Online Monitoring of Hot Die Forging Processes Using Acoustic Emission (Part-I)
|Autoren:||Elgaly, I.; Behrens, B.- A.|
|Veröffentlichung:||International Journal of Acoustic Emission, Vol. 26, Jan.- Dez. 2008|
Online process monitoring systems have been used on forming machines such as forging hammers or multi-stage presses for a good number of years. These systems typically measure forming forces, punch displacement or frame strains and compare them to learned target values trying to infer about the tooling or the product condition. In spite of the reached measurement accuracy, these methods are not physically capable or not sensitive enough to express many types of the tooling failures or product damage. Over the last few decades, acoustic emission (AE) has proved its strength and reliability as an online monitoring technique, and demonstrated a high degree of confidence in characterizing various phenomena related to material deformation, phase transformation as well as crack initiation and propagation at various scales.
In this paper, the concept of a forging support system, based on AE as an online monitoring and analysis technique, is introduced. The proposed support system relies on a damage and failure diagnosis module. This diagnosis module combines different AE analysis and clustering and pattern recognition methods to infer about different types of damage or failures taking place during the forging operation. AE patterns recorded from error-free forgings produced on faultless undamaged dies serve as a reference for the comparison. In addition, patterns generated by samples with pre-induced damages or artificial defects, or AE patterns collected during the deformation under predefined faulty machine or process settings are used as reference to assist in analyzing the complex patterns, which will be obtained during real forging processes.
Some preliminary results obtained during upsetting of magnesium-alloy specimens are presented. Three different geometries have been machined from AZ31 and AZ80 extruded bars. The specimens were upset at three constant levels of strain rates and at three different temperatures. The results reflect the influences of alloy composition, forming speed, and temperature on the obtained AE signals. In addition, different AE patterns could be correlated to the sequence of deformation and the evolution of damage based on the geometry of the specimen and the induced stress states.