Laser scanner use in predictive maintenance at mining

Mining machines are subject to considerable wear and tear. Predictive maintenance is therefore important to avoid unplanned machine downtime.

Mining is becoming increasingly important in the age of growing demand for ores and rare earths. It is estimated that an increase of 7,000% in the yield of copper ore alone will be required to achieve the goals of electromobility.

Problem: Machine failure

As machines in opencast mining are subject to heavy wear and tear, unplanned downtimes mean considerable costs due to long waiting times for spare parts procurement and repairs.  Predictive maintenance can be used to minimize downtimes due to unplanned repairs. This involves constantly measuring the most important wearing parts and calculating the degree of wear. This data can be used to calculate and plan a maintenance date. Spare parts and maintenance personnel are then available in a coordinated process.

New solution: 3D laser scanners measure wear

Example 1: Conveyor belts

In large opencast mines, conveyor belts with a length of 10-20 km are sometimes used. These conveyor belts are made of vulcanized rubber with steel inserts. Some of the material being conveyed consists of pointed and sharp-edged stones that fall from a tower onto the conveyor belt at a certain height. Sometimes these stones cut through the conveyor belt, causing a crack. If this crack is not noticed and repaired, it can expand due to the forces acting on the belt and eventually cut the belt completely open. As the plant continues to run for a while, the rock then builds up into a mountain and the plant has to come to an unplanned standstill. This often means that the downstream processing operations also come to a standstill. Such an accident is associated with high costs.

SOLUTION: Inline monitoring of the conveyor belts with QuellTech line laser

3D laser line sensors from QuellTech are used for the non-contact detection of cracks. The sensors project a laser line perpendicular to the direction of movement of the conveyor belt onto the underside at the point where the rock falls onto the belt. If a stone cuts through the belt, this surface change is detected in 3D by the sensor and recorded. Depending on the size of the defect, an alarm is triggered and, if necessary, the system is shut down in a controlled manner and repaired immediately. At another point, the surface of the conveyor belt is measured for wear using QuellTech 3D laser line sensors. As the belt is running at this point without conveyed goods and has been cleaned, the belt thickness and gradual wear can be measured at individual points. As the fault location is also recorded, a repair can be carried out precisely at the points found as part of predictive maintenance. This allows the service life of a conveyor belt to be extended in a controlled manner. The use of highly robust conveyor belts, which are sometimes 10 times more expensive, can thus be avoided.

New solution: 3D laser scanners measure wear

Example 2: Wear detection in mineral processing

In mineral processing, heavy machines are used to crush and grind rocks and raw materials to prepare the extraction of the valuable materials and minerals. A significant opportunity to reduce energy and emissions sits within comminution, which is the process that turns big rocks into small particles. This process is responsible for at least one-third of an average mine’s energy use and CO2 emissions and globally consumes around 3% of the world’s electrical power. One of these machines in the flowsheet are so called high pressure grinding rollers (HPGRs). HPGRs are commonly found in the tertiary or quaternary processing plant of mining operations. Essentially the HPGR creates micro cracks and fractures into a bed of particles which move within the gap between two counter-rotating tyres. HPGRs enables the user to reduce particle sizes from >85 mm down to a micron-sized product. During the grinding process, the tyres wearing down considerably over time.

SOLUTION: Inline monitoring of roller surface with QuellTech line laser

Identification of the wear level of HPGR tyres is important for e.g. planning of tyre replacements. Besides that, identification of localized damage is important to prevent it from escalating into a catastrophic failure of the tyre before its expected wear life. Tyre wear measurement is currently only possible by manual measurements while the machine is not operating. Localized damage often remains undetected until a catastrophic failure occurs. The surface of the tyres has to be checked and measured regularly to calculate the lifetime and to estimate the exchange date of the tyres.
QuellTech 3D line lasers are used in this application to continuously monitor the wear condition of the rollers. For this purpose, a laser line is projected onto the roller surface by the sensor. Using the triangulation method, the diffuse reflection of this laser line is converted into 3D information on an image acquisition chip. This generates a three-dimensional point cloud of the entire roller surface. This point cloud enables a statement to be made on the wear condition and a calculation of the further prognosis until the roller is replaced.

Advantages of the QuellTech solution for mining

  • 3D display provides an overview of the wear condition over the entire surface
  • Continuous checking of the wear condition allows for forward-looking planning.
  • Quality assurance through early alarm in the event of serious faults, an emergency system stop prevents serious damage
  • Precise localization of defects enables fast repairs, eliminating time-consuming searches
  • Higher productivity thanks to less unplanned downtime
  • Cost savings through predictive maintenance

Can we help you with your measurement task?

We would like to help you to evaluate your specific measurement task.
With a free first test measurement of your application, we can give an early assessment of the feasibility. Do not hesitate to contact us for more information or to make an appointment for a consultation. Please talk to us!

Stefan Ringwald
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