Corrosion of carbon steel under mineral wool insulation was studied using the electrochemical current noise (ECN) method. Intensities of corrosion were validated using gravimetry, and the form of corrosion confirmed using optical microscopy. The standard deviation of the current noise signal agreed with weight loss results and was demonstrated as a reliable indicator of the degree of corrosion under mineral wool insulation. Recurrence quantification analysis was used to extract feature variables from ECN signals, which were later used to develop a random forest model to identify the type of corrosion, i.e., uniform or localised corrosion. The trained model was successfully applied to predict the extent of localised corrosion associated with mineral wool insulation.

利用电化学电流噪声（ECN）方法研究了碳纤维在矿棉绝缘下的腐蚀。使用重量分析法验证腐蚀强度，并使用光学显微镜确认腐蚀形式。当前噪声信号的标准偏差与减重结果一致，并被证明是矿棉绝缘下腐蚀程度的可靠指标。递归定量分析用于从ECN信号中提取特征变量，随后将其用于开发随机森林模型以识别腐蚀的类型，即均匀腐蚀或局部腐蚀。训练有素的模型已成功应用于预测与矿棉绝缘相关的局部腐蚀程度。