Machine performance and Acoustic fingerprints of cutting and drilling

‘It is always dark ahead of the pick!’ This centuries-old miners’ expression reveals the still persisting uncertainty about rock properties during exploration and extraction processes. It is still difficult to predict what a drill rig or a cutting machine will encounter during operation.

Therefore, during the RealTime Mining project different sensors or sensor combinations were tested during cutting and drilling processes to a) depict the machine performance of the machine at any time and b) use sensor information to delineate mechanical rock properties during the process.

One of the most important rock properties for drilling and cutting is rock strength. Increasing rock strength during an extraction process leads to increasing forces that are needed to break a certain amount of rock. Hence, e.g. measuring the torque of a drill string or the cutting forces can be an indicator on rock resistance or rock strength. Of equal importance is the characteristic rock breakage behavior which can be classified by the use of ‘acoustic’ sensors. Different rock properties have different characteristic fractures resulting from the drilling or cutting tool. These fractures can be translated into audible and also inaudible acoustic waves that propagate through the machine body and can be gathered on the machine by piezo-electric sensors. The interpretation of these signals could lead to a material classification already during the extraction process.

Over the course of the project, several tests with different sensor technologies have been conducted in a laboratory environment as well in field tests. The most promising results were presented in an article published in the conference proceedings of the Conference on Innovation on Raw Materials Extraction in Amsterdam 2017.

RWTH Publications Record

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s