Self-adaptive CH4 concentration detection system based on infrared spectrum absorption principle

Considering that the noises resulting from low modulation frequency are serious and cannot be totally eliminated by the classic filters, a novel infrared (IR) gas concentration detection system based on the least square fast transverse filtering (LS-FTF) self-adaptive modern filter structure is proposed. The principle, procedure and simulation on the LS-FTF algorithm are described. The system schematic diagram and key techniques are discussed. The procedures for the ARM7 processor, including LS-FTF and main program, are demonstrated. Comparisons between the experimental results of the detection system using the LS-FTF algorithm and those of the system without using this algorithm are performed. By using the LS-FTF algorithm, the maximum detection error is decreased from 14.3% to 5.4%, and also the detection stability increases as the variation range of the relative error becomes much smaller. The proposed LS-FTF self-adaptive denoising method can be of practical value for mid-IR gas detection, especially for weak signal detection.