Rock Mass Hardness Estimation for Adaptive Blasting Parameters
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current blasting practices in mining face inefficiencies due to non-uniform fragmentation resulting from varying rock mass hardness, as they rely on sparse geological survey data and heuristic methods, leading to inconsistent explosive energy application and suboptimal blast design.
Innovation Solution
A system and method for estimating rock mass hardness during operation using live drilling data to update a rock mass model, calculate a drilling index, and set blasting parameters dynamically, incorporating feedback from secondary industrial machines to improve fragmentation consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If sparse geological survey data and heuristic methods are used for blasting design, then the process is simple and quick, but the fragmentation uniformity is poor due to inaccurate rock mass property knowledge
Solution Approach 1:
The system performs preliminary drilling operations to collect rock mass property data before final blasting. By drilling test holes and measuring rock properties in advance, the system obtains accurate geological information that informs the blasting design, thereby improving fragmentation uniformity without requiring complex real-time monitoring during blasting itself.
Solution Approach 2:
The system uses drilling performance data and rock property measurements as feedback to continuously refine blasting design parameters. The drilling index calculated from measured rock properties provides feedback that adjusts explosive energy distribution, ensuring uniform fragmentation while maintaining a manageable process complexity through automated calculations.
2Measurement precision
If core sampling is used to obtain geological survey data, then rock mass properties can be measured, but the resolution is limited by the cost and time required
Solution Approach 1:
The drilling operation itself serves dual purposes: it performs the primary function of creating blast holes while simultaneously collecting rock mass property data through measurements taken during drilling. This self-service approach eliminates the need for separate, time-consuming core sampling operations, achieving both drilling objectives and geological characterization in a single process.
Solution Approach 2:
The system continuously collects rock mass property data throughout the drilling process rather than taking discrete samples. By continuously measuring drilling parameters and rock properties as the drill progresses, the system maintains continuous useful action, obtaining comprehensive geological information without interrupting the drilling workflow for separate sampling operations.
3Manufacturing precision
If blasting is planned based on average material properties across a large rock mass, then the planning process is simplified, but variations in lithology result in variability in achieved fragmentation
Solution Approach 1:
The system applies local quality by tailoring blasting parameters to specific locations within the rock mass based on locally measured rock properties. Instead of using uniform average properties, the system calculates location-specific drilling indices and adjusts explosive energy distribution accordingly, ensuring each area receives appropriate energy for its specific lithology, thereby achieving consistent fragmentation across varied rock conditions.
Solution Approach 2:
The system segments the rock mass into zones with similar rock properties based on drilling data, allowing differentiated blasting design for each zone. By dividing the blast area into segments with homogeneous characteristics and applying optimized parameters to each segment, the system achieves uniform fragmentation across the entire mass while maintaining operational simplicity through automated segmentation and parameter assignment.
Data Source
AI summary
Systems and methods for estimating a hardness of a rock mass during operation of an industrial machine. One system includes an electronic processor configured to receive a rock mass model and to receive live drilling data from the industrial machine. The electronic processor is also configured to update the rock mass model based on the live drilling data and to estimate a drilling index for a hole based on the updated rock mass model. After estimating a drilling index for the hole, the electronic processor is also configured to set a blasting parameter for the hole based on the estimated drilling index.