Transportation dumping system for assisting in dumping anode carbon blocks

Abstract

The invention discloses a transportation dumping system for assisting in dumping anode carbon blocks, which belongs to the field of transportation dumping and comprises a transportation module, a dumping module, an intelligent sensing and control module and a remote monitoring module. By adopting the electric rail car with lower cost and the sensor and control module which are configured on the basis, the construction cost is effectively controlled while the basic production requirements are met, so that middle and small-scale enterprises can realize intelligent management of transportation and dumping of the anode carbon blocks with lower investment. According to the embodiment of the large factory, an advanced unmanned transport vehicle and a high-precision sensor are selected, a powerful intelligent sensing and control module is combined, the system adapts to complex terrains and heavy production tasks of the large factory, the transport efficiency and the dumping precision are improved, and management chaos and production accidents caused by scale enlargement are avoided.

Description

Technical Field

[0001] This invention relates to the field of transportation and unloading technology, and in particular to a transportation and unloading system for assisting in unloading anode carbon blocks. Background Technology

[0002] As an indispensable and critical consumable component in the aluminum electrolysis production process, the quality and stability of the supply of anode carbon blocks have a decisive impact on the smooth operation of the aluminum electrolysis process and the final yield and quality of aluminum products. In the aluminum industry production process, anode carbon blocks need to be transported to the electrolysis workshop efficiently, accurately, and safely, and unloaded at specific locations to meet the requirements of continuous and stable operation of the electrolytic cells.

[0003] However, the transportation and unloading of anode carbon blocks currently faces numerous severe challenges. During transportation, the diverse scale and layout of aluminum plant areas—including the spatial limitations of small and medium-sized plants, the complex terrain of large plants, and the cross-regional scheduling needs under a multi-plant collaborative production system—make traditional transportation methods ill-suited to the requirements of different scenarios. Traditional transportation vehicles lack intelligent route planning and adaptive adjustment capabilities, easily leading to unreasonable route selection and low transportation efficiency in complex terrain. They may even cause transportation accidents due to the inability to avoid obstacles in time, affecting the normal supply of anode carbon blocks.

[0004] In the unloading process, insufficient precision is a prominent issue. Traditional unloading equipment often relies on simple mechanical control, making it difficult to operate precisely based on the actual position and condition of the anode carbon blocks, as well as the specific unloading requirements of different plant areas. This can lead to collisions and damage to the anode carbon blocks during unloading, resulting not only in resource waste and increased production costs, but also potentially affecting the normal operation of the electrolytic cell, reducing production efficiency and product quality.

[0005] To address this, we provide a transport and unloading system for assisting in the unloading of anode carbon blocks. Summary of the Invention

[0006] The purpose of this invention is to solve the problems in the prior art by proposing a transport and unloading system for assisting in the unloading of anode carbon blocks.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: A transport and unloading system for assisting in unloading anode carbon blocks includes a transport module, an unloading module, an intelligent sensing and control module, and a remote monitoring module; The transportation module is used to transport the anode carbon blocks and integrates a geographic information system, a real-time positioning system, multiple environmental sensors, and an adaptive suspension system. The unloading module is used to achieve precise unloading of anode carbon blocks, and integrates an intelligent unloading mechanism, a machine vision camera and a force feedback sensor; The intelligent sensing and control module is used for multi-source data fusion processing, dynamic path planning, and dumping parameter control. The remote monitoring module is built on a cloud computing platform and is used to realize remote monitoring, fault early warning and production scheduling optimization of the system; each module realizes data interaction and collaborative work through Internet of Things technology.

[0008] Preferably, in the transportation module, the geographic information system is used to acquire factory area terrain information; the real-time positioning system is used to acquire the location and speed of the transport vehicle in real time; the various environmental sensors include a temperature sensor, a humidity sensor, and an obstacle detection sensor, used to acquire temperature, humidity, and obstacle distribution data of the transportation environment; the adaptive suspension system automatically adjusts the suspension parameters of the transport vehicle based on the data acquired by the environmental sensors to maintain the stability of the transportation process.

[0009] Preferably, the dynamic path planning algorithm of the intelligent sensing and control module is based on the factory area terrain information obtained by the geographic information system, the position and speed of the transport vehicle obtained by the real-time positioning system, and environmental data obtained by various environmental sensors, and adjusts the transport path in real time to ensure that the transport vehicle reaches the destination in the shortest time and with the lowest energy consumption.

[0010] Preferably, the adaptive transportation module of the intelligent sensing and control module automatically adjusts transportation parameters based on information provided by the multi-source data fusion platform; when the transportation environment is detected to be high temperature and high humidity, the transportation speed is reduced; when the transportation road surface is detected to be uneven, the vehicle's suspension system is adjusted.

[0011] Preferably, the machine vision camera captures the position, posture, and trajectory of the anode carbon block in real time during the unloading process, and uses an image recognition algorithm to determine whether the carbon block deviates from the predetermined unloading position; the force feedback sensor is installed in a key part of the unloading mechanism to monitor the magnitude and direction of the force applied to the carbon block in real time during the unloading process.

[0012] Preferably, when the force feedback sensor detects an abnormal force, the intelligent sensing and control module immediately adjusts the unloading parameters, including the unloading angle and speed; when the force is too large and may damage the carbon block, the unloading angle or speed is reduced; when the force is too small and unloading cannot be completed, the unloading angle or speed is increased.

[0013] Preferably, the unloading module also has a status monitoring function, which records various data during the unloading process, including unloading time, force change curve, and carbon block position offset, and transmits these data to the intelligent sensing and control module for analysis and storage.

[0014] Preferably, the remote monitoring module transmits real-time data of the transport unloading system, including the location, speed, and status of the transport vehicles, and various parameters during the unloading process, to the cloud server via Internet of Things (IoT) technology; operators can then monitor the system's operating status in real time through terminal devices.

[0015] Preferably, the remote monitoring module utilizes big data analytics to deeply mine and analyze historical and real-time data, establishes a fault prediction model, predicts potential equipment failures in advance and issues early warning information; optimizes production scheduling based on production needs and system operation data, and rationally arranges transportation tasks and unloading times.

[0016] Preferably, the transportation module uses an electric railcar or an unmanned transport vehicle as the transportation carrier; the intelligent sensing and control module uses an algorithm model to realize the intelligent operation of the system; and the remote monitoring module provides a visual interface and remote operation functions.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. Employing low-cost electric railcars and basic sensor and control modules effectively controls construction costs while meeting basic production needs, enabling small and medium-sized enterprises to achieve intelligent management of anode carbon block transportation and unloading with minimal investment. The large-scale plant implementation uses advanced driverless transport vehicles and high-precision sensors, combined with powerful intelligent sensing and control modules, adapting to the complex terrain and heavy production tasks of large plants. This improves transportation efficiency and unloading accuracy, avoids management chaos and production accidents caused by scale expansion, and enhances overall production efficiency. The multi-plant collaborative production implementation, through hybrid transport carriers and a unified IoT platform, enables collaborative operations between plants of different sizes, optimizes resource allocation, reduces overall operating costs, and enhances the company's market competitiveness in complex production environments.

[0018] 2. In the transportation module, a high-precision Geographic Information System (GIS) and real-time positioning system, employing centimeter-level positioning accuracy and advanced obstacle detection sensors, significantly reduce the risk of collisions during transportation. In the unloading module, the intelligent unloading mechanism, combined with machine vision and force feedback sensors, can accurately identify the position and state of the anode carbon blocks, achieving precise unloading and avoiding damage to the carbon blocks and production accidents caused by improper unloading. The multi-plant collaborative production implementation also optimized parameters for the specifications of anode carbon blocks in different plants, further improving the accuracy of unloading.

[0019] 3. The intelligent sensing and control module, through multi-source data fusion and advanced algorithms, enables dynamic path planning to optimize transportation routes and reduce transportation time based on real-time traffic information and production tasks. Adaptive transportation parameter adjustment and unloading parameter control can adjust system operating parameters in real time according to environmental changes and production needs, improving the system's adaptability. The remote monitoring module enables remote real-time monitoring and management of the system, allowing operators to view system operating status anytime, anywhere, promptly identify and handle faults, and optimize production scheduling. In the multi-plant collaborative production embodiment, the unified remote monitoring center can comprehensively analyze production data from multiple plants, achieving global fault warnings and production scheduling optimization, further improving the overall operational efficiency of the production system. Detailed Implementation

[0020] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention. Example 1

[0021] In small and medium-sized aluminum plants, an electric railcar is used as the transport vehicle to construct an auxiliary unloading system for anode carbon blocks. This system consists of a transport module, an unloading module, an intelligent sensing and control module, and a remote monitoring module. These modules interact and collaborate using IoT technology. The transport module, integrated into the electric railcar, is responsible for acquiring relevant transport information and ensuring transport stability; the unloading module enables precise unloading and status recording of the anode carbon blocks; the intelligent sensing and control module provides intelligent decision-making for system operation; and the remote monitoring module enables remote management and monitoring of the system.

[0022] Transportation Module: The Geographic Information System (GIS) uses the open-source QGIS software to input terrain data such as the factory's track layout, curve radii, and slopes into the database. The real-time positioning system uses a GPS positioning module, installed at the front of the electric railcar, achieving meter-level accuracy. Temperature sensors, specifically the DS18B20, are installed inside the railcar near the anode carbon blocks; humidity sensors, such as the HS1101, are also installed inside the car. Obstacle detection sensors are ultrasonic sensors, installed at both the front and rear ends of the railcar, with a detection distance of 0.2-3 meters. The adaptive suspension system is designed specifically for the railcar's characteristics; sensors monitor vehicle vibration, and the controller uses a PID control algorithm to adjust the suspension spring stiffness.

[0023] Unloading Module: The intelligent unloading mechanism is driven by an electric push rod and installed at the rear of the railcar. The unloading angle can be adjusted within the range of 0-60°. A low-cost OV7670 machine vision camera is used, mounted above the rear of the railcar, and identifies the position of the anode carbon blocks through a simple image processing algorithm. A miniature strain gauge sensor is used for force feedback, installed at the connection between the electric push rod and the unloading platform, with a measurement range of 0-5000N. The status monitoring function records unloading time, force changes, and other data through a microcontroller and stores them in a local Flash chip.

[0024] Intelligent Sensing and Control Module: The multi-source data fusion platform uses a microcontroller as the core processor to perform simple fusion processing on data from the transportation and unloading modules. The dynamic path planning algorithm, based on GIS data and real-time location information, uses a simple shortest path algorithm to plan the railcar's route. Adaptive transportation parameter adjustment adjusts the transportation speed by controlling the railcar motor speed based on temperature and humidity data. Unloading parameter control adjusts the unloading angle by controlling the extension and retraction of the electric push rod based on force and visual information.

[0025] Remote monitoring module: Data is transmitted via Wi-Fi to a local server within the factory and stored using a MySQL database. Operators can view the track car's location, unloading status, and other information in real time using simple monitoring software installed on their computers, and can remotely control the track car's start and stop. Historical data is used for simple statistical analysis to provide fault warnings and optimize production scheduling. Example 2

[0026] In large aluminum plants, driverless transport vehicles are used to construct a transport and unloading system for auxiliary unloading of anode carbon blocks. The system also consists of a transport module, an unloading module, an intelligent sensing and control module, and a remote monitoring module. Through Internet of Things (IoT) technology, efficient data interaction and collaborative work between the modules are achieved to meet the transport and unloading needs of the complex production environment in large plants.

[0027] Transportation Module: The Geographic Information System (GIS) uses professional ArcGIS software to record detailed information on the complex terrain, building distribution, and road conditions of the factory area. The real-time positioning system employs dual-mode positioning using both GPS and BeiDou satellite navigation systems, achieving centimeter-level accuracy, and is installed on the roof of the transport vehicle. High-precision PT100 temperature sensors and Vaisala HMP110 humidity sensors are used, installed in multiple key locations inside the transport vehicle. Obstacle detection sensors combine LiDAR and millimeter-wave radar. The LiDAR, installed on the roof of the transport vehicle, can detect obstacles within a 50m range; the millimeter-wave radar is installed at the front and rear bumpers to detect nearby obstacles. The adaptive suspension system utilizes advanced magnetorheological suspension technology. Sensors monitor the vehicle's attitude in real time, and the controller uses a fuzzy control algorithm to quickly adjust the suspension damping.

[0028] Unloading Module: The intelligent unloading mechanism is hydraulically driven, using high-precision servo hydraulic cylinders. The unloading angle can be precisely adjusted within the range of 0-90°. The machine vision camera uses a high-resolution Baslerace2 series camera with a professional lens, mounted above the rear of the transport vehicle, and employs deep learning algorithms for the identification and positioning of anode carbon blocks. A high-precision six-dimensional force sensor is used for force feedback, installed at key locations in the unloading mechanism, with a measurement range of 0-20000N. The status monitoring function records detailed unloading data via an industrial computer and uploads it to a cloud server in real time.

[0029] Intelligent Sensing and Control Module: The multi-source data fusion platform uses a high-performance industrial computer as its core processor and employs a Kalman filter algorithm to fuse multi-source data. The dynamic path planning algorithm, based on GIS data, real-time location information, and traffic flow data, combines algorithms with dynamic obstacle avoidance strategies to plan the optimal path. Adaptive transportation parameter adjustment adjusts the vehicle's speed, acceleration, and other parameters in real time based on environmental data and transportation task requirements. Unloading parameter control uses advanced control algorithms to precisely adjust the unloading angle and speed based on force and visual information.

[0030] Remote monitoring module: Data is transmitted at high speed to the cloud server via 5G network and stored using a distributed storage system to ensure data security and reliability. Operators can monitor the real-time operating status of transport vehicles, unloading processes, and other information through professional monitoring software installed on computers or mobile terminals, enabling remote and precise control. Big data analytics and machine learning algorithms are used to deeply mine historical data, achieving accurate fault warnings and intelligent production scheduling optimization. Example 3

[0031] In a collaborative production system comprised of multiple aluminum plants, a mixed system of electric railcars and driverless transport vehicles is used to construct an auxiliary unloading system for anode carbon blocks. This system utilizes a unified Internet of Things (IoT) platform to enable data exchange and collaborative operation between the transport and unloading systems of each plant, adapting to the complex production scheduling and transportation needs of multiple plants.

[0032] Transportation Module: For electric railcars, GIS data is entered into the track information of each factory area using a unified coordinate system. The real-time positioning system selects an appropriate positioning method based on the different factory environments, such as using BeiDou short message positioning assistance in obstructed areas. The environmental sensor configuration is similar to that in Example 1, but is appropriately adjusted according to the climate characteristics of different factory areas. The adaptive suspension system is optimized for track characteristics. For unmanned transport vehicles, GIS data covers road and terrain information of multiple factory areas. The real-time positioning system uses multi-system fusion positioning to ensure accuracy. The environmental sensor configuration is the same as in Example 2, and the adaptive suspension system adjusts the control strategy according to the road conditions of different factory areas.

[0033] Unloading Module: The unloading module of the electric railcar is an improvement upon Embodiment 1. The intelligent unloading mechanism adds a manual emergency control device, the machine vision camera increases the image acquisition frequency, and the force feedback sensor enhances data transmission stability. The unloading module of the driverless transport vehicle is basically the same as Embodiment 2, but parameters are optimized for different anode carbon block specifications in different plant areas. The status monitoring function uniformly uses industrial Ethernet for data transmission to ensure data real-time performance.

[0034] Intelligent Sensing and Control Module: The multi-source data fusion platform utilizes cloud computing technology to centrally process data from multiple plant areas, employing more complex multi-source data fusion algorithms to improve data accuracy. The dynamic path planning algorithm considers the production plans and transportation tasks of multiple plant areas, using a genetic algorithm for global optimization path planning. Adaptive transportation parameter adjustment formulates personalized parameter adjustment strategies based on the environmental standards and production requirements of different plant areas. Unloading parameter control provides refined control based on the quality and unloading requirements of anode carbon blocks in different plant areas.

[0035] Remote monitoring module: A unified remote monitoring center is established, connecting the systems of various factory areas via a high-speed dedicated network. Data storage adopts a distributed file system to ensure data security and scalability. Operators can monitor the transportation and unloading situation of multiple factory areas in real time through a unified monitoring platform, enabling cross-factory scheduling and control. Big data and artificial intelligence technologies are used to comprehensively analyze production data from multiple factory areas, achieving global fault early warning and production scheduling optimization.

[0036] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A transport and unloading system for assisting in unloading anode carbon blocks, characterized in that, It includes a transportation module, a dumping module, an intelligent sensing and control module, and a remote monitoring module; The transportation module is used to transport the anode carbon blocks and integrates a geographic information system, a real-time positioning system, multiple environmental sensors, and an adaptive suspension system. The unloading module is used to achieve precise unloading of anode carbon blocks, and integrates an intelligent unloading mechanism, a machine vision camera and a force feedback sensor; The intelligent sensing and control module is used for multi-source data fusion processing, dynamic path planning, and dumping parameter control. The remote monitoring module is built on a cloud computing platform and is used to realize remote monitoring, fault early warning and production scheduling optimization of the system; each module realizes data interaction and collaborative work through Internet of Things technology.

2. The transport and unloading system for auxiliary unloading of anode carbon blocks according to claim 1, characterized in that, In the transportation module, the geographic information system is used to acquire factory area terrain information; the real-time positioning system is used to acquire the location and speed of the transport vehicle in real time; the various environmental sensors include temperature sensors, humidity sensors, and obstacle detection sensors, used to acquire temperature, humidity, and obstacle distribution data of the transportation environment; the adaptive suspension system automatically adjusts the suspension parameters of the transport vehicle based on the data acquired by the environmental sensors to maintain the stability of the transportation process.

3. The transport and unloading system for auxiliary unloading of anode carbon blocks according to claim 1, characterized in that, The dynamic path planning algorithm of the intelligent sensing and control module is based on the factory terrain information obtained by the geographic information system, the location and speed of the transport vehicles obtained by the real-time positioning system, and environmental data obtained by various environmental sensors. It adjusts the transport path in real time to ensure that the transport vehicles reach their destination in the shortest time and with the lowest energy consumption.

4. The transport and unloading system for auxiliary unloading of anode carbon blocks according to claim 1, characterized in that, The adaptive transportation module of the intelligent sensing and control module automatically adjusts transportation parameters based on information provided by the multi-source data fusion platform; when the transportation environment is detected to be high temperature and high humidity, the transportation speed is reduced; when the transportation road surface is detected to be uneven, the vehicle's suspension system is adjusted.

5. The transport and unloading system for auxiliary unloading of anode carbon blocks according to claim 1, characterized in that, In the unloading module, the machine vision camera captures the position, posture and trajectory of the anode carbon block in real time during the unloading process, and uses an image recognition algorithm to determine whether the carbon block deviates from the predetermined unloading position; the force feedback sensor is installed in a key part of the unloading mechanism to monitor the magnitude and direction of the force applied to the carbon block in real time during the unloading process.

6. The auxiliary unloading system for transporting and unloading anode carbon blocks according to claim 5, characterized in that, When the force feedback sensor detects an abnormal force, the intelligent sensing and control module immediately adjusts the unloading parameters, including the unloading angle and speed. If the force is too large and may damage the carbon block, the unloading angle or speed is reduced. If the force is too small and unloading cannot be completed, the unloading angle or speed is increased.

7. The transport and unloading system for auxiliary unloading of anode carbon blocks according to claim 1, characterized in that, The unloading module also has a status monitoring function, which records various data during the unloading process, including unloading time, force change curve, and carbon block position offset, and transmits these data to the intelligent sensing and control module for analysis and storage.

8. The transport and unloading system for auxiliary unloading of anode carbon blocks according to claim 1, characterized in that, The remote monitoring module transmits real-time data from the transport unloading system, including the location, speed, and status of the transport vehicles, as well as various parameters during the unloading process, to the cloud server via Internet of Things (IoT) technology; operators can then monitor the system's operational status in real time through terminal devices.

9. The transport and unloading system for auxiliary unloading of anode carbon blocks according to claim 1, characterized in that, The remote monitoring module utilizes big data analytics to deeply mine and analyze historical and real-time data, establishes fault prediction models, predicts potential equipment failures in advance, and issues early warning information; it also optimizes production scheduling based on production needs and system operation data, and rationally arranges transportation tasks and unloading times.

10. The transport and unloading system for auxiliary unloading of anode carbon blocks according to claim 1, characterized in that, The transportation module uses electric railcars or driverless transport vehicles as the transportation carrier; the intelligent sensing and control module uses algorithm models to realize the intelligent operation of the system; and the remote monitoring module provides a visual interface and remote operation functions.