Compressive sensing for direct time of flight estimation in ultrasound-based NDT

Carmelo Mineo, Antoniadou, Mineo, Ramon Fuentes, Cross, Keith Worden, Stephen Gareth Pierce, Elizabeth J. Cross

Risultato della ricerca: Conference contribution

2 Citazioni (Scopus)


This paper presents an approach for estimation of ultrasonic time-of-flight (TOF) within a Non Destructive Testing (NDT) and Structural Health Monitoring (SHM) context. The presented method leverages recent advances in the field of Compressive Sensing (CS), which makes use of sparsity in a transform domain of a signal in order to reduce the number of samples required to store it. CS achieves this through a two key ideas: random matrix projections, and l1-penalised linear regression. In this case, sparsity arises from the observation that in a pulse-echo ultrasound test, the number of echoes is relatively small compared to the number of measurement points in a waveform. This sparsity is evident in the autocorrelation of ultrasound waveforms. A method is suggested in this paper for building suitable basis functions, based on Hankel matrices, which transform a signal into its autocorrelation domain. It is shown how this can be combined with standard CS techniques in order to achieve a very low error in TOF estimates with up to one-tenth of the original ultrasound samples.
Lingua originaleEnglish
Titolo della pubblicazione ospiteStructural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, IWSHM 2017
Numero di pagine10
Stato di pubblicazionePublished - 2017

All Science Journal Classification (ASJC) codes

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  • ???subjectarea.asjc.1700.1706???


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