Ultrasonic NDT and Imaging of Centrifugally Cast Stainless Steel Samples

Centrifugally cast stainless steel (CCSS) components are currently being used in many critical industrial applications such as nuclear reactors, which have stringent inspection requirements. Non-destructive testing (NDT) of these components are governed by strict guidelines to insure safe operating conditions. Current literature indicates that ultrasonic NDT techniques provide potentially the most promising and reliable methods for the inspection of CCSS components. However, the received signal often has low signal-to-noise ratio (SNR) due to ultrasonic attenuation caused by grain scattering. Furthermore, ultrasonic inspection of CCSS components is plagued by high attenuation, velocity variations, mode conversion, beam divergence and/or convergence, and skewing. Therefore, the signals arising from metallurgical discontinuities or defects caused by thermal fatigue and stress corrosion, can appear to a manual ultrasonic inspector as random, stationary-noise signals. The ability to detect such defects is at best limited with the conventional non-destructive evaluation techniques. In this paper, some spectral methods are presented to improve flaw visibility by reducing the background noise from the CCSS microstructure.</p

Nondestructive Testing Potential of a Magnetoacoustic Storage Correlator (MASC)

A simple magnetoacoustic storage correlator (MASC) was tested as a pulse compressor in an ultrasonic nondestructive testing application. The pulse compression ratio reached was 30. Higher compression ratios are readily available through choice of different device lengths and device operating regime. The system is flexible; it is not limited to any particular type of large time-bandwidth signal. The correlator reference signal is easily programmable and erasable, and can be changed at any time. This system offers real-time correlation signal processing at a repetition rate that is only limited by the temporal length of the large time-bandwidth signal

Implementation of Self-Noise Suppression Techniques for Ultrasonic Correlation Systems

Pseudo-random signal correlation techniques can improve the flaw detection capability of ultrasonic NDE systems. While the correlation-based systems provide significant improvement in the signal-to-noise ratio compared to pulsed systems, their performance is limited by the so-called “self-noise” of the system. Self-noise is a result of imperfect autocorrelation characteristics of the excitation signal. Last year, we suggested some techniques for improving the flaw detection capability of continuous-mode ultrasonic NDE systems [1]. These systems use a continuously transmitted coded waveform as an excitation signal, and the received signal is processed through a correlation filter. This year, we present another new approach and demonstrate performance results and the practicability of each approach.</p

Choice of Coded Waveform and Correlation Filter for Self-Noise Suppression in Ultrasonic Correlation Systems

Various ultrasonic correlation systems have been suggested in the past [1–5] in order to improve the flaw detection capability of ultrasonic NDE systems. These systems use a coded waveform for transmission, and the received signal is processed through a correlation filter. Although, these systems provide considerable improvement in the flaw detection capability, their performance is limited by what is called “self-noise” of the system. This paper discusses the self-noise limitation of conventional ultrasonic correlation systems and presents various approaches for self-noise suppression. Theoretically predicted performance has been verified using detailed computer simulations. Finally, comparison of the performance and practicability of each approach is discussed

A transaction replication scheme for a replicated database with node autonomy

Ultrasonic nondestructive testing of large grained materials is limited by the ability of the detection process to distinguish the flaw signals from the backscattered grain boundary echoes. This coherent grain noise often masks the echo from inhomogeneities and defects in the material. Absorption and scattering effects further reduce the ultrasound energy leading to poor signal-to-noise ratio in the received signal. It is not possible to reduce the grain clutter by conventional time averaging techniques due to its coherent nature. Different algorithms utilizing the principles of frequency diversity and spatial diversity have been used in the past for signal-to-noise ratio enhancement. In NDE applications where the noise is primarily due to Rayleigh scattering, it can be shown that flaw detection can be improved significantly by merely bandpass filtering the lower part of the received wideband echo spectrum. Both theoretical and experimental results are presented to support this conclusion. The filtering technique is successfully tested on materials with different grain sizes. The main advantage of this method is its relative simplicity, which eliminates the need for sophisticated and computationally intensive signal processing algorithms. Furthermore, this technique allows simple hardware implementation for real-time applications. The optimal parameters, i.e., the center frequency and bandwidth of the bandpass filter are experimentally determined

A Robust Detection Algorithm Using Frequency Diverse Multiple Observations

The detection of a flaw embedded in large-grained material using high-resolution broadband ultrasonic pulses is hindered by high amplitude interfering echoes (speckle) due to the unresolvable grain boundaries. The application of an optimal linear processor in this case is complicated by the fact that statistical parameters of the grain noise are not known a priori</p

A Cube Model for Web Access Sessions and Cluster Analysis

The major problem in an ultrasonic flaw detection system is the presence of microstructure noise (clutter) resulting from scattering at grain boundaries. Ultrasonic grain echoes are random in amplitude and arrival time and often interfere and mask the flaw echo. Grain echoes are stationary and correlated from scan to scan in the same propagation path. An effective method of decorrelating grain echoes can be achieved by changing the frequency from scan to scan, a method known as frequency diversity. In practice frequency diverse grain echoes can be obtained by transmitting a broadband echo through the materials and bandpass filtering the received echoes over many bands of frequencies. At any given time the outputs of bandpass filters are the features representing information related to flaw or grain echoes. Although these outputs are random, the statistics of flaws and grains echoes are different. This situation permits application of statistical pattern recognition using a Bayes classifier. Experimental data and computer simulation have confirmed that flaw and clutter echoes over different frequency bands have a Gaussian distribution with different covariance matrices. For this situation the Bayes classifier is quadratic and provides optimal flaw detection performance. Presented here is the design of an optimal classifier with experimental and simulated results

Supporting ranking pattern-based aggregate queries in sequence data cubes

Sequence data processing has been studied extensively in the literature. In recent years, the warehousing and online-analytical processing (OLAP) of archived sequence data have received growing attentions. In particular, the concept of sequence OLAP is recently proposed with the objective of evaluating various kinds of so-called Pattern-Based Aggregate (PBA) queries so that various kinds of data analytical tasks on sequence data can be carried out efficiently. This paper studies the evaluation of ranking PBA queries, which rank the results of PBA queries and return only the top-ranked ones to users. We discuss how ranking PBA queries drastically improve the usability of S-OLAP systems and present techniques that can evaluate various kinds of ranking PBA queries efficiently. Copyright 2009 ACM.link_to_OA_fulltex