用于发电设备性能优化的智能传感器技术

Komandur S. Sunder Raj
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引用次数: 2

摘要

智能传感器技术在优化发电设备性能的几个方面正在进行重要的研究。这些倡议包括:1。具有先进计算算法的实时模型,传感器和组件级别的嵌入式智能,可降低运营成本,提高效率并降低排放。2. 光学蓝宝石传感器用于监测恶劣环境中关键部件的操作和性能,用于提高燃烧监测测量的准确性,并降低操作成本。3.无线技术使用(a)微波声学传感器实时监测高温/高压环境下的设备;(b)集成气体/温度声学传感器用于监测各种恶劣环境位置的燃烧,以提高燃烧效率,减少排放,降低维护成本;(c)传感器用于感知燃煤锅炉内部的温度,应变和烟尘积累,以进行详细的状态监测。更好地理解燃烧和热交换过程,改进设计,更有效地运行。4. 分布式光纤传感系统,用于实时监测和优化高温剖面,以提高效率和降低排放。5. 具有嵌入式传感器的智能部件,用于对现有和新设施中的多个参数进行现场监测。6. 优化用于恶劣环境组件中的嵌入式传感器的先进3D制造工艺,以降低成本并提高具有碳捕获能力的发电设施的效率。7. 用于在恶劣环境中为无线传感器供电的新型能量收集材料,提高无线传感器在苛刻环境中的可靠性,以及设备和系统的现场监测和性能。8. 在恶劣环境中,实时、准确、可靠地监测传感器分布位置的温度,以提高作业效率,降低作业成本。9. 利用分布式智能设计控制系统以实现发电设施的最优控制的算法和方法。10. 气体传感器用于监测恶劣环境下的高温,以降低操作成本,更好地控制操作。11. 智能传感器在认知行为和自我学习网络中的优化放置。本文概述了智能传感器技术及其在优化发电设施性能方面的应用。
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Smart Sensor Technologies for Performance Optimization of Power Generating Assets
Significant research is ongoing on several fronts in smart sensor technologies for optimizing the performance of power generating assets. The initiatives include: 1. Real-time models with advanced computational algorithms, embedded intelligence at sensor and component level for reducing operating costs, improving efficiencies, and lowering emissions. 2. Optical sapphire sensors for monitoring operation and performance of critical components in harsh environments, for improving accuracy of measurements in combustion monitoring, and lowering operating costs. 3. Wireless technologies using (a) microwave acoustic sensors for real-time monitoring of equipment in high temperature/pressure environments (b) integrated gas/temperature acoustic sensors for combustion monitoring in diverse harsh environment locations to improve combustion efficiency, reduce emissions, and lower maintenance costs (c) sensors for sensing temperature, strain and soot accumulation inside coal-fired boilers for detailed condition monitoring, better understanding of combustion and heat exchange processes, improved designs, more efficient operation. 4. Distributed optical fiber sensing system for real-time monitoring and optimization of high temperature profiles for improving efficiency and lowering emissions. 5. Smart parts with embedded sensors for in situ monitoring of multiple parameters in existing and new facilities. 6. Optimizing advanced 3D manufacturing processes for embedded sensors in components for harsh environments to reduce costs and improve efficiency of power generation facilities with carbon capture capabilities. 7. New energy-harvesting materials for powering wireless sensors in harsh environments, improving reliability of wireless sensors in demanding environments, and in-situ monitoring and performance of devices and systems. 8. Real-time, accurate and reliable monitoring of temperature at distributed locations of sensors in harsh environments for improving operations and reducing operating costs. 9. Algorithms and methodologies for designing control systems utilizing distributed intelligence for optimal control of power generation facilities. 10. Gas sensors for monitoring high temperatures in harsh environments for lowering operating costs and better control of operations. 11. Optimizing placement of smart sensors in networks for cognitive behavior and self-learning. This paper provides an overview of the initiatives in smart sensor technologies and their applications in optimizing the performance of power generating facilities.
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