This paper highlights a high-frequency nanosecond infrared pulsed laser paint removal LIBS monitoring platform and investigates the on-line monitoring of laser paint removal thickness on aluminium alloy panels coated with a double layer of paint.

The plasma generation and evolution processes are susceptible to matrix effects, environmental noise, pulse energy jitter, etc., resulting in the instability of the spectral data, which makes it difficult to ensure the validity of the monitoring criterion established based on a single spectral line. The monitoring criterion established by continuous multiple LIBS spectra combined with statistical methods can effectively improve the monitoring accuracy of paint removal based on LIBS technology. Based on a high-frequency nanosecond infrared pulsed laser paint removal LIBS online monitoring platform, the paper collected continuous multiple LIBS spectra of the paint removal process in reaLtime. After the spectral data were pre-processed by baseline correction and normalization, the spectral peaks of Ba I (712. 55 nm) Cr I (357. 48 nm), Cr I (425. 43 nm) Ti I (427. 45 nm), Cu II (309. 76 nm), Cu I (484. 22 nm) were used as the characteristic spectral lines and the paint removal effect was monitored. The intensity variation of the six characteristic spectral lines in different paint removal effects was studied, and the mapping relationship between different paint removal effects and the intensity variation of the selected characteristic spectral lines was established. The intensity of the above 6 spectral lines for each spectrum is extracted as data units. The data units of 10 consecutive spectral lines are used as data sets, and the data sets of each 10 iterations of the paint removal process are called data flow disks. The data cells and data sets in the data flow disk are analyzed. The confidence intervals are combined to determine the paint removal effect in the paint removal area in reaLtime. The monitoring criterion based on the data flow disk is obtained. The results show that this criterion can effectively monitor the paint removal effect in five categories: still on the top coat, completely removed top coat, still on the bottom coat, completely removed bottom coat, and substrate damage. The threedimensional micro-pattern analysis showed that the accuracy of complete topcoat removal reached 1. 2 mu m, which effectively verified the applicability and stability of the LIBS-based data flow disc monitoring criterion.

Online monitoring technology plays a pivotal role in advancing the utilization of laser paint removal in aircraft maintenance and automation. Through the utilization of a high-frequency infrared pulse laser paint removal laser-induced breakdown spectroscopy (LIBS) online monitoring platform, this research conducted data collection encompassing 60 sets of LIBS spectra during the paint removal process. Classification and identification models were established employing principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA). These models served as the foundation for creating criteria and rules for the online LIBS monitoring of the controlled paint removal process for aircraft skin. In this research, 12 selected characteristic spectral lines were used to construct the OPLS-DA model, with a predictive root mean square error (RMSEP) of 0.2873. Both full spectrum and feature spectral line data achieved a predictive accuracy of 94.4%. The selection of feature spectral lines maintains predictive performance while significantly reducing the amount of input data. Consequently, this research offers a methodological reference for further advancements in online monitoring technology for laser paint removal in aircraft skin.

The monitoring of aircraft paint cleaning based on Laser-induced breakdown spectroscopy (LIBS) technology requires limiting the peak power density range to ensure the stability of plasma excitation and paint cleaning. However, for the widely used high-frequency (kHz-level) pulsed laser paint removal technique, the peak power density is relatively low, which limits the plasma excitation during the paint removal process, and the strong continuous background spectra generated by the high-frequency laser ablation of the material interferes with the plasma spectral acquisition. Based on the demand for controllable cleaning of the functional paint layer of the skin, the thesis designs a LIBS monitoring platform for high-frequency laser paint removal based on the writing of the control software of LabVIEW embedded development system and the integration of laser cleaning, spectral acquisition, control and display modules. The 2024-T3 aluminum alloy double-paint layer specimen was selected as the research object, and the spectra of the paint layer/substrate system with wavelengths in the range of 360 similar to 700 nm were collected (top paint layer: TC; bottom paint layer: PR; substrate: AS). The original spectra were preprocessed by smoothing filter, baseline correction, and normalization, and 12 characteristic spectral lines were selected for principal component analysis (PCA), and their dimensionality reduction data were used as the input variables for linear discriminant analysis (LDA), to establish the PCA-LDA discriminant model. Finally, the model was imported into the LIBS monitoring platform, and the classification accuracy of the high-frequency laser paint removal LIBS monitoring platform was verified through experiments. The results show that: only the cumulative variance explanation rate is greater than 85% as the principle of principal component selection, which can not meet the classification needs of LDA in the paint removal process; by optimizing the number of principal components of LDA, and ultimately selecting the first 9 principal components as the input of LDA, the detection accuracy of the LIBS platform is significantly improved. At this time, the classification accuracy of the PCA-LDA model based on LIBS spectra reaches 92.5%. It can be seen that the designed high-frequency laser paint removal LIBS monitoring platform can complete the material identification of different structural layers of the paint layer/substrate system, thus realizing the effective monitoring of high-frequency pulsed laser controllable paint removal.

Correction for 'Research on online monitoring of aircraft skin laser paint removal thickness using standard curve method and PCA-SVR based on LIBS' by Wenfeng Yang et al., Anal. Methods, 2024, https://doi.org/10.1039/D4AY00872C.

Laser-induced breakdown spectroscopy (LIBS) is expected to be used for real-time monitoring and closed-loop control of laser-based layered controlled paint removal (LLCPR) from aircraft skin. However, the LIBS spectrum must be rapidly and accurately analyzed, and the monitoring criteria should be established based on machine learning algorithms. Hence, this study develops a self-built LIBS monitoring platform for the paint removal process utilizing a high-frequency (kilohertz-level) nanosecond infrared pulsed laser and collects the LIBS spectrum during the laser removal process of the top coating (TC), primer (PR), and aluminum substrate (AS). After subtracting the spectrum's continuous background and screening the key features, we construct a classification model of three types of spectra (TC, PR, and AS) based on a random forest algorithm, and the real-time monitoring criterion based on the classification model and multiple LIBS spectra was established and verified experimentally. The results show that the classification accuracy is 98.89%, the time-consuming classification is about 0.03 ms per spectrum, and the monitoring results of the paint removal process are consistent with the macroscopic observation and microscopic profile analysis results of the samples. Overall, this research provides core technical support for the real-time monitoring and closed-loop control of LLCPR from aircraft skin.

激光分层除漆的可靠性与可控性依赖于有效的在线监测技术,采用激光诱导击穿光谱(LIBS)技术能有效监控激光除漆过程.本文采用激光去除飞机碳纤维复合材料(CFRP)表面漆层,并基于高重频激光除漆LIBS在线监测平台,在线采集除漆过程所激发的面漆和底漆2类光谱共60组.分别建立了基于主成分分析(PCA)和偏最小二乘法(PLS)的判别和预测模型,研究了激光分层除漆过程中LIBS光谱的分类判别.PCA模型前两个主成分累计贡献率达到了79.2％,PLS-DA模型前两个主成分累计贡献率达到了85.5％.PLS回归模型校正标准差(RMSEE)为0.142923,均方根误差(RMSEcv)为0.152053,模型的预测标准差(RMSEP)为0.142421,对20组激光清洗面漆和底漆的混合数据集进行预测,预测准确率达100％.结果表明PLS判别模型比PCA模型分类判别效果更好,PLS预测模型实时评估和自动分类漆层具有较好的预测精度.本研究可为LIBS在线监测激光除漆过程,实现自动化、智能化的激光除漆提供技术支持.

随着飞机蒙皮"部分褪漆"维修理念的提出,多漆层结构激光除漆的可控性值得关注.基于响应面分析方法,建立了激光参数(光斑搭接率、激光功率及扫描次数)与可控性指标(漆层去除厚度、表面粗糙度)间的数学模型,分析了激光多参数耦合作用对可控性指标的影响规律.结果表明:激光参数对漆层去除厚度的影响顺序依次为扫描次数、激光功率、光斑搭接率,且均为正相关;表面粗糙度随光斑搭接率的增大而减小,随激光功率的增大而增大,扫描次数对表面粗糙度的影响具有峰值效应.验证试验结果表明:响应面模型可为厚度精度为±5 μm的激光可控除漆提供参考.基于响应面分析方法建立的多漆层结构激光可控清除数学模型,可为飞机蒙皮漆层的激光可控清除提供方法指导与理论支撑.

为精准还原单脉冲激光褪漆过程,建立了单点褪漆有限元计算模型,分析了激光褪漆的温度场和热应力场变化规律,通过生死单元技术实现了漆层形貌仿真还原,并完成了不同功率的激光试验对比验证.结果表明:单脉冲激光褪漆过程中,温度判据决定最大烧蚀形貌深度,热应力判据决定最大烧蚀形貌宽度.所提多物理场分析模型获得的褪漆形貌与试验的平均贴合度达到93.3%,较传统单温度场的仿真形貌精度提高6.5%,该研究对实际激光褪漆工艺具有较好的指导与应用价值.

Objective Understanding the crater morphology on the surface of a paint layer after a single laser pulse can effectively suppress the superposition effects of multiple laser parameters and the photothermal and photomechanical effects of a pulse overlap. This helps reveal the laser- material interaction mechanism and provides a basis for the optimization of laser parameters. In recent years, many scholars have simulated the morphology of craters on the surface of a paint layer with the help of finite element software after nanosecond pulsed laser action based on the ablation mechanism. The laser parameters are then optimized based on the simulation results. For nanosecond pulsed lasers, the main mechanism of the laser-material interaction varies at different energy densities (the main mechanism is the ablation mechanism at low energy density, and the plasma shock and thermal radiation mechanism at high energy density). The ablation mechanism, plasma shock, and thermal radiation mechanism have different effects on the morphology of the crater. This study aims to establish a model of the damage form and the removal process of the paint layer during a single pulse of a nanosecond laser under different energy densities, to reveal the differences in the influence of the laser-material mechanism on the morphology of craters under different energy densities, and to provide a reference for the precise control and parameter optimization of the paint removal effect at high and low energy densities. Methods A nanosecond pulsed laser with a wavelength of 1064 nm and beam energy following a Gaussian distribution was applied to the epoxy primer surface. The diameter, depth, and three-dimensional morphology data of the craters on the surface of the paint layer were measured using a 3D optical surface profiler after the laser pulse. A simulation model of crater morphology was established based on the ablation mechanism and the fitting relationship between the depth (d) of the craters and energy densities (F). MATLAB was used to simulate the morphology of the craters in the energy density range of 13. 58. 27. 16 J/cm(2), and an experimental verification was carried out. Error analysis of the experimental and simulation results under a high density revealed the influence of the plasma shock and thermal radiation mechanism on the morphology of the crater. The model correction and experimental verification were carried out based on the plasma shock and thermal radiation mechanisms. Results and Discussions The simulation model of crater morphology based on the ablation mechanism has an error of less than 5% for crater depth and diameter at a low energy density (13. 58. 16. 98 J/ cm(2)), less than 5% for crater depth error at a high energy density (20. 37. 27. 16 J/ cm(2)), and up to 40% for diameter error (Fig. 5). The error analysis shows that at a high energy density, the plasma shock and thermal radiation mechanisms are the main reason for the diameter error (Fig. 7). After the model was corrected based on the above analysis, the diameter and depth errors of the craters under a high energy density were controlled within 5%, which significantly improved the accuracy of the model (Fig. 9). The model shows that at a low energy density, the surface of the crater is approximately rotated paraboloid, and the profile of the crater is similar to a parabola; at a high energy density, the surface of the crater can be regarded as a combination of multiple normally-distributed surfaces, and the crater profile as a combination of multiple normal distribution curves. Conclusions At different energy densities, differences in the laser-material mechanism are noted; the ablation mechanism at a low energy density and the laser plasma shock and thermal radiation mechanisms at a high energy density are the main interaction mechanisms. Differences in the laser-material interaction mechanisms cause damage to the paint layer. Compared to the ablation mechanism, the plasma shock and thermal radiation mechanisms lead to an increase in the amount of paint removed near the surface of the crater and a wider profile near the crater surface. A simulation model of crater morphology is established for different laser-material mechanisms, thereby effectively improving the model accuracy. The study results provide a reference for the accurate control of the laser paint removal process and the optimization of paint removal parameters under high and low energy densities.

Reliability and controllability of selective removal of multiple paint layers from the surface of aircraft skin depend on effective online monitoring technology. An analysis was performed on the multi-pulse laser-induced breakdown spectroscopy (LIBS) on the surface of the aluminum alloy substrate, primer, and topcoat. Based on that, an exploration was conducted on the changes of the characteristic peaks corresponding to the characteristic elements that are contained in the topcoat, primer, and substrate with different layers of a laser action, in combination with analysis of microscopic morphology, composition, and depth of laser multi-pulse pits. The results show that the appearance and increase of the characteristic peak intensity of the Ca I at the wavelength of 422.7 nm can be regarded as the basis for the complete removal of the topcoat; the decrease or disappearance of the characteristic peak intensity can be regarded as the basis for the complete removal of the primer. Al I spectrum at the wavelength of 394.5 nm and 396.2 nm can be adopted to characterize the degree of damage to the aluminum alloy substrate. The feasibility and accuracy of the LIBS technology for the laser selective paint removal process and effect monitoring of aircraft skin were verified. Demonstrating that under the premise of not damaging the substrate, laser-based layered controlled paint removal (LLCPR) from aircraft skin can be achieved by monitoring the spectrum and composition change law of specified wavelength position corresponding tothe characteristic elements that are contained in the specific paint layer.