Air-sea cross-domain communication gateway energy optimization management system and method of coupling environment

Abstract

The invention relates to the technical field of air-sea cross-domain communication, and particularly provides an air-sea cross-domain communication gateway energy optimization management system and method of a coupling environment, environment sensing data is collected in real time through an inertial measurement unit, and after data analysis and fusion are carried out through an embedded processor module, the environment sensing data are transmitted to the air-sea cross-domain communication gateway energy optimization management system and method. The environment state judgment unit is used for analyzing the environment state, switching the power supply mode of the system module according to the environment state, monitoring the residual electric quantity of the system power supply battery pack, and further adjusting the sampling rate of the inertial measurement unit. According to the system, power consumption is reduced through dynamic adjustment and data compression in a daily mode, stability is guaranteed through redundancy design in an extreme mode, complex environment adaptability is improved based on mode switching of real-time motion parameters, and power supply fluctuation and hardware faults are effectively handled through a surge suppression and self-checking mechanism.

Description

Technical Field

[0001] The present invention relates to the technical field of air-sea cross-domain communication, and more particularly, to an energy optimization management system and method for an air-sea cross-domain communication gateway in a coupled environment. Background Art

[0002] With the growth of the demand for ocean resource development and monitoring, air-sea cross-domain communication devices (such as communication buoys, underwater robots, etc.) are increasingly widely used in complex ocean environments. In the prior art, the energy management of such devices mostly relies on static strategies, such as fixed-time sleep or single-threshold control. However, the ocean environment is highly dynamic, and conventional strategies are difficult to cope with the problem of a sharp increase in energy consumption caused by extreme working conditions (such as strong winds and waves, and severe shaking of the device). For example, when the device encounters strong winds and waves, the communication module needs to frequently adjust the signal transmission power to maintain the link stability, resulting in a sudden increase in energy consumption; while the traditional power management module lacks the ability to sense the environment and cannot dynamically adjust the power supply strategy, which is likely to cause energy waste or system downtime.

[0003] In addition, the existing inertial measurement unit (IMU) is mostly used for attitude monitoring or navigation and is not deeply integrated with energy management. Although some studies have attempted to optimize the device power consumption through motion data, their algorithms are mostly one-way control and lack the ability to adapt to extreme environments. Therefore, there is an urgent need for a system that can combine environmental state perception and dynamic energy management to solve the problems of energy efficiency and reliability under complex working conditions. Summary of the Invention

[0004] In view of this, the present invention proposes an energy optimization management system and method for an air-sea cross-domain communication gateway in a coupled environment to solve the problems existing in the above prior art.

[0005] On the one hand, to achieve the above object, the present invention proposes an energy optimization management system for an air-sea cross-domain communication gateway in a coupled environment, including a main control module and an energy management module. The main control module includes an inertial measurement unit, an embedded processor module, an environmental state determination unit, a communication link scheduler, and a recording and fault diagnosis module; The inertial measurement unit is used to collect environmental sensing data in real time; The embedded processor module uses a floating-point operation unit for data parsing and fusion, and uses a dynamic power management algorithm to coordinate task priorities; The environmental state determination unit is used to analyze the environmental state according to the environmental sensing data; The communication link scheduler is used to dynamically switch the module communication mode by using an optimal communication link selection algorithm; The recording and fault diagnosis module is used to store the system operation log, self-check result, and abnormal event; The energy management module includes a dynamic power conversion unit, a multi-mode power supply network, and an emergency energy storage unit; The dynamic energy conversion unit is used to provide a stable voltage and monitor the battery pack power; The multi-mode power supply network is used to switch the power supply mode of the battery pack according to the environmental state; The emergency energy storage unit is used to provide buffered power supply when the power supply is abnormal.

[0006] Further, the inertial measurement unit is arranged at the central part of the ocean buoy, and includes an accelerometer, a gyroscope, a transducer, and an antenna module. The acceleration data and angular velocity data are collected by the accelerometer and gyroscope as the environmental sensing data, and the environmental sensing data is transmitted to the embedded processor module through the antenna module.

[0007] Further, after the embedded processor module performs data fusion on the environmental sensing data using a floating-point arithmetic unit, the environmental state determination unit constructs a motion model based on the fused data and performs motion state calculation to obtain vibration intensity data and tilt rate of change data, and judges the environmental state by comparing with a threshold.

[0008] Further, the working modes of the multi-mode power supply network include a daily mode and an extreme event mode. When the vibration intensity data and the tilt rate of change data do not exceed the threshold, the daily mode is executed. When the vibration intensity data and the tilt rate of change data exceed the threshold, the extreme event mode is executed; The daily mode includes: supplying power with a single lithium battery pack, turning off non-core circuits through an opto-isolated relay, compressing data using Huffman coding and performing data backhaul; The extreme event mode includes: activating the TVS surge suppression circuit and redundant lithium battery packs, cutting off non-core functions, and preferentially supplying power for data communication of the inertial measurement unit.

[0009] Further, the module communication methods include 4G transmission, Beidou communication, data transmission radio, and underwater acoustic communication. The communication link scheduler collects the key indicators of the links in each communication method every 1s, normalizes the key indicators and assigns weights. The communication methods with scores higher than the threshold enter the candidate pool, and the communication method with the highest score in the candidate pool is used as the main communication method, and the communication method with the second highest score is used as the alternative communication method; During the communication process, based on historical data, a Bayesian network is used to update the weight allocation model in real time. When the score of the main communication method is lower than the threshold for 3 consecutive times, the alternative communication method is switched to, and a fault log is recorded.

[0010] Further, the dynamic energy conversion unit includes a DC / DC conversion chip and a coulomb meter. The DC / DC conversion chip outputs a voltage adjustment range according to the input specified voltage. The remaining battery power of the battery pack is monitored in real time through the coulomb meter, and the embedded processor module adjusts the sampling rate of the inertial measurement unit according to the remaining battery power of the battery pack.

[0011] On the other hand, to achieve the above object, the present invention proposes an energy optimization management method for a coupled environment air-sea cross-domain communication gateway, including the following steps: The inertial measurement unit is arranged in the ocean buoy to collect acceleration data and angular velocity data in real time; After parsing and fusing the acceleration data and the angular velocity data, the environmental state is judged according to the fused data through threshold comparison; The power supply mode of the system module is switched in real time according to the threshold comparison result; The remaining battery power of the battery pack is monitored, and the sampling rate of the inertial measurement unit is adjusted according to the remaining power.

[0012] Further, the process of judging the environmental state according to the fused data through threshold comparison includes: Based on the fused data, a motion model is constructed and the motion state is calculated to obtain vibration intensity data and inclination change rate data. When the vibration intensity data and the inclination change rate data do not exceed the threshold, the daily mode is executed. When the vibration intensity data and the inclination change rate data exceed the threshold, the extreme event mode is executed.

[0013] Further, the daily mode includes: powering by a single lithium battery pack, turning off non-core circuits through an optocoupler isolation relay, compressing data using Huffman coding and performing data backhaul; The extreme event mode includes: activating the TVS surge suppression circuit and the redundant lithium battery pack, cutting off non-core functions, and preferentially powering the data communication of the inertial measurement unit.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. Efficient energy management: The present invention adopts the daily mode to reduce power consumption through dynamic regulation and data compression, and the extreme mode to ensure stability through redundant design; 2. Environment adaptability: Based on the mode switching of real-time motion parameters, the adaptability to complex environments is improved; 3. High reliability: The surge suppression and self-check mechanism can effectively cope with power fluctuations and hardware failures; 4. Wide applicability: It can be extended to various mobile platforms such as unmanned aerial vehicles and unmanned ships. Description of the Drawings

[0015] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. In the drawings: Figure 1 It is a schematic diagram of the functional principle of the main control module in the embodiment of the present invention; Figure 2 It is a schematic diagram of the functional principle of the energy management module in the embodiment of the present invention; Figure 3 It is a schematic diagram of the method flow in the embodiment of the present invention; Figure 4 It is a schematic diagram of the feedback mechanism flow in the embodiment of the present invention; Figure 5 It is a schematic diagram of the structure of the inertial measurement unit in the embodiment of the present invention. Detailed implementation manners

[0016] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully conveyed to those skilled in the art. It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the drawings and in combination with the embodiments.

[0017] This embodiment proposes an energy optimization management system for an air-sea cross-domain communication gateway coupled with the environment, which mainly includes two parts: a main control module and an energy management module.

[0018] Among them, as Figure 1 shown, the main control module is the core decision-making unit of the system, responsible for data integration, mode switching, communication scheduling and energy collaborative management, and specifically includes the following sub-modules: The inertial measurement unit is arranged at the central part of the ocean buoy and includes an accelerometer, a gyroscope, a transducer and an antenna module, and collects acceleration data and angular velocity data through the accelerometer and the gyroscope as environmental sensing data.

[0019] The embedded processor module: adopts a low-power consumption embedded module, integrates a floating-point operation unit, supports multi-thread parallel processing, is responsible for real-time parsing of inertial measurement unit (IMU) data, executing a dynamic power management algorithm, and coordinating the task priorities of each communication module.

[0020] Specifically, the embedded processor module uses an ARMv8 quad-core floating-point arithmetic unit integrated with a NEON coprocessor to perform data parsing and fusion, and dynamically allocates CPU resources by constructing a task priority queue. For example, in an extreme sea state scenario, according to the system task requirements, the dynamic power management algorithm preferentially schedules the data processing tasks of the inertial measurement unit to ensure real-time processing of key data, while reducing the resource occupancy of unnecessary tasks to achieve power consumption optimization and task coordination; Environmental status determination unit: Based on the real-time data of the accelerometer and gyroscope, the Kalman filtering algorithm is used to eliminate noise interference, dynamically calculate the motion state of the device, and trigger the mode switching threshold (switch to the extreme mode when vibration > βg or the inclination change rate > θ° / s).

[0021] Communication link scheduler: According to the optimal communication link selection algorithm (comprehensive evaluation of signal strength, bit error rate, and delay), it automatically switches the 4G, Beidou, data transmission radio, or underwater acoustic communication module to ensure cross-domain communication stability.

[0022] The algorithm is based on a multi-dimensional channel quality evaluation and dynamic weight decision model, and the specific process is as follows: Step 1: Real-time channel state perception Parameter collection: Periodically (at 1s intervals), key indicators of each communication link are collected respectively: Signal strength (RSSI); Bit error rate (BER, calculated based on preamble check); Transmission delay (measured through the two-way handshake protocol); Link available bandwidth (based on traffic monitoring and protocol analysis); Energy consumption level (estimated according to the current transmit power and module power consumption model).

[0023] Step 2: Comprehensive evaluation of channel quality Normalization processing: Map each parameter to the interval [0, 1], and the formula is: , where Q i represents the mapped value of the parameter, is the original parameter value, is the preset threshold.

[0024] Weighted scoring: Dynamically adjust the weights according to the service type for weight allocation.

[0025] Step 3: Link priority sorting Arrange the available links in descending order of the comprehensive score, and the links with scores higher than the threshold (default 0.7) enter the candidate pool; If the candidate pool is empty, trigger the redundant link cooperation mechanism (such as 4G + Beidou dual-channel concurrent transmission).

[0026] Step 4: Dynamic switching and fault tolerance processing Handover decision: Select the link with the highest score in the candidate pool as the primary link and the sub-optimal link as the backup; Handover execution: Send AT commands to the corresponding module through the main control board to complete the physical layer link handover (handover latency < 200 ms); Abnormality monitoring: If the evaluation score of the primary link is lower than the threshold for three consecutive times, immediately switch to the backup link and record the fault log.

[0027] Step 5: Adaptive parameter optimization Based on historical data (such as the link stability statistics within 24 hours), use the Bayesian network to update the weight allocation model to improve the algorithm's environmental adaptability.

[0028] Algorithm performance verification: After lake trials and South China Sea open sea tests, the algorithm can achieve the following under sea state level 3: Link selection accuracy rate ≥ 95%; Handover latency ≤ 0.5 s; Overall communication energy consumption reduced by 18% - 25%; Cross-domain data transmission success rate increased to 99.3%.

[0029] Log recording and fault diagnosis module: Built-in non-volatile memory (NAND Flash), records the system operation logs, self-check results and abnormal events, and supports remote fault diagnosis and firmware upgrade.

[0030] As Figure 2 shown, the energy management module realizes efficient power supply and emergency guarantee through multi-level dynamic regulation, specifically including the following sub-modules: Dynamic power conversion unit: Includes a DC / DC conversion chip. Input a specified voltage to the chip, and the output adjustable range ensures that the minimum conversion efficiency can reach the required value, and can provide stable voltage for each module. A coulomb meter is added to monitor the remaining power of the lithium battery pack in real time and feedback it to the main control module to dynamically adjust the sensor sampling rate.

[0031] Multi-mode power supply network: Includes two working modes: daily mode and extreme event mode. When in the daily mode: In a calm and ideal daily environment, a single lithium battery pack is used for power supply. The non-core circuits are turned off through an opto-isolated relay, and data is compressed using Huffman coding to reduce transmission power consumption. Extreme mode: When an extreme situation occurs, such as strong winds and high waves, and the daily mode cannot be carried out, the extreme mode is adopted. Activate the TVS surge suppression circuit and redundant lithium battery packs, cut off non-core functions (such as the data storage unit), and give priority to ensuring the normal operation of the IMU sensor and the Beidou communication module.

[0032] Emergency energy storage unit: Applying a supercapacitor array to ensure high charge and discharge efficiency, instantaneously respond when the power supply is abnormal, and provide buffered power supply for critical circuits. At the same time, a self-check protection mechanism is adopted: periodically detect the state of health (SOH) of the battery. If the capacity attenuation is too large or the internal resistance is abnormal, trigger an alarm and switch to the backup power supply for power supply.

[0033] Based on the above system, this embodiment proposes an energy optimization management method for an air-sea cross-domain communication gateway coupled with the environment, as Figure 3 shown, including the following steps: Set the inertial measurement unit in the ocean buoy to collect acceleration data and angular velocity data in real time; After parsing and fusing the acceleration data and the angular velocity data, judge the environmental state according to the fused data and through threshold comparison; Switch the power supply mode of the system module in real time according to the threshold comparison result; Monitor the remaining power of the battery pack and adjust the sampling rate of the inertial measurement unit according to the remaining power.

[0034] In a specific embodiment, the working process of the system of the present invention is as follows: initialization, start the self-check program, and verify the sensor and power supply status. Select the working mode according to the real-time motion parameters and adapt through environmental determination. In the daily mode, use Huffman coding to compress data to reduce transmission power consumption. In the extreme event mode, turn off non-core functions (such as wireless communication) and give priority to ensuring sensor power supply. If a fault occurs, for example, when a power supply abnormality is detected, enable the backup battery and record the fault log.

[0035] In the specific application of the system, first deploy and initialize the device. Put the communication buoy integrated with the inertial measurement unit IMU into the target sea area, the floating body automatically unfolds, the transducer sinks underwater, and the antenna module emerges above the water surface. Power on the system. After the system is powered on, execute the self-check program to verify the status of the IMU sensor, power module, communication link (4G / Beidou / underwater acoustic) and energy storage unit. Record the self-check result in the log and upload it to the shore-based platform.

[0036] After the deployment is completed, it works normally under daily conditions. The determination of the daily mode is carried out by the IMU collecting relevant data of vibration intensity and inclination angle in real time, requiring the vibration intensity > βg and the inclination angle change rate > θ° / s. At the same time, from the perspective of energy conservation, a low-power strategy is adopted: the main control module dynamically reduces the sensor sampling rate, turns off the data transmission radio module, and only enables the Beidou short message communication. The battery capacity is monitored by a coulomb meter. If the remaining power is less than the specified value, the solar panel is activated for supplementary charging to achieve energy balance. When an extreme environment occurs, such as encountering strong wind and waves, and the IMU detects that the vibration intensity > the limit value, the main control module immediately switches to the extreme mode. The emergency power supply mode is enabled: the redundant lithium battery pack is activated, the power supply of the 4G module is cut off, the underwater acoustic communication is switched to spread spectrum modulation (with strong anti-interference), the Beidou module reports the position once every minute, and at the same time, the data protection function is enabled to prevent the loss of measurement-related information in the strong wind and wave environment. Core data (such as ocean temperature, salinity) is given priority for transmission, and non-real-time data is temporarily stored in the local flash memory and uploaded after the environment stabilizes.

[0037] After the detection task is completed, the main control module sends a termination instruction, turns off the underwater acoustic communication and sensors, and only keeps the Beidou module on standby. The system enters the low-power state, wakes up regularly to report the heartbeat signal until the next task is triggered. If some faults occur during operation, there is also a complete emergency handling plan. If the supercapacitor detects an instantaneous overvoltage, the TVS diode array starts to discharge, and at the same time, it switches to the backup battery. If a communication interruption problem occurs, for example, after 3 consecutive link connection failures, the main control module will restart the data transmission radio and send a fault code to the adjacent buoy networking relay through the underwater acoustic communication.

[0038] Refer to Figure 4 The feedback mechanism flowchart describes the feedback mechanism of this patent in more detail. After the sensor receives relevant information, it performs real-time data acquisition through devices such as accelerometers and gyroscopes, and fuses the acceleration data and angular velocity data. The processed data passes through a Kalman filter for dynamic state calculation and determination. The threshold varies according to the environment and required accuracy. If it is determined to be in an extreme situation, an emergency protocol needs to be started for corresponding operations. If it is in the daily situation, continue to detect and transmit the data back.

[0039] Refer to Figure 5 The device diagram describes the general shape of the inertial measurement unit described in the present invention. The module is located in the center of the buoy and is combined with the power module, etc., which is convenient for the system to be powered on and self-check regularly. After this unit is put into the water, it can float on the water surface. The transducer is located underwater, and the antenna module emerges from the water surface, which is convenient for receiving and sending information. This schematic diagram is convenient for more intuitively understanding this patent, and the specific details can be improved according to the application scenario and requirements.

[0040] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: it is still possible to modify the specific implementation manners of the present invention or make equivalent replacements, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. An energy optimization management system for air-sea cross-domain communication gateways in a coupled environment, characterized in that: It includes a main control module and an energy management module, wherein the main control module includes an inertial measurement unit, an embedded processor module, an environmental state determination unit, a communication link scheduler, and a recording and fault diagnosis module; The inertial measurement unit is used to collect environmental sensor data in real time; The embedded processor module uses a floating point unit to perform data analysis and fusion, and uses a dynamic power management algorithm to coordinate task priorities; The environmental state determination unit is used to analyze the environmental state according to the environmental sensor data; The communication link scheduler is used to dynamically switch the module communication mode using an optimal communication link selection algorithm; The recording and fault diagnosis module is used to store system operation logs, self-test results and abnormal events; The energy management module includes a dynamic power conversion unit, a multi-mode power supply network and an emergency energy storage unit; The dynamic power conversion unit is used to provide a stable voltage and monitor the power of the battery pack; The multi-mode power supply network is used to switch the power supply mode of the battery pack according to the environmental state; The emergency energy storage unit is used to provide buffer power supply when the power supply is abnormal.

2. The energy optimization management system for air-sea cross-domain communication gateways of coupled environments according to claim 1 is characterized in that: The inertial measurement unit is arranged at the center of the ocean buoy, and includes an accelerometer, a gyroscope, a transducer and an antenna module. The accelerometer and the gyroscope are used to collect acceleration data and angular velocity data as the environmental sensing data, and the environmental sensing data is transmitted to the embedded processor module through the antenna module.

3. The energy optimization management system for air-sea cross-domain communication gateways of coupled environments according to claim 1 is characterized in that: After the embedded processor module uses a floating-point operation unit to fuse the environmental sensor data, the environmental state determination unit constructs a motion model based on the fused data and performs motion state calculation, obtains vibration intensity data and inclination change rate data, and determines the environmental state by comparing the threshold.

4. The energy optimization management system for air-sea cross-domain communication gateways of coupled environments according to claim 3 is characterized in that: The working mode of the multi-mode power supply network includes a daily mode and an extreme event mode. When the vibration intensity data and the inclination change rate data do not exceed the threshold value, the daily mode is executed, and when the vibration intensity data and the inclination change rate data exceed the threshold value, the extreme event mode is executed; The daily mode includes: using a single lithium battery pack for power supply, shutting down non-core circuits through optocoupler isolation relays, and using Huffman coding to compress data and transmit data back; The extreme event mode includes: activating the TVS surge suppression circuit and the redundant lithium battery pack, cutting off non-core functions, and giving priority to powering the data communication of the inertial measurement unit.

5. The energy optimization management system for air-sea cross-domain communication gateways of coupled environments according to claim 1 is characterized in that: The module communication modes include 4G transmission, Beidou communication, digital radio, and underwater acoustic communication. The communication link scheduler collects key indicators of the links in each communication mode every 1 second, normalizes the key indicators and assigns weights. The communication modes with scores higher than the threshold enter the candidate pool, and the communication mode with the highest score in the candidate pool is used as the main communication mode, and the communication mode with the second highest score is used as the alternative communication mode; During the communication process, the Bayesian network is used to update the weight distribution model in real time based on historical data. When the score of the main communication mode is lower than the threshold for three consecutive times, it switches to the alternative communication mode and records the fault log.

6. The energy optimization management system for air-sea cross-domain communication gateways of coupled environments according to claim 1 is characterized in that: The dynamic energy conversion unit includes a DC / DC conversion chip and a coulomb meter. The DC / DC conversion chip outputs a voltage adjustment range according to the input specified voltage. The coulomb meter monitors the remaining power of the battery pack in real time, and the embedded processor module adjusts the sampling rate of the inertial measurement unit according to the remaining power of the battery pack.

7. A method for optimizing energy management of air-sea cross-domain communication gateways based on the coupled environment of the system according to any one of claims 1 to 6, characterized in that: The following steps are involved: An inertial measurement unit is installed in an ocean buoy to collect acceleration and angular velocity data in real time; After analyzing and fusing the acceleration data and the angular velocity data, judging the environmental state according to the fused data and by comparing the threshold value; Switch the power supply mode of the system module in real time according to the threshold comparison result; Adopt the optimal communication link selection algorithm to dynamically switch the module communication mode; The remaining power of the battery pack is monitored, and the sampling rate of the inertial measurement unit is adjusted according to the remaining power.

8. The method for optimizing energy management of air-sea cross-domain communication gateways in a coupled environment according to claim 7, characterized in that: The process of judging the environmental status based on the fused data and threshold comparison includes: Based on the fused data, a motion model is constructed and the motion state is calculated to obtain vibration intensity data and inclination change rate data. When the vibration intensity data and inclination change rate data do not exceed the threshold, the daily mode is executed. When the vibration intensity data and inclination change rate data exceed the threshold, the extreme event mode is executed.

9. The method for optimizing energy management of air-sea cross-domain communication gateways in coupled environments according to claim 8 is characterized in that: The daily mode includes: using a single lithium battery pack for power supply, shutting down non-core circuits through an optocoupler isolation relay, and using Huffman coding to compress data and transmit the data back; The extreme event mode includes: activating the TVS surge suppression circuit and the redundant lithium battery pack, cutting off non-core functions, and giving priority to powering the data communication of the inertial measurement unit.

10. The method for optimizing energy management of air-sea cross-domain communication gateways in coupled environments according to claim 7, characterized in that: The process of dynamically switching module communication modes using the optimal communication link selection algorithm includes: The key indicators of the links in each communication mode are collected every 1s, the key indicators are normalized and weighted, and the communication modes with scores higher than the threshold are entered into the candidate pool, and the communication mode with the highest score in the candidate pool is used as the main communication mode, and the communication mode with the second highest score is used as the alternative communication mode; During the communication process, the Bayesian network is used to update the weight distribution model in real time based on historical data. When the score of the main communication mode is lower than the threshold for three consecutive times, it switches to the alternative communication mode and records the fault log.

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