18 research outputs found
Opportunities for the next generation of optical boiler diagnostics
No full textPaper from the AFRC 2015 conference titled Opportunities for the next generation of optical boiler diagnosticsInefficient boiler operation and control are responsible for wasting large amounts of fuel and releasing excess greenhouse gases (CO2 and N2O) and pollutants (CO, NOx). This is especially true in the United States where more than 80% of the energy used across all sectors is generated by fossil-fuels combustion. It is now recognized that continuous monitoring and control of both individual burners and groups of burners in boilers is essential to meet and sustain ever more stringent greenhouse and pollutant emission limits. This has become especially true as incremental improvements in burner performance have become disproportionately more difficult, and variations in fuel properties due to the widespread practice of fuel blending require frequent adjustment in burner settings to maintain optimum performance. One approach for advanced optical burner monitoring has been pioneered and successfully implemented commercially on coal-fired utility boilers by The Babcock & Wilcox Company. The Flame Doctor® system statistically characterizes dynamic information in the flicker signals captured by optical flame scanners to assess (and potentially adjust) the performance of individual burners or ensembles of burners (e.g., by mill group). While the value of this technology has been demonstrated repeatedly for over 12 years, it is inherently limited because conventional flame-scanner systems have been designed to meet very specific safety objectives and were never intended to be used for burner performance monitoring. In this work, we describe the current state of the art for burner diagnostics as embodied in the Flame Doctor system. Next, we present the theoretical basis for a new generation of advanced optical flame monitoring technology that could go well beyond the capabilities of current flame-scanner-based systems. We expect that the need for such capabilities will increase substantially as boiler fuel sources and needs for tighter emissions and efficiency controls continue to grow
Field Measurements of Flame Scanners in a Gas-Fired Boiler under Controlled Operation Charges
No full textPaper from the AFRC 2017 conference titled Field Measurements of Flame Scanners in a Gas-Fired Boiler under Controlled Operation ChargesReal-time monitoring of coal-fired utility boiler flames has been in active commercial implementation for at least two decades. One such system - Flame Doctor® - relies on numerical analysis and pattern matching of flickering dynamics as measured by visible-IR flame scanners installed on each burner. This diagnosis system can monitor up to hundreds of burners in large furnaces and allow operators to optimize the unit for combustion efficiency and emissions. Field experience has shown that significant improvements in emissions performance can be achieved with changes to just a small number of burners, and the ability to monitor all flames, especially where visual access is not possible, is of great utility for plant operation.; We have begun adapting the successful Flame Doctor paradigm to gas-fired furnaces and process heater systems. As a first step, we present here analysis of field data acquired from a six-burner gas-fired furnace firing natural gas. A portable Flame Doctor system monitored the output of custom visible-UV flame scanners, and the furnace operating parameters were varied through a series of controlled experiments. We show how the statistical changes in the furnace flame response show promise for a gas-fired flame-monitoring system which would be applicable from single-burner process heaters to large, multi-burner furnaces
Identifying Sources of Thermoacoustic Vibrations in Industrial Furnaces and Boilers
No full textPaper from the AFRC 2018 conference titled Identifying Sources of Thermoacoustic Vibrations in Industrial Furnaces and BoilersIndustrial gas-fired boilers, furnaces and heaters occasionally suffer low-frequency vibrations generated by dynamic feedback between the burner (or burners) and acoustic modes in adjacent cavities in the main combustion chamber or ductwork. Feedback occurs when pressure pulses associated with acoustic resonances propagate to the burner so that they are in phase with combustion rate fluctuations. When the combustion and acoustic fluctuations become sufficiently phase-synchronized, normal sources of dissipation are insufficient to damp the combined pressure waves, and they can become sufficiently amplified to reduce thermal efficiency, increase emissions, and even cause structural damage. In the literature, such oscillations are referred to as thermoacoustic oscillations or ‘rumble\u27, and their basic physics have been the subject of numerous investigations for well over a century. Although it occurs relatively infrequently, rumble poses a significant challenge because it is difficult to predict, diagnose, and resolve. The underlying relationships involved are sufficiently complex that it is possible for two apparently identical boilers or furnaces to exhibit completely different rumble tendencies. In this study, we review common sources of rumble and how nonlinear signal analyses, such as bivariate mutual information and transfer entropy, can be used to locate both its sources and impact in boilers, furnaces and heaters
Opportunities for optical flame diagnostics in commercial and industrial furnaces
No full textConference pape
Thermoacoustic Vibrations in Industrial Furnaces and Boilers
No full textPaper from the AFRC 2017 conference titled Thermoacoustic Vibrations in Industrial Furnaces and BoilersIndustrial boilers and furnaces occasionally suffer low-frequency vibrations generated by a dynamic feedback process between the burner (or burners) and acoustic modes in adjacent gas-filled cavities in the main combustion chamber or connecting ductwork. This occurs when pressure pulses associated with acoustic resonances propagate to the burner so that they are in phase with combustion rate fluctuations caused by turbulence and reaction dynamics. When these pressure pulses become sufficiently phase-synchronized with fluctuations in heat release from the flame, the forces that normally dissipate the pressure waves are overwhelmed and an amplifying feedback loop is created. In the literature, such oscillations are referred to as thermoacoustic oscillations or ‘rumble,\u27 and their basic physics have been the subject of numerous investigations for well over a century. Unfortunately, rumble amplitudes can be large enough to negatively impact thermal efficiency and emissions, and the associated mechanical vibrations they cause can even lead to structural damage. The potential for rumble poses a significant challenge to combustion engineers because it is often very difficult to predict and can be associated with a large number of design and operating factors such as fuel quality, burner swirl and staging, induction and draft fan characteristics, ducting design and combustion cavity shape. The underlying relationships involved are sufficiently complex that it is possible for two apparently identical boilers or furnaces to exhibit completely different rumble tendencies. In this study, we review the published information currently available about the causes and suppression of burner rumble and suggest possible opportunities for improving its prediction, diagnosis, and active control
De toegevoegde waarde van architectuur voor de zorg in ziekenhuizen
No full textArchitectureArchitectur
Symbolic Time Series Analysis in Economics
No full textIn this paper I describe and apply the methods of Symbolic Time Series Analysis (STSA) to an experimental framework. The idea behind Symbolic Time Series Analysis is simple: the values of a given time series data are transformed into a finite set of symbols obtaining a finite string. Then, we can process the symbolic sequence using tools from information theory and symbolic dynamics. I discuss data symbolization as a tool for identifying temporal patterns in experimental data and use symbol sequence statistics in a model strategy. To explain these applications, I describe methods to select the symbolization of the data (Section 2), I introduce the symbolic sequence histograms and some tools to characterize and compare these histograms (Section 3). I show that the methods of symbolic time series analysis can be a good tool to describe and recognize time patterns in complex dynamical processes and to extract dynamical information about this kind of system. In particular, the method gives us a language in which to express and analyze these time patterns. In section 4 I report some applications of STSA to study the evolution of ifferent economies. In these applications data symbolization is based on economic criteria using the notion of economic regime introduced earlier in this thesis. I use STSA methods to describe the dynamical behavior of these economies and to do comparative analysis of their regime dynamics. In section 5 I use STSA to reconstruct a model of a dynamical system from measured time series data. In particular, I will show how the observed symbolic sequence statistics can be used as a target for measuring the goodness of fit of proposed models.
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Cycle-by-cycle combustion variations in spark-ignited engines
No full textUnder constant nominal operating conditions, internal combustion engines can exhibit substantial variation in combustion efficiency from one cycle to the next. Previous researchers have attempted to explain these variations as resulting from stochastic, linear, or chaotic physical processes. Our investigations indicate that cyclic combustion variations can be explained as the result of interactions between a global low-dimensional nonlinearity and small-scale, high-dimensional processes that perturb the nonlinearity. Using this approach, we have proposed a simple model that accurately simulates experimentally observed patterns in cyclic combustion variations. Our model also explains the apparent discrepancies among previous investigators regarding the basic nature of cyclic variations. Further, it appears that symbol dynamics are useful for characterizing the observed model and experimental behavior
