RESUMO
We propose a novel methane leakage rate remote sensor that combines a single-photon avalanche diode detector with a near-infrared 1653.7â nm low-power laser. The proposed M sequence and triangle wave signal modulation method simultaneously realizes the detection of methane leakage and target point clouds. Innovatively, the sensor's methane concentration and leakage rate quantification ability were simulated by combining the Gaussian plume diffusion model and the Risley prism. The effects of the prism rotation ratio, wind speed, leakage rate, atmospheric stability (AS), target reflectivity, signal averaging period, and concentration spatial interpolation method on leakage rate are discussed. When plume methane concentrations reduce from 10,000 to 500â ppm·m, the relative concentration bias rise from 1% to 30%, the absolute concentration bias is approximately 100â ppm·m. Two spatial concentration interpolation methods introduced leakage rate bias ranging from 6%-25%. For a low AS, the leakage rate bias under the cubic interpolation method was small (approximately 1.6%). In addition, when the initial leakage rate increased from 100 to 1,000â mg/s, the leakage rate bias was approximately 20% smaller.
RESUMO
High-precision temperature control of large-area blackbodies has a pivotal role in temperature calibration and thermal imaging correction. Meanwhile, it is necessary to correct the temperature difference between the radiating (surface of use) and back surfaces (where the temperature sensor is installed) of the blackbody during the testing phase. Moreover, large-area blackbodies are usually composed of multiple temperature control channels, and manual correction in this scenario is error-prone and inefficient. At present, there is no method that can achieve temperature-automated calibration for a large-area blackbody radiation source. Therefore, this article is dedicated to achieving temperature-automated calibration for a large-area blackbody radiation source. First, utilizing two calibrated infrared thermometers, the optimal temperature measurement location was determined using a focusing algorithm. Then, a three-axis movement system was used to obtain the true temperature at the same measurement location on a large-area blackbody surface from different channels. This temperature was subtracted from the blackbody's back surface. The temperature difference was calculated employing a weighted algorithm to derive the parameters for calibration. Finally, regarding experimental verification, the consistency error of the temperature measurement point was reduced by 85.4%, the temperature uniformity of the surface source was improved by 40.4%, and the average temperature measurement deviation decreased by 43.8%. In addition, this system demonstrated the characteristics of strong environmental adaptability that was able to perform temperature calibration under the working conditions of a blackbody surface temperature from 100 K to 573 K, which decreased the calibration time by 9.82 times.