Cross-platform bridge type sampling machine control system based on credential

Abstract

The embodiment of the invention relates to the technical field of industrial automation control, and particularly discloses a cross-platform bridge type sampling machine control system based on credential creativity. According to the embodiment of the invention, the card swiping information and the vehicle sampling authority are verified through the identity verification module; the laser radar control module scans the position of a vehicle and identifies the size of a carriage when the sampling authority exists; the random point distribution algorithm module is used for generating random sampling point coordinates in a compartment space range according to the compartment size; the sampling process control module is used for performing automatic process control driven by a state machine; and the historical data management module is used for acquiring, storing and querying sampling records, equipment states and operation logs. Multi-device cooperative control can be realized by adopting a FastDDS distributed communication technology, the method has the characteristics of autonomous controllability, strong real-time performance, high stability and the like, and the technical problems of poor cross-platform compatibility, backward communication architecture, complex device integration, lack of intelligent control and the like in the prior art can be solved.

Description

Technical Field

[0001] This invention belongs to the field of industrial automation control technology, and in particular relates to a cross-platform bridge sampler control system based on domestic information technology innovation. Background Technology

[0002] The sampling software for bridge samplers in thermal power plants is a software system used to control and manage the operation of bridge samplers, specifically for automated sampling of coal from trucks.

[0003] The existing bridge sampler control system mainly has the following technical problems:

[0004] (1) Poor cross-platform compatibility: Traditional control software is usually developed for specific platforms and is difficult to port between different operating systems, which limits the adaptability and scalability of the system.

[0005] (2) Outdated communication architecture: Existing systems mostly adopt traditional point-to-point communication or centralized architecture, which are inadequate in terms of equipment integration, real-time performance and reliability;

[0006] (3) Complex equipment integration: Different manufacturers' equipment (OPC UA server, card reader, lidar, etc.) use different communication protocols, which makes integration difficult and maintenance cost high;

[0007] (4) Lack of intelligent control: Traditional systems lack intelligent process control and data processing capabilities, and have a low degree of automation. Summary of the Invention

[0008] The purpose of this invention is to provide a cross-platform bridge sampling machine control system based on domestic IT innovation, aiming to solve the problems mentioned in the background art.

[0009] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0010] This is a cross-platform bridge sampling machine control system based on domestic IT innovation. The system adopts the QT6 cross-platform development framework and QML declarative user interface technology. It integrates with the sampling machine OPC UA communication, card reader communication, LiDAR control, and vehicle stop control through FastDDS distributed communication middleware. Specifically, the system includes an authentication module, a LiDAR control module, a random sampling algorithm module, a sampling process control module, and a historical data management module, wherein:

[0011] The identity verification module is used to verify card swipe information and check vehicle sampling permissions;

[0012] The lidar control module is used to scan the vehicle's location and identify the vehicle's dimensions when sampling permissions are available;

[0013] The random sampling point algorithm module is used to generate random sampling point coordinates within the space of the vehicle body based on the vehicle body dimensions;

[0014] The sampling process control module is used for state machine-driven automated process control.

[0015] The historical data management module is used to acquire, store, and query sampling records, device status, and operation logs.

[0016] As a further limitation of the technical solution of the embodiment of the present invention, the system adopts a distributed publish-subscribe communication mode and performs real-time data transmission between devices through the FastDDS distributed communication middleware.

[0017] As a further limitation of the technical solution of this embodiment of the invention, the authentication module communicates with the card reader through the RS232 / RS485 serial port protocol, receives RFID card information, and compares it with the authorized user information in the preset SQLite database to verify the driver's identity and vehicle sampling authority.

[0018] As a further limitation of the technical solution of this embodiment of the invention, the lidar control module receives 3D point cloud scanning data through the UDP network protocol, uses point cloud processing algorithm to identify vehicle boundaries, calculates the length, width and height parameters of the vehicle body, and obtains the vehicle body dimensions.

[0019] As a further limitation of the technical solution of this embodiment of the invention, the random sampling point algorithm module adopts the Monte Carlo method to generate multiple random sampling point coordinates in the three-dimensional space of the vehicle body corresponding to the vehicle body size, ensuring that the sampling points are evenly distributed and avoid vehicle structural components. Each sampling point includes X, Y, Z three-dimensional coordinates and sampling depth parameters.

[0020] As a further limitation of the technical solution of the embodiment of the present invention, the automated process control of the sampling process control module includes seven states: waiting for card swiping, identity verification, laser scanning, random point placement, sampling execution, data saving, and raising the vehicle barrier. The state transition is based on an event-driven mechanism.

[0021] As a further limitation of the technical solution of this embodiment of the invention, the historical data management module adopts an SQLite embedded database, which includes a sampling record table, a device status table and an operation log table, and supports compound queries and statistical analysis based on time range, license plate number and / or driver name.

[0022] As a further limitation of the technical solution of the present invention, the FastDDS distributed communication middleware adopts the DDS-RTPS protocol, supports two transmission modes: UDP multicast and TCP unicast, the communication domain ID is set to 100, and the data types include five message types: SamplingCommand, DeviceStatus, CardReaderEvent, LidarScanData, and BarrierControl.

[0023] As a further limitation of the technical solution of the present invention, the point cloud processing algorithm includes four steps: point cloud denoising, plane segmentation, cluster analysis and boundary extraction. The RANSAC algorithm is used for plane detection, the Euclidean clustering algorithm is used for target segmentation, and the convex hull algorithm is used to calculate the vehicle boundary contour.

[0024] As a further limitation of the technical solution of the embodiment of the present invention, the state machine includes a timeout protection mechanism. When the card swipe verification times out by 30 seconds, the laser scan times out by 60 seconds, and / or the sampling execution times out by 300 seconds, it automatically returns to the initial state and records the abnormal log.

[0025] Compared with the prior art, the beneficial effects of the present invention are:

[0026] (1) Strong cross-platform compatibility: It is developed using the QT6 framework and QML declarative interface technology. The QML scene graph rendering engine supports multiple graphics APIs such as OpenGL, Vulkan, and Metal, and can run on multiple operating systems and hardware platforms. It has excellent interface rendering performance and improves system adaptability.

[0027] (2) Advantages of distributed architecture: FastDDS distributed communication provides better real-time performance, scalability and fault tolerance;

[0028] (3) High system integration: The unified software architecture enables seamless integration of various heterogeneous devices;

[0029] (4) High level of intelligence: Automated sampling process control improves work efficiency and accuracy. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention.

[0031] Figure 1 An application architecture diagram of the system provided in an embodiment of the present invention is shown. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0033] It is understandable that the existing bridge sampling machine control system has the following technical problems: (1) poor cross-platform compatibility: traditional control software is usually developed for specific platforms and is difficult to port between different operating systems, which limits the adaptability and scalability of the system; (2) outdated communication architecture: existing systems mostly adopt traditional point-to-point communication or centralized architecture, which are insufficient in terms of equipment integration, real-time performance and reliability; (3) complex equipment integration: different manufacturers' equipment (OPC UA server, card reader, lidar, etc.) use different communication protocols, which makes integration difficult and maintenance costs high; (4) lack of intelligent control: traditional systems lack intelligent process control and data processing capabilities and have a low degree of automation.

[0034] To address the aforementioned issues, this invention employs the QT6 cross-platform development framework and QML declarative user interface technology. It integrates FastDDS distributed communication middleware with sampling machine OPC UA communication, card reader communication, LiDAR control, and vehicle stop control. The system includes: an authentication module for verifying card information and vehicle sampling permissions; a LiDAR control module for scanning vehicle locations and identifying vehicle dimensions when sampling permissions are granted; a random sampling point algorithm module for generating random sampling point coordinates within the vehicle space based on vehicle dimensions; a sampling process control module for state machine-driven automated process control; and a historical data management module for acquiring, storing, and querying sampling records, device status, and operation logs. This system enables multi-device collaborative control using FastDDS distributed communication technology, featuring autonomous controllability, strong real-time performance, and high stability. It addresses existing technical problems such as poor cross-platform compatibility, outdated communication architecture, complex device integration, and lack of intelligent control.

[0035] Figure 1 An application architecture diagram of the system provided in an embodiment of the present invention is shown.

[0036] Specifically, the cross-platform bridge sampling machine control system based on domestic IT innovation is characterized by adopting the QT6 cross-platform development framework and QML declarative user interface technology. It integrates with the sampling machine OPCUA communication, card reader communication, LiDAR control, and vehicle stop control through the FastDDS distributed communication middleware. The system specifically includes an authentication module, a LiDAR control module, a random sampling algorithm module, a sampling process control module, and a historical data management module, wherein:

[0037] The identity verification module is used to verify card swipe information and check vehicle sampling permissions.

[0038] In this embodiment of the invention, the authentication module communicates with the card reader via RS232 / RS485 serial port protocol, receives RFID card information, and compares it with authorized user information in a preset SQLite database to verify the driver's identity and vehicle sampling authority.

[0039] The lidar control module is used to scan the vehicle's location and identify the vehicle's dimensions when sampling authority is available.

[0040] In this embodiment of the invention, the lidar control module receives 3D point cloud scanning data via the UDP network protocol, uses a point cloud processing algorithm to identify the vehicle boundary, calculates the length, width, and height parameters of the vehicle body to obtain the vehicle body size, and provides spatial constraint information for random point placement. The point cloud processing algorithm includes four steps: point cloud denoising, plane segmentation, cluster analysis, and boundary extraction. The RANSAC algorithm is used for plane detection, the Euclidean clustering algorithm is used for target segmentation, and the convex hull algorithm is used to calculate the vehicle boundary contour.

[0041] The random sampling point algorithm module is used to generate random sampling point coordinates within the space of the vehicle body based on the vehicle body dimensions.

[0042] In this embodiment of the invention, the random sampling algorithm module adopts the Monte Carlo method to generate N (N≥3 and N≤10) random sampling points in the three-dimensional space of the vehicle body corresponding to the vehicle body size, ensuring that the sampling points are evenly distributed and avoid vehicle structural components. Each sampling point includes X, Y, Z three-dimensional coordinates and sampling depth parameters.

[0043] The sampling process control module is used for state machine-driven automated process control.

[0044] In this embodiment of the invention, the automated process control of the sampling process control module includes seven states: waiting for card swiping, identity verification, laser scanning, random point placement, sampling execution, data saving, and raising the vehicle barrier. The state transitions are based on an event-driven mechanism.

[0045] Understandably, the state machine includes a timeout protection mechanism. When the card swipe verification times out by 30 seconds, the laser scan times out by 60 seconds, and / or the sampling execution times out by 300 seconds, it automatically returns to the initial state and records the exception log.

[0046] The historical data management module is used to acquire, store, and query sampling records, device status, and operation logs.

[0047] In this embodiment of the invention, the historical data management module uses an embedded SQLite database, which includes a sampling record table, a device status table, and an operation log table, and supports compound queries and statistical analysis based on time range, license plate number, and / or driver name.

[0048] It is understood that, in this embodiment of the invention, the cross-platform bridge sampling machine control system based on domestically developed information technology adopts a distributed publish-subscribe communication mode. Real-time data transmission between devices is achieved through the FastDDS distributed communication middleware. The CPU architecture supports x86_64, ARM64, MIPS64, etc., with at least 8GB of RAM and at least 100GB of SSD storage. The network uses a gigabit Ethernet interface and possesses a QoS (Quality of Service) guarantee mechanism with reliable transmission (RELIABLE), real-time guarantee (REAL_TIME), persistent storage (TRANSIENT), and resource limitation (KEEP_LAST). The FastDDS distributed communication middleware uses the DDS-RTPS protocol, supports both UDP multicast and TCP unicast transmission modes, has a communication domain ID set to 100, and includes five message types: SamplingCommand, DeviceStatus, CardReaderEvent, LidarScanData, and BarrierControl.

[0049] In one embodiment of the present invention, starting from the driver swiping their card, the card reader transmits the card information to the control software for authentication. After successful authentication, the control software initiates a LiDAR scan. The LiDAR sends the scan data back to the control software. The software generates random sampling points after vehicle recognition processing and then sends a sampling command to the sampling device. The sampling device performs sampling and provides feedback on the status. After sampling is completed, the control software is notified. The software saves the sampling record and controls the vehicle stop to lift and release the vehicle. The vehicle departure process ends. The specific procedure is as follows:

[0050]

[0051]

[0052] In this embodiment of the invention, the distributed communication architecture employs FastDDS (Fast Data Distribution Service) distributed real-time communication middleware; it performs publish-subscribe communication between devices; and it provides QoS (Quality of Service) guarantees to ensure the real-time performance and reliability of critical data.

[0053] In this embodiment of the invention, the OPC UA communication module enables standardized industrial communication with the sampler to achieve automated sampling process control; the card reader communication module handles identity verification and access management for coal transport vehicles and controls the sampler to start sampling; the lidar control module uses three-dimensional scanning and identification of coal transport vehicle positioning and carriage dimensions to facilitate the calculation of sampling point allocation; and the vehicle stop control module enables passage control of coal transport vehicles within the sampling area.

[0054] In this embodiment of the invention, the intelligent control process includes: identity verification and permission check; automatic vehicle location detection; random sampling algorithm; automated control of the sampling process; and historical data storage and retrieval.

[0055] In this embodiment of the invention, the overall system architecture is structured hierarchically from bottom to top as follows: hardware abstraction layer, communication middleware layer, device control layer, business logic layer, and human-computer interaction layer. The hardware abstraction layer is based on a desktop operating system and supports various CPUs such as Phytium, Hygon, Sunway, Loongson, and Kunpeng. The communication middleware layer uses FastDDS distributed communication middleware, involving functions such as network transmission, data serialization, service discovery, and QoS management. The device control layer covers modules such as OPC UA client, vehicle stop control, LiDAR control, and card reader communication. The business logic layer includes sampling control services, system configuration, authentication services, device monitoring services, and data management services. The human-computer interaction layer includes a main control panel, device monitoring, historical query, and alarm display. These layers work collaboratively to ensure the stable operation and functional implementation of the software, reflecting the integrity and logic of the system architecture. Specifically:

[0056] Hardware Abstraction Layer: Operating system, CPU hardware platform support, device driver interface;

[0057] Communication middleware layer: FastDDS distributed communication middleware implementation;

[0058] Equipment Control Layer: OPC UA Client Module: Enables standardized communication with the sampler; Card Reader Communication Module: Handles serial / network communication protocols; LiDAR Control Module: Enables point cloud data processing and vehicle recognition; Vehicle Stop Control Module: Implements switch control logic;

[0059] Business Logic Layer: Authentication Service: Verifies vehicle and driver information; Sampling Control Service: Implements random sampling and sampling process control; Data Management Service: Stores and queries historical data; Equipment Status Monitoring Service: Monitors equipment operating status in real time;

[0060] Human-computer interaction layer: based on the QT6 framework and QML declarative user interface technology.

[0061] In this embodiment of the invention, the distributed communication architecture of the system is based on the FastDDS distributed communication domain (Domain ID: 100). The communication relationship between the system and the card reader, lidar device, sampling device, and vehicle stop device is realized through the publisher and subscriber pattern, involving data types such as CardReaderEvent, LidarScanData, SamplingCommand, BarrierControl, and DeviceStatus. For QoS configuration, it includes resource limits (KEEP_LAST), persistent storage (TRANSIENT), real-time guarantee (REAL_TIME), and reliable transmission (RELIABLE). These configurations ensure efficient, stable, and reliable communication between devices.

[0062] In this embodiment of the invention, the system and various devices and their network connection topology involve devices such as card readers, vehicle stop devices, lidar devices, and sampling devices. The control software host communicates with these devices through the FastDDS middleware, using communication protocols such as Modbus TCP, UDP / TCP, OPC UA / TCP, and RS232 serial port.

[0063] In this embodiment of the invention, the storage location of the SQLite database ( / var / lib / sampling) and the related data tables (operation log table, device status table, sampling record table) are all located on a gigabit Ethernet industrial network infrastructure. Each device is connected through an industrial Ethernet switch to form a complete device integration network, which reflects the system's integration level and the collaborative working method between devices.

[0064] In another embodiment of the present invention, a human-machine interface layout diagram is provided for fully automated coal sampling operations in thermal power plants. It integrates multi-dimensional information to assist in accurate sampling and mainly includes multiple modules such as a video monitoring area, a sampling point information area, an equipment status area, a vehicle information area, and a sampling control operation area.

[0065] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0066] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0067] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0068] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0069] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A cross-platform bridge sampler control system based on domestic IT innovation, characterized in that, The system adopts the QT6 cross-platform development framework and QML declarative user interface technology. It integrates with the sampling machine OPC UA communication, card reader communication, LiDAR control, and vehicle stop control through the FastDDS distributed communication middleware. Specifically, the system includes an authentication module, a LiDAR control module, a random sampling algorithm module, a sampling process control module, and a historical data management module, wherein: The identity verification module is used to verify card swipe information and check vehicle sampling permissions; The lidar control module is used to scan the vehicle's location and identify the vehicle's dimensions when sampling permissions are available; The random sampling point algorithm module is used to generate random sampling point coordinates within the space of the vehicle body based on the vehicle body dimensions; The sampling process control module is used for state machine-driven automated process control. The historical data management module is used to acquire, store, and query sampling records, device status, and operation logs.

2. The cross-platform bridge sampling machine control system based on domestic IT innovation according to claim 1, characterized in that, The system adopts a distributed publish-subscribe communication mode and uses the FastDDS distributed communication middleware to perform real-time data transmission between devices.

3. The cross-platform bridge sampling machine control system based on domestic IT innovation according to claim 1, characterized in that, The authentication module communicates with the card reader via RS232 / RS485 serial port protocol, receives RFID card information, and compares it with authorized user information in the preset SQLite database to verify the driver's identity and vehicle sampling authority.

4. The cross-platform bridge sampling machine control system based on domestic IT innovation according to claim 1, characterized in that, The lidar control module receives 3D point cloud scanning data via UDP network protocol, uses point cloud processing algorithm to identify vehicle boundaries, calculates the length, width and height parameters of the vehicle body, and obtains the vehicle body dimensions.

5. The cross-platform bridge sampling machine control system based on domestic information technology innovation according to claim 1, characterized in that, The random sampling point algorithm module uses the Monte Carlo method to generate multiple random sampling point coordinates in the three-dimensional space of the vehicle body corresponding to the vehicle body size, ensuring that the sampling points are evenly distributed and avoid vehicle structural components. Each sampling point includes X, Y, Z three-dimensional coordinates and sampling depth parameters.

6. The cross-platform bridge sampling machine control system based on domestic IT innovation according to claim 1, characterized in that, The automated process control of the sampling process control module includes seven states: waiting for card swiping, identity verification, laser scanning, random point placement, sampling execution, data saving, and raising the vehicle barrier. The state transitions are based on an event-driven mechanism.

7. The cross-platform bridge sampling machine control system based on domestic IT innovation according to claim 1, characterized in that, The historical data management module uses an embedded SQLite database, which includes a sampling record table, a device status table, and an operation log table. It supports compound queries and statistical analysis based on time range, license plate number, and / or driver name.

8. The cross-platform bridge sampling machine control system based on domestic IT innovation according to claim 1, characterized in that, The FastDDS distributed communication middleware adopts the DDS-RTPS protocol, supports both UDP multicast and TCP unicast transmission modes, sets the communication domain ID to 100, and includes five message types: SamplingCommand, DeviceStatus, CardReaderEvent, LidarScanData, and BarrierControl.

9. The cross-platform bridge sampling machine control system based on domestic IT innovation according to claim 4, characterized in that, The point cloud processing algorithm includes four steps: point cloud denoising, plane segmentation, cluster analysis, and boundary extraction. The RANSAC algorithm is used for plane detection, the Euclidean clustering algorithm is used for target segmentation, and the convex hull algorithm is used to calculate the vehicle boundary contour.

10. The cross-platform bridge sampling machine control system based on domestic information technology innovation according to claim 1, characterized in that, The state machine includes a timeout protection mechanism. When the card swipe verification times out by 30 seconds, the laser scan times out by 60 seconds, and / or the sampling execution times out by 300 seconds, it automatically returns to the initial state and records the exception log.

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