CL2021003235A1 - Ore monitoring (divisional from application no. 202100547) - Google Patents
Ore monitoring (divisional from application no. 202100547)Info
- Publication number
- CL2021003235A1 CL2021003235A1 CL2021003235A CL2021003235A CL2021003235A1 CL 2021003235 A1 CL2021003235 A1 CL 2021003235A1 CL 2021003235 A CL2021003235 A CL 2021003235A CL 2021003235 A CL2021003235 A CL 2021003235A CL 2021003235 A1 CL2021003235 A1 CL 2021003235A1
- Authority
- CL
- Chile
- Prior art keywords
- ore
- image
- load
- transport vehicle
- data relating
- Prior art date
Links
- 238000012544 monitoring process Methods 0.000 title abstract 3
- 239000002245 particle Substances 0.000 abstract 2
- 238000010801 machine learning Methods 0.000 abstract 1
- 239000000463 material Substances 0.000 abstract 1
- 238000000034 method Methods 0.000 abstract 1
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/02—Investigating particle size or size distribution
- G01N15/0205—Investigating particle size or size distribution by optical means
- G01N15/0227—Investigating particle size or size distribution by optical means using imaging; using holography
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/24—Earth materials
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20081—Training; Learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Molecular Biology (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Analytical Chemistry (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Pathology (AREA)
- Immunology (AREA)
- Biochemistry (AREA)
- Quality & Reliability (AREA)
- Geometry (AREA)
- Food Science & Technology (AREA)
- Medicinal Chemistry (AREA)
- Remote Sensing (AREA)
- Geology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Environmental & Geological Engineering (AREA)
- Dispersion Chemistry (AREA)
- Image Processing (AREA)
- Image Analysis (AREA)
Abstract
Se describen sistemas y métodos para estimar la magnitud de una carga de mena, determinar la distribución del tamaño de partícula (PSD) de la mena, reconocer material extraño en las imágenes de la mena, monitorear la mena y monitorear el equipo de procesamiento de mineral. Se recibe una imagen de un vehículo de transporte de mena de un dispositivo de captura de imágenes. Los datos que se relacionan con una carga de mena en el vehículo de transporte de mena se detectan con un escáner. Se calcula una magnitud estimada de la carga de mena al acceder a los datos que se relacionan con la carga de mena, los datos de la imagen y los datos que se relacionan con el vehículo de transporte de mena. Se utiliza un módulo de aprendizaje de máquina para identificar una región de mena en una imagen de mena y reconocer las partículas de mena u objetos dentro de la imagen. Se calcula un valor PSD de la mena. Se genera un indicador que estima la condición del equipo de procesamiento de mineral al utilizar el valor PSD y al operar los parámetros.Systems and methods are described for estimating the magnitude of an ore load, determining the particle size distribution (PSD) of the ore, recognizing foreign material in ore images, monitoring the ore, and monitoring ore processing equipment. . An image of an ore transport vehicle is received from an image capture device. Data relating to an ore load on the ore transport vehicle is detected by a scanner. An estimated magnitude of the ore load is calculated by accessing data relating to the ore load, image data and data relating to the ore transport vehicle. A machine learning module is used to identify an ore region in an ore image and recognize the ore particles or objects within the image. A PSD value of the ore is calculated. An indicator is generated that estimates the condition of the ore processing equipment by using the PSD value and operating parameters.
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
ZA201806000 | 2018-09-07 |
Publications (1)
Publication Number | Publication Date |
---|---|
CL2021003235A1 true CL2021003235A1 (en) | 2022-08-26 |
Family
ID=69723056
Family Applications (3)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CL2021000547A CL2021000547A1 (en) | 2018-09-07 | 2021-03-05 | Ore monitoring |
CL2021003235A CL2021003235A1 (en) | 2018-09-07 | 2021-12-06 | Ore monitoring (divisional from application no. 202100547) |
CL2021003234A CL2021003234A1 (en) | 2018-09-07 | 2021-12-06 | Ore monitoring (divisional from application no. 202100547) |
Family Applications Before (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CL2021000547A CL2021000547A1 (en) | 2018-09-07 | 2021-03-05 | Ore monitoring |
Family Applications After (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CL2021003234A CL2021003234A1 (en) | 2018-09-07 | 2021-12-06 | Ore monitoring (divisional from application no. 202100547) |
Country Status (5)
Country | Link |
---|---|
AU (1) | AU2019335607A1 (en) |
BR (1) | BR112021004248A2 (en) |
CL (3) | CL2021000547A1 (en) |
PE (1) | PE20210695A1 (en) |
WO (1) | WO2020049517A1 (en) |
Families Citing this family (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP3965940B1 (en) | 2020-04-23 | 2023-08-16 | Gebr. Pfeiffer SE | Grinding method and apparatus with material entry detection |
AT523755A2 (en) * | 2020-05-13 | 2021-11-15 | Rubble Master Hmh Gmbh | Method for determining the grain size distribution in sections of a bulk material placed on a conveyor belt |
AT523806B1 (en) * | 2020-05-13 | 2022-09-15 | Rubble Master Hmh Gmbh | Process for cleaning off crushed grain in crushers |
CN111680268B (en) * | 2020-06-11 | 2023-05-23 | 重庆邮电大学 | Multi-granularity coal mine gas risk prediction method based on cloud model |
CN111812671A (en) * | 2020-06-24 | 2020-10-23 | 北京佳力诚义科技有限公司 | Artificial intelligence ore recognition device and method based on laser imaging |
CN112232449B (en) * | 2020-12-14 | 2021-04-27 | 浙江大华技术股份有限公司 | Neural network training method, electronic device, and storage medium |
CN112614139B (en) * | 2020-12-17 | 2022-09-16 | 武汉工程大学 | Conveyor belt ore briquette screening method based on depth map |
CN112785557A (en) * | 2020-12-31 | 2021-05-11 | 神华黄骅港务有限责任公司 | Belt material flow detection method and device and belt material flow detection system |
WO2022155701A1 (en) * | 2021-01-22 | 2022-07-28 | Nexus Mine Pty Ltd | System and method for monitoring the operation of one or more trucks |
WO2023000023A1 (en) * | 2021-07-19 | 2023-01-26 | Transcale Pty Ltd | System and method for determining fragmentation |
CN113702254B (en) * | 2021-08-30 | 2023-09-26 | 云南阿姆德电气工程有限公司 | Device and method for automatically detecting ore fraction of beneficiation ore |
CN114359372A (en) * | 2022-01-05 | 2022-04-15 | 山东工大中能科技有限公司 | Mine car load capacity detection method, system and device based on computer vision |
WO2023212021A1 (en) * | 2022-04-27 | 2023-11-02 | Vermeer Manufacturing Company | Productivity monitor in material reduction or separating machine |
WO2024112827A1 (en) * | 2022-11-21 | 2024-05-30 | Motion Metrics International Corp. | Spectral imaging for material characterization and control of systems and methods for processing earthen materials |
CN116664553B (en) * | 2023-07-26 | 2023-10-20 | 天津矿山工程有限公司 | Explosion drilling method, device, equipment and medium based on artificial intelligence |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7542873B2 (en) * | 2003-05-28 | 2009-06-02 | Bm Alliance Coal Operations Pty Ltd | Method and apparatus for determining particle parameter and processor performance in a coal and mineral processing system |
RU2282176C1 (en) * | 2005-03-14 | 2006-08-20 | Общество с ограниченной ответственностью Фирма "ДАТА-ЦЕНТР" (ООО Фирма "ДАТА-ЦЕНТР") | Method of determining granulometric composition of mixture of arbitrary shaped particles |
CL2009001924A1 (en) * | 2009-09-30 | 2010-06-25 | Tecnologia Integral S A | A system and method to detect hidden metal parts within a mineral load, directly in a means of transport to a primary crusher. |
FI20155909A (en) * | 2015-12-01 | 2017-06-02 | Outotec Finland Oy | Method and arrangement for controlling the comminution process |
GB2559964A (en) * | 2017-02-16 | 2018-08-29 | Her Majesty In Right Of Canada As Represented By The Mini Of Natural Resources | Methods for measuring properties of rock pieces |
-
2019
- 2019-09-06 WO PCT/IB2019/057528 patent/WO2020049517A1/en active Application Filing
- 2019-09-06 BR BR112021004248-2A patent/BR112021004248A2/en unknown
- 2019-09-06 AU AU2019335607A patent/AU2019335607A1/en active Pending
- 2019-09-06 PE PE2021000301A patent/PE20210695A1/en unknown
-
2021
- 2021-03-05 CL CL2021000547A patent/CL2021000547A1/en unknown
- 2021-12-06 CL CL2021003235A patent/CL2021003235A1/en unknown
- 2021-12-06 CL CL2021003234A patent/CL2021003234A1/en unknown
Also Published As
Publication number | Publication date |
---|---|
AU2019335607A1 (en) | 2021-04-01 |
BR112021004248A2 (en) | 2021-05-18 |
WO2020049517A1 (en) | 2020-03-12 |
PE20210695A1 (en) | 2021-04-12 |
CL2021003234A1 (en) | 2022-08-26 |
CL2021000547A1 (en) | 2021-09-24 |
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