Structural health monitoring of offshore wind turbines: A review through the Statistical Pattern Recognition Paradigm

Offshore Wind has become the most profitable renewable energy source due to the remarkable development it has experienced in Europe over the last decade. In this paper, a review of Structural Health Monitoring Systems (SHMS) for offshore wind turbines (OWT) has been carried out considering the topic as a Statistical Pattern Recognition problem. Therefore, each one of the stages of this paradigm has been reviewed focusing on OWT application. These stages are: Operational Evaluation; Data Acquisition, Normalization and Cleansing; Feature Extraction and Information Condensation; and Statistical Model Development. It is expected that optimizing each stage, SHMS can contribute to the development of efficient Condition-Based Maintenance Strategies. Optimizing this strategy will help reduce labor costs of OWTs׳ inspection, avoid unnecessary maintenance, identify design weaknesses before failure, improve the availability of power production while preventing wind turbines׳ overloading, therefore, maximizing the investments׳ return. In the forthcoming years, a growing interest in SHM technologies for OWT is expected, enhancing the potential of offshore wind farm deployments further offshore. Increasing efficiency in operational management will contribute towards achieving UK׳s 2020 and 2050 targets, through ultimately reducing the Levelised Cost of Energy (LCOE)

Low-cost wireless structural health monitoring of bridges

Nowadays, low-cost accelerometers are getting more attention from civil engineers to make Structural Health Monitoring (SHM) applications affordable and applicable to a broader range of structures. The present accelerometers based on Arduino or Raspberry Pi technologies in the literature share some of the following drawbacks: (1) high Noise Density (ND), (2) low sampling frequency, (3) not having the Internet’s timestamp with microsecond resolution, (4) not being used in experimental eigenfrequency analysis of a flexible and a less-flexible bridge, and (5) synchronization issues. To solve these problems, a new low-cost triaxial accelerometer based on Arduino technology is presented in this work (Low-cost Adaptable Reliable Accelerometer—LARA). Laboratory test results show that LARA has a ND of 51 µg/vHz, and a frequency sampling speed of 333 Hz. In addition, LARA has been applied to the eigenfrequency analysis of a short-span footbridge and its results are compared with those of a high-precision commercial sensor.The authors are indebted to the Spanish Ministry of Economy and Competitiveness for the funding provided through the research project BIA2017-86811-C2-1-R directed by José Turmo and BIA2017-86811-C2-2-R. All these projects are funded with FEDER funds. The authors are also indebted to the Secretaria d’ Universitats i Recerca de la Generalitat de Catalunya, Catalunya, Spain, for the funding provided through Agaur (2017 SGR 1482). It is also to be noted that funding for this research has been provided for the Seyedmilad Komarizadehasl by the Spanish Agencia Estatal de Investigación del Ministerio de Ciencia Innovación y Universidades grant and the Fondo Social Europeo grant (PRE2018-083238).Peer ReviewedPostprint (published version

Measurement of acceleration response functions with scalable low-cost devices. An application to the experimental modal analysis

Producción CientíficaOne of the most popular options in the Structural Health Monitoring field is the tracking of the modal parameters, which are estimated through the frequency response functions of the structure, usually in the form of accelerances, which are computed as the ratio between the measured accelerations and the applied forces. This requires the use of devices capable of synchronously recording accelerations at several points of the structure at high sampling rates and the subsequent computational analysis using the recorded data. To this end, this work presents and validates a new scalable acquisition system based on multiple myRIO devices and digital MEMS (Micro-Electro-Mechanical System) accelerometers, intended for modal analysis of large structures. A simple form of this system was presented by the authors in a previous work, showing that a single board with some accelerometers connected to it got to obtain high quality measurements in both time and frequency domains. Now, a larger system composed by several slave boards connected and synchronized to a master one is presented. Delays lower than 100 ns are found between the synchronised channels of the proposed system. For validation purposes, a case study is presented where the devices are deployed on a timber platform to estimate its modal properties, which are compared with the ones provided by a commercial system, based on analog accelerometers, to show that similar results are obtained at a significantly lower cost.Junta de Castilla y León - FEDER (VA095P17 y VA228P20)Ministerio de Ciencia e Innovación y Ministerio de Universidades - FEDER (RTI2018-098425