Research Data for the Publication: Generalization of LSTM and CNN Autoencoders for Anomaly Detection Across Orthogonal and Longitudinal Turning

Wu, Ya-JingYa-JingWu2026-04-072026-04-072026-04-07https://hdl.handle.net/11420/62446The dataset consists of several turning tests and is supplementary to the paper 'Generalization of LSTM and CNN Autoencoders for Anomaly Detection Across Orthogonal and Longitudinal Turning'. The experiments cover two datasets by Hamburg University of Technology and TU Dortmund University. The experiments include cutting edges of various indexable inserts, each of which was used with constant process parameters until failure. The three-axis force data is available as in-situ online measurements.enhttps://creativecommons.org/publicdomain/mark/1.0/TurningIndexable insertsIn-Situ MeasurementTechnology::670: ManufacturingResearch Data for the Publication: Generalization of LSTM and CNN Autoencoders for Anomaly Detection Across Orthogonal and Longitudinal TurningDatasethttps://doi.org/10.15480/882.1692310.15480/882.16923Zemke, JensJensZemkeDege, Jan HendrikJan HendrikDegeSchibsdat, SebastianSebastianSchibsdatVolke, PascalPascalVolkeWu, Ya-JingYa-JingWuKopp, JustinJustinKopp