Name
Title | ||
|---|---|---|
Identification and Analysis of Tool Wear Signal in CNC Machine Tool Based on Chaos Method |
Abstract | ||
|---|---|---|
In this paper, the tooth-tool in CNC machine tool is taken as the research object, and the time series of tool vibration signal is analyzed based on chaos theory, which verifies the effectiveness of using chaos theory to analyze vibration signal. Firstly, the time series of tool vibration signals is obtained by the experimental system, and the phase space of the obtained experimental data is reconstructed to determine the best embedding dimension m and delay time τ of the time series. Then, combined with the best embedding dimension and delay time, the phase diagram is constructed and the maximum Lyapunov exponent of the time series is calculated by using the small data volume method, thus verifying that the passive intermodulation power time series has chaotic characteristics qualitatively and quantitatively. On this basis, the vibration signal is analyzed by SE complexity, which shows that the greater the wear value, the greater the complexity of vibration signal. The chaos theory proposed in this paper provides a new idea for developing mechanical fault diagnosis technology and improving the performance of mechanical system. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICPHM51084.2021.9486525 | 2021 IEEE International Conference on Prognostics and Health Management (ICPHM) |
Keywords | DocType | ISBN |
CNC,chaos,Lyapunov exponent,Complexity | Conference | 978-1-6654-2996-2 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fu Haiyan | 1 | 1 | 0.69 |
| Lei Tengfei | 2 | 1 | 0.69 |
| Xin Miaomiao | 3 | 1 | 0.35 |
| Cao Feng | 4 | 1 | 0.35 |
| Jin Minglei | 5 | 1 | 0.35 |
| Yan Tingyang | 6 | 1 | 0.69 |