10 Oct 2022
 | 10 Oct 2022
Status: a revised version of this preprint was accepted for the journal WES.

Population Based Structural Health Monitoring: Homogeneous Offshore Wind Model Development

Innes Murdo Black, Moritz Werther Häckell, and Athanasios Kolios

Abstract. This is a development of the preceding paper that introduced the idea and methodology of population-based structural health monitoring (PBSHM). PBSHM involves transferring knowledge from one structure to a different structure so that predictions about the structural health on each of the members in the population can be inferred. One of the most important aspects of PBSHM involves using the information on the source domain structure and the target domain structure to create an effective classifier. Domain adaptation is a subcategory of transfer learning that can create a general classifier using both the source and target domain structures to create an enhanced overall classifier of the entire population. This paper presents a novel domain adaptation model for PBSHM in offshore wind.

Innes Murdo Black et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2022-93', Anonymous Referee #1, 04 Nov 2022
    • AC1: 'Reply on RC1', Innes Black, 30 Jan 2023
  • RC2: 'Comment on wes-2022-93', Anonymous Referee #2, 30 Dec 2022
    • AC2: 'Reply on RC2', Innes Black, 30 Jan 2023
  • RC3: 'Comment on wes-2022-93', Anonymous Referee #3, 05 Jan 2023
    • AC3: 'Reply on RC3', Innes Black, 30 Jan 2023
  • AC4: 'Comment on wes-2022-93', Innes Black, 10 Feb 2023

Innes Murdo Black et al.

Innes Murdo Black et al.


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Short summary
Population based structural health monitoring is a low-cost monitoring campaign. The cost reduction from this type of digital enabled asset management tool is manifested by sharing information, in this case a wind farm foundation, within the population. By sharing the information in the wind farm this reduces the amount of sensors and physical model updating, reducing the cost of the monitoring campaign.