26 research outputs found
Lifecycle Prognostics Architecture for Selected High-Cost Active Components
There are an extensive body of knowledge and some commercial products available for calculating prognostics, remaining useful life, and damage index parameters. The application of these technologies within the nuclear power community is still in its infancy. Online monitoring and condition-based maintenance is seeing increasing acceptance and deployment, and these activities provide the technological bases for expanding to add predictive/prognostics capabilities. In looking to deploy prognostics there are three key aspects of systems that are presented and discussed: (1) component/system/structure selection, (2) prognostic algorithms, and (3) prognostics architectures. Criteria are presented for component selection: feasibility, failure probability, consequences of failure, and benefits of the prognostics and health management (PHM) system. The basis and methods commonly used for prognostics algorithms are reviewed and summarized. Criteria for evaluating PHM architectures are presented: open, modular architecture; platform independence; graphical user interface for system development and/or results viewing; web enabled tools; scalability; and standards compatibility. Thirteen software products were identified and discussed in the context of being potentially useful for deployment in a PHM program applied to systems in a nuclear power plant (NPP). These products were evaluated by using information available from company websites, product brochures, fact sheets, scholarly publications, and direct communication with vendors. The thirteen products were classified into four groups of software: (1) research tools, (2) PHM system development tools, (3) deployable architectures, and (4) peripheral tools. Eight software tools fell into the deployable architectures category. Of those eight, only two employ all six modules of a full PHM system. Five systems did not offer prognostic estimates, and one system employed the full health monitoring suite but lacked operations and maintenance support. Each product is briefly described in Appendix A. Selection of the most appropriate software package for a particular application will depend on the chosen component, system, or structure. Ongoing research will determine the most appropriate choices for a successful demonstration of PHM systems in aging NPPs
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Lifecycle Prognostics Architecture for Selected High-Cost Active Components
There are an extensive body of knowledge and some commercial products available for calculating prognostics, remaining useful life, and damage index parameters. The application of these technologies within the nuclear power community is still in its infancy. Online monitoring and condition-based maintenance is seeing increasing acceptance and deployment, and these activities provide the technological bases for expanding to add predictive/prognostics capabilities. In looking to deploy prognostics there are three key aspects of systems that are presented and discussed: (1) component/system/structure selection, (2) prognostic algorithms, and (3) prognostics architectures. Criteria are presented for component selection: feasibility, failure probability, consequences of failure, and benefits of the prognostics and health management (PHM) system. The basis and methods commonly used for prognostics algorithms are reviewed and summarized. Criteria for evaluating PHM architectures are presented: open, modular architecture; platform independence; graphical user interface for system development and/or results viewing; web enabled tools; scalability; and standards compatibility. Thirteen software products were identified and discussed in the context of being potentially useful for deployment in a PHM program applied to systems in a nuclear power plant (NPP). These products were evaluated by using information available from company websites, product brochures, fact sheets, scholarly publications, and direct communication with vendors. The thirteen products were classified into four groups of software: (1) research tools, (2) PHM system development tools, (3) deployable architectures, and (4) peripheral tools. Eight software tools fell into the deployable architectures category. Of those eight, only two employ all six modules of a full PHM system. Five systems did not offer prognostic estimates, and one system employed the full health monitoring suite but lacked operations and maintenance support. Each product is briefly described in Appendix A. Selection of the most appropriate software package for a particular application will depend on the chosen component, system, or structure. Ongoing research will determine the most appropriate choices for a successful demonstration of PHM systems in aging NPPs
Determining Remaining Useful Life of Aging Cables in Nuclear Power Plants ? Interim Study FY13
The most important criterion for cable performance is its ability to withstand a design-basis accident. With nearly 1000 km of power, control, instrumentation, and other cables typically found in an NPP, it would be a significant undertaking to inspect all of the cables. Degradation of the cable jacket, electrical insulation, and other cable components is a key issue that is likely to affect the ability of the currently installed cables to operate safely and reliably for another 20 to 40 years beyond the initial operating life. The development of one or more nondestructive evaluation (NDE) techniques and supporting models that could assist in determining the remaining life expectancy of cables or their current degradation state would be of significant interest. The ability to nondestructively determine material and electrical properties of cable jackets and insulation without disturbing the cables or connections has been deemed essential. Currently, the only technique accepted by industry to measure cable elasticity (the gold standard for determining cable insulation degradation) is the indentation measurement. All other NDE techniques are used to find flaws in the cable and do not provide information to determine the current health or life expectancy. There is no single NDE technique that can satisfy all of the requirements needed for making a life-expectancy determination, but a wide range of methods have been evaluated for use in NPPs as part of a continuous evaluation program. The commonly used methods are indentation and visual inspection, but these are only suitable for easily accessible cables. Several NDE methodologies using electrical techniques are in use today for flaw detection but there are none that can predict the life of a cable. There are, however, several physical and chemical ptoperty changes in cable insulation as a result of thermal and radiation damage. In principle, these properties may be targets for advanced NDE methods to provide early warning of aging and degradation. Examples of such key indicators include changes in chemical structure, mechanical modulus, and dielectric permittivity. While some of these indicators are the basis of currently used technologies, there is a need to increase the volume of cable that may be inspected with a single measurement, and if possible, to develop techniques for in-situ inspection (i.e., while the cable is in operation). This is the focus of the present report
Design of wavelet neural networks based on symmetry fuzzy C-means for function approximation
Specifying the number and locations of the translation vectors for wavelet neural networks (WNNs) is of paramount significance as the quality of approximation may be drastically reduced if initialization of WNNs parameters was not done judiciously. In this paper, an enhanced fuzzy C-means algorithm, specifically the modified point symmetry–based fuzzy C-means algorithm (MPSDFCM), was proposed, in order to determine the optimal initial locations for the translation vectors. The proposed neural network models were then employed in approximating five different nonlinear continuous functions. Assessment analysis showed that integration of the MPSDFCM in the learning phase of WNNs would lead to a significant improvement in WNNs prediction accuracy. Performance comparison with the approaches reported in the literature in approximating the same benchmark piecewise function verified the superiority of the proposed strategy
A Signal Classification Network That Computes its Own Reliability
Automatic signal classification (ASC) systems are used extensively for signal interpretation in non-destructive evaluation (NDE) applications. Their popularity stems from the fact that they are capable of rapid analysis of large amounts of data. In addition, they offer more accurate and consistent data interpretation as well as allow storage of expert knowledge.</p
Artmap Networks for Classification of Ultrasonic Weld Inspection Signals
Inverse problems in Nondestructive Evaluation (NDE) involve estimating the characteristics of flaws from measurements obtained during an inspection. Several techniques have been developed over the years for solving the inverse problem [1]. These techniques range from calibration approaches to numerical methods based on integral equations. Signal identification and classification is one of the more popular approaches for inverse problems encountered in many practical NDE applications.</p
A Signal Classification Network That Computes its Own Reliability
Automatic signal classification (ASC) systems are used extensively for signal interpretation in non-destructive evaluation (NDE) applications. Their popularity stems from the fact that they are capable of rapid analysis of large amounts of data. In addition, they offer more accurate and consistent data interpretation as well as allow storage of expert knowledge
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Irradiation Testing of Ultrasonic Transducers
Ultrasonic technologies offer the potential to me
Qualification requirements of guided ultrasonic waves for inspection of piping in light water reactors
It is anticipated that guided ultrasonic wave (GUW) techniques will eventually see widespread application in the nuclear power industry as there are several near-term and future needs that could benefit from the availability of GUW technologies. Already, GUW techniques are receiving consideration for inspecting buried piping at nuclear power plants and future applications may include several Class 1 and 2 components. To accept the results of a nondestructive examination of safety critical components, the U.S. Nuclear Regulatory Commission requires that the examinations be performed using qualified equipment, personnel, and procedures. As the use of GUW techniques becomes more frequent, qualification may be required. Performance demonstration has been the approach to qualifying conventional NDE methods in the nuclear power industry. This paper highlights potential issues and research needs associated with facilitating GUW qualification for the nuclear power industry. Parametric studies of essential inspection parameters are necessary to understand their influence on inspection performance. The large volume sampling capability introduces several challenges for qualifying GUW techniques including the quantification of performance, potential interference caused by the presence of multiple flaws in the inspection region, and the practicality of manufacturing several large qualification specimens. Computer simulation may have a significant role in reducing the experimental burden associated with qualifying GUW techniques for nuclear power plant examinations.Copyright 2013 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics.
This article appeared in AIP Conference Proceedings 1511 (2013): 1662–1669 and may be found at http://dx.doi.org/10.1063/1.4789241.</p