DAYPSCI: Event-based dataset for anomaly detection through fault injection in PLC-controlled industrial cyber-physical systems
Juan Vicente Martín-Fraile, Nuño Basurto Hornillos, Jesús Enrique Sierra-García, Álvaro Herrero · 2026
Read DAYPSCI: Event-based dataset for anomaly detection through fault injection in PLC-controlled industrial cyber-physical systems by Juan Vicente Martín-Fraile, Nuño Basurto Hornillos, Jesús Enrique Sierra-García, Álvaro Herrero (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13505426.txt.
Description
Martín-Fraile and three co-authors share a fault-test data set for plant gear nets in this twenty twenty-six paper. Plant nets run by coded chiefs must be watched for odd acts that hint at faults. Real fault data is rare, since plants can not be tripped for fun.
Inside, a test bed with true plant gear and a twin rig made the data in safe form. Logs note just the shifts in each gauge, with the gap time kept per shift. Faults were shot into sensors, movers, or both in set test runs. True tags came from the test plan and from live chief states as the runs went. Files hold both clean and fault runs, plus net tap tapes for each batch.
Catalog record
| CREATOR | Juan Vicente Martín-Fraile, Nuño Basurto Hornillos, Jesús Enrique Sierra-García, Álvaro Herrero |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 29 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |