WO2023187501A1

WO2023187501A1 - System and method for measuring burden profile in a metallurgical furnace

Info

Publication number: WO2023187501A1
Application number: PCT/IB2023/051991
Authority: WO
Inventors: Rohan OHRI; Ujjwal Chandrakant Chaudhari; Samik Nag; Ishwari Prasad Gupta; Amit -; Mayank Tiwari; Shambhu Nath; Padmapal -; Uttam Singh
Original assignee: Tata Steel Limited
Priority date: 2022-03-29
Filing date: 2023-03-03
Publication date: 2023-10-05
Also published as: KR20250006065A

Abstract

Embodiment of disclosure relates to a system for measuring two-dimensional (2D) burden profile distribution in a metallurgical furnace. The system includes a thermal detection module configured to scan a top burden surface in the metallurgical furnace and capture thermal data corresponding to profile of the top burden surface. The system further includes a processing unit communicatively coupled to the thermal detection module. The processing unit is configured to receive data corresponding to the top burden surface from the thermal detection module. The processing unit is further configured to filter noise from the data received by the thermal detection module corresponding to the top burden surface. Further, the processing unit is adapted to generate a 2D burden profile using the data corresponding to profile of the top burden surface that is filtered of noise.

Description

TITLE: “SYSTEM AND METHOD FOR MEASURING BURDEN PROFILE IN A METALLURGICAL FURNACE”

TECHNICAL FIELD

Present disclosure relates in general to a field of metallurgy. Particularly, but not exclusively, the present disclosure relates to metallurgical furnaces. Further, embodiments of the present disclosure disclose a method and system for measuring burden profile inside a metallurgical furnace.

BACKGROUND OF THE DISCLOSURE

Iron making process using metallurgical furnaces such as blast furnace may be considered to be a leading process for providing steel making raw materials. Operations performed inside the blast furnaces is considered as black boxes. This is due to the fact that implementation of any direct measurement technique inside the blast furnace is hindered by harsh conditions inside the blast furnace. The blast furnace an integrated part of steel plant, any disturbance in the blast furnace may drastically and adversely affect overall production.

Among all factors that influence operations of the blast furnace, profile distribution of surface of burden inside the blast furnace is most important factor that is to be measured. Such burden profile distribution helps in modulating burden charging sequences to increase efficiency. Also, knowledge of changing burden profile distribution of burden material in the blast furnace is a valuable aid in improving the stability and control of furnace operation. The burden profile distribution is directly influenced by gas permeability, which is result of the charging angle juxtaposition. With uniform gas permeability, iron-making productivity and furnace campaign life are incremented in a high heat utilization furnace. It is required to achieve an accurate measurement of the burden profile distribution without gas leakage risks and heavy maintaining load. However, with high temperatures and pressure and hostile atmosphere, both performance and life cycle of installed mechanisms of measurements may be affected negatively. It may be particularly difficult to understand the distribution of burden materials because of the complex behavior of particular materials.

Obtaining a burden profile distribution for the blast furnace at an elevated accuracy, resolution and high data throughput is a demanding task in research field of metallurgy. Many techniques for performing measurement of the burden profile distribution include installing multiple units with mechanical movement. However, engineering costs of such techniques are prohibitive. Some conventional techniques depend on mathematical models and approximations to operate the blast furnace. Such modelling methods to measure the burden profile distribution may be implemented using physical experiment method or mechanism-based method or data-driven method. Application of measuring technologies using hardware components placed inside the furnace have been hindered by the harsh conditions in the blast furnaces. Also, building compact size prototypes for measuring the burden profile distribution have lacked the accuracy because of situations such as charging of burden in real-time, high temperature environment and so on.

Some non-contact methods including vision-based methods, interferometry, as well as time- of-flight technique may be implemented to measure the burden profile distribution. Few other techniques use radio waves for the measurement. However, as the radio waves have longer wavelength, measurement resolution is poor.

Also, the conventional radars are prone to false echoes from various surrounding metallic structures which are usually present at industrial site.

The information disclosed in this background of the disclosure section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already kno wn to a person skilled in the art.

SUMMARY OF THE DISCLOSURE

One or more shortcomings of the prior art are overcome by a system and a method as disclosed and additional advantages are provided through the system and the method as described in the present disclosure.

Additional features and advantages are realized through the techniques of the present disclosure. Other embodiments and aspects of the disclosure are described in detail herein and are considered a part of the claimed disclosure.

In one non-limiting embodiment of the present disclosure, a system for measuring 2D burden profile distribution in a metallurgical furnace is disclosed. The system includes a thermal detection module configured to scan a top burden surface in the metallurgical furnace and capture thermal data corresponding to profile of the top burden surface. The system further includes a processing unit communicatively coupled to the thermal detection module. The processing unit is configured to receive data corresponding to the top burden surface from the thermal detection module. The processing unit is further configured to filter noise from the data received by the thermal detection module corresponding to the top burden surface. Further, the processing unit is adapted to generate a 2D burden profile using the data corresponding to profile of the top burden surface that is filtered of noise.

In an embodiment of the present disclosure, the thermal detection module is disposed within an enclosure. Further, a cooling unit is configured around the enclosure to cool the thermal detection module. The enclosure further includes a dust cleaning unit configured to clean dust settled on the enclosure.

In an embodiment of the present disclosure, the processing unit includes a noise reduction unit, a data separation unit, and a heat map generation unit. The processing unit further includes a raw material identification unit.

In an embodiment of the present disclosure, the noise reduction unit comprises one or more filters to remove the noise from the data corresponding to profile of the top burden surface. The data separation unit is configured to separate the data corresponding to the profile of the top burden surface from data of furnace wall surface, dust, and steam. Further, the heat map generation unit is configured to generate a radiograph of the detected heat of the top burden surface.

In another non-limiting embodiment of the present disclosure, a method for measuring burden profile distribution in a metallurgical furnace is described. The method includes steps of scanning a top burden surface in the metallurgical furnace and capturing data corresponding to profile of the top burden surface using a thermal detection module. Further, the method includes receiving by a processing unit, data corresponding to the profile of the top burden surface from the thermal detection module. The processing unit is configured to filter noise from the data received by the thermal detection module corresponding to the profile of the top burden surface. The processing unit generates a 2D burden profile using the data corresponding to profile of the top burden surface that is filtered of noise.

In an embodiment of the present disclosure, scanning of the top burden profile is performed on an inner surface of the metallurgical furnace. It is to be understood that the aspects and embodiments of the disclosure described above may be used in any combination with each other. Several of the aspects and embodiments may be combined together to form a further embodiment of the disclosure.

The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.

BRIEF DESCRIPTION OF THE ACCOMPANYING FIGURES

The novel features and characteristics of the disclosure are set forth in the appended claims. The disclosure itself, however, as well as a preferred mode of use, further objectives, and advantages thereof, will best be understood by reference to the following detailed description of an illustrative embodiments when read in conjunction with the accompanying figures. One or more embodiments are now described, by way of example only, with reference to the accompanying figures wherein like reference numerals represent like elements and in which:

Figures la, lb and 1c illustrate schematic representations of a system for measuring burden profile distribution inside a blast furnace, in accordance with some embodiments of present disclosure; and

Figure 2 is a flowchart illustrating an exemplary method for measuring top burden surface inside a blast furnace, in accordance with some embodiments of present disclosure.

It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether such computer or processor is explicitly shown.

DETAILED DESCRIPTION

The foregoing has broadly outlined the features and technical advantages of the present disclosure in order that the detailed description of the disclosure that follows may be better understood. Additional features and advantages of the disclosure will be described hereinafter which forms the subject of the claims of the disclosure. It should be appreciated by those skilled in the art that, the conception and specific embodiments disclosed may be readily utilized as a basis for modifying other devices, systems, assemblies, and mechanisms for carrying out the same purposes of the present disclosure. It should also be realized by those skilled in the art that, such equivalent constructions do not depart from the scope of the disclosure as set forth in the appended claims. The novel features which are believed to be characteristics of the disclosure, to its system, together with further objects and advantages will be better understood from the following description when considered in connection with the accompanying figures. It is to be expressly understood, however, that each of the figures is provided for the purpose of illustration and description only and is not intended as a definition of the limits of the present disclosure.

In accordance with various embodiments of the present disclosure, a system for measuring a 2D burden profile distribution in a metallurgical furnace is described. The system includes a thermal detection module positioned on an inner circumference at a throat portion of the metallurgical furnace. The thermal detection module may be configured to scan a top burden surface in the metallurgical furnace and capture thermal data corresponding to profile of the top burden surface. In an embodiment, scanning of the top burden profile is performed at an inner surface of the metallurgical furnace. The burden, in general refers to furnace charge of iron-bearing materials (e.g., iron ore pellets and sinter), coke, and flux (e.g., limestone) descends through the shaft, where it is preheated and reacts with ascending reducing gases to produce liquid iron and slag that accumulate in the hearth. Further, the system includes a processing unit communicatively coupled to the thermal detection module. The processing unit may include one or more processing unit integrated or individually associated with the processing unit. In an embodiment, the processing unit may include a noise reduction unit, a data separation unit, a heat map generation unit and a raw material identification unit. The noise reduction unit associated with the processing unit includes one or more filters to remove noise from the data corresponding to profile of the top burden furnace. Further, the data separation unit is configured to separate the data corresponding to the profile of the top burden surface from data of furnace wall surface, dust and steam but not limiting to the same. Similarly, the heat map generation unit generates a radiograph of the detected heat of the top burden surface. Also, embodiments of the present disclosure describe a method of measuring burden profile distribution in the metallurgical furnace. In the forthcoming embodiments, system and method will be elucidated in detail in conjunction with FIG(s) la to 2. The terms “comprises.... a”, “comprising”, or any other variations thereof used in the specification, are intended to cover a non-exclusive inclusions, such that a system and method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such system or method. In other words, one or more elements in an assembly proceeded by “comprises. . . a” does not, without more constraints, preclude the existence of other elements or additional elements in the system.

The terms “includes”, “including”, or any other variations thereof, are intended to cover a nonexclusive inclusion, such that a setup, device or method that includes a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “includes... a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or method.

In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings that form a part hereof, and in which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.

Figure la illustrates schematic representation of a system (101) for measuring burden profile distribution in a metallurgical furnace (104). The system (101) may be implemented in an exemplary environment 100 comprising the blast furnace (104). The metallurgical furnace (104) may be a blast furnace (104) used for smelting to produce industrial metals. The metallurgical furnace (104) may also be referred to as a blast furnace (104) and may be interchangeably used in the forthcoming embodiments. The industrials metals may include, but are not limited to, pig iron, lead, copper and so on. The blast furnace (104) may be a vertical shaft furnace that produces liquid metals . The mixture may include, but is not limited to, at least one of metallic ore, coke, limestone, hematite and flux. The mixture may be termed as “burden” or “charge”. Studies on operation of the blast furnace (104) include to measure or determine charge level distribution shape (also termed as burden profile distribution) inside the blast furnace (104). Such measurement may be used to effectively control gas injection into the blast furnace (104) and smooth operation of the blast furnace (104). Therefore, measurement of the burden profile distribution is an important step of automated operation of the blast furnace (104). The measuring of the burden profile distribution includes to accurately obtains burden shape information in real-time. The proposed system is configured to accurately obtain the burden profile distribution in the blast furnace (104) without affecting the operations of the blast furnace (104).

The system (101) for measuring the burden profile distribution in the blast furnace (104) comprises a thermal detection module (102). In an embodiment, the thermal detection module (102) is a heat sensor. The thermal detection module (102) is configured to scan top burden surface in the blast furnace (104). Further, the thermal detection module (102) is configured to measure the burden profile distribution inside the blast furnace (104) based on the scans. In an embodiment, the thermal detection module (102) may be disposed within an enclosure. The enclosure may be configured with a cooling unit. In an embodiment, the cooling unit may be configured around the periphery of the enclosure. The cooling unit may be provided around the enclosure to protect the thermal detection module (102) from hostile environment inside the blast furnace (102). Further, the enclosure also includes a dust cleaning unit adapted to clean dust settled on the enclosure. The dust may be cleaned continuously on the enclosure, thereby enabling the interference free scanning for the thermal detection module.

Further, the thermal detection module (102) may be communicatively coupled to a processing unit (103). The plurality of scans may be performed using the thermal detection module (103) and may be processed by the processing unit (103). In an embodiment, the measurement of the burden profile distribution may be performed by the processing unit (103). For instance, the thermal detection module (102) may be configured to receive heat signals. The beams of heat signals are converged to thermal detection module (102) from different directions. The thermal detection module (102) may include an array of receivers configured to receive thermal signals.

In an embodiment, as shown in Figure la and Figure lb, the thermal detection module (102) may be placed on inner surface of top of the blast furnace (104). In such embodiment, as shown in Figure 1c, the thermal detection module (102) may be oriented at a predefined angle on the inner surface to perform the plurality of scans. The orientation of the thermal detection module (102) is in such a way that entire region across a stock line (105) of the blast furnace (104) is scanned by the thermal detection module (102).

In an embodiment, the processing unit (103) is communicatively coupled with the thermal detection module (102). The heat signals received by the thermal detection module (102) may be provided to the processing unit (103) for processing and measuring the burden profile distribution inside the blast furnace (104). As shown in Figure la, the processing unit (103) may be placed exterior to the blast furnace (104). Thus, the processing unit (103) may not be impacted by higher temperatures of the blast furnace (104). In an embodiment, the processing unit (103) may include a processor, I/O interface, and a memory (not shown in the figure). In some embodiments, the memory may be communicatively coupled to the processor. The memory stores instructions, executable by the processor, which, on execution, may cause the processing unit (103) to measure the burden profile distribution, as disclosed in the present disclosure. In an embodiment, the memory may include one or more modules and data. The one or more modules may be configured to perform the steps of the present disclosure using the data, to measure the burden profile distribution. In an embodiment, each of the one or more modules may be a hardware unit which may be outside the memory and coupled with the processing unit (103). In an embodiment, the processing unit (103), for measuring the burden profile distribution, may be implemented in a variety of computing systems, such as a laptop computer, a desktop computer, a Personal Computer (PC), a notebook, a smartphone, a tablet, e-book readers, a server, a network server, a cloud-based server and the like. In an embodiment, the processing unit (103) may be implemented in a cloud-based server or a dedicated server and may be in communication with the thermal detection module (102) via a communication network. The communication network may include, without limitation, a direct interconnection, Local Area Network (LAN), Wide Area Network (WAN), wireless network (e.g., using Wireless Application Protocol), the Internet, and the like. In an embodiment, the processing unit 103 may be configured to receive and transmit data via the I/O interface.

In an embodiment, the processing unit (103) comprises a noise reduction unit, a data separation unit, a raw material identification unit and a heat map generation unit. The noise reduction unit [not shown] comprises one or more filters to remove the noise from the data corresponding to profile of the top burden surface. The data separation unit is configured to separate the data corresponding to the profile of the top burden surface from data of the furnace wall surface, dust and steam. The heat map generation unit may be configured to generate a radiograph of the detected heat of the top burden surface. Further, the raw material identification unit associated with the processing unit (103) is configured to determine type of raw material in the blast furnace (104). Generally, coke and ferrous burden are used as burden materials in blast furnace (104). Sinter, pellets, and lump ore are used to make the ferrous burden. The emissivity of coke particles and ferrous burden particles differs significantly. The emissivity of coke and ferrous burden particles can be easily distinguished using thermal detection module (102). The radiograph is created with this emissivity data easily distinguishing between materials of varying colours. The raw material identification unit associated with the processing unit (103) use machine learning tool to auto identify the type of material and processes the live radiographs to detect exact co-ordinates of different materials in relation to blast furnace (104) dimensions.

Figure 2 shows a flowchart illustrating an exemplary method for measuring the burden profile distribution inside the blast furnace 104.

Using the proposed system (101), the steps of method of measuring the burden profile may be performed in real-time, without altering regular operation of the blast furnace (104). Further, the method is performed using the system (101) which includes the thermal detection module (102) and the processing unit (103). The thermal detection module (101) is configured to perform scans on regular basis or on continuous basis.

At block 201, the thermal detection module (102) of the system (101) may be configured to perform the scans in interior of the blast furnace (104) to capture thermal data of top burden surface. In an embodiment, electronics associated with the thermal detection module (102) may be placed inside a dust cleaning and cooling enclosure to withstand harsh conditions inside the blast furnace (104). Further, a cooling unit may be additionally provided to cool the thermal detection module (102). In an embodiment, the scans may be performed by receiving the signals from the interior of the blast furnace (104). The thermal detection module (102) eliminates the need for movable parts inside the blast furnace 104 for performing the scans. The thermal detection module (102) may be placed on inner surface of top of the blast furnace (104). In an embodiment, the thermal detection module (102) may be placed at the predefined angle on the inner surface to perform the scans. In an embodiment, the thermal detection module (102) may be placed at top of the the blast furnace (104), along vertical axis of the blast furnace (104). The placement of the thermal detection module (102) needs to be optimal to scan entire region inside the blast furnace (104).

As shown at block 202, upon performing the scans, the processing unit (103) of the system

(101) may be configured to measure the burden profile distribution of the blast furnace (104). In an embodiment, the processing unit (103) may be electronically coupled with the optical unit (102) to receive the hat signals and measure the burden profile distribution based on the received heat signals. In an embodiment, one or more techniques, known to a person skilled in the art, may be implemented in the processing unit (103), to measure the burden profile distribution. In an embodiment, the processing unit (103), upon processing the received heat signals, may output 2D burden profile distribution from the scans.

At block 203, the processing unit (103) is configured to filter the noise from the thermal data generated by the heat map generation unit. The thermal data corresponds to profile of the top burden surface. But the captured thermal data still includes noise caused from the dust and needs to be filtered to obtain clean data. One or more filters are used to reduce the noise from the captured data. The noise is included due to for example, multiple reflections from wall surfaces of the blast furnace (104), dust and/or steam. Noise reduction may also comprise separating the data of the burden profile the top burden surface from data of furnace wall, dust and/or steam. In an exemplary embodiment, a sigma filter may be used to remove the noise. Further, machine learning (ML) techniques or deep learning (DL) techniques may be used to remove the noise. For example, unsupervised clustering techniques may be used to detect outliers in the data and separate the outliers. In another example, convolution neural network (CNN) can be used to remove noise from the point cloud data. In yet another example, K- nearest neighbour (KNN) can be applied. In an embodiment, the ML or DL techniques can be applied on the 2D data.

The data filtered of noise is unstructured data. Further process is required for obtaining the coordinates for top burden surface and eliminate the points due to dust and blast furnace wall, it converted to structured data by data converting means. The data convertor means is configured with co-ordinate shifting logic for the structured points. The tip of thermal detection module

(102) can be considered as a reference origin for co-ordinate and new origin is shifted along a center line of the furnace at an elevation of design stock level for the furnace. The one or more filters are configured to identify the points that lie on wall of furnace by comparing them with generated points for wall of furnace. The one or more filters are also configured with a multiframe comparison method, where the data from multiple frames captured by the thermal detection module (102) in a predefined time frames (e.g., 5 seconds) are compared. Dynamic points due to dust particles in these frames are identified and removed while static points from top burden surface are retained. The resultant data is only for top furnace surface.

Upon obtaining the 2D burden profile distribution of the plurality of scans, the processing unit (103) may be configured to perform interpolation the 2D burden profile distribution measured for adjacent diameters from the plurality of diameters to determine one or more interpolated burden profile distributions. One or more techniques, known to a person skilled in the art, may be implemented in the processing unit (103), to perform the interpolation.

In an embodiment, the scans and the measuring of the burden profile distribution may be performed during regular operation of the blast furnace (104). In an embodiment, the system may be configured to operate automatically at regular interval of time to perform the method (200). In an embodiment, the system (101) may be configured to perform the step upon receiving trigger from a user associated with the blast furnace (104). In an embodiment, the burden profile distribution measured by the system (101) may be used to control amount of gas/hot air injected inside the blast furnace (104). In an embodiment, a control unit may be fed with the burden profile distribution measured by the system (101), to automatically control injection of the gas/hot air by analyzing the burden profile distribution.

At block 204 the processing unit (103) generates the 2D burden profile using the noise free processed data. A 2D top surface extracting means may be coupled with the data converting means. The 2D top furnace surface extracting means may be configured to store the coordinates for 2D top burden surface measured at any instant. A layer profile visualizer means may be coupled with the 2D top furnace surface extractor means, which is configured to generate 2D profile using top burden surface of consecutive charges dumped in furnace. A 2D layer profile generator may use a volume balance mechanism, which descents the 2D layers based on volume of burden dumped in furnace for a charge to generate the resultant 2D layer profile in blast furnace. A burden descent rate calculator means may be coupled with the 2D top burden surface extracting means, and may be configured to compare co-ordinates of multiple 2D top burden surface measured at predefined frequency in a predefined time duration for a charge dumped in furnace. Further, the burden descent rate is calculated at each point along the surface of top furnace surface. The burden descent rate calculating means is configured with the visualization means to highlight areas of low and high descent rates.

. The method 200 may be described in the general context of computer executable instructions. Generally, computer executable instructions can include routines, programs, objects, components, data structures, procedures, modules, and functions, which perform particular functions or implement particular abstract data types.

The order in which the method (200) are described may not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method. Additionally, individual blocks may be deleted from the methods without departing from the scope of the subject matter described herein. Furthermore, the method can be implemented in any suitable hardware, software, firmware, or combination thereof.

An embodiment of the present disclosure includes stationed thermal detection module (102) to perform plurality of scans. Thus, need for movable parts for efficient scan may be eliminated. Further, mechanical errors caused due to such movable parts are also reduced. Also, the system can be operated any time without obstructing normal operation of the blast furnace.

An embodiment of the present disclosure provides a compact system placed inside the blast furnace and processing part is placed outside the blast furnace. Thus, the proposed system may be easily compatible with any geometry of the blast furnace. Also, the system (101) is protected against harsh condition in blast furnace.

An embodiment of the present disclosure provisions to perform efficient scanning and measurement of the burden profile distribution. Higher resolution of the burden profile distribution may be achieved by performed the interpolation of data obtained from scanned regions.

The terms “an embodiment”, “embodiment”, “embodiments”, “the embodiment”, “the embodiments”, “one or more embodiments”, “some embodiments”, and “one embodiment” mean “one or more (but not all) embodiments of the invention(s)” unless expressly specified otherwise. The terms “including”, “comprising”, “having” and variations thereof mean “including but not limited to”, unless expressly specified otherwise.

The enumerated listing of items does not imply that any or all of the items are mutually exclusive, unless expressly specified otherwise.

The terms “a”, “an” and “the” mean “one or more”, unless expressly specified otherwise.

A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention.

When a single device or article is described herein, it will be readily apparent that more than one device/article (whether or not they cooperate) may be used in place of a single device/article. Similarly, where more than one device or article is described herein (whether or not they cooperate), it will be readily apparent that a single device/article may be used in place of the more than one device or article or a different number of devices/articles may be used instead of the shown number of devices or programs. The functionality and/or the features of a device may be alternatively embodied by one or more other devices which are not explicitly described as having such functionality /features. Thus, other embodiments of the invention need not include the device itself.

The illustrated operations of Figure 2 shows certain events occurring in a certain order. In alternative embodiments, certain operations may be performed in a different order, modified, or removed. Moreover, steps may be added to the above described logic and still conform to the described embodiments. Further, operations described herein may occur sequentially or certain operations may be processed in parallel. Yet further, operations may be performed by a single processing unit or by distributed processing units.

Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the disclosure of the embodiments of the invention is intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims. While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope being indicated by the following claims.

With respect to the use of substantially any plural and/or singular terms herein, those having skill in the art can translate from the plural to the singular and/or from the singular to the plural as is appropriate to the context and/or application. The various singular/plural permutations may be expressly set forth herein for sake of clarity.

It will be understood by those within the art that, in general, terms used herein, and especially in the appended claims (e.g., bodies of the appended claims) are generally intended as “open” terms (e.g., the term “including” should be interpreted as “including but not limited to,” the term “having” should be interpreted as “having at least,” the term “includes” should be interpreted as “includes but is not limited to,” etc.). It will be further understood by those within the art that if a specific number of an introduced claim recitation is intended, such an intent will be explicitly recited in the claim, and in the absence of such recitation no such intent is present. For example, as an aid to understanding, the following appended claims may contain usage of the introductory phrases “at least one” and “one or more” to introduce claim recitations. However, the use of such phrases should not be construed to imply that the introduction of a claim recitation by the indefinite articles “a” or “an” limits any particular claim containing such introduced claim recitation to inventions containing only one such recitation, even when the same claim includes the introductory phrases “one or more” or “at least one” and indefinite articles such as “a” or “an” (e.g., “a” and/or “an” should typically be interpreted to mean “at least one” or “one or more”); the same holds true for the use of definite articles used to introduce claim recitations. In addition, even if a specific number of an introduced claim recitation is explicitly recited, those skilled in the art will recognize that such recitation should typically be interpreted to mean at least the recited number (e.g., the bare recitation of “two recitations,” without other modifiers, typically means at least two recitations, or two or more recitations). Furthermore, in those instances where a convention analogous to “at least one of A, B, and C, etc.” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., “a system having at least one of A, B, and C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). In those instances where a convention analogous to “at least one of A, B, or C, etc.” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., “a system having at least one of A, B, or C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). It will be further understood by those within the art that virtually any disjunctive word and/or phrase presenting two or more alternative terms, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase “A or B” will be understood to include the possibilities of “A” or “B” or “A and B.”

In addition, where features or aspects of the disclosure are described in terms of Markush groups, those skilled in the art will recognize that the disclosure is also thereby described in terms of any individual member or subgroup of members of the Markush group.

While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.

Referral numerals:

Claims

Claims:

1. A system (101) for measuring 2D burden profile distribution in a metallurgical furnace (104), the system comprising: a thermal detection module (102) configured to scan a top burden surface in the metallurgical furnace (104) and capture thermal data corresponding to profile of the top burden surface; and a processing unit (103) communicatively coupled to the thermal detection module (102), the processing unit (103) configured to: receive data corresponding to the top burden surface from the thermal detection module (102); filter noise from the data received by the thermal detection module (102) corresponding to the top burden surface; and generate a 2D burden profile using the data corresponding to profile of the top burden surface that is filtered of noise.

2. The system (101) as claimed in claim 1, wherein the thermal detection module (102) is disposed within an enclosure.

3. The system (101) as claimed in claim 2, wherein a cooling unit is configured around the enclosure.

4. The system (101) as claimed in claim 1, wherein the enclosure comprises a dust cleaning unit configured to clean dust settled on the enclosure.

5. The system (101) as claimed in claim 1, wherein the thermal detection module (102) is heat sensor.

6. The system (101) as claimed in claim 1, wherein the processing unit (103) comprises a noise reduction unit, a data separation unit, and a heat map generation unit.

7. The system (101) as claimed in claim 1, wherein the processing unit (103) comprises a raw material identification unit.

8. The system (101) as claimed in claim 6, wherein the noise reduction unit comprises one or more filters to remove the noise from the data corresponding to profile of the top burden furnace.

9. The system (101) as claimed in claim 6, wherein the data separation unit is configured to separate the data corresponding to the profile of the top burden surface from data of furnace wall surface, dust, and steam.

10. The system (101) as claimed in claim 6, wherein the heat map generation unit generates a radiograph of the detected heat of the top burden surface.

11. A method of measuring 2D burden profile distribution in a metallurgical furnace (104), the method comprising: scanning a top burden surface in the metallurgical furnace (104) and capturing data corresponding to profile of the top burden surface using a thermal detection module (102); receiving, by a processing unit (103), data corresponding to the profile of the top burden surface from the thermal detection module (102); filtering, by the processing unit (103), noise from the data received by the thermal detection module (102) corresponding to profile of the top burden surface; and generating, by the processing unit (103), a 2D burden profile using the data corresponding to profile of the top burden surface that is filtered of noise.

12. The method as claimed in claim 11, wherein scanning of the top burden profile is performed on an inner surface of the metallurgical furnace (104).

13. The method as claimed in claim 11 comprises separating the data of the profile of the top burden surface from data of furnace wall surface, dust, and steam.

14. The method as claimed in claim 11, wherein the 2D burden profile is generated using the data based on burden descent calculated using volume of burden provided to the metallurgical furnace (104).

15. The method as claimed in claim 11 comprises identifying raw material by a raw material identification unit associated with the processing unit (103)