Sensor Signal Analysis By Neural Networks For Surveillance In Nuclear Reactors

The application of neural networks as a tool for reactor diagnostics is examined here. Reactor pump signals utilized in a wear-out monitoring system developed for early detection of the degradation of a pump shaft [17] are analyzed as a semi-benchmark test to study the feasibility of neural networks for monitoring and surveillance in nuclear reactors. The Adaptive Resonance Theory (ART 2 and ART 2-A) paradigm of neural networks is applied in this study. The signals are collected signals as well as generated signals simulating the wear progress. The wear-out monitoring system applies noise analysis techniques and is capable of distinguishing these signals apart and providing a measure of the progress of the degradation. This paper presents the results of the analysis of these data and provides an evaluation on the performance of ART 2-A and ART 2 for reactor signal analysis. The selection of ART 2 is due to its desired design principles such as unsupervised learning, stability-plasticity, search-direct access, and the match-reset tradeoffs. ART 2-A is selected for its speed. Two simulators are built. One is ART 2, and the other ART 2-A. The result is a success for both paradigms, and the study shows that ART 2-A is not only able to learn and distinguish the patterns from each other, its learning speed is also extremely fast despite the high-dimensional input spaces. © 1992 IEE

Diagnostics and Control of Natural Gas-Fired furnaces via Flame Image Analysis using Machine Vision & Artificial Intelligence Techniques

A new approach for the detection of real-time properties of flames is used in this project to develop improved diagnostics and controls for natural gas fired furnaces. The system utilizes video images along with advanced image analysis and artificial intelligence techniques to provide virtual sensors in a stand-alone expert shell environment. One of the sensors is a flame sensor encompassing a flame detector and a flame analyzer to provide combustion status. The flame detector can identify any burner that has not fired in a multi-burner furnace. Another sensor is a 3-D temperature profiler. One important aspect of combustion control is product quality. The 3-D temperature profiler of this on-line system is intended to provide a tool for a better temperature control in a furnace to improve product quality. In summary, this on-line diagnostic and control system offers great potential for improving furnace thermal efficiency, lowering NOx and carbon monoxide emissions, and improving product quality. The system is applicable in natural gas-fired furnaces in the glass industry and reheating furnaces used in steel and forging industries

Progress report no. 7

Statement of responsibility on title-page reads: editor: M.J. Driscoll; contributors: D.C. Aldrich, M.J. Driscoll, O.K. Kadiroglu, S. Keyvan, H.U.R. Khan, D.D. Lanning, R. Morton, J. Pasztor, T.J. Reckart, A.A. Salehi, J.I. Shin, A.T. Supple, D.J. Wargo, and S.S. WuIncludes bibliographical referencesProgress report; September 30, 1976U.S. Atomic Energy Commission contracts: E(11-1) 225

Computer-Based Teaching and Assessment in Topics on Basic Physics

This paper describes an experience in computer-based teaching and assessment in three topics in basic physics. A module is developed for each topic using the Authorware courseware authoring tool. The first module is on fundamental particles, the second on binding energy, and the third on atom density calculation. These modules are also installed on the web. Each module has four components: 1) definition, 2) example, 3) review questions, and 4) quiz. Students can see their performance on review questions interactively and have the option to repeat them, and receive on-line feedback on their score. Similarly, their performance on a quiz is evaluated on-line and feedback is provided to them. In addition, their score on each quiz as well as the time they spent taking the quiz are sent back to the instructor and stored in a permanent file. The courseware provides an overall assessment, in graphical format, of the average performance of all students who took a quiz, as well as each individual student\u27s performance. These modules are taught as supplementary part s of a course in Fundamentals of Nuclear Engineering at the University of Missouri-Rolla Nuclear Engineering Department. The experience has been positive with more than 80% of the students supporting the value of the interactive and self-pace learning of these modules

Combustion Control Experimentations at a Pilot Scale Glass Furnace

In a multi-burner furnace, inefficient operation of individual burners could result in furnace operation at less than optimal fuel efficiency and elevated pollutant emissions. This paper presents various experimental explorations using a pilot scale glass furnace to investigate the impact of optimum combustion on flue gas emissions such as NOx. the glass furnace utilized is a 23-146 kW pilot scale furnace that can melt from about 45 kg to 900 kg of glass/day. Furnace design allows both air-gas and oxy-fuel combustion with different burner types and burner arrangements. the furnace is controlled through a Lab View hardware and software control system. Results from combustion control experimentation under ramp-up condition and various oxygen/fuel ratios from this pilot scale glass furnace are presented here. the oxygen/fuel ratio was varied from 1.8 to 2.4 with various combustion control experimentations in both step and ramp-up fashion. using a spectrometer, spectral intensity data were collected over the ultraviolet/visible regions. the data was analyzed for specific radical chemiluminescence and the electromagnetic emission spectrum. Direct correlation and dynamic response was observed from the emission band from the hydroxyl flame radical, OH, to burner stoichiometry and flue gas NOx emissions. the results show a great promise for online combustion monitoring at the burner level for gas-fired glass furnace applications