Blast Reconciliation Using AI and Laser Scanning
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Solution Overview
Problem
Current methods for determining raw material extraction in underground mining, such as the 'survey' and 'spot' techniques, face challenges in accurately and efficiently reconciling differences and providing real-time data, leading to inaccuracies and losses in material handling.
Innovation Solution
A system utilizing a digital terrain view on a mobility platform with handheld devices for real-time data capture and transmission, combined with artificial intelligence and machine learning models for near real-time blast reconciliation, enabling accurate tonnage measurement and prediction of material yield.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional survey or spot techniques are used to determine raw material extraction, then equipment simplicity is maintained, but measurement precision and reconciliation accuracy deteriorate
Solution Approach 1:
The system segments the measurement process into distinct phases: pre-blast survey, post-blast survey, and reconciliation processing. Each phase uses specialized devices (laser scanners, handheld computers) to capture specific data sets, which are then processed separately through machine learning models to determine final tonnage measurements.
Solution Approach 2:
The system introduces an intermediary reconciliation process that acts as a mediator between pre-blast and post-blast survey data. This intermediary layer uses machine learning models and digital terrain views to process raw survey data, reconcile differences, and produce accurate tonnage measurements without requiring direct physical measurement of extracted material.
2Productivity
If traditional survey techniques are used for material extraction determination, then equipment simplicity is maintained, but productivity and real-time data provision deteriorate
Solution Approach 1:
The system performs preliminary actions by conducting pre-blast surveys and creating digital terrain views before the blasting operation occurs. This advance data collection and processing setup enables rapid post-blast reconciliation, as the baseline data is already captured and stored, eliminating the need for time-consuming post-blast survey setup.
Solution Approach 2:
The system maintains continuity of useful action through continuous data collection and processing. Pre-blast and post-blast surveys are conducted as continuous operations with automated data transfer and processing pipelines. The machine learning models continuously process survey data to provide real-time tonnage measurements, eliminating idle time between survey phases.
3Measurement precision
If traditional spot technique with vehicle counting is used, then equipment simplicity is maintained, but measurement precision and material handling accuracy deteriorate
Solution Approach 1:
The system replaces mechanical counting methods (vehicle spot checks) with automated laser scanning and digital terrain view technology. The laser scanners mechanically capture precise three-dimensional data of the mine face and extracted material volumes, which are then processed by machine learning models to determine accurate tonnage measurements, eliminating the need for manual vehicle counting and estimation.
Data Source
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AI summary
According to an example, with respect to blast reconciliation for mines, pre blast measurement data and post blast measurement data associated with a blasting operation for a mining site may be ascertained from a pre and post blast measurer. A blast reconciliation model may be generated using existing pre blast measurement data and existing post blast measurement data, and used to analyze the ascertained pre blast measurement data and the ascertained post blast measurement data. Based on the analysis of the ascertained pre blast measurement data and the ascertained post blast measurement data, a blast material yield for the mining site may be determined as a result of the blasting operation. An alert indicative of the blast material yield may be generated.