|InterJournal Complex Systems, 938
|Manuscript Number: |
Submission Date: 2004
|Complex Nonlinear stochastic dynamics of precision grinding operations: Implications for health monitoring and control|
Precision grinding is an important manufacturing process in aerospace industries as many of the industries' core technologies such as air bearings and electromechanical systems rely on this process. Owing to the distributed thermomechanics and deformation mechanisms coupled with the complex interactions between these mechanisms and the dynamics of various components of the grinding machine, controlling the process performance is challenging. Aerospace industries call this process a "black magic." Our research has characterized the nonlinear stochastic dynamics underlying the various behaviors of the process from sensor signals measuring structural vibrations and acoustic emission. We have derived a novel appraoch to reconstruct a nonlinear stochastic differential equation model from a multitude of machine structure-mounted vibration sensor signals. The model can capture the various observed behaviors of the process, and it was computationally tractable for real-time control. A 62% improvement in the control of performance was achieved by tracking features extracted based on this model.
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