Dual-mode communication load monitoring system and method based on adaptive switching of HPLC (High Performance Liquid Chromatography) and HRF (High Frequency)

Abstract

The invention provides a dual-mode communication load monitoring system and method based on adaptive switching of HPLC and HRF, and the system comprises a dual-mode communication module which is used for the parallel transmission and dynamic switching of two communication modes of HPLC and HRF; the load monitoring unit is used for collecting load data of the power equipment in real time; the self-adaptive switching control unit is used for evaluating the communication quality and a preset dynamic weight and generating a switching instruction; the dynamic priority scheduling unit is used for adjusting task estimation running time in real time and optimizing communication resource distribution by adopting an improved HRF dynamic priority scheduling algorithm based on load data in an HRF communication mode; and the load prediction correction unit dynamically corrects a load prediction value through an exponential weighted moving average and resource demand modeling method in combination with historical load data and a real-time monitoring result, and feeds back the load prediction value to the adaptive switching control unit. And the continuity of load data transmission is ensured.

Description

Technical Field

[0001] This invention relates to the field of communication monitoring technology, and in particular to a dual-mode communication load monitoring system and method based on adaptive switching of HPLC and HRF. Background Technology

[0002] With the deep integration of smart grid and Internet of Things (IoT) technologies, local communication units (such as smart meters, data concentrators, and IoT gateways) need to support both high-speed power line carrier communication (HPLC) and high-speed radio frequency communication (HRF) to achieve complementary coverage of power lines and wireless channels. HPLC technology uses power lines as a transmission medium and has the advantages of no need for additional wiring and wide coverage, but its signal is susceptible to power line noise and impedance changes. HRF technology transmits data through wireless frequency bands and has flexible networking capabilities, but it faces challenges such as multipath fading and interference coexistence.

[0003] To overcome the shortcomings of a single communication mode, HPLC and HRF dual-mode communication technology has been proposed. By working together with power lines and wireless channels, they can complement each other's advantages. However, the switching threshold of traditional dual-mode systems is fixed and cannot adapt to dynamically changing load demands and communication environments. In HRF communication, the estimated running time of tasks is statically set and does not take into account the actual delay caused by resource contention, which can easily lead to priority inversion.

[0004] Therefore, it is necessary to provide a new dual-mode communication load monitoring system and method based on adaptive switching of HPLC and HRF to solve the above-mentioned technical problems. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a dual-mode communication load monitoring system and method based on adaptive switching of HPLC and HRF.

[0006] The present invention provides a dual-mode communication load monitoring system based on adaptive switching of HPLC and HRF, comprising: a dual-mode communication module for parallel transmission and dynamic switching of HPLC and HRF communication modes; The dual-mode communication module includes: a load monitoring unit, used to collect load data of power equipment in real time, including voltage, current, power factor and harmonic parameters; An adaptive switching control unit is used to evaluate communication quality and preset dynamic weights, dynamically select HPLC or HRF communication mode based on load monitoring requirements, and generate switching commands. The dynamic priority scheduling unit, based on load data in the HRF communication mode, adopts an improved HRF dynamic priority scheduling algorithm to adjust the estimated running time of tasks in real time and optimize the allocation of communication resources. The load forecasting correction unit combines historical load data and real-time monitoring results, and dynamically corrects the load forecast using exponentially weighted moving average and resource demand modeling methods, feeding the results back to the adaptive switching control unit.

[0007] Furthermore, the adaptive switching control unit includes: The communication quality assessment subunit monitors the signal-to-noise ratio, bit error rate, and link stability of HPLC and HRF in real time. The decision-making subunit is switched, and a switching instruction is generated based on a preset threshold and a dynamic weighting algorithm. The smooth transition subunit performs data buffering and synchronization during mode switching to avoid data loss or duplicate transmission.

[0008] Furthermore, the dynamic priority scheduling unit includes: The task estimated runtime initialization subunit assigns an initial runtime value based on the load type and historical execution data; The real-time correction subunit dynamically adjusts the initial runtime based on the actual task execution time and resource utilization rate in HRF communication mode. The priority allocation subunit dynamically allocates communication bandwidth and transmission time slots based on the corrected initial runtime value and the urgency of the task.

[0009] Furthermore, the smooth transition subunit stores unsent data in a FIFO queue before mode switching, prioritizing it according to task urgency, and aligning the clocks of HPLC and HRF with timestamps to avoid data misordering. If the first packet is lost after switching, it triggers a fast retransmission of HRF.

[0010] Furthermore, the switching condition of the switching instruction satisfies at least one of the following: The SNR of HPLC is below the first threshold and the SNR of HRF is above the second threshold; The BER of the HPLC exceeded the upper limit of error tolerance; The load monitoring data type is high-frequency sampling data, and the real-time performance of HRF is better than that of HPLC.

[0011] Furthermore, the load prediction correction unit includes: The historical data storage subunit records the load monitoring data and communication mode selection results of the power equipment from the past N times. Multi-model fusion prediction subunit is used to generate load estimates; The feedback correction subunit compares the prediction results with real-time monitoring data. If the deviation exceeds the threshold, it triggers the adaptive switching control unit to re-evaluate the communication mode.

[0012] Furthermore, the multi-model fusion prediction subunit generates load estimates based on the following models: EWMA model: Weighted average of the most recent M load data; Resource demand model: Establish a linear regression equation based on load type to predict future load change trends; Quantile adjustment model: The 90th percentile of historical load data is used as the upper limit of the estimated value.

[0013] Furthermore, the multi-model fusion prediction subunit adopts a weighted voting mechanism, and the weights of each model are dynamically adjusted according to the historical prediction accuracy.

[0014] Another aspect of the present invention provides a dual-mode communication load monitoring method based on adaptive switching of HPLC and HRF, the method comprising the following steps: Step 1: Initialize the system: Set the communication quality threshold, initialize dynamic parameters and configure the load prediction model weights. The system enters standby mode and waits for real-time data acquisition. Step 2: Real-time load data acquisition: The load monitoring unit continuously acquires real-time load data of the power equipment. The dual-mode communication module transmits data in parallel in the current communication mode, while preparing a data buffer for the HPLC and HRF communication links. The real-time load data stream enters the communication quality assessment subunit. Step 3, Communication Quality Assessment: The communication quality assessment subunit monitors HPLC and HRF indicators in real time, compares the monitored values ​​with the thresholds set in Step 1, and generates an assessment report. Step 4: Dynamic weight calculation and switching decision: Calculate the weights of HPLC and HRF respectively, and trigger the switch if any of the switching conditions are met. Step 5, Smooth Transition: Store the currently unsent data in the data processing queue, sort them according to the urgency of the task, align the HPLC and HRF communication clocks with the timestamp, switch modes, verify data integrity after switching, smoothly transition the completion signal, and the system runs in the new communication mode. Step 6, Dynamic Priority Scheduling: Based on load type and historical execution data, an initial running time is assigned. In HRF mode, the corrected running time is calculated based on the actual task execution time and resource utilization. Communication bandwidth and transmission time slots are dynamically allocated according to the running time and task urgency. Step 7, Load Forecast Correction: Store the current load data and communication mode in the historical data storage sub-unit, use multi-model fusion forecasting, dynamically adjust the weight of each model based on the historical forecast accuracy, compare the forecast value with the real-time monitoring value, and calculate the deviation. Step 8, Feedback and Reassessment: If the deviation in Step 7 is greater than the preset threshold, the corrected load estimate is fed back to the adaptive switching control unit. The load type is adjusted based on the new estimate, the dynamic weights of HPLC and HRF are recalculated, the switching conditions in Step 4 are rechecked, a new switching command is triggered, and the process returns to Step 2 to continue the monitoring process.

[0015] Furthermore, after the mode switch in step five, if the first packet is lost and the HRF fast retransmission mechanism is triggered, the HPLC transmission is paused during the switching process, and the data processing queue data is sent first.

[0016] Compared with related technologies, the dual-mode communication load monitoring system and method based on adaptive switching of HPLC and HRF provided by the present invention has the following advantages: 1. This invention dynamically evaluates the communication quality of HPLC and HRF, automatically selects the optimal communication mode, switches to HRF when there is strong power grid noise interference, and switches to HPLC when the wireless signal is severely blocked, effectively avoiding the limitations of single-mode communication and ensuring the continuity of load data transmission.

[0017] 2. By integrating data buffering, synchronous calibration and fast retransmission technologies, this invention can ensure the timely transmission of critical data through local caching and priority scheduling even in the event of communication interruption or mode switching.

[0018] 3. This invention is based on an improved HRF algorithm. The system dynamically corrects the estimated task execution time, allocates bandwidth based on resource utilization and task urgency, and adjusts the communication strategy in real time through multi-model fusion prediction. When a peak grid load is predicted, the system switches to the low-latency HRF mode in advance to reduce data backlog and end-to-end transmission latency. Attached Figure Description

[0019] Figure 1 A system block diagram of the dual-mode communication load monitoring system based on adaptive switching of HPLC and HRF provided by the present invention; Figure 2 This is a structural block diagram of the adaptive switching control unit provided by the present invention; Figure 3 The structural block diagram of the dynamic priority scheduling unit provided by the present invention; Figure 4 This is a structural block diagram of the load prediction correction unit provided by the present invention; Figure 5 The flowchart illustrates the dual-mode communication load monitoring method based on adaptive switching of HPLC and HRF provided by this invention. Detailed Implementation

[0020] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0021] Please refer to the following: Figure 1 , Figure 2 , Figure 3 , Figure 4 as well as Figure 5 ,in, Figure 1 A system block diagram of the dual-mode communication load monitoring system based on adaptive switching of HPLC and HRF provided by the present invention; Figure 2 This is a structural block diagram of the adaptive switching control unit provided by the present invention; Figure 3 The structural block diagram of the dynamic priority scheduling unit provided by the present invention; Figure 4 This is a structural block diagram of the load prediction correction unit provided by the present invention; Figure 5 The flowchart illustrates the dual-mode communication load monitoring method based on adaptive switching of HPLC and HRF provided by this invention. Example 1:

[0022] In the specific implementation process, such as Figure 1 As shown, the dual-mode communication load monitoring system based on adaptive switching of HPLC and HRF includes: a dual-mode communication module for parallel transmission and dynamic switching of HPLC and HRF communication modes; The dual-mode communication module includes: a load monitoring unit, used to collect load data of power equipment in real time, including voltage, current, power factor and harmonic parameters; An adaptive switching control unit is used to evaluate communication quality and preset dynamic weights, dynamically select HPLC or HRF communication mode based on load monitoring requirements, and generate switching commands. The dynamic priority scheduling unit, based on load data in the HRF communication mode, adopts an improved HRF dynamic priority scheduling algorithm to adjust the estimated running time of tasks in real time and optimize the allocation of communication resources. The load forecasting correction unit combines historical load data and real-time monitoring results, and dynamically corrects the load forecast using exponentially weighted moving average and resource demand modeling methods, feeding the results back to the adaptive switching control unit.

[0023] In some embodiments, reference Figure 2 As shown, the adaptive switching control unit includes: The communication quality assessment subunit monitors the signal-to-noise ratio, bit error rate, and link stability of HPLC and HRF in real time. The decision-making subunit is switched, and a switching instruction is generated based on a preset threshold and a dynamic weighting algorithm. The smooth transition subunit performs data buffering and synchronization during mode switching to avoid data loss or duplicate transmission.

[0024] It should be noted that the HPLC evaluation indicators are as follows: SNR: Calculated by preamble detection, threshold ≥15dB; BER: Cyclic Redundancy Check (CRC) is used, with a tolerance limit of ≤10⁻³; Link stability: Count the number of retransmissions within 5 seconds, with a threshold of ≤3 times.

[0025] The HRF evaluation metrics are as follows: SNR: Calculated using the beacon frame received strength indication, with a threshold of ≥20dB; Channel occupancy rate: Detected using a spectrum sensing algorithm, threshold ≤70%; Packet loss rate: Statistically measured using ACK frames, with a threshold of ≤5%.

[0026] The dynamic weighting algorithm triggers a switch when any of the following conditions are met: The HRF weight is greater than the HPLC weight and the duration is 500ms; The load data is sampled at high frequency, and the real-time performance of HRF is better than that of HPLC. The BER of the HPLC exceeded the tolerance limit.

[0027] The dynamic weighting algorithm is as follows:

[0028]

[0029] Where k is the sensitivity coefficient, and SNR HPLC SNR for HPLC HRF For HRF, SNR, BER HPLC The degree of interference from wireless transmission to HPLC; It should be noted that the smooth transition subunit stores unsent data in a FIFO queue before mode switching, prioritizing it according to the urgency of the task, and aligning the clocks of HPLC and HRF with timestamps to avoid data misordering. If the first packet is lost after switching, it triggers a fast retransmission of HRF.

[0030] It should be noted that the switching condition for the switching instruction must meet at least one of the following: The SNR of HPLC is below the first threshold and the SNR of HRF is above the second threshold; The BER of the HPLC exceeded the upper limit of error tolerance; The load monitoring data type is high-frequency sampling data, and the real-time performance of HRF is better than that of HPLC.

[0031] In some embodiments, reference Figure 3 As shown, the dynamic priority scheduling unit includes: The task estimated runtime initialization subunit assigns an initial runtime value based on the load type and historical execution data; The real-time correction subunit, in HRF communication mode, dynamically adjusts the initial runtime S based on the actual task execution time and resource utilization using the following formula:

[0032] Where α is the weighting coefficient, 𝑡 actual R is the execution time, β is the resource penalty coefficient, and R is the execution time. p This is compensation for delays caused by resource competition; The priority allocation subunit dynamically allocates communication bandwidth and transmission time slots based on the corrected initial runtime value and the urgency of the task.

[0033] In some embodiments, reference Figure 4 As shown, the load prediction correction unit includes: The historical data storage subunit records the load monitoring data and communication mode selection results of the power equipment from the past N times. Multi-model fusion prediction subunit is used to generate load estimates; The feedback correction subunit compares the prediction results with real-time monitoring data. If the deviation exceeds the threshold, it triggers the adaptive switching control unit to re-evaluate the communication mode.

[0034] It should be noted that the multi-model fusion prediction subunit generates load estimates based on the following models: EWMA model: Weighted average of the most recent M load data; Resource demand model: Establish a linear regression equation based on load type to predict future load change trends; Quantile adjustment model: The 90th percentile of historical load data is used as the upper limit of the estimated value.

[0035] It should be noted that the multi-model fusion prediction sub-unit adopts a weighted voting mechanism, and the weights of each model are dynamically adjusted based on the historical prediction accuracy. Example 2:

[0036] In some specific implementation processes, refer to Figure 5 As shown, a dual-mode communication load monitoring method based on adaptive switching of HPLC and HRF is described, the method comprising the following steps: Step 1: Initialize the system: Set the communication quality threshold, initialize dynamic parameters and configure the load prediction model weights. The system enters standby mode and waits for real-time data acquisition.

[0037] Step 2: Real-time load data acquisition: The load monitoring unit continuously acquires real-time load data of the power equipment. The dual-mode communication module transmits data in parallel in the current communication mode, while preparing a data buffer for the HPLC and HRF communication links. The real-time load data stream enters the communication quality assessment subunit.

[0038] Step 3, Communication Quality Assessment: The communication quality assessment subunit monitors HPLC and HRF indicators in real time, compares the monitored values ​​with the thresholds set in Step 1, and generates an assessment report.

[0039] Step 4: Dynamic weight calculation and switching decision: Calculate the weights of HPLC and HRF respectively, and trigger the switching if any of the switching conditions are met.

[0040] Step 5, Smooth Transition: Store the currently unsent data in the data processing queue, sort them according to task urgency, align the HPLC and HRF communication clocks using timestamps, and after mode switching, if the first packet is lost, trigger the HRF fast retransmission mechanism. During the switching process, HPLC transmission is paused, and data in the data processing queue is sent first. After the switch is completed, verify the data integrity, and a smooth transition completion signal is issued. The system then operates in the new communication mode.

[0041] Step 6: Dynamic Priority Scheduling: Based on the load type and historical execution data, an initial running time is assigned. In HRF mode, the corrected running time is calculated based on the actual task execution time and resource utilization. Communication bandwidth and transmission time slots are dynamically allocated according to the running time and task urgency.

[0042] Step 7, Load Forecast Correction: Store the current load data and communication mode in the historical data storage sub-unit, use multi-model fusion forecasting, dynamically adjust the weight of each model based on the historical forecast accuracy, compare the forecast value with the real-time monitoring value, and calculate the deviation.

[0043] Step 8, Feedback and Reassessment: If the deviation in Step 7 is greater than the preset threshold, the corrected load estimate is fed back to the adaptive switching control unit. The load type is adjusted based on the new estimate, the dynamic weights of HPLC and HRF are recalculated, the switching conditions in Step 4 are rechecked, a new switching command is triggered, and the process returns to Step 2 to continue the monitoring process.

[0044] According to embodiments of the present invention, a computing device that can be used to implement the above method includes a processor and a memory.

[0045] The processor can be a multi-core processor or include multiple processors. In some embodiments, the processor may include a general-purpose main processor and one or more special coprocessors, such as a graphics processing unit (GPU), a digital signal processor (DSP), etc. In some embodiments, the processor may be implemented using custom circuitry, such as an application-specific integrated circuit (ASIC) or a field-programmable gate array (FPGA).

[0046] Memory can include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage devices. ROM can store static data or instructions required by the processor or other modules of the computer. Permanent storage devices can be read-write storage devices. Permanent storage devices can be non-volatile storage devices that retain stored instructions and data even when the computer is powered off. In some embodiments, permanent storage devices use mass storage devices (e.g., magnetic or optical disks, flash memory) as permanent storage devices. In other embodiments, permanent storage devices can be removable storage devices (e.g., floppy disks, optical drives). System memory can be a read-write storage device or a volatile read-write storage device, such as dynamic random access memory. System memory can store some or all of the instructions and data required by the processor during operation. Furthermore, memory can include any combination of computer-readable storage media, including various types of semiconductor memory chips (DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and disks and / or optical disks can also be used. In some implementations, the memory may include removable storage devices that are readable and / or writable, such as laser discs (CDs), read-only digital versatile optical discs (e.g., DVD-ROMs, dual-layer DVD-ROMs), read-only Blu-ray discs, ultra-high density optical discs, flash memory cards (e.g., SD cards, mini SD cards, Micro-SD cards, etc.), magnetic floppy disks, etc. Computer-readable storage media do not include carrier waves and transient electronic signals transmitted wirelessly or via wired connections.

[0047] It should be understood that, unless otherwise expressly stated herein, there is no strict order restriction on the execution of the above steps, and these steps may be executed in other orders. Moreover, at least some steps in the processes involved in the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but may be executed at different times. The execution order of these steps or stages is not necessarily sequential, but may be performed alternately or in turn with other steps or at least some of the steps or stages in other steps.

[0048] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or basic characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects. The scope of the invention is defined by the appended claims rather than the foregoing description. Therefore, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention, and no reference numerals in the claims should be construed as limiting the scope of the claims.

[0049] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment includes only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A dual mode communication load monitoring system based on HPLC and HRF adaptive switching, characterized by, Comprising: A dual-mode communication module for parallel transmission and dynamic switching between HPLC and HRF communication modes; The dual-mode communication module comprises: A load monitoring unit for real-time acquisition of load data of the power equipment, including voltage, current, power factor and harmonic parameters; An adaptive switching control unit for evaluating communication quality and preset dynamic weights, dynamically selecting HPLC or HRF communication mode in combination with load monitoring requirements, and generating switching instructions; A dynamic priority scheduling unit that uses an improved HRF dynamic priority scheduling algorithm to adjust the estimated running time of tasks in real time based on load data in HRF communication mode, and optimizes communication resource allocation; 2. The dual mode communication load monitoring system based on adaptive switching of HPLC and HRF as claimed in claim 1, wherein, A load prediction correction unit that combines historical load data and real-time monitoring results, dynamically corrects the load estimate value through exponential weighted moving average and resource demand modeling method, and feeds back to the adaptive switching control unit. The adaptive switching control unit comprises: A communication quality evaluation subunit for real-time monitoring of the signal-to-noise ratio, bit error rate and link stability of HPLC and HRF; A switching decision subunit for generating switching instructions according to preset threshold values and dynamic weight algorithms; 3. The dual mode communication load monitoring system based on adaptive switching of HPLC and HRF as claimed in claim 1, wherein, A smooth transition subunit for executing data buffering and synchronization during mode switching to avoid data loss or repeated transmission. The dynamic priority scheduling unit comprises: A task estimated running time initialization subunit for assigning an initial running time value based on load type and historical execution data; A real-time correction subunit for dynamically adjusting the initial running time based on actual task execution time and resource occupancy rate in HRF communication mode; 4. The dual mode communication load monitoring system based on adaptive switching of HPLC and HRF as claimed in claim 2, wherein, A priority allocation subunit for dynamically allocating communication bandwidth and transmission time slots based on the corrected initial running time value and task urgency.

5. The dual mode communication load monitoring system based on adaptive switching of HPLC and HRF as claimed in claim 2, wherein, The smooth transition subunit stores unsent data in a FIFO queue before mode switching, prioritizes tasks according to urgency, aligns the clocks of HPLC and HRF through timestamps to avoid data out-of-order, and triggers fast retransmission of HRF if the first packet is lost after switching. The switching conditions of the switching instructions meet at least one of the following: The SNR of HPLC is below a first threshold value and the SNR of HRF is above a second threshold value; The BER of HPLC exceeds the upper limit of error tolerance; 6. The dual mode communication load monitoring system based on adaptive switching of HPLC and HRF as claimed in claim 1, wherein, The load monitoring data type is high-frequency sampling data, and the real-time index of HRF is better than that of HPLC. The load prediction correction unit comprises: A historical data storage subunit for recording the past N times of load monitoring data and communication mode selection results of the power equipment; A multi-model fusion prediction subunit for generating load estimate values; 7. The dual mode communication load monitoring system based on adaptive switching of HPLC and HRF as claimed in claim 6, wherein, A feedback correction subunit for comparing the prediction results with real-time monitoring data, and triggering the adaptive switching control unit to re-evaluate the communication mode if the deviation exceeds the threshold value. The multi-model fusion prediction subunit generates load estimate values based on the following models: EWMA model: weighted average of recent M times of load data; Resource demand model: linear regression equation is established according to load type to predict future load trend; Quantile adjustment model: take the 90% quantile of historical load data as the upper limit of the estimate value.

8. The dual mode communication load monitoring system based on adaptive switching of HPLC and HRF according to claim 7, wherein, The multi-model fusion predictor unit adopts a weighted voting mechanism, and the weight of each model is dynamically adjusted according to the historical prediction accuracy.

9. A dual-mode communication load monitoring method based on HPLC and HRF adaptive switching, applicable to the dual-mode communication load monitoring system based on HPLC and HRF adaptive switching according to any one of claims 1-8, characterized in that, The method comprises the following steps: Step one, initialize the system: set the communication quality threshold, initialize the dynamic parameters and configure the load prediction model weight, the system enters the standby state, and waits for real-time data collection; Step two, real-time load data collection: the load monitoring unit continuously collects real-time load data of the power equipment, transmits the data in parallel in the current communication mode, and prepares a data buffer for the HPLC and HRF communication links at the same time, and the real-time load data stream enters the communication quality evaluation subunit; Step three, communication quality evaluation: the communication quality evaluation subunit monitors the HPLC index and the HRF index in real time, compares the monitoring value with the threshold set in step one, and generates an evaluation report; Step four, dynamic weight calculation and switching decision: the weights of HPLC and HRF are calculated respectively, and the switching condition is checked to meet any condition to trigger the switching; Step five, smooth transition: store the current unsent data into the data processing queue, sort according to the task urgency, align the HPLC and HRF communication clocks through time stamp, switch the mode, check the data integrity after switching, and send the smooth transition completion signal, and the system runs in the new communication mode; Step six, dynamic priority scheduling: based on the load type and historical execution data, an initial running time is assigned, in the HRF mode, according to the actual task execution time and resource occupancy rate, a corrected running time is calculated, according to the running time and task urgency, the communication bandwidth and transmission time slot are dynamically allocated; Step seven, load prediction correction: store the current load data and communication mode into the historical data storage subunit, use multi-model fusion prediction, dynamically adjust the weight of each model based on the historical prediction accuracy, compare the predicted value with the real-time monitoring value, and calculate the deviation; Step eight, feedback and reevaluation: if the deviation in step seven is greater than the preset threshold, the corrected load estimate value is fed back to the adaptive switching control unit, the load type is adjusted based on the new estimated value, the dynamic weights of HPLC and HRF are recalculated, the switching condition in step four is rechecked, a new switching instruction is triggered, and the process returns to step two for continuous monitoring.

10. The dual mode communication load monitoring method based on HPLC and HRF adaptive switching as claimed in claim 9, wherein, After the mode switching in step five, if the first packet loss triggers the HRF fast retransmission mechanism, the HPLC transmission is suspended during the switching process, and the data in the data processing queue is transmitted preferentially.

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