Using genetic algorithms to optimize an active sensor network on a stiffened aerospace panel with 3D scanning laser vibrometry data

Marks, Ryan; Clarke, Alastair; Featherston, Carol Ann; Kawashita, Luiz F.; Paget, Christophe; Pullin, Rhys

doi:10.1088/1742-6596/628/1/012116

Cited by 2 publications

(4 citation statements)

References 10 publications

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“…Previously published results 33 indicate that Lamb wave interaction with the disbonded region produces a diffraction pattern and as such would result in low crosscorrelation coefficients in the regions where these sensors have been placed. 34 The placement of the two-sensor network places the majority of the sensors in-line with the disbonded region. One sensor for the 100 kHz excitation was placed in the lower right-hand corner which is likely to be due to the diffraction pattern.…”

Section: Sensor Location Resultsmentioning

confidence: 99%

“…A uniform probability of mutation of 0.1 was used for this problem as good results in a previous, preliminary study demonstrated search space exploration with convergence on the global maxima. 34 The fittest 10% of solutions were made immune from allele mutation which prevented good solutions being mutated into poorer solutions, and hence being discarded.…”

Section: Gasmentioning

confidence: 99%

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Optimization of acousto-ultrasonic sensor networks using genetic algorithms based on experimental and numerical data sets

Marks

Clarke

Featherston

et al. 2017

International Journal of Distributed Sensor Networks

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Aircraft structural damage detection is becoming of increased importance. Technologies such as acousto-ultrasonic have been suggested for this application; however, an optimization strategy for sensor network design is required to ensure a high detection probability while minimizing sensor network mass. A methodology for optimizing acousto-ultrasonic transducer placement for adhesive disbond detection on metallic aerospace structures is presented. Experimental data sets were acquired using three-dimensional scanning laser vibrometry enabling in-plane and out-of-plane Lamb wave components to be considered. This approach employs a novel multi-sensor site strategy which is difficult to achieve with physical transducers. Different excitation frequencies and source-damage-sensor paths were considered. A fitness assessment criterion which compared baseline and damaged data sets using cross-correlation coefficients was developed empirically. Efficient sensor network optimization was achieved using a bespoke genetic algorithm for different network sizes with the effectiveness assessed and discussed. A comparable numerical data set was also produced using the local interaction simulation approach and optimized using the same methodology. Comparable results with those of the experimental data set indicated a good agreement. As such, the numerical approach demonstrates that acoustoultrasonic sensor networks can be optimized using simulation (with some further refinement) during an aircraft design phase, being a useful tool to sensor network designers.

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Section: Sensor Location Resultsmentioning

confidence: 99%

Section: Gasmentioning

confidence: 99%

Optimization of acousto-ultrasonic sensor networks using genetic algorithms based on experimental and numerical data sets

Marks

Clarke

Featherston

et al. 2017

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

show abstract

“…Three transducer excitation frequencies of 100kHz, 200kHz and 300kHz were selected to investigate the sensitivity of different wavelengths to the presence of impact damage. Although 100kHz lies outside of the published operating resonance of the transducer it has shown to produce useful results in previous studies 53,57,58 . Due to the maximum sampling frequency of the vibrometer being 2.56MHz, frequencies above 300kHz were not considered due to insufficient temporal resolution A 150V, 5-cycle sine burst was generated by a Mistras Group Limited (MGL) WaveGen function generator software which was connected to MGL μdisp/NB-8 hardware.…”

Section: D Scanning Laser Vibrometry Setupmentioning

confidence: 98%

“…Although 100 kHz lies outside of the published operating resonance of the transducer, it has shown to produce useful results in previous studies. 53,59,60 To investigate the sensitivity of different wavelengths to the presence of impact damage, 300 kHz was selected despite a higher dispersion characteristic for the S 0 mode. Due to the maximum sampling frequency of the vibrometer being 2.56 MHz, frequencies above 300 kHz were not considered due to insufficient temporal resolution.…”

Section: Experimental Studymentioning

confidence: 99%

Damage detection in a composite wind turbine blade using 3D scanning laser vibrometry

Marks

Gillam

Clarke

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part C:

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As worldwide wind energy generation capacity grows, there is an increasing demand to ensure structural integrity of the turbine blades to maintain efficient and safe energy generation. Currently, traditional non-destructive testing methods and visual inspections are employed which require the turbine to be out-of-operation during the inspection periods, resulting in costly and lengthy downtime. This study experimentally investigates the potential for using Lamb waves to monitor the structural integrity of a composite wind turbine blade that has been subject to an impact representative of damage which occurs in service. 3D scanning laser vibrometry was used to measure Lamb waves excited at three different frequencies both prior to, and after, impact to identify settings for an optimal system. Signal processing techniques were applied to the datasets to successfully locate the damage and highlight regions on the structure where the Lamb wave was significantly influenced by the presence of the impact damage. Damage size resulting from the impact was found to correlate well with the laser vibrometry results. The study concluded that acousto-ultrasonic-based structural health monitoring systems have great potential for monitoring the structural integrity of wind turbine blades.

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Using genetic algorithms to optimize an active sensor network on a stiffened aerospace panel with 3D scanning laser vibrometry data

Cited by 2 publications

References 10 publications

Optimization of acousto-ultrasonic sensor networks using genetic algorithms based on experimental and numerical data sets

Optimization of acousto-ultrasonic sensor networks using genetic algorithms based on experimental and numerical data sets

Damage detection in a composite wind turbine blade using 3D scanning laser vibrometry

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