A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Unsupervised Fouling Reconstruction in the Pipe Bend
Guided wave tomography allows the investigation of extended areas with a limited number of measurements, typically using transducer arrays. Most imaging methods rely heavily on the material properties such as dispersion curves, that in the case of fouling deposition are not always known. In the case of complex shaped structures, geometrical anisotropy can bring additional complexity. Here we present an unsupervised machine learning approach based on the Gaussian process to detect and characterize the fouling in a pipe bend that relies only on the difference between clean/healthy and fouled/damaged measured signals. ; Peer reviewed
Unsupervised Fouling Reconstruction in the Pipe Bend
Guided wave tomography allows the investigation of extended areas with a limited number of measurements, typically using transducer arrays. Most imaging methods rely heavily on the material properties such as dispersion curves, that in the case of fouling deposition are not always known. In the case of complex shaped structures, geometrical anisotropy can bring additional complexity. Here we present an unsupervised machine learning approach based on the Gaussian process to detect and characterize the fouling in a pipe bend that relies only on the difference between clean/healthy and fouled/damaged measured signals. ; Peer reviewed
Unsupervised Fouling Reconstruction in the Pipe Bend
Iablonskyi, Denys (author) / Rasgado-Moreno, Carlos-Omar (author) / Ratassepp, Madis (author) / Klami, Arto (author) / Haeggström, Edward (author) / Salmi, Ari (author) / Department of Computer Science / Helsinki Institute for Information Technology / Department of Physics
2023-11-20
Conference paper
Electronic Resource
English
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