Pattern recognition by wavelet transforms using macro fibre composites transducers

González-Carrato, Raúl Ruiz de la Hermosa; Márquez, Fausto Pedro García; Dimlaye, Vichaar; Ruiz-Hernández, Diego

doi:10.1016/j.ymssp.2014.04.002

Cited by 46 publications

(12 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The CMS employs an ultrasonic system (see the WTB modify its flow [31]. The change in the wave velocities with temperature depends on frequency of the wave.…”

Section: Methodsmentioning

confidence: 99%

Wavelet transforms and pattern recognition on ultrasonic guides waves for frozen surface state diagnosis

2018

Self Cite

View full text Add to dashboard Cite

Icing blades require of advanced condition monitoring systems to reduce the failures and downtimes in Wind Turbine Blades (WTB). This paper presents a case study that combines ultrasonic techniques with Wavelet transforms for detecting ice on the blades. Lamb waves were generated with Macro Fibre Composites (MFC) and then were collected with MFC. Ice affects to the normal propagation of the wave through the material of the blade. The changes in the signal are due to the forces that ice exercise on the surface. Three different scenarios were considered: at room temperature; the frozen blade without accumulation of ice, and; the frozen blade with accumulation of ice on its surface. The novel approach can determine the state of the WTB. It leads a reduction of costs in inspection, downtime and the appearance of false alarms.

show abstract

“…The CMS employs an ultrasonic system (see the WTB modify its flow [31]. The change in the wave velocities with temperature depends on frequency of the wave.…”

Section: Methodsmentioning

confidence: 99%

Wavelet transforms and pattern recognition on ultrasonic guides waves for frozen surface state diagnosis

2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…Figure 6 shows the original signal and the de-noised signal after applied different de-noised filters. In contrast to other digital filters, the wavelet de-noising filter does not produce an undesired signal delay [35,36]. It is observed that the filter removes noise significantly, and it also does not eliminate events occurring in the signal with a specific frequency.…”

Section: Signal Processing Approachmentioning

confidence: 98%

Cracks and welds detection approach in solar receiver tubes employing electromagnetic acoustic transducers

Muñoz

Jiménez

Márquez

et al. 2017

Structural Health Monitoring

View full text Add to dashboard Cite

Where a licence is displayed above, please note the terms and conditions of the licence govern your use of this document. When citing, please reference the published version. Take down policy While the University of Birmingham exercises care and attention in making items available there are rare occasions when an item has been uploaded in error or has been deemed to be commercially or otherwise sensitive.

show abstract

“…The acquisition of accurate data is critical to determine the occurrence of a fault and to address the solution to apply. Nowadays, different techniques are available for CM: vibration analysis [3,11], acoustic emission [3,12], ultrasonic testing techniques [13,14], oil analysis [15], thermography [3,13] and other methods [16].…”

Section: Applied To Wtmentioning

confidence: 99%

Optimal Maintenance Management of Offshore Wind Farms

2016

View full text Add to dashboard Cite

Abstract:Nowadays offshore wind energy is the renewable energy source with the highest growth. Offshore wind farms are composed of large and complex wind turbines, requiring a high level of reliability, availability, maintainability and safety (RAMS). Firms are employing robust remote condition monitoring systems in order to improve RAMS, considering the difficulty to access the wind farm. The main objective of this research work is to optimise the maintenance management of wind farms through the fault probability of each wind turbine. The probability has been calculated by Fault Tree Analysis (FTA) employing the Binary Decision Diagram (BDD) in order to reduce the computational cost. The fault tree presented in this paper has been designed and validated based on qualitative data from the literature and expert from important European collaborative research projects. The basic events of the fault tree have been prioritized employing the criticality method in order to use resources efficiently. Exogenous variables, e.g., weather conditions, have been also considered in this research work. The results provided by the dynamic probability of failure and the importance measures have been employed to develop a scheduled maintenance that contributes to improve the decision making and, consequently, to reduce the maintenance costs.

show abstract

Pattern recognition by wavelet transforms using macro fibre composites transducers

Cited by 46 publications

References 47 publications

Wavelet transforms and pattern recognition on ultrasonic guides waves for frozen surface state diagnosis

Wavelet transforms and pattern recognition on ultrasonic guides waves for frozen surface state diagnosis

Cracks and welds detection approach in solar receiver tubes employing electromagnetic acoustic transducers

Optimal Maintenance Management of Offshore Wind Farms

Contact Info

Product

Resources

About