LAS-on-edge: A real-time laser absorption spectroscopic water vapor sensor on edge computing platforms

Abstract

Real-time and in situ water vapor (H2O) sensors are increasingly demanded to indicate thermochemical parameters of energy systems. As an accurate, fast and non-intrusive sensing technology, laser absorption spectroscopy (LAS) enables simultaneous measurement of gas concentration and temperature. Due to the complex spectral computation, real-time and rapid LAS signal processing are still challenging. Most state-of-the-art LAS sensors utilize high-level computing units to post-process laser measurements in real time, hindering their portable deployment in harsh industrial environments. To address the above challenge, we developed an online LAS gas sensor on edging computing platforms, named as LAS-on-Edge. The developed sensor achieves an online monitoring rate up to 62.5 Hz by deploying a spectral-informed neural network on an embedded device. Simultaneously, it reserves the raw kilo-Hz measurements offline for underlying dynamics understanding. The LAS-on-Edge sensor’s compactness also enables its flexible and in situ integration. The sensor is firstly used to monitor a slow mist diffusion and accumulation process, exhibiting a high measurement accuracy with low spectra recovery residuals below 0.01. It is further applied to online monitor the H2O concentration and temperature variation during a lab-scale propane combustion process. It demonstrates a minimal temperature deviation of 1.86 % compared to the thermocouple reference in the flame. The sensor also successfully detects the fundamental flame pulsation at 5.65 Hz as well as high-frequency pulsations exceeding 200 Hz, thereby effectively reveals underlying flame dynamic behaviors.