Abstract
This paper presents a new online machining process monitoring system based on the PXI hardware platform and the LabVIEW software platform. The whole system is composed of the following interconnected packages: sensing, triggering, data acquisition, characterisation, condition monitoring and feature extraction packages. Several signal processing methods, namely, cross-correlation, resample, short-time Fourier transform (STFT) and statistical process control, are developed to extract the features of tool malfunctions and construct the thresholds of malfunction-free zones. Experimental results show that the developed online process monitoring system is efficient for acquiring, analysing and presenting sensory signals simultaneously, while the developed signal processing techniques are effective for detecting tool wear and constructing thresholds for tool-malfunction-free zones. Additionally, a sensitivity analysis of the signals acquired from alternative sensors versus those collected from a dedicated platform dynamometer has been carried out. This enables the evaluation of the possibility to employ alternative sensing techniques in an industrial environment.
| Original language | English |
|---|---|
| Pages (from-to) | 34-46 |
| Number of pages | 13 |
| Journal | International Journal of Advanced Manufacturing Technology |
| Volume | 34 |
| Issue number | 1-2 |
| DOIs | |
| Publication status | Published - Aug 2007 |
| Externally published | Yes |
Keywords
- Broaching
- Feature extraction
- Process monitoring
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- Mechanical Engineering
- Computer Science Applications
- Industrial and Manufacturing Engineering