Non-destructive inspection for additive manufacturing lattice structures using a convolutional neural network and electrical resistance analysis

This dataset contains the raw and processed data supporting the study "Non-destructive inspection for additive manufacturing lattice structures using a convolutional neural network and electrical resistance analysis." The work develops a low-cost, rapid non-destructive inspection method that identifies internal damage locations in conductive resin lattice structures fabricated by additive manufacturing, based on changes in surface temperature distribution when an electric current is applied.本数据集包含支撑题为《基于卷积神经网络（Convolutional Neural Network）与电阻分析（Electrical Resistance Analysis）的增材制造（Additive Manufacturing）晶格结构无损检测》的研究的原始数据与处理后数据。该研究开发了一种低成本、快速的无损检测方法，通过分析通电状态下导电树脂晶格结构的表面温度分布变化，实现对增材制造制备的导电树脂晶格结构内部损伤位置的识别。