Research on a belt roller fault diagnosis method based on adaptive band-time KAN
Zhiyong Yang, Guangxu Luo, Guilin Hu, Jun Wang, Hongyu Zhang, Fucheng Yang, Lei Li, Wenhan Zhao · 2026
Read Research on a belt roller fault diagnosis method based on adaptive band-time KAN by Zhiyong Yang, Guangxu Luo, Guilin Hu, Jun Wang, Hongyu Zhang, Fucheng Yang, Lei Li, Wenhan Zhao (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/PMC13503824.txt.
Description
Zhiyong Yang and seven colleagues build a system to spot faults in belt conveyor rollers, in a 2026 paper. Rollers carry heavy loads in harsh plants and fail often, which stops whole lines. Sound and shake data hold clues, but past smart tools read the signals too coarsely and adapted poorly.
Their system first reshapes the sound spectrum to sharpen the bands where faults speak loudest. A time-aware network then tracks patterns across long spans. A special layer with flexible curve functions reads tangled links between tones. Under real plant conditions the system reached fault accuracy above 81 percent. The authors say the design suits live plant use where loads and speeds shift.
Catalog record
| CREATOR | Zhiyong Yang, Guangxu Luo, Guilin Hu, Jun Wang, Hongyu Zhang, Fucheng Yang, Lei Li, Wenhan Zhao |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 46912 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |