System and method for measuring burden profile in a blast furnace

Abstract

The disclosed embodiments relate to a system and method for measuring a burden profile distribution in a blast furnace. The system comprises a phased array based radar unit configured to perform multiple scans inside the blast furnace using electronic beamforming. Furthermore, the phased array based radar unit is configured to measure the burden profile distribution inside the blast furnace based on the multiple scans. With the proposed method, efficient scanning and accurate measurement of the burden profile distribution is achieved by using a compact and stationary system.

Description

[Technical field]

[0001] The present disclosure relates generally to the field of metallurgy and furnaces. In particular, but not exclusively, the present disclosure relates to a method and system for measuring a charge profile inside a blast furnace. [Background technology]

[0002] The iron making process using the blast furnace can be considered as the main process for providing the raw material for steel making. The operations carried out inside the blast furnace are not fully known. This is because the implementation of any direct measurement techniques inside the blast furnace is hindered by the poor conditions inside the blast furnace. The blast furnace is the master plant for an integrated steelworks and any fault in the blast furnace can dramatically affect the entire steelworks production.

[0003] Among all the factors that affect the operation of a blast furnace, the profile distribution of the charge surface inside the blast furnace is the most important factor to be measured. Such charge profile distribution helps to adjust the charge loading sequence to improve production efficiency. Knowledge of the charging of charge profile distribution of charge material in the blast furnace also greatly helps to improve the stability and control of the furnace operation. The charge profile distribution is directly influenced by the gas permeability, which is a result of the juxtaposition of the loading angle. With uniform gas permeability, the steelmaking productivity and the furnace operation improves the life of the high heat utilization furnace. It is necessary to achieve accurate measurement of the charge profile distribution without the risk of gas leakage and heavy maintenance load. However, high temperature and pressure as well as adverse atmospheres can adversely affect both the performance and the life cycle of the installed measurement mechanism. Understanding the distribution of charge material can be particularly difficult due to the complex behavior of certain materials.

[0004] Acquiring the burden profile distribution of a blast furnace with high accuracy, resolution, and high data throughput is a challenging task in the field of metrology research. Many techniques for performing the measurement of the burden profile distribution include introducing multiple units with mechanical operations. However, the engineering costs of such techniques are prohibitive. Some conventional techniques rely on mathematical models and approximation methods for operating a blast furnace. Such modeling methods for measuring the burden profile distribution may be implemented using physical experimental methods or mechanism-based methods or data-driven methods. The application of measurement techniques using hardware components located inside the furnace has been hindered by the poor conditions inside the blast furnace. Also, building a compact size prototype for measuring the burden profile distribution lacks precision due to conditions such as real-time burden loading, high temperature environment, etc.

[0005] Several non-contact methods, including visual, interferometric, and time-of-flight techniques, can be implemented to measure the charge profile distribution. Some other techniques, such as Radar's, use radio waves for the measurement. However, radio waves have a long wavelength and therefore the measurement resolution is insufficient. Also, conventional radars are susceptible to false echoes from various surrounding metal structures that are usually present in industrial sites. The use of laser-based scanning and imaging systems has also enabled the measurement of 3D top charge profiles for blast furnaces. High-intensity laser scanners using class 3 lasers and imaging systems to measure the top charge profile can be one of the solutions to achieve high-resolution 3D top charge profiles, but they require rugged mechanical scanners with mirrors and high-speed imaging systems. Also, these visible light-based scanners stop working when the central chimney flame is bright. Therefore, a standalone scanner that operates in the non-visible wavelengths of the electromagnetic spectrum and has a wavelength small enough to perform high-resolution scans is needed. Light detection and ranging (LiDAR) systems that operate within infrared wavelengths are ideal for this application. LiDARs with a pulse-scan mode of operation will have a delay in capturing multiple points in 3D space, so a LiDAR with a flash mode of operation is suitable for the proposed invention.

[0006] The information disclosed in this Background of the Disclosure section is intended only to enhance understanding of the general background of the present invention, and should not be construed as an admission or in any way suggestion that this information forms prior art known to those skilled in the art. Summary of the Invention

[0007] One or more of the shortcomings of the prior art are overcome by the disclosed systems and methods, and additional advantages are provided through the systems and methods described in this disclosure.

[0008] Additional features and advantages are realized through the techniques of the present disclosure.Other embodiments and aspects of the present disclosure are described in detail herein and are considered a part of the claimed disclosure.

[0009] In one embodiment, the present disclosure discloses a system for measuring a burden profile in a blast furnace, the system includes a Light Detection and Ranging (LiDAR) unit configured to scan a top burden surface in the blast furnace and capture 3D point cloud data of the top burden surface, and a processing unit configured to filter noise from the 3D point cloud data of the top burden surface and use the noise-filtered 3D point cloud data to generate a 3D burden profile.

[0010] In one embodiment, the present disclosure discloses a method for measuring a burden profile distribution in a blast furnace, the method includes: scanning a top burden surface in a blast furnace, using a light detection and ranging (LiDAR) unit to capture 3D point cloud data of the top burden surface, filtering noise from the 3D point cloud data of the top burden surface by a processing unit, and using the noise-filtered 3D point cloud data to generate a 3D burden profile by the processing unit.

[0011] In one embodiment, the LiDAR unit is positioned inside the blast furnace to capture the top charge surface.

[0012] In one embodiment, the LiDAR unit comprises a transmitter configured to transmit a signal and a receiver configured to receive a signal from the top charge surface, and the LiDAR unit is oriented at a predefined angle above the interior surface of the blast furnace.

[0013] In one embodiment, the processing unit comprises a noise reduction unit, a data separation unit, and a map generation unit.

[0014] In one embodiment, the noise reduction unit comprises one or more filters for removing noise from the 3D point cloud data.

[0015] In one embodiment, the data separation unit is configured to separate the 3D point cloud data of the top charge surface from the 3D point cloud data of the furnace wall surface.

[0016] In one embodiment, the map generation unit generates a 3D charge profile using the 3D point cloud data.

[0017] It should be understood that the aspects and embodiments of the disclosure described above can be used in any combination with each other. Some of the aspects and embodiments can be combined to form further embodiments of the disclosure.

[0018] 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.

[0019] The accompanying drawings, which are incorporated in and constitute a part of this disclosure, and together with the description, illustrate exemplary embodiments and explain the disclosed principles. In the drawings, the leftmost digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the drawings to reference like features and components. Some embodiments of systems and / or methods according to embodiments of the present subject matter will now be described, by way of example only, and with reference to the accompanying drawings, in which: [Brief description of the drawings]

[0020] [Figure 1a] FIG. 1 is a schematic diagram illustrating a system for measuring a burden profile distribution inside a blast furnace, according to some embodiments of the present disclosure. [Figure 1b] FIG. 1 is a schematic diagram illustrating a system for measuring a burden profile distribution inside a blast furnace, according to some embodiments of the present disclosure. [Figure 1c]FIG. 1 is a schematic diagram illustrating a system for measuring a burden profile distribution inside a blast furnace, according to some embodiments of the present disclosure. [Diagram 2] 2 is a flow chart illustrating an example method for measuring a top charge surface inside a blast furnace, according to some embodiments of the present disclosure. [Diagram 3] FIG. 1 illustrates an example embodiment associated with a system showing a measured burden profile distribution inside a blast furnace, according to some embodiments of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] Those skilled in the art will appreciate that any block diagrams herein represent conceptual views of example systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudocode, and the like may be substantially represented in a computer-readable medium and represent various processes that may be executed by such a computer or processor, whether or not a computer or processor is explicitly depicted.

[0022] The word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

[0023] While the present disclosure is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and are described in detail below, however, it is to be understood that it is not intended to limit the disclosure to the precise form disclosed, but on the contrary, the disclosure is intended to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure.

[0024] "Comprises," "comprising," or any other variation thereof, is intended to cover a non-exclusive inclusion, such that a set-up, device, or method comprising 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 set-up or device or method. In other words, one or more elements in a system or apparatus preceded by "comprising..." does not, without further constraints, preclude the presence of other or additional elements in the system or method.

[0025] "Comprise", "comprising" or any other variation thereof is intended to cover a non-exclusive inclusion, such that a set-up, 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 that are not expressly listed or that are inherent to such set-up or device or method. In other words, one or more elements in a system or apparatus preceded by "comprising" does not, without further constraints, exclude the presence of other or additional elements in the system or method.

[0026] In the following detailed description of embodiments of the present disclosure, reference is made to the accompanying drawings which form a part hereof, and in which is shown by way of illustration specific embodiments in which the present disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, with the understanding that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. Accordingly, the following description is not to be construed in a limiting sense.

[0027] The present disclosure discloses a system and method for measuring a burden profile distribution in a blast furnace. The system includes a Light Detection and Ranging (LiDAR) unit for measuring a burden profile distribution inside the blast furnace. The LiDAR unit includes a processing unit located outside the blast furnace. The proposed system is configured to perform a scan of the blast furnace interior and measure the burden profile distribution based on the scan. The proposed system is a compact scanning system that accurately measures the burden profile distribution without interfering with the normal operation of the blast furnace.

[0028] FIG. 1a shows a schematic diagram of a system for measuring a burden profile distribution in a blast furnace 104. The system may be implemented in an example environment 100 comprising a blast furnace 104. The blast furnace 104 is a type of metallurgical furnace used in smelting to produce industrial metals. The industrial metals may include, but are not limited to, pig iron, lead, copper, and the like. The blast furnace 104 may be a vertical shaft furnace that produces liquid metal by reaction of an air stream introduced under pressure to the bottom of the blast furnace 104 with a mixture of materials fed to the top. The mixture may include, but is not limited to, at least one of a metal ore such as hematite, coke, and a flux such as limestone. The mixture is referred to as a "burden" or "charge." Studies on the operation of the blast furnace 104 include measuring or determining the burden level distribution shape (also referred to as a burden profile distribution) inside the blast furnace 104. Such measurements may be used to effectively control gas injection into the blast furnace 104 and the smooth operation of the blast furnace 104. Therefore, measurement of the burden profile distribution is a key step in the automated operation of the blast furnace 104. Measurement of the burden profile distribution involves accurately acquiring burden shape information in real time. The proposed system is configured to accurately acquire the burden profile distribution in the blast furnace 104 without affecting the operation of the blast furnace 104.

[0029] The system for measuring a burden profile distribution in a blast furnace 104 includes a light detection and ranging (LiDAR) unit 101. The LiDAR unit 101 is configured to scan a top burden surface in the blast furnace 104. Further, the LiDAR unit 101 is configured to measure a burden profile distribution in the blast furnace 104 based on the scan. In an embodiment, the LiDAR unit 101 may include an optical unit 102 and a processing unit 103. The scan may be performed using the optical unit 102. The measurement of the burden profile distribution may be performed by the processing unit 103.

[0030] In one embodiment, the optical unit 102 in the LiDAR unit 101 includes an array of laser sources controlled to emit signals. The beams of the signals are directed to points in different directions. In one embodiment, directing the signals can be programmed. The direction of the signals can be predefined, taking into account the location of the LiDAR unit 101. The optical unit 102 can include a rugged array of LiDAR assemblies mounted in a dust-cleaning and cooling enclosure. The optical unit 102 can include an array of transmitters and an array of receivers configured to transmit and receive signals, respectively. The transmitters are configured to transmit signals to the top charge surface. The receivers are configured to capture signals reflected by the top charge surface. The signals are then added together in the optical or electronic domain to form 3D point cloud data.

[0031] In one embodiment, as shown in Figures 1a and 1b, the optical unit 102 may be placed on the interior surface of the top of the blast furnace 104. In such an embodiment, the optical unit 102 may be oriented at a predefined angle on the interior surface to perform the scan, as shown in Figure 1c. The orientation of the optical unit 102 is such that the entire area across the stockline 105 of the blast furnace 104 is scanned by the optical unit 102.

[0032] In one embodiment, the processing unit 103 is electronically coupled to the optical unit 102. The signal received by the optical unit 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 FIG. 1a, the processing unit 103 may be located outside the blast furnace 104. Thus, the processing unit 103 may not be affected by the high temperature of the blast furnace 104. In one embodiment, the processing unit 103 may include a processor, an I / O interface, and a memory (not shown). In some embodiments, the memory may be communicatively coupled to the processor. The memory stores instructions executable by the processor that, when executed, may cause the processing unit 103 to measure the burden profile distribution as disclosed in the present disclosure. In one 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 one embodiment, each of the one or more modules may be a hardware unit that is external to the memory and may be coupled to the processing unit 103. In one embodiment, the processing unit 103 for measuring the charge profile distribution may be implemented in various computing systems, such as laptop computers, desktop computers, personal computers (PCs), notebooks, smartphones, tablets, e-book readers, servers, network servers, cloud-based servers, etc. In one embodiment, the processing unit 103 may be implemented in a cloud-based server or a dedicated server and may communicate with the optical unit 102 via a communication network. The communication network may include, but is not limited to, a direct interconnection, a local area network (LAN), a wide area network (WAN), a wireless network (e.g., using a wireless application protocol), the Internet, etc. In one embodiment, the processing unit 103 may be configured to receive and transmit data via an I / O interface.

[0033] In one embodiment, the processing unit 103 comprises a noise reduction unit, a data separation unit, and a map generation unit. The noise reduction unit comprises one or more filters for removing noise from the 3D point cloud data. The noise may include stray signals from signals received by the receiver of the sensor from other sources, or signals after multiple reflections inside the furnace. The data separation unit is configured to separate the 3D point cloud data of the top charge surface from the 3D point cloud data of the furnace wall surface. The charge profile does not need to include the furnace wall, since the blast furnace operator needs to evaluate the top charge profile of the charge raw material. Also, to generate a bed profile from multiple charges, it is necessary to process the top charge surface, and unwanted signals from the furnace wall may create an inaccurate bed profile that will later cause the operation to be incorrect. The map generation unit uses the 3D point cloud data to generate the 3D charge profile by converting the point cloud data in the blast furnace coordinates, taking into account the actual dimensions of the blast furnace and the designed stock level of the top charge surface. The data in the new coordinate system is rendered and visualized as a 3D surface.

[0034] FIG. 2 shows a flow chart illustrating an exemplary method for measuring a burden profile distribution in a blast furnace 104.

[0035] Using the proposed system, the method steps of measuring the burden profile can be performed in real time without modifying the regular operation of the blast furnace 104. Furthermore, the method is performed using a LiDAR unit 101 comprising an optical unit 102 and a processing unit 103. The LiDAR unit 101 is configured to perform scans periodically or continuously.

[0036] In block 201, the optical unit 102 of the LiDAR unit 101 may be configured to perform scanning inside the blast furnace 104 using electronic beam forming to capture 3D point cloud data of the top charge surface. In one embodiment, the electronics associated with the optical unit 102 may be disposed inside a dust cleaning and cooling enclosure to withstand the harsh conditions inside the blast furnace 104. Furthermore, a cooling unit may be additionally provided to cool the optics and electronics of the LiDAR unit 101. In one embodiment, the scanning may be performed by transmitting and receiving signals inside the blast furnace 104. The optical unit 102 may be disposed on an inner surface of the top of the blast furnace 104. In one embodiment, the electronics and optics configured to perform the transmission and reception of signals may be installed inside the blast furnace 104. In one embodiment, the optical unit 102 may be disposed at a predefined angle on the inner surface to perform the scanning.

[0037] In one embodiment, the optical unit 102 may be positioned at the top of the blast furnace 104 along the longitudinal axis of the blast furnace 104. The LiDAR unit 101 scans the entire area inside the blast furnace 104 in one scan.

[0038] In one embodiment, the 3D point cloud data is collected without delay using an interface driver, hi one embodiment, the 3D point cloud data is stored with a timestamp.

[0039] When performing the scan, the processing unit 103 of the LiDAR unit 101 may be configured to measure a burden profile distribution of the blast furnace 104. In one embodiment, the processing unit 103 may be electronically coupled to the optical unit 102 to receive signals and measure a burden profile distribution based on the received signals.

[0040] In block 202, the processing unit 103 is configured to filter out noise from the 3D point cloud data. The LiDAR is exposed to noisy data. However, the LiDAR has improved penetration into dust particles. However, the captured 3D point cloud data still includes noise resulting from dust, which needs to be filtered out to obtain clean data. One or more filters are used to reduce noise from the captured 3D point cloud data. The noise is included, for example, due to multiple reflections from the wall surface of the blast furnace 104. The noise reduction may also include separating the 3D point cloud data of the top charge surface from the 3D point cloud data of the furnace wall surface. In an exemplary embodiment, a sigma filter may be used to remove noise. Furthermore, machine learning (ML) or deep learning (DL) techniques may be used to remove noise. For example, unsupervised cluster techniques may be used to detect outliers in the 3D point cloud data and separate the outliers. In another example, a convolutional neural network (CNN) may be used to remove noise from the 3D point cloud data. In yet another example, K-nearest neighbors (KNN) can be applied. In an exemplary embodiment, when a 6 sigma filter is used, outliers greater than +3σ and less than −3σ are removed. The formula for the 6 sigma filter is shown in Equation 1.

[0041]

number

[0042] where c=x, y, and z are the coordinates of the 3D point cloud data, and μ is the mean of N points.

[0043] The 3D point cloud data is unstructured data. Further processing is required to obtain coordinates for the top charge surface and eliminate points due to dust and blast furnace walls, which are converted into structured data by the data conversion means. The data conversion means is configured with coordinate shift logic for the structured points. The tip of the optical unit 102 can be considered as the reference origin of the coordinates, and the new origin is shifted along the centerline of the furnace at the height of the design stock level of the furnace. The one or more filters are configured to identify points that are on the walls of the furnace by comparing them with the points generated for the walls of the furnace. The one or more filters are also configured with a multi-frame comparison method, in which the 3D point cloud data from multiple frames captured by the optical means 102 within a predefined time frame (e.g., 5 seconds) is compared. While the static points from the top charge surface are retained, the dynamic points due to dust particles in these frames are identified and removed. The resulting 3D point cloud data is only for the top furnace surface.

[0044] An example representation of an image showing the 3D charge profile distribution 302 is shown in FIG. 3d.

[0045] In one embodiment, the scanning and measurement of the burden profile distribution may be performed during regular operation of the blast furnace 104. In one embodiment, the system may be configured to automatically operate at regular time intervals to perform the method 200. In one embodiment, the system may be configured to perform the steps upon receiving a trigger from a user associated with the blast furnace 104. In one embodiment, the burden profile distribution measured by the system may be used to control the amount of gas / hot air injected into the blast furnace 104. In one embodiment, the burden profile distribution measured by the system may be provided to a control unit to automatically control the injection of gas / hot air by analyzing the burden profile distribution.

[0046] In block 203, the processing unit 102 uses the noise-free 3D point cloud data to generate a 3D charge profile. A 3D top surface extraction means may be coupled with the data conversion means. The 3D top furnace surface extraction means may be configured to store coordinates for the 3D top charge surface measured at any instant. A layer profile visualization means may be coupled with the 3D top furnace surface extraction means, configured to generate a 3D layer profile using the top charge surface of the continuous charge thrown into the furnace. The 3D layer profile generator may use a volume balance mechanism to lower the 3D layer based on the volume of the charge thrown into the furnace for the charge to generate the resulting 3D layer profile in the blast furnace. A charge descent rate calculator means may be coupled with the 3D top charge surface extraction means and configured to compare x, y, and z coordinates of a plurality of 3D top charge surface measurements at a predefined frequency (e.g., 1 Hz) within a predefined duration (e.g., 2 minutes) for a charge introduced into the furnace. Further, a charge descent rate is calculated at each point along the surface of the top furnace surface. The charge descent rate calculator means is configured with visualization means for low descent rate and high descent rate highlighting areas.

[0047] 2, the method 200 may include one or more blocks for performing a process within the phased array based LiDAR unit 101. The method 200 may be described in the general context of computer-executable instructions. Generally, computer-executable instructions may include routines, programs, objects, components, data structures, procedures, modules, and functions that perform particular functions or implement particular abstract data types.

[0048] The order in which method 200 is described should not be construed as a limitation, as any number of the described method blocks can be combined in any order to implement the method. Additionally, individual blocks can be deleted from the method 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.

[0049] The LiDAR unit can be eliminated, eliminating the need for moving parts for efficient scanning. Furthermore, the mechanical errors caused by such moving parts are also reduced. Also, the system can operate at any time without interfering with the normal operation of the blast furnace.

[0050] An embodiment of the present disclosure provides for performing efficient scanning and measurement of the charge profile distribution. Higher resolution of the charge profile distribution can be achieved by performing interpolation of the data acquired from the scanned area.

[0051] "An embodiment," "embodiment," "embodiments," "the embodiment," "the embodiment," "one or more embodiment," "some embodiments," and "one embodiment" mean "one or more (but not all) embodiments of the invention," unless otherwise specified.

[0052] The words "including," "comprising," "having," and variations thereof mean "including but not limited to," unless expressly stated otherwise.

[0053] The listing of enumerated items does not imply that any or all of the items are mutually exclusive, unless expressly stated otherwise.

[0054] The terms "a," "an," and "the" mean "one or more" unless otherwise specified.

[0055] A description of an embodiment with several components in communication with each other does not imply that all such components are required. Rather, a variety of optional components are described to illustrate the wide variety of possible embodiments of the present invention.

[0056] It will be readily apparent that when a single device or article is described herein, multiple devices / articles (whether they cooperate or not) may be used in place of the single device / article. Similarly, when multiple devices or articles are described herein (whether they cooperate or not), it will be readily apparent that a single device / article may be used in place of the multiple devices or articles, or a different number of devices / articles may be used in place of the number of devices or programs shown. The functionality and / or features of a device may alternatively be embodied by one or more other devices not explicitly described as having such functionality / features. Thus, other embodiments of the invention need not include the device itself.

[0057] The operations depicted in FIG. 2 depict certain events occurring in a certain order. In alternative embodiments, certain operations may be performed in a different order, modified, or removed. Furthermore, steps may be added to the logic above and still be consistent with the described embodiment. Additionally, operations described herein may occur sequentially or certain operations may be processed in parallel. Still further, operations may be performed by a single processing unit or by distributed processing units.

[0058] Finally, the language used herein has been selected primarily for readability and instructional purposes, and not to delineate or limit the subject matter of the invention. Accordingly, it is intended that the scope of the invention be limited not by this detailed description, but rather by any claims that arise in applications based on the invention. Accordingly, the disclosure of 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.

[0059] While various aspects and embodiments are disclosed herein, other aspects and embodiments will be apparent to those of ordinary skill in the art. The various aspects and embodiments disclosed herein are for illustrative purposes only and are not intended to be limited in true scope by the following claims. [Explanation of symbols]

[0060] [Table 1]

Claims

1. 1. A system for measuring a burden profile in a blast furnace, comprising: a Light Detection and Ranging (LiDAR) unit configured to scan a top charge surface within the blast furnace and capture 3D point cloud data of the top charge surface; a processing unit configured to filter noise from the 3D point cloud data of the top charge surface and to generate a 3D charge profile using the noise-filtered 3D point cloud data; A system comprising:

2. 2. The system of claim 1, wherein a LiDAR unit is positioned inside the blast furnace to capture the top charge surface.

3. The LiDAR unit includes: a transmitter configured to transmit and a receiver configured to receive signals from the top charge surface, wherein the LiDAR unit is oriented at a predefined angle on an interior surface of the blast furnace; The system of claim 1 , comprising:

4. The system of claim 1 , wherein the processing unit comprises a noise reduction unit, a data separation unit, and a map generation unit.

5. The system of claim 4 , wherein the noise reduction unit comprises one or more filters for removing the noise from the 3D point cloud data.

6. The system of claim 4 , wherein the data separation unit is configured to separate the 3D point cloud data of the top charge surface from 3D point cloud data of a furnace wall surface.

7. The system of claim 4 , wherein the map generation unit uses the 3D point cloud data to generate the 3D charge profile.

8. A method for measuring a burden profile distribution in a blast furnace, comprising: scanning a top charge surface within the blast furnace and capturing 3D point cloud data of the top charge surface using a Light Detection and Ranging (LiDAR) unit; filtering out noise from the 3D point cloud data of the top charge surface by a processing unit; and generating, by the processing unit, a 3D charge profile using the noise filtered 3D point cloud data; A method comprising:

9. 9. The method of claim 8, wherein scanning the top charge profile is performed at a predefined angle from an interior surface of the blast furnace.

10. The method of claim 8 , wherein the 3D point cloud data is filtered to reduce noise from the 3D point cloud data.

11. 11. The method of claim 10, comprising separating the 3D point cloud data of the top charge surface from 3D point cloud data of a blast furnace wall surface.

12. 9. The method of claim 8, wherein the 3D burden layer profile is generated using the 3D point cloud data based on a burden drop calculated using a volume of the burden provided to the blast furnace.

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