Computational intelligence approaches for data analysis, the next step of innovation for advanced UT techniques in NDT
A Gonzalez Rodriguez, A Gosselin, R Rhéaume and N Harrap
There is no doubt in how advanced ultrasonic testing (UT) techniques such as phased array ultrasound (PAUT) and time-of-flight diffraction (TOFD) have taken over the non-destructive testing industry (NDT). The benefits of using these techniques are countless. Worldwide, there has been an increase in companies from different sectors taking advantage of the available technology for these practices. As a result, the equipment is becoming more affordable, data processing for real-time and automated applications is more powerful and the amount of data being produced is substantially high. Regarding this last subject, nowadays, the data acquired relies mainly on humans for analysis, critical assessment and decision-making, which are critical tasks that humans are more than capable of handling. However, when the data available for PAUT and TOFD goes from one simple dataset (scan) to hundreds of datasets for just a single project, unavoidable critical errors emerge.
For most NDT experts, interpretation of signals as well as analysis of data in huge amounts can inevitably lead to mistakes such as missing defects, wrong sizing or false call of a defect. Furthermore, the amount of time operators devote to data analysis is increasing exponentially for these advanced UT techniques. The NDT industry relies on consistent and reliable data analysis which, with the technologies available now, is incompatible with the amount of data to be analysed. For these reasons, Ondia and TWI have gathered a group of experts in NDT, software development and artificial intelligence to implement advanced computational intelligence (CI) techniques and develop algorithms to better harness the data available, in order to enhance the quality of data analysis. This innovation will naturally and drastically reduce the time invested in a single analysis, while addressing the challenges that big data analysis and processing bring about for advanced NDT techniques.
For most NDT experts, interpretation of signals as well as analysis of data in huge amounts can inevitably lead to mistakes such as missing defects, wrong sizing or false call of a defect. Furthermore, the amount of time operators devote to data analysis is increasing exponentially for these advanced UT techniques. The NDT industry relies on consistent and reliable data analysis which, with the technologies available now, is incompatible with the amount of data to be analysed. For these reasons, Ondia and TWI have gathered a group of experts in NDT, software development and artificial intelligence to implement advanced computational intelligence (CI) techniques and develop algorithms to better harness the data available, in order to enhance the quality of data analysis. This innovation will naturally and drastically reduce the time invested in a single analysis, while addressing the challenges that big data analysis and processing bring about for advanced NDT techniques.
