Oil field station dosing barrel shelf management method

Abstract

The invention provides an oil field station dosing barrel shelf management method, which belongs to the field of oil equipment warehouse logistics distribution, and comprises the following three steps: establishing a third normal form database, respectively storing barrel, shelf and coordinate data in a corresponding table, and ensuring that the data are standard and consistent; establishing a medicine barrel goods shelf coordinate distribution model, and determining the optimal goods shelf position of the medicine barrel by calculating the distance between the medicine barrel and the goods shelf and considering the residual capacity constraint of the goods shelf; the method comprises the following steps: establishing a path planning model of the medicine barrel transfer robot, calculating the shortest path of the robot from a starting point to a target shelf position, performing path priority calculation by adopting an A * algorithm heuristic function to ensure that the path does not pass through an obstacle, and meanwhile, realizing quick query by a database through index optimization and table connection. And a transaction management mechanism is introduced to ensure the data consistency during concurrent operation of multiple robots. The method improves the efficiency and accuracy of medicine barrel shelf management, and adapts to the dynamic change of warehouse layout.

Description

Technical Field

[0001] The invention belongs to the technical field of storage, logistics and distribution of petroleum production equipment, and in particular relates to a method for managing drug barrel shelves at an oilfield station. Background Art

[0002] The storage management and logistics distribution of petroleum production equipment are crucial components of oilfield management. In recent years, smart management methods have been actively promoted for oilfield equipment and supplies. In response to the petrochemical industry's push for intelligent and unmanned factories, the storage management of dosing barrels and shelves at oilfield stations needs to be intelligent and automated to reduce the labor intensity of dosing workshop workers and improve operational safety and efficiency.

[0003] In the existing technology of general shelf warehouse management, CN202111296159 is a shelf layer determination method, device and medium based on image recognition. It adopts a preset product recognition model and shelf recognition model to respectively identify the image coordinates and several sub-shelves corresponding to each product in the shelf package. This invention is based on image recognition to locate shelves and goods, so it has certain limitations in application and has relatively high requirements for environmental adaptability. In some working conditions, especially in places with insufficient light, image recognition has a certain error rate, which will lead to instability in the business operation of the entire system.

[0004] CN201910783213 discloses a LiDAR-based device and method for detecting shelf positioning holes. The device comprises an actuator, a detection unit, a data storage unit, an information processing unit, a communication unit, and a power supply unit. The actuator comprises a DC motor, a lead screw, a coupling, and a bracket, while the detection unit comprises a workbench and a LiDAR sensor. This invention uses a DC motor to drive the workbench and a LiDAR sensor to scan and acquire cloud data of shelf surface points. While this method accurately locates the shelf, the device is expensive to set up and operate, and does not consider the shelf's remaining storage capacity.

[0005] CN202211342592 is a method and system for quickly taking inventory of materials on three-dimensional shelves based on drone inventory. The method constructs a spatial coordinate system for the three-dimensional shelves, obtains the hovering coordinate points of the drone when taking inventory at each storage location, and determines the completion of the material inventory task according to the material inventory priority. This invention needs to be implemented based on drones, but drones cannot be used in the dosing workshop in the oil field station. Therefore, this invention cannot meet the needs of being applied to the oil field dosing workshop. Summary of the Invention

[0006] Existing technologies in the field of petroleum equipment storage and logistics generally use manual operations rather than mechanized, automated, and intelligent operations. Conventional shelf monitoring methods are not suitable for dosing workshop scenarios. To this end, in order to solve the above-mentioned problems, the present invention provides a method for managing drug barrel shelves at oilfield stations. The design of a drug barrel shelf coordinate system based on database paradigm management solves problems such as data redundancy, complex management, and low query efficiency during drug barrel storage and dosing. The specific solution is as follows:

[0007] A method for managing drug barrel shelves at an oilfield station, comprising the following specific steps:

[0008] S1. Establish a third normal form (3NF) database design and store medicine barrel information, shelf information, and coordinate data information in the medicine barrel table, shelf table, and coordinate table, respectively, to ensure data normalization and consistency.

[0009] S2. Establish a medicine barrel shelf coordinate allocation model, calculate the minimum shelf storage distance plan for each medicine barrel, and obtain the final assigned shelf position of each medicine barrel.

[0010] S3. Establish a path planning model for the medicine barrel handling robot, calculate the shortest path planning from the robot's starting point to the assigned shelf location, and the robot performs the medicine barrel handling work according to the path planning.

[0011] Specifically, in step S1, the medicine barrel table stores the medicine barrel number, medicine type, and medicine barrel capacity information; the shelf table stores the shelf number, carrying capacity, and area information; and the coordinate table stores the shelf number and its associated three-dimensional coordinate position in the warehouse.

[0012] Furthermore, the coordinate system of the coordinate table uses high-precision three-dimensional coordinates (X, Y, Z) to locate and mark the shelf positions, and supports dynamic adjustment of coordinates to cope with changes in shelf positions or warehouse layout optimization.

[0013] Furthermore, the database of step S1 enables the medicine barrel handling robot to quickly query the medicine barrel location through index optimization and table connection, and ensures data consistency when multiple robots operate concurrently by introducing a transaction management mechanism.

[0014] Specifically, in step S2, the medicine barrel shelf coordinate allocation model is established by defining the medicine barrel coordinate position in the warehouse coordinate system as C = (x, y, z), and the coordinate position of each shelf i as S i =(x i ,y i ,z i ), set the objective function min||CS i ||2, the goal is to find an optimal shelf location that minimizes the storage distance, where:

[0015]

[0016] Traverse and calculate each shelf, and finally determine the coordinate position of the medicine barrel allocation shelf:

[0017]

[0018] Among them, R i For each shelf i, V b is the volume of the medicine barrel, and the constraint condition must satisfy R i ≥V b .

[0019] Specifically, in step S3, the path planning model of the medicine barrel transport robot is established as follows: the robot starts from the starting point P start =(x s ,y s ,z s ) Move to the end point P end =(x e ,y e ,z e ), end point P end The coordinates are the S* coordinates determined in step S2, and the total accumulated path length of the robot is L:

[0020]

[0021] Among them, P k For any point in the path, P1=P start , P n =P end ;

[0022] Set the optimal path objective function to minimize the robot path:

[0023]

[0024] in, is a set of obstacles, and the constraint condition is any point P in the path k Cannot fall into obstacles

[0025] Furthermore, the path planning model of the medicine barrel handling robot adopts the A* algorithm heuristic function, and the heuristic estimate is:

[0026] h(P k , P end )=|x k -x e |+|y k -y e |+|z k -z e |;

[0027] Path priority is calculated as follows:

[0028] f(P k )=g(P k )+h(P k , P end );

[0029] Among them, g(P k ) is the cumulative path length of the robot from the starting point to the current point.

[0030] Furthermore, the coordinate table supports dynamic adjustment of coordinates. Specifically, if the warehouse layout is adjusted and the shelf position changes, the coordinates are updated as follows:

[0031] S i '=S i +△S;

[0032] Among them, △S=(△x,△y,△z) is the position adjustment vector.

[0033] Beneficial effects:

[0034] The present invention realizes efficient allocation and management of medicine barrels on shelves by introducing a medicine barrel shelf coordinate system based on database paradigm management.

[0035] 1. Dynamic optimization of medicine barrel storage locations improves space utilization and reduces storage costs.

[0036] 2. The path planning algorithm ensures that the dosing robot completes the task in the shortest possible path, reducing running time and energy consumption.

[0037] 3. The standardization and flexibility of the coordinate system provide support for warehouse layout adjustments, enhance the adaptability and scalability of the system, and help improve the overall efficiency and automation level of the dosing system. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to make the contents of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments of the present invention in conjunction with the accompanying drawings.

[0039] Figure 1 A diagram of method steps according to an embodiment of the present invention.

[0040] Figure 2 This is a diagram of the information interaction relationship of the robot carrying the medicine barrel in an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. The principles and features of the present invention will be described below with reference to the accompanying drawings. It should be noted that the embodiments are only used to explain the present invention and are not used to limit the scope of the present invention.

[0042] A method for managing drug barrel shelves at oilfield stations, such as Figure 1 A diagram of method steps according to an embodiment of the present invention.

[0043] The specific steps are:

[0044] S1. Establish a third normal form (3NF) database design and store medicine barrel information, shelf information, and coordinate data information in the medicine barrel table, shelf table, and coordinate table, respectively, to ensure data normalization and consistency.

[0045] S2. Establish a medicine barrel shelf coordinate allocation model, calculate the minimum shelf storage distance plan for each medicine barrel, and obtain the final assigned shelf position of each medicine barrel.

[0046] S3. Establish a path planning model for the medicine barrel handling robot, calculate the shortest path planning from the robot's starting point to the assigned shelf location, and the robot performs the medicine barrel handling work according to the path planning.

[0047] Specifically, in step S1, the medicine barrel table stores the medicine barrel number, medicine type, and medicine barrel capacity information; the shelf table stores the shelf number, carrying capacity, and area information; and the coordinate table stores the shelf number and its associated three-dimensional coordinate position in the warehouse.

[0048] Furthermore, the coordinate system of the coordinate table uses high-precision three-dimensional coordinates (X, Y, Z) to locate and mark the shelf positions, and supports dynamic adjustment of coordinates to cope with changes in shelf positions or warehouse layout optimization.

[0049] Furthermore, the database of step S1 enables the medicine barrel handling robot to quickly query the medicine barrel location through index optimization and table connection, and ensures data consistency when multiple robots operate concurrently by introducing a transaction management mechanism.

[0050] Specifically, in step S2, the medicine barrel shelf coordinate allocation model is established by defining the medicine barrel coordinate position in the warehouse coordinate system as C = (x, y, z), and the coordinate position of each shelf i as S i =(x i ,y i ,z i ), set the objective function min||CS i ||2, the goal is to find an optimal shelf location that minimizes the storage distance, where:

[0051]

[0052] Traverse and calculate each shelf, and finally determine the coordinate position of the medicine barrel allocation shelf:

[0053]

[0054] Among them, R i For each shelf i, V b is the volume of the medicine barrel, and the constraint condition must satisfy R i ≥V b .

[0055] Specifically, in step S3, the path planning model of the medicine barrel transport robot is established as follows: the robot starts from the starting point P start =(x s ,y s ,z s ) Move to the end point P end =(x e ,y e ,z e ), end point P end The coordinates are the S* coordinates determined in step S2, and the total accumulated path length of the robot is L:

[0056]

[0057] Among them, P k For any point in the path, P1=P start , P n =P end ;

[0058] Set the optimal path objective function to minimize the robot path:

[0059]

[0060] in, is a set of obstacles, and the constraint condition is any point P in the path k Cannot fall into obstacles

[0061] Furthermore, the path planning model of the medicine barrel handling robot adopts the A* algorithm heuristic function, and the heuristic estimate is:

[0062] h(P k , P end )=|x k -x e |+|y k -y e |+|z k -z e |;

[0063] Path priority is calculated as follows:

[0064] f(P k )=g(P k )+h(P k , P end );

[0065] Among them, g(P k ) is the cumulative path length of the robot from the starting point to the current point.

[0066] Furthermore, the coordinate table supports dynamic adjustment of coordinates. Specifically, if the warehouse layout is adjusted and the shelf position changes, the coordinates are updated as follows:

[0067] S i '=S i +△S;

[0068] Among them, △S=(△x,△y,△z) is the position adjustment vector.

[0069] Example

[0070] This invention uses a three-dimensional coordinate system to precisely manage medicine barrel shelves. The shelves are composed of multiple sections, each with several locations. Each location uses a unified coordinate naming convention, encompassing the (X, Y, Z) dimensions, representing the shelf's horizontal, vertical, and height positions, respectively.

[0071] Shelf coordinate allocation process:

[0072] When a new medicine barrel enters the warehouse, the system selects a suitable location based on the size and weight of the barrel, using capacity constraints and distance optimization algorithms, and dynamically generates the storage coordinates for the barrel. The specific process is as follows:

[0073] Step 1: Collect the specifications and weight of the medicine barrel and enter them into the database.

[0074] Step 2: Query the remaining capacity of the shelf and filter the set of shelves that meet the conditions.

[0075] Step 3: Calculate the Euclidean distance between each cargo location coordinate and the coordinate of the medicine barrel entry point, and select the cargo location with the shortest path for allocation.

[0076] Step 4: Update the shelf database to store the coordinate information of the medicine barrels.

[0077] Path planning and navigation:

[0078] The dosing robot uses the A* algorithm to plan a path based on the coordinates of the target location, avoiding obstacles and moving to the target location. Path planning adheres to the shortest path principle and combines real-time obstacle monitoring data to achieve flexible obstacle avoidance and precise navigation.

[0079] Dynamic adjustment and expansion:

[0080] When the warehouse layout changes or shelves are expanded, the system automatically updates coordinate data. Through database paradigm management, data consistency and integrity are guaranteed, coordinate conflicts are avoided, and seamless access to newly added shelves or areas is achieved.

[0081] like Figure 2 , which is an information interaction relationship diagram of the robot carrying medicine barrels. The medicine barrels of the present invention use wireless / optical / magnetic / wired tags, so that the position information of the medicine barrels and the handling robot is updated during the storage and transportation process, and a reliable information loop is achieved based on the updated medicine barrel position information, medicine barrel processing status information, and robot path coding landmarks. On this hardware basis, according to the aforementioned medicine barrel shelf management steps, a medicine barrel-shelf-robot path coordinate system based on the database paradigm management method is carried. Among them, the specific selection of the label is determined by factors such as the explosion-proof requirements of the visual environment, cost, and the scale of the medicine barrel shelf. The medicine barrel position information is transmitted by the shelf / robot, the medicine barrel processing status information is obtained by the explosion-proof optical fiber interface of the medicine adding cabinet, and the robot path coding landmarks indicate the robot position and path. The information loop uses distributed, scalable, explosion-proof hardware that does not rely on continuous power supply to record information and update in real time.

[0082] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When software is used for implementation, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrations. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0083] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention. It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In actual applications, those skilled in the art can select some or all of them according to actual needs to achieve the purpose of the solution of this embodiment, and this is not limited here.

Claims

1. A method for managing drug barrel shelves at oilfield stations, characterized in that: The specific steps are: S1. Establish a database in Third Normal Form (3NF) and store barrel information, shelf information, and coordinate data in the barrel table, shelf table, and coordinate table, respectively, to ensure data normalization and consistency. S2. Establish a medicine barrel shelf coordinate allocation model, calculate the minimum shelf storage distance plan for each medicine barrel, and obtain the final assigned shelf location for each medicine barrel; S3. Establish a path planning model for the medicine barrel handling robot, calculate the shortest path planning from the robot's starting point to the assigned shelf location, and the robot performs the medicine barrel handling work according to the path planning.

2. The method for managing drug barrel shelves at an oilfield station according to claim 1, characterized in that: In step S1, the medicine barrel table stores the medicine barrel number, medicine type, and medicine barrel capacity information; the shelf table stores the shelf number, carrying capacity, and area information; and the coordinate table stores the shelf number and its associated three-dimensional coordinate position in the warehouse.

3. The method for managing drug barrel shelves at an oilfield station according to claim 2, characterized in that: The coordinate system of the coordinate table uses high-precision three-dimensional coordinates (X, Y, Z) to locate and mark the shelf positions, and supports dynamic adjustment of coordinates to cope with changes in shelf positions or warehouse layout optimization.

4. The method for managing drug barrel shelves at an oilfield station according to claim 1, characterized in that: The database in step S1 is optimized through indexes and table connections, enabling the medicine barrel handling robot to quickly query the medicine barrel location, and introducing a transaction management mechanism to ensure data consistency during concurrent operations of multiple robots.

5. The method for managing drug barrel shelves at an oilfield station according to claim 1, characterized in that: In step S2, the medicine barrel shelf coordinate allocation model is established by defining the medicine barrel coordinate position in the warehouse coordinate system as C = (x, y, z), and the coordinate position of each shelf i as S i =(x i ,y i ,z i ), set the objective function min||CS i ||2, the goal is to find an optimal shelf location that minimizes the storage distance, where: Traverse and calculate each shelf, and finally determine the coordinate position of the medicine barrel allocation shelf: Among them, R i For each shelf i, V b is the volume of the medicine barrel, and the constraint condition must satisfy R i ≥V b .

6. The method for managing drug barrel shelves at an oilfield station according to claim 1, characterized in that: In step S3, the path planning model of the medicine barrel transport robot is established as follows: the robot starts from the starting point P start =(x s ,y s ,z s ) Move to the end point P end =(x e ,y e ,z e ), end point P end The coordinates are the S* coordinates determined in step S2, and the total accumulated path length of the robot is L: Among them, P k For any point in the path, P1=P start , P n =P end ; Set the optimal path objective function to minimize the robot path: in, is a set of obstacles, and the constraint condition is any point P in the path k Cannot fall into obstacles 7. The method for managing drug barrel shelves at an oilfield station according to claim 6, characterized in that: The path planning model of the medicine barrel handling robot adopts the A* algorithm heuristic function, and the heuristic estimate is: h(P k ,P end )=|x k -x e |+|y k -y e |+|z k -z e |; Path priority is calculated as follows: f(P k )=g(P k )+h(P k ,P end ); Among them, g(P k ) is the cumulative path length of the robot from the starting point to the current point.

8. The method for managing drug barrel shelves at an oilfield station according to claim 3, characterized in that: The coordinate table supports dynamic adjustment of coordinates. Specifically, if the warehouse layout is adjusted and the shelf position changes, the coordinates are updated as follows: S i ’=S i +△S; Among them, △S=(△x,△y,△z) is the position adjustment vector.

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