The Development of a Monitoring and Control System for Pulverised Coal Flames Using Artificial Intelligence Techniques

2005 ◽  
Author(s):  
Oui Hong Tan ◽  
Steven John Wilcox ◽  
John Ward
Keyword(s):  
Acoustic Emission ◽  
Low Cost ◽  
Combustion Noise ◽  
Pollutant Emissions ◽  
Airflow Rate ◽  
Gaseous Emissions ◽  
Monitoring And Control ◽  
Infra Red ◽  
The Individual ◽  
Pulverised Coal

This paper discusses the application of low cost sensors for monitoring pulverised coal flames. A series of burner diagnostics tests using Infra-red (IR), Microphone and Acoustic Emission (AE) sensors were conducted on a 150 kW pulverised fuel (pf) burner rig based at Casella CRE Ltd. in the United Kingdom. These experiments systematically varied the burner swirl number and the secondary airflow rate over a significant range for two different coals so that both satisfactory and ‘poor’ combustion conditions were obtained. The infra-red radiation from the flame, the combustion noise and the acoustic emission generated in the burner body were measured, as were the fuel and airflow rates and pollutant emissions. The signals from the sensors were analysed by using signal processing techniques to reveal a number of features. These in turn were compared with the three major combustion gases such as Nitrogen Oxides (NOx), Carbon monoxide (CO) and Oxygen (O2) followed by correlation coefficient analysis (CCA). It is envisaged that these sensors can be used for predicting gaseous emissions and will be particularly attractive for multiple burner installations where the pollutant emissions are often discharged through a common manifold, so that the individual burner performance is often not known and cannot be optimised.

The Development of a Monitoring and Control System for Pulverised Coal Flames Using Neural Networks

2003 ◽  
Author(s):  
O. H. Tan ◽  
S. J. Wilcox ◽  
J. Ward ◽  
M. Lewitt
Keyword(s):  
Control System ◽  
Low Cost ◽  
Air Flow ◽  
Combustion Process ◽  
Combustion Noise ◽  
Pollutant Emissions ◽  
Furnace Chamber ◽  
Gaseous Emissions ◽  
Monitoring And Control ◽  
Secondary Air

This paper presents the results obtained from a series of experiments that have been conducted on a 150kW pf burner rig based at Casella CRE Ltd. in the United Kingdom. These experiments systematically varied the burner swirl number and the secondary air flow rate over a significant range for two different coals so that both satisfactory and ‘poor’ combustion conditions were obtained. The infra-red emissions from the flame and the combustion noise generated in the furnace chamber were measured with appropriate sensors as were the fuel and air flow rates and pollutant emissions. The signals from the sensors were analysed using signal processing techniques to yield a number of features. These in turn were employed to train a neural network to accurately estimate the gaseous emissions from the rig, such as NOx and CO. In a separate set of experiments, where the combustion process was placed in a poor condition, the sensors were coupled with the neural models and incorporated into an intelligent control system, which was able to alter the excess air level to improve the process. In this fashion simultaneous low Nox and CO levels were achieved with both coal types. This method thus uses a combination of relatively low cost sensors and artificial intelligence techniques to control the combustion of the pulverised fuel burner. It is envisaged as particularly attractive for multiple burner installations that are fed from a common manifold, where individual burner performance is not known.

scholarly journals IoT Platform for Energy Sustainability in University Campuses

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 357
Author(s):  
Pedro Moura ◽  
José Ignacio Moreno ◽  
Gregorio López López ◽  
Manuel Alvarez-Campana
Keyword(s):  
Energy Demand ◽  
New Technologies ◽  
Low Cost ◽  
Sustainable Use ◽  
High Energy ◽  
Appropriate Technology ◽  
Monitoring And Control ◽  
Energy Sustainability ◽  
University Campuses ◽  
Iot Platform

University campuses are normally constituted of large buildings responsible for high energy demand, and are also important as demonstration sites for new technologies and systems. This paper presents the results of achieving energy sustainability in a testbed composed of a set of four buildings that constitute the Telecommunications Engineering School of the Universidad Politécnica de Madrid. In the paper, after characterizing the consumption of university buildings for a complete year, different options to achieve more sustainable use of energy are presented, considering the integration of renewable generation sources, namely photovoltaic generation, and monitoring and controlling electricity demand. To ensure the implementation of the desired monitoring and control, an internet of things (IoT) platform based on wireless sensor network (WSN) infrastructure was designed and installed. Such a platform supports a smart system to control the heating, ventilation, and air conditioning (HVAC) and lighting systems in buildings. Furthermore, the paper presents the developed IoT-based platform, as well as the implemented services. As a result, the paper illustrates how providing old existing buildings with the appropriate technology can contribute to the objective of transforming such buildings into nearly zero-energy buildings (nZEB) at a low cost.

scholarly journals Multi-Blockchain-Based IoT Data Processing Techniques to Ensure the Integrity of IoT Data in AIoT Edge Computing Environments

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3515
Author(s):  
Sung-Ho Sim ◽  
Yoon-Su Jeong
Keyword(s):  
Low Cost ◽  
Third Party ◽  
Monitoring And Control ◽  
Constant Size ◽  
Computing Environments ◽  
Iot Devices ◽  
Cloud Servers ◽  
The Cost ◽  
Processing Techniques ◽  
And Control

As the development of IoT technologies has progressed rapidly recently, most IoT data are focused on monitoring and control to process IoT data, but the cost of collecting and linking various IoT data increases, requiring the ability to proactively integrate and analyze collected IoT data so that cloud servers (data centers) can process smartly. In this paper, we propose a blockchain-based IoT big data integrity verification technique to ensure the safety of the Third Party Auditor (TPA), which has a role in auditing the integrity of AIoT data. The proposed technique aims to minimize IoT information loss by multiple blockchain groupings of information and signature keys from IoT devices. The proposed technique allows IoT information to be effectively guaranteed the integrity of AIoT data by linking hash values designated as arbitrary, constant-size blocks with previous blocks in hierarchical chains. The proposed technique performs synchronization using location information between the central server and IoT devices to manage the cost of the integrity of IoT information at low cost. In order to easily control a large number of locations of IoT devices, we perform cross-distributed and blockchain linkage processing under constant rules to improve the load and throughput generated by IoT devices.

scholarly journals Evaluation of Tomato-Based Packing Material for Retention of Ammonia, Nitrous Oxide, Carbon Dioxide and Methane in Gas Phase Biofilters: A Laboratory Study

Agronomy ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 360
Author(s):  
José L. S. Pereira ◽  
Adelaide Perdigão ◽  
Francisco Marques ◽  
Catarina Coelho ◽  
Mariana Mota ◽  
...  
Keyword(s):  
Oxalic Acid ◽  
Laboratory Study ◽  
Packing Material ◽  
Control Treatment ◽  
Airflow Rate ◽  
Pig Slurry ◽  
Air Pollution Control ◽  
Gaseous Emissions ◽  
Packing Materials ◽  
Tomato Waste

Biofilters are an effective air pollution control technology to break down gaseous contaminants and produce innocuous end products. This laboratory study aimed to evaluate a biofilter media, mainly composed by tomato waste, as packing material to reduce NH3, N2O, CO2 and CH4 losses from stored pig slurry. Three mixtures of packing materials, with and without oxalic acid, were arranged in treatments, namely: mixture of tomato waste, pine bark and agricultural compost; mixture of tomato waste and rice husk; tomato waste only. A control treatment (no biofilter) was also included. The experiments were conducted using a system of laboratory scale biofilters connected to jars filled with pig slurry and under a constant airflow rate. The gas concentrations were measured for 14 days and the physicochemical of the packing materials were assessed. Results showed that biofilter media mixtures had a potential for NH3 retention ranging from 51 to 77% and the addition of oxalic acid to these biofilters increased NH3 retention to 72–79%. Additionally, the biofilter media mixtures with and without oxalic acid showed a potential retention for CH4 (29–69%) but not for N2O, yet with no impact on the global warming potential. It can be concluded that tomato based biofilters had the potential to reduce gaseous emissions from slurry.

Thermoacoustic Shape Optimization of a Subsonic Nozzle

2013 ◽  
Vol 135 (10) ◽  
Author(s):  
Alexis Giauque ◽  
Maxime Huet ◽  
Franck Clero ◽  
Sébastien Ducruix ◽  
Franck Richecoeur
Keyword(s):  
Acoustic Emission ◽  
Cross Section ◽  
Source Term ◽  
Combustion Noise ◽  
Noise Emission ◽  
Cross Section Area ◽  
Section Area ◽  
The Cross ◽  
Nozzle Flows ◽  
Subsonic Nozzle

Indirect combustion noise originates from the acceleration of nonuniform temperature or high vorticity regions when convected through a nozzle or a turbine. In a recent contribution (Giauque et al., 2012, “Analytical Analysis of Indirect Combustion Noise in Subcritical Nozzles,” ASME J. Eng. Gas Turbies Power, 134(11), p. 111202) the authors have presented an analytical thermoacoustic model providing the indirect combustion noise generated by a subcritical nozzle when forced with entropy waves. This model explicitly takes into account the effect of the local changes in the cross-section area along the configuration of interest. In this article, the authors introduce this model into an optimization procedure in order to minimize or maximize the thermoacoustic noise emitted by arbitrarily shaped nozzles operating under subsonic conditions. Each component of the complete algorithm is described in detail. The evolution of the cross-section changes are introduced using Bezier's splines, which provide the necessary freedom to actually achieve arbitrary shapes. Bezier's polar coordinates constitute the parameters defining the geometry of a given individual nozzle. Starting from a population of nozzles of random shapes, it is shown that a specifically designed genetic optimization algorithm coupled with the analytical model converges at will toward a quieter or noisier population. As already described by Bloy (Bloy, 1979, “The Pressure Waves Produced by the Convection of Temperature Disturbances in High Subsonic Nozzle Flows,” J. Fluid Mech., 94(3), pp. 465–475), the results therefore confirm the significant dependence of the indirect combustion noise with respect to the shape of the nozzle, even when the operating regime is kept constant. It appears that the quietest nozzle profile evolves almost linearly along its converging and diverging sections, leading to a square evolution of the cross-section area. Providing insight into the underlying physical reason leading to the difference in the noise emission between two extreme individuals, the integral value of the source term of the equation describing the behavior of the acoustic pressure of the nozzle is considered. It is shown that its evolution with the frequency can be related to the global acoustic emission. Strong evidence suggest that the noise emission increases as the source term in the converging and diverging parts less compensate each other. The main result of this article is the definition and proposition of an acoustic emission factor, which can be used as a surrogate to the complex determination of the exact acoustic levels in the nozzle for the thermoacoustic shape optimization of nozzle flows. This acoustic emission factor, which is much faster to compute, only involves the knowledge of the evolution of the cross-section area and the inlet thermodynamic and velocity characteristics to be computed.

scholarly journals Shaping Streamflow Using a Real-Time Stormwater Control Network

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2259 ◽  
Author(s):  
Abhiram Mullapudi ◽  
Matthew Bartos ◽  
Brandon Wong ◽  
Branko Kerkez
Keyword(s):  
Real Time ◽  
Control Strategies ◽  
Low Cost ◽  
Control Network ◽  
Monitoring And Control ◽  
Set Point ◽  
Smart Water ◽  
Decay Times ◽  
Retention Basins ◽  
Scale Control

“Smart” water systems are transforming the field of stormwater management by enabling real-time monitoring and control of previously static infrastructure. While the localized benefits of active control are well-established, the potential for system-scale control of watersheds is poorly understood. This study shows how a real-world smart stormwater system can be leveraged to shape streamflow within an urban watershed. Specifically, we coordinate releases from two internet-controlled stormwater basins to achieve desired control objectives downstream—such as maintaining the flow at a set-point, and generating interleaved waves. In the first part of the study, we describe the construction of the control network using a low-cost, open-source hardware stack and a cloud-based controller scheduling application. Next, we characterize the system’s control capabilities by determining the travel times, decay times, and magnitudes of various waves released from the upstream retention basins. With this characterization in hand, we use the system to generate two desired responses at a critical downstream junction. First, we generate a set-point hydrograph, in which flow is maintained at an approximately constant rate. Next, we generate a series of overlapping and interleaved waves using timed releases from both retention basins. We discuss how these control strategies can be used to stabilize flows, thereby mitigating streambed erosion and reducing contaminant loads into downstream waterbodies.

A Low-Cost Acoustic Emission Sensor based on Piezoelectric Diaphragm

2020 ◽  
pp. 1-1
Author(s):  
Martin A. Aulestia Viera ◽  
Reinaldo Gotz ◽  
Paulo R. de Aguiar ◽  
Felipe A. Alexandre ◽  
Breno O. Fernandez ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Low Cost ◽  
Acoustic Emission Sensor

Damage Development in SiCf/SiC Composites Through Mechanical Loading

2017 ◽  
Author(s):  
Martin R. Bache ◽  
J. Paul Jones ◽  
Zak Quiney ◽  
Louise Gale
Keyword(s):  
Acoustic Emission ◽  
Mechanical Loading ◽  
Ceramic Matrix Composites ◽  
Potential Drop ◽  
Image Correlation ◽  
Stress Concentrations ◽  
Damage Development ◽  
Macro Scale ◽  
Sic Composites ◽  
The Individual

Sophisticated mechanical characterisation is vital in support of a fundamental understanding of deformation in ceramic matrix composites. On the component scale, “damage tolerant” design and lifing philosophies depend upon laboratory assessments of macro-scale specimens, incorporating typical fibre architectures and matrix under representative stress-strain states. Standard SiCf/SiC processing techniques inherently introduce porosity between the individual reinforcing fibres and between woven fibre bundles. Subsequent mechanical loading (static or cyclic) may initiate cracking from these stress concentrations in addition to fibre/matrix decohesion and delamination. The localised coalescence of such damage ultimately leads to rapid failure. Proven techniques for the monitoring of damage in structural metallics, i.e. optical microscopy, potential drop systems, acoustic emission (AE) and digital image correlation (DIC), have been adapted for the characterisation of CMC’s tested at room temperature. As processed SiCf/SiC panels were subjected to detailed X-ray computed tomography (XCT) inspection prior to specimen extraction and subsequent static and cyclic mechanical testing to verify their condition. DIC strain measurements, acoustic emission and resistance monitoring were performed and correlated to monitor the onset of damage during loading, followed by intermittent XCT inspections throughout the course of selected tests.

scholarly journals Mitigation of Gaseous Emissions from Swine Manure with the Surficial Application of Biochars

2020 ◽  
Author(s):  
Zhanibek Meiirkhanuly ◽  
Jacek A. Koziel ◽  
Baitong Chen ◽  
Andrzej Białowiec ◽  
Myeongseong Lee ◽  
...  
Keyword(s):  
Low Cost ◽  
Swine Manure ◽  
Animal Manure ◽  
Isobutyric Acid ◽  
Lessons Learned ◽  
Regulatory Agencies ◽  
Gaseous Emissions ◽  
Percent Reduction ◽  
Volatile Organic ◽  
The Impact

Environmental impact associated with odor and gaseous emissions from animal manure is one of the challenges for communities, farmers, and regulatory agencies. Microbe-based manure additives treatments are marketed and used by farmers for mitigation of emissions. However, their performance is difficult to assess objectively. Thus, comprehensive, practical, and low-cost treatments are still in demand. We have been advancing such treatments based on physicochemical principles. The objective of this research was to test the effect of the surficial application of a thin layer (¼"; 6.3 mm) of biochar on the mitigation of gaseous emissions (as the percent reduction, % R) from swine manure. Two types of biochar were tested: highly alkaline and porous (HAP) biochar made from corn stover and red oak (RO), both with different pH and morphology. Three 30-day trials were conducted with a layer of HAP and RO (2.0 & 1.65 kg∙m-2, respectively) applied on manure surface, and emissions of ammonia (NH3), hydrogen sulfide (H2S), greenhouse gases (GHG), and odorous volatile organic compounds (VOCs) were measured. The manure and biochar type and properties had an impact on the mitigation effect and its duration. RO significantly reduced NH3 (19-39%) and p-cresol (66-78%). H2S was mitigated (16~23%), but not significantly for all trials. Significant (66~78%) reductions for p-cresol were observed for all trials. The phenolic VOCs had relatively high % R in most trials but not significantly for all trials. HAP reduced NH3 (4~21%) and H2S (2~22%), but not significantly for all trials. Significant % R for p-cresol (91~97%) and skatole (74~95%) were observed for all trials. The % R for phenol and indole ranged from (60~99%) & (29~94%) but was not significant for all trials. The impact on GHGs, isobutyric acid, and the odor was mixed with some mitigation and generation effects. However, larger-scale experiments are needed to understand how biochar properties and the dose and frequency of application can be optimized to mitigate odor and gaseous emissions from swine manure. The lessons learned can also be applicable to surficial biochar treatment of gaseous emissions from other waste and area sources.

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