The behavior of any grinding process is very dependent on the tool performance. In addition to changes in the grinding wheel surface during the grinding process, the ideal conditions may be lost from its own manufacturing process. Thus, the grinding results are directly related to the topographical conditions of the grinding wheel surface. Once these conditions are changed, the dressing operation becomes crucial to the process. The objective of this work is the study of the single point dresser wear through the digital processing of raw vibration signals and neural models for estimation and prediction of wear. The analysis conditions of wear will be carried out by measuring the wear of the tip of the dresser of conventional grinding wheels. The expectation of this research is to provide results of correlation parameters of vibration signals with the wear of the dresser, frequency analyses as well as obtaining estimation and prediction models. Therefore, the work will contribute to useful tools for monitoring the dressing operation, and thus to optimize the grinding process.
News published in Agência FAPESP Newsletter about the scholarship: