A control system for a deep-sea data logger

Abstract

This invention discloses a control system for a deep-sea data acquisition device, comprising: 1) a sampling control module: used to control the sampling operation of sensors, configure sampling strategies, and perform preliminary processing on the acquired data; 2) a storage control module: used for data storage and management, receiving data from the sampling control module and storing it in a memory; 3) an energy management module: used to monitor and manage the energy consumption of the deep-sea data acquisition device, allocate electrical energy, monitor power consumption, and optimize energy usage strategies; and 4) a transmission control module: used for data transmission and communication, responsible for data encoding, decoding, and protocol conversion. This control system for a deep-sea data acquisition device features low energy consumption, long standby time, and powerful functionality.

Description

Technical Field

[0001] This invention relates to the field of deep-sea data acquisition technology, specifically a control system for a deep-sea data acquisition device. Background Technology

[0002] The deep-sea environment, as one of the most mysterious and difficult-to-explore regions on Earth, contains abundant resources and environmental information. However, due to the extreme conditions of the deep-sea environment, such as high pressure, low temperature, and darkness, accurate data collection and long-term monitoring have always been major challenges in marine scientific research and marine resource development. In recent years, with the in-depth development of marine science, the demand for deep-sea environmental data has been increasing, especially in areas such as global climate change, marine ecosystem protection, and deep-sea mineral resource development, where this demand has become more urgent.

[0003] Currently, the control systems of deep-sea data acquisition devices mainly face the following technical challenges:

[0004] 1) Energy Management and Allocation. Batteries are the most common energy source for deep-sea data loggers. These loggers are equipped with various sensors, communication devices, and actuators, each with different energy requirements at different mission phases. How to rationally power each device, ensuring the normal operation of critical equipment while maximizing the logger's operating time, is a key aspect of energy management.

[0005] 2) Data Transmission and Communication. Abnormal data transmission can lead to data loss or delays, impacting subsequent data analysis and decision-making. Therefore, it is necessary to optimize transmission protocols, improve data transmission efficiency, and ensure the stability and reliability of data transmission. The deep-sea environment is complex, and communication signals are easily interfered with. Ensuring stable and reliable communication in the deep-sea environment is a significant challenge for the data transmission control module.

[0006] 3) Sampling control accuracy and efficiency. The deep-sea environment is complex and variable, requiring high accuracy and real-time performance in data acquisition. Therefore, it is necessary to improve the accuracy and efficiency of the sampling control module to meet the needs of deep-sea data acquisition.

[0007] 4) Storage Control and Management. Deep-sea data acquisition devices need to operate for extended periods, collecting vast amounts of data. How to efficiently store and manage this data, ensuring its integrity and security, is also a problem that needs to be solved.

[0008] Therefore, a control system for a deep-sea data acquisition device is needed to meet the needs of deep-sea exploration and scientific research. Summary of the Invention

[0009] To improve the energy management, data transmission, sampling control, and storage control of deep-sea data acquisition devices, this invention provides a control system for a deep-sea data acquisition device, comprising the following modules:

[0010] 1) Sampling control module: Used to control the sampling operation of the sensor, configure the sampling strategy, and perform preliminary processing on the collected data;

[0011] 2) Storage control module: Used for data storage and management, receiving data from the sampling control module and storing it in the memory;

[0012] 3) Energy Management Module: Used to monitor and manage the energy consumption of the deep-sea data acquisition unit, allocate power, monitor power consumption, and optimize energy usage strategies;

[0013] 4) Transmission control module: Used for data transmission and communication, responsible for data encoding, decoding and protocol conversion.

[0014] Preferably, the sampling control module includes the following sub-modules:

[0015] 1) Sensor interface submodule: used to connect and communicate with various sensors in the deep sea, including temperature sensors, pressure sensors, salinity sensors, optical sensors and acoustic sensors;

[0016] 2) Sampling strategy submodule: used to determine when to sample and the sampling frequency based on a preset sampling strategy or user instructions;

[0017] 3) Data processing and verification submodule: used to perform preliminary processing and verification of the collected data.

[0018] Preferably, the sampling strategy includes: 1) a time interval-based sampling strategy; 2) an event-triggered sampling strategy; 3) a specific condition-based sampling strategy; 4) a location-aware sampling strategy; 5) an energy efficiency optimization-based sampling strategy; 6) an adaptive sampling strategy; and 7) a hybrid sampling strategy.

[0019] Preferably, the storage control module includes the following sub-modules:

[0020] 1) Data storage management submodule: Used for data receiving, storage and retrieval operations, and managing memory space allocation;

[0021] 2) Data Compression and Optimization Submodule: Used for data compression to reduce storage space usage, data redundancy, and noise interference;

[0022] 3) Storage Status Monitoring Submodule: Used to monitor the storage status, predict and warn of the storage status, issue alarms in a timely manner and take protective measures. The storage status includes storage space, read / write speed and error rate.

[0023] 4) Storage strategy adjustment submodule: used to dynamically adjust the storage strategy based on the characteristics of the deep-sea environment, sampling strategy and data transmission status.

[0024] Preferably, the data compression employs a lossless compression algorithm, including the LZO data compression algorithm and the Zstandard data compression algorithm.

[0025] Preferably, the energy management module includes the following sub-modules:

[0026] 1) Power consumption optimization submodule: Used to reduce the power consumption of the deep-sea data acquisition unit, optimize the processing flow to achieve low power operation, and extend the running time;

[0027] 2) Energy Allocation Submodule: Used to allocate power according to the sensor's working status and energy allocation strategy, predict the sensor's working mode and energy consumption trend, and realize energy allocation and scheduling;

[0028] 3) Energy Monitoring and Early Warning Submodule: Used to monitor the energy usage of the deep-sea data acquisition device, provide timely early warnings, and take appropriate measures;

[0029] 4) Energy Utilization Submodule: Utilizes renewable energy sources in the marine environment to provide auxiliary power to the deep-sea data acquisition unit, extending its operating time.

[0030] Preferably, the energy allocation strategy includes: 1) a sampling-based energy allocation strategy; 2) a prediction-based energy allocation strategy; and 3) a priority-based energy allocation strategy.

[0031] Preferably, the transmission control module includes the following sub-modules:

[0032] 1) Communication mode switching submodule: used to select the communication mode based on sea conditions, data transmission requirements, and the energy status of the deep-sea data acquisition device itself;

[0033] 2) Data Encryption Submodule: Used to encrypt data during data transmission;

[0034] 3) Data transmission optimization submodule: used to optimize bandwidth utilization and reduce latency and errors during data transmission;

[0035] 4) Communication Protocol Management Submodule: Used to manage and maintain the communication protocol between the deep-sea data acquisition device and the surface or shore base station.

[0036] Preferably, the communication method includes acoustic communication and optical fiber communication, and the communication method switching submodule performs the following functions:

[0037] 1) Monitor sea conditions, assess the suitability of communication methods under the current environment, select the optimal communication method under the current environment, and ensure data continuity and integrity when switching communication methods;

[0038] 2) Construct a multi-path transmission network using multiple communication methods, monitor the status of each path, and dynamically adjust the data transmission path.

[0039] The control system and method for a deep-sea data acquisition device of the present invention have the following beneficial effects:

[0040] 1) The sampling control module controls the sampling operation of the sensor, sets and configures the sampling strategy, and supports multiple sampling strategies.

[0041] 2) The storage control module manages the storage of data, compresses storage space, and protects the data.

[0042] 3) Monitor and manage the energy consumption of the deep-sea data acquisition unit through the energy management module, allocate power, monitor power consumption, and optimize energy usage strategies.

[0043] 4) The deep-sea data acquisition device achieves efficient data transmission through the transmission control module.

[0044] The present invention provides a control system for a deep-sea data acquisition device, which features low energy consumption, long standby time, and powerful functions. Attached Figure Description

[0045] Figure 1 This is a block diagram of the control system module of a deep-sea data acquisition device according to an embodiment of the present invention. Detailed Implementation

[0046] To further understand the present invention, embodiments of the present invention are described below in conjunction with examples. However, it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, and not for limiting the scope of the claims of the present invention.

[0047] An embodiment of the present invention provides a control system for a deep-sea data acquisition device, such as... Figure 1 As shown, it includes a sampling control module, a storage control module, an energy management module, a transmission control module, etc. The following will provide further explanation of each module.

[0048] The sampling control module is responsible for controlling the accuracy and frequency of data acquisition. It includes the following sub-modules:

[0049] 1) Sensor Interface Submodule. This submodule is responsible for connecting and communicating with various sensors in the deep sea, including temperature sensors, pressure sensors, salinity sensors, optical sensors, and acoustic sensors. These sensors are used to measure various parameters of the deep-sea environment and can simultaneously collect multiple marine environmental parameters. The sensor interface submodule ensures the accurate acquisition and transmission of sensor data.

[0050] 2) Sampling Strategy Submodule. Based on a preset sampling strategy or user instructions, this submodule determines when and how frequently to perform sampling. Sampling strategies may be based on various factors such as time intervals, event triggers, or specific conditions. This submodule controls the sampling process to ensure data continuity and integrity.

[0051] 3) Data Processing and Verification Submodule. This submodule performs preliminary processing and verification of the collected data. It may include operations such as data smoothing, filtering, and outlier detection to improve data quality and reliability. The data processing and verification submodule helps reduce data errors and noise, providing more valuable information for subsequent data analysis.

[0052] The sampling strategy submodule is the most complex part of the sampling control module. To adapt to the special environment of deep-sea sampling, the following sampling strategy can be adopted in this embodiment of the invention:

[0053] 1) Time-interval-based sampling strategy. This is the most basic sampling strategy, which samples according to a preset time interval. For example, it can be set to collect data once every hour, every half hour, or even shorter intervals. This strategy is suitable for situations where deep-sea environmental parameters change relatively stably, ensuring the continuity and regularity of the data.

[0054] 2) Event-triggered sampling strategy. Sampling is triggered when a specific event occurs, such as when parameters like temperature, pressure, or salinity in the deep sea exceed a preset threshold. This strategy can capture sudden changes in the deep-sea environment and is suitable for studying deep-sea events or anomalies.

[0055] 3) Condition-specific sampling strategies. This strategy involves sampling based on specific conditions of the deep-sea environment, such as sampling at specific depths, water temperatures, or salinity levels. This approach enables data collection targeting specific deep-sea environmental characteristics, contributing to a deeper understanding of the complexity and diversity of the deep-sea environment.

[0056] 4) Location-aware sampling strategy. The positioning system equipped on the deep-sea data logger enables it to perform targeted sampling within specific geographical locations or depth ranges. For example, when the deep-sea data logger reaches preset geographical coordinates or water depths, the system will initiate a specific sampling procedure to ensure more accurate data collection in key areas.

[0057] 5) Energy-efficient sampling strategy. In conjunction with the energy management module, the sampling strategy submodule automatically adjusts the sampling strategy based on the remaining power of the deep-sea data logger and the estimated operating time to achieve optimal energy utilization efficiency. For example, when the power level falls below a certain threshold, the system automatically switches to a low-power sampling mode to reduce unnecessary sampling operations.

[0058] 6) Adaptive Sampling Strategy. The sampling frequency can be dynamically adjusted, and the deep-sea data acquisition system can automatically adjust the sampling frequency based on real-time environmental changes. For example, when drastic changes in the marine environment are detected, the system will automatically increase the sampling frequency to capture more detailed data; while when the environment is relatively stable, the system will reduce the sampling frequency to save energy and storage space.

[0059] 7) Hybrid Sampling Strategy. This involves combining two or more of the above sampling strategies to form a hybrid sampling strategy. For example, it can be set up to perform additional sampling when a specific event is detected or a specific condition is met, in addition to time-interval sampling. This strategy can balance data continuity and relevance, improving the efficiency and value of data collection.

[0060] The sampling strategy submodule supports user configuration and settings. Users can customize sampling strategies at different times and depths according to specific research needs or mission objectives to meet the special needs of deep-sea data acquisition devices.

[0061] In the control system of a deep-sea data acquisition device, the storage control module is crucial for ensuring secure and efficient data storage. In the deep-sea environment, data acquisition devices sometimes cannot transmit data in real time, making high-capacity storage an essential component. Simultaneously, data compression algorithms are used to reduce storage space usage. Given the unique characteristics of the deep-sea environment, these compression algorithms typically need to minimize data redundancy and noise interference while maintaining data quality. Considering the special features of the deep-sea environment and the data storage requirements, the storage control module can be divided into the following sub-modules:

[0062] 1) The data storage management submodule is responsible for data reception, storage, and retrieval operations. It manages memory space allocation to ensure data is stored sequentially and completely. Advanced storage management technologies, such as dynamic storage allocation and data block reorganization, can be employed to improve storage efficiency. Data encryption functions can also be integrated to ensure data security. High-density solid-state storage, such as NAND flash memory, can be used to ensure storage capacity while improving storage speed and stability.

[0063] 2) Data Compression and Optimization Submodule. This submodule applies data compression algorithms to reduce storage space usage. While ensuring data quality, it minimizes data redundancy and noise interference. Data compression algorithms tailored to the characteristics of the deep-sea environment can be used to improve compression efficiency and data quality. Data preprocessing techniques, such as data smoothing and filtering, can be combined to further optimize the quality of stored data.

[0064] In this embodiment of the invention, a lossless compression algorithm is preferably used, which can be:

[0065] a) The LZO data compression algorithm offers fast compression and decompression speeds, making it suitable for scenarios requiring frequent data reads and writes. In deep-sea data acquisition systems with high real-time requirements, the LZO algorithm can quickly decompress and recompress data, ensuring efficient system operation.

[0066] b) The Zstandard data compression algorithm offers a high compression ratio, compressing data into a smaller space. It is suitable for environments with limited storage resources or scenarios requiring long-term storage of large amounts of data. For the large amounts of sensor data collected by deep-sea data loggers, the Zstandard algorithm can be used for compression to save storage space.

[0067] 3) Storage Status Monitoring Submodule. This submodule monitors the storage status in real time, including storage space, read / write speed, and error rate. It employs intelligent monitoring technology and predictive algorithms to predict and issue early warnings about the storage status. When storage anomalies occur, it promptly issues alarms and takes appropriate protective measures. It integrates fault recovery mechanisms, such as data backup and automatic repair, to improve the reliability of the storage system.

[0068] 4) Storage Strategy Adjustment Submodule. This submodule dynamically adjusts the storage strategy based on the characteristics of the deep-sea environment, sampling strategy, and data transmission. It can employ an adaptive storage strategy adjustment algorithm, taking into account deep-sea environment parameters and the characteristics of the sampled data. This optimizes the utilization of storage resources, ensuring that data can be read and transmitted promptly at critical moments. A user-defined storage strategy function can also be introduced to meet the needs of different scientific research tasks.

[0069] It is evident that the storage control module in the control system of the deep-sea data acquisition device can ensure that the data is stored safely, efficiently, and reliably, providing strong support for deep-sea scientific research.

[0070] Deep-sea data loggers cannot utilize traditional external wired power supplies in the deep-sea environment and typically rely on internal batteries, which limits their operating time. To extend operating time, the power consumption of deep-sea data loggers must be minimized, but this can sometimes affect sampling frequency and data quality. Deep-sea data loggers can employ various energy efficiency optimization technologies, such as low-power processors, intelligent sleep modes, dynamic energy allocation based on operating status, and energy allocation strategies based on task priority and remaining energy. Intelligent energy management modules can dynamically allocate power according to the sensor's operating status and enter a low-power mode when sampling is not required. Research on utilizing ocean thermal differences or wave energy to power deep-sea data loggers has further extended their operating time.

[0071] In this embodiment of the invention, the energy management module of the deep-sea data acquisition device is the part that ensures its continuous and efficient operation in the energy-constrained deep-sea environment. This module includes the following sub-modules:

[0072] 1) Power Consumption Optimization Submodule. In hardware circuit design, advanced semiconductor processes and power management technologies can be employed to further reduce the device's static and dynamic power consumption. This includes using low-power components and reducing unnecessary circuit connections. In software design and application, data processing flows can be optimized and unnecessary calculations reduced, enabling low-power operation of the deep-sea data acquisition unit and extending its operating time in power-constrained deep-sea environments.

[0073] 2) Energy Allocation Submodule. The intelligent energy management module dynamically allocates power based on the sensor's operating status, such as sampling frequency and data transmission rate, ensuring sufficient energy support for critical tasks while reducing energy consumption during off-peak hours or in low-power modes. More precise energy allocation and scheduling can be achieved by predicting sensor operating modes and energy consumption trends. Possible energy allocation strategies include:

[0074] a) Sampling-based energy allocation algorithm. The working time of nodes is dynamically adjusted based on energy status and task requirements. When remaining energy is low, the active time is reduced to decrease energy consumption; when remaining energy is sufficient, the active time is increased to improve performance. Working time and energy allocation can be dynamically adjusted based on parameters such as sensor sampling frequency and data transmission rate to ensure sufficient energy support for critical tasks while reducing energy consumption during off-peak hours or in low-power modes.

[0075] b) Prediction-based energy allocation algorithm. This algorithm uses historical data or models to predict sensor operating modes and energy consumption trends. By analyzing parameters such as sensor sampling frequency, data transmission rate, and operating environment, predictive models can be established, enabling accurate predictions of future energy consumption. Based on the prediction results, the prediction-based energy allocation algorithm can adjust the energy allocation strategy in advance to ensure that the sensor receives sufficient energy when needed, while avoiding unnecessary energy waste.

[0076] c) Priority-based energy allocation algorithm. Sensors are assigned different priorities based on the importance and urgency of the tasks. In situations with limited energy, the energy needs of high-priority tasks are prioritized. In deep-sea data loggers, priority-driven energy allocation algorithms can dynamically adjust their energy allocation strategy based on factors such as sensor task type and data transmission urgency, ensuring that critical tasks are processed first.

[0077] 3) Energy Monitoring and Early Warning Submodule. This submodule monitors the energy usage of the deep-sea data acquisition unit in real time, including remaining power and energy consumption rate. It issues an early warning signal when the energy is about to run out, allowing for timely intervention, such as activating a low-power mode or surfacing to replace the battery. This real-time monitoring and early warning of energy usage improves the reliability and safety of the deep-sea data acquisition unit.

[0078] 4) Energy Utilization Submodule. This module utilizes renewable energy sources in the marine environment, such as ocean thermal energy and wave energy, to provide auxiliary power to the deep-sea data acquisition unit, further extending its operating time. It employs efficient and reliable marine renewable energy conversion devices and integration technologies to achieve renewable energy power supply and long-term operation of the deep-sea data acquisition unit.

[0079] The energy management module of the deep-sea data acquisition unit integrates multiple sub-modules and innovative technologies to achieve efficient energy management and utilization, providing strong support for the continuous and stable operation of deep-sea data acquisition missions.

[0080] Deep-sea data acquisition devices can operate at depths exceeding 8000 meters. However, due to the strong absorption of electromagnetic waves by seawater, traditional radio communication is sometimes unusable in the deep sea, posing a significant challenge to real-time data transmission. While acoustic communication or periodic data retrieval can be used, both methods suffer from drawbacks such as high latency, low bandwidth, or operational complexity. In this embodiment of the invention, the deep-sea data acquisition device not only supports acoustic and fiber optic communication but also intelligently switches between real-time and delayed transmission, selecting the optimal transmission method based on sea conditions to reduce latency and errors during data transmission.

[0081] The transmission control module of the deep-sea data acquisition device is responsible for ensuring the efficient and secure transmission of data from the deep sea to surface or shore-based base stations. In this embodiment of the invention, the transmission control module includes the following sub-modules:

[0082] 1) Communication Mode Switching Submodule. Based on sea conditions, data transmission requirements, and the deep-sea data acquisition device's own energy status, the optimal communication mode is intelligently selected, including acoustic communication and fiber optic communication. Possible methods include:

[0083] a) Utilize software algorithms and sensor technology to monitor sea conditions in real time, such as water flow velocity, temperature, and salinity, as well as the status of deep-sea data acquisition devices, such as remaining battery power and communication module status. Based on the monitoring data, evaluate the applicability of various communication methods in the current environment, considering factors such as communication speed, stability, and energy consumption. Based on the evaluation results, select the optimal communication method for the current environment. For example, in a deep-sea environment, acoustic communication may be preferred due to its good penetration and propagation distance; while under specific conditions suitable for fiber optic deployment, fiber optic communication may be more advantageous due to its high speed and low attenuation. When switching communication methods, ensure data continuity and integrity. This can be achieved using techniques such as data caching and retransmission mechanisms to ensure no data loss during the switching process.

[0084] (b) Besides choosing a single optimal communication method, multi-path transmission networks can be constructed using various communication methods such as sound waves and optical fibers. This can further improve the reliability and fault tolerance of data transmission. In a multi-path transmission network, the status of each path needs to be monitored in real time, and the data transmission path needs to be dynamically adjusted as needed. This also ensures that if a path fails, data can be quickly switched to other paths to continue transmission.

[0085] 2) Data Encryption Submodule. During data transmission, the data is encrypted to ensure it is not intercepted or tampered with. Advanced encryption algorithms and key management techniques can be used, such as symmetric encryption algorithms, asymmetric encryption algorithms, and hash algorithms. Appropriate encryption algorithms and key management techniques are selected based on specific requirements to improve data transmission security and ensure that the data is not intercepted or tampered with when transmitted to water or shore base stations.

[0086] Encryption methods for deep-sea data transmission should comprehensively consider factors such as algorithm security, performance, resource consumption, and compatibility. In situations where there are no data security risks, such as in open, controllable areas of the open ocean, encryption of transmitted data can be omitted to improve performance and reduce resource consumption.

[0087] 3) Data Transmission Optimization Submodule. This submodule optimizes bandwidth utilization and reduces latency and errors during data transmission. This includes data compression, error detection and correction, and retransmission mechanisms. Signal processing techniques and coding algorithms are used to improve the efficiency and accuracy of data transmission. For example, adaptive filtering, signal enhancement, wavelet transform, and other signal processing techniques, as well as error detection and correction coding, data compression algorithms, and efficient coding formats, are all well-suited for the deep-sea data transmission optimization submodule. The application of these techniques and algorithms can improve the efficiency and accuracy of data transmission, optimize bandwidth utilization, and reduce latency and errors.

[0088] 4) Communication Protocol Management Submodule. This submodule manages and maintains the communication protocol between the deep-sea data acquisition unit and surface or shore-based stations. This includes data packet format, transmission sequence, and error handling. It designs and adopts communication protocols suitable for deep-sea data transmission to improve reliability and flexibility. For example, it employs a highly adaptive communication protocol that can dynamically adjust data packet size and transmission frequency based on sea conditions and the status of the deep-sea data acquisition unit.

[0089] The transmission control module of the deep-sea data acquisition device integrates multiple sub-modules to achieve efficient and secure data transmission, improving the efficiency and reliability of data transmission and providing strong support for the continuous and stable execution of deep-sea data acquisition tasks.

[0090] In the control system of the deep-sea data acquisition device, the sampling control module, storage control module, energy management module, and transmission control module are its main components. These modules work together in accordance with the aforementioned description to achieve precise control of the deep-sea data acquisition device and complete the deep-sea exploration data acquisition task.

[0091] The above description of the embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. It should be noted that those skilled in the art can make several improvements and modifications to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

Claims

1. A control system for a deep-sea data acquisition device, characterized in that, Includes the following modules: 1) Sampling control module: Used to control the sampling operation of the sensor, configure the sampling strategy, and perform preliminary processing on the collected data; 2) Storage control module: Used for data storage and management, receiving data from the sampling control module and storing it in the memory; 3) Energy Management Module: Used to monitor and manage the energy consumption of the deep-sea data acquisition unit, allocate power, monitor power consumption, and optimize energy usage strategies; 4) Transmission control module: Used for data transmission and communication, responsible for data encoding, decoding and protocol conversion.

2. The control system for a deep-sea data acquisition device according to claim 1, characterized in that, The sampling control module includes the following sub-modules: 1) Sensor interface submodule: used to connect and communicate with various sensors in the deep sea, including temperature sensors, pressure sensors, salinity sensors, optical sensors and acoustic sensors; 2) Sampling strategy submodule: used to determine when to sample and the sampling frequency based on a preset sampling strategy or user instructions; 3) Data processing and verification submodule: used to perform preliminary processing and verification of the collected data.

3. The control system for a deep-sea data acquisition device according to claim 2, characterized in that, The sampling strategies include: 1) time interval-based sampling strategy; 2) event-triggered sampling strategy; 3) condition-based sampling strategy; 4) location-aware sampling strategy; 5) energy efficiency optimization-based sampling strategy; 6) adaptive sampling strategy; and 7) hybrid sampling strategy.

4. The control system for a deep-sea data acquisition device according to claim 1, characterized in that, The storage control module includes the following sub-modules: 1) Data storage management submodule: Used for data receiving, storage and retrieval operations, and managing memory space allocation; 2) Data Compression and Optimization Submodule: Used for data compression to reduce storage space usage, data redundancy, and noise interference; 3) Storage Status Monitoring Submodule: Used to monitor the storage status, predict and warn about the storage status, issue alarms in a timely manner and take protective measures. The storage status includes storage space, read / write speed and error rate. 4) Storage strategy adjustment submodule: used to dynamically adjust the storage strategy based on the characteristics of the deep-sea environment, sampling strategy and data transmission status.

5. A control system for a deep ocean data logger according to claim 4, wherein, The data compression employs lossless compression algorithms, including the LZO data compression algorithm and the Zstandard data compression algorithm.

6. The control system for a deep-sea data acquisition device according to claim 1, characterized in that, The energy management module includes the following sub-modules: 1) Power consumption optimization submodule: Used to reduce the power consumption of the deep-sea data acquisition unit, optimize the processing flow to achieve low power operation, and extend the running time; 2) Energy Allocation Submodule: Used to allocate power according to the sensor's working status and energy allocation strategy, predict the sensor's working mode and energy consumption trend, and realize energy allocation and scheduling; 3) Energy Monitoring and Early Warning Submodule: Used to monitor the energy usage of the deep-sea data acquisition device, provide timely early warnings, and take appropriate measures; 4) Energy Utilization Submodule: Utilizes renewable energy sources in the marine environment to provide auxiliary power to the deep-sea data acquisition unit, extending its operating time.

7. The control system for a deep-sea data acquisition device according to claim 6, characterized in that, The energy allocation strategies include: 1) a sampling-based energy allocation strategy; 2) a prediction-based energy allocation strategy; and 3) a priority-based energy allocation strategy.

8. A control system for a deep ocean data logger according to any one of claims 1 to 7, wherein, The transmission control module includes the following sub-modules: 1) Communication mode switching submodule: used to select the communication mode based on sea conditions, data transmission requirements, and the energy status of the deep-sea data acquisition device itself; 2) Data Encryption Submodule: Used to encrypt data during data transmission; 3) Data transmission optimization submodule: used to optimize bandwidth utilization and reduce latency and errors during data transmission; 4) Communication Protocol Management Submodule: Used to manage and maintain the communication protocol between the deep-sea data acquisition device and the surface or shore base station.

9. A control system for a deep ocean data logger according to claim 8, wherein, The communication methods include acoustic communication and optical fiber communication. The communication method switching submodule performs the following functions: 1) Monitor sea conditions, assess the suitability of communication methods under the current environment, select the optimal communication method under the current environment, and ensure data continuity and integrity when switching communication methods; 2) Construct a multi-path transmission network using various communication methods, monitor the status of each path, and dynamically adjust the data transmission path.

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