RESUMO
Operations and maintenance (O&M) of floating offshore wind turbines (FOWTs) require regular inspection activities to predict, detect, and troubleshoot faults at high altitudes and in harsh environments such as strong winds, waves, and tides. Their costs typically account for more than 30% of the lifetime cost due to high labor costs and long downtime. Different inspection methods, including manual inspection, permanent sensors, climbing robots, remotely operated vehicles (ROVs), and unmanned aerial vehicles (UAVs), can be employed to fulfill O&M missions. The UAVs, as an enabling technology, can deal with time and space constraints easily and complete tasks in a cost-effective and efficient manner, which have been widely used in different industries in recent years. This study provides valuable insights into the existing applications of UAVs in FOWT inspection, highlighting their potential to reduce the inspection cost and thereby reduce the cost of energy production. The article introduces the rationale for applying UAVs to FOWT inspection and examines the current technical status, research gaps, and future directions in this field by conducting a comprehensive literature review over the past 10 years. This paper will also include a review of UAVs' applications in other infrastructure inspections, such as onshore wind turbines, bridges, power lines, solar power plants, and offshore oil and gas fields, since FOWTs are still in the early stages of development. Finally, the trends of UAV technology and its application in FOWTs inspection are discussed, leading to our future research direction.
RESUMO
This review focuses on the definitions, modalities, applications, and performance of various aspects of digital twins (DTs) in the context of transmission and industrial machinery. In this regard, the context around Industry 4.0 and even aspirations for Industry 5.0 are discussed. The many definitions and interpretations of DTs in this domain are first summarized. Subsequently, their adoption and performance levels for rotating and industrial machineries for manufacturing and lifetime performance are observed, along with the type of validations that are available. A significant focus on integrating fundamental operations of the system and scenarios over the lifetime, with sensors and advanced machine or deep learning, along with other statistical or data-driven methods are highlighted. This review summarizes how individual aspects around DTs are extremely helpful for lifetime design, manufacturing, or decision making even when a DT can remain incomplete or limited.
RESUMO
This study proposes the new condition monitoring concept of using features in the measured rotation, or 'pitch' signal, of a crossing vehicle as an indicator of the presence of foundation scour in a bridge. The concept is explored through two-dimensional vehicle-bridge interaction modelling, with a reduction in stiffness under a pier used to represent the effects of scour. A train consisting of three 10-degree-of-freedom carriages cross the model on a profiled train track, each train varying slightly in terms of mass and velocity. An analysis of the pitch of the train carriages can clearly identify when scour is present. The concept is further tested in a scaled laboratory experiment consisting of a tractor-trailer crossing a four-span simply supported bridge on piers. The foundation support is represented by four springs under each pier, which can be replaced with springs of a reduced stiffness to mimic the effect of scour. The laboratory model also consistently shows a divergence in vehicle pitch between healthy and scoured bridge states.
RESUMO
OBJECTIVES: This study: (i) quantified the typical noise levels in an Irish neonatal intensive care unit (NICU) and compared the values to recommendations by the American Academy of Paediatrics (AAP) and the European Standards for Care for Newborn Health (EFCNI) and to occupational exposure limit value and exposure action values; and (ii) qualified the perception of noise levels and the sources of noise across the various stakeholders within a typical NICU. METHODS: A noise survey was conducted in an Irish NICU. Observations identified practices and behaviours in the NICU that potentially had an impact on noise levels. Noise levels were compared to occupational exposure limits and AAP and EFCNI standards. A noise perception survey was conducted to identify noise sources and awareness of noise levels in the NICU. Results were analysed using SPSS Statistics to determine statistical significance. RESULTS: Noise levels recorded were consistent with previous similar studies and in all cases, the average noise levels recorded exceeded the 45 dBA as recommended by the AAP and EFCNI. There was a statistically significant difference (P < 0.01) between noise levels recorded on the day shift compared to the night shift. The perception of noise levels reported by nurses versus parents was found to be statistically significant (P = 0.001). 38.3% of all respondents reported having received no information or training with regard to noise in the NICU. There was a statistically significant difference in the perception of who is most likely to be affected by noise in the NICU, with nurses reporting those most likely to be affected by noise were patients, and parents reporting those most likely to be affected were staff (P = 0.003). CONCLUSIONS: This study supports the hypothesis that noise levels within the NICU are of concern and require regular assessment and monitoring. Training and awareness programmes are an important component to ensuring all persons in the NICU recognise their potential impact on noise levels in the NICU and in reducing the risk for patients and staff.
Assuntos
Unidades de Terapia Intensiva Neonatal , Ruído Ocupacional , Exposição Ocupacional , Humanos , Unidades de Terapia Intensiva Neonatal/estatística & dados numéricos , Irlanda , Ruído Ocupacional/estatística & dados numéricos , Ruído Ocupacional/efeitos adversos , Exposição Ocupacional/estatística & dados numéricos , Recém-Nascido , Ruído/efeitos adversos , Inquéritos e Questionários , Masculino , Pais/psicologia , FemininoRESUMO
This work experimentally addresses damage calibration of an unmanned aerial vehicle in operational condition. A wide range of damage level and types are simulated and controlled by an electric motor via pulse width modulation in this regard. The measurement is carried out via established protocols of using a piezo-patch on one of the 8 arms, utilising the vibration sensitivity and flexibility of the arms, demonstrating repeatability of such protocol. Subsequently, recurrence analysis on the voltage time series data is performed for detection of damage. Quantifiers of damage extent are then created for the full range of damage conditions, including the extreme case of complete loss of power. Experimental baseline condition for no damage condition is also established in this regard. Both diagonal-line and vertical-line based indicators from recurrence analysis are sensitive to the quantitative estimates of damage levels and a statistical test of significance analysis confirms that it is possible to automate distinguishing the levels of damage. The damage quantifiers proposed in this paper are useful for rapid monitoring of unmanned aerial vehicle operations of connection.
RESUMO
The present work offers a comprehensive overview of methods related to condition assessment of bridges through Structural Health Monitoring (SHM) procedures, with a particular interest on aspects of seismic assessment. Established techniques pertaining to different levels of the SHM hierarchy, reflecting increasing detail and complexity, are first outlined. A significant portion of this review work is then devoted to the overview of computational intelligence schemes across various aspects of bridge condition assessment, including sensor placement and health tracking. The paper concludes with illustrative examples of two long-span suspension bridges, in which several instrumentation aspects and assessments of seismic response issues are discussed.