As a new laser surface treatment technology, laser shock peening (LSP) has been applied to strengthen and prolong the life of critical components such as the aero-engine and gearbox. Ensuring the consistency and stability of LSP processing quality is of great significance to the long service life of the aviation mentioned above equipment. However, the protective coating is easily ablated and damaged in the high-energy transient LSP process, limiting the industrial application of LSP significantly. Therefore, this paper proposed a real-time detection method for protective coating damage of LSP based on ReliefF feature weight fusion by analyzing laser-induced plasma spectrum signal. The 7075 aluminum alloy with a thickness of 4 mm was used as an LSP target, and the black tape was used as the protective coating. Firstly, the Ocean Optics-HR4000 spectrometer with a wide wavelength range and Princeton SP2750 spectrometer with a high resolution was used to synchronously collect the plasma spectra produced in the LSP transient process.Secondly, according to the spectral signals with a high resolution collected by the Princeton SP2750 spectrometer,the peak intensities and Stark-FWHMs of Al Ⅰ spectra at 394.40 and 396.15 nm and that of Fe Ⅰ spectra at 393.36 and 396.80 nm were extracted, then, combined with the feature importance obtained by the ReliefF algorithm to screen out two Al Ⅰ spectra that were more sensitive to the damage states of the protective coating, andqualitatively analyzedthe sensitivity and the law of transient variation for intensity and Stark-FWHM of Al Ⅰ spectra to the damage states of the protective coating. Furthermore, a feature named intensity-FWHM (I-FWHM) fusing the information of multiple spectral emission lines was constructed using the ReliefF algorithm, and then, the ability of each feature to distinguish the three kinds of damage states was quantitatively evaluated based on the distance between classes. Finally, combined with the threshold segmentation method, real-time detection of LSP protection layer damage was realized. The experimental results show that the intensity is very poor in distinguishing between normal state and slight damage but very strong in distinguishing between slight damage and complete damage. The Stark-FWHM is far better than intensity in distinguishing between the normal state and slight damage, but the abilityis relatively weak in distinguishing between slight and complete damage. The I-FWHM combines the advantages of the above single feature and can better distinguish the three types of damage states simultaneously. Therefore, I-FWHM has stronger anti-interference ability and higher robustness for the real-time detection of protective coating damage state in the LSP process.