Intelligent inspection and temperature measurement system and inspection and temperature measurement method for slow cooling field cinder ladles

Abstract

The invention discloses an intelligent inspection and temperature measurement system and method for a slow cooling field slag ladle, and the system comprises a mobile unmanned trolley, a background management system which carries out the data interaction with the mobile unmanned trolley through a wireless communication network, a UWB positioning base station and an automatic charging pile, and the mobile unmanned trolley is provided with a calculation unit, a drive unit and a sensing unit. The sensing unit comprises a laser radar, an on-line temperature measurement imager and a 2D camera, the calculation unit obtains sensing data from the sensing unit and generates a motion control instruction, and the calculation unit is used for calculating slag ladle temperature information obtained from the on-line temperature measurement imager and slag ladle number image information obtained from the 2D camera according to the motion control instruction. The positioning coordinate information is automatically associated with the UWB positioning base station and is sent to the background management system; according to the inspection temperature measurement method realized based on the system, an optimal path can be formulated based on trolley decision planning, and online temperature measurement is carried out on the cinder ladle along the pre-calculated path through the carried online temperature measurement imager.

Description

Technical Field

[0001] This application relates to the field of slow cooling management technology for smelting slag, and in particular to an intelligent patrol and temperature monitoring system and method for slag bags in slow cooling fields. Background Technology

[0002] A slow cooling field for smelting slag is a specially designed site or facility for the slow, controlled cooling process of molten slag from smelting furnaces. By controlling the cooling rate, slag can be transformed from an industrial waste into a recyclable secondary resource. After molten slag is discharged from the smelter, it is loaded into slag bags, which are then transported to the slow cooling field for heat dissipation and cooling. Slag bag cooling combines automatic and manual cooling methods to ensure that the slag is handled and stored at safe temperatures. Typically, converter slag cooling takes approximately 72 hours (24 hours of natural cooling and 48 hours of water cooling), while bottom-blown furnace slag cooling takes approximately 54 hours (18 hours of natural cooling and 36 hours of water cooling).

[0003] Regarding temperature measurement of slag bales in slow cooling fields, existing technologies have the technical problem of not being able to perform patrol temperature measurement of slag bales in slow cooling fields without gantry cranes or portal cranes.

[0004] To address the aforementioned issues, Chinese invention patent CN115683354A discloses a method and system for inspecting the temperature of slag bags in a slow cooling field. This system uses a ground-based wheeled mobile inspection robot equipped with an RFID reader, an infrared thermal imager, and a real-time positioning device to replace manual inspections. During routine inspections, it simultaneously acquires information about the slag bags, enabling the identification of the bag's location and number, and conducting temperature checks on the sidewalls of the slag bags.

[0005] Although the solutions disclosed in the aforementioned patent documents can be used for temperature monitoring of slag bags in slow cooling fields without gantry cranes or portal cranes, they still have the following drawbacks:

[0006] 1. Slag bag identification relies on RFID, requiring each slag bag to be fitted with a physical tag. In the rough industrial environment of slag bag handling, dumping, and stacking, the tags are easily impacted, torn, melted, or detached from the slag bag, resulting in permanent data loss. In addition, slag bags themselves are huge metal bodies, which have a shielding and reflection effect on radio signals, which will severely shorten the reading distance or even make them unreadable. Expensive anti-metal tags must be used. Therefore, the initial and ongoing investment costs of RFID are high. Furthermore, RFID systems usually only store a unique ID, and all associated information needs to be queried in the background database. The information obtained is limited in scope, and the system cannot identify slag bags without tags, which limits its applicability and flexibility.

[0007] 2. By equipping the ground wheeled mobile inspection robot with a real-time positioning device to achieve slag bag positioning and tracking, the real-time positioning device cannot assist the robot's movement route. Therefore, the solution described in this literature cannot cope with complex dynamic environments, poses a safety operation risk, and is difficult to achieve stable and efficient autonomous inspection when the site layout changes or temporary obstacles exist.

[0008] Therefore, the existing slag bag inspection and temperature monitoring system has high construction costs and insufficient adaptability and flexibility. It is necessary to provide a slag bag inspection solution that is more convenient to deploy, more intelligent to operate, and can achieve truly unmanned operation. Summary of the Invention

[0009] This application provides an intelligent patrol and temperature monitoring system and method for slag bags in a slow cooling field, which solves the problems of high deployment cost and insufficient system adaptability and flexibility of the existing slag bag patrol and temperature monitoring system.

[0010] To achieve the above objectives, this application provides the following technical solution:

[0011] On the one hand, this application provides an intelligent inspection and temperature monitoring system for slag bags in a slow cooling field, including a mobile unmanned vehicle, fixed auxiliary facilities and a background management system. The mobile unmanned vehicle interacts with the fixed auxiliary facilities and the background management system through a wireless communication network. The fixed auxiliary facilities include a UWB positioning base station that provides an absolute position reference for the mobile unmanned vehicle, and an automatic charging pile for charging the mobile unmanned vehicle.

[0012] The mobile unmanned vehicle includes a vehicle body, and a computing unit, a sensing unit, a driving unit, a communication module, a battery module, and a UWB positioning tag integrated on the vehicle body; the computing unit is electrically connected to the sensing unit and the driving unit respectively, and the computing unit is used to acquire sensing data from the sensing unit and generate control commands based on the sensing data;

[0013] The sensing unit includes at least an online temperature imaging device for collecting slag bag temperature information, a lidar and a vision camera for environmental perception, and a 2D camera for acquiring slag bag number image information; the computing unit is used to correlate the slag bag temperature information acquired from the online temperature imaging device, the slag bag number image information acquired from the 2D camera, and the positioning coordinate information acquired from the UWB positioning base station, and send them to the background management system through the communication module.

[0014] Optionally, in the above technical solution, the computing unit is an industrial control computer.

[0015] Optionally, the online temperature imaging device, lidar, vision camera, and 2D camera are communicatively connected to the computing unit via an Ethernet interface or a USB interface, and the computing unit is signal-connected to the communication module.

[0016] Optionally, the drive unit includes a motor driver, which receives vehicle motion control commands from the computing unit via a CAN bus or serial port. The motor driver can drive a servo motor mounted on the vehicle body according to the received vehicle motion control commands.

[0017] Optionally, the sensing unit further includes an inertial measurement unit, which is connected to the computing unit via a serial port or SPI interface. The inertial measurement unit is used to provide the computing unit with the attitude and acceleration data of the mobile unmanned vehicle.

[0018] Optionally, the visual camera is mounted on the mobile unmanned vehicle, and the computing unit is used to execute a path planning algorithm based on the point cloud data acquired by the lidar to plan the vehicle's travel path and perform synchronous positioning and map construction. The computing unit is also used to execute a visual perception algorithm based on the image information acquired by the visual camera to identify dynamic obstacles, thereby realizing the vehicle's autonomous navigation and obstacle avoidance.

[0019] Optionally, the fixed auxiliary facility also includes a wireless access point covering the slow cooling field operation area. The mobile unmanned vehicle is equipped with a wireless client, which establishes a network connection with the background management system through the wireless access point to realize data communication between the computing unit and the background management system. The computing unit can upload vehicle location information, vehicle travel path information, vehicle speed information, vehicle power information, slag bag temperature information, and slag bag number image information to the background management system.

[0020] Optionally, the back-end management system includes a manufacturing execution system and / or a data server.

[0021] Optionally, the automatic charging pile and the mobile unmanned vehicle have a communication interface. The computing unit is used to monitor the battery module's power level in real time and compare the real-time power level of the battery module with a charging threshold. The computing unit can control the mobile unmanned vehicle to move to the physical docking position of the automatic charging pile and initiate the charging process through the communication interface.

[0022] Optionally, the intelligent temperature monitoring system for slag bags in the slow cooling field also includes a human-machine interface terminal; the human-machine interface terminal is an industrial control computer display or touch screen installed on the on-site operating console or in the remote monitoring room, and the human-machine interface terminal is connected to the background management system and / or the computing unit of the mobile unmanned vehicle through a wireless network. The human-machine interface terminal is used to display the system status, send one-click start commands, send emergency stop commands, and perform remote control.

[0023] Optionally, the mobile unmanned vehicle is equipped with an electric gimbal, and the online temperature measurement imager is mounted on the electric gimbal. The electric gimbal includes a drive motor module for driving the online temperature measurement imager to perform pitch and horizontal rotation movements. The drive motor module is communicatively connected to the computing unit. The computing unit controls the movement of the drive motor module according to the position and size of the target slag bag, thereby adjusting the pitch and horizontal rotation angles of the online temperature measurement imager.

[0024] On the other hand, based on the aforementioned intelligent temperature monitoring system for slag bags in slow cooling zones, this application also provides a method for temperature monitoring of slag bags in slow cooling zones, the method comprising:

[0025] The background management system sends inspection task instructions to the computing unit of the mobile unmanned vehicle;

[0026] The computing unit performs global path planning based on the inspection task instructions and the environmental data obtained from the lidar and vision camera.

[0027] The drive unit drives the mobile unmanned vehicle to move along the planned path according to the motion control commands generated by the computing unit;

[0028] During the movement, the computing unit receives and processes the perception data from the lidar and vision camera in real time, and fuses the absolute position information obtained from the UWB positioning base station to achieve real-time positioning and dynamic obstacle avoidance.

[0029] When the device moves to the target slag bag, the online temperature imaging instrument acquires an infrared thermal image of the side wall of the slag bag, and the computing unit identifies the temperature of the slag bag; the 2D camera captures an image of the slag bag number, and the computing unit performs image recognition to obtain the slag bag number; the computing unit associates the obtained slag bag number with the identified temperature data, and uploads it to the background management system via a wireless communication network.

[0030] The above technical solution includes "performing global path planning based on environmental data acquired from the lidar and vision camera" specifically as follows:

[0031] The point cloud data acquired by the lidar is fused with the image data acquired by the vision camera to construct a two-dimensional cost map containing semantic information about obstacles.

[0032] On the two-dimensional cost map, based on the given starting point and target point, a collision-free optimal global path is planned using the Hybrid A* algorithm.

[0033] The above technical solution's phrase "the computing unit receives and processes the perception data from the lidar and vision camera in real time, and fuses it with the absolute location information obtained from the UWB positioning base station" specifically includes:

[0034] Using the aforementioned lidar and vision camera, a local high-precision point cloud map is generated based on the SLAM algorithm, and the pose of the mobile unmanned vehicle is estimated.

[0035] The absolute coordinates of the mobile unmanned vehicle are obtained through the UWB positioning base station;

[0036] The Kalman filter algorithm is used to fuse the pose of the mobile unmanned vehicle estimated by the SLAM algorithm with the UWB absolute coordinates to output the optimized pose of the mobile unmanned vehicle.

[0037] In the above technical solution, after "the calculation unit associates the obtained slag bag number with the identified temperature data and uploads it to the background management system via a wireless communication network," it further includes:

[0038] The back-end management system receives and stores the bound data;

[0039] The background management system generates a temperature change trend chart based on the temperature data of the same slag bag at different time points. When the temperature change trend chart shows an abnormal rate of temperature decrease or the current temperature exceeds the safety threshold, a signal is sent to the human-machine interaction terminal, which then issues an alarm message.

[0040] Compared with the prior art, this application has at least the following beneficial effects:

[0041] 1. This application utilizes a 2D camera to achieve long-distance image acquisition of slag bag numbers. No hardware modifications to existing slag bags are required during system deployment. Image acquisition not only allows for the reading of slag bag numbers but also provides direct visual information for verification when manual inspection is needed. Furthermore, the image information can also acquire additional visual information, such as slag bag shape, surface condition, leakage status, and surrounding environmental safety, providing a wide range of information dimensions. In addition, this system completely eliminates the risk of identification failure due to label damage, detachment, or contamination in harsh industrial environments during long-term operation and maintenance, significantly improving system reliability and stability. Moreover, this system is highly versatile and can flexibly identify any slag bag entering the slow cooling field, even if the bag has not been entered into the system or is unlabeled, thus solving the problems of limited applicability and insufficient flexibility of existing technical solutions. Furthermore, compared to existing technologies that may rely on simple preset paths or navigation schemes with limited accuracy, the mobile unmanned vehicle in this system can obtain its precise location in the environment in real time and achieve autonomous navigation and dynamic obstacle avoidance through lidar. The vehicle can autonomously and flexibly reach each target slag bag without relying on a fixed track, which greatly improves the safety of the vehicle's operation in complex and dynamic industrial sites. Finally, this application automatically associates and sends the slag bag temperature information, slag bag number image information, and vehicle location information to the background management system through the calculation unit. This provides precise information such as "the mobile unmanned vehicle measured the temperature of which slag bag at which location and at what time," which can provide real-time and accurate decision-making basis for production management. Managers can clearly grasp the cooling process of each slag bag and improve the level of process management.

[0042] 2. This application uses lidar and vision cameras for environmental perception, providing a hardware foundation and reliable perception data for the vehicle's autonomous navigation and obstacle avoidance. In addition, the motor driver on the vehicle receives the vehicle motion control commands issued by the computing unit through the CAN bus or serial port, ensuring the real-time performance, anti-interference and accuracy of the control command transmission, making the vehicle's movement more precise and stable, and able to adapt to complex ground conditions in a slow-cooling field.

[0043] 3. This application considers that the data from LiDAR and vision cameras may be temporarily blurred or lost when the vehicle moves at high speed or experiences severe bumps, causing jumps or drifts in the instantaneous position and attitude calculated based on them. Therefore, the perception unit of this application also includes an inertial measurement unit (IMU). The IMU can continuously measure the angular velocity and acceleration of the vehicle and provide high-frequency attitude and position change information through calculation. By fusing the IMU data with LiDAR SLAM, the IMU data can be used to compensate for the positioning estimation during severe motion or temporary sensor failure, and always provide a stable attitude reference for the robot, thereby making the robot's positioning results more reliable and the navigation trajectory smoother.

[0044] 4. The mobile unmanned vehicle in this application can use its onboard LiDAR to scan the surrounding environment, generate point cloud data, and use a visual camera to assist in identifying dynamic obstacles. An IMU is used to compensate for vibrations and tilts during movement. A SLAM algorithm combining LiDAR and vision is used to build a high-precision map of the station in real time. The absolute positioning of the UWB positioning base station is combined with the local positioning of the LiDAR to ensure high-precision positioning in the station where GPS signals are limited. In addition, the Hybrid A* algorithm can be used to generate the optimal path based on the information in the map and achieve autonomous obstacle avoidance. Therefore, the mobile unmanned vehicle in this application has environmental perception, localization and mapping, path planning and dynamic obstacle avoidance functions, ensuring that the vehicle can move safely and efficiently in the cooling field and accurately reach the target work position.

[0045] 5. This application uses a wireless network covering the entire site to communicate, enabling continuous and stable high-speed data interaction between the mobile unmanned vehicle and the back-end management system. Specifically, the mobile unmanned vehicle can transmit the collected slag bag temperature data, slag bag number information, and its own status information to the back-end management system in real time and without interruption. At the same time, the control commands and scheduling tasks issued by the back-end can also be reliably received by the vehicle, which provides a reliable communication guarantee for real-time monitoring and remote scheduling of the entire process.

[0046] 6. This application manages the vehicle's power in real time through the computing unit on the vehicle, and automatically returns to the charging station to complete charging when the power is low, without the need for manual intervention, thus achieving unmanned operation.

[0047] 7. The intelligent patrol temperature monitoring system provided in this application can upload the measured slag bag number information, slag bag temperature, real-time location and other information to the Manufacturing Execution System (MES), providing the MES system with accurate real-time on-site data, enabling production schedulers to directly monitor the cooling status of each slag bag in the MES, accurately guide production operations, and realize the visualization and refined management of the production process.

[0048] 8. The intelligent inspection and temperature monitoring system provided in this application has a human-machine interface terminal, which provides an intuitive and convenient operation and monitoring entry point for the entire life cycle management of the system, greatly improving the system's ease of use and maintainability. Through the graphical human-machine interface, operators can clearly grasp the operating status of the entire system, the trolley position status, the slag bag temperature, and alarm information. The "one-click start" function simplifies complex inspection tasks into a single operation, greatly reducing the operating threshold. In addition, the remote control function provides a safe and effective intervention method for the system to handle abnormal situations, ensuring the safety of the system and personnel in complex emergencies and realizing human-machine collaboration.

[0049] 9. Based on the intelligent inspection and temperature monitoring system for slag bags in the slow cooling field provided in this application, this application also provides a method for inspection and temperature monitoring of slag bags in the slow cooling field. This method provides a highly collaborative, fully automated, and intelligent closed-loop operation process. Specifically, this method uses a lidar SLAM algorithm to achieve autonomous navigation and dynamic obstacle avoidance of the vehicle, and obtains slag bag number information non-contactly through image recognition, avoiding the burden of deploying and maintaining physical tags. In addition, this method can intelligently associate and upload the tags with temperature information, forming a complete and reliable data chain. This method not only greatly improves operation efficiency and safety, but also ensures the accuracy and traceability of the collected data. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the embodiments will be briefly described below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. It should be understood that the specific shapes and structures shown in the drawings should not generally be regarded as limiting conditions for implementing this application. For example, based on the technical concepts disclosed in this application and the exemplary drawings, those skilled in the art are able to easily make conventional adjustments or further optimizations to the addition / reduction / classification, specific shapes, positional relationships, connection methods, and size ratios of certain units (components).

[0051] Figure 1 This is a system architecture diagram of the intelligent temperature monitoring system for slag bags in the slow cooling field provided in this application, as one embodiment.

[0052] Figure 2 This is a system hardware architecture diagram of the intelligent inspection and temperature monitoring system for slag bags in the slow cooling field provided in this application, as one embodiment.

[0053] Figure 3 This is a system software architecture diagram of the intelligent patrol and temperature monitoring system for slag bags in the slow cooling field provided in this application, as one embodiment.

[0054] Figure 4 This is a schematic diagram of the backend interface for autonomous navigation, positioning, and trajectory planning of a mobile unmanned vehicle in one embodiment.

[0055] Figure 5 This is a schematic diagram of the structure of the mobile unmanned vehicle in this application in one embodiment;

[0056] Figure 6 This is a system overall design layout diagram in one embodiment, which mainly shows the placement of slag bags and the inspection route of the trolley.

[0057] Explanation of reference numerals in the attached figures:

[0058] 1. LiDAR; 2. Voice warning light; 3. Online temperature imaging device; 4. Mobile chassis; 5. Slag bag; 6. Cart inspection route. Detailed Implementation

[0059] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0060] In the description of this application: unless otherwise stated, "a plurality of" means two or more. The terms "comprising," "including," "having," etc., used in this application also mean "not limited to" (certain units, components, materials, steps, etc.).

[0061] The terms used in this application, such as "upper," "lower," "left," "right," and "middle," are generally used to facilitate intuitive understanding by referring to the accompanying drawings, and are not absolute limitations on the positional relationships in the actual product. Changes in these relative positional relationships, without departing from the technical concept disclosed in this application, should also be considered within the scope of this application.

[0062] This application provides an intelligent temperature monitoring system for slag bags in a slow cooling field, mainly comprising a human-computer interaction layer, an execution layer, a decision-making layer, and a perception layer, such as... Figure 1 The human-machine interface (HMI) layer primarily consists of the human-machine interface, such as a control panel or touchscreen. The execution layer comprises the execution mechanism, mainly including mobile unmanned vehicles (UAVs). The decision-making layer mainly includes trajectory planning, motion control, and autonomous obstacle avoidance for the mobile UAVs. The perception layer includes LiDAR, 2D cameras, and online temperature imaging devices. This system utilizes mobile UAVs carrying online temperature imaging devices, combined with autonomous driving technology, wireless communication technology, image recognition technology, and intelligent control technology, to automatically collect and identify the numbers of each slag bag stored in the slow-cooling area, automatically collect and detect its temperature, and determine its placement. Simultaneously, the collected data is transmitted in real-time to the slag bag information management system in the slow-cooling area. This system is highly integrated and easy to deploy on-site. Only one mobile UAV system is needed to complete the temperature measurement of slag bags throughout the entire plant area. Using this system enables intelligent patrol and temperature monitoring by the UAVs, reducing manual intervention, lowering labor costs, improving the working environment, and enhancing worker safety. The following detailed description of the system architecture and functions of this intelligent patrol and temperature monitoring system for slag bags in the slow-cooling area, using specific embodiments, is provided below.

[0063] Example 1

[0064] This application provides an intelligent inspection and temperature monitoring system for slag bags in a slow-cooling field. The system mainly includes a mobile unmanned vehicle, fixed auxiliary facilities, and a back-end management system. The mobile unmanned vehicle interacts with both the fixed auxiliary facilities and the back-end management system via a wireless communication network. The mobile unmanned vehicle acts as a composite robot that automatically moves within the target area, replacing humans in inspections.

[0065] The mobile unmanned vehicle (UAV), serving as the system's mobile execution terminal, comprises the vehicle body and integrated computing, sensing, drive, communication, battery, and UWB positioning tags. The computing unit is electrically connected to both the sensing and drive units, acquiring sensory data and generating control commands based on it. As the control core, the computing unit connects to all other units via internal cables, primarily handling sensory computation, decision-making, planning, and motion control of the UAV. The sensing unit is mounted on the top of the vehicle. An online temperature imaging device faces sideways for scanning slag bags. A lidar sensor, serving as the primary environmental sensor, can be single or multiple. A single lidar can be mounted at the center of the roof, while multiple lidars can be distributed around the vehicle. A vision camera assists in visual recognition and can be mounted on the front wall of the vehicle. A 2D camera acquires images of slag bag numbers; it is installed facing sideways to capture images of slag bags on both sides. The drive unit's motor driver is installed inside the vehicle and directly connected to the control motor. The battery module (high-capacity lithium battery pack) serves as the power source and is placed at the bottom of the vehicle to lower the center of gravity.

[0066] Fixed auxiliary facilities include UWB positioning base stations that provide absolute position references for the mobile unmanned vehicles (UAVs), and automatic charging stations for charging the UAVs. At least three UWB positioning base stations are deployed on the rooftops or pillars of the cooling field, forming a positioning network covering the entire work area. After the UWB base station transmits a signal, the UWB tag on the UAV receives the signal, and then the computing unit obtains the positioning data from the UWB tag to obtain the UAV's absolute coordinates. Automatic charging stations are installed in a dedicated charging area at the edge of the site, with their charging contacts physically corresponding to the charging contacts on the UAV.

[0067] The back-end management system mainly runs the system's monitoring and scheduling software.

[0068] The mobile unmanned vehicle connects to the on-site wireless access point (a fixed facility) via its built-in Wi-Fi / 5G module, thereby communicating with the back-end management system (back-end server) and the UWB base station network. This enables the mobile unmanned vehicle to autonomously navigate and locate itself in the slow cooling field, plan its trajectory, and control its motion. It also performs automatic temperature measurement of slag bags during autonomous driving. The mobile unmanned vehicle's computing unit correlates the slag bag temperature information acquired from the online temperature imaging device, the slag bag number image information acquired from the 2D camera, and the positioning coordinate information obtained from the UWB positioning base station, and sends this information to the back-end management system via the communication module. This provides precise information such as "the mobile unmanned vehicle measured the temperature of which slag bag at which location and at what time," offering real-time and accurate decision-making support for production management. Managers can clearly grasp the cooling process of each slag bag, improving process management.

[0069] In a preferred embodiment of this application, the computing unit may be an industrial control computer (ICC). The online temperature imaging device, lidar, vision camera, and 2D camera are all connected to the ICC's network port via network cables to transmit large amounts of thermal images, point cloud data, visual image information, and slag bag number image information. The drive unit on the trolley includes a motor driver. The ICC is connected to the motor driver via a CAN bus or serial port. The ICC can send command information to the motor driver via the CAN protocol, and the motor driver then drives the servo motors connected to the wheels to perform motion, thereby realizing the motion control of the trolley.

[0070] In a preferred embodiment of this application, the sensing unit further includes an inertial measurement unit (IMU). The IMU is connected to the computing unit via a serial port or SPI interface. The IMU provides the computing unit with attitude and acceleration data of the mobile unmanned vehicle. The IMU is directly connected to the serial port of the industrial control computer via a serial cable. During vehicle navigation, the computing unit reads the three-axis acceleration and angular velocity data provided by the IMU in real time to compensate for vehicle motion during LiDAR scanning intervals, reducing positioning drift. This is particularly effective in improving positioning accuracy when the vehicle accelerates or decelerates rapidly or traverses bumpy surfaces.

[0071] In a preferred embodiment of this application, the computing unit is equipped with a path planning algorithm and a visual perception algorithm. The computing unit can execute the path planning algorithm based on the point cloud data acquired by the lidar to plan the vehicle's travel path and perform synchronous positioning and map construction. The computing unit can also execute the visual perception algorithm based on the image information acquired by the visual camera to identify dynamic obstacles, thereby realizing the vehicle's autonomous navigation and obstacle avoidance.

[0072] In a preferred embodiment of this application, the fixed auxiliary facilities further include wireless access points (APs) covering the slow cooling field operation area. These APs are connected to a switch via network cables to form a roaming network. The mobile unmanned vehicle is equipped with a wireless client (such as a WiFi / 5G module). When the mobile unmanned vehicle moves within the field, it can automatically switch between different APs to maintain a stable connection with the network, thereby ensuring uninterrupted data communication with the back-end management system (such as uploading vehicle location information, vehicle travel path information, vehicle speed information, vehicle battery information, slag bag temperature information, slag bag number image information, and receiving instructions).

[0073] In a preferred embodiment of this application, the back-end management system includes a Manufacturing Execution System (MES) and / or a data server. After the mobile unmanned vehicle completes temperature measurement of a slag bag, the computing unit associates the data "slag bag number, current location, highest temperature, and timestamp" and sends it to the back-end management system. The back-end management system receives and parses the data before storing and displaying it. This Manufacturing Execution System (MES) can be an information management system for slag bags in the factory's slow cooling area. That is, the data measured by the mobile unmanned vehicle can also be synchronized to the MES system via the Enterprise Service Bus (ESB), allowing production managers to directly view the real-time cooling status of each slag bag in the MES, thus achieving synchronization between inspection data and production management.

[0074] In a preferred embodiment of this application, the automatic charging pile and the mobile unmanned vehicle have a communication interface. The computing unit monitors the battery module's power level in real time and compares it with a charging threshold. When the real-time power level is lower than the charging threshold, the computing unit controls the mobile unmanned vehicle to move to the physical docking position of the automatic charging pile and initiates a charging process through the communication interface. The mobile unmanned vehicle's return path to the charging pile can be autonomously navigated by LiDAR and a vision camera. When the mobile unmanned vehicle approaches the automatic charging pile, it can automatically dock and charge. After fully charged, the charging pile can send a stop signal to the computing unit, which then controls the vehicle to automatically detach from the charging pile and move to a standby position.

[0075] In a preferred embodiment of this application, the intelligent temperature monitoring system for slag bags in the slow cooling field further includes a human-machine interface (HMI) terminal. The HMI terminal is an industrial control computer display or touchscreen installed on the on-site operating console or in a remote monitoring room. The HMI terminal is connected to the back-end management system and / or the computing unit of the mobile unmanned vehicle via a wireless network. The HMI terminal is used to display system status, send one-click start commands, send emergency stop commands, and perform remote control. In specific applications, a touchscreen can be installed in the central control room as the HMI terminal. This touchscreen is connected to the back-end management system (i.e., the back-end server) via a network cable to display the monitoring interface. The operator can see a map of the entire slow cooling field, the real-time location of the vehicle, a list of temperatures for all slag bags, and alarm information on the interface. Simultaneously, the interface also has a "one-click start" button. Clicking this button sends control commands to the back-end management system via the network, which then dispatches the mobile unmanned vehicle to execute tasks. Furthermore, the interface provides a remote control mode. When intervention is needed, the operator can switch to this mode and send direct movement commands to the robot via a virtual joystick on the interface.

[0076] In a preferred embodiment of this application, an electric gimbal is installed on a mobile unmanned vehicle, and the online temperature measuring imager is mounted on the electric gimbal. The electric gimbal includes a drive motor module for driving the online temperature measuring imager to perform pitch and horizontal rotation movements. The drive motor module is communicatively connected to the computing unit. The computing unit controls the movement of the drive motor module according to the position and size of the target slag bag, thereby adjusting the pitch and horizontal rotation angles of the online temperature measuring imager. This facilitates the online temperature measuring imager to acquire images of the slag bag numbers, and the imager can scan the temperature of the slag bag from a distance, improving operational efficiency.

[0077] In one embodiment, a slag bag inspection route can be planned in the slow cooling field, such as... Figure 6 The mobile unmanned vehicle can perform inspections along the slag bag inspection route, detecting dynamic obstacles in real time during its movement and autonomously avoiding them if any are found. Of course, the mobile unmanned vehicle in this application has autonomous navigation and path planning capabilities; therefore, planning the slag bag inspection route in the cooling field is not necessary. In practice, instructions can be issued to the mobile unmanned vehicle to designate specific areas for inspection, and the vehicle can automatically navigate to the target area, autonomously avoiding obstacles during its journey.

[0078] In one embodiment, the mobile unmanned vehicle is equipped with a voice warning light that can issue voice warnings during movement.

[0079] In summary, the intelligent inspection and temperature monitoring system for slag bags in the slow cooling field provided in this application requires no hardware modification to existing slag bags during system deployment. Through image acquisition, it can not only read the slag bag number but also directly view the number for easy verification when manual inspection is required. Simultaneously, it can acquire additional visual information through image data, such as slag bag shape, surface condition, leakage status, and surrounding environmental safety, providing a wide range of information dimensions. Furthermore, this system completely avoids the risk of identification failure due to label damage, detachment, or contamination in harsh industrial environments during long-term operation and maintenance, greatly improving the system's reliability and stability. Moreover, this system is highly versatile and can flexibly identify any slag bag entering the slow cooling field, even if the slag bag has not been entered into the system or is unlabeled, thus solving the problems of limited applicability and insufficient flexibility of existing technical solutions. Furthermore, compared to existing technologies that may rely on simple preset paths or navigation schemes with limited accuracy, the mobile unmanned vehicle in this system can obtain its precise location in the environment in real time and achieve autonomous navigation and dynamic obstacle avoidance through lidar. The vehicle can autonomously and flexibly reach each target slag bag without relying on a fixed track, greatly improving the safety of the vehicle's operation in complex and dynamic industrial environments. Finally, this application automatically associates and sends the slag bag temperature information, slag bag number image information, and vehicle location information to the background management system through a computing unit. This provides precise information such as "the mobile unmanned vehicle measured the temperature of which slag bag at which location and at what time," providing real-time and accurate decision-making basis for production management. Managers can clearly grasp the cooling process of each slag bag, improving the level of process management.

[0080] Example 2

[0081] Based on the intelligent temperature monitoring system for slag bags in a slow cooling field provided in Embodiment 1, this embodiment provides a method for temperature monitoring of slag bags in a slow cooling field, which includes the following steps:

[0082] S1: The background management system sends an inspection task instruction to the computing unit of the mobile unmanned vehicle;

[0083] S2: The computing unit performs global path planning based on the inspection task instruction and the environmental data obtained from the lidar and vision camera;

[0084] S3: The driving unit drives the mobile unmanned vehicle to move along the planned path according to the motion control command generated by the computing unit;

[0085] S4: During the movement, the computing unit receives and processes the perception data from the lidar and vision camera in real time, and fuses the absolute position information obtained from the UWB positioning base station to achieve real-time positioning and dynamic obstacle avoidance.

[0086] S5: When moving to the target slag bag, the online temperature imaging instrument acquires an infrared thermal image of the side wall of the slag bag, and the calculation unit identifies the temperature of the slag bag; the 2D camera captures an image of the slag bag number, and the calculation unit performs image recognition to obtain the slag bag number; the calculation unit associates the obtained slag bag number with the identified temperature data, and uploads it to the background management system through a wireless communication network.

[0087] The step S2 above, "performing global path planning based on environmental data acquired from the LiDAR and the vision camera", specifically includes: fusing the point cloud data acquired by the LiDAR with the image data acquired by the vision camera to construct a two-dimensional cost map containing obstacle semantic information; and on the two-dimensional cost map, based on a given starting point and target point, planning a collision-free optimal global path using the Hybrid A* algorithm.

[0088] The step S4 above, "the computing unit receives and processes the perception data from the LiDAR and the vision camera in real time, and fuses the absolute position information obtained from the UWB positioning base station," specifically includes: generating a local high-precision point cloud map based on the SLAM algorithm using the LiDAR and the vision camera, and estimating the pose of the mobile unmanned vehicle; obtaining the absolute coordinates of the mobile unmanned vehicle using the UWB positioning base station; and using the Kalman filter algorithm to fuse the mobile unmanned vehicle pose estimated by the SLAM algorithm with the UWB absolute coordinates, and outputting the optimized mobile unmanned vehicle pose.

[0089] After the above step S5, which states that "the calculation unit associates the obtained slag bag number with the identified temperature data and uploads it to the background management system via the wireless communication network," the following additional steps are included:

[0090] The back-end management system receives and stores the bound data;

[0091] The background management system generates a temperature change trend chart based on the temperature data of the same slag bag at different time points. When the temperature change trend chart shows an abnormal rate of temperature decrease or the current temperature exceeds the safety threshold, a signal is sent to the human-machine interaction terminal, which then issues an alarm message.

[0092] The software platform architecture supporting the above-mentioned slow-cooling field slag bag temperature monitoring method includes: user layer, application layer, algorithm layer, data layer, communication layer, driver layer, and hardware layer. (See [link to relevant documentation]). Figure 3 .in:

[0093] 1. The hardware layer includes mobile unmanned vehicles and sensors (visual and online temperature imaging devices).

[0094] 2. Driver layer: Provides drivers and standardized interfaces for hardware devices, such as motor drivers, sensor data reading, and protocol parsing.

[0095] 3. Communication Layer: Handles inter-module communication, task scheduling, and resource management, such as operating system, real-time message passing, message queue, and service calls.

[0096] 4. Data Layer: Responsible for real-time data stream processing and historical database storage, recording relevant data of system operation, such as the number of system operations, the time of each operation, system failure rate, etc., which can be queried by year, month, day and work group.

[0097] 5. Algorithm Layer: Implements core intelligent algorithms and functional services, such as computer vision, perception and localization, mobile vehicle trajectory planning and motion control, machine learning, etc. The algorithm layer focuses on processing specific business logic and realizing the core functions of the system.

[0098] 6. Application Layer: The core of the application layer, handling business logic, executing business logic and specific task flows, including process flow, task scheduling, exception handling logic, and integration with the on-site MES system. The application layer receives data and instructions from the user interface layer and performs logical processing and data manipulation according to the system's business requirements. This layer contains many services, business modules, and algorithms to complete specific functions and tasks. The application layer does not depend on a specific data storage method but interacts with the data access layer through interfaces.

[0099] 7. User Layer: This is the part where users directly interact. It provides a graphical or command-line interface, allowing users to input data, send commands, and view system output. The user layer provides human-computer interaction and monitoring interfaces, such as HMIs, remote control terminals, debugging tools, logs, and alarms. The main task of this layer is to receive user input, display data, and pass user actions to the next layer for processing. It focuses on user experience and interaction and is typically responsible for front-end development.

[0100] The temperature monitoring method for slag bags in the slow cooling field provided in this application enables automatic online temperature measurement by a trolley. Based on the unmanned vehicle's decision-making and planning, an optimal path is formulated. The online temperature measurement imager mounted on the top of the unmanned vehicle measures the temperature of the slag bag along the pre-calculated path. The trolley's autonomous navigation, positioning, and trajectory planning functions ensure that the trolley can move safely and efficiently within the factory and accurately reach the target work location. During the movement, environmental perception, positioning and mapping, path planning, and dynamic obstacle avoidance are achieved. The mobile unmanned vehicle's work area does not require human intervention, and the operator can operate it with one click indoors.

[0101] In summary, the slag bag temperature monitoring method for slow cooling fields provided in this application offers a highly collaborative, fully automated, and intelligent closed-loop operation process. This method utilizes a lidar SLAM algorithm to achieve autonomous navigation and dynamic obstacle avoidance for the vehicle, and obtains slag bag number information non-contactly through image recognition, avoiding the burden of deploying and maintaining physical tags. Furthermore, this method can intelligently associate and upload the tags with temperature information, forming a complete and reliable data chain. This approach not only significantly improves operational efficiency and safety but also ensures the accuracy and traceability of the collected data.

[0102] The technical features of the above embodiments can be combined in any way (as long as there is no contradiction in the combination of these technical features). For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described; these embodiments not explicitly written should also be considered to be within the scope of this specification.

[0103] The present application has been described in a relatively specific and detailed manner above through general descriptions and specific embodiments. It should be understood that, based on the technical concept of the present application, several conventional adjustments or further innovations can be made to these specific embodiments; however, as long as they do not depart from the technical concept of the present application, the technical solutions obtained by these conventional adjustments or further innovations also fall within the protection scope of the claims of the present application.

Claims

1. A smart temperature monitoring system for slag bags in a slow cooling field, characterized in that, The system includes a mobile unmanned vehicle, fixed auxiliary facilities, and a back-end management system. The mobile unmanned vehicle interacts with the fixed auxiliary facilities and the back-end management system via a wireless communication network. The fixed auxiliary facilities include a UWB positioning base station that provides an absolute position reference for the mobile unmanned vehicle, and an automatic charging pile that charges the mobile unmanned vehicle. The mobile unmanned vehicle includes a vehicle body, and a computing unit, a sensing unit, a driving unit, a communication module, a battery module, and a UWB positioning tag integrated on the vehicle body; the computing unit is electrically connected to the sensing unit and the driving unit respectively, and the computing unit is used to acquire sensing data from the sensing unit and generate control commands based on the sensing data; The sensing unit includes at least an online temperature imaging device for collecting slag bag temperature information, a lidar and a vision camera for environmental perception, and a 2D camera for acquiring slag bag number image information; the computing unit is used to correlate the slag bag temperature information acquired from the online temperature imaging device, the slag bag number image information acquired from the 2D camera, and the positioning coordinate information acquired from the UWB positioning base station, and send them to the background management system through the communication module.

2. The intelligent temperature monitoring system for slag bags in the slow cooling field according to claim 1, characterized in that, The computing unit is an industrial control computer; The online temperature imaging device, lidar, vision camera and 2D camera are connected to the computing unit via Ethernet interface or USB interface, and the computing unit is signal-connected to the communication module. The drive unit includes a motor driver, which receives vehicle motion control commands from the computing unit via a CAN bus or serial port. The motor driver can drive a servo motor mounted on the vehicle body according to the received vehicle motion control commands.

3. The intelligent temperature monitoring system for slag bags in the slow cooling field according to claim 2, characterized in that, The sensing unit also includes an inertial measurement unit, which is connected to the computing unit via a serial port or SPI interface. The inertial measurement unit is used to provide the computing unit with the attitude and acceleration data of the mobile unmanned vehicle.

4. The intelligent temperature monitoring system for slag bags in the slow cooling field according to claim 2, characterized in that, The visual camera is mounted on the mobile unmanned vehicle. The computing unit is used to execute a path planning algorithm based on the point cloud data acquired by the lidar to plan the vehicle's travel path and perform synchronous positioning and map construction. The computing unit is also used to execute a visual perception algorithm based on the image information acquired by the visual camera to identify dynamic obstacles, thereby enabling the vehicle to achieve autonomous navigation and obstacle avoidance.

5. The intelligent temperature monitoring system for slag bags in the slow cooling field according to claim 1, characterized in that, The fixed auxiliary facilities also include wireless access points covering the slow cooling field operation area. The mobile unmanned vehicle is equipped with a wireless client. The wireless client establishes a network connection with the background management system through the wireless access point to realize data communication between the computing unit and the background management system. The computing unit can upload vehicle location information, vehicle travel path information, vehicle speed information, vehicle power information, slag bag temperature information, and slag bag number image information to the background management system. The back-end management system includes a manufacturing execution system and / or a data server; The automatic charging pile and the mobile unmanned vehicle have a communication interface. The computing unit is used to monitor the battery module's power level in real time and compare the real-time power level of the battery module with the charging threshold. The computing unit can control the mobile unmanned vehicle to move to the physical docking position of the automatic charging pile and initiate the charging process through the communication interface.

6. The intelligent temperature monitoring system for slag bags in the slow cooling field according to claim 1, characterized in that, The intelligent temperature monitoring system for slag bags in the slow cooling field also includes a human-computer interaction terminal. The human-machine interface terminal is an industrial control computer display or touch screen installed on the field operating console or in the remote monitoring room. The human-machine interface terminal is connected to the background management system and / or the computing unit of the mobile unmanned vehicle through a wireless network. The human-machine interface terminal is used to display system status, send one-click start commands, send emergency stop commands, and perform remote control.

7. The intelligent temperature monitoring system for slag bags in the slow cooling field according to claim 1, characterized in that, The mobile unmanned vehicle is equipped with an electric gimbal, and the online temperature measurement imager is mounted on the electric gimbal. The electric gimbal includes a drive motor module for driving the online temperature measurement imager to perform pitch and horizontal rotation movements. The drive motor module is communicatively connected to the computing unit. The computing unit controls the movement of the drive motor module according to the position and size of the target slag bag, thereby adjusting the pitch and horizontal rotation angles of the online temperature measurement imager.

8. A method for temperature monitoring of slag bales in a slow-cooling field based on the intelligent patrol and temperature monitoring system for slag bales in a slow-cooling field according to any one of claims 1 to 7, characterized in that, include: The background management system sends inspection task instructions to the computing unit of the mobile unmanned vehicle; The computing unit performs global path planning based on the inspection task instructions and the environmental data obtained from the lidar and vision camera. The drive unit drives the mobile unmanned vehicle to move along the planned path according to the motion control commands generated by the computing unit; During the movement, the computing unit receives and processes the perception data from the lidar and vision camera in real time, and fuses the absolute position information obtained from the UWB positioning base station to achieve real-time positioning and dynamic obstacle avoidance. When the device moves to the target slag bag, the online temperature imaging instrument acquires an infrared thermal image of the side wall of the slag bag, and the computing unit identifies the temperature of the slag bag; the 2D camera captures an image of the slag bag number, and the computing unit performs image recognition to obtain the slag bag number; the computing unit associates the obtained slag bag number with the identified temperature data, and uploads it to the background management system via a wireless communication network.

9. The method for monitoring and detecting the temperature of slag bags in a slow cooling field according to claim 8, characterized in that, "Performing global path planning based on environmental data acquired from the LiDAR and vision camera" specifically includes: The point cloud data acquired by the lidar is fused with the image data acquired by the vision camera to construct a two-dimensional cost map containing semantic information about obstacles. On the two-dimensional cost map, based on the given starting point and target point, a collision-free optimal global path is planned using the Hybrid A* algorithm; "The computing unit receives and processes the perception data from the lidar and vision camera in real time, and fuses the absolute location information obtained from the UWB positioning base station," specifically including: Using the aforementioned lidar and vision camera, a local high-precision point cloud map is generated based on the SLAM algorithm, and the pose of the mobile unmanned vehicle is estimated. The absolute coordinates of the mobile unmanned vehicle are obtained through the UWB positioning base station; The Kalman filter algorithm is used to fuse the pose of the mobile unmanned vehicle estimated by the SLAM algorithm with the UWB absolute coordinates to output the optimized pose of the mobile unmanned vehicle.

10. The method for monitoring and detecting the temperature of slag bags in a slow cooling field according to claim 8, characterized in that, Following the statement "The calculation unit associates the obtained slag bag number with the identified temperature data and uploads it to the background management system via a wireless communication network," the following is also included: The back-end management system receives and stores the bound data; The background management system generates a temperature change trend chart based on the temperature data of the same slag bag at different time points. When the temperature change trend chart shows an abnormal rate of temperature decrease or the current temperature exceeds the safety threshold, a signal is sent to the human-machine interaction terminal, which then issues an alarm message.

Images