Researchers at the Timken Company conceived a project to develop an on-line instrument for wall thickness measurement of steel seamless mechanical tubing based on laser ultrasonic techology. The instrument, which has been installed and tested at a piercing mill, provides data on tube eccentricity and concentricity. Such measurements permit fine-tuning of manufacturing processes to eliminate excess material in the tube wall and therefore provide a more precisely dimensioned product for their customers. The resulting process energy savings are substantial, as is lowered environmental burden. The expected savings are $85.8 million per year in seamless mechanical tube piercing alone. Applied across the industry, this measurement has a potential of reducing energy consumption by 6 ~ 1 0 ’ ~ BTU per year, greenhouse gas emissions by 0.3 million metric tons carbon equivalent per year, and toxic waste by 0.255 million pounds per year. The principal technical contributors to the project were the Timken Company, Tndustrial Materials Institute (IMI, a contractor to Timken), and Oak Ridge National Laboratory (ORNL). Timken provided mill access as well as process and metallurgical understanding. Timken researchers had previously developed fundamental ultrasonice analysis methods on which this project is based. TMT developed and fabricated the laser ultrasonic generation and receiver systems. ORNL developed Bayesian and wavelet based real-time signal processing, spread-spectrum wireless communication, and explored feature extraction and pattern recognition methods. The resulting instrument has successfully measured production tubes at one of Timken’s piercing mills. This report concentrates on ORNL’s contribution through the CRADA mechanism. The three components of O m ’ s contribution were met with mixed success. The real-time signal-processing task accomplished its goal o f improvement in detecting time of f l ight information with a minimum of false data. The signal processing algorithm development resulted in a combination of processing steps that can be set to generate no spoofs from noise, while simultaneously missing fewer than 10% of good trials. The algorithm leads to a 95% probability that the estimate of time of flight is good to within 4 time bins or fewer for laser excitations above 30 mJ for the first two echoes of the signal. Receiver Operating Characteristic (ROC) curves for the algorithm indicate that the algorithm is very robust against errors for excitations above at 35 mJ and above, tolerable at 30 mJ and unacceptable below 30 mJ. For the wireless tube detection task, a 91 6.4 MHz spread spectrum transmitter, repeater, receiver system was developed based on previous wireless research at ORNL. The wireless detector identified when a hot tube or billet entered the piercing process and signaled the laser systems to get ready for a measurement. At the first of the installation, we saw slight microwave interference from a nearby nationwide pager system, which we corrected by moving the center fi-equency of our direct sequence, spread spectrum transmitter. We determined that exposure to the harsh environments of the steel mill over long duration did not seem to adversely effect the equipment. However, we continued to see glitches in the digital portion of the data processing, which seemed to originate from the handshake between the IMI computer and the ORNL receiver. The continuous poling

As U.S. natural gas supply pipelines are aging, non-destructive inspection techniques are needed to maintain the integrity and reliability of the natural gas supply infrastructure. Ultrasonic waves are one promising method for non-destructive inspection of pipeline integrity. As the waves travel through the pipe wall, they are affected by the features they encounter. In order to build a practical inspection system that uses ultrasonic waves, an analysis method is needed that can distinguish between normal pipe wall features, such as welds, and potentially serious flaws, such as cracks and corrosion. Ideally, the determination between “flaw” and “no-flaw” must be made in real-time as the inspection system passes through the pipe. Because wavelet basis functions share some common traits with ultrasonic waves, wavelet analysis is particularly well-suited for this application. Using relatively simple features derived from the wavelet analysis of ultrasonic wave signatures traveling in a pipe wall, we have successfully demonstrated the ability to distinguish between the “flaw” and “no-flaw” classes of ultrasonic features.

At its substratum, brain/mind organization requires both synaptic firings and non-synaptic events. Synaptic firings organize the pattern of non-synaptic events. Non-synaptic events organize the pattern of synaptic firings. The processes are related in a bizarre hierarchy. Comparing these processes to electric circuits, it is as if we have two circuits that each continuously and simultaneously update the topology, and consequently, the dynamical laws of the other. Since either can be seen to be rebuilding the other, from its own perspective each process appears higher than the other in a hierarchy. This same kind of hierarchy is found in a hyperset structure. Interpreted as a directed graph, the nodes in a hyperset form a hierarchy in which, from the perspective of any node in the hierarchy, that node is at the top. This organizational structure violates the Foundation Axiom. Algorithmic computation strictly complies with the Foundation Axiom. Thus, an algorithm organized like a hyperset is a contradiction in terms. Does this contradiction mean are we precluded forever from implementing brain-like activities artificially? Not at all! An algorithm is incapable of doing the job, but nothing prevents us from constructing interacting analog processes that update each other's dynamical laws on the fly.

This paper is concerned with the detection of physical flaws on pipe walls in gas pipelines. The sensor technology is EMAT, a non-contact ultrasonic technology. One EMAT is used as a transmitter, exciting an ultrasonic impulse into the pipe wall. Another EMAT located a few inches away from the first is used as a receiving transducer. This paper reports on the identification of flaw signatures in the receiver output. The first step in flaw characterization is to perform wavelet analysis of the signature. Being non-shift-invariant, an array of coefficients of a discrete wavelet transfor of a signal is not directly suitable as a pattern recognition feature. However, comparing composite properties of the signal on different scales is useful, because the more conversion caused by a flaw, changes the composite properties of the signal in wavelet space. For EMAT data, the useful information projects onto five mutually orthogonal wavelet scales. This paper reports onteh use of a robust 17-dimensional feature vector that mutually orthogonal wavelet scales. This paper reports on the use of a robust 17-dimensional featuer vector that consistently distinguishes "flaw" signatures from "no-flaw" signatures in a substantial collection of experimental data.

The problem of disentangling overlapping modes has been a persistent barrier to the practical use of confined ultrasonic waves for NDE. In the time-domain, the ultrasonic signature of overlapping waves is an unintelligible mess. Because each confined wave mode is dispersive and because many modes overlap in the frequency-domain, Fourier analysis is of little practical help. Research at ORNL shows that Bayesian parameter estimation has great potential for many NDE applications using confined ultrasonic waves.

A persistent problem in the analysis of Lamb wave signatures in experimental data is the fact that several different modes appear simultaneously in the signal. The modes overlap in both frequency and time domains. Attempts to separate the overlapping Lamb wave signatures by conventional signal processing methods have been unsatisfactory, As might be expected, the transient nature of Lamb waves makes them readily tractable to wavelet analysis. The authors have used the discrete wavelet transform and the wavelet packet transform to untangle the Lamb wave signature. Furthermore, both techniques are realizable in the highly parallel cascaded-lattice architecture, and are well suited for on-line real-time instrumentation. For signatures of Lamb waves captured in laser ultrasonic data in tailor-welded blanks, this has led to straightforward detection of weld defects and demonstration of principle that weld defects can be classified according to the type of defect as revealed by features in wavelet space. This technique has considerable commercial value for online monitoring of manufacturing processes. For example, laser-based ultrasonic (LBU) measurement shows great promise for on-line monitoring of weld quality in tailor-welded blanks. Tailor-welded blanks are steel blanks made from plates of differing thickness and/or properties butt-welded together; they are used in automobile manufacturing to produce body, frame, and closure panels.

Self-referential systems have some remarkable properties. The processes of life and mind are not only self-referential, but self-reference turns out to be a crucial property of both. However, they are difficult to understand. From a given starting point, both endogenous systems (self-referential natural systems) and impredicative systems (self-referential formal systems) have infinitely many logically consistent consequences. Both are incomputable; neither halts after a finite number of steps. Therefore, neither can produce an exact prediction of the behavior of the other in finitely many steps. Despite the fact that all engineering decisions are based on incomplete information, this inherent inability of an impredicative model to produce exact predictions of an endogenous system is troubling to some engineers. Nevertheless, self-reference leads to a more general, but no less rational, form of modeling than that provided by traditional reductionism. Although the mathematics of self-reference is unfamiliar to engineers, its power is dramatic. For example, it resolves the apparent paradox of how a brain/mind possessing freewill can operate in a deterministic Universe.

Laser-based ultrasonic (LBU) measurement shows great promise for on-line monitoring of weld quality in tailor-welded blanks. Tailor-welded blanks are steel blanks made from plates of differing thickness and/or properties butt-welded together; they are used in automobile manufacturing to produce body, frame, and closure panels. LBU uses a pulsed laser to generate the ultrasound and a continuous wave laser interferometer to detect the ultrasound at the point of interrogation to perform ultrasonic inspection. LBU enables in-process measurements since there is no sensor contact or near-contact with the workpiece. The authors are using laser-generated plate waves to propagate from one plate into the weld nugget as a means of detecting defects.

Investigates a potential solution to the "large-population" speaker identification problem by characterizing a voice by the entailments in two different kinds of models. These entailments are found in the representational models of neuro-linguistic programming (NLP) and in the model of the mechanics of the voice as revealed by the continuous wavelet transform (CWT). Results to date have been obtained from examining samples in the TIMIT database and human subjects. Local features correlated with individual speakers for selected vowel sounds have been found in the CWT space. Features of NLP representation systems have also been found and are compared with voice features for speakers whose NLP representation systems are known a priori. Gaussian mixture models are used to calculate probability density functions from the local feature distributions. This speaker identification strategy combines three elements of novelty. First, it exploits the fact that the 2D CWT of a 1D signal can be interpreted as an image, and can thus use feature extraction techniques first developed for image processing. Second, voice waveforms are systematically studied to identify features that are attributed to the speaker's mental representation. Third, the reliability of the identification is strengthened by combining entailments from these two completely different aspects of the speaker's identity: the mechanical aspects of the speaker's vocal tract and the pattern of representation.

Laser-based ultrasonic (LBU) measurement shows great promise for on-line monitoring of weld quality in tailor-welded blanks. Tailor-welded blanks are steel blanks made from plates of differing thickness and/or properties bun-welded together; they are used in automobile manufacturing to produce body, frame, and closure panels. LBU uses a pulsed laser to generate the ultrasound and a continuous wave (CW) laser interferometer to detect the ultrasound at the point of interrogation to perform ultrasonic inspection. LBU enables in-process measurements since there is no sensor contact or near-contact with the workpiece. The authors are using laser-generated plate (Lamb) waves to propagate from one plate into the weld nugget as a means of detecting defects.A persistent problem in the analysis of Lamb wave signatures in experimental data is the fact that several different modes appear simultaneously in the signal. The modes overlap in both frequency and time domains. Attempts to separate the overlapping Lamb wave signatures by conventional signal processing methods have been unsatisfactory. As might be expected, the transient nature of Lamb waves makes them readily tractable to wavelet analysis. The authors have used discrete wavelet and wavelet packet analysis to untangle the Lamb wave signature. For signatures of Lamb waves captured in laser ultrasonic data in tailor-welded blanks, this has led to straightforward detection of weld defects. Furthermore, both techniques are realizable in the highly parallel cascaded-lattice architecture, and are well suited for on-line real-time monitoring of laser ultrasonic signals.

Examines the shortcomings of conventional analysis when applied to complex processes, and considers the consequences of ignoring process behaviors simply because they do not conveniently project on to lists of numbers. Complex behavior is bizarre, but not absurd. Bizarre systems are counter-intuitive, and yet bizarre behavior is logically tractable. The inferential linkages within a bizarre system's epistemological model are congruent with the causal linkages that govern its ontological behavior. From the perspective of neurophysiology, the behaviors that we normally consider to be intelligent are irreducible to a list of numbers. This being the case, no list of numbers, no matter how big, can emulate intelligent behavior. To discuss intelligence other than by empirical observation, some logical description of it must be found that is not limited to predicative inferential structures. Mathematics abounds with such alternatives; impredicative mathematical entities provide powerful ways of describing complex behavior. They do so at a cost, being non-algorithmic. Engineering decisions based on predictions made by attempting to reduce complex behaviors to algorithms cannot be trusted; the projection ignores key aspects of the behavior. Present-day computers only work for algorithmic processes. An engineered artifact that exhibits intelligent behavior requires at least one, and possibly both, of the following developments: a more powerful model of computation than the Turing machine, and/or a computing element that has entailments similar to those observed in complex processes.

The "mind" can be defined as a range of functions created from sensory experience that are paired with our representation systems reflected through our behavior. These representation systems (visual, auditory and kinesthetic modalities) are foundations for how effective choices and belief systems are generated through sensory-derived processes; how decision-making and learning strategies are constructed; how memory is accessed, stored, retrieved or recalled, and how behavior and knowledge is actualized at both the conscious and unconscious levels. It is these same representational systems that provide us with the capability to model and replicate the cognitive processing of the human mind. This paper provides an explanation for modeling the inner workings of the 'cognitive black box', better known as the 'mind'.

The objective of this research, and subsequent testing, was to identify specific features of cavitation that could be used as a model-based descriptor in a context-dependent condition-based maintenance (CD-CBM) anticipatory prognostic and health assessment model. This descriptor is based on the physics of the phenomena, capturing the salient features of the process dynamics. The test methodology and approach were developed to make the cavitation features the dominant effect in the process and collected signatures. This would allow the accurate characterization of the salient cavitation features at different operational states. By developing such an abstraction, these attributes can be used as a general diagnostic for a system or any of its components. In this study, the particular focus will be pumps. As many as 90% of pump failures are catastrophic. They seem to be operating normally and fail abruptly without warning. This is true whether the failure is sudden hardware damage requiring repair, such as a gasket failure, or a transition into an undesired operating mode, such as cavitation. This means that conventional diagnostic methods fail to predict 90% of incipient failures and that in addressing this problem, model-based methods can add value where it is actually needed.

In today's manufacturing environment, plants, systems, and equipment are being asked to perform at levels not thought possible a decade ago. The intent is to improve process operations and equipment reliability, availability, and maintainability without costly upgrades. Of course these gains must be achieved without impacting operational performance. Downsizing is also taking its toll on operations. Loss of personnel, particularly those who represent the corporate history, is depleting US industries of their valuable experiential base which has been relied on so heavily in the past. These realizations are causing companies to rethink their condition-based maintenance policies by moving away from reacting to equipment problems to taking a proactive approach by anticipating needs based on market and customer requirements. This paper describes a different approach to condition-based maintenance-context-dependent prognostics and health assessment. This diagnostic capability is developed around a context-dependent model that provides a capability to anticipate impending failures and determine machine performance over a protracted period of time. This prognostic capability links operational requirements to an economic performance model. In this context, a system may provide 100% operability with less than 100% functionality. This paradigm is used to facilitate optimal logistic supply and support.

A major problem with cavitation in pumps and other hydraulic devices is that there is no effective method for detecting or predicting its inception. The traditional approach is to declare the pump in cavitation when the total head pressure drops by some arbitrary value (typically 3o/0) in response to a reduction in pump inlet pressure. However, the pump is already cavitating at this point. A method is needed in which cavitation events are captured as they occur and characterized by their process dynamics. The object of this research was to identify specific features of cavitation that could be used as a model-based descriptor in a context-dependent condition-based maintenance (CD-CBM) anticipatory prognostic and health assessment model. This descriptor was based on the physics of the phenomena, capturing the salient features of the process dynamics. An important element of this concept is the development and formulation of the extended process feature vector @) or model vector. Thk model-based descriptor encodes the specific information that describes the phenomena and its dynamics and is formulated as a data structure consisting of several elements. The first is a descriptive model abstracting the phenomena. The second is the parameter list associated with the functional model. The third is a figure of merit, a single number between [0,1] representing a confidence factor that the functional model and parameter list actually describes the observed data. Using this as a basis and applying it to the cavitation problem, any given location in a flow loop will have this data structure, differing in value but not content. The extended process feature vector is formulated as follows: E`> [ , {parameter Iist}, confidence factor]. (1) For this study, the model that characterized cavitation was a chirped-exponentially decaying sinusoid. Using the parameters defined by this model, the parameter list included frequency, decay, and chirp rate. Based on this, the process feature vector has the form: @=> [ , {01 = a, ~= b, ~ = c}, cf = 0.80]. (2) In this experiment a reversible catastrophe was examined. The reason for this is that the same catastrophe could be repeated to ensure the statistical significance of the data.

Laser-based ultrasonic (LBU) measurement shows great promise for on-line monitoring of weld quality in tailor-welded blanks. Tailor-welded blanks are steel blanks made from plates of differing thickness and/or properties butt-welded together; they are used in automobile manufacturing to produce body, frame, and closure panels. LBU uses a pulsed laser to generate the ultrasound and a continuous wave (CW) laser interferometer to detect the ultrasound at the point of interrogation to perform ultrasonic inspection. LBU enables in-process measurements since there is no sensor contact or near-contact with the workpiece. The authors have used laser-generated plate (Lamb) waves to propagate from one plate into the weld nugget as a means of detecting defects. This report recounts an investigation of a number of inspection architectures based on processing of signals from selected plate waves, which are either reflected from or transmitted through the weld zone. Bayesian parameter estimation and wavelet analysis (both continuous and discrete) have shown that the LBU time-series signal is readily separable into components that provide distinguishing features, which describe weld quality. The authors anticipate that, in an on-line industrial application, these measurements can be implemented just downstream from the weld cell. Then the weld quality data can be fed back to control critical weld parameters or alert the operator of a problem requiring maintenance. Internal weld defects and deviations from the desired surface profile can then be corrected before defective parts are produced. The major conclusions of this study are as follows. Bayesian parameter estimation is able to separate entangled Lamb wave modes. Pattern recognition algorithms applied to Lamb mode features have produced robust features for distinguishing between several types of weld defects. In other words, the information is present in the output of the laser ultrasonic hardware, and it is feasible to extract it. Wavelet analysis produces results that are almost as good as Bayesian, but execute a thousand times faster. This study demonstrates the principle that it is feasible to construct a laser ultrasonic system to detect weld defects in thin metal parts on-line in real-time, and to classify the defects according to type.

The Anticipatory System (AS) formalism developed by Robert Rosen provides some insight into the problem of embedding intelligent behavior in machines. AS emulates the anticipatory behavior of biological systems. AS bases its behavior on its expectations about the near future and those expectations are modified as the system gains experience. The expectation is based on an internal model that is drawn from an appeal to physical reality. To be adaptive, the model must be able to update itself. To be practical, the model must run faster than real-time. The need for a physical model and the requirement that the model execute at extreme speeds, has held back the application of AS to practical problems.Two recent advances make it possible to consider the use of AS for practical intelligent sensors. First advances in transducer technology make it possible to obtain previously unavailable data from which a model can be derived. For example, acoustic emissions (AE) can be fed into a Bayesian system identifier that enables the separation of a weak characterizing signal such as the signature of pump cavitation precursors, from a strong masking signal, such as a pump vibration feature. The second advance is the development of extremely fast, but inexpensive, digital signal processing hardware on which it is possible to run an adaptive Bayesian-derived model faster than real-time. This paper reports the investigation of an AS using a model of cavitation based on hydrodynamic principles and Bayesian analysis of data from high-performance AE sensors.

Laser-based ultrasonic (LBU) measurement shows great promise for on-line monitoring of weld quality in tailor-welded blanks. Tailor-welded blanks are steel blanks made from plates of differing thicknesses and/or properties butt- welded together, they are used in automobile manufacturing to produce body, frame, and closure panels. LBU uses a pulsed laser to generate the ultrasound and a continuous wave laser interferometer to detect the ultrasound at the point of interrogation to perform ultrasonic inspection. LBU enables in-process measurements since there is no sensor contact or near-contact with the workpiece.