Fig. 1. Schematic diagram of laser cleaning principle^[8]

Fig. 2. Acoustic wave generated during laser irradiation on uncleaned copper surfaces at fluences^[16]

Fig. 3. The duration of sound waves varies with the number of laser^[18]

Fig. 4. (a) Schematic diagram of the monitoring experimental setup of using laser to remove graffiti on marble; (b) SEM images of the irradiated areas at the onset of graffiti ablation, effective cleaning and substrate damage; (c) Relationship between the average normalized PA signal and the laser energy flow density; (d) The normalized PA signal changes with the number of pulses at different laser fluences^[13]

Fig. 5. (a) Surface morphology of 100 W, 10 kHz laser paint removal; (b), (c) Waveform and spectrogram of paint removal acoustic signal under the action of 100 W laser, respectively^[11]

Fig. 6. (a) Surface topography of the paint after the first, fourth, sixth and ninth pulse irradiation; (b) Time-domain signals with different number of acting pulses; (c) Frequency domain waveform of the acoustic signal; (d) The change of frequency domain signal with the number of acting pulses; (e) LSD varies with the number of pulses^[20]

Fig. 7. Schematic diagram of the working mechanism of LIBS ^[24]

Fig. 8. LIBS spectra in the spectral region from 245 to 310 nm obtained by two laser pulses each on the black crust and the laser-cleaned region^[27]

Fig. 9. Relationship between the total spectral intensity and the depth of action of the laser^[33]

Fig. 10. (a) Evolution of (0.5-1.2 μs) signals at 375.9 nm (Ti) when different laser pulses act on paint over time; (b)-(i) Evolution of signals at 375.9 nm (Ti) after different laser pulses act on the paint sample^[41]

Fig. 11. Surface morphology of the thin blue paint after being irradiated by (a) three, (b) four, and (c) five laser pulses; TRS signal at 368.5 nm and its double exponential function fitting (solid line) of (d) third, (e) fourth, and (f) fifth pulses on thin blue paint and substrate (black dotted line); (g) Detailed TRS signal at 368.5 nm (Ti); (h) Intensity of the TRS signal versus pulse number at 0.3 µs; (i) Ratio of the coefficient (A_short/A_long) of the TRS signal of blue paint as a function of pulse numbers^[42]

Fig. 12. [in Chinese]

Fig. 12. (a) Schematic diagram of a reflected light spectroscopy monitoring device for laser cleaning surface monitoring and process diagnostics; (b) The change of chromaticity with the number of irradiated laser pulses; (c) Characteristic values at different pulse numbers of irradiation and (d) Characteristic values of contaminated, cleaned and damaged surfaces; (e) Characteristic values of contaminated, cleaned and damaged surfaces in the X-Y plane coordinate system of the main wavelengths and energy levels; (f) Micrographs of cleaned and damaged surfaces^[44]

Fig. 13. (a) Reflected light signal power measuring device; (b) Reflected optical power variation curves at different power densities and pulse numbers^[45]; (c) Schematic diagram of He-Ne laser reflected optical signal power measurement system device for online monitoring of coating removal; (d) Reflected optical power change curve under different power densities and pulses per point^[46]

Fig. 14. (a)-(b) Photocoherent imaging images of clean and uncleaned surfaces of oil paintings; (c) Fourier transform infrared spectra of clean and unclean surfaces of oil paintings and original paint layers and substrates^[47]

Fig. 15. Fluorescence spectroscopy measurement comparison results when laser cleaning oil paintings^[47]

Fig. 16. (a) Plot of results obtained by following the cleaning steps using the Nd:YAG laser LQS, SFR mode and chemical ointment (CH) on the fresco; (b) Corresponding OCT scanning plot (2 cm length) measured by different cleaning steps^[57]

Fig. 17. Schematic diagram of laser cleaning detection^[61]

Fig. 18. (a) Laser cleaning rust experimental device; (b) Image acquisition device; (c) Loss function and prediction accuracy curves^[63]

Fig. 19. (a) Schematic diagram of the photoacoustic and image mixed measurement experimental setup; (b) Acoustic signal acting on the first 15 laser pulses; (c) Optical photograph after irradiation of the first 15 laser pulses^[64]

Fig. 20. (a) 13 point areas where the FORS measurement was made, laser-treated areas (red dots) and uncleaned areas (yellow dots); (b) Four Vis-NIR reflectance spectra obtained by FORS; (c) Reference reflectance spectrum of gypsum; (d)-(e) Pseudo-color RGB plots in the Vis spectral range (420-885 nm) and NIR spectral range (1300-1615 nm), respectively; (f) Spectral angle mapper (SAM) classification plot for the 950-1650 nm range; (g) RGB images reconstructed from HSI data are used for direct comparison with plots and visual localization of processed and untreated areas^[56]

Fig. 21. (a) Schematic diagram and physical diagram of the cleaning device; (b) Comparison before and after laser cleaning of the surface of the steel plate sample based on the process monitoring method; (c) 3D morphology of the rust layer; (d) 3D morphology after cleaning^[65]