structure that is normally measured during operation.

  • Defining damage a priori. The success of any damage detection technique will be directly related to the ability to define the damage that is to be detected in as much detail as possible and in as quantifiable terms as possible.

  • Defining the requisite sensing system properties. A significant challenge for SHM is to develop the capability to define the required sensing system properties before field deployment and, if possible, to demonstrate that the sensor system itself will not be damaged when deployed in the field.

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