Application of New Technologies for PSD Data Acquisition

Any organization that subjects its activities to a continuous improvement methodology, aiming to optimize their processes and services, must be able to adequately measure the results of the implemented changes to pursue better outcomes. This is no different for mining companies. When it comes to blasting, an accurate fragmentation analysis can correlate blast design and rock mass parameters to particle size distribution, enabling us to further analyze the correspondence of specific design patterns, applied to specific rock mass properties and the result in measured fragmentation indicators. Over time, many tools were developed for us to obtain PSD data, albeit each of them had their own shortcomings. The first ones to be developed involved photographing the muck pile including a scale object, uploading those photos to a PC, and using specialized software to analyze each one. As a result, analysts would get a PSD curve that served as reference for the performance of the blast. This method, which is still used, has major shortcomings. The most obvious one is that it is only able to capture a slice of the blast, which corresponds to the exposed section of the muck pile the analyst has access to, and even there its reach is limited to the areas that are safe for getting close enough for placing the scale, which are not many. Consequently, this is a very limited way to get a fragmentation performance assess for a blast. Currently, autonomous systems are capable of taking continuous pictures of the muck pile. Installed on a shovel, conveyor belt or crusher feed, these systems can take a continuous stream of pictures that are later analyzed automatically without the need of human intervention. These systems greatly increase the volume of data and, consequently, we have a PSD curve that is more representative of the blast performance. However, this technology still had issues when trying to sample front end loaders mining operations or getting results from underground blasting due to the inherent difficulties of these operations. New algorithms used for capturing and processing data for front end loaders can overcome the harsh environment of their operations and produce PSD data in high vibration environments and difficult mining angles. For underground mining, algorithms can be used to sample each truck exiting the mine, giving a reliable source of fragmentation analysis that can be traced back to their stope of origin. The development of this technology extends the existing system’s capabilities and helps us in our efforts to improve fragmentation results with each blast.