High-order spectra-based deconvolution of ultrasonic NDT signals for defect identification

In ultrasonic nondestructive testing (NDT) of materials, pulse-echo measurements are masked by the characteristics of the measuring instruments, the propagation paths taken by the ultrasonic pulses, and noise. This measured pulse-echo signal is modeled by the convolution of the defect impulse response and the measurement system response, added to noise. The deconvolution operation, therefore, seeks to undo the effect of the convolution and extract the defect impulse response which is essential for defect identification. In this contribution, we show that the defect ultrasonic model can be formulated in the higher order-spectra (HOS) domain in which the processing is more suitable to unravel the effect of the measurement system and the additive Gaussian noise. In addition, a new technique is developed to faithfully recover the impulse response signal from its HOS. Synthesized ultrasonic signals as well as real signals obtained from artificial defects are used to show that the proposed technique is superior to conventional second-order statistics-based deconvolution techniques commonly used in NDT

An Efficient Iris Segmentation Technique based on a Multiscale Approach

The use of biometric signatures, instead of tokens such as identification cards or computer passwords, continues to gain increasing attention as an efficient means of identification and verification of individuals for controlling access to secured areas, materials, or systems and a wide variety of biometrics has been considered over the years in support of these challenges. Iris recognition is especially attractive due to the stability of the iris texture patterns with age and health conditions. Iris image segmentation and localisation is a key step in iris recognition and plays an essential role the accuracy of matching. In this paper, we propose a new iris segmentation technique using a multiscale approach for edge detection, which is a fundamental issue in image analysis. Due to the presence of speckles, which can be modelled as a a strong multiplicative noise, edge detection for iris segmentation is very important and methods developed so far are generally applied in one single scale. In our proposed method, we introduce the concept of multiscale edge detection to improve iris segmentation. The technique is effecient for edge detetcion, greatly reduces the search space for the Hough transform and at the same time is robust to noise thus improving the overall performance. Linear Hough transform has been used for eyelids isolation, and an adaptive thresholding has been used for isolating eyelashes. Once the iris is segmented, a normalization step has been carried out by converting an iris image from cartesien into polar coordinates which are more suitable to deal with rotation and translation problems. Extensive experiments have been carried out and results obtained have shown an effectiveness of the proposed method which provides a high segmentation success of 99.6%

SHAFT LATERAL AND TORSIONAL VIBRATION RESPONSES TO BLADE(S) RANDOM VIBRATION EXCITATION

In this study, an experimental set-up for blades-shaft vibration monitoring under blade(s) random vibration excitation is used. The set-up natural frequencies and mode shapes are found using the ANSYS finite element package. The blades and shaft lateral and torsional vibration are monitored using blades strain-gages, bearing accelerometers and shaft torsional strain-gages stations. The results showed that the shaft torsional vibration measurement represents the blade(s) vibration more closely than the bearing accelerometers. In particular, the blades vibration at low frequencies corresponding to the blades bending and shaft torsional coupled modes is closely represented by the shaft torsional vibration signals. The results of this study increased the confidence in using the torsional vibration measurement for blades vibration identification and shed more light on the nature of coupling between the blade bending and shaft torsional vibration that occur at low frequencies

SHAFT LATERAL AND TORSIONAL VIBRATION RESPONSES TO BLADE(S) RANDOM VIBRATION EXCITATION

In this study, an experimental set-up for blades-shaft vibration monitoring under blade(s) random vibration excitation is used. The set-up natural frequencies and mode shapes are found using the ANSYS finite element package. The blades and shaft lateral and torsional vibration are monitored using blades strain-gages, bearing accelerometers and shaft torsional strain-gages stations. The results showed that the shaft torsional vibration measurement represents the blade(s) vibration more closely than the bearing accelerometers. In particular, the blades vibration at low frequencies corresponding to the blades bending and shaft torsional coupled modes is closely represented by the shaft torsional vibration signals. The results of this study increased the confidence in using the torsional vibration measurement for blades vibration identification and shed more light on the nature of coupling between the blade bending and shaft torsional vibration that occur at low frequencies

An Efficient Iris Segmentation Technique based on a Multiscale Approach

The use of biometric signatures, instead of tokens such as identification cards or computer passwords, continues to gain increasing attention as an efficient means of identification and verification of individuals for controlling access to secured areas, materials, or systems and a wide variety of biometrics has been considered over the years in support of these challenges. Iris recognition is especially attractive due to the stability of the iris texture patterns with age and health conditions. Iris image segmentation and localisation is a key step in iris recognition and plays an essential role the accuracy of matching. In this paper, we propose a new iris segmentation technique using a multiscale approach for edge detection, which is a fundamental issue in image analysis. Due to the presence of speckles, which can be modelled as a a strong multiplicative noise, edge detection for iris segmentation is very important and methods developed so far are generally applied in one single scale. In our proposed method, we introduce the concept of multiscale edge detection to improve iris segmentation. The technique is effecient for edge detetcion, greatly reduces the search space for the Hough transform and at the same time is robust to noise thus improving the overall performance. Linear Hough transform has been used for eyelids isolation, and an adaptive thresholding has been used for isolating eyelashes. Once the iris is segmented, a normalization step has been carried out by converting an iris image from cartesien into polar coordinates which are more suitable to deal with rotation and translation problems. Extensive experiments have been carried out and results obtained have shown an effectiveness of the proposed method which provides a high segmentation success of 99.6%

Experiments on the extraction of blade vibration signature from the shaft torsional vibration signals

This paper presents experiment results that examine the validity of extracting blade vibration signature from the shaft torsional vibration signals. A special test rig was designed and manufactured for this objective. A set of strain gages were bonded to the shaft and to the blades to measure the shaft twisting and blade bending deformations respectively. A controlled frequency exciter excited the blade vibration. The shaft torsional and blade bending vibration signals were simultaneously recorded and presented in the time and frequency domains. The blade bending vibration frequencies appeared dominantly in the shaft torsional vibration signals for all blade vibration frequencies up to 100Hz. For frequencies higher than 100Hz, less sensitivity of the torsional vibration to blade vibration was observed

ON THE INVESTIGATION OF VIBRATION SIGNALS USING JOINT TIME FREQUENCY ANALYSIS

This paper addresses the problem of coupled blade bending and shaft torsional vibration signals using the Joint Time Frequency Analysis (JTFA). Simulation results for the blade bending and shaft torsional vibration are studied using the Fast Fourier Transform (FFT) and the JTFA. The FFT spectra showed little information on the nonlinear dynamic interaction between the blade bending and the shaft torsional vibration; and thus cannot be used as a tool for monitoring the blade vibration by looking into the shaft torsional vibration signal. In contrast, the JTFA in the form of Wigner Ville Distribution (WVD) has given more useful information and reflected the dynamic interaction between different vibration modes on one side and between the blade vibration and the shaft torsional vibration on the other side. The obtained WVD representations of the shaft torsional vibration showed frequency layers that represent blade vibration activity

Kinetics of biodegradation of diethylketone by Arthrobacter viscosus

The performance of an Arthrobacter viscosus culture to remove diethylketone from aqueous solutions was evaluated. The effect of initial concentration of diethylketone on the growth of the bacteria was evaluated for the range of concentration between 0 and 4.8 g/l, aiming to evaluate a possible toxicological effect. The maximum specific growth rate achieved is 0.221 h-1 at 1.6 g/l of initial diethylketone concentration, suggesting that for higher concentrations an inhibitory effect on the growth occurs. The removal percentages obtained were approximately 88%, for all the initial concentrations tested. The kinetic parameters were estimated using four growth kinetic models for biodegradation of organic compounds available in the literature. The experimental data found is well fitted by the Haldane model (R2 = 1) as compared to Monod model (R2 = 0.99), Powell (R2 = 0.82) and Loung model (R2 = 0.95). The biodegradation of diethylketone using concentrated biomass was studied for an initial diethylketone concentration ranging from 0.8–3.9 g/l in a batch with recirculation mode of operation. The biodegradation rate found followed the pseudo-second order kinetics and the resulting kinetic parameters are reported. The removal percentages obtained were approximately 100%, for all the initial concentrations tested, suggesting that the increment on the biomass concentration allows better results in terms of removal of diethylketone. This study showed that these bacteria are very effective for the removal of diethylketone from aqueous solutions.The authors would like to gratefully acknowledge the financial support of this project by the Fundacao para a Ciencia e Tecnologia (FCT), Ministerio da Ciencia e Tecnologia, Portugal and Fundo Social Europeu (FSE). Cristina Quintelas thanks FCT for a Post-Doc grant

Contemporary Management of Locally Advanced and Recurrent Rectal Cancer: Views from the PelvEx Collaborative

Pelvic exenteration is a complex operation performed for locally advanced and recurrent pelvic cancers. The goal of surgery is to achieve clear margins, therefore identifying adjacent or involved organs, bone, muscle, nerves and/or vascular structures that may need resection. While these extensive resections are potentially curative, they can be associated with substantial morbidity. Recently, there has been a move to centralize care to specialized units, as this facilitates better multi-disciplinary care input. Advancements in pelvic oncology and surgical innovation have redefined the boundaries of pelvic exenterative surgery. Combined with improved neoadjuvant therapies, advances in diagnostics, and better reconstructive techniques have provided quicker recovery and better quality of life outcomes, with improved survival This article provides highlights of the current management of advanced pelvic cancers in terms of surgical strategy and potential future developments