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A 9-Step Process for Developing a Structural Health Monitoring System



"The portion of the structural health-monitoring process that has received the least attention in the technical literature is the development of statistical models to enhance the SHM (structural health monitoring) process", according to a book-length literature review (Sohn et al. 2004, p. 157). This article will help fill this gap by extensions to general SHM applications of the statistical advances made for the SHMs for emissions controls, mandated on all new cars and trucks sold in the developed world and in many developing countries. In the 1990s tightening legal mandates for "on-board diagnostics (OBDs)" pushed the Low Emissions Partnership of Chrysler, Ford and General Motors to fund research to (a) improve the statistical sophistication of their OBD work, and (b) help them negotiate with regulators. A summary of this research was embedded in the "8-step process for OBDs" described by Box et al. (2000). This paper will compare a 9-step extension of this Box et al. (2000) process with the 4-part SHM process of Ferrar et al. (2001), used by Sohn et al. (2004) to structure their literature review; see Table 1. There are similarities between the monitoring processes of Table 1 and the 6-step Structural Identification process of Catbas, Moon, and Aktan (2010), but the purposes can be different. Structural identification is often but not always conducted as part of monitor design, and monitors (i.e., monitoring systems) can be designed without a formal structural identification effort. Further comparison of structural identification and monitor design will not be attempted here.

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