(Photo: 1663 Los Alamos Science and Technology Magazine. Schematic Source: Department of Civil and Environmental Engineering, MIT)
Structural Health Monitoring (SHM) began in the early 1800’s with railroad wheel-tappers, which used the sound of a hammer striking the train wheel to evaluate if damage was present. The IoT sensor proliferation that continues to increase the number of application instances will soon deliver this significant SHM concept, which is similar, yet different, than our Fault Detection and Diagnostics — nearer and nearer to our workstations (cautious optimism), because SHM will be incorporated into everything: buildings, bridges, every mode of transportation, as well as every large piece of HVAC equipment around us — that we will hopefully continue to integrate with in some manner. FAST COMPANY has the Connected Home Sweet Home covered, but it was this article by Craig Tyler, published in July 2013, in The Los Alamos Science and Technology Magazine, that really spells out the pervasiveness of this technology. Chuck Farrar and David Mascarenas, among other luminaries at the Engineering Institute at Los Alamos, a research and education collaboration between Los Alamos National Laboratory and the University of California, San Diego, are all about solving really sophisticated data-to-decision problems.
Fundamental Axioms of SHM IVa: Sensors cannot measure damage. Feature extraction through signal processing and statistical classification is necessary to convert sensor data into damage information (http://en.wikipedia.org/).
Did you know that sensors evolve? According to Eric Flynn, a colleague of David Mascarenas, and postdoctoral researcher at the Engineering Institute researcher at the Los Alamos Engineering Institute: “Over many different trials, the sensor network develops a lifetime of experience. Detector locations, or sets of locations, that do not help enough are like animals that are unfit for survival or reproduction; they are deleted from the “gene pool.” New sensor locations are introduced to replace the ones that are deleted, based on “mutation” and “breeding” among the remaining sensor “population,” in a process that repeats for each new “generation.” In this way, the 3D sensor locations “evolve” to their optimal configuration. Los Alamos Engineering Institute researchers working in the field of structural health monitoring (SHM) are developing sensor systems to track health and damage information for the nation’s major infrastructure objects—including buildings and bridges, power plants and industrial plants, ships and aircraft, and other large-investment equipment for transportation, entertainment, and scientific research. They are designing and building SHM hardware as well as developing algorithms to screen raw SHM sensor data reliably for evidence of structural degradation.”
More Background:
Los Alamos Engineering Institute researchers working in the field of structural health monitoring (SHM) are developing sensor systems to track health and damage information for the nation’s major infrastructure objects—including buildings and bridges, power plants and industrial plants, ships and aircraft, and other large-investment equipment for transportation, entertainment, and scientific research. They are designing and building SHM hardware as well as developing algorithms to screen raw SHM sensor data reliably for evidence of structural degradation.
Los Alamos Engineering Institute researchers working in the field of structural health monitoring (SHM) are developing sensor systems to track health and damage information for the nation’s major infrastructure objects—including buildings and bridges, power plants and industrial plants, ships and aircraft, and other large-investment equipment for transportation, entertainment, and scientific research. They are designing and building SHM hardware as well as developing algorithms to screen raw SHM sensor data reliably for evidence of structural degradation.
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