System and method including neural net for tool break detection
US5579232A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Mar 9, 1995 |
| Grant date | Nov 26, 1996 |
| Priority date | — |
| Expiry date | Mar 9, 2015 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG05B2219/37245
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
A system and method for monitoring vibrations of a cutting tool uses a neural network for classifying signal features as break or non-break or, in another embodiment, as non-break or abnormal. A vibration signal is produced by an accelerometer, positioned to sense vibrations at the tool-workpiece interface. The signal is pre-processed to extract low frequency machining noise and detect the energy in a higher frequency band. The signal is then sampled and segments of the digitized signals are processed by digital logic into feature vectors for input to a trained neural net having two output nodes for classification. The use of a neural net provides performance improvement and economies over previously known heuristic methods of signal analysis.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.