On-line fuel identification using digital signal processing and fuzzy inference techniques
On-line fuel identification using digital signal processing and fuzzy inference techniques
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DOI：
10.1109/tim.2004.830573
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发表时间：
2004-07
影响因子：
5.6
通讯作者：
Lijun Xu;Yong Yan;S. Cornwell;G. Riley
中科院分区：
文献类型：
--
作者：
Lijun Xu;Yong Yan;S. Cornwell;G. Riley
本文提出了一种使用数字信号处理（DSP）和模糊推理技术进行在线燃料识别的新方法。包含三个光电二极管的火焰探测器用于获取涵盖从红外到紫外到可见光波段的宽火焰光谱的多个信号。采用先进的数字信号处理和模糊推理技术来识别火焰在时域和频域中的动态“指纹”，并最终识别燃烧的煤炭类型。使用英国 RWE Innogy plc 运营的 0.5 MW/sub 燃烧测试设备进行了一系列实验。获得的结果表明，该方法可用于识别稳定燃烧条件下燃烧的煤的类型。
This paper presents a novel approach for on-line fuel identification using digital signal processing (DSP) and fuzzy inference techniques. A flame detector containing three photodiodes is used to derive multiple signals covering a wide spectrum of the flame from infrared to ultraviolet through visible band. Advanced digital signal processing and fuzzy inference techniques are deployed to identify the dynamic "fingerprints" of the flame both in time and frequency domains and ultimately the type of coal being burnt. A series of experiments was carried out using a 0.5-MW/sub th/ combustion test facility operated by RWE Innogy plc, UK. The results obtained demonstrate that this approach can be used to identify the type of coal being burnt under steady combustion conditions.