基于串联自适应噪声消除器的热工过程数据融合技术

Data Fusion Method in Thermal Process Based on Serial Adaptive Noise Canceller

针对火电厂现场数据容易受到各种噪声干扰的问题,提出了一种二级串联自适应噪声消除器,将ANC系统与ALE系统串联起来联合消噪,提高了信号精度。对于多个传感器的数据融合问题,结合一种分布式融合结构模型,并采用一种权值最优分配准则作为融合中心算法,改善了数据处理方式,提高了数据可用性。最后,基于一种热量信号构造模型的实际数据仿真进行仿真,得到的计算热量信号数据波动较小,稳态效果更好,去噪效果明显。

Since the data in thermal power plant is vulnerable to various noise interference, this paper presents a two-order tandem-type adaptive noise canceller, whose ANC and ALE are connected in series to improve signal accuracy. As to the data fusion of multiple sensors, a weighted optimal allocation criteria is used as the key fusion algorithm combined with a distributed fusion architecture model in order to improve data processing method and data availabili-ty. Finally, the simulation based on a heat release signal calculated model shows that the calculated heat signal data is less volatile but more stable, and that the denoising effect is obvious.