电厂炉的高效声学温度计方法基于LMS二次交叉相关性
Jidong Yan1, Liansuo An1, Guoqing Shen1
1School of Energy, Power and Mechanical Engineering, North China Electric Power University, 102206 Beijing, China.
本研究引入了一种新的算法,它结合了最小平均平方 (LMS) 适应过和一般化的二次交叉相关性,用于在声学温度计中准确的时间延迟估计. 该方法在具有挑战性的发电厂炉环境中提高了温度测量准确度.
科学领域:
- 工程 工程师 工程师 工程师
- 信号处理 信号处理
- 测温仪测温仪是指温度测量仪.
背景情况:
- 精确的温度测量对于发电厂炉效率和安全至关重要.
- 声波温度计为炉温度监测提供了一种非侵入性方法.
- 现有的时间延迟估计方法在恶劣的工业环境中与噪音作斗争.
研究的目的:
- 开发和验证一个强大的时间延迟估计算法用于发电厂炉中的声学温度计.
- 为了提高单路径声学温度测量的准确性.
- 为应对炉环境中噪音和恶劣环境所带来的挑战.
主要方法:
- 开发了一种新的算法,结合了最小平均平方 (LMS) 适应性过和一般化的二次交叉相关性.
- 进行了数值模拟来评估算法的性能.
- 实验验证是在实验室环境和750/日废物焚烧炉测试平台上进行的.
- 拟议的算法与一般化的二次方位交叉相关算法进行了比较.
主要成果:
- 在数值模拟和实验室条件下,LMS二次交叉相关算法有效地过了噪声.
- 即使在电厂炉的恶劣环境中,也可以实现准确的时间延迟估计.
- 单路径声学温度测量的准确性得到显著改善.
结论:
- 拟议的LMS二次交叉相关算法为电厂炉的声学温度计中的时间延迟估计提供了可靠的解决方案.
- 该算法的在噪音和恶劣环境中的稳定性使其适用于工业应用.
- 这一进步提高了关键基础设施声温度监测的精度.
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