Performance Enhancement of Mid-infrared NH Sensor Using 9.06 μm QCL Based on Spectral Optimization and NGO-LSTM Model

A detection sensor for mid-infrared ammonia (NH) has been developed according to wavelength modulation spectroscopy-tunable diode laser absorption spectroscopy (WMS-TDLAS) technology, which can be applied in the chemical and aquaculture industries. A 9.06 µm quantum cascade laser (QCL) and a 41.5 m multipass gas cell (MPGC) were used to increase the detection limit of NH. Spectral optimization and the NGO-LSTM (northern goshawk optimization-long short-term memory) model applied to gas detection are designed to improve the accuracy of sensor. Among them, the design of the temperature compensation and spectral drift correction reduces the effect of temperature and other environmental factors. The original second harmonic signal was denoised using the CEEMDAN-WPD (complete ensemble empirical mode decomposition with adaptive noise-wavelet packet decomposition) algorithm. And the NGO-LSTM algorithm was applied to NH concentration inversion, adaptively optimizing the weight parameters. The experiment reflects that the measured value of the sensor has an excellent linear relationship with the set value (R 0.9992). The long-term stability of the sensor was verified based on 400 ppb NH, with an RMSE (root mean square error) of 4.754 ppb. Allan-Werle bias analysis shows that the detection limit (LoD) is approximately 792 ppt at an integration time of 232 s. Subsequent response time and atmospheric environment simulation experiments have proven that this sensor provides an efficient approach for real-time monitoring of NH.