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Artificial intelligence to track excavator operations

The company Zyfra has developed an automated system to monitor the condition of excavator bucket teeth based on the machine vision BucketControl system. The system is designed to detect the presence or absence of excavator bucket crowns quickly and features functions to alert the operator to the excavator if a crown is lost or ceases to work. This is an application developed jointly by the AI and Mining divisions of Zyfra.

The on-board controller acquires images from the camera, processes them using internal software, analyzes them and sends a signal to the operator if a crown is lost or ceases to work. The wear of the tooth is also assessed, and when a critical value is reached, a notification is sent to the dispatcher. This data is transmitted to the server in real time.

“With the help of machine vision, you can locate a broken tooth immediately and prevent it from getting into the crushing compartment, whose breakdown threatens the company with a loss of up to 200 000 dollars. When mining ore, a broken tooth may cause damage to the bucket, which would entail additional damage worth several million rubles. Our BucketControl system will ensure a cost reduction of 90% when finding a broken tooth,” said Alexander Smolensky, Business Development Director of Zyfra.

The automated system to monitor excavator bucket teeth has been further developed to produce Fragmentation – an automated system designed to determine the granulometric composition of crushed rock. This application measures continuously the size of the pieces of rock in the excavator bucket. Correlating that size with the location coordinates yields a performance map of rock which measures the efficiency of rock blasting to balance the cost of blasting against the quarry output.

“In contrast to images taken after the blast, the entire depth of exposed rock is analyzed. That enables us to increase excavator productivity by up to 3%, minimizes the chances of oversized pieces hitting the crushing compartment, makes it possible to track the quality of blasting operations and ultimately increase rock removal by up to 10%. Using the system to analyze previous blasting operations will also help determine the amount of explosives required for future blast works,” added Smolensky.

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