Metal structures and infrastructures subjected to demanding working conditions must be carefully monitored throughout their entire life cycle. In fact, high operating temperatures and interaction with aggressive environments produce significant variation of the mechanical characteristics of the materials, and eventually compromise the overall structural integrity. The evolution over time of metal properties can be determined in fast, cheap and non-destructive manner by hardness tests, processing the data that describe the geometry of the residual deformation left on the indented surface. The required equipment can be mounted on the arms of collaborative robots, and/or on frames that move on wheels or rails, to detect the material characteristics automatically, over large distances and with high spatial resolution. The reliability of such a diagnostic approach depends on the accuracy of the information that can be collected, in situ, by portable devices that perform 3D contactless measurement, and on the robustness of the data filtering and interpretation procedures. These issues are illustrated in this contribution.
Potentially Automated Mechanical Characterization of Metal Components by Means of Hardness Test Complemented by Non-Contact 3D Measurement
Bolzon, Gabriella
2022-01-01
Abstract
Metal structures and infrastructures subjected to demanding working conditions must be carefully monitored throughout their entire life cycle. In fact, high operating temperatures and interaction with aggressive environments produce significant variation of the mechanical characteristics of the materials, and eventually compromise the overall structural integrity. The evolution over time of metal properties can be determined in fast, cheap and non-destructive manner by hardness tests, processing the data that describe the geometry of the residual deformation left on the indented surface. The required equipment can be mounted on the arms of collaborative robots, and/or on frames that move on wheels or rails, to detect the material characteristics automatically, over large distances and with high spatial resolution. The reliability of such a diagnostic approach depends on the accuracy of the information that can be collected, in situ, by portable devices that perform 3D contactless measurement, and on the robustness of the data filtering and interpretation procedures. These issues are illustrated in this contribution.File | Dimensione | Formato | |
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