Based on tunable semiconductor laser absorption spectroscopy (TDLAS) and frequency division multiplexing (FDM) method, a near-infrared multi-component trace gas identification and detection system based on support vector machine (SVM) classification was studied. When laser spectroscopy technology characterizes gas absorption spectral lines, the absorption capacity of gas in the near-infrared band is lower than that in the far-infrared band. The absorption signal of gas detected by single-band laser spectrum is weak, and each gas component interferes with each other greatly. To improve detection accuracy, accurately identify gas components and perform multi-component detection at the same time, based on tunable semiconductor laser absorption spectroscopy technology, the frequency division multiplexing near-infrared TDLAS technology method is used, and the SVM classification algorithm is used to perform the real-time detection process of mixed gases. It effectively avoids cross-interference of various gases and realizes trace detection of eight gas markers: nitric oxide NO, hydrogen sulfide H₂S, ammonia NH₃, nitrogen dioxide NO₂, acetylene C₂H₂, carbon dioxide CO₂, methane CH₄, and hydrogen chloride HCl. When eight lasers work simultaneously, the system controls the band-pass filter to perform time-sharing filtering. It sequentially transmits the second harmonic data after differential phase locking to the host computer for real-time display. The recognition rate is over 96.3%, and the average content prediction accuracy is higher than 99.6%. It has achieved high-precision detection results with the lowest detection limit of CH₄ being 0.01 μL·L^-1, NO₂ being 0.05 μL·L^-1, and C₂H₂ being 0.03 μL·L^-1, and the detection limits of other gases are below 5 μL·L^-1. Conduct anti-interference analysis and detection lower limit analysis on the multi-channel detection of the system to verify that the system can achieve high-precision concentration detection of mixed gases when the system is operating stably. This system uses a distributed feedback laser drive and lock-in amplifier combined with the SVM algorithm model of data processing to realize multi-component trace gas identification and detection of near-infrared TDLAS technology, which can meet the trace level detection of trace gases and provide ultra-low performance for the future. The detection of concentration mixed gases is of very important significance.