Description:FORM 2

THE PATENTS ACT, 1970 (39 of 1970)
&
THE PATENT RULES, 2003

COMPLETE SPECIFICATION
(See Section 10 and Rule 13)

Title of invention:

AUTONOMOUS NON-DESTRUCTIVE EVALUATION OF A CONTAINER

Applicant:
TARDID TECHNOLOGIES PRIVATE LIMITED
An Indian Company,
Having Address #33 Galaxy Enclave, Jakkur, Plantation Road, Bangalore-560064

The following specification describes the invention and the manner in which it is to be performed.
PRIORITY INFORMATION
[001] The present application does not claim a priority from any other application.
TECHNICAL FIELD
[002] The present subject matter described herein, in general, relates to an autonomous non-destructive evaluation of a container, and more particularly to the evaluation of an empty metallic container.
BACKGROUND
[003] The use of Liquefied Petroleum Gas (LPG) is very common for household and industrial purposes. The LPG is filled in a metallic container that is generally cylindrical or bottle-shaped. The metallic container must be void of anomalies. There are multiple areas of the metallic container that may be compromised such as a valve pin – used to control the outward flow of LPG, an O-ring - used as a gasket for sealing purposes, or the cylinder might be expired past its due date. It is very important to validate the condition of the metallic container and check for cylinders expiry date before filling the metallic container with LPG or hydrocarbon.
SUMMARY
[004] Before the present system(s) and method(s), are described, it is to be understood that this application is not limited to the particular systems, and methodologies described, as there can be multiple possible embodiments which are not expressly illustrated in the present disclosure. It is also to be understood that the terminology used in the description is for the purpose of describing the particular versions or embodiments only and is not intended to limit the scope of the present application. This summary is provided to introduce concepts related to systems and methods for evaluating a metallic container and the concepts are further described below in the detailed description. This summary is not intended to identify essential features of the claimed subject matter nor is it intended for use in determining or limiting the scope of the claimed subject matter.
[005] In one implementation, a system for evaluating a metallic container is disclosed. Initially, a plurality of images of the metallic container from a vision camera may be received. Further, the plurality of images may be analysed to detect an expiry date of the metallic container. The expiry date of the metallic container may be present on the metallic container. Subsequently, a defect in a valve pin and an O-ring of the metallic container may be identified using Machine Learning Models and Deep Learning Algorithms. Finally, information may be generated to eliminate the metallic container when at least the expiry date is passed, the defect is detected in the O-ring and the valve pin, thereby evaluating the metallic container.
[006] In another implementation, a system for evaluating a metallic container is disclosed. The system may comprise a housing, a conveyer belt, and a pneumatic actuator. The housing may comprise a proximity sensor, a pneumatic stopper, a vision camera, and a Programmable Logic Controller (PLC). The proximity sensor may be used to detect a metallic container from the plurality of metallic containers entering the housing. It may be noted that each metallic container is empty. The housing may comprise a pneumatic stopper to stop the metallic container after receiving a trigger from the Programmable Logic Controller (PLC) based on proximity sensor information. The proximity sensor information comprises information received by the proximity sensor. Further, the housing may comprise a vision camera to capture a plurality of images of the metallic container entering the housing. It may be noted that one or more vision cameras may be used to capture the plurality of images of the metallic container entering the housing. The plurality of images may comprise at least a top view of the metallic container and one or more side views of the metallic container. The top view may depict a valve pin and an O-ring. The one or more side views of the metallic container may depict a collar and one or more vertical plates of the metallic container. Further, the PLC may be used for transmitting an identity number of each metallic container entering the housing. A conveyer belt may be passed through the housing. The plurality of metallic containers may be placed on the conveyer belt. A pneumatic actuator may be installed outside the housing. The pneumatic actuator may eliminate the metallic container having anomaly from the conveyer belt. The pneumatic actuator may receive information from the PLC based on the rejection information shared by the server. The anomaly may occur when at least a defect is identified in the valve pin, the O-ring, and when the metallic container is expired.
[007] In yet another implementation, a method for evaluating a metallic container is disclosed. A plurality of images of the metallic container may be received from a vision camera. Further, the plurality of images may be analysed to detect an expiry date of the metallic container. The expiry date of the metallic container may be present on the metallic container. Subsequently, a defect in a valve pin and an O-ring of the metallic container may be identified using Machine Learning Models and Deep Learning Algorithms. Finally, information may be generated to eliminate the metallic container when at least the expiry date is passed, or the defect is detected in the O-ring and the valve pin, thereby evaluating the metallic container.
[008] In yet another implementation, a method for evaluating a metallic container is disclosed. Initially, a metallic container from the plurality of metallic containers entering the housing may be detected. It may be noted that each metallic container is empty. Further, a trigger may be received from the proximity sensor via a Programmable Logic Controller (PLC) to stop the metallic container. Subsequently, a vision camera may capture a plurality of images of the metallic container entering the housing. It may be noted that one or more vision cameras may be used to capture the plurality of images of the metallic container entering the housing. The plurality of images may comprise at least a top view of the metallic container and one or more side views of the metallic container. The top view may depict cylinder valve and O-ring. The one or more side views of the metallic container may depict a collar, one or more vertical plates of the metallic container. Further, an identity number of each metallic container entering the housing may be updated in the PLC, which has been received and stored by the server. Finally, a pneumatic actuator may eliminate the metallic container having anomaly from the conveyer belt. It may be noted that the pneumatic actuator may receive information from the server via the PLC.
BRIEF DESCRIPTION OF THE DRAWINGS
[009] The foregoing detailed description of embodiments is better understood when read in conjunction with the appended drawings. For the purpose of illustrating of the present subject matter, an example of a construction of the present subject matter is provided as figures, however, the invention is not limited to the specific method and system for evaluating a metallic container disclosed in the document and the figures.
[010] The present subject matter is described in detail with reference to the accompanying figures. 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 drawings to refer to various features of the present subject matter.
[011] Figure 1 illustrates a network implementation for evaluating a metallic container, in accordance with an embodiment of the present subject matter.
[012] Figure 2 illustrates a system for evaluating a metallic container, in accordance with an embodiment of the present subject matter.
[013] Figures 3 and 4 illustrate methods for evaluating a metallic container. The method is illustrated in the form of flow chart, in accordance with an embodiment of the present subject matter.
[014] The figure depicts an embodiment of the present disclosure for purposes of illustration only. One skilled in the art will readily recognize from the following discussion that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTIONS
[015] Some embodiments of this disclosure, illustrating all its features, will now be discussed in detail. The words “receiving”, “analysing”, “identifying,”, “generating”, and “transmitting”, “eliminating”, “capturing”, “detecting” and other forms thereof, are intended to be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items or meant to be limited to only the listed item or items. It must also be noted that as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise. Although any systems and methods similar or equivalent to those described herein can be used in the practice or testing of embodiments of the present disclosure, the exemplary systems and methods are now described.
[016] The disclosed embodiments are merely exemplary of the disclosure, which may be embodied in various forms. Various modifications to the embodiment will be readily apparent to those skilled in the art and the generic principles herein may be applied to other embodiments. However, one of ordinary skill in the art will readily recognize that the present disclosure is not intended to be limited to the embodiments illustrated but is to be accorded the widest scope consistent with the principles and features described herein.
[017] The present subject matter discloses a method and a system for evaluating a metallic container. In order to evaluate a metallic container a plurality of metallic containers may be placed on a conveyer belt. Further, the metallic container may be moved inside a housing via the conveyer belt. It may be noted that a vision camera may be installed inside the housing. The vision camera may capture one or more images of the metallic container. In an example, the metallic container may be a liquefied petroleum gas container. An expiry date of the metallic container is present on a vertical plate of the metallic container. The metallic container also comprises a pin valve and an O-ring. The vision camera may be used to capture the expiry date of the metallic container and area around the pin valve and the O-ring. It must be noted that the goal of the invention is to identify an anomaly in the metallic container. The anomaly is identified at least when the metallic container is expired or abnormality is found in the pin valve or the O-ring.
[018] In one implementation, the plurality of images of the metallic container may be received by a server. Further, the plurality of images may be analysed to detect an expiry date of the metallic container. Furthermore, a defect in the valve pin and the O-ring of the metallic container may be identified. It may be noted that the checking for expiry date, the valve pin defect identification and detection of presence or absence of O-ring may be performed by analysing the plurality of images. When an anomaly is detected the server sends information to a Programmable logic controller (PLC) to eliminate the metallic container having anomaly.
[019] Referring now to Figure 1, a network implementation 100 of a system 102 for evaluating a metallic container is disclosed. Initially, the system 102 receives data related to the metallic container. The intelligent system 114 receives data from system 102. The user may use one or more user devices 104-1, 104-2, …104-N, collectively referred to as user devices 104, hereinafter, or applications residing on the user devices 104 for sending an input to the intelligent system 114. Further, the intelligent system 114 may send information to eliminate the metallic container having anomaly from the conveyer belt.
[020] It may be noted that the system 102 and the intelligent system 114 may be accessed by multiple users through one or more user devices 104-1, 104-2…104-N. In one implementation, the system 102 and the intelligent system 114 may be communicatively connected to a cloud-based computing environment. Examples of the user devices 104 may include, but are not limited to, a portable computer, a personal digital assistant, a handheld device, a mobile device, a tablet, and a workstation. The user devices 104 are communicatively coupled to the system 102 and the intelligent system 114 through a series of network 106 referred as a network 106-A, a network 106-B, and a network 106-C.
[021] Although the present disclosure is explained considering that the intelligent system 114, it may be understood that the intelligent system 114 may be implemented in a variety of computing systems, such as a laptop computer, a desktop computer, a notebook, a workstation, a virtual environment, a mainframe computer, a server, a network server, the cloud-based computing environment. It will be understood that the intelligent system 114 may be accessed by multiple users through one or more user devices 104-1, 104-2…104-N. In one implementation, the intelligent system 114 may comprise the cloud-based computing environment in which the user may operate individual computing systems configured to execute remotely located applications. Examples of the user devices 104 may include, but are not limited to, a portable computer, a personal digital assistant, a handheld device, a mobile device, a tablet, and a workstation. The user devices 104 are communicatively coupled to the intelligent system 114 through a network 106-A.
[022] In one implementation, the series of network 106-A, 106-B, and 106-C may be a wireless network, a wired network, or a combination thereof. The series of network 106-A, 106-B, and 106-C can be implemented as one of the different types of networks, such as intranet, local area network (LAN), wide area network (WAN), the internet, and the like. The series of network 106-A, 106-B, and 106-C may either be a dedicated network or a shared network. The shared network 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), and the like, to communicate with one another. Further the series of network 106-A, 106-B, and 106-C may include a variety of network devices, including routers, bridges, servers, computing devices, storage devices, and the like.
[023] In one embodiment, the system 102 may include at least a vision camera 212, a first proximity sensor 206, a second proximity sensor 208, and a PLC 118. The intelligent system 114 may include a processor 108, an input/output (I/O) interface 110, and a memory 112. It may be noted that the processor 108 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital information processors, Central Processing Units (CPUs), state machines, logic circuitries, and/or any devices that manipulate information based on operational instructions. Among other capabilities, the processor 108 is configured to fetch and execute computer-readable instructions stored in the memory 112.
[024] The I/O interface 110 may include a variety of software and hardware interfaces, for example, a web interface, a graphical user interface, and the like. The intelligent system 114 may allow the system 102 to interact with the user directly or through the user devices 104. Similarly, the I/O interface 110 may allow the intelligent system 114 to interact with the user directly or through the user devices 104. Further, the I/O interface 110 may enable the system 102 and the intelligent system 114 to communicate with other computing devices, such as web servers and external data servers (not shown). The I/O interface 110 can facilitate multiple communications within a wide variety of networks and protocol types, including wired networks, for example, LAN, cable, etc., and wireless networks, such as Wireless Local area network (WLAN), cellular, or satellite. The I/O interface 110 may include one or more ports for connecting a number of devices to one another or to another server.
[025] The memory 112 may include any computer-readable medium or computer program product known in the art including, for example, volatile memory, such as static random-access memory (SRAM) and dynamic random-access memory (DRAM), and/or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, Solid State Disks (SSD), optical disks, and magnetic tapes. The memory 112 may include routines, programs, objects, components, data structures, etc., which perform particular tasks or implement particular abstract data types. In one embodiment, the memory 112, amongst other things, serves as a repository for storing data processed, received, and generated by one or more of the programs or the coded instructions.
[026] As there are various challenges observed in the existing art, the challenges necessitate the need to build the system 102 for evaluating a metallic container. At first, a user may use the user device 104 to access the system 102 via the intelligent system 114. The user may register the user devices 104 using the I/O interface 110 in order to use the system 102. In one aspect, the user may access the I/O interface 110 of the intelligent system 114.
[027] The present subject matter discloses a system and a method for autonomous non-destructive evaluation of a metallic container. It may be noted that the metallic container is empty. A conveyer belt may be passed through a housing. The plurality of metallic containers may be placed on the conveyer belt. The conveyer belt is continuously moving. In an embodiment, the plurality of metallic containers may be a plurality of empty LPG cylinders. The housing may comprise a proximity sensor, a pneumatic stopper, a vision camera, and a Programmable Logic Controller (PLC). The proximity sensor may detect a metallic container from the plurality of metallic containers entering the housing. It may be noted that each metallic container is empty. In an embodiment, the proximity sensor information may also be used by the logic deployed in PLC to differentiate between industrial cylinders and domestic cylinders. The proximity sensor may be one of an Optical Proximity Sensor, an Inductive Proximity Sensor, a Capacitive Proximity Sensor, a Magnetic Proximity Sensor, or an Ultrasonic proximity Sensor. It may be noted that only one metallic container can enter the housing at a time.
[028] Further, the pneumatic stopper may stop the metallic container after receiving a trigger from the PLC based on the proximity sensor information. In an embodiment, the pneumatic stopper may be coupled with a second proximity sensor. The second proximity sensor may help the pneumatic stopper to stop the metallic container at a particular position inside the housing. It may be noted that the pneumatic stopper and the second proximity sensor may be installed inside the housing. In an embodiment, when a metallic container comes at a particular position the second proximity sensor sends information via the PLC to the pneumatic stopper to stop the metallic container.
[029] Furthermore, a vision camera may be used to capture a plurality of images of the metallic container entering the housing. The plurality of images may comprise at least a top view of the metallic container and one or more side views of the metallic container. The top view may depict a valve pin and an O-ring of the metallic container. The one or more side views of the metallic container may depict a collar, one or more vertical plates, and a bung area of the metallic container. In an embodiment, when the pneumatic stopper stops the metallic container the vision camera captures the plurality of images of the metallic container. Further to capturing, the metallic container is moved outside the housing. In another embodiment, the multiple vision camera may also be used to capture at least a 360-degree video of the metallic container and 360-degree images of the metallic container from the different orientations.
[030] In another embodiment, one or more vision cameras may also be used to capture the plurality of images of the metallic container. The one or more vision cameras may be installed inside the housing to capture the top view and the side view of the metallic container. The one or more vision cameras capture the top view image of the metallic container and the side views. The plurality of images must contain the expiry date of the metallic container and a top view image depicting a valve pin and an O-ring. Further to capturing, the metallic container may be moved outside the housing. It may be noted that the intelligent system may extract the plurality of images of the metallic container from the one or more vision cameras.
[031] The LPG cylinders usually comprise a base ring, a bottom dome, a circumferential weld, a top dome, a bung area, a valve pin, an O-ring, three vertical plates (120° apart), and a collar. The expiry date of the LPG cylinder is generally present on one of the three vertical plates. The expiry date is present in a code language (e.g., B.23). “B.23” may be read as the second quarter of the year 2023. In other words, the expiry date of the LPG cylinder is around April 2023 to June 2023.
[032] Consider an example, a plurality of LPG cylinders (metallic container) may be placed on a conveyer belt. It may be noted that the conveyer belt is continuously moving. A proximity sensor may detect an LPG cylinder out of the plurality of cylinders. The LPG cylinder may be moved inside the housing. A pneumatic stopper may stop the LPG cylinder. Further, four vision cameras may be installed inside the housing. A vision camera out of four vision cameras may be installed to capture a top view of the LPG cylinder. The top view of the LPG cylinder may depict a valve pin and an O-ring. Further, three vision cameras out of four vision cameras may be installed in order to capture the area around the three vertical plates of the LPG cylinder. Once, the plurality of images has been captured the cylinder is released by the Pneumatic stopper and moved out of the housing.
[033] Further, a Programmable logic controller (PLC) may update and transmit an identity number of each metallic container entering the housing. It may be noted that the PLC updates the count data based on the information sent by the one or more proximity sensors. The PLC logs the count data, and the server pulls the same from the PLC. In an embodiment, the count data may be pulled by an intelligent system 114 from the PLC 118 via the network 106-B. In an embodiment, each metallic container entering the housing is assigned an identity number.
[034] In an embodiment, when the metallic container goes out of the housing an identity number to the metallic container is assigned in its respective registry in the PLC. In yet another embodiment, the metallic container is assigned a number when the metallic container is stopped by the pneumatic stopper in its respective registry in the PLC.
[035] Further, the plurality of images of the metallic container may be analysed to detect an expiry date of the metallic container. It may be noted that the expiry date may be mentioned on the vertical plates of the metallic container. The plurality of images captured by the vision camera may be analysed in order to interpret and process the image of the expiry date on the metallic container. The intelligent system compares the interpreted expiry date of the metallic container with the current date. Consider an example, the expiry date present on the metallic container is C.21. The intelligent system compares the expiry date with the current date. When the expiry date of the metallic container has passed the current date of scanning the intelligent system flags the metallic container.
[036] Further to analysing the plurality of images, a defect in a valve pin and an O-ring of the metallic container may be identified using Machine Learning Models, Deep Learning Algorithms, and Image Processing Techniques. In an example and not by way of any limitation, the Deep learning Algorithms may comprise contour matching and character recognition. The defect may be detected by analysing the plurality of images. In an example and not by way of any limitation, the defect is detected by processing the plurality of images with pre-trained machine learning models and/or deep learning models. The Machine Learning Models and Deep Learning Algorithms are trained to identify the defect in the valve pin and the O-ring of the metallic container. It may be noted that an image of the top view of the metallic container helps to identify a defect in the valve pin and the O-ring of the metallic container. When an anomaly in either the valve pin or the O-ring is detected, the intelligent system flags the metallic container.
[037] Further to identifying the defect, rejection information may be generated to eliminate the metallic container when at least the expiry date is passed, or the defect is detected in the O-ring and the valve pin. It may be noted that a pneumatic actuator may be installed outside the housing to eliminate the metallic container having anomaly from the conveyer belt. The pneumatic actuator may receive the rejection information from the PLC. The anomaly may occur when a defect is identified in the valve pin or the O-ring, or the metallic container is expired. It may be noted that the intelligent system may store or discard the plurality of images of the metallic container when no anomaly is identified.
[038] Consider an example, an LPG cylinder enters the housing. The LPG cylinder is stopped by a pneumatic actuator. The LPG cylinder is assigned an identity number. Let us assume the identity number is 20. Further, one or more vision cameras may capture a plurality of images of the LPG cylinder. The plurality of images of the metallic container is extracted by an intelligent system via the network 106-A. Further, the intelligent system may pull information regarding the identity number of the LPG cylinder from the PLC. Further, the plurality of images is analysed to detect any anomaly associated with the LPG cylinder. When an anomaly is identified the intelligent system sends rejection information to PLC to eliminate the LPG cylinder. The PLC then sends a command to a pneumatic actuator to eliminate the metallic container having anomaly from the conveyer belt.
[039] Consider another example, hundreds of metallic containers are placed on a conveyer belt. Further, the metallic container enters the housing one by one. Furthermore, an identity number is assigned to each metallic container as they enter the housing. The vision camera may capture a plurality of images of the metallic container. Further, the metallic container is moved out of the housing. Let us assume that the 20th metallic container is expired or has some defect in the valve pin or the O-ring. The PLC may activate the pneumatic actuator installed outside the housing to eliminate the 20th metallic container. In an embodiment, the intelligent system also logs the number of the metallic containers which get eliminated because of an anomaly. The intelligent system may also maintain a reason for eliminating the metallic container. In yet another embodiment, the intelligent system stores an image from the plurality of images of a metallic container which shows an anomaly.
[040] Referring to figure 2, a system (102) for evaluating a metallic container is disclosed. Initially, a metallic container (204) may be placed on a conveyer belt (202). It may be noted that the metallic container (204) is empty. Further, a PLC differentiates between the different sizes of the metallic container based on proximity sensor information received from a first proximity sensor (206) installed outside the housing (208). Further, a second proximity sensor (222) may detect the entry of the metallic container (204) into the housing (208). Furthermore, upon detection of the metallic container (204) by the second proximity sensor (222), a pneumatic stopper (224) is activated to stop the metallic container (204). Further, a vision camera (212) may capture a plurality of images of the metallic container (204). When the plurality of images is captured, the metallic container (204) moves outside the housing (208). Further, a pneumatic actuator (216) may eliminate the metallic container (204) having anomaly. In an example and not by way of any limitation, one or more pneumatic actuators may be used to eliminate the metallic container (204) having anomaly. When no anomaly is associated with the metallic container (204), the metallic container may be moved to a filling station (218). When an anomaly is identified the metallic container (204) is removed from the conveyer belt (202).
[041] Referring now to figure 3, a side view of the metallic container is shown. The metallic container comprises three vertical plates (304 A, 304 B, and 304 C) installed on a top dome (308). An expiry date (302) of the metallic container is mentioned on the inner side of one of the vertical plates. A collar (306) is present at the top of the three vertical plates. It may be noted that an image from the plurality of images captured from the vision camera may look like this.
[042] Referring now to figure 4, a method 400 for evaluating a metallic container is shown, in accordance with an embodiment of the present subject matter. The method 400 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, functions, etc., that perform particular functions or implement particular abstract data types.
[043] The order in which the method 400 is described is 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 400 or alternate methods for evaluating a metallic container. Additionally, individual blocks may be deleted from the method 400 without departing from the scope of the subject matter described herein. Furthermore, the method 400 for evaluating a metallic container can be implemented in any suitable hardware, software, firmware, or combination thereof. However, for ease of explanation, in the embodiments described below the method 400 may be considered to be implemented in the above-described system 102.
[044] At block 402, a metallic container from the plurality of metallic containers entering the housing may be detected.
[045] At block 404, a trigger to stop the metallic container may be received from a Programmable Logic Controller (PLC) based on proximity sensor information.
[046] At block 406, a vision camera may capture a plurality of images of the metallic container entering the housing. The plurality of images may comprise at least a top view of the metallic container and one or more side views of the metallic container. The top view may depict a valve pin and an O-ring. The one or more side views of the metallic container may depict a collar, one or more vertical plates, and a bung area of the metallic container.
[047] At block 408, an identity number of each metallic container entering the housing may be updated.
[048] At block 410, the metallic container having anomaly may be eliminated from the conveyer belt.
[049] Referring now to figure 5, a method 500 for evaluating a metallic container is shown, in accordance with an embodiment of the present subject matter. The method 500 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, functions, etc., that perform particular functions or implement particular abstract data types.
[050] The order in which the method 500 is described is 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 500 or alternate methods for evaluating a metallic container. Additionally, individual blocks may be deleted from the method 500 without departing from the scope of the subject matter described herein. Furthermore, the method 500 for evaluating a metallic container can be implemented in any suitable hardware, software, firmware, or combination thereof. However, for ease of explanation, in the embodiments described below the method 500 may be considered to be implemented in the above-described system 112.
[051] At block 502, a plurality of images of the metallic container from a vision camera may be received.
[052] At block 504, the plurality of images may be analysed to detect an expiry date of the metallic container.
[053] At block 506, a defect in a valve pin and an O-ring of the metallic container may be identified using Machine Learning Models and Deep Learning Algorithms.
[054] At block 508, rejection information may be generated to eliminate the metallic container when at least the expiry date is passed, and the anomaly is detected in the O-ring and the valve pin.
[055] Exemplary embodiments discussed above may provide certain advantages. Though not required to practice aspects of the disclosure, these advantages may include those provided by the following features.
[056] In some embodiments, the method or the system may help in increasing the efficiency of the LPG plants.
[057] In some embodiments, the method or the system may help to reduce the risk of filling a damaged metallic container with flammable gas or liquid.
[058] In some embodiments, the method or the system may help in completely automating the process of evaluating a certain quality aspect of metal containers.
[059] In some embodiments, the method or the system may prevent the wastage of expensive gasses or liquids by detecting defects in metal containers before filling.
[060] In some embodiments, the method may improve efficiency by identifying the component and reason for a defect in the metal container making it easy to repair rather than replace.
[061] In some embodiments, the method or the system may save time by removing metal containers from the above-mentioned anomalies from the continuously moving conveyor belt.
[062] Although implementations for a method and system for evaluating a metallic container have been described in a language specific to structural features and/or methods, it is to be understood that the appended claims are not necessarily limited to the specific features or methods described. Rather, the specific features and methods are disclosed as examples of implementations for constructing the method and system for evaluating a metallic container. , Claims:I/We claim:
1. An intelligent system (114) for evaluating a metallic container, the intelligent system (114) comprises:
receiving, by a processor (108), a plurality of images of a metallic container from a vision camera;
analysing, by the processor (108), the plurality of images to detect an expiry date of the metallic container, wherein the expiry date of the metallic container is present on the metallic container;
identifying, by the processor (108), a defect in a valve pin and an O-ring of the metallic container based on Machine Learning Model and Deep Learning Algorithms; and
generating, by the processor (108), information to eliminate the metallic container when at least the expiry date is passed, the defect is detected in the O-ring and the valve pin, thereby evaluating the metallic container.

2. A system (102) for evaluating a metallic container (204), the system (102) comprises:
a conveyer belt (202) passing through a housing (208), wherein a plurality of metallic containers is placed on the conveyer belt (202);
characterized in that
the housing (208) comprising
a proximity sensor (206) for detecting a metallic container (204) from the plurality of metallic containers entering the housing (208);
a pneumatic stopper (224) to stop the metallic container (204) after receiving a trigger from a Programmable Logic Controller (PLC) based on proximity sensor information;
a vision camera (212) to capture a plurality of images of the metallic container (204) entering the housing (208); and
the Programmable Logic Controller (PLC) for transmitting an identity number of each metallic container entering the housing (208); and
a pneumatic actuator (216), installed outside the housing (208), to eliminate the metallic container (204) having anomaly from the conveyer belt (202), wherein the pneumatic actuator (216) receives rejection information from a server via the PLC to eliminate the metallic container (204), and wherein the anomaly occurs when at least a defect is identified in a valve pin, an O-ring, and when the metallic container (204) is expired.

3. The system (102) as claimed in claim 2, wherein the plurality of images comprises at least a top view of the metallic container and a side view of the metallic container, and wherein the top view depicts the valve pin and the O-ring, and wherein the side view of the metallic container depicts at least a collar, one or more vertical plates of the metallic container.

4. The system (102) as claimed in claim 2, wherein the server analyses the plurality of images to detect an expiry date of the metallic container, wherein the expiry date of the metallic container is present on the metallic container.

5. The system (102) as claimed in claim 2, wherein the PLC receives information comprising the identity number of the metallic container from the server and the identity number of the metallic cylinder to be eliminated.

6. The system (102) as claimed in claim 2, wherein the PLC counts the number of each metallic container entering the housing based on the signal received from the proximity sensor.

7. The system (102) as claimed in claim 2, wherein the defect is identified in the valve pin and the O-ring of the metallic container using Machine Learning Models and Deep Learning Algorithms.

8. The system (102) as claimed in claim 2, wherein the metallic container moves to a filling station when the metallic container is not expired, and the defect is not detected.

9. A method (400) for evaluating a metallic container, the method comprises:
detecting, by a proximity sensor, a metallic container from a plurality of metallic containers entering the housing;
receiving, by a pneumatic stopper, a trigger to stop the metallic container from a Programmable Logic Controller (PLC) based on proximity sensor information;
capturing, by a vision camera, a plurality of images of the metallic container entering the housing;
updating, by the PLC, an identity number of each metallic container entering the housing; and
eliminating, by a pneumatic actuator, the metallic container having anomaly from the conveyer belt, wherein the pneumatic actuator receives rejection information from the PLC, and wherein the anomaly occurs when a defect is identified in the valve pin or the O-ring, or when the metallic container is expired.

10. A method (500) for evaluating a metallic container, the method comprises:
receiving, by a processor (108), a plurality of images of a metallic container from a vision camera;
analysing, by the processor (108), the plurality of images to detect an expiry date of the metallic container, wherein the expiry date of the metallic container is present on the metallic container;
identifying, by the processor (108), a defect in a valve pin and an O-ring of the metallic container using Machine Learning Models and Deep Learning Algorithms; and
generating, by the processor (108), rejection information to eliminate the metallic container when at least the expiry date is passed, or the defect is detected in the O-ring and the valve pin, thereby evaluating the metallic container.

Dated this 6th day of June 2022