In the field of mineral sorting, sorting machines generally comprise a single stage of sensor arrays controlling (via micro controller or other digital control system) a matched array of diverters, either physical (flaps or gates) or indirect (air jets). Sensors can be of diverse origin, including photometric (light source and detector), radiometric (radiation detector), electromagnetic (source and detector or induced potential), or more high-energy electromagnetic source/detectors such as x-ray source (fluorescence or transmission) or gamma-ray source types. Diversion is typically accomplished by air jets, although small scale mechanical diverters such as flaps or paddles are also used.
Matched sensor/diverter arrays are typically mounted onto a substrate which transports the material to be sorted over the sensors and on to the diverters where the material is sorted. Suitable substrates include vibrating feeders or belt conveyors. Sorting is typically undertaken by one or more high-efficiency machines in a single stage, or in more sophisticated arrangements, such as rougher/scavenger, rougher/cleaner, or rougher/cleaner/scavenger. Sorter capacity is limited by several factors, including micro controller speed and belt or feeder width, as well as limitations in sensor and diverter size (hence limitations in feed particle size).
Embodiments of the present disclosure will be described and explained through the use of the accompanying drawings in which:
The drawings have not necessarily been drawn to scale. For example, the dimensions of some of the elements of the figures may be expanded or reduced to help improve the understanding of the embodiments of the present application. Similarly, some components and/or operations may be separated into different blocks or combined into a single block for the purposes of discussion of some of the embodiments of the present application. Moreover, while the disclosure is amenable to various modification and alternative forms, specific embodiments have been show by way of example in the drawings and are described in detail below. The intention, however, is not to limit the disclosure to the particular embodiments described. On the contrary, the disclosure is intended to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.
Described herein are systems and methods wherein material is delivered to a multimodal array of different types of sensors by a material handling system, such as a conveyor belt. The arrays of different sensors sense the material and collect data which is subsequently used together to identify the composition of the material and make a determination as to whether to accept or reject the material as it passes off the terminal end of the material handling system. Diverters are positioned at the terminal end of the material handling system and are positioned in either an accept or reject position based on the data collected and processed to identify the composition of the material.
In some embodiments, the multiple arrays of different types of sensors are aligned with the material handling system such that one sensor in each array is positioned over a lane or channel of the material handling system (the lane or channel being effectively parallel with the direction of transport). A single diverter can also be positioned at the end of each channel, and the data collected from the sensors associated with each channel can be used to identify the material within the associated channel and make a reject or accept decision for the only material within the specific channel.
Various embodiments will now be described. The following description provides specific details for a thorough understanding and enabling description of these embodiments. One skilled in the art will understand, however, that the invention may be practiced without many of these details. Additionally, some well-known structures or functions may not be shown or described in detail, so as to avoid unnecessarily obscuring the relevant description of the various embodiments.
The terminology used in the description presented below is intended to be interpreted in its broadest reasonable manner, even though it is being used in conjunction with a detailed description of certain specific embodiments of the invention. Certain terms may even be emphasized below; however, any terminology intended to be interpreted in any restricted manner will be overtly and specifically defined as such in this Detailed Description section.
Referring now to
The material transport system 20 can generally include a system suitable for transporting mining material in at least a first direction and which allows for the material being transported to be sensed by sensor arrays 100, 105. Suitable material transport systems include, but are not limited to, conveyor belts and vibrating feeders. For the purposes of this description, the material transport system 20 may generally be referred to as a conveyor belt, though it should be understood that other transport systems can be used.
With reference now to
In some embodiments, the first array 100 includes sensors that are all the same type of sensor, and the second array 105 includes sensors that are all the same type of sensor, but the sensors of the first array 100 are of a different type from the sensors in the second array 105 (and therefor produce a different type of signal from the first array of sensors). Any type of sensor that is suitable for sensing mining material can be used within each array 100, 105. In some embodiments, the first array of sensors 100 are electromagnetic field sensors and the second array of sensors 105 are source/detector type sensors, while in some embodiments, the reverse is true. Suitable sensors that can be used within each array 100, 105 include, but are not limited to, photometric, radiometric, and electromagnetic sensors.
In some embodiments, the first array of first sensors 100 includes the same number of sensors as in the second array of second sensors 105. Any number of sensors within each array can be used, so long as an equal number of sensors is used in each array. Additionally, as shown in
Each array 100, 105 includes a signal processing system 110, 120 having an analogue to digital signal converter 115, 125 for converting analogue signals produced by the sensors when measuring the mining material to digital signals. Any suitable analogue to digital signal converter can be used in the signal processing system.
The digital signals produced by the analogue to digital signal converter 115, 125 are subsequently transmitted to the signal processing system 30 including a spectral analysis stage 130, a pattern recognition stage 135, and a pattern matching 140 stage. The signal processing system 30 is generally used for performing data analysis to identify the composition of the mining material. The spectral analysis stage 130, pattern recognition stage 135, and pattern matching 140 stage can all be implemented on a high performance parallel processing type computational substrate.
The spectral analysis stage can generally include performing Fourier Analysis on the digital data received from the analogue to digital converter 115, 125. Fourier Analysis can generally include using a field programmable gate array to generate spectral data of amplitude/frequency or amplitude/wavelength format via Fast Fourier Transform (FFT) implemented on the field programmable gate array.
The arbitrary power spectra generated in the Fourier Analysis is subsequently compared to previously determined and known spectra in the pattern matching stage 140. Known spectra data may be stored in a database accessed by the signal processing system 30. A pattern matching algorithm is generally used to perform the matching stage. The pattern matching algorithm works to recognize generated arbitrary power spectra that match the spectra of desired material based on the predetermined and known spectra of the desired material.
As noted previously, the first array of first sensors generally includes first sensors of a first type and the second array of second sensors generally includes second sensors of a second type different from the first type. As a result, the first sensors generally produce a first data signal and the second sensors produce a second, different data signal (e.g., a first magnetometer sensor and a second x-ray sensor). The signal processing equipment can then use the different types of data signals to improve the certainty of the material identification. Using the two or more different types of data signals to improve identification can be carried out in any suitable manner. In some embodiments, the signal processing equipment makes a first material identification using first signals (typically having a first confidence level or threshold) and a second material identification using the second signals (typically having a second confidence level/threshold).
The two identifications (and associated confidence levels/thresholds) can then be used together to make a final identification determination using various types of identification algorithms designed to combine separate identifications made on separate data. Because two separate identifications are made using different types of data signals, the certainty of final material identification based on the two separate identifications is typically improved. In other embodiments, the first data signals and second data signals are processed together to make a single identification using identification algorithms designed to use multiple sets of raw data to generate a single identification. In such embodiments, the confidence level of the identification is typically improved due to the use of two or more different types of data collected on the material.
The system may employ various identification and analysis approaches with corresponding algorithms (including machine learning algorithms that operate on spectral data produced by the sensors). One approach involves simple correlation between sensor output for each of the two different sensors, and prior sensor readings of known samples. Other approaches can employ more complex relationships between signals output from the two different sensors and a database of data developed from prior experimentations. Moreover, the system may employ synthetic data with probabilistic reasoning and machine learning approaches for further accuracy.
When a match between spectra is made (or not made, or not sufficiently made), a reject or accept decision can be generated and transmitted forward in the system, with the decision ultimately resulting in a diverter in a diverter array 170 being moved to an accept or reject position. In some embodiments, the reject or accept decision is carried forward initially using PLCs 145 and control relays 150 that are coupled to an electromechanical diversion array comprising control unit 155 with PLC 160 and control relays 165 connected via electrical connection to the array of diverters 170. The accept or reject decision received by the PLC 160 results in the control relays 165 activating or not activating the individual diverters in the diverter array 170.
In some embodiments, the number of diverters in the diverter array 170 is equal to the number of first sensors in the first array 100 and the number of sensors in the second array 105. Put another way, a diverter is provided at the end of each channel a, b, c, d, e, so that individual accept or reject decision can be made on a per channel basis. The data analysis is carried out such that the data collected by a pair of first and second sensors within the same array results in an accept or reject decision being transmitted to the diverter that is part of the same channel. The data analysis is also carried out with a time component that takes into account the speed of the material transport system so that when material within a channel changes from, for example, desirable to undesirable and back to desirable, the diverter within that channel can be moved from an accept to reject for only the period of time during which the undesirable material in the channel is passing over the terminal end of the material transport system.
Any type of diverters can be used in the diverter array 170. In some embodiments, the individual diverters are angular paddle type diverters, while in other embodiments, the diverters are of a linear type. Regardless of shape or type, each diverter may be composed of an electro-servotube linear actuator with a diverter plate either fixed or pin mounted.
The diverter array 170 can be mounted above a diverter chute comprising combined ‘accept’ 190 and ‘reject’ 195 diverter chutes. Material diverted by the diverter array 170 to an ‘accept’ 190 or ‘reject’ 195 chute are guided by suitably designed chutes to a product conveyance or waste conveyance.
As can be seen in
While not shown in
The system described herein can operate in bulk, semi-bulk, or particle-diversion mode, depending on the separation outcome desired by the operator. The system may also operate in real time (e.g., less than 2 ms for measurement and response) to ensure accurate sorting of material. At a minimum, the system should be able to conduct the data analysis and send an accept or reject instruction to the appropriate diverter in the time it takes for the material to pass the last sensor array and arrive at the terminal end of the conveyor 20.
With reference to
With reference to
In
In
In
The systems described herein are fully scalable. As shown in
With reference now to
In contrast and according to various embodiments described herein,
The embodiments described herein can also be practiced in distributed computing environments, where tasks or modules are performed by remote processing devices, which are linked through a communications network, such as a Local Area Network (“LAN”), Wide Area Network (“WAN”) or the Internet. In a distributed computing environment, program modules or sub-routines may be located in both local and remote memory storage devices. Aspects of the system described below may be stored or distributed on computer-readable media, including magnetic and optically readable and removable computer discs, stored as in chips (e.g., EEPROM or flash memory chips). Alternatively, aspects of the system disclosed herein may be distributed electronically over the Internet or over other networks (including wireless networks). Those skilled in the relevant art will recognize that portions of the embodiments described herein may reside on a server computer, while corresponding portions reside on a client computer. Data structures and transmission of data particular to aspects of the system described herein are also encompassed within the scope of this application.
Referring to
The input devices 1020 may include a keyboard and/or a pointing device such as a mouse. Other input devices are possible such as a microphone, joystick, pen, game pad, scanner, digital camera, video camera, and the like. The data storage devices 1040 may include any type of computer-readable media that can store data accessible by the computer 1000, such as magnetic hard and floppy disk drives, optical disk drives, magnetic cassettes, tape drives, flash memory cards, digital video disks (DVDs), Bernoulli cartridges, RAMs, ROMs, smart cards, etc. Indeed, any medium for storing or transmitting computer-readable instructions and data may be employed, including a connection port to or node on a network such as a local area network (LAN), wide area network (WAN) or the Internet (not shown in
Aspects of the system described herein may be practiced in a variety of other computing environments. For example, referring to
At least one server computer 2080, coupled to the Internet or World Wide Web (“Web”) 2060, performs much or all of the functions for receiving, routing and storing of electronic messages, such as web pages, audio signals, and electronic images. While the Internet is shown, a private network, such as an intranet may indeed be preferred in some applications. The network may have a client-server architecture, in which a computer is dedicated to serving other client computers, or it may have other architectures such as a peer-to-peer, in which one or more computers serve simultaneously as servers and clients. A database 2100 or databases, coupled to the server computer(s), stores much of the web pages and content exchanged between the user computers. The server computer(s), including the database(s), may employ security measures to inhibit malicious attacks on the system, and to preserve integrity of the messages and data stored therein (e.g., firewall systems, secure socket layers (SSL), password protection schemes, encryption, and the like).
The server computer 2080 may include a server engine 2120, a web page management component 2140, a content management component 2160 and a database management component 2180. The server engine performs basic processing and operating system level tasks. The web page management component handles creation and display or routing of web pages. Users may access the server computer by means of a URL associated therewith. The content management component handles most of the functions in the embodiments described herein. The database management component includes storage and retrieval tasks with respect to the database, queries to the database, and storage of data.
In general, the detailed description of embodiments of the invention is not intended to be exhaustive or to limit the invention to the precise form disclosed above. While specific embodiments of, and examples for, the invention are described above for illustrative purposes, various equivalent modifications are possible within the scope of the invention, as those skilled in the relevant art will recognize. For example, while processes or blocks are presented in a given order, alternative embodiments may perform routines having steps, or employ systems having blocks, in a different order, and some processes or blocks may be deleted, moved, added, subdivided, combined, and/or modified. Each of these processes or blocks may be implemented in a variety of different ways. Also, while processes or blocks are at times shown as being performed in series, these processes or blocks may instead be performed in parallel, or may be performed at different times.
Aspects of the invention may be stored or distributed on computer-readable media, including magnetically or optically readable computer discs, hard-wired or preprogrammed chips (e.g., EEPROM semiconductor chips), nanotechnology memory, biological memory, or other data storage media. Alternatively, computer implemented instructions, data structures, screen displays, and other data under aspects of the invention may be distributed over the Internet or over other networks (including wireless networks), on a propagated signal on a propagation medium (e.g., an electromagnetic wave(s), a sound wave, etc.) over a period of time, or they may be provided on any analog or digital network (packet switched, circuit switched, or other scheme). Those skilled in the relevant art will recognize that portions of the invention reside on a server computer, while corresponding portions reside on a client computer such as a mobile or portable device, and thus, while certain hardware platforms are described herein, aspects of the invention are equally applicable to nodes on a network.
The teachings of the invention provided herein can be applied to other systems, not necessarily the system described herein. The elements and acts of the various embodiments described herein can be combined to provide further embodiments.
Any patents, applications and other references, including any that may be listed in accompanying filing papers, are incorporated herein by reference. Aspects of the invention can be modified, if necessary, to employ the systems, functions, and concepts of the various references described above to provide yet further embodiments of the invention.
These and other changes can be made to the invention in light of the above Detailed Description. While the above description details certain embodiments of the invention and describes the best mode contemplated, no matter how detailed the above appears in text, the invention can be practiced in many ways. Details of the invention may vary considerably in its implementation details, while still being encompassed by the invention disclosed herein. As noted above, particular terminology used when describing certain features or aspects of the invention should not be taken to imply that the terminology is being redefined herein to be restricted to any specific characteristics, features, or aspects of the invention with which that terminology is associated. In general, the terms used in the following claims should not be construed to limit the invention to the specific embodiments disclosed in the specification, unless the above Detailed Description section explicitly defines such terms. Accordingly, the actual scope of the invention encompasses not only the disclosed embodiments, but also all equivalent ways of practicing or implementing the invention.
This application is a continuation of U.S. Non-Provisional application Ser. No. 15/857,034, filed Dec. 28, 2017, entitled “High Capacity Separation Of Coarse Ore Minerals From Waste Minerals,” which is a continuation of U.S. Non-Provisional application Ser. No. 14/805,333, filed Jul. 21, 2015, entitled “High Capacity Separation Of Coarse Ore Minerals From Waste Minerals”, which claims the benefit under 35 U.S.C. § 119(e) of U.S. Provisional Application No. 62/027,118, filed Jul. 21, 2014, entitled “High Capacity Separation Of Coarse Ore Minerals From Waste Minerals”, each of which is hereby incorporated by reference for all purposes in its entirety.
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Number | Date | Country | |
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20200139406 A1 | May 2020 | US |
Number | Date | Country | |
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62027118 | Jul 2014 | US |
Number | Date | Country | |
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Parent | 15857034 | Dec 2017 | US |
Child | 16673533 | US | |
Parent | 14805333 | Jul 2015 | US |
Child | 15857034 | US |