Brunel Innovation Center

Great Abington, United Kingdom

Brunel Innovation Center

Great Abington, United Kingdom
SEARCH FILTERS
Time filter
Source Type

Ferrando Chacon J.L.,Brunel Innovation Center | Artigao Andicoberry E.,Brunel Innovation Center | Kappatos V.,Brunel Innovation Center | Asfis G.,Brunel Innovation Center | And 2 more authors.
Applied Acoustics | Year: 2014

Shaft angular misalignment (SAM) is a common and crucial problem in rotating machinery. Misalignment can produce several shortcomings such as premature bearing failure, increase in energy consumption, excessive seal lubricant leakage and coupling failure. Vibration analysis has been traditionally used to detect SAM; however, it presents some drawbacks i.e. high influence of machine operational conditions and strong impact of the coupling type and stiffness on vibration spectra. This paper presents an extensive experimental investigation in order to evaluate the possibility of detecting SAM, using acoustic emission (AE) technique. The test rig was operated at under different operational conditions of load and speed in order to evaluate the impact on the AE and vibration signature under normal operating conditions. To the best of the author's knowledge, this is the first attempt to use AE for the detection of SAM under varying operational conditions. A comparative study of vibration and AE was carried out to demonstrate the potentially better performance of AE. The experimental results show that AE technique can be used as a reliable technique for SAM detection, providing enhancements over vibration analysis. © 2014 Elsevier Ltd. All rights reserved.


Artigao E.,Brunel Innovation Center | Ferrando J.L.,Brunel Innovation Center | Gan T.-H.,Brunel Innovation Center | Wang B.,Brunel Innovation Center | And 3 more authors.
Insight: Non-Destructive Testing and Condition Monitoring | Year: 2014

Existing wind turbine condition monitoring methodologies can be time-consuming and costly processes that fail to achieve the reliability and operational efficiency required by the industry[1]. Present studies on monitoring data for wind turbines is restricted to a few case histories and for certain sensors is yet scarcer[2]. In order to overcome this issue, the development of a reliable baseline is desirable. In this paper, motor current signature analysis (MCSA) is proposed in order to generate a baseline to define the normal operating conditions of the induction generator in a wind turbine. Electrical current data is collected for an initial period of time, serving as a training process. Different signal processing methods are used to extract the wind turbine generator's features. The features extracted during this initial period are used to create a baseline that defines the behaviour of the generator under normal operation. A range of maximum and minimum values for these features is calculated using statistical methods. Using this approach, the generator monitoring process can be performed by comparing each new set of data acquired to the original baseline created during the initial stage. © 2014 The British Institute of Non-Destructive Testing.


Kalman V.,Ateknea Solutions | Baczo C.,Ateknea Solutions | Livadas M.,Brunel Innovation Center | Csielka T.,Brunel Innovation Center
Studies in Health Technology and Informatics | Year: 2015

Today as embedded computing technology and sensors become cheaper and smaller wearable technologies experience an unprecedented boom. This article presents two wearable systems that aim to help people with low vision and the blind in performing everyday tasks and doing sports. DIGIGLASSES is a project aimed at creating a pair of augmented reality digital glasses that present controlled light and contrast levels and marks selectable features on the field of vision to aid in everyday tasks. BLINDTRACK is guidance system that uses wireless localization and an innovative haptic feedback belt to guide blind runners along the running track. Both systems are briefly presented along with the most relevant technical details and user feedback where applicable. Both projects were funded by the EU FP7. © 2015 The authors and IOS Press. All rights reserved.


Habibi H.,Brunel Innovation Center | Edwards G.,Twi Ltd. | Cheng L.,Brunel Innovation Center | Zheng H.,Brunel Innovation Center | And 4 more authors.
SAE Technical Papers | Year: 2015

Icing conditions in cold regions of the world may cause problems for wind turbine operations, since accreted ice can reduce the efficiency of power generation and create concerns regarding ice-shedding. This paper covers modelling studies and some experimental development for an ongoing ice protection system that provides both deicing and anti-icing actions for wind turbine blades. The modelling process contained two main sections. The first part involved simulation of vibrations with very short wavelength or ultrasonic guided waves (UGW) on the blade to determine optimal excitation frequency and transducer configuration. This excitation creates horizontal shear stress at the interface between ice and blade and focuses energy at the leading edge for de-bonding ice layers. The second modelling approach simulated the effects of vibrations with very long wavelength along with estimation of fatigue life due to harmonic forces to characterise the best parameters for shaker (s) mounted on blades. In parallel with this study, an empirical array of novel resonating shear transducers has been developed using a Design of Experiments (DoE) approach to demonstrate the practicability of inducing shear horizontal waves at the leading edge of wind turbine blades. This experimental verification also makes it possible to investigate the many parameters influencing ice-removal. In addition, piezo-electric and macro-fibre composite actuators have been investigated in place of conventional electro-magnetic shakers, in order to save weight and simplify integration of the deicing system components. The ongoing research is intended to provide an active solution for icing prevention and deicing, enabling safe and reliable operation of wind turbines in adverse weather conditions. Copyright © Brunel Innovation Centre (BIC).


Artigao E.,Brunel Innovation Center | Ferrando J.L.,Brunel Innovation Center | Wang B.,Brunel Innovation Center | Kappatos V.,Brunel Innovation Center | And 2 more authors.
11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, CM 2014 / MFPT 2014 | Year: 2014

Existing wind turbine condition monitoring methodologies can be time-consuming and a costly processes and fail to achieve the reliability and operational efficiency required by the industry(1). Present studies on monitoring data for wind turbines is restricted to a few case histories, for certain sensors is yet scarcer(2). In order to overcome this issue, the development of a reliable baseline would be desirable. In this paper, Motor Current Signature Analysis (MCSA) is proposed in order to generate a baseline to define the normal operating conditions of the induction generator in a wind turbine. Electrical current data is collected for an initial period of time, serving as a training process. Different signal processing methods are used to extract the wind turbine generator's features. The features extracted during this initial period are used to create a baseline that defines the behaviour of the generator under normal operation. A range of maximum and minimum values for these features is calculated using statistical methods. Using this approach, the generator monitoring process can be performed by comparing each new set of data acquired to the original baseline created during the initial stage.


PubMed | Ateknea Solutions and Brunel Innovation Center
Type: | Journal: Studies in health technology and informatics | Year: 2015

Today as embedded computing technology and sensors become cheaper and smaller wearable technologies experience an unprecedented boom. This article presents two wearable systems that aim to help people with low vision and the blind in performing everyday tasks and doing sports. DIGIGLASSES is a project aimed at creating a pair of augmented reality digital glasses that present controlled light and contrast levels and marks selectable features on the field of vision to aid in everyday tasks. BLINDTRACK is guidance system that uses wireless localization and an innovative haptic feedback belt to guide blind runners along the running track. Both systems are briefly presented along with the most relevant technical details and user feedback where applicable. Both projects were funded by the EU FP7. Corresponding author V. Kalman: viktor.kalman@ateknea.com.

Loading Brunel Innovation Center collaborators
Loading Brunel Innovation Center collaborators