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Autonomous Drones for Mining Applications

Drones are in regular use at many mine sites and have gone from being a novelty to a just another piece of production equipment. Most mines have them now, and almost every operation initially uses them for stockpile surveying, to which they are ideally suited. 

While the value of drones is no longer in dispute, they are, to a certain extent, victims of their own success. As they continue to demonstrate their value, more and more groups on the site want to use them. 

Current drone operations need a pilot, someone to take the drone out, unpack it, launch it, watch it fly, land it, change the battery if more work needs to be done, relaunch, etc. As more and more groups at the mine site see the value of drones, availability of pilots quickly becomes a limitation to flying. 

But what if you did not need a pilot? What if the drone was truly autonomous? I will describe two use cases for autonomous drones, where they can be used to automate routine flying, leaving the pilots available for other, less routine missions.

A good example of an affordable autonomous drone system is the skymineUAV autonomous drone platform for mining, powered by Asylon’s DroneCore. This autonomous drone sits in a weatherproof box, placed to provide easy access to the area requiring regular flying. The system includes a weather station, so the drone can check that it is safe to fly before launching. 

If weather conditions are within acceptable ranges, the box opens, the drone launches, flies the mission and returns to the box. The box has 12 batteries onboard, so when the drone lands, the drained battery is removed and placed in a charger, and a fully charged battery is placed in the drone. At this point the drone can take off again if there are other missions to complete, or the box will close until the next scheduled mission. Battery swapping takes as little as 3 minutes, so you can have the drone flying missions for 50 minutes of every hour. The system also has the capability to change the payload, further enhancing its flexibility.

This article will focus on two use cases for an autonomous drone system – short term stockpiles and tailings dam monitoring.

Short Term Stockpiles

The first use case for an autonomous drone is short-term stockpile volumes. For many stockpiles, a weekly or even daily flight is all that is necessary and can be easily done by a pilot. But what happens when you want volumes more often? 

For example, assume you have a series of small, short term stockpiles that feed a crusher. The size and composition of these stockpiles changes regularly throughout the day and night, as new material is dumped on the stockpiles and existing stockpile material is transported to the crusher. Ideally the stockpile volumes would be updated every 6 hours, providing the operation with the detailed information they need to optimize the ore processing. As hauling and feeding the crusher takes place 24 hours a day, volume updates will be needed 24 hours a day. This frequency of updates, night and day, means using a pilot to manage the flights is unrealistic.

But with an autonomous system, there is no need for a pilot. The drone box would be placed near the stockpile, weather permitting the flights would take place every 6 hours, and the data would be collected, uploaded to a cloud processing solution, such as Propeller or Delair.ai, and the processed data would be sent to the mine. 

Once this system is set up, the data collection and processing are automatic, and the data appears in the online portal when it is needed. This frees the experts on the site from the drudgery of data collection and processing and allows them to focus on analysis and interpretation. 

This solution also frees up the site pilots to perform other, less routine flying, meaning the site can do more with their existing drones. In addition, as the stockpile monitoring only needs to happen every 6 hours, and the drone box has a large supply of batteries, the autonomous drone can be programmed to perform other tasks, such as haul road monitoring. Autonomously, of course.

In addition, by incorporating truck load data from the Dispatch system, and controlling where rock is dumped on, and loaded from the stockpiles, it is possible to know in some detail the exact composition – grade, mineralogy, etc. – of the rock on the stockpile. Knowing how the makeup of the stockpile changes every 6 hours, or even every three hours, as some have suggested, gives the mining operation unprecedented control over what goes to the crusher and will allow fine-tuning of the process plant to match the current feed. 

Over time a 3D model of the stockpile will be developed, which will provide very tight control over what is being sent to the crusher, allowing the process team to request specific rock types be prioritized to optimize reagent use and recovery.

Tailings Dam Monitoring

Tailings dams are an unfortunate, but necessary feature of mining operations. And sometimes they fail. In 2019 alone there have been 4 significant failures that have resulted in close to 300 deaths, immense property damage, and environmental devastation. Anything can help prevent further disasters deserves close attention. 

Monitoring tailings dams is a complex process that uses are variety of technologies, including remote monitoring via satellite, fixed cameras, various stress sensors and manually digging pits and trenches to check for seepage and leaks. An autonomous drone system can provide a useful complement to existing methods, with the added advantage of being automatic and flexible.

The autonomous drone system provides a fast, easy way to address two of the common causes of tailings dam failures:

Seepage and Leaking Pipes

Typically attempts are made to detect seepage problems using surface observation and sometimes through the digging of pits and application of moisture meters and other geotechnical equipment. These are manual solutions that are slow, expensive, difficult and are limited to safely accessible areas of the dam. 

This is where drones can help. Three things are needed for a fast, easy, safe and inexpensive drone monitoring solution: 

In this use case an autonomous drone-in-a-box that would be located near the tailings dam. It would be scheduled to fly the entire perimeter of the dam at whatever frequency is necessary, using the thermal camera to collect imagery. In the case of large tailing facilities, where a single flight may not be enough to cover the whole dam, the battery swapping capability of the system will allow the drone to return to base, get a new battery, and finish the survey. 

Once the survey is done, the imagery would be uploaded to the selected cloud processing facility and processed to detect the thermal contrasts that would indicate seepage or a leaking pipe. If detected, an alert would be sent to the appropriate people at the mine, along with the imagery. Figure 4, taken from an article in the June 13, 2018 edition of PositionIT magazine, shows the expected contrast between tailings dam seepage and the surrounding rock.  

The drone would also collect RGB imagery of the dam that would be used to create a 3D DEM of the dam. This would be stored in the cloud and the data from each flight could be compared to that from previous flights to detect any changes in the size, shape or structure of the dam.

Poor Management and Maintenance

The United Nations Environmental Program published a report in 2017 titled Mine Tailings Storage: Safety is No Accident. One of their conclusions was:

“In the literature on the topic, the majority of the tailings storage-facility failures discussed can be attributed to a few factors – in particular, the lack of management continuity and inadequate resourcing (especially financial) for the facility. In cases of failure triggered by mechanisms such as overtopping or piping, inadequate management has occurred over a period of time. The failure may ultimately have been triggered by a particular mechanism, but the tailings storage facility should never have been permitted to reach a point where it was susceptible to such a triggering mechanism in the first place.” 

The solution proposed above addresses this management and maintenance issue by automating the surveys, data processing and preliminary analysis. Since the monitoring and data processing happen automatically, it is much less likely to be skipped or forgotten, addressing both the lack of resources and continuity issues.

The proposed solution also provides a high level of flexibility. Surveys can be scheduled for whatever frequency is necessary, and this can be changed to accommodate local conditions.  

For example, weather and seismic events can be contributing factors to tailings dam failure. Unusual levels of runoff, snowmelt or rainfall can overstress a dam. With an autonomous drone you can easily program it to fly more frequently when these conditions arise, detecting incipient problems before they become serious. If the typical monitoring flight happens every week, but there has been a recent seismic or significant rainfall event, the frequency of flights can be increased to as often as every hour. 

It is the autonomous nature of this solution that makes it so compelling. Once it is set up, there is no other human involvement necessary. The flights, data upload, data processing and communication of results all happen automatically. Once they are happy that the data collection and processing is being done correctly, all the mine cares about is the data. With the autonomous drone solution they will receive the data automatically and can focus their time and expertise on detailed analysis and interpretation.