Modelling of the frequency modulated thermal wave imaging process through the finite element method for non-destructive testing of a mild steel sample

Abstract

Modelling of the frequency modulated thermal wave imaging process through the finite element method for non-destructive testing of a mild steel sample Frequency modulated thermal wave imaging involves mapping of the thermal response over the test sample for a given incident frequency modulated heat flux within a suitable band of frequencies that are launched into the sample from its surface. This contribution describes finite element analysis-based modelling for the characterisation of a mild steel sample with defects of different shapes using frequency modulated thermal wave imaging. The present work highlights the comparative results obtained from frequency and time domain phase analysis schemes adopted on the mean-removed generated temporal thermal data.

Hierarchical low-rank and sparse tensor micro defects decomposition by electromagnetic thermography imaging system

“…Siddiqui et. al proposed the Finite element analysis method for modelling the frequency modulated thermal wave imaging process in non-destructive testing of a mild steel sample [45]. Kaur et.al [46] proposed Principal Component Analysis (PCA) and Sparse PCA(SPCA) based post-processing schemes for improving spatial contrast over the defective regions and enhancing the signal to noise ratio (SNR) , which was applied in frequency modulated thermal wave imaging for inspection of steel material.…”

Defect characterisation using pulse compression‐based quadratic frequency modulated thermal wave imaging

“…Pulse compression [21][22][23][24][25][26][27] differentiates the subsurface anomalies from the non-defect region by using the delay and attenuation in the thermal profiles. In this, a reference profile is selected from non-defect location and CC has carried with the remaining pixel's profile, which results in a normalised correlation coefficient data sequence.…”

“…This time-domain phase has a feature of emissivity normalised contrast parameter possessing an enhanced dynamic range and higher sensitivity, unlike in the frequencydomain phase. [5] It is a multi-transform method [21][22][23][24][25][26] to obtain a time-domain phase contrast to defect detection by calculating the phase difference between the conventional frequency-domain pulse compression data value to Hilbert transform-based pulse compression data value of same pixel's thermal profile. The same procedure is repeated with remaining pixels profile and phase images are formed by rearranging extracted phase values into its corresponding pixel location, as shown in Fig.…”

Infrared thermography for detection and evaluation of bone density variations by non-stationary thermal wave imaging

“…In general IRT can be implemented either in active or in passive approach [10]. In active mode, an external thermal stimulus (heating or cooling) is needed to produce significant thermal contrasts for the detection of subsurface variations and abnormalities located deep inside [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24]. However, in passive approach mapping of the thermal profile is carried out in the absence of any external stimulus [10].…”

“…Depending on the shape of the external stimulus, different active thermographic methods have been developed, such as pulse thermography (PT) [11], pulse phase thermography (PPT) [10,12] and lock-in thermography (LT) [13,14]. Former techniques (PT and PPT) demands high peak power pulse shaped incident heat flux whereas the later (LT) uses a mono frequency modulated incident heat flux [15][16][17][18][19]. Present work focus on a non-stationary thermal wave imaging technique which can be carried out even with low peak power incident heat flux in comparison with pulse based techniques (PT and PPT) and in a limited span of experimental time in comparison with modulated LT.…”