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Table 5 Damage detection, case 2

From: Fully convolutional networks for structural health monitoring through multivariate time series classification

\(\varvec{f}_{\varvec{min}}\) - \(\varvec{f}_{\varvec{max}}\)(Hz)

\(\varvec{\lbrace {\mathcal {F}}_{*} \rbrace }\)

\(\varvec{A}^{\varvec{d}}\)

\(15-17\)

\(\{{\varvec{u}}^{sh}_i\}_{i=1}^8\)

0.998

\(15-17\)

\(\{{\varvec{u}}^{ax}_i\}_{i=1}^8\)

0.997

\(15-17\)

\(\{{\varvec{u}}^{sh}_i\}_{i=1}^8\) and \(\{{\varvec{u}}^{ax}_i\}_{i=1}^8\)

0.999

\(5-7\)

\(\{{\varvec{u}}^{sh}_i\}_{i=1}^8\)

0.996

\(5-7\)

\(\{{\varvec{u}}^{ax}_i\}_{i=1}^8\)

0.892

\(5-7\)

\(\{{\varvec{u}}^{sh}_i\}_{i=1}^8\) and \(\{{\varvec{u}}^{ax}_i\}_{i=1}^8\)

0.998

  1. Accuracy \({\mathbb {A}}_{d}\) of the classifier \({\mathcal {G}}_d\) evaluated on \({\mathbb {D}}^d_{test}\)