基于TDLAS技术的CO_(2)浓度检测方法研究

Research on CO_(2) concentration detection method based on TDLAS technology

全球变暖日益严重,二氧化碳作为温室气体的主要成分,需要精准把控。可调谐半导体激光吸收光谱技术因其具有高灵敏度、高分辨率的特点,被广泛应用于气体检测等领域。为了进一步提高TDLAS系统的测量精度,在小波去噪的基础上,对去噪后的TDLAS二次谐波信号进行了频域分析处理,利用离散小波变换提取与CO_(2)浓度变化相关的频域特征信号,建立回归模型反演气体浓度。时域回归模型校正集与预测集的相关系数分别为0.998 5和0.997 3,RMSE值分别为0.045 9%和0.017 9%,预测集的最大相对误差为4.62%;频域回归模型校正集与预测集的相关系数分别为0.999 3和0.999 7,RMSE值分别为0.032 0%和0.006 9%,预测集的最大相对误差为1.54%。实验结果表明TDLAS系统的预测能力和测量精度均有效提高,验证了该方法的可行性。

Global warming is becoming more and more serious, and carbon dioxide, as the main component of greenhouse gases, needs to be precisely controlled. Tunable semiconductor laser absorption spectroscopy is widely used in gas detection and other fields due to its high sensitivity and high resolution. In order to further improve the measurement accuracy of the TDLAS system, the denoised TDLAS second harmonic signal was analyzed in the frequency domain on the basis of wavelet denoising, and the frequency domain characteristic signal related to the change of CO_(2) concentration was extracted by discrete wavelet transform. And establish a regression model to invert the gas concentration. The correlation coefficients of the time domain regression model calibration set and prediction set are 0.998 5 and 0.997 3, the root mean square error(RMSE) values were 0.045 9% and 0.017 9%, respectively, and the maximum relative error of the prediction set is 4.62%. The correlation coefficients of the frequency domain regression model calibration set and prediction set were 0.999 3 and 0.999 7, the RMSE values were 0.032 0% and 0.006 9%, respectively, and the maximum relative error of the prediction set was 1.54%. The experiment results show that the prediction ability and measurement accuracy of the TDLAS system were effectively improved, which verifies the feasibility of the method.