Pub Date : 2012-12-13DOI: 10.1109/FIIW.2012.6378352
M. Buckner, L. Love
The ultimate objective of additive manufacturing is the implementation of techniques that can be used throughout the full manufacturing cycle. However, since its introduction, the additive manufacturing process has been used for little more than pre-production prototyping. The goal of some current work at ORNL is to change that reality. ORNL recently completed the first step towards optimizing the final design and manufacture of a component part (a cantilever in this case) using computer-aided design (CAD) tools, finite element analysis and simulations, and internally-developed optimization software. This paper will describe the present design process, the tools used, and the progress made thus far. It will also discuss the recent porting of ORNL's Multi-Objective Constrained Evolutionary Optimization (MOCEO) algorithms to ORNL's high performance computing (HPC) resources and to other resources available for Cloud computing, and the path forward for implementing additive manufacturing designs on these resources.
{"title":"Automating and accelerating the additive manufacturing design process with multi-objective constrained evolutionary optimization and HPC/Cloud computing","authors":"M. Buckner, L. Love","doi":"10.1109/FIIW.2012.6378352","DOIUrl":"https://doi.org/10.1109/FIIW.2012.6378352","url":null,"abstract":"The ultimate objective of additive manufacturing is the implementation of techniques that can be used throughout the full manufacturing cycle. However, since its introduction, the additive manufacturing process has been used for little more than pre-production prototyping. The goal of some current work at ORNL is to change that reality. ORNL recently completed the first step towards optimizing the final design and manufacture of a component part (a cantilever in this case) using computer-aided design (CAD) tools, finite element analysis and simulations, and internally-developed optimization software. This paper will describe the present design process, the tools used, and the progress made thus far. It will also discuss the recent porting of ORNL's Multi-Objective Constrained Evolutionary Optimization (MOCEO) algorithms to ORNL's high performance computing (HPC) resources and to other resources available for Cloud computing, and the path forward for implementing additive manufacturing designs on these resources.","PeriodicalId":170653,"journal":{"name":"2012 Future of Instrumentation International Workshop (FIIW) Proceedings","volume":"508 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116330444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-13DOI: 10.1109/FIIW.2012.6378319
M. Buric, B. Chorpening, J. Mullen, S. Woodruff, J. Ranalli
A gas composition sensor based on Raman spectroscopy using reflective metal lined capillary waveguides is tested under field conditions for feedforward applications in combustion control. The capillary waveguide enables effective use of low powered lasers and rapid composition determination, for computation of required parameters to pre-adjust burner control based on incoming fuel. Tests on high pressure fuel streams show sub-second time response and better than one percent accuracy on natural gas fuel mixtures. Fuel composition and Wobbe constant values are provided at one second intervals or faster. The sensor, designed and constructed at NETL, is packaged for Class I Division 2 operations typical of gas turbine and boiler environments, and samples gas at up to 800 psig. Simultaneous determination of the hydrocarbons methane, ethane, and propane plus CO, CO2, H2O, H2, N2, and O2 are realized. The capillary waveguide permits use of miniature spectrometers and laser power of less than 100 mW. The capillary dimensions of 1 m length and 300 μm ID also enable a full sample exchange in 0.4 s or less at 5 psig pressure differential, which allows a fast response to changes in sample composition. Sensor operation under field operation conditions will be reported.
{"title":"Field tests of the Raman gas composition sensor","authors":"M. Buric, B. Chorpening, J. Mullen, S. Woodruff, J. Ranalli","doi":"10.1109/FIIW.2012.6378319","DOIUrl":"https://doi.org/10.1109/FIIW.2012.6378319","url":null,"abstract":"A gas composition sensor based on Raman spectroscopy using reflective metal lined capillary waveguides is tested under field conditions for feedforward applications in combustion control. The capillary waveguide enables effective use of low powered lasers and rapid composition determination, for computation of required parameters to pre-adjust burner control based on incoming fuel. Tests on high pressure fuel streams show sub-second time response and better than one percent accuracy on natural gas fuel mixtures. Fuel composition and Wobbe constant values are provided at one second intervals or faster. The sensor, designed and constructed at NETL, is packaged for Class I Division 2 operations typical of gas turbine and boiler environments, and samples gas at up to 800 psig. Simultaneous determination of the hydrocarbons methane, ethane, and propane plus CO, CO2, H2O, H2, N2, and O2 are realized. The capillary waveguide permits use of miniature spectrometers and laser power of less than 100 mW. The capillary dimensions of 1 m length and 300 μm ID also enable a full sample exchange in 0.4 s or less at 5 psig pressure differential, which allows a fast response to changes in sample composition. Sensor operation under field operation conditions will be reported.","PeriodicalId":170653,"journal":{"name":"2012 Future of Instrumentation International Workshop (FIIW) Proceedings","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124716032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-13DOI: 10.1109/FIIW.2012.6378348
J. Coble, P. Ramuhalli, R. Meyer, H. Hashemian, B. Shumaker, D. Cummins
Currently in the United States, periodic sensor recalibration is required for all safety-related sensors, typically occurring at every refueling outage; and it has emerged as a critical path item for shortening outage duration in some plants. International application of calibration monitoring has shown that sensors may operate for longer periods within calibration tolerances. This issue is expected to also be important as the United States looks to the next generation of reactor designs (such as small modular reactors and advanced reactor concepts), given the anticipated longer refueling cycles, proposed advanced sensors, and digital instrumentation and control systems. Online monitoring (OLM) can be employed to identify those sensors that require calibration, allowing for calibration of only those sensors that need it. The U.S. Nuclear Regulatory Commission (NRC) accepted the general concept of OLM for sensor calibration monitoring in 2000, but no U.S. plants have been granted the necessary license amendment to apply it. This paper summarizes a recent state-of-the-art assessment of online calibration monitoring in the nuclear power industry, including sensors, calibration practice, and OLM algorithms. This assessment identifies key research needs and gaps that prohibit integration of the NRC-approved online calibration monitoring system in the U.S. nuclear power industry. Several technical needs were identified, including an understanding of the impacts of sensor degradation on measurements for both conventional and emerging sensors; the quantification of uncertainty in online calibration assessment; determination of calibration acceptance criteria and quantification of the effect of acceptance criteria variability on system performance; and assessment of the feasibility of using virtual sensor estimates to replace identified faulty sensors in order to extend operation to the next convenient maintenance opportunity.
{"title":"Calibration monitoring for sensor calibration interval extension: Identifying technical gaps","authors":"J. Coble, P. Ramuhalli, R. Meyer, H. Hashemian, B. Shumaker, D. Cummins","doi":"10.1109/FIIW.2012.6378348","DOIUrl":"https://doi.org/10.1109/FIIW.2012.6378348","url":null,"abstract":"Currently in the United States, periodic sensor recalibration is required for all safety-related sensors, typically occurring at every refueling outage; and it has emerged as a critical path item for shortening outage duration in some plants. International application of calibration monitoring has shown that sensors may operate for longer periods within calibration tolerances. This issue is expected to also be important as the United States looks to the next generation of reactor designs (such as small modular reactors and advanced reactor concepts), given the anticipated longer refueling cycles, proposed advanced sensors, and digital instrumentation and control systems. Online monitoring (OLM) can be employed to identify those sensors that require calibration, allowing for calibration of only those sensors that need it. The U.S. Nuclear Regulatory Commission (NRC) accepted the general concept of OLM for sensor calibration monitoring in 2000, but no U.S. plants have been granted the necessary license amendment to apply it. This paper summarizes a recent state-of-the-art assessment of online calibration monitoring in the nuclear power industry, including sensors, calibration practice, and OLM algorithms. This assessment identifies key research needs and gaps that prohibit integration of the NRC-approved online calibration monitoring system in the U.S. nuclear power industry. Several technical needs were identified, including an understanding of the impacts of sensor degradation on measurements for both conventional and emerging sensors; the quantification of uncertainty in online calibration assessment; determination of calibration acceptance criteria and quantification of the effect of acceptance criteria variability on system performance; and assessment of the feasibility of using virtual sensor estimates to replace identified faulty sensors in order to extend operation to the next convenient maintenance opportunity.","PeriodicalId":170653,"journal":{"name":"2012 Future of Instrumentation International Workshop (FIIW) Proceedings","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114489541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-13DOI: 10.1109/FIIW.2012.6378321
B. Daniel, J. Meredith, J. Sumner, B. Vacaliuc, J. Ellenburg
Graphics processing units (GPUs) are being fused together with the traditional central processing units (CPUs) to form accelerated processing units (APUs). These hybrid computing machines provide a viable alternative to traditional processors for high-performance computing systems thanks to substantial computational performance and advanced programmability. A team at Oak Ridge National Laboratory experienced with radar clutter modeling and simulation, and with computation using a variety of processors, has explored the viability of GPUs for accelerating clutter simulation for the Joint Research Analysis and Assessment Center at the Missile and Space Intelligence Center. The results show substantial performance gains of approximately 20× relative to a CPU-only algorithm. We show a number of ways these accelerated clutter calculations provide real-time results starting from readily extended simulation models.
{"title":"Evaluating graphical processing units for clutter model calculation in a simulation facility","authors":"B. Daniel, J. Meredith, J. Sumner, B. Vacaliuc, J. Ellenburg","doi":"10.1109/FIIW.2012.6378321","DOIUrl":"https://doi.org/10.1109/FIIW.2012.6378321","url":null,"abstract":"Graphics processing units (GPUs) are being fused together with the traditional central processing units (CPUs) to form accelerated processing units (APUs). These hybrid computing machines provide a viable alternative to traditional processors for high-performance computing systems thanks to substantial computational performance and advanced programmability. A team at Oak Ridge National Laboratory experienced with radar clutter modeling and simulation, and with computation using a variety of processors, has explored the viability of GPUs for accelerating clutter simulation for the Joint Research Analysis and Assessment Center at the Missile and Space Intelligence Center. The results show substantial performance gains of approximately 20× relative to a CPU-only algorithm. We show a number of ways these accelerated clutter calculations provide real-time results starting from readily extended simulation models.","PeriodicalId":170653,"journal":{"name":"2012 Future of Instrumentation International Workshop (FIIW) Proceedings","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133116747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-13DOI: 10.1109/FIIW.2012.6378338
J. Rossman, T. Laughner, A. Murphy, D. E. Marler, G. Kobet
This paper presents transmission level voltage unbalance as measured by two different methods across the Tennessee Valley Authority (TVA) Transmission system. It also discusses the recent focus on distribution voltage control. Two national standards mentioning voltage unbalance are discussed as well as TVA's operations and limitations on voltage balancing. An example of equipment malfunction creating voltage unbalance is discussed. A team was formed to address voltage unbalance concerns and this team made a number of measurements across the TVA system. The team determined the average transmission system unbalance delivered to customer sites to be 0.59% (method 1) and 0.64% (method 2).
{"title":"Transmission voltage unbalance evaluation","authors":"J. Rossman, T. Laughner, A. Murphy, D. E. Marler, G. Kobet","doi":"10.1109/FIIW.2012.6378338","DOIUrl":"https://doi.org/10.1109/FIIW.2012.6378338","url":null,"abstract":"This paper presents transmission level voltage unbalance as measured by two different methods across the Tennessee Valley Authority (TVA) Transmission system. It also discusses the recent focus on distribution voltage control. Two national standards mentioning voltage unbalance are discussed as well as TVA's operations and limitations on voltage balancing. An example of equipment malfunction creating voltage unbalance is discussed. A team was formed to address voltage unbalance concerns and this team made a number of measurements across the TVA system. The team determined the average transmission system unbalance delivered to customer sites to be 0.59% (method 1) and 0.64% (method 2).","PeriodicalId":170653,"journal":{"name":"2012 Future of Instrumentation International Workshop (FIIW) Proceedings","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133474966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-13DOI: 10.1109/FIIW.2012.6378351
M. R. Moore, M. Buckner, M. Young, A. Albright, M. Bobrek, H. D. Haynes, G. R. Wetherington
ORNL recently applied its “learning-from-signals” (LFS) techniques to evaluating and improving the energy efficiency of buildings at military installations. LFS is a term coined by ORNL to describe the machine learning algorithms that it has developed for mining, processing, and classifying signals either purposefully or inadvertently being picked up from infrastructure or individual devices. For this particular application, ORNL provided technical support to the Defense Advanced Research Projects Agency (DARPA) Service Chiefs Program for disaggregating electrical power consumption at the device level in a military residential dormitory at Fort Meyer in Washington, DC. The ORNL researchers showed that patterns of device utilization could be monitored on a building's power infrastructure. These devices included cooling/heating water pumps, lighting, washers, dryers, refrigerators, and stoves. This paper discusses the process and initial results of the research effort, as well as the path forward for similar industrial, commercial, and government undertakings.
{"title":"Building energy management using learning-from-signals","authors":"M. R. Moore, M. Buckner, M. Young, A. Albright, M. Bobrek, H. D. Haynes, G. R. Wetherington","doi":"10.1109/FIIW.2012.6378351","DOIUrl":"https://doi.org/10.1109/FIIW.2012.6378351","url":null,"abstract":"ORNL recently applied its “learning-from-signals” (LFS) techniques to evaluating and improving the energy efficiency of buildings at military installations. LFS is a term coined by ORNL to describe the machine learning algorithms that it has developed for mining, processing, and classifying signals either purposefully or inadvertently being picked up from infrastructure or individual devices. For this particular application, ORNL provided technical support to the Defense Advanced Research Projects Agency (DARPA) Service Chiefs Program for disaggregating electrical power consumption at the device level in a military residential dormitory at Fort Meyer in Washington, DC. The ORNL researchers showed that patterns of device utilization could be monitored on a building's power infrastructure. These devices included cooling/heating water pumps, lighting, washers, dryers, refrigerators, and stoves. This paper discusses the process and initial results of the research effort, as well as the path forward for similar industrial, commercial, and government undertakings.","PeriodicalId":170653,"journal":{"name":"2012 Future of Instrumentation International Workshop (FIIW) Proceedings","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127009703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-13DOI: 10.1109/FIIW.2012.6378327
M. McGranaghan, B. Deaver
This paper discusses new types of sensors and data management approaches that can be applied to operate and manage the grid more efficiently and flexibly while maintaining reliability. Sensors can help increase awareness of asset condition and grid conditions for more optimum management of the grid. Integration of sensors with system models to predict conditions on the grid can further improve the grid management potential. Examples of sensors that can contribute to smart grid goals include advanced meters, wireless voltage and current sensors, line post sensors, sensors integrated with IEDs, PMUs, etc. These devices must be integrated with data collection systems, data management systems, and system models to help achieve new functionality that benefits the overall efficiency, reliability, and flexibility of the grid.
{"title":"Sensors and monitoring challenges in the smart grid","authors":"M. McGranaghan, B. Deaver","doi":"10.1109/FIIW.2012.6378327","DOIUrl":"https://doi.org/10.1109/FIIW.2012.6378327","url":null,"abstract":"This paper discusses new types of sensors and data management approaches that can be applied to operate and manage the grid more efficiently and flexibly while maintaining reliability. Sensors can help increase awareness of asset condition and grid conditions for more optimum management of the grid. Integration of sensors with system models to predict conditions on the grid can further improve the grid management potential. Examples of sensors that can contribute to smart grid goals include advanced meters, wireless voltage and current sensors, line post sensors, sensors integrated with IEDs, PMUs, etc. These devices must be integrated with data collection systems, data management systems, and system models to help achieve new functionality that benefits the overall efficiency, reliability, and flexibility of the grid.","PeriodicalId":170653,"journal":{"name":"2012 Future of Instrumentation International Workshop (FIIW) Proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129848411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-13DOI: 10.1109/FIIW.2012.6378345
S. Kher, V. Nutt, D. Dasgupta, H. Ali, P. Mixon
In this paper, we present a model to monitor the smart grid for any anomalous/malicious activity or attack. The model uses machine learning techniques to detect and classify anomalies from the sensory observations. It is helpful for ensuring the security and stability of the smart grid. The model relies on the real time data collected using wireless sensor networks as an overlay network on the power distribution grid. The overlay network of wireless sensors /devices uses a cluster topology at each tower to collect local information about the tower that is augmented by the linear chain topology to connect to the base station (usually at the substation). Preliminary results show that our classification mechanism is promising and is able to detect anomalous events that may cause a threat to the smart grid.
{"title":"A detection model for anomalies in smart grid with sensor network","authors":"S. Kher, V. Nutt, D. Dasgupta, H. Ali, P. Mixon","doi":"10.1109/FIIW.2012.6378345","DOIUrl":"https://doi.org/10.1109/FIIW.2012.6378345","url":null,"abstract":"In this paper, we present a model to monitor the smart grid for any anomalous/malicious activity or attack. The model uses machine learning techniques to detect and classify anomalies from the sensory observations. It is helpful for ensuring the security and stability of the smart grid. The model relies on the real time data collected using wireless sensor networks as an overlay network on the power distribution grid. The overlay network of wireless sensors /devices uses a cluster topology at each tower to collect local information about the tower that is augmented by the linear chain topology to connect to the base station (usually at the substation). Preliminary results show that our classification mechanism is promising and is able to detect anomalous events that may cause a threat to the smart grid.","PeriodicalId":170653,"journal":{"name":"2012 Future of Instrumentation International Workshop (FIIW) Proceedings","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133774250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-13DOI: 10.1109/FIIW.2012.6378324
C. Kiger, B. Shumaker
In general, the world's nuclear power fleet is comprised of facilities that were built on designs created nearly a half century ago. There are numerous instances of original vintage equipment still installed and operating in these plants. This absence of modernization is due to many factors including the reliability of the existing equipment, lack of confidence and operating experience of digital systems, funding considerations, and regulatory concerns. There are however several successful instances of plant upgrades providing enhanced power output, efficiency, safety, and monitoring capabilities. With these successes, other technologies that can provide a benefit to the nuclear power industry will begin to gain acceptance. Wireless is one such technology that can find widespread use. Wireless technology has and will continue to face many perceived obstacles for implementation including cyber security, reliability, return on investment, and electromagnetic compatibility. Another issue that will arise with an expansion of wireless installations will be wireless coexistence. These concerns have been addressed by several utilities that have implemented wireless devices at various levels. However, nuclear power plants are typically slow to adopt cutting-edge technologies. Therefore, the advanced wireless protocols and sensor devices being developed today and in the near future will have to provide sufficient justification to address the implementation concerns. The two areas that will be difficult to address are electromagnetic compatibility and wireless coexistence. There is currently minimal guidance for the nuclear utilities with respect to either of these issues as they relate to wireless technology. Several organizations have and continue to perform research in these areas for the nuclear industry but further work is necessary to fully understand and address the real concerns.
{"title":"Managing the electromagnetic compatibility and wireless coexistence concerns for the implementation of existing and future wireless technologies in nuclear power plants","authors":"C. Kiger, B. Shumaker","doi":"10.1109/FIIW.2012.6378324","DOIUrl":"https://doi.org/10.1109/FIIW.2012.6378324","url":null,"abstract":"In general, the world's nuclear power fleet is comprised of facilities that were built on designs created nearly a half century ago. There are numerous instances of original vintage equipment still installed and operating in these plants. This absence of modernization is due to many factors including the reliability of the existing equipment, lack of confidence and operating experience of digital systems, funding considerations, and regulatory concerns. There are however several successful instances of plant upgrades providing enhanced power output, efficiency, safety, and monitoring capabilities. With these successes, other technologies that can provide a benefit to the nuclear power industry will begin to gain acceptance. Wireless is one such technology that can find widespread use. Wireless technology has and will continue to face many perceived obstacles for implementation including cyber security, reliability, return on investment, and electromagnetic compatibility. Another issue that will arise with an expansion of wireless installations will be wireless coexistence. These concerns have been addressed by several utilities that have implemented wireless devices at various levels. However, nuclear power plants are typically slow to adopt cutting-edge technologies. Therefore, the advanced wireless protocols and sensor devices being developed today and in the near future will have to provide sufficient justification to address the implementation concerns. The two areas that will be difficult to address are electromagnetic compatibility and wireless coexistence. There is currently minimal guidance for the nuclear utilities with respect to either of these issues as they relate to wireless technology. Several organizations have and continue to perform research in these areas for the nuclear industry but further work is necessary to fully understand and address the real concerns.","PeriodicalId":170653,"journal":{"name":"2012 Future of Instrumentation International Workshop (FIIW) Proceedings","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124158545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-13DOI: 10.1109/FIIW.2012.6378337
M. Abdallah
Data acquisition (DAQ) is a crucial component in instrumentation and control. It typically involves the sampling of multiple analog signals, and converting them into digital formats so that they can be processed. DAQ systems also involve microprocessors, microcontrollers, digital signal processing, and/or storage devices. Many multi-channel DAQs, which utilize some sort of processing for simultaneous input channels, are found in various applications. In this research, for heterogeneous multichannel signals, different sampling rates are identified for each channel, and optimized for best data quality with minimal storage requirement. Accordingly, power consumption and transmission times can be reduced. The fidelity of the proposed Scheduler-on-Chip (SchoC) is increased by using reconfigurable chip technology, where flexibility, concurrency, speed and reconfiguration can be achieved in hardware. Therefore, SchoC can be utilized in various real world applications especially hazardous environments, or isolated areas, for remote architecture reconfiguration, while keeping the cost of the device low. Performance evaluations show that the speed of the proposed SchoC is 24% faster than a comparable software-based scheduler. The proposed SchoC reduces the amount of data being acquired by 59%, which in turn decreases memory requirements.
{"title":"Implementation of a data acquisition Scheduler-on-Chip (SchoC) for heterogeneous multi-channel signals","authors":"M. Abdallah","doi":"10.1109/FIIW.2012.6378337","DOIUrl":"https://doi.org/10.1109/FIIW.2012.6378337","url":null,"abstract":"Data acquisition (DAQ) is a crucial component in instrumentation and control. It typically involves the sampling of multiple analog signals, and converting them into digital formats so that they can be processed. DAQ systems also involve microprocessors, microcontrollers, digital signal processing, and/or storage devices. Many multi-channel DAQs, which utilize some sort of processing for simultaneous input channels, are found in various applications. In this research, for heterogeneous multichannel signals, different sampling rates are identified for each channel, and optimized for best data quality with minimal storage requirement. Accordingly, power consumption and transmission times can be reduced. The fidelity of the proposed Scheduler-on-Chip (SchoC) is increased by using reconfigurable chip technology, where flexibility, concurrency, speed and reconfiguration can be achieved in hardware. Therefore, SchoC can be utilized in various real world applications especially hazardous environments, or isolated areas, for remote architecture reconfiguration, while keeping the cost of the device low. Performance evaluations show that the speed of the proposed SchoC is 24% faster than a comparable software-based scheduler. The proposed SchoC reduces the amount of data being acquired by 59%, which in turn decreases memory requirements.","PeriodicalId":170653,"journal":{"name":"2012 Future of Instrumentation International Workshop (FIIW) Proceedings","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128029439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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