Description:TECHNICAL FIELD
Present disclosure relates in general to a field of metallurgy and furnace. Particularly, but not exclusively, the present disclosure relates to method and system for detecting defect in arrangement of grate bars in an induration furnace of pellet plant.

BACKGROUND OF THE DISCLOSURE

In steel industry, pellet plant is a crucial part of integrated steel plant. Pelletizing is an agglomeration process which converts very fine-grained iron ore into balls of a certain diameter range (i.e., 10-20mm) known as pellets. A stationary bed of pellets is transported on an endless travelling grate bars called induration conveyor system, to process the pellets before feeding to the blast furnace as raw material. The processing of the pellets may include drying, oxidation, sintering, cooling and so on. The bed of pellets is arranged in an organized way in each of the plurality of cars of the conveyor system. The bed of pellets is supported using plurality of grate bars in the plurality of cars.

Amount of the pellets which is to be provided to the blast furnace is predefined and shortage of the pellets may adversely impact volume of iron making by the blast furnace. There may be significant loss in production of the pellets due to unplanned maintenance caused by defects in arrangement of the grate bars. With passage of time during processing of the pellets, shape of grate bars may change. At times, some grate bars may dislodge from its frame at base of corresponding car. Due to such defects, the pellets may fall off from the conveyor system via the defected grate bars, causing loss in the pellets.

Currently, a person manually monitors the conveyor system to detect the defect in the arrangement of the grate bars. The pellet plant is incapable of reliably identifying defects in the conveyor system all time, due to current practice of sporadic manual monitoring. Also, the person at the conveyor system may not be able to identify defect accurately due to hostile conditions at the pellet plant. Also, when the defect is not detected at initial stage, and eventuallythe defect worsens, loss of the pellet may occur. Thereby, affecting volume of iron making by the blast furnace.

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 known 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.

Embodiments of the present disclosure relate to a system for detecting defect in arrangement of grate bars of a conveyor system implemented in an induration furnace of pellet plant. The system comprises a first unit, a second unit and a processing unit for detecting the defect. The first unit captures a first image related to plurality of grate bars arranged in a car of plurality of cars in the induration furnace. The second unit captures a second image related to unique code embossed on the car, said unique code represents identification data of the car. The processing unit is in communication with the first unit and the second unit. The processing unit is configured to dynamically receive the first image and the second image from the first unit and the second unit, respectively. Further, the processing unit identifies defect in arrangement of the plurality of grate bars in the car, using the first image and identifies the identification data of the car using the second image, upon identification of the defect.

Embodiments of the present disclosure further discloses a method for detecting defect in arrangement of grate bars of a conveyor system implemented in an induration furnace of pellet plant. For detecting the defect, a first image related to plurality of grate bars arranged in a car of plurality of cars in the induration furnace is captured. Further, a second image related to unique code embossed on the car is captured. The unique code represents identification data of the car. Defect in arrangement of the plurality of grate bars in the car is identified using the first image. Upon identification of the defect, the identification data of the car is identified using the second image.

Embodiments of the present disclosure further discloses a processing unit for detecting defect in arrangement of grate bars of a conveyor system implemented in an induration furnace of pellet plant. The processing unit comprises a processor and a memory communicatively coupled to the processor. The memory stores processor-executable instructions, which, on execution, cause the processor to detect the defect. For detecting the defect, a first image captured by a first unit, and a second image captured by a second unit is received dynamically by the processing unit. The first image is related to plurality of grate bars arranged in a car of plurality of cars in a conveyor system implemented in an induration furnace and the second image is related to unique code embossed on the car. The unique code represents identification data of the car. Further, defect in arrangement of the plurality of grate bars in the car is identified using the first image. Upon identification of the defect, the identification data of the car is identified using the second image.

Embodiments of the present disclosure further discloses a method for detecting defect in arrangement of grate bars of a conveyor system implemented in an induration furnace of pellet plant. For detecting the defect, the method includes dynamically receiving a first image captured by a first unit, and a second image captured by a second unit. The first image is related to plurality of grate bars arranged in a car of plurality of cars in a conveyor system implemented in an induration furnace and the second image is related to unique code embossed on the car. The unique code represents identification data of the car. Further, defect in arrangement of the plurality of grate bars in the car is identified using the first image. Upon identification of the defect, the identification data of the car is identified using the second image.

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 accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, serve to explain the disclosed principles. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and regarding the accompanying figures, in which:

Figures 1a and 1b illustrate schematic representations of a system for detecting defect in arrangement of grate bars of a conveyor system implemented in an induration furnace of pellet plant, in accordance with some embodiments of present disclosure;

Figure 2 shows a detailed block diagram of a processing unit for detecting defect in arrangement of grate bars of a conveyor system implemented in an induration furnace of pellet plant, in accordance with some embodiments of the present disclosure;

Figure 3 shows a flowchart illustrating an exemplary method for detecting defect in arrangement of grate bars of a conveyor system implemented in an induration furnace of pellet plant, in accordance with some embodiments of present disclosure;

Figures 4a-4c illustrate exemplary embodiments associated with a system for detecting defect in arrangement of grate bars of a conveyor system implemented in an induration furnace of pellet plant, in accordance with some embodiments of present disclosure; and

Figure 5 illustrates a block diagram of an exemplary computer system for implementing embodiments consistent with the 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
In the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however that it is not intended to limit the disclosure to the forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternative falling within the scope of the disclosure.

The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device or 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 setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or method.

The terms “includes”, “including”, or any other variations thereof, are intended to cover a non-exclusive 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.

Present disclosure discloses a system and method for detecting defect in arrangement of grate bars of a conveyor system implemented in an induration furnace of pellet plant. The present disclosure proposes to use image feeds of the conveyor system and process the image feeds to detect the defect. Along with detecting the detect, the proposed system and method proposes to detect an exact location of the defect by identifying car related to the grates. By implementing such detection system in the pellet plant, automated and accurate detection of the defect may be achieved. Also, alerting based on the detection is provided to a user to take immediate actions to rectify the defect.

Figures 1a and 1b illustrate schematic representation of a system 101 for detecting defect in arrangement of grate bars of a conveyor system implemented in an induration furnace of pellet plant. The system 101 may be implemented in environment 100 of the pellet plant. The environment 100 may be inside the pellet plant. The system 101 is associated with a conveyor system 102 of the induration furnace of the pellet plant. The induration furnace is used for pelletizing which is an agglomeration process for converting very fine-grained iron ore into balls of a certain diameter range known as pellets. Diameter of the pellets may range from 10mm to 20mm. The pellets are fed to the blast furnace as raw material. As shown in Figure 1a, plurality of pellets 103 are transported and heated using the conveyor system 102 and furnace below. The plurality of pellets 103 are arranged on plurality of grate bars in the plurality of cars of the conveyor system 102. Usually, the conveyor system 102 may include 282 cars. Each of the plurality of cars are embossed with unique code 104 representing respective car. Each car has vertical rails called grate bars with a gap of 5mm between the grate bars. The gap ensures uniform heating and cooling of pellets.

During the transportation, the plurality of pellets is processed by passing through multiple zones on way to the blast furnace. The multiple zones may include, but are not limited to, heating zone, drying zone, oxidation zone, sintering zone, cooling zone and so on. Due to the processing of the pellets, the conveyor system 102 along with the plurality of pellets are mostly in hostile environment with adverse conditions. Such hostile environment may have its effect on the plurality of grate bars. The plurality of grate bars is subjected to high stress from thermal load due to high temperature variation between heating in furnace and cooling down from ambient air in every cycle. As time passes, the plurality of grate bars starts to dislodge causing the gap to be widen significantly. Sometimes, due to dislodging, the gap may be greater than 40mm. Dislodging of one grate bar may create a domino effect and accelerate deterioration of others grate bars as well. In such scenarios, the pellets may fall off through the gap leading to unplanned shut down to replace defective car and incur production loss.

The proposed system 101 is configured to detect defect in the arrangement of the plurality of grate bars. The system 101 comprises a first unit 105, a second unit 106 and a processing unit 107. The first unit 105 is configured to capture a first image related to plurality of grate bars arranged in a car of plurality of cars in an induration furnace. The second unit 106 is configured to capture a second image related to unique code embossed on the car. The unique code represents identification data of the car. As shown in Figure 1b, the first unit 105 and the second unit 106 may be an image capturing units. For example, the first unit 105 and the second unit 106 may be camera which is placed in the pellet plant to capture the first image and the second image. In an embodiment, the first unit may capture video of the plurality of grate bars arranged in the car. A frame from the video may be extracted as the first image.

Due to hostile conditions in environment of the pellet plant, the conveyor system 102 may lack proper lighting or may be covered with dust. In such cases, in an embodiment, as shown in Figure 1b, the system 101 further comprises a lighting unit 108 and a dust dispenser unit 109, deployed over the lightning unit (108). In an embodiment, the lighting unit 108 may be configured to illuminate the car with light for capturing the first image and the second image. The lighting unit 108 may be placed at the conveyor system 102 to illuminate the conveyor system 102 with the light. In an embodiment, the lighting unit 108 may be integral part of at least one of the first unit 105 and the second unit 106. In an embodiment, the lighting unit 108 may illuminate the conveyor system 102 with light when at least one of the first unit 105 and the second unit 106 are triggered to capture the first image and the second image, respectively. In an embodiment, the lighting unit 108 may be any light illuminating device which is configured to illuminate the conveyor system 102 with light. For example, the lighting unit 108 may be a torch or a spotlight or an array of Light Emitting Diodes (LEDs) and so on. In an embodiment, each of the first unit 105 and the second unit 106 may be associated with a dedicated lighting unit (not shown in the figures). In an embodiment, the trigger unit 110 may also be connected with the lighting unit 108 and may be configured to trigger the lighting unit 108 while triggering at least one of the first unit 105 and the second unit 106. In an embodiment, the trigger unit 110 may implement laser technique to identify if the car is in the field of view of the first unit 105 and the second unit 106.

In an embodiment, the system 101 may include a dust dispenser unit 109 which is configured to dispense dust from environment of the car while capturing at least one of the first image and the second image. In an embodiment, the dust dispenser unit 109 aims in removing dust from the environment by using a fan or pressurized air or suction mechanism. In an embodiment, any other technique, known to a person skilled in the art, may be implemented as the dust dispenser unit 109, to dispense the dust. In an embodiment, as shown in Figure 1b, a single dust dispenser unit 109 may be used while capturing both the first image and the second image. Such single dust dispenser unit may be placed nearer to the conveyor system 102. In an embodiment, each of the first unit 105 and the second unit 106 may be connected with a dedicated dust dispenser unit. In such case, respective dust dispenser unit may dispense dust at the time of capturing of the first image and the second image. In an embodiment, the trigger unit 110 may also be connected the dust dispenser unit 109 and may be configured to trigger the dust dispenser unit 109 when capturing the image from at least one of the first unit 105 and the second unit 106.

Figure 2 shows a detailed block diagram of the processing unit 107 of the system 101. The processing unit 107 may include one or more processors 201, Input/Output (I/O) interface 202 and a memory 203. In some embodiments, the memory 203 may be communicatively coupled to the one or more processors 201. The memory 203 stores instructions, executable by the one or more processors 201, which on execution, may cause the processing unit 107 to identify the defect in arrangement of the plurality of grate bars. In an embodiment, the memory 203 may include one or more modules 204 and data 205. The one or more modules 204 may be configured to perform the steps of the present disclosure using the data 205, to identify the defect. In an embodiment, each of the one or more modules 204 may be a hardware unit which may be outside the memory 203 and coupled with the processing unit 107. In an embodiment, the processing unit 107 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, cloud server and the like. In an embodiment, the processing unit 107 may be dedicated server or a cloud-based server, which is configured to communicate with the components of the system 101 to detect and notify the defect.

The data 205 and the one or more modules 204 in the memory 203 of the processing unit 107 is described herein in detail.

In one implementation, the one or more modules 204 may include, but are not limited to, an image reception module 206, a defect identify module 207, an identification data identify module 208, and one or more other modules 209, associated with the processing unit 107.

In one implementation, the data 205 in the memory 203 may include first image data 210, second image data 211, defect data 212, identification data 213, and other data 214 associated with the processing unit 107.

In an embodiment, the data 205 in the memory 203 may be processed by the one or more modules 204 of the processing unit 107. In an embodiment, the one or more modules 204 may be implemented as dedicated units and when implemented in such a manner, said modules may be configured with the functionality defined in the present disclosure to result in a novel hardware. As used herein, the term module may refer to an Application Specific Integrated Circuit (ASIC), an electronic circuit, a Field-Programmable Gate Arrays (FPGA), Programmable System-on-Chip (PSoC), a combinational logic circuit, and/or other suitable components that provide the described functionality.

The one or more modules 204 of the present disclosure function to identify the defect in the arrangement of the plurality of grates. The one or more modules 204 along with the data 205, may be implemented in any device or system, for the detection.

The processing unit 107 is in communication with the first unit 105 and the second unit 106. The processing unit 107 may be placed in Level 2 room of the pellet plant. In an embodiment, the processing unit 107 may communicate with at least one of the first unit 105 and the second unit 106 via a communication network (not shown in the figure). 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, a dedicated communication network may be implemented to establish communication between the processing unit 107 and each of the first unit 105 and the second unit 106.

The image reception module 206 of the processing unit 107 may be configured to dynamically receive the first image and the second image from the first unit 105 and the second unit 106, respectively. In an embodiment, the processing unit 107 may receive the first image and the second image via the I/O interface 202. In an embodiment, as shown in Figure 1b, the system 101 may include a trigger unit 110 connected with the first unit 105. In an embodiment, the trigger unit 110 may be configured to provide a trigger to the first unit 105 to capture the first image, wherein the trigger is provided when the car is aligned to field of view of the first unit 105. In an embodiment, the trigger unit 110 may be configured to trigger the second unit 106 for capturing the second image when triggering the first unit 105. In an embodiment, each of the first unit 105 and the second unit 106 may be associated with a dedicated trigger unit 110. In an embodiment, the trigger unit 110 may be integral part of at least one of the first unit 105 and the second unit 106. The trigger unit 110 may implement image processing techniques to determine if the car is aligned with the field of view. In an embodiment, the trigger unit 110 may be a sensor placed in the conveyor system 102 to track movement of the plurality of cars. One or more other techniques, known to a person skilled in the art, may be implemented to trigger at the least one of the first unit 105 and the second unit 106, for capturing the first image and the second image. In an embodiment, plurality of first images and plurality of second images may be captured sequentially for the plurality of cars. The plurality of first images may be stored as first image data 210 in the memory 203. The plurality of second images may be storesd as second image data 211 in the memory 203.

Further, the defect identify module 207 of the processing unit 107 may be configured to identify defect in arrangement of the plurality of grate bars in the car, using the first image. The first image may be dynamically processed by the defect identify module 207 upon capturing of the first image. In an embodiment, the first image may be stored in the memory 203 and processed at a predefined time to detect the defect. In an embodiment, the defect identify module may be configured to detect the defect by detecting presence of one or more gaps between consecutive grate bars amongst the plurality of grate bars in the first image. Further, area of each of the one or more gaps is determined. The area of each of the one or more gaps is compared with a predefined threshold value. The defect is identified at location of a gap from the one or more gaps, when the area of the gap is greater than the predefined threshold value. In an embodiment, the identified defect may be stored as the defect data 212 in the memory 203. In an embodiment, information related to presence of the one or more gaps, the area of the one or more gaps and the predefined threshold value may be stored as the other data 214 in the memory 203.

Upon identification of the defect, the identification data identify module may be configured to identify the identification data 213 of the car in which the defect is detected. The identification data 213 is identified using the second image. In an embodiment, the second image may be dynamically processed upon capturing the second image. In an embodiment, the second image may be received and pre-stored in the memory 203. Such pre-stored second image may be processed when the defect is detected using corresponding first image. In an embodiment, the identification data identify module 208 may be configured to identify the identification data 213 by computing feature image of the second image. Further, the feature information is compared with plurality of predefined images to identify a matched predefined image amongst the plurality of predefined images for the feature image. In an embodiment, the plurality of predefined images is associated with identification data 213 of the plurality of cars. Further, the identification data 213 associated with the matched predefined image is selected to be the identification data 213 of the car. In an embodiment, the feature information, the plurality of predefined images, information related to comparison and information related to matched predefined data may be stored as other data 214, in the memory 203.

In an embodiment, the system 101 may further include an alerting unit 111 as shown in Figure 1b. In an embodiment, the alerting unit 111 may be connected with the processing unit 107. Upon identifying the defect and the identification data 213, the processing unit 107 may be configured to communicate information related to the defect and the identification data 213 to the alerting unit 111. Upon receiving such information, the alerting unit 111 may be configured to alert a user associated with the induration furnace, regarding the defect. In an embodiment, the alerting unit 111 may be associated with a display unit for displaying details of the defect to the user using the display unit. In an embodiment, the alerting unit 111 may be connected with the conveyor system 102 and may be configured to abort operation of the induration furnace. One or more other methods may be implemented in the alerting unit 111 to alert the user regarding the defect.

Figure 3 shows a flowchart illustrating an exemplary method for detecting defect in the arrangement of grate bars of the conveyor system 102.

Using the proposed system 101, the steps of method of detecting the defect may be automated, thereby eliminating the need of manual intervention for the detection. Further, using the proposed method accurate detection of the defect and the identification details of the defect maybe identified.

At block 301, the first unit 105 of the system 101 may be configured to capture first image related to the plurality of grate bars arranged in the car. In an embodiment, the first unit 105 may be a camera configured to capture the first image. In an embodiment, the first unit 105 may be placed in the pellet plant near the conveyor system 102. The first unit 105 may be placed with a predefined orientation, such the field of view of the first unit 105 covers the plurality of grate bars on the plurality of cars. In an embodiment, the first unit 105 may be mounted at roof of maintenance bay in the pellet plant, to capture the first image. In an embodiment, the first image may include image for a car with bed of pellets placed on plurality of grate bases of the car. The first unit 105 may be configured to capture first image for each of the plurality of cars sequentially.

At block 302, when capturing the first image, the second unit 106 of the system 101 may be configured to capture the second image. The second image is of the unique code of the car for which first image is captured. In the conveyor system 102 of the pellet plant, each of the plurality of cars are embossed with respective unique code representing the corresponding car. This unique code may be used to identify a particular car. In an embodiment, unique code may be alpha numeric code, all-numbers code, all-letters code, Quick Response (QR) code or any code known to a person skilled in the art. Image processing of such unique code enables in identifying corresponding car. In an embodiment, the second unit 106 may be placed in the pellet plant near the conveyor system 102. The second unit 106 may be placed with a predefined orientation, such the field of view of the second unit 106 covers the unique code of the car for which the first image is captured. In an embodiment, the second unit 106 may be placed next to the first camera to capture the unique code of the car. In an embodiment, the first image may include side railing of the car withembossment of the unique code. The second unit 106 may be configured to capture second image for each of the plurality of cars sequentially.

In an embodiment, each of the first unit 105 and the second unit 106 may be configured to have specific focal length to capture the first image and the second image, respectively. The first unit 105 and the second unit 106 simultaneously capture the first image and the second image, respectively. In an embodiment, the movement of the plurality of cars is controller such that each of the plurality of cars is stationed when a car in within field of view of the first unit 105 and the second unit 106. The plurality of cars resume the movement upon capturing of the first image and the second. In an embodiment, the plurality of cars may be stationed for a predefined duration of time, and the first unit 105 and the second unit 106 may be configured to capture the first image and the second image during the predefined duration of time. An exemplary representation of the first image of the plurality of grate bars is shown as image 401 in Figure 4a. An exemplary representation of the second image of the unique code is shown as image 407 in Figure 4b.

At block 303, the processing unit 107 of the system 101 may be configured to identify defect in arrangement of the plurality of grate bars in the car. The defect in the arrangement may be identified using the fist image. The first image may be dynamically processed by the processing unit 107 upon capturing of the first image. In an embodiment, one or more image processing techniques may be used on the first image to detect the defect. For example, consider the image 401 from Figure 4a as the first image. Initially, the image 401 may be pre-processed. In the pre-processing, suitable affine transformation is applied on the image. Such transformation may be achieved by performing search in a confined parameter range involving 3?? rotation, (????, ????, ????) and translation variables, (????, ????, ????), respectively. By performing such perceptive transformation, view of the image 401 may be corrected. Corrected view of the image 401 is shown as image 402 in Figure 4a. Further, the image may be processed to segment region of interest as represented in image 403 in Figure 4a. By such segmentation. Gaps between the grate bars may be easily identified as shown in image 404 in Figure 4a. In image 404, the one or more gaps may be identified as gap 405.1 and gap 405.2. In an embodiment, using the image 404, the processing unit 107 may be configured to detect presence of one or more gaps between consecutive grate bars amongst the plurality of grate bars in the first image i.e., the image 401. In an embodiment, the image 404 may be compared with previously captured images of the car to identify the one or more gaps. One or more techniques, known to a person skilled in the art, may be implemented to detect the presence of the one or more gaps. Further, area of each of the one or more gaps is determined. In an embodiment, the area of the one or more gaps may be determined using Computer-Aided Design (CAD) drawings. The area of each of the one or more gaps is compared with a predefined threshold value. The defect is identified at location of a gap from the one or more gaps, when the area of the gap is greater than the predefined threshold value. In an embodiment, the predefined threshold value may be 5mm. When area of a gap is greater than 5mm, the car including grate bars with such gap may be identified to be defective.

Further, in an embodiment, upon detecting the defect, the processing unit 107 may be configured to classify the defect to be one of plurality of stages of the defect. For the classification, defection percentage may be calculated for each of the one or more gaps. In an embodiment, the defect percentage of a gap may be calculated using equation 1, given below:

Defect percentage=(Area of the gap)/(Total area of the one or more gaps) X100……………(1)

Using the defect percentage, the defect may be classified to be associated with one of stage 1, stage 2, stage 3, stage 4, and stage 5 of the defect. Image 406.1 represents stage 1 of defect with minimal defect percentage. In stage 1, single pellet may get stuck and jammed for long time between two grate bars. Also, such stage of defect may arise any time during the palletization. Image 406.2 represents stage 2 of the defect with defect slightly greater than the defect in stage 1. Stage 2 of the defect may occur when adjacent grate bars are continuously heated until the grate bars crack and fall off. Stage 2 of the defect may arise some months after stage 1 of the defect. Image 406.3 represents stage 3 of the defect with defect greater than the defect in stage 2. Such stage may occur with more space between the grate bars. Thus, easy movement of the pellets is possible in stage 3 of the defect. Also, more gaps may be formed because of the movement. Stage 3 may occur any time after stage 2 of the defect. Image 406.4 represents stage 4 of the defect with defect greater than the defect in stage 3. Such stage may occur with higher amount of gaps and lead to quicker degeneration of the grate bars. Higher number of grate bars may crack and fall off from the car. Process disturbance of the induration furnace may be noticed in this stage of the defect. Stage 4 may occur approximately 1 to 3 weeks after stage 3. Image 406.5 represents stage 5 of the defect with defect greater than the defect in stage 4. Such stage may occur with entire pellet row being fallen off from the conveyor system 102. In this stage, major process disturbances may occur with premature equipment failure.

At block 304, upon identification of the defect, the processing unit 107 is configured to identify the identification data 213 of the car in which the defect is detected. The identification data 213 is identified using the second image. In an embodiment, the second image may be dynamically processed upon capturing the second image. In an embodiment, the identification data 213 may be identified by template matching using normalized cross correlation search. Every image of unique code i.e., the second image is matched with the plurality of predefined images which are pre-stored. Consider the image 407 from Figure 4b, representing the second image. The image 407 is image of unique code embossed on the car for which defect is detected. In an embodiment, multiple image processing techniques may be implemented on the image 407 to identify the identification data 213. Initially, perceptive transformation is performed in the image 407 to obtain image 408 with corrected view. Feature extraction may be performed on the image 408 to compute feature image i.e., image 409. Further, the feature information is compared with plurality of predefined images to identify a matched predefined image amongst the plurality of predefined images for the feature image. An exemplary representation of the plurality of predefined images is shown in image 410. The plurality of predefined images represent unique code associated with the plurality of cars in the conveyor system 102. Each of the plurality of predefined images are labelled with corresponding unique code of the car. For example, unique codes may be “227C10WC6SY”, “228C10WC6SY”, “229C10WC6SY”, “230C10WC6SY” and the like. By performing matching with the plurality of predefined images, a score may be computed for the image 409 with each of the plurality of predefined images. For example, below score may be computed for the image 409.

Unique code Score
227C10WC6SY 0.104
228C10WC6SY 0.114
229C10WC6SY 0.206
230C10WC6SY 0.122
019D09W06SY 0.989
319D09W06SY 0.814
019D10W06SY 0.850

The highest score is obtained for predefined image with unique code “019D09W06SY”. Thus, the identification data 213 for the image 409 may be identified as “019D09W06SY”. The car with unique code “019D09W06SY” is detected to be with defect in the arrangement of the grate bars.

Upon identifying the defect and the identification data 213, the processing unit 107 may be configured to communicate information related to the defect and the identification data 213 to the alerting unit 111. In an embodiment, the alerting unit 111 may be connected with the conveyor system 102 and may be configured to abort operation of the induration furnace. In an embodiment, the alerting unit 111 may be associated with a display unit for displaying details of the defect to the user using the display unit. An exemplary representation of a display 411 of the display unit is illustrated in Figure 4c. As shown in the display 411, based on the detection of the defect, the car with the defect may be highlighted to the user. Also, details of the defect such as the unique of the car with the defect, the defect percentage of the car and also stage of the defect may be indicated to the user. Images captured by the first unit and the second unit 106 along with processed images may also be provided to the user. Such display helps in easy identification and rectification of the defect.

As illustrated in Figure 3, the method 300 may include one or more blocks for executing processes in the system 101. The method 300 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 300 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.

Computing System
Figure 5 illustrates a block diagram of an exemplary computer system 500 for implementing embodiments consistent with the present disclosure. In an embodiment, the computer system 500 is used to implement the processing unit 107 for detecting the defect in arrangement of the plurality of grate bars of the induration furnace in the pellet plant. The computer system 500 may include a central processing unit (“CPU” or “processor”) 502. The processor 502 may include at least one data processor for executing processes in Virtual Storage Area Network. The processor 502 may include specialized processing units such as, integrated system (bus) controllers, memory management control units, floating point units, graphics processing units, digital signal processing units, etc.

The processor 502 may be disposed in communication with one or more input/output (I/O) devices 509 and 510 via I/O interface 501. The I/O interface 501 may employ communication protocols/methods such as, without limitation, audio, analog, digital, monaural, RCA, stereo, IEEE-1394, serial bus, universal serial bus (USB), infrared, PS/2, BNC, coaxial, component, composite, digital visual interface (DVI), high-definition multimedia interface (HDMI), radio frequency (RF) antennas, S-Video, VGA, IEEE 802.n /b/g/n/x, Bluetooth, cellular (e.g., code-division multiple access (CDMA), high-speed packet access (HSPA+), global system for mobile communications (GSM), long-term evolution (LTE), WiMax, or the like), etc.

Using the I/O interface 501, the computer system 500 may communicate with one or more I/O devices 509 and 510. For example, the input devices 509 may be an antenna, keyboard, mouse, joystick, (infrared) remote control, camera, card reader, fax machine, dongle, biometric reader, microphone, touch screen, touchpad, trackball, stylus, scanner, storage device, transceiver, video device/source, etc. The output devices 510 may be a printer, fax machine, video display (e.g., cathode ray tube (CRT), liquid crystal display (LCD), light-emitting diode (LED), plasma, Plasma Display Panel (PDP), Organic light-emitting diode display (OLED) or the like), audio speaker, etc.

In some embodiments, the computer system 500 may consist of the processing unit 107. The processor 502 may be disposed in communication with a communication network (not shown in figure) via a network interface 503. The network interface 503 may communicate with the communication network. The network interface 503 may employ connection protocols including, without limitation, direct connect, Ethernet (e.g., twisted pair 10/100/1000 Base T), transmission control protocol/internet protocol (TCP/IP), token ring, IEEE 802.11a/b/g/n/x, etc. 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, etc. Using the network interface 503 and the communication network, the computer system 500 may communicate with at least one of a first unit 511, a second unit 512 and an alerting unit 513, for detecting the defect in the arrangement. The network interface 503 may employ connection protocols include, but not limited to, direct connect, Ethernet (e.g., twisted pair 10/100/1000 Base T), transmission control protocol/internet protocol (TCP/IP), token ring, IEEE 802.11a/b/g/n/x, etc.

The communication network includes, but is not limited to, a direct interconnection, an e-commerce network, a peer to peer (P2P) network, local area network (LAN), wide area network (WAN), wireless network (e.g., using Wireless Application Protocol), the Internet, Wi-Fi, and such. The first network and the second network may either be a dedicated network or a shared network, which represents an association of the different types of networks that use a variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP), etc., to communicate with each other. Further, the first network and the second network may include a variety of network devices, including routers, bridges, servers, computing devices, storage devices, etc.

In some embodiments, the processor 502 may be disposed in communication with a memory 505 (e.g., RAM, ROM, etc. not shown in Figure 5) via a storage interface 504. The storage interface 504 may connect to memory 505 including, without limitation, memory drives, removable disc drives, etc., employing connection protocols such as, serial advanced technology attachment (SATA), Integrated Drive Electronics (IDE), IEEE-1394, Universal Serial Bus (USB), fibre channel, Small Computer Systems Interface (SCSI), etc. The memory drives may further include a drum, magnetic disc drive, magneto-optical drive, optical drive, Redundant Array of Independent Discs (RAID), solid-state memory devices, solid-state drives, etc.

The memory 505 may store a collection of program or database components, including, without limitation, user interface 506, an operating system 507, web browser 508 etc. In some embodiments, computer system 500 may store user/application data, such as, the data, variables, records, etc., as described in this disclosure. Such databases may be implemented as fault-tolerant, relational, scalable, secure databases such as Oracle ® or Sybase®.

The operating system 507 may facilitate resource management and operation of the computer system 500. Examples of operating systems include, without limitation, APPLE MACINTOSH® OS X, UNIX®, UNIX-like system distributions (E.G., BERKELEY SOFTWARE DISTRIBUTIONTM (BSD), FREEBSDTM, NETBSDTM, OPENBSDTM, etc.), LINUX DISTRIBUTIONSTM (E.G., RED HATTM, UBUNTUTM, KUBUNTUTM, etc.), IBMTM OS/2, MICROSOFTTM WINDOWSTM (XPTM, VISTATM/7/8, 10 etc.), APPLE® IOSTM, GOOGLE® ANDROIDTM, BLACKBERRY® OS, or the like.

In some embodiments, the computer system 500 may implement a web browser 508 stored program component. The web browser 508 may be a hypertext viewing application, such as Microsoft Internet Explorer, Google Chrome, Mozilla Firefox, Apple Safari, etc. Secure web browsing may be provided using Hypertext Transport Protocol Secure (HTTPS), Secure Sockets Layer (SSL), Transport Layer Security (TLS), etc. Web browsers 508 may utilize facilities such as AJAX, DHTML, Adobe Flash, JavaScript, Java, Application Programming Interfaces (APIs), etc. In some embodiments, the computer system 500 may implement a mail server stored program component. The mail server may be an Internet mail server such as Microsoft Exchange, or the like. The mail server may utilize facilities such as ASP, ActiveX, ANSI C++/C#, Microsoft .NET, Common Gateway Interface (CGI) scripts, Java, JavaScript, PERL, PHP, Python, WebObjects, etc. The mail server may utilize communication protocols such as Internet Message Access Protocol (IMAP), Messaging Application Programming Interface (MAPI), Microsoft Exchange, Post Office Protocol (POP), Simple Mail Transfer Protocol (SMTP), or the like. In some embodiments, the computer system 500 may implement a mail client stored program component. The mail client may be a mail viewing application, such as Apple Mail, Microsoft Entourage, Microsoft Outlook, Mozilla Thunderbird, etc.

Furthermore, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present disclosure. A computer-readable storage medium refers to any type of physical memory on which information or data readable by a processor may be stored. Thus, a computer-readable storage medium may store instructions for execution by one or more processors, including instructions for causing the processor(s) to perform steps or stages consistent with the embodiments described herein. The term “computer-readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., be non-transitory. Examples include Random Access Memory (RAM), Read-Only Memory (ROM), volatile memory, non-volatile memory, hard drives, Compact Disc (CD) ROMs, DVDs, flash drives, disks, and any other known physical storage media.
media.

The described operations may be implemented as a method, system or article of manufacture using standard programming and/or engineering techniques to produce software, firmware, hardware, or any combination thereof. The described operations may be implemented as code maintained in a “non-transitory computer readable medium”, where a processor may read and execute the code from the computer readable medium. The processor is at least one of a microprocessor and a processor capable of processing and executing the queries. A non-transitory computer readable medium may include media such as magnetic storage medium (e.g., hard disk drives, floppy disks, tape, etc.), optical storage (CD-ROMs, DVDs, optical disks, etc.), volatile and non-volatile memory devices (e.g., EEPROMs, ROMs, PROMs, RAMs, DRAMs, SRAMs, Flash Memory, firmware, programmable logic, etc.), etc. Further, non-transitory computer-readable media may include all computer-readable media except for a transitory. The code implementing the described operations may further be implemented in hardware logic (e.g., an integrated circuit chip, Programmable Gate Array (PGA), Application Specific Integrated Circuit (ASIC), etc.).

An “article of manufacture” includes non-transitory computer readable medium, and /or hardware logic, in which code may be implemented. A device in which the code implementing the described embodiments of operations is encoded may include a computer readable medium or hardware logic. Of course, those skilled in the art will recognize that many modifications may be made to this configuration without departing from the scope of the invention, and that the article of manufacture may include suitable information bearing medium known in the art.

An embodiment of the present disclosure proposes an automated, reliable, and robust system capable of autonomously identifying and quantifying dislodged grate bars. Further, the system proposes to track defective car and provide a prediction of its lifetime with replacement notification for entire conveyor system. Such system eliminates need for a personnel to monitor for the defect in hostile conditions.

An embodiment of the present disclosure proposes early prediction of the defect by using image processing techniques which are fast and reliable. By implementing the proposed system, unplanned shutdowns and production loss occurring the pellet plant is eliminated. Also, the proposed system aids in improvement of efficiency and production capability of pellet plant with uninterrupted supply of pellets to blast furnace for iron making.

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 3 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.

Referral numerals:
Reference Number Description
100 Environment
101 System
102 Conveyor system
103 Plurality of pellets
104 Unique code
105 First unit
106 Second unit
107 Processing unit
108 Lighting unit
109 Dust dispenser unit
110 Trigger unit
111 Alerting unit
201 One or more processors
202 I/O interface
203 Memory
204 Modules
205 Data
206 Image reception module
207 Defect identify module
208 Identification data identify module
209 Other modules
210 First image data
211 Second image data
212 Defect data
213 Identification data
214 Other data
401-404 First images
405.1-405.2 One or more gaps
406.1-406.5 Stages of defect
407-409 Second images
410 Plurality of predefined images
411 Display
500 Computer System
501 I/O Interface
502 Processor
503 Network Interface
504 Storage Interface
505 Memory
506 User Interface
507 Operating System
508 Web Server
509 Input Devices
510 Output Devices
511 First unit
512 Second unit
513 Alerting unit

Claims:WE CLAIM:

1. A system (101) for detecting defect in arrangement of grate bars of a conveyor system (102) implemented in an induration furnace of pellet plant, the system (101) comprises:
a first unit (105) to capture a first image related to plurality of grate bars arranged in a car of plurality of cars in an induration furnace;
a second unit (106) to capture a second image related to unique code embossed on the car, said unique code represents identification data of the car;
a processing unit (107) in communication with the first unit (105) and the second unit (106), the processing unit (107) configured to:
dynamically receive the first image and the second image from the first unit (105) and the second unit (106), respectively;
identify defect in arrangement of the plurality of grate bars in the car, using the first image; and
identify the identification data of the car using the second image, upon identification of the defect.

2. The system (101) as claimed in claim 1, further comprises an alerting unit (111) to alert a user associated with the induration furnace, regarding the defect.

3. The system (101) as claimed in claim 2, wherein the alert comprises at least one of:
displaying details of the defect to the user using a display unit; and
aborting operation of the induration furnace.

4. The system (101) as claimed in claim 1, further comprises a trigger unit (110) configured to provide a trigger to the first unit (105) to capture the first image, wherein the trigger is provided when the car is aligned to field of view of the first unit (105).

5. The system (101) as claimed in claim 1, further comprises a lighting unit (108) configured to illuminate the car with light for capturing the first image and the second image.

6. The system (101) as claimed in claim 1, further comprises a dust dispenser unit (109) configured to dispense dust from environment of the car for capturing at least one of the first image and the second image.

7. The system (101) as claimed in claim 1, wherein identifying the defect using the first image comprises:
detecting presence of one or more gaps between consecutive grate bars amongst the plurality of grate bars in the first image;
determining area of each of the one or more gaps;
comparing area of each of the one or more gaps with a predefined threshold value; and
identifying the defect at location of a gap from the one or more gaps, when the area of the gap is greater than the predefined threshold value.

8. The system (101) as claimed in claim 1, wherein identifying the identification data of the car using the second image comprises:
compute feature image of the second image;
compare the feature information with plurality of predefined images to identify a matched predefined image amongst the plurality of predefined images for the feature image, wherein the plurality of predefined images is associated with identification data of the plurality of cars; and
select identification data associated with the matched predefined image to be the identification data of the car.

9. A method for detecting defect in arrangement of grate bars of a conveyor system (102) implemented in an induration furnace of pellet plant, the method comprising:
capturing a first image related to plurality of grate bars arranged in a car of plurality of cars in an induration furnace;
capturing a second image related to unique code embossed on the car, said unique code represents identification data of the car;
identifying defect in arrangement of the plurality of grate bars in the car, using the first image; and
identifying the identification data of the car using the second image, upon identification of the defect.

10. The method as claimed in claim 9, further comprising alerting a user associated with the induration furnace, regarding the defect.

11. The method as claimed in claim 10, wherein the alerting comprises at least one of:
displaying details of the defect to the user using a display unit; and
aborting operation of the conveyor system (102).

12. The method as claimed in claim 9, further comprising triggering to capture the first image when the car is aligned to field of view of the first unit (105).

13. The method as claimed in claim 9, further comprising illuminating the car with light for capturing the first image and the second image.

14. The method as claimed in claim 9, further comprising dispensing dust from environment of the car for capturing at least one of the first image and the second image.

15. The method as claimed in claim 9, wherein identifying the defect using the first image comprises:
detecting presence of one or more gaps between consecutive grate bars amongst the plurality of grate bars in the first image;
determining area of each of the one or more gaps;
comparing area of each of the one or more gaps with a predefined threshold value; and
identifying the defect at location of a gap from the one or more gaps, when the area of the gap is greater than the predefined threshold value.

16. The method as claimed in claim 9, wherein identifying the identification data of the car using the second image comprises:
compute feature image of the second image;
compare the feature information with plurality of predefined images to identify a matched predefined image amongst the plurality of predefined images for the feature image, wherein the plurality of predefined images is associated with identification data of the plurality of cars; and
select identification data associated with the matched predefined image to be the identification data of the car.

17. A processing unit (107) for detecting defect in arrangement of grate bars of a conveyor system (102) implemented in an induration furnace of pellet plant, the processing unit (107) comprises:
a processor; and
a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, cause the processor to:
dynamically receive a first image captured by a first unit (105), and a second image captured by a second unit (106), wherein the first image is related to plurality of grate bars arranged in a car of plurality of cars in a conveyor system (102) implemented in an induration furnace, wherein the second image is related to unique code embossed on the car, said unique code represents identification data of the car;
identify defect in arrangement of the plurality of grate bars in the car, using the first image; and
identify the identification data of the car using the second image, upon identification of the defect.

18. The processing unit (107) as claimed in claim 17, wherein identifying the defect using the first image comprises:
detecting presence of one or more gaps between consecutive grate bars amongst the plurality of grate bars in the first image;
determining area of each of the one or more gaps;
comparing area of each of the one or more gaps with a predefined threshold value; and
identifying the defect at location of a gap from the one or more gaps, when the area of the gap is greater than the predefined threshold value.

19. The processing unit (107) as claimed in claim 17, wherein identifying the identification data of the car using the second image comprises:
computing feature image of the second image;
comparing the feature image with plurality of predefined images to identify a match between the feature image and one of the plurality of predefined images, wherein the plurality of predefined images is associated with identification data of the plurality of cars; and
selecting identification data associated with matched predefined image to be the identification data of the car.

20. A method for detecting defect in arrangement of grate bars of a conveyor system (102) implemented in an induration furnace of pellet plant, the method comprising:
dynamically receiving, by a processing unit (107), a first image captured by a first unit (105), and a second image captured by a second unit (106), wherein the first image is related to plurality of grate bars arranged in a car of plurality of cars in a conveyor system (102) implemented in an induration furnace, wherein the second image is related to unique code embossed on the car, said unique code represents identification data of the car;
identifying, by the processing unit (107), defect in arrangement of the plurality of grate bars in the car, using the first image; and
identifying, by the processing unit (107), the identification data of the car, upon identification of the defect, using the second image.

21. The method as claimed in claim 20, wherein identifying the defect using the first image comprises:
detecting presence of one or more gaps between consecutive grate bars amongst the plurality of grate bars in the first image;
determining area of each of the one or more gaps;
comparing area of each of the one or more gaps with a predefined threshold value; and
identifying the defect at location of a gap from the one or more gaps, when the area of the gap is greater than the predefined threshold value.

22. The method as claimed in claim 20, wherein identifying the identification data of the car using the second image comprises:
computing feature image of the second image;
comparing the feature image with plurality of predefined images to identify a match between the feature image and one of the plurality of predefined images, wherein the plurality of predefined images is associated with identification data of the plurality of cars; and
selecting identification data associated with matched predefined image to be the identification data of the car.