In this paper, we present challenges and achievements in development and use of a compact ultrasonic Phased Array (PA) module with signal processing and imaging technology for autonomous non-destructive evaluation of composite aerospace structures. We analyse two different sets of ultrasonic scan data, acquired from 5 MHz and 10 MHz PA transducers. Although higher frequency transducers promise higher axial (depth) resolution in PA imaging, we face several signal processing challenges to detect defects in composite specimens at 10 MHz. One of the challenges is the presence of multiple echoes at the boundary of the composite layers called structural noise. Here, we propose a wavelet transform-based algorithm that is able to detect and characterize defects (depth, size, and shape in 3D plots). This algorithm uses a smart thresholding technique based on the extracted statistical mean and standard deviation of the structural noise. Finally, we use the proposed algorithm to detect and characterize defects in a standard calibration specimen and validate the results by comparing to the designed depth information.

https://www.mdpi.com/1424-8220/20/2/559/pdf

Improving Depth Resolution of Ultrasonic Phased Array Imaging to Inspect Aerospace Composite Structures

Stainless steels (SS) have earned a unique position as a widely accepted class of alloys with track record of steadily improving the performance and increasing applications from 1913 till date. This distinction is attributed to R&D, innovations and applications leading to harnessing the rare combination of properties of stainless steels, since its discovery hundred years back. Though the initial discovery of stainless steel is basically serendipity, and based on previous work, its indispensable position today, in many a wide range of applications is due to intense R&D efforts in understanding its physical, chemical, thermal and thermo-mechanical response for various chemistries and microstructures. A deliberate attempt to extend its application spectrum through various routes of manufacturing in the last century is another crucial aspect of the success story. The first part of the presentation would briefly review this exciting journey of unravelling the mysteries of stainless steels.The second part of the presentation would highlight the evolution of stainless steels in the nuclear industry, especially for the sodium cooled fast reactors. Early 70s have seen the application of stainless steels in first generation water based nuclear power plants and AISI types 304 and 316 SS was recommended for structural and core applications in fast spectrum reactors (FSR). Failure of some of the components even in the manufacturing stage and quest for improving mechanical properties and sensitisation and intergranular corrosion resistances resulted in the development of 304L, 304LN, 316L, 316LN SS during 1980-90 for further applications in FSRs. Towards core applications in intense radiation environments, three generations of stainless steels namely 20% cold worked 316 SS, D9, and D9I have been developed to yield high burnup and to triple the lifetime of the core components of the fast reactors. Towards closing the fuel cycle, again 304L SS was the workhorse material which was upgraded with newer varieties like nitric acid grade alloys for improved corrosion resistance and longer life. Manufacturing of special grades of SS and the developments in fabrication technologies was necessary in order to enhance the performance of components and to avoid failures. Welding, inspection, quality assurance and structural integrity of various components of SS for FSRs and fuel cycle facilities resulted in developments in areas like modelling, devices, methodologies and analysis. An opportunity existed for the development and application of innovative non-destructive testing techniques for robust examination of critical components.Nuclear industry is embarking a state of the art fourth generation reactors. The consequent newer generation of SS are evolving with improved properties to match the expectations of performance in increased temperature, pressure, chemical and other physical constraints. It is of paramount importance to consider the extension of the lifetime of the current reactors from 40-60 to 60-80 years for economic considerations, and in this regard innovations are necessary in the development of newer varieties of stainless steels with respect to modelling and life prediction, manufacturing, fabrication, testing and evaluation. Thus the management approach to knit a network of industry-research-academia is a key approach for way forward. A development of roadmap for robust science based technology development with foresight is a desired management strategy.

Development of Stainless Steels in Nuclear Industry: With Emphasis on Sodium Cooled Fast Spectrum Reactors History, Technology and Foresight

Ultrasonic B-scan imaging is affected by the acoustic diffraction and electrical effects in nondestructive testing (NDT), resulting in insufficient lateral and temporal resolution for defect characterization. The minimum mean squared error (MMSE) method can improve the resolution by inversing a linear imaging model, which takes the acoustic diffraction and electrical effects into account, and achieve higher resolution than the synthetic aperture focusing technique (SAFT). However, its computation efficiency and resolution improvement are unsatisfactory due to the hypothetical Gaussian distribution of defects. To overcome these problems, a model-based regularized inverse method for ultrasonic B-scan image reconstruction is proposed. Benefitting from the sparse distribution of defects in NDT applications, the proposed method formulates an inverse objective function composed of -norm as well as -norm, and the sparse reconstruction by a separable approximation (SpaRSA) algorithm is adopted to obtain the optimal solution. The performance of the proposed method is evaluated by B-scan imaging of two 0.3 mm steel wires conducted both in simulation and experiment. The results verify that the proposed method improves the lateral and temporal resolution simultaneously with high computation efficiency.

https://iopscience.iop.org/article/10.1088/0957-0233/26/10/105401/pdf

A model-based regularized inverse method for ultrasonic B-scan image reconstruction

Evaluation of material degradation using phased array ultrasonic technique with full matrix capture

A method for prediction and providing compressed image quality for lossy compression techniques based on discrete cosine transform (DCT) is proposed. A specific property of the designed method is its ability to predict compressed image quality with appropriately high accuracy using a limited number of analyzed blocks. This accelerates prediction of lossy compression quality substantially. The method is originally proposed for JPEG with uniform quantization and then generalized for other, advanced, DCT based coders AGU and ADCT.

Image quality prediction for DCT-based compression

Signal quality enhancement using higher order wavelets for ultrasonic TOFD signals from austenitic stainless steel welds

The basic idea of compression is to try to reduce the average number of bits per pixel to adequately represent the image. Image compression is urgently needed for very large medical or satellite images, both for reducing the storage requirements and for improving transmission efficiency. Fourier-based transforms (e.g. DCT and DFT) are efficient in exploiting the low frequency nature of an image. The high frequency coefficients are coarsely quantized, and hence the reconstructed quality of the image at the edges will have poor quality. On the other hand, wavelets are efficient in representing nonstationary signals because of the adaptive time-frequency window. So the Discrete Wavelet Transform (DWT) is applied to an image and the energy compaction performance of both Discrete Cosine Transform (DCT) and DWT is compared. It is observed that both transforms provide comparable energy compaction performance.

Comparison of DCT and wavelets in image coding

FPGA Implementation of Spatial Image Filters using Xilinx System Generator

Non Destructive testing of structural materials is an important activity in many industries. Ultrasonic NDT is one such method widely used in this field. Pulse Echo and Through Transmission are conventional testing techniques which use reflected and transmitted sound energy respectively. But these techniques are highly dependent on defect orientation. Time of Flight Diffraction (TOFD) is a recent method which uses diffracted sound energy to detect the defects and is independent of orientation of the defects in the material. TOFD signals are dominated by noise arriving from various sources namely instrumental noise, material (structural) noise, thermal noise etc. Signal processing is an important step in the evaluation of the signals for detecting, positioning and characterizing the defects. Fourier Transform is widely used in the analysis and de-noising of signals of different kind. In this paper Ultrasonic TOFD signals obtained from Austenitic Stainless Steel weldments are analyzed using Fourier Transforms.

https://research.ijcaonline.org/volume71/number9/pxc3888737.pdf

Fourier Analysis of Ultrasonic TOFD Signals for Defect Detection in Austenitic Stainless Steel Welds

Inspection of structural materials is an important aspect in many industrial applications. Ultrasonic Non-Destructive Testing (NDT) is one of the most widely used techniques in this aspect. Conventional pulse echo and through transmission methods in Ultrasonic Testing (UT) are not reliable in detection of defects with random orientation due to its reflection principle. Time of Flight Diffraction (ToFD) method has gained more popularity in this area in the recent past. It uses diffraction energy and has more advantages in detection, sizing and positioning of the defects irrespective of type, orientation and characteristics. This technique is hampered by several of the unwanted signals arising due to ultrasonic interaction with the material grains. This noise affects the visibility of a defect signal especially when the defect size is small. Many signal processing techniques such as split spectrum processing, wavelet transform and correlation etc are available for de-noising of signals. Among this Discrete Wavelet Transform (DWT) is widely used due to its added advantage of time-frequency information simultaneously. Stationary Wavelet Transform (SWT) is a form of DWT with the main difference that it is translation invariant unlike DWT. In this paper SWT has been used for de-noising of the real time ultrasonic ToFD signals from austenitic stainless steel welds and its performance is compared with that of the DWT. General Terms NDT, Ultrasonic Testing, ToFD, Signal Processing, Wavelets.

/pdf/de-noising-of-tofd-signals-from-austenitic-stainless-steel-4d4xtwoqt1.pdf

Angam Praveen

Papers

Signal quality enhancement using higher order wavelets for ultrasonic TOFD signals from austenitic stainless steel welds

Comparison of DCT and wavelets in image coding

FPGA Implementation of Spatial Image Filters using Xilinx System Generator

Fourier Analysis of Ultrasonic TOFD Signals for Defect Detection in Austenitic Stainless Steel Welds

De-noising of ToFD Signals from Austenitic Stainless Steel Welds using Stationary Wavelet Transform