Informatics Publishing Limited

Sujatha Kumaran ¹, B. Sheela Rani ²

Affiliations
1 Sathyabama University, Jeppiaar Nagar, Rajiv Gandhi Road, Chennai 600 119, IN
2 Sathyabama University, Jeppiaar Nagar, Rajiv Gandhi Road, Chennai 600 119

Abstract

The condition of bowing of fuel rods in nuclear reactors is often detected through imaging of sub-assembly tops using C-Scans obtained from Pulse Echo Ultrasonic technique. The detection of bowing by means of post processing of A-Scan signals is discussed in this paper. Techniques have been initially developed on hollow cylinders, which mimic the sub-assembly tops. A-Scans are collected by placing the unfocussed ultrasonic transducer at the top of the hollow cylinder, kept in the water bath. The beam spread causes the object to be detected even when the transducer is not exactly above the object. This results in over sizing of the object. The objective is to estimate the width precisely by means of which, condition of bowing could be detected. Synthetic Aperture Focusing Technique is applied on these A-Scans to estimate the width. The width of the object can be estimated at different positions on the top surface of the object, from which centre points at each position can be obtained. If these centre points form an ellipse or a deformed circle, then bowing condition is detected, else normal condition is indicated. Two hollow cylinders of known width 5 mm and 3 mm have been used here. Application of this technique with a synthetic aperture of 14.4 mm, has given a minimal error of 1.4 mm and 0.3 mm for the 5 mm and 3 mm cylinders respectively.

Keywords

A-scan, Bowing, Pulse Echo, SAFT, Width

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A. Nandhini ¹, V. Kannan ², E. Logashanmugam ¹, B. Sheela Rani ¹, Raju Daniel ³

Affiliations
1 Sathyabama University, Sholinganallur, Chennai, Tamilnadu, IN
2 Jeppiaar Institute of Technology, Kunnam, Kanchipuram District, IN
3 Institute of Plasma Research, Bhat, Gujrat, IN

Abstract

A stable integrator of long duration up to 5s has been designed for Aditya tokamak. In tokamaks, the accurate knowledge about the plasma position has been required for maintaining the distance between plasma and in vessel component. Hence, the value of plasma current, magnetic field and magnetic flux are to be calculated by integrating signals from the magnetic pick up loops. High accuracy integrators are required for the accurate magnetic measurements for long duration signals. The proposed integrator design composed of microcontroller, DAC, integrator and ADC. This design provides a stable output for noisy and drift input signal level up to 5s. The microcontroller has been used to maintain the stability of the output signal and also eliminate the offset induced noise components.

Keywords

ADC, Drift, Integrator, Microcontroller, Plasma.

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C. F. Theresa Cenate ¹, B. Sheela Rani ¹, B. Venkatraman ²

Affiliations
1 Sathyabama University, Chennai-600 119, IN
2 Indira Gandhi Centre for Atomic Research, Kalpakkam–603 102, IN

Abstract

Time of Flight Diffraction (TOFD) is an advanced Ultrasonic Technique for examination of weld specimen in process industries. Ultrasonic experts are required for defect detection which means increase in resource is needed increased resource. Hence an algorithm has to be developed to automate the defect segmentation. This research work develops an algorithm involving the stages of preprocessing, global thresholding and segmentation procedure of image processing. The proposed algorithm was tested on the TOFD image acquired in the laboratory condition. According to the result obtained the algorithm developed and applied to TOFD images for segmentation of defects are highly reliable.

Keywords

Time of Flight Diffraction (TOFD), Segmentation, Morphology, Image Processing, Defect Detection, Global Thresholding.

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M. Selva Kumar ¹, Santosh P. Pandya ², N. M. Nandhitha ¹, B. Sheela Rani ³

Affiliations
1 Department of Electronics and Telecommunication Engineering, Sathyabama University, IN
2 SC Institute for Plasma Research, Gujarat, IN
3 Sathyabama University, IN

Abstract

With the need for highly accurate computer aided analysis, extensive research is carried out in the development of effective feature extraction methods. Through spatial, frequency and wavelet based approaches provide better results, they suffer from certain limitations especially during local frequency amplitude analysis. Hence the paradigm has shifted to Stockwell transform that combines a frequency dependent resolution of the time-frequency in addition to providing the relationship between time and frequency, Stockwell transform also gives information about phase. Moreover S-Transform is also sensitive to noise. This paper provides a extensive survey on the application of S-Transform for signal an image analysis. From the survey it is found that S-Transform provides better results when compared to conventional denoising and feature extraction algorithm.

Keywords

Frequency Domain, Image Processing Stockwell Transform, Wavelet Transform.

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P. Chitra ¹, B. Sheela Rani ¹, B. Venkataraman ², Baldev Raj ³

Affiliations
1 Sathyabama University, Chennai 119, IN
2 Quality Assurance Division, Indira Gandhi Centre for Atomic Research, Kalpakkam, IN
3 Indira Gandhi Centre for Atomic Research, Kalpakkam, IN

Abstract

Radiography is one of the oldest Non Destructive Techniques used to find the volumetric defects in welding. After digitization, radiographic images are generally of low contrast, dark and have high noise. Hence it is difficult to detect the defects with very high accuracy. Hence, image enhancement is a significant part of automated radiography inspection system. Weld defect detection or classification is a multi-step process which plays a vital role in processing of the radiographic weld image. Edge Detection is one of the pre-processing step to eliminate the unwanted information from the radiographic image and used to extract the required defect information (edge of the Radiographic image) during further processing. This paper mainly deals with first derivative edge detection filters which are applied on the radiographic weld image. The optimum threshold value for the edge detection filters based on the type of defects is obtained. The major defects like weaving faults, crack, under cut and slag inclusion are analyzed.

Keywords

Digital Radiography, Edge Detection, Morphological Processing, Weld Defects.

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B. Vijayalakshmi ¹, B. Sheela Rani ², N. Manoharan ¹

Affiliations
1 Sathyabama University, Chennai-600119, IN
2 Dept of EIE, Sathyabama University, Chennai-600119, IN

Abstract

Feature Detection and their similarities is a central problem in the field of vision based modeling. It is significant in the field of automation to locate objects and obstacles, or in the case of computer-guided surgery, or study of mathematical structures as well as in machine vision. It arises from the task of distinctive feature detection to classify and recognize structures of their observed silhouette. Defining natural distances between image discontinuities creates a metric space of shapes, whose mathematical structure is inherently relevant to the classification task. One intriguing metric space is identified from using conformal mappings through image matching with the help of mask from 2D stereo images. The poor image quality of many video surveillance cameras effectively renders them useless for the purposes of identifying features from grabbed image. Under certain conditions, however, it may be possible by comparing multiple stereo video frames for such identification tasks. For this a simple and computationally efficient technique for feature detection to detect the objects of an environment is discussed. The efficiency of this technique is shown on real video sequences.

Keywords

Stabilizing Factor, Object Distortion, 3D Reconstruction, Aperture Problem, Stereo Image.

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J. Jebastine ¹, B. Sheela Rani ²

Affiliations
1 Sathyabama University, Chennai-600119, IN
2 Sathyabama University, Chennai- 600119, IN

Abstract

This paper describes the Normalized Least Mean Square algorithm and Fast Transversal Least Mean Square Algorithm for effective noise cancellation. The Simulink model for NLMS and Fast Transversal LMS Algorithm had been designed which results in a noise free signal as output in ASSP. The filter used here is adaptive filter and the algorithm used is Least Mean Square algorithm and Fast Transversal Least Mean Square Algorithm. The input given is the original speech signal/sinusoidal varying input where in white Gaussian noise / Random noise are deliberately introduced to the block. By varying the adaptive step size, Signal to Noise Ratio is determined and are compared for both the algorithms. Based on these results the optimum step size is found for noise free output and the best efficient algorithm is identified. The Fast Transversal LMS algorithm is found to be a suitable solution for adaptive filtering applications and hence chosen for implementation in hardware using TMS320C5X processor. Thus hardware has been implemented for effective removal of noise in audio and speech processing and it can be widely used in the detection of Narrow band signals in Broad band Noise.

Keywords

Adaptive Filter, ASSP, FT-LMS and N-LMS, Tms320c5x Processor.

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S. Lalitha Kumari ¹, B. Sheela Rani ¹, B. Venkatraman ²

Affiliations
1 Sathyabama University, Chennai, IN
2 IGCAR, Kalpakkam, IN

Abstract

Non Destructive Evaluation is generally used for defect detection in welds. ToFD technique is one of the NDE methods, used in weld inspection to identify the weld defects. In ToFD testing, the quality of the signal is an important factor for identifying and classifying the defects. So, signal denoising is a key to successful application of ToFD testing. Many signal processing techniques are followed to improve the quality of the signal. Wavelet Transform is one of the effective signal processing techniques. This paper presents a denoising algorithm ,which is suitable for denoising the ToFD signal of an unknown weld defect.
In this work, five austenitic stainless steel weldments were fabricated with different types of defects. The ToFD experiment is conducted on these welds. According to the characteristics of the resultant ToFD signals, discrete wavelet transform via different thresholdings are employed. Symlet and coiflet are chosen as mother wavelets. Various combination of wavelets, decomposition levels and different thresholdings are applied to find out the optimum denoising method. Finally evaluation of wavelet based denoising is achieved by calculating the SNR.
Results show that the noises can be suppressed well and SNR is improved. Symlet 4 with the 5th decomposition level in association with the hard thresholding is found as the effective signal denoising algorithm for all the 5 different types of defected ToFD signals.

Keywords

Ultrasonic Testing, Symlet, Coiflet, Thresholding, SNR.

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J. Femila Roseline ¹, Yasser Arafat ², Jigneshkumar J. Patel ³, J. Govindarajan ⁴, N. M. Nandhitha ⁵, B. Sheela Rani ⁶

Affiliations
1 Department of Electrical and Electronics Engineering, Sathyabama University, Jeppiaar Nagar, Old Mahabalipuram Road, Chennai-600119, IN
2 Sathyabama University, Jeppiaar Nagar, Old Mahabalipuram Road, Chennai-600119, IN
3 Electronics Group, Institute of Plasma Research, IN
4 Institute of Plasma Research, IN
5 Department of Electronics and Telecommunication Engineering, Sathyabama University, Jeppiaar Nagar, Old Mahabalipuram Road, Chennai-600119, IN
6 Electronics & Instrumentation, Sathyabama University, Chennai-600119, IN

Abstract

Tokamaks are machines used for generating electrical power through nuclear fusion from plasma that is confined within the toroidal chamber. As Tokamaks require large amount of input power to produce plasma, the efficiency can be improved only when significant output power is generated. Hence in recent years, research has begun in this area to improve its efficiency. From the literature, it is found that the amount of power generated is dependent on the density of the plasma, plasma position and time duration for which the plasma is properly stabilized. In order to improve the efficiency, it is necessary to confine the plasma for longer durations within the chamber. This paper provides an extensive review of various researches conducted in this area to improve the efficiency of the Tokamak machines by stabilizing the plasma. From the literature cited, it is obvious that an adaptive plasma positioning system is yet to be evolved.

Keywords

Tokamaks, Plasma, Position Confinement, PID Controller, Fuzzy Logic Controller.

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C. F. Theresa Cenate ¹, B. Sheela Rani ¹, D. N. Sangeetha ², B. Venkatraman ²

Affiliations
1 Sathyabama University, Chennai - 600 119, Tamil Nadu, IN
2 Indira Gandhi Centre for Atomic Research, Kalpakkam - 603 102, Tamil Nadu, IN

Abstract

Background/Objectives: Grain structure of Austenitic Stainless Steel (ASS) weld causes difficulty in defect detection while inspecting using Time of Flight Diffraction (TOFD) method. This study aims at comparing segmentation methods to overcome this difficulty based on defect characterization. Methods/Statistical Analysis: This study makes use of TOFD and Radiographic images of ASS weld pads fabricated with defined linear and volumetric defects. The Region-Based Level Set algorithm and Discontinuity Based Segmentation algorithm were explored for achieving flaw segmentation and quantitative characterization and validation of the result with that of standard radiographic results. Findings: The efficiency of the algorithms was analyzed by comparing and validating the size of defect with that of standard radiographic results in the form of error percentage. The consistency of error percentage in defect sizing (up to 11%) achieved by Region- Based Level Set algorithm for all the test images given in the database indicate that, this algorithm is the best as compared to Discontinuity Based Segmentation algorithm(error percentage up to 47%) for defect segmentation and characterization in TOFD images. Application/Improvements: The segmentation algorithm enables automation of measurement process and enhanced detection and characterization of defects at the initial stage. Further, it reduces human fatigue caused by operator while defect detection as the volume of data increases. The future direction is to fully automate the system in order to save time for interpretation and to modify the algorithm to segment images with multiple defects.

Keywords

Defect Characterization, Discontinuity Based Segmentation, Flaw Segmentation, Region-Based Level Set Segmentation, Time of Flight Diffraction (TOFD), Weld Defect

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