CORDIS provides links to public deliverables and publications of HORIZON projects.
Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .
Exploitable results
A simple model has been developed to explain the acoustic emission (AE) generated by friction processes produced during cutting which are the main sources of AE. The model describes the interaction between the rough surfaces of two solid materials which slide against each other. Each interaction generates one AE event. The average signal level depends on relative velocity, pressure, surface roughness, surface area of interaction and hardness of the materials. Since no commercial AE system exists for capturing and analysis of continuous AE which fulfils the requirements of on-line tool monitoring, equipment was specially designed and developed for that purpose (laboratory prototype). It analyses the average signal level (ASL) and the peak amplitude of AE within a selectable integration time. Burst signals from chip impact on the tool and from chip breakage which interfere with the continuous AE can be separated from the continuous AE. This feature is crucial for tool wear monitoring with respect to turning since most turning processes are accompanied by chip formation and breakage. The equipment has been successfully tested with artificial AE signals and with real signals from grinding tests. The equipment consists of a small front-end unit and a board to be inserted into a personal computer. The software for data capture, storage and evaluation is implemented in a Windows graphical software. The AE system is intended for use not only in tool wear monitoring but also for monitoring of all processes where ultrasound is generated by friction (the diverse finishing processes, monitoring of bearings and gaskets in pumps).
To verify the model, friction investigations with accompanying AE measurements have been performed by tribometer and grinding experiments. It has been found that the model qualitatively fits the experimental results, thus the principal assumptions of the model are justified.
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