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Understanding the influence of turbulence in imaging Fourier transform spectroscopy of smokestack plumes

机译:了解湍流对烟囱羽流成像傅里叶变换光谱的影响

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A Telops Hyper-Cam Fourier-transform spectrometer (IFTS) was used to collect infrared hyper-spectral imagery of the smokestack plume from a coal-burning power facility to assess the influence of turbulence on spectral retrieval of temperature (T) and pollutant concentrations (Ci ). The mid-wave (1.5-5.5 μm) system features a 320x256 InSb focal-plane array with a 326 μrad instantaneous field-of-view (IFOV). The line-of-sight distance to the 76mtall smokestack exit was 350m(11.4 x 11.4 cm2 IFOV). Approximately 5000 interferogram cubes were collected in 30 minutes on a 128x128 pixel window corresponding to a spectral resolution of 20 cm-1. Radiance fluctuations due to plume turbulence were observed on a time scale much shorter than hyper-spectral image acquisition rate, suggesting scene change artifacts (SCA) would be present in the Fourier-transformed spectra. Time-averaging the spectra minimized SCA magnitudes, but accurate T and Ci retrieval requires a priori knowledge of the statistical distribution of temperature and other stochastic flow field parameters. A method of quantile sorting in interferogram space prior to Fourier-transformation is presented and used to identify turbulence throughout the plume. Immediately above the stack exit, T and CO2 concentration estimates from the median spectrum are 395 K and 6%, respectively, which compare well to in situ measurements. Turbulence is small above the stack exit and introduced systematic errors in T and Ci on the order of 0.5 K and 0.01%, respectively. In some plume locations, turbulent fluctuations introduced errors in T and Ci on the order of 8 K and 1%, respectively. While more complicated radiance fluctuations precluded straightforward retrieval of the temperature probability distribution, the results demonstrate the utility of additional information content associated with multiple interferogram quantiles and suggest IFTS may find use as a tool for non-intrusive flow field analysis
机译:使用Telops Hyper-Cam傅里叶变换光谱仪(IFTS)收集来自燃煤发电设施的烟囱烟流的红外高光谱图像,以评估湍流对温度(T)和污染物浓度的光谱检索的影响( Ci)。中波(1.5-5.5μm)系统具有320x256 InSb焦平面阵列和326μrad瞬时视场(IFOV)。到76mtall烟囱出口的视线距离为350m(11.4 x 11.4 cm2 IFOV)。在30分钟内在对应于20 cm-1光谱分辨率的128x128像素窗口上收集了大约5000个干涉图立方体。在比高光谱图像采集速率短得多的时间尺度上观察到由于羽流湍流引起的辐射波动,这表明场景变化伪像(SCA)将出现在傅立叶变换光谱中。对频谱进行时间平均可将SCA幅度最小化,但要准确地进行T和Ci检索,则需要先验温度和其他随机流场参数的统计分布。提出了一种在傅立叶变换之前在干涉图空间中进行分位数排序的方法,该方法用于识别整个羽流中的湍流。在烟囱出口正上方,根据中值光谱估算的T和CO2浓度分别为395 K和6%,与现场测量结果相比非常好。在烟囱出口上方的湍流很小,并且在T和Ci中引入了系统误差,分别为0.5 K和0.01%。在某些羽状流位置,湍流波动导致T和Ci的误差分别约为8 K和1%。尽管更复杂的辐射度波动无法直接获取温度概率分布,但结果证明了与多个干涉图分位数相关的附加信息内容的实用性,并暗示IFTS可能会用作非侵入式流场分析的工具

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