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建立了能够定量预测热像仪探测泄漏气体能力的信噪比(SNR)与气体浓度(C)模型SNR-C,利用该模型对制冷热像仪GasFindIRTM在SNR=1时对应的甲烷气体浓度进行预测,预测数据与实际测试数据吻合。搭建了SNR-C室内测试装置,测试了非制冷热像仪Photon320在以298、303、308、313和318 K面源黑体为背景时探测乙烯气体的SNR-C曲线。数据分析发现,Photon 320在SNR≈5时,实测与预测乙烯浓度在各黑体背景温度下均比较接近。在SNR=5时,模型预测的乙烯气体浓度分别为3146、987、570、394和298 ppm,该变化规律与实际测量结果一致。建立的SNR-C模型能预测热像仪探测气体的能力,而搭建的测试装置能定量测量热像仪探测泄漏气体时信噪比与气体浓度之间的变化关系,可用于热像仪探测泄漏气体的室内性能测试。
The signal-to-noise ratio (SNR) and gas concentration (C) model SNR-C, which can quantitatively predict the capability of thermal imager to detect leaking gas, were established and the methane gas concentration corresponding to GasFindIRTM was obtained Forecast, forecast data and the actual test data. The SNR-C indoor test set-up was set up to test the SNR-C curve of uncooled thermal imager Photon 320 in detecting ethylene gas with 298, 303, 308, 313, and 318 K faceted blackbody as the background. Data analysis showed that the measured and predicted ethylene concentrations at Photon 320 at SNR ≈ 5 were all close at each blackbody background temperature. At SNR = 5, the model predicts ethylene gas concentrations of 3146, 987, 570, 394 and 298 ppm, respectively, consistent with the actual measurements. The established SNR-C model can predict the ability of thermal imager to detect gas, and the built test device can quantitatively measure the change of signal-to-noise ratio and gas concentration when the thermal imager detects the leakage gas and can be used to detect the leakage Gas Indoor Performance Test.