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Steel structure has been widely used in modern buildings due to their excellent building performance, but their poor fire resistance requires special coating which can resistant fire for protection. With the increasing demand for fire-resistant coatings for steel structure, fire-resistant coatings with different fire-retardant mechanisms have emerged one after another. The market complexity has increased, and there is a significant difference in fire resistance performance among products, requiring real-time and effective supervision by the relevant department. However, due to the wide variety of fire-resistant coatings and the complexity of standard detecting methods, it brings difficulties for fire supervision and on-site inspection of fire-resistant coatings. The research proposed an efficient method based spectral analysis to detect the fire-resistant coatings with different fire resistive mechanisms, including both intumescent coatings and non-intumescent coating. Principal component analysis is used to quickly identify the spectral consistency of different coatings. The experiment selected samples of fire-resistant coatings with excellent performance verified by standard detection methods and ordinary one for visible to shortwave infrared 400-2500nm spectral collection and spectral feature analysis. The experimental result indicates that samples of high-performance fireproof coatings have high consistency in spectral feature. Through intelligent recognition algorithms, coating samples with unsatisfactory performance can be quickly and accurately detected. The research has shown that the intelligent spectral imaging technology is expected to provide a reliable basis for rapid on-site identification of fire resistive coatings for steel structure.
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