Blasthole Scanning and Internal Geometry Measurement Underground
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies struggle to accurately detect and examine blastholes in a rock face, particularly in underground mining, due to internal collapse or directional deviations, and require geolocation for effective explosive calculation, which is not feasible in all mining environments.
Innovation Solution
An automated method using 2D LiDAR sensors and ToF cameras for scanning and detecting blastholes, combined with a sensorized probe for internal geometry measurement, allowing for precise detection and alignment without geolocation, and incorporating visible spectrum imaging for enhanced detection of distant holes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If LiDAR sensors are used to scan and detect blastholes, then detection capability is improved, but internal collapse and directional deviations cannot be accurately examined
Solution Approach 1:
A sensorized probe is introduced as an intermediary device to examine the internal geometry of blastholes. The probe includes sensors (accelerometer, gyroscope, depth sensor) that directly measure internal characteristics such as collapse, deviations, and actual hole geometry, providing accurate data that external LiDAR sensors cannot obtain.
Solution Approach 2:
The solution transitions from external 2D LiDAR scanning to internal 3D measurement by inserting a probe inside the blasthole. This dimensional transition allows comprehensive examination of internal geometry, including collapse and directional deviations, by measuring from within the hole rather than from the external rock face.
2Measurement precision
If geolocation data is used for explosive calculation, then positioning accuracy is improved, but applicability in underground mining environments deteriorates
Solution Approach 1:
The system uses self-contained sensors (accelerometer, gyroscope, depth sensor) on the probe to autonomously determine blasthole characteristics without relying on external geolocation systems. The sensors self-measure internal geometry and orientation, making the system independent of GPS or other external positioning infrastructure.
Solution Approach 2:
The patent replaces geolocation-based positioning systems with an inertial measurement system using accelerometers and gyroscopes. This substitution allows accurate measurement of blasthole orientation and position through mechanical sensing of acceleration and rotation, rather than relying on satellite-based geolocation that doesn't work underground.
3Area of stationary object
If 2D LiDAR sensors are used for scanning, then detection coverage is improved, but point density and resolution deteriorate
Solution Approach 1:
The scanning process is segmented into two distinct phases: a first scan with lower point density for broad coverage and blasthole detection, and a second scan with higher point density for precise geometric measurement. This segmentation allows optimization of point density for different operational requirements without compromising overall system effectiveness.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate detection and alignment of blastholes, facilitating precise explosive calculation and operation in underground environments, while overcoming issues of internal collapse and directional deviations.
Implementation Method 1
The method uses as information a record of scans from light detection and ranging (LiDAR) sensors - preferably 2D LiDAR sensors, which measure the distance by using a laser mounted on a motor and additionally employing a time-of-flight (ToF) camera for phase detection
Implementation Method 2
employing a time-of-flight (ToF) camera for phase detection
Data Source
Figure 1~2
Figure 3~4
Figure 5
AI summary
The present invention relates to an automated method and system for detecting perforations in a rock face that detects perforations in a perforated face in order to position instruments relative to each hole. The method uses a record of light detection and ranging (LiDAR) sensor scans as information, as well as a time-of-flight (ToF) camera. The method requires complementing and comparing a set of perforation candidates obtained from scans with the information from a perforation plan executed on the rock face in order to define a set of perforations.