RGV rail transport flat car control communication transmission system and method

Abstract

The control communication transmission system and method for the RGV rail transport flat car comprises the steps that a link quality evaluation model is constructed, and link signal-to-noise ratios corresponding to different communication transmission types of all areas of a target plant area are obtained to construct a comparison table; according to the RGV control communication data of each vehicle-mounted terminal and the comparison table, performing predictive decision making and intelligent link pre-switching operation on transmission links of various types of data in the RGV control communication data; constructing a pre-switching link table, and obtaining a pre-switching transmission link of a next target area of the vehicle-mounted terminal in the intelligent link pre-switching operation; according to the method, communication links between vehicle-mounted terminals in all areas of a target plant and a cloud monitoring platform are monitored in real time, whether abnormal links or terminal equipment fault information is generated or not is judged according to a real-time monitoring result, and rapid switching operation is carried out on the judged abnormal links based on a pre-switching link table. And the transmission efficiency and reliability of communication transmission of the RGV rail transportation flat car are improved.

Description

Technical Field

[0001] This invention relates to the field of logistics communication control technology, specifically to an RGV rail transport flatbed vehicle control communication transmission system and method. Background Technology

[0002] In fields such as intelligent manufacturing and warehousing logistics, RGV (Automated Guided Vehicle) rail transport flatbed trucks serve as core equipment for automated material handling. The real-time performance, reliability, and security of their control communication transmission directly determine the operational efficiency and stability of the entire logistics system. Existing RGV control communication transmission methods primarily employ single-link or simple dual-link backup, which suffers from insufficient link switching reliability. Current dual-link backups often use a "fail-safe switching" mode, resulting in long switching delays (typically greater than 50ms). In scenarios involving high-speed RGV movement or multi-vehicle collaborative scheduling, switching delays can easily lead to control command interruptions, causing safety hazards such as stopping or collisions. Furthermore, data transmission priorities are inconsistent: different types of data, such as control commands, status feedback, and safety signals, are transmitted through the same channel without prioritization. This can easily lead to safety signals being blocked by other data, failing to meet SIL2 / 3 safety requirements. Summary of the Invention

[0003] To address the aforementioned technical problems, the present invention aims to provide a control communication transmission system for RGV rail transport flatbed vehicles, comprising a cloud monitoring platform, an on-board terminal, a link quality assessment module, a transmission preprocessing module, a link analysis module, and a real-time transmission control module. The link quality assessment module is used to build a link quality assessment model and obtain the link signal-to-noise ratio corresponding to different communication transmission types in various areas of the target plant to construct a comparison table; The transmission preprocessing module is used to make predictive decisions and perform intelligent link pre-switching operations on the transmission links of various types of data in the RGV control communication data based on the RGV control communication data and the lookup table of each vehicle terminal. The link analysis module is used to build a pre-switching link table and obtain the pre-switching transmission link of the next target area of ​​the vehicle terminal during the intelligent link pre-switching operation. The real-time transmission control module is used to monitor the communication links between the vehicle terminals and the cloud monitoring platform in various areas of the target factory in real time. Based on the real-time monitoring results, it determines whether abnormal links or terminal equipment fault information are generated, and performs a fast switching operation on the identified abnormal links based on the pre-switching link table.

[0004] Furthermore, on-board terminals are deployed on the RGV rail transport flatbed vehicles in the target plant area. The cloud monitoring platform communicates with each on-board terminal. The on-board terminals are used to transmit RGV control communication data. The cloud monitoring platform is equipped with a link quality assessment module, a transmission preprocessing module, a link analysis module, a real-time transmission control module, and a database. The database is used to store the RGV control communication data of each on-board terminal during the historical collection period.

[0005] Furthermore, the process of constructing a link quality assessment model and obtaining a comparison table of link signal-to-noise ratios for different communication transmission types in various areas of the target plant includes: RGV control communication data of each vehicle terminal in several historical collection periods are extracted from the database. Communication transmission type, link parameters and RGV position parameters are extracted from the RGV control communication data as training dataset. The training dataset is standardized and normalized preprocessed. Derived features are constructed from the link parameters in the preprocessed training dataset to obtain time-series derived features and correlation derived features. A link quality assessment model is constructed. The model is trained based on the communication transmission type, RGV location parameters, time-series derived features, and correlation derived features in the training dataset. The trained link quality assessment model outputs the link signal-to-noise ratio (SNR) corresponding to different communication transmission types in each area of ​​the target plant. A comparison table is constructed based on the link SNR corresponding to different communication transmission types in each area of ​​the target plant.

[0006] Furthermore, based on the RGV control communication data of each on-board terminal and the lookup table, the process of making predictive decisions on the transmission links of various types of data in the RGV control communication data includes: Based on the real-time control command data of each vehicle terminal and the RGV position parameters at the current moment, the next target area of ​​each vehicle terminal is obtained; Obtain the transmission links and preset security priorities of each type of data in the RGV control communication data transmitted by each vehicle terminal at the current moment, and obtain the link signal-to-noise ratio of the communication transmission type corresponding to each type of data transmission link of each vehicle terminal in the next target area according to the reference table. Preset link signal-to-noise ratio (SNR) thresholds corresponding to different security priorities, obtain the link SNR thresholds corresponding to the security priorities of each type of data, compare the link SNR of the transmission link of each type of data in the next target area with the corresponding link SNR threshold, if the link SNR of the transmission link of the type of data in the next target area is less than the corresponding link SNR threshold, then the type of data is marked as data to be switched and intelligent link switching operation is performed, if the link SNR of the transmission link of the type of data in the next target area is greater than or equal to the corresponding link SNR threshold, then the transmission link of the type of data is maintained.

[0007] Furthermore, the process of performing intelligent link pre-switching includes: The system obtains the pre-switching transmission link for each type of data to be switched within the next target area of ​​the vehicle terminal, and obtains the real-time boundary distance and trigger threshold between the vehicle terminal and the next target area based on the real-time control command data and status feedback data of the vehicle terminal. When the real-time boundary distance between the vehicle terminal and the next target area is equal to the trigger threshold, a pre-connection is established between the vehicle terminal and each type of data to be switched. When the real-time boundary distance between the vehicle terminal and the next target area is zero, the transmission links of the data to be switched are sorted in ascending order according to the security priority of each type of data to be switched, and a switching list is generated. The transmission links of the data to be switched are switched to the pre-switched transmission links in turn according to the switching list.

[0008] Furthermore, the process of obtaining the pre-handover transmission link for each type of data to be handed over in the next target area of ​​the vehicle terminal includes: Obtain the transmission efficiency constraints of the data to be switched by the vehicle terminal at the current moment, as well as the link parameters of each transmission link in the next target area. Eliminate the transmission links in the next target area whose corresponding link parameters do not meet the transmission efficiency constraints. Obtain the link signal-to-noise ratio of each communication transmission type corresponding to each retained transmission link in the next target area according to the lookup table. Obtain the comprehensive link score of each transmission link in the next target area according to the link parameters and link signal-to-noise ratio of each transmission link in the next target area. Based on the comprehensive link score, each transmission link in the next target area is sorted in ascending order, and a pre-switching link table for the data type to be switched in the next target area is constructed. The first pre-switching link in the pre-switching link table is selected as the pre-switching transmission link for the data type to be switched.

[0009] Furthermore, the process of real-time monitoring of the communication links between vehicle-mounted terminals and the cloud monitoring platform in various areas of the target factory includes: Obtain the threshold range of link parameters for different communication transmission types in each area of ​​the target factory, obtain the link parameters of the communication link between the vehicle terminal and the cloud monitoring platform in each area of ​​the target factory, compare the link parameters with the threshold range of link parameters, and obtain the cumulative time when the link parameters are not within the threshold range of link parameters. When the cumulative time exceeds the cumulative time threshold, abnormal link parameters are marked, the region of the vehicle terminal to which the abnormal link parameter belongs is obtained, and the number of other vehicle terminals in the region whose same link parameter is marked as abnormal link parameters is obtained. When the number of abnormal link parameters in the region exceeds the preset decision threshold, the communication link to which the abnormal link parameter belongs in the region is marked as an abnormal link, and a fast communication link switching operation is performed in the region. When the number of abnormal link parameters in the region is less than or equal to the preset decision threshold, terminal equipment fault information of the vehicle terminal to which the abnormal link parameter belongs is generated.

[0010] Furthermore, the process of quickly switching over identified abnormal links includes: The data transmitted by each vehicle terminal in the area through abnormal links is marked as key data type. A pre-switching link table for each key data type in the current area is obtained. Abnormal links in the pre-switching link table are removed. The key data type is clustered according to the security priority of each key data type to obtain key datasets with different security priorities. First, the following steps are performed on the key dataset with the highest security priority: Step 1: Randomly select a key data type from the key dataset, obtain the bandwidth occupied by the key data type, and retrieve the remaining bandwidth and link signal-to-noise ratio of the first pre-switching link in the pre-switching link table of the key data type at the current time. Step 2: Determine whether the bandwidth occupied by a certain critical data type is less than the remaining bandwidth of the first pre-switching link. If it is less, proceed to step 3; otherwise, proceed to step 4. Step 3: Determine whether the link signal-to-noise ratio of the current pre-switched link is less than the link signal-to-noise ratio threshold of a certain key data type. If it is less, proceed to step 5. If it is not less, perform baseband signal encoding analysis of a certain key data type and determine whether the bandwidth occupied by the key data type after baseband signal encoding is less than the remaining bandwidth of the current pre-switched link. If it is less, proceed to step 5. If it is not less, proceed to step 4. Step 4: Retrieve the remaining bandwidth and link signal-to-noise ratio of the next pre-switching link in the pre-switching link table for a certain key type of data, and determine whether the bandwidth occupied by a certain key type of data is less than the remaining bandwidth of the next pre-switching link. If it is less, proceed to step 3; otherwise, continue to step 4. Step 5: Use the current switching link as the switching transmission link for a certain key type of data, remove the key type of data from the key dataset, and re-execute Step 1. When re-executing Step 1, determine whether the key dataset is an empty set. If it is an empty set, force the above steps to end. Then, perform the above steps on the second-highest security priority critical dataset, and so on, until the critical dataset with the lowest security priority has completed the above steps.

[0011] Furthermore, the process of performing baseband signal coding analysis on a specific type of data includes: A preset baseband coding lookup table is used, which includes the bit error rate corresponding to different LDPC coding parameters at different link signal-to-noise ratio levels. The bit error rate threshold corresponding to the security priority of a certain key type of data is obtained. Based on the link signal-to-noise ratio of the current pre-switched link, the bit error rate threshold, and the baseband coding lookup table, the LDPC coding parameters of a certain key type of data are obtained, and the bandwidth occupied after LDPC coding of a certain key type of data is obtained.

[0012] The control communication transmission method for RGV rail transport flatbed vehicles includes the following steps: Step s1: Construct a link quality assessment model and obtain a comparison table of link signal-to-noise ratios corresponding to different communication transmission types in various areas of the target plant. Step s2: Based on the RGV control communication data and the lookup table of each vehicle terminal, perform predictive decision-making and intelligent link pre-switching operations on the transmission links of each type of data in the RGV control communication data. Step s3: Construct a pre-switching link table and obtain the pre-switching transmission link of the next target area of ​​the vehicle terminal in the intelligent link pre-switching operation; Step s4: Monitor the communication links between the vehicle terminals and the cloud monitoring platform in each area of ​​the target factory in real time. Determine whether abnormal links or terminal equipment failure information are generated based on the real-time monitoring results. Perform a fast switching operation on the identified abnormal links based on the pre-switching link table.

[0013] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention constructs a link quality assessment model, trains it using historical communication data and RGV location parameters, and outputs a link signal-to-noise ratio (SNR) comparison table corresponding to different communication transmission types in various areas of the target plant. This method overcomes the limitations of traditional link quality assessment, which relies on manual sampling and is highly subjective, achieving quantitative assessment and precise regional mapping of link quality. This provides a scientific basis for subsequent link selection and switching. Based on real-time RGV control communication data and the SNR comparison table, it predicts the link compatibility of the next target area in advance and marks data types that do not meet the requirements as types to be switched. Pre-connection operations are triggered based on the boundary distance between the RGV and the target area. This "predictive decision-making + pre-connection" mechanism abandons the passive mode of traditional "fault-based switching," avoiding data interruption or delay during link switching. It is particularly suitable for complex scenarios where RGVs operate across regions, ensuring the continuous and stable transmission of critical data such as control commands and safety signals.

[0014] 2. The pre-switching link table constructed by the link analysis module can select the optimal pre-switching link by combining the transmission requirements of the data type to be switched with the link characteristics of the target area. Simultaneously, during link switching, the switching operation is executed according to security priority, realizing on-demand allocation and priority management of link resources. This avoids the problem of low-priority data preempting high-priority data transmission resources, improving the overall transmission efficiency and resource utilization of the communication system.

[0015] 3. The real-time transmission control module monitors the communication links between the vehicle-mounted terminals and the cloud monitoring platform throughout the plant in real time. By comparing the threshold ranges of link parameters with the cumulative time of abnormal parameters, it accurately distinguishes between abnormal links and terminal equipment failures, avoiding the problem of confusing link and equipment failures in traditional fault diagnosis. For abnormal links, a fast switching operation is performed based on the pre-switching link table, and strategies such as bandwidth adaptation and encoding optimization are used to ensure the switching transmission of critical data, significantly shortening fault handling time and reducing the workload and cost of manual maintenance. Attached Figure Description

[0016] Figure 1 This is a flowchart of the RGV rail transport flatbed vehicle control communication transmission system according to an embodiment of this application.

[0017] Figure 2 This is a flowchart illustrating the control communication transmission method for the RGV rail transport flatbed vehicle according to an embodiment of this application. Detailed Implementation

[0018] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] like Figure 1 As shown, the RGV rail transport flatbed vehicle control communication transmission system includes a cloud monitoring platform, an on-board terminal, a link quality assessment module, a transmission preprocessing module, a link analysis module, and a real-time transmission control module. The link quality assessment module is used to build a link quality assessment model and obtain the link signal-to-noise ratio corresponding to different communication transmission types in various areas of the target plant to construct a comparison table; The transmission preprocessing module is used to make predictive decisions and perform intelligent link pre-switching operations on the transmission links of various types of data in the RGV control communication data based on the RGV control communication data and the lookup table of each vehicle terminal. The link analysis module is used to build a pre-switching link table and obtain the pre-switching transmission link of the next target area of ​​the vehicle terminal during the intelligent link pre-switching operation. The real-time transmission control module is used to monitor the communication links between the vehicle terminals and the cloud monitoring platform in various areas of the target factory in real time. Based on the real-time monitoring results, it determines whether abnormal links or terminal equipment fault information are generated, and performs a fast switching operation on the identified abnormal links based on the pre-switching link table.

[0020] It should be further explained that, in the specific implementation process, a cloud monitoring platform is built, and on-board terminals are deployed on the RGV rail transport flatbed vehicles in the target factory area. The cloud monitoring platform communicates with each on-board terminal. The on-board terminals are used to transmit RGV control communication data. The various types of data in the RGV control communication data include safety signal data (emergency stop signal, anti-collision sensor signal, limit signal), real-time control command data (RGV start / stop command, speed adjustment command, positioning command), status feedback data (RGV position data, speed data, fault code data, data flow, communication transmission type of communication link, signal strength (RSSI), packet loss rate, transmission delay, bit error rate), and non-real-time interactive data (task scheduling information, historical data traceability information). The cloud monitoring platform includes a link quality assessment module, a transmission preprocessing module, a link analysis module, a real-time transmission control module, and a database. The database stores RGV control communication data from each vehicle terminal during its historical acquisition period.

[0021] It should be further explained that, in the specific implementation process, the process of constructing a link quality assessment model and obtaining a comparison table of link signal-to-noise ratios corresponding to different communication transmission types in various areas of the target plant includes: RGV control communication data from various vehicle terminals within several historical collection periods (nearly 3 months) were extracted from the database. Communication transmission type (including industrial Wi-Fi, conductor rail communication, industrial-grade 5G, etc.), link parameters (signal strength (RSSI), packet loss rate, transmission delay, bit error rate, bandwidth utilization), and RGV location parameters (latitude / longitude / track coordinates, location area (e.g., regular transportation area, strong electromagnetic interference area, junction area, high-precision positioning area)) were extracted from this data to serve as a training dataset. The training dataset underwent data standardization and normalization preprocessing, including: Link parameters are standardized using Z-Score, with the formula X'=(X-μ) / σ, where μ is the mean of the parameters and σ is the standard deviation. μ and σ are calculated separately for different communication transmission types (e.g., the mean RSSI of industrial Wi-Fi differs from that of conductor rail communication) to ensure that standardization adapts to the characteristics of each transmission type. RGV position parameters are normalized by mapping the RGV orbital coordinates (e.g., X∈[0,1200m], Y∈[0,500m]) to the interval [0,1], using the formula X'=X / (X_max-X_min). Category data such as "Industrial WI-FI", "Sliding conductor communication", and "Industrial 5G" are converted into numerical data using one-hot encoding (e.g., Industrial WI-FI → [1,0,0], Sliding conductor communication → [0,1,0]). Derived features are constructed from the link parameters in the preprocessed training dataset to obtain temporal derived features and correlation derived features; Time-series derived features: Parameter change rate: Calculate the change rate of the link parameters in the current acquisition period compared to the previous acquisition period (e.g., RSSI change rate = (RSSI of the current acquisition period - RSSI of the previous acquisition period) / RSSI of the previous acquisition period). Parameter moving average: Calculate the moving average of link parameters over the last 5 acquisition cycles (e.g., RSSI moving average = (acquisition cycle + RSSI of the previous 4 acquisition cycles) / 5); Parameter fluctuation range: Calculate the standard deviation of link parameters over the past 10 acquisition cycles (e.g., transmission delay fluctuation range = standard deviation of delay over the past 10 acquisition cycles).

[0022] Related derived features: Link Quality Composite Index: Calculated based on the entropy weight method (weights: RSSI 0.3, packet loss rate 0.3, transmission delay 0.25, bit error rate 0.15), the formula is QI=0.3×(1-RSSI)+0.3×packet loss rate+0.25×delay+0.15×bit error rate; Location-transmission type matching degree: The historical normality rate of different communication transmission types in each area is pre-statistically calculated and used as the matching degree feature (e.g., if the normality rate of industrial WI-FI in a typical area is 95%, then the matching degree = 0.95). A link quality assessment model was constructed (using LightGBM gradient boosting tree, with a temporal attention mechanism added before the LightGBM input layer to assign dynamic weights to temporal derived features (such as parameter change rate and moving average) to enhance the influence of temporal patterns on fault prediction); the output layer uses the Sigmoid activation function to output the link signal-to-noise ratio (value [0,1]). The link quality assessment model was trained based on the communication transmission type, RGV location parameters, temporal derived features, and associated derived features in the training dataset, using the cross-entropy loss function and the Adam optimizer. The momentum parameters β1=0.9, β2=0.999, and weight decay=1e-5 to avoid gradient explosion during training. The training set is input into the model in batches (batch size=256), and the predicted values ​​are calculated through forward propagation and the model parameters are updated through backpropagation. Every 100 iterations, AUC, precision, recall, and F1 score are calculated on the validation set, and the optimal model parameters are recorded. If the validation set AUC does not improve for 20 consecutive iterations (error ≤0.001), training is stopped to avoid overfitting. At the same time, the optimal model parameters during training (the parameters when the validation set AUC is the highest) are saved.

[0023] Based on the completed link quality assessment model, output the link signal-to-noise ratio (SNR) corresponding to different communication transmission types in each area of ​​the target plant, and construct a comparison table based on the link SNR corresponding to different communication transmission types in each area of ​​the target plant.

[0024] It should be further explained that, in the specific implementation process, the process of making predictive decisions on the transmission links of various types of data in the RGV control communication data based on the RGV control communication data of each vehicle terminal and the lookup table includes: Based on the real-time control command data of each vehicle terminal and the RGV position parameters at the current moment, the next target area of ​​each vehicle terminal is obtained; Obtain the transmission links and preset safety priorities (Level 1 priority - safety signal data - link signal-to-noise ratio threshold 95%, Level 2 priority - real-time control command data - link signal-to-noise ratio threshold 90%, Level 3 priority - status feedback data - link signal-to-noise ratio threshold 85%, Level 4 priority - non-real-time interactive data - link signal-to-noise ratio threshold 80%, Level 1 priority > Level 2 priority > Level 3 priority > Level 4 priority, Level 1 priority is the highest, Level 2 priority is the second highest, and Level 4 priority is the lowest) of the communication transmission type corresponding to the transmission link of each type of data of each vehicle terminal in the next target area according to the reference table. Preset link signal-to-noise ratio (SNR) thresholds corresponding to different security priorities, obtain the link SNR thresholds corresponding to the security priorities of each type of data, compare the link SNR of the transmission link of each type of data in the next target area with the corresponding link SNR threshold, if the link SNR of the transmission link of the type of data in the next target area is less than the corresponding link SNR threshold, then the type of data is marked as data to be switched and intelligent link switching operation is performed, if the link SNR of the transmission link of the type of data in the next target area is greater than or equal to the corresponding link SNR threshold, then the transmission link of the type of data is maintained.

[0025] It should be further explained that, in the specific implementation process, the intelligent link pre-switching operation includes: The system acquires the pre-switching transmission links for each type of data to be switched within the next target area of ​​the vehicle terminal. Based on the real-time control command data and status feedback data of the vehicle terminal, it obtains the real-time boundary distance and trigger threshold D between the vehicle terminal and the next target area. ,in For the operating speed of the vehicle terminal, This is the time required for pre-connection; When the real-time boundary distance between the vehicle terminal and the next target area equals the trigger threshold, a pre-connection is established between the vehicle terminal and each type of data to be switched. This includes establishing a connection with the link base station / terminal in the target area in advance to complete channel negotiation, parameter configuration, and authentication, avoiding handshake delays during switching. For example, when the RGV enters a strong electromagnetic interference area from the normal operating area and is 50m away from the boundary, the vehicle module establishes a Profibus protocol connection with the sliding contact line communication module in advance to synchronize parameters such as baud rate and parity method. When the real-time boundary distance between the vehicle terminal and the next target area is zero, the transmission links of each type of data to be switched are sorted in ascending order according to their security priority (the higher the security priority, the higher the ranking), generating a switching list. According to the switching list, the transmission links of the data to be switched are switched to the pre-switched transmission links in sequence. First, the first-priority safety signal is switched to ensure that the emergency stop and collision avoidance signals are not interrupted; then the second-priority real-time control command is switched; and finally, the third / fourth-priority non-real-time data is switched to complete the full-link switching.

[0026] It should be further explained that, in the specific implementation process, the pre-handover transmission link for obtaining the data of each type to be handed over in the next target area of ​​the vehicle terminal includes: Obtain the transmission efficiency constraints (transmission delay threshold, bandwidth requirements) of the data to be switched at the current moment for the vehicle terminal, as well as the link parameters of each transmission link in the next target area. Eliminate transmission links in the next target area whose corresponding link parameters do not meet the transmission efficiency constraints (e.g., transmission delay greater than the transmission delay threshold). Obtain the link signal-to-noise ratio (SNR) of each communication transmission type corresponding to the retained transmission links in the next target area according to the lookup table. Based on the link parameters and SNR of each transmission link in the next target area, obtain the comprehensive link score for each transmission link in the next target area. The formula for calculating the comprehensive link score is as follows: ; in, For comprehensive link scoring, For the link signal-to-noise ratio, It is 0.6. It is 0.3. It is 0.1. For signal strength, For transmission delay, For bandwidth utilization; Based on the comprehensive link score, each transmission link in the next target area is sorted in ascending order, and a pre-switching link table for the data to be switched in the next target area is constructed (the higher the comprehensive link score of the transmission link, the higher its ranking in the pre-switching link table). The first pre-switching link in the pre-switching link table is selected as the pre-switching transmission link for the data to be switched.

[0027] It should be further explained that, in the specific implementation process, the communication links between the vehicle-mounted terminals and the cloud monitoring platform in various areas of the target factory are monitored in real time, and the process of determining whether abnormal links or terminal equipment fault information are generated based on the real-time monitoring results includes: Obtain the threshold range of link parameters for different communication transmission types in each area of ​​the target factory (obtained by statistically averaging the historical link parameters for different communication transmission types in each area), obtain the link parameters of the communication link between the vehicle terminal and the cloud monitoring platform in each area of ​​the target factory, compare the link parameters with the threshold range of the link parameters, and obtain the cumulative time when the link parameters are not within the threshold range of the link parameters. When the cumulative time exceeds the cumulative time threshold, abnormal link parameters are marked, the region of the vehicle terminal to which the abnormal link parameter belongs is obtained, and the number of other vehicle terminals in the region with the same link parameter (link parameter of the same type as the abnormal link parameter) marked as abnormal link parameters is obtained. When the number of abnormal link parameters marked in the region exceeds the preset decision threshold (number of vehicle terminals in the region / 2 + 1), the communication link to which the abnormal link parameter belongs in the region is marked as an abnormal link, and a fast communication link switching operation is performed in the region. When the number of abnormal link parameters marked in the region is less than or equal to the preset decision threshold (number of vehicle terminals in the region / 2 + 1), terminal equipment fault information of the vehicle terminal to which the abnormal link parameter belongs is generated.

[0028] It should be further explained that, in the specific implementation process, the process of quickly switching over the identified abnormal links includes: The data transmitted by each vehicle terminal in the area through abnormal links is marked as key data type. A pre-switching link table for each key data type in the current area is obtained. Abnormal links in the pre-switching link table are removed. The key data type is clustered according to the security priority of each key data type to obtain key datasets with different security priorities. First, the following steps are performed on the key dataset with the highest security priority: Step 1: Randomly select a key data type from the key dataset, obtain the bandwidth occupied by the key data type, and retrieve the remaining bandwidth and link signal-to-noise ratio of the first pre-switching link in the pre-switching link table of the key data type at the current time. Step 2: Determine whether the bandwidth occupied by a certain critical data type is less than the remaining bandwidth of the first pre-switching link. If it is less, proceed to step 3; otherwise, proceed to step 4. Step 3: Determine whether the link signal-to-noise ratio of the current pre-switched link is less than the link signal-to-noise ratio threshold of a certain key data type. If it is less, proceed to step 5. If it is not less, perform baseband signal encoding analysis of a certain key data type and determine whether the bandwidth occupied by the key data type after baseband signal encoding is less than the remaining bandwidth of the current pre-switched link. If it is less, proceed to step 5. If it is not less, proceed to step 4. Step 4: Retrieve the remaining bandwidth and link signal-to-noise ratio of the next pre-switching link in the pre-switching link table for a certain key type of data, and determine whether the bandwidth occupied by a certain key type of data is less than the remaining bandwidth of the next pre-switching link. If it is less, proceed to step 3; otherwise, continue to step 4. Step 5: Use the current switching link as the switching transmission link for a certain key type of data, remove the key type of data from the key dataset, and re-execute Step 1. When re-executing Step 1, determine whether the key dataset is an empty set. If it is an empty set, force the end of the above steps (Steps 1 to 5). Then, perform the above steps (steps 1 to 5) on the second highest security priority critical dataset, and so on, until the lowest security priority critical dataset has completed the above steps.

[0029] It should be further explained that, in the specific implementation process, the baseband signal encoding analysis of a certain key type of data includes: A baseband coding lookup table is pre-set. Communication links at different signal-to-noise ratio (SNR) levels, different LDPC coding parameters, and identical original training data are pre-set between the transmitter and receiver. The transmitter is pre-simulated to encode the original training data according to different LDPC coding parameters, generating coded data, which is then transmitted through communication links at different SNR levels. The receiver decodes the coded data under different LDPC coding parameters and SNR levels, obtaining the bit error rate (BER) of the decoded original training data corresponding to the pre-set BER. After multiple simulation tests of the above process, the BER of the original training data is obtained. A baseband coding lookup table is constructed based on the bit error rate corresponding to the LDPC coding parameters and signal-to-noise ratio (SNR) levels. The baseband coding lookup table includes the bit error rate corresponding to different LDPC coding parameters at different link SNR levels. The bit error rate threshold corresponding to the security priority of a certain key type of data is obtained. Based on the link SNR of the current pre-switched link, the bit error rate threshold, and the baseband coding lookup table, the LDPC coding parameters of a certain key type of data are obtained (the bit error rate of the LDPC coding parameters under the link SNR conditions of the current pre-switched link is greater than or equal to the bit error rate threshold). The bandwidth occupied after LDPC coding of a certain key type of data is obtained.

[0030] like Figure 2As shown, the control communication transmission method for RGV rail transport flatbed vehicles includes the following steps: Step s1: Construct a link quality assessment model and obtain a comparison table of link signal-to-noise ratios corresponding to different communication transmission types in various areas of the target plant. Step s2: Based on the RGV control communication data and the lookup table of each vehicle terminal, perform predictive decision-making and intelligent link pre-switching operations on the transmission links of each type of data in the RGV control communication data. Step s3: Construct a pre-switching link table and obtain the pre-switching transmission link of the next target area of ​​the vehicle terminal in the intelligent link pre-switching operation; Step s4: Monitor the communication links between the vehicle terminals and the cloud monitoring platform in each area of ​​the target factory in real time. Determine whether abnormal links or terminal equipment failure information are generated based on the real-time monitoring results. Perform a fast switching operation on the identified abnormal links based on the pre-switching link table.

[0031] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. An RGV rail transport flatbed vehicle control and communication transmission system, characterized in that, It includes a cloud monitoring platform, vehicle-mounted terminal, link quality assessment module, transmission preprocessing module, link analysis module, and real-time transmission control module; The link quality assessment module is used to build a link quality assessment model and obtain the link signal-to-noise ratio corresponding to different communication transmission types in various areas of the target plant to construct a comparison table; The transmission preprocessing module is used to make predictive decisions and perform intelligent link pre-switching operations on the transmission links of various types of data in the RGV control communication data based on the RGV control communication data and the lookup table of each vehicle terminal. The link analysis module is used to build a pre-switching link table and obtain the pre-switching transmission link of the next target area of ​​the vehicle terminal during the intelligent link pre-switching operation. The real-time transmission control module is used to monitor the communication links between the vehicle terminals and the cloud monitoring platform in various areas of the target factory in real time. Based on the real-time monitoring results, it determines whether abnormal links or terminal equipment fault information are generated, and performs a fast switching operation on the identified abnormal links based on the pre-switching link table.

2. The RGV rail transport flatbed vehicle control communication transmission system according to claim 1, characterized in that, Onboard terminals are deployed on RGV rail transport flatbed vehicles in the target factory area. The cloud monitoring platform communicates with each onboard terminal. The onboard terminals are used to transmit RGV control communication data. The cloud monitoring platform is equipped with a link quality assessment module, a transmission preprocessing module, a link analysis module, a real-time transmission control module, and a database. The database is used to store RGV control communication data from each onboard terminal during its historical acquisition period.

3. The RGV rail transport flatbed vehicle control communication transmission system according to claim 2, characterized in that, The process of constructing a link quality assessment model and obtaining the link signal-to-noise ratio (SNR) for different communication transmission types in various areas of the target plant, and building a comparison table, includes: RGV control communication data of each vehicle terminal in several historical collection periods are extracted from the database. Communication transmission type, link parameters and RGV position parameters are extracted from the RGV control communication data as training dataset. The training dataset is standardized and normalized preprocessed. Derived features are constructed from the link parameters in the preprocessed training dataset to obtain time-series derived features and correlation derived features. A link quality assessment model is constructed. The model is trained based on the communication transmission type, RGV location parameters, time-series derived features, and correlation derived features in the training dataset. The trained link quality assessment model outputs the link signal-to-noise ratio (SNR) corresponding to different communication transmission types in each area of ​​the target plant. A comparison table is constructed based on the link SNR corresponding to different communication transmission types in each area of ​​the target plant.

4. The RGV rail transport flatbed vehicle control communication transmission system according to claim 3, characterized in that, The process of making predictive decisions on the transmission links of various types of data in the RGV control communication data based on the RGV control communication data of each vehicle terminal and the corresponding lookup table includes: Based on the real-time control command data of each vehicle terminal and the RGV position parameters at the current moment, the next target area of ​​each vehicle terminal is obtained; Obtain the transmission links and preset security priorities of each type of data in the RGV control communication data transmitted by each vehicle terminal at the current moment, and obtain the link signal-to-noise ratio of the communication transmission type corresponding to each type of data transmission link of each vehicle terminal in the next target area according to the reference table. Preset link signal-to-noise ratio (SNR) thresholds corresponding to different security priorities, obtain the link SNR thresholds corresponding to the security priorities of each type of data, compare the link SNR of the transmission link of each type of data in the next target area with the corresponding link SNR threshold, if the link SNR of the transmission link of the type of data in the next target area is less than the corresponding link SNR threshold, then the type of data is marked as data to be switched and intelligent link switching operation is performed, if the link SNR of the transmission link of the type of data in the next target area is greater than or equal to the corresponding link SNR threshold, then the transmission link of the type of data is maintained.

5. The RGV rail transport flatbed vehicle control communication transmission system according to claim 4, characterized in that, The process of performing intelligent link pre-switching includes: The system obtains the pre-switching transmission link for each type of data to be switched within the next target area of ​​the vehicle terminal, and obtains the real-time boundary distance and trigger threshold between the vehicle terminal and the next target area based on the real-time control command data and status feedback data of the vehicle terminal. When the real-time boundary distance between the vehicle terminal and the next target area is equal to the trigger threshold, a pre-connection is established between the vehicle terminal and each type of data to be switched. When the real-time boundary distance between the vehicle terminal and the next target area is zero, the transmission links of the data to be switched are sorted in ascending order according to the security priority of each type of data to be switched, and a switching list is generated. The transmission links of the data to be switched are switched to the pre-switched transmission links in turn according to the switching list.

6. The RGV rail transport flatbed vehicle control communication transmission system according to claim 5, characterized in that, The process of obtaining the pre-handover transmission link for each type of data to be handed over in the next target area of ​​the vehicle terminal includes: Obtain the transmission efficiency constraints of the data to be switched by the vehicle terminal at the current moment, as well as the link parameters of each transmission link in the next target area. Eliminate the transmission links in the next target area whose corresponding link parameters do not meet the transmission efficiency constraints. Obtain the link signal-to-noise ratio of each communication transmission type corresponding to each retained transmission link in the next target area according to the lookup table. Obtain the comprehensive link score of each transmission link in the next target area according to the link parameters and link signal-to-noise ratio of each transmission link in the next target area. Based on the comprehensive link score, each transmission link in the next target area is sorted in ascending order, and a pre-switching link table for the data type to be switched in the next target area is constructed. The first pre-switching link in the pre-switching link table is selected as the pre-switching transmission link for the data type to be switched.

7. The RGV rail transport flatbed vehicle control communication transmission system according to claim 6, characterized in that, The process of real-time monitoring of the communication links between vehicle-mounted terminals and the cloud monitoring platform in various areas of the target factory includes: Obtain the threshold range of link parameters for different communication transmission types in each area of ​​the target factory, obtain the link parameters of the communication link between the vehicle terminal and the cloud monitoring platform in each area of ​​the target factory, compare the link parameters with the threshold range of link parameters, and obtain the cumulative time when the link parameters are not within the threshold range of link parameters. When the cumulative time exceeds the cumulative time threshold, abnormal link parameters are marked, the region of the vehicle terminal to which the abnormal link parameter belongs is obtained, and the number of other vehicle terminals in the region whose same link parameter is marked as abnormal link parameters is obtained. When the number of abnormal link parameters in the region exceeds the preset decision threshold, the communication link to which the abnormal link parameter belongs in the region is marked as an abnormal link, and a fast communication link switching operation is performed in the region. When the number of abnormal link parameters in the region is less than or equal to the preset decision threshold, terminal equipment fault information of the vehicle terminal to which the abnormal link parameter belongs is generated.

8. The RGV rail transport flatbed vehicle control communication transmission system according to claim 7, characterized in that, The process of quickly switching over identified abnormal links includes: The data transmitted by each vehicle terminal in the area through abnormal links is marked as key data type. A pre-switching link table for each key data type in the current area is obtained. Abnormal links in the pre-switching link table are removed. The key data type is clustered according to the security priority of each key data type to obtain key datasets with different security priorities. First, the following steps are performed on the key dataset with the highest security priority: Step 1: Randomly select a key data type from the key dataset, obtain the bandwidth occupied by the key data type, and retrieve the remaining bandwidth and link signal-to-noise ratio of the first pre-switching link in the pre-switching link table of the key data type at the current time. Step 2: Determine whether the bandwidth occupied by a certain critical data type is less than the remaining bandwidth of the first pre-switching link. If it is less, proceed to step 3; otherwise, proceed to step 4. Step 3: Determine whether the link signal-to-noise ratio of the current pre-switched link is less than the link signal-to-noise ratio threshold of a certain key data type. If it is less, proceed to step 5. If it is not less, perform baseband signal encoding analysis of a certain key data type and determine whether the bandwidth occupied by the key data type after baseband signal encoding is less than the remaining bandwidth of the current pre-switched link. If it is less, proceed to step 5. If it is not less, proceed to step 4. Step 4: Retrieve the remaining bandwidth and link signal-to-noise ratio of the next pre-switching link in the pre-switching link table for a certain key type of data, and determine whether the bandwidth occupied by a certain key type of data is less than the remaining bandwidth of the next pre-switching link. If it is less, proceed to step 3; otherwise, continue to step 4. Step 5: Use the current switching link as the switching transmission link for a certain key type of data, remove the key type of data from the key dataset, and re-execute Step 1. When re-executing Step 1, determine whether the key dataset is an empty set. If it is an empty set, force the above steps to end. Then, perform the above steps on the second-highest security priority critical dataset, and so on, until the critical dataset with the lowest security priority has completed the above steps.

9. The RGV rail transport flatbed vehicle control communication transmission system according to claim 8, characterized in that, The process of performing baseband signal coding analysis on a specific type of data includes: A preset baseband coding lookup table is used, which includes the bit error rate corresponding to different LDPC coding parameters at different link signal-to-noise ratio levels. The bit error rate threshold corresponding to the security priority of a certain key type of data is obtained. Based on the link signal-to-noise ratio of the current pre-switched link, the bit error rate threshold, and the baseband coding lookup table, the LDPC coding parameters of a certain key type of data are obtained, and the bandwidth occupied after LDPC coding of a certain key type of data is obtained.

10. A control communication transmission method for an RGV rail transport flatbed vehicle, specifically applied to the control communication transmission system for an RGV rail transport flatbed vehicle as described in any one of claims 1 to 9, characterized in that, Includes the following steps: Step s1: Construct a link quality assessment model and obtain a comparison table of link signal-to-noise ratios corresponding to different communication transmission types in various areas of the target plant. Step s2: Based on the RGV control communication data and the lookup table of each vehicle terminal, perform predictive decision-making and intelligent link pre-switching operations on the transmission links of each type of data in the RGV control communication data. Step s3: Construct a pre-switching link table and obtain the pre-switching transmission link of the next target area of ​​the vehicle terminal in the intelligent link pre-switching operation; Step s4: Monitor the communication links between the vehicle terminals and the cloud monitoring platform in each area of ​​the target factory in real time. Determine whether abnormal links or terminal equipment failure information are generated based on the real-time monitoring results. Perform a fast switching operation on the identified abnormal links based on the pre-switching link table.

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