Combustible Type Identification: Multi-Spectral Perceptual Fusion, Accurate Discrimination, and Fire-Extinguishing Decision Support

    Judging the type of combustible is a crucial link in fire extinguishing. The combustible type identification technology of our company’s firefighting robot achieves accurate judgment of combustible types based on the spectral characteristics of material combustion, combined with advanced multi-sensor collaboration and deep learning algorithms.

    When atoms or ions of different elements are excited by the high temperature of a flame to jump to a high-energy state, they emit light of specific wavelengths when returning to the ground state, forming unique characteristic spectral lines. For instance, when substances like wood, liquid fuels, and metals burn, they produce spectral signals with distinct combinations and intensities. Equipped with a spectral detector, the firefighting robot collects flame spectral information in real time to obtain the "spectral fingerprint" of the combustible.

    In real-world fire scenarios, combustibles are often mixtures of multiple substances, with their spectral characteristics intricately intertwined—making it difficult for traditional analysis methods to identify them quickly and accurately. Leveraging the powerful feature extraction and pattern recognition capabilities of Convolutional Neural Networks (CNN), the model is trained on a large volume of experimental data, enabling it to precisely parse key information from complex spectral data. Meanwhile, the event camera accurately captures the dynamic features of flame flicker to eliminate static interference, ensuring the collected spectral data is authentic and valid; the stereo camera assists in determining the flame’s position and works in synergy with the spectral detector to conduct real-time analysis of flame spectra (such as the characteristic spectral lines of OH* and CH* free radicals), guaranteeing the accuracy of spectral collection.

    Through the synergy of these technologies, the firefighting robot can classify 6 major categories of combustibles—including wood, liquid fuels, gaseous fuels, and electrical materials—within 1 second, with an identification accuracy rate of up to 98%. This breakthrough effectively addresses the challenge of traditional methods struggling to quickly analyze mixed combustibles, providing a scientific and precise basis for formulating fire-extinguishing strategies.

    The in-depth integration of multiple technologies endows the firefighting robot with an identification capability akin to a "sharp eye for fire." In the incipient stage of a fire, the robot can quickly lock onto the fire source, accurately determine the combustible type, and select an appropriate fire-extinguishing agent accordingly. This prevents the fire from escalating due to improper use of fire-extinguishing agents, greatly improving fire-extinguishing efficiency while significantly enhancing the scientificity and precision of fire rescue—providing strong support for protecting lives and property.