Automatic profile buoy self-destruction device and method based on multi-parameter fusion decision

Abstract

This invention provides an automatic profile buoy self-destruction device and method based on multi-parameter fusion decision-making, belonging to the field of buoy self-destruction technology. The device includes a buoy terminal and a host computer. The buoy terminal includes a control module and a power module, a Beidou communication module, a hydraulic drive module, a storage module, and a data acquisition module, all connected to the control module. The Beidou communication module establishes a Beidou satellite communication link between the buoy terminal and the host computer, enabling data uploading, command reception, and remote communication-based self-destruction. The storage module performs data security destruction. The hydraulic drive module receives commands from the control module and executes the buoy terminal's self-sinking operation. The beneficial effects of this invention are: integrating three functional modules—data security destruction, remote Beidou communication module self-destruction, and buoy self-sinking—proactively addressing risks such as loss of control, loss of communication, and accidental salvage, protecting data and the safety of the equipment itself.

Description

Technical Field

[0001] This invention belongs to the field of buoy self-destruction technology, and in particular relates to an automatic profile buoy self-destruction device and method based on multi-parameter fusion decision-making. Background Technology

[0002] With the development of ocean observation technology, automatic profiling buoys (APPs) have been deployed in large numbers in key sea areas. These buoys are usually deployed in the high seas and may be carried by ocean currents into the exclusive economic zones or even territorial waters of other countries, potentially leading to disputes over infringements on their jurisdiction or territorial rights. Furthermore, the marine environmental data stored inside the buoys, as well as the sensors and communication technologies they carry, are sensitive and confidential. If illegally salvaged, this could result in information leaks, and technical secrets could be analyzed and recovered through reverse engineering.

[0003] Existing automated profiling buoys primarily focus on ocean data acquisition and transmission, lacking a robust safety protection mechanism. Current technology suffers from the following drawbacks: a simplistic triggering mechanism, relying on only a single parameter (such as a cap-opening signal or communication signal), making it susceptible to environmental interference leading to false or missed triggers. This design exhibits poor robustness and cannot cope with complex and ever-changing maritime conditions. Furthermore, the high false alarm rate, due to the overly simplistic triggering mechanism, may result in accidental self-destruction, leading to unexpected loss of equipment and data. Additionally, there is a risk of missing real threats due to temporary sensor malfunctions or signal interference. Therefore, there is an urgent need for an automated profiling buoy capable of proactively addressing risks such as loss of control, loss of communication, and accidental salvage, while protecting both data and the equipment itself. Summary of the Invention

[0004] In view of this, the present invention aims to overcome the shortcomings of the above-mentioned problems in the prior art and proposes an automatic profile buoy self-destruct device and method based on multi-parameter fusion decision.

[0005] To achieve the above objectives, the technical solution of the present invention is implemented as follows: The first aspect of the present invention provides an automatic profile buoy self-destruct device based on multi-parameter fusion decision-making, including a buoy terminal and a host computer deployed on the ground; The buoy terminal includes a shell and a hatch connected to the opening of the shell, as well as a control module, a power module, a Beidou communication module, a hydraulic drive module, a storage module, and a data acquisition module installed inside the shell. The data acquisition module includes a water pressure acquisition module, a vacuum degree acquisition module, a positioning acquisition module, a communication signal acquisition module, and a hatch opening and closing detection module, which are used to acquire the water pressure outside the buoy terminal, the vacuum degree inside the hull, the position coordinates, the communication signal strength, and the hatch opening and closing status, respectively. The control module is connected to the power module, Beidou communication module, hydraulic drive module, storage module, and each acquisition module. It is configured to periodically acquire parameters from each acquisition module, filter and normalize the parameters, calculate the confidence coefficient and comprehensive risk score for each parameter, perform redundancy checks, and determine dynamic thresholds when redundancy conditions are met. Based on the comparison between the comprehensive risk score and the dynamic threshold, it triggers self-destruct operations in stages, controls the storage module, hydraulic drive module, and Beidou communication module to execute corresponding self-destruct actions, generates a self-destruct execution report, and uploads it to the host computer or local storage via the Beidou communication module. It also receives alarm cancellation commands from the host computer via the Beidou communication module, adjusts decision parameters, and stores the entire trigger process data in a false alarm pattern library to achieve self-learning and optimization of decision-making. The host computer communicates with the buoy terminal via the BeiDou satellite communication link and can issue a command to cancel the alarm to determine if it is falsely triggered. The Beidou communication module is used to establish a Beidou satellite communication link between the buoy terminal and the host computer, enabling data uploading, command reception, and execution of remote communication operations; The storage module is used to perform data security destruction operations under the control of the control module, and to store self-destruct execution reports, decision parameters, and false alarm pattern library data; The hydraulic drive module is used to perform the self-sinking operation of the buoy terminal under the control of the control module.

[0006] A second aspect of the present invention also provides an automatic profile buoy self-destruction method based on multi-parameter fusion decision-making, implemented by the aforementioned automatic profile buoy self-destruction device based on multi-parameter fusion decision-making, comprising the following steps: S1. Parameter acquisition: The buoy terminal's acquisition module periodically acquires the corresponding raw parameter data, including position coordinates, water pressure, vacuum degree, communication signal strength, and hatch opening and closing status. S2. Preprocessing: The raw data of each parameter is filtered and denoised, and normalized according to the preset risk threshold to map the parameter to a risk value of 0 or 1. The risk value is 0 when the parameter is in a safe state and 1 when the parameter is in an abnormal risk state. S3. Confidence assessment: Calculate the confidence coefficient for each parameter; S4. The weighted fusion calculation of the comprehensive risk score uses the confidence coefficient of each parameter as an adjustment factor to normalize and redistribute the preset basic weights of each parameter to obtain the dynamic weights of each parameter. Then, the comprehensive risk score at the current moment is calculated by weighted summation based on the risk value of each parameter and the corresponding dynamic weight. S5. Redundancy check: Based on the parameters participating in the weighted fusion in step S4, count the number of parameters that are valid in state but abnormal in parameter. When the number of parameters meets the preset redundancy judgment condition, proceed to step S6 for dynamic threshold judgment; if there is a failed parameter, remove the failed parameter, return to step S4, reallocate the dynamic weights based on the remaining valid parameters, and adjust the redundancy judgment condition; where, a parameter that is valid in state but abnormal in parameter refers to a parameter whose corresponding acquisition module is valid in state and whose risk value meets the preset abnormal judgment condition. S6. Dynamic threshold judgment and graded triggering: The dynamic threshold is determined based on the preset basic threshold and the comprehensive environmental noise. If the comprehensive risk score is greater than or equal to the dynamic threshold, the self-destruct response level is determined based on the comprehensive risk score and the number of parameters that are valid and abnormal, and the corresponding self-destruct operation is triggered. If the comprehensive risk score is less than the dynamic threshold, the process returns to step S1 to continue parameter acquisition. S7. Response Execution: Execute the self-destruct operation that matches the self-destruct response level, generate a self-destruct execution report, and upload or store it locally; S8. False trigger feedback and self-learning optimization: Record relevant data for the entire process of hierarchical triggering, and determine false triggering results for hierarchical triggering; when determined to be a false trigger, initiate feedback correction, adjust decision parameters, and store the entire process data of this hierarchical triggering into the false alarm pattern library to achieve decision self-learning optimization.

[0007] Furthermore, in step S2, the process of normalizing each parameter according to a preset risk threshold is as follows: The risk value of the location coordinates is determined based on the preset geofence. If the location enters the preset geofence, the risk value is 1; otherwise, it is 0. The risk value of water pressure is determined based on the preset water outlet threshold. If the water pressure value is lower than the preset water outlet threshold, the risk value is 1, and it is 0 at normal depth. The risk value of vacuum is determined based on a preset deviation threshold. If the deviation of the internal air pressure of the shell from the normal sealing air pressure reaches the preset deviation threshold, the risk value is 1; otherwise, it is 0. The risk value of the communication signal strength is determined based on the status of the communication signal. If the communication signal is lost, the risk value is 1; otherwise, it is 0. The risk value of the hatch opening and closing status is determined based on the hatch opening signal. If the opening signal is high, the risk value is 1; otherwise, it is 0.

[0008] Furthermore, the confidence assessment process in step S3 involves setting a real-time confidence coefficient for the parameters of each acquisition module. Its value range is [0,1], and its initial value is 1; and the confidence coefficient The specific rules are as follows: If the drift speed exceeds a preset speed threshold compared to the position coordinates of the previous cycle, the confidence coefficient of the position coordinates will be reduced. If the location coordinates, vacuum degree, and water pressure exceed the normal measurement values, the corresponding confidence coefficient will be set to zero. If the buoy terminal is located outside the coverage area of ​​the BeiDou satellite communication link, the confidence coefficient of the communication signal strength will be reduced. If the hatch is detected to be in the open state and the duration of the open state does not exceed the preset anti-shake time threshold, it is determined to be an instantaneous interference caused by mechanical vibration, and the confidence coefficient of the hatch opening and closing state is reduced.

[0009] Furthermore, in step S4, a dynamic weighted voting algorithm is used for weighted fusion calculation, and the specific process is as follows: No. i Dynamic weights of each parameter The calculation formula is as follows: , in, For the first i The preset base weights of each parameter, For the first i The confidence coefficients of each parameter Comprehensive Risk Score S The calculation formula is as follows: , in, For the first i The risk values ​​of each parameter after normalization.

[0010] Furthermore, in step S5, the preset anomaly judgment condition is that if the current risk value of a parameter is greater than 0.5, then the parameter is judged to be abnormal; the preset redundancy judgment condition is that the number of abnormal parameters is greater than or equal to 3.

[0011] Furthermore, in step S6, the dynamic threshold... The calculation formula is as follows: , in, The preset base threshold; As a comprehensive environmental noise, and , For the first i The standard deviation of the readings of each parameter within a preset time window.

[0012] Furthermore, in step S6, the self-destruct response level and the corresponding self-destruct operation are as follows: When the comprehensive risk score meets the first threshold condition, a Level 1 response is executed, which only involves data security destruction. When the number of parameters that are valid and abnormal meets the second threshold condition, a level 2 response is executed to perform data security destruction and remote communication termination. When the number of parameters that are valid and abnormal meets the third threshold condition, a three-level response is executed, including data security destruction, remote communication termination, and self-sinking of the buoy terminal.

[0013] Furthermore, in step S8, the data collected by the acquisition module, environmental parameters, and decision logs are recorded for a period of time before and after each graded trigger; when the host computer and the buoy terminal resume communication and issue a command to cancel the alarm, it is determined that the triggering condition has been met and feedback correction is initiated; when a false trigger occurs, the preset basic weights and preset basic thresholds of each parameter are adjusted and stored in the false alarm pattern library to optimize subsequent triggering decisions.

[0014] Compared with the prior art, the present invention has the following advantages: (1) The automatic profile buoy self-destruct device based on multi-parameter fusion decision-making described in this invention adopts a three-level architecture consisting of a host computer, a Beidou satellite communication link, and a buoy terminal. By acquiring the parameters collected by the acquisition module of the buoy terminal, the safety of the buoy terminal is determined. It integrates three functional modules: data security destruction, remote destruction of the Beidou communication module, and buoy self-sinking. It actively responds to risks such as loss of control, loss of contact, and accidental salvage, and protects the data and equipment security itself. (2) The automatic profile buoy self-destruction method based on multi-parameter fusion decision-making described in this invention proposes a multi-parameter fusion triggering algorithm based on weighted voting algorithm, which integrates five parameters: position coordinates, water pressure, vacuum degree, communication signal strength and hatch opening and closing status, effectively improving the triggering accuracy of buoy terminal self-destruction response; it designs a dynamic threshold adaptive false alarm rate control algorithm, which effectively reduces the false triggering rate of buoy terminal self-destruction response through redundancy verification; it adopts a hierarchical self-destruction response mechanism, which executes three levels of response: data level, communication level and system level according to risk level, and the self-destruction execution time is relatively short. Attached Figure Description

[0015] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a schematic diagram of the automatic profile buoy self-destruct device based on multi-parameter fusion decision-making as described in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the buoy terminal structure according to Embodiment 1 of the present invention; Figure 3 This is a flowchart of the automatic profile buoy self-destruction method based on multi-parameter fusion decision-making as described in Embodiment 2 of the present invention; Figure 4This is a flowchart illustrating the automatic profile buoy self-destruction method based on multi-parameter fusion decision-making as described in Embodiment 2 of the present invention.

[0016] Explanation of reference numerals in the attached figures: 1. Water pressure acquisition module; 2. Beidou communication module; 3. Control module; 4. Hydraulic drive module; 5. Housing; 6. Power supply module; 7. Leather bag. Detailed Implementation

[0017] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0018] In the description of this invention, it should be understood that these descriptions are merely exemplary and not intended to limit the scope of this application. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of this application for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0019] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0020] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0021] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0022] Example 1 like Figure 1 and Figure 2 As shown, the automatic profile buoy self-destruct device based on multi-parameter fusion decision-making includes a buoy terminal and a host computer deployed on the ground. The buoy terminal includes a shell 5 and a hatch connected to the opening end of the shell, and also includes a control module 3, a power module 6, a Beidou communication module 2, a hydraulic drive module 4, a storage module, and a data acquisition module installed inside the shell. The data acquisition module includes a water pressure acquisition module 1, a vacuum degree acquisition module, a positioning acquisition module, a communication signal acquisition module, and a hatch opening and closing detection module, which are used to acquire the water pressure outside the buoy terminal, the vacuum degree inside the hull, the position coordinates, the communication signal strength, and the hatch opening and closing status, respectively. The control module is connected to the power module, Beidou communication module, hydraulic drive module, storage module, and each acquisition module. It is configured to periodically acquire parameters from each acquisition module, filter and normalize the parameters, calculate the confidence coefficient and comprehensive risk score for each parameter, perform redundancy checks, and determine dynamic thresholds when redundancy conditions are met. Based on the comparison between the comprehensive risk score and the dynamic threshold, it triggers self-destruct operations in stages, controls the storage module, hydraulic drive module, and Beidou communication module to execute corresponding self-destruct actions, generates a self-destruct execution report, and uploads it to the host computer or local storage via the Beidou communication module. It also receives alarm cancellation commands from the host computer via the Beidou communication module, adjusts decision parameters, and stores the entire trigger process data in a false alarm pattern library to achieve self-learning and optimization of decision-making. The host computer communicates with the buoy terminal via the BeiDou satellite communication link and can issue a command to cancel the alarm to determine if it is falsely triggered. The Beidou communication module is used to establish a Beidou satellite communication link between the buoy terminal and the host computer, enabling data uploading, command reception, and execution of remote communication operations; The storage module is used to perform data security destruction operations under the control of the control module, and to store self-destruct execution reports, decision parameters, and false alarm pattern library data; The hydraulic drive module is used to perform the self-sinking operation of the buoy terminal under the control of the control module.

[0023] In this embodiment, multiple buoy terminals can be configured to collect marine data, such as... Figure 1 As shown.

[0024] In this embodiment, the water pressure acquisition module uses a temperature, salinity, and depth sensor. The measured values ​​are used to determine whether the buoy terminal has floated to shallow water or been retrieved from the water. The threshold corresponds to a water depth of less than 1 meter. There is a fixed correspondence between water pressure and water depth. When the water pressure collected by the temperature, salinity, and depth sensor is converted to the corresponding water depth, if the water depth is less than 1 meter, it is determined that the buoy has floated to a shallow water area or has been retrieved from the water. The vacuum degree acquisition module uses a pressure sensor. A vacuum degree of less than 1000 hPa is considered normal. The threshold corresponds to a vacuum degree of greater than 1000 hPa. If the vacuum degree is greater than 1000 hPa, it is determined that the seal has failed. The communication signal acquisition module obtains the communication signal strength by monitoring the received signal strength (RSSI) of the Beidou communication module. The disappearance of the signal is judged as abnormal. The positioning acquisition module and the communication signal acquisition module are both integrated into the Beidou communication module.

[0025] In this embodiment, the hatch opening / closing detection module is a hatch opening / closing detection circuit. The opening / closing state of the hatch is obtained by detecting the GPIO level of the hatch opening / closing detection circuit. A high level indicates that the hatch is open. Specifically, the hatch opening / closing detection module includes a thin metal connecting line laid at the joint surface between the hatch and the shell. One end of the connecting line is grounded, and the other end is connected to a GPIO pin with an internal pull-up resistor in the control module. When the hatch is closed, the line is conducting, and the GPIO reads a low level. When the hatch is illegally opened, the line is disconnected, and the GPIO becomes high due to the pull-up resistor. At this time, trigger signals can be sent to the storage module, the Beidou communication module, and the hydraulic drive module simultaneously to achieve multi-level linkage protection. In addition, the hatch opening / closing detection circuit includes an RC filter circuit to filter out instantaneous disconnection interference caused by mechanical vibration.

[0026] In this embodiment, the control module is an MCU, configured to perform self-destruct operations, including at least one of data security destruction, remote termination of the communication module, and buoy self-sinking; the control module includes a preprocessing unit, a confidence evaluation unit, a weighted fusion unit, a redundancy check unit, a hierarchical triggering unit, and a feedback self-learning optimization unit; in this embodiment, the storage module uses an E-type storage module that supports byte erasure and rewriting. 2 The PROM is used as a non-volatile storage medium; the control module is configured to adjust the basic weights and dynamic thresholds of each acquisition module when a false trigger is detected.

[0027] In this embodiment, the hydraulic drive module is configured to perform the buoy's self-sinking action. The hydraulic drive module includes a cylinder and a plunger pump fixed inside the shell, and a bladder 7 installed on the bottom outer side of the shell. The cylinder, plunger pump, and bladder are sequentially and sealed together via hydraulic lines. The plunger pump can be started under the control of the control module, changing the volume of hydraulic oil in the bladder through the hydraulic lines, thereby changing the volume of the buoy terminal in the seawater, enabling the buoy terminal to rise and sink. For example, the hydraulic oil in the bladder can be drawn back into the cylinder, causing the bladder to contract and reducing buoyancy. In this embodiment, a protective cover is provided at the bottom outer side of the shell, the bladder is located inside the protective cover, and a through hole is provided at the bottom of the protective cover for seawater to pass through.

[0028] In this embodiment, the BeiDou communication module is configured to perform a remote shutdown action. Specifically, in this embodiment, the BeiDou communication module adopts a BeiDou-3 module that supports remote shutdown. Its remote shutdown function is achieved by writing a locking instruction to a specific register. After the instruction is executed, the radio frequency and baseband circuits of the BeiDou communication module are permanently disabled.

[0029] Example 2 like Figure 3 and Figure 4 As shown, the automatic profile buoy self-destruction method based on multi-parameter fusion decision-making is implemented through the automatic profile buoy self-destruction device based on multi-parameter fusion decision-making described in Example 1, and includes the following steps: S1. Parameter acquisition: The buoy terminal's acquisition module periodically acquires the corresponding raw parameter data, including position coordinates, water pressure, vacuum degree, communication signal strength, and hatch opening and closing status. S2. Preprocessing: The original data of each parameter is filtered and denoised, and normalized according to the preset risk threshold. The parameters are binarized and mapped to risk values ​​of 0 or 1. The risk value is 0 when the parameter is in a safe state and 1 when the parameter is in an abnormal risk state. S3. Confidence assessment: Calculate the confidence coefficient for each parameter; S4. Weighted fusion calculation of comprehensive risk score: using the confidence coefficient of each parameter as the adjustment factor, the preset basic weight of each parameter is normalized and redistributed to obtain the dynamic weight of each parameter. Then, the risk value of each parameter and the corresponding dynamic weight are weighted and summed to calculate the comprehensive risk score of the entire device at the current moment. S5. Redundancy check: Based on the parameters participating in the weighted fusion in step S4, count the number of parameters that are valid in state but abnormal in parameter. When the number of parameters meets the preset redundancy judgment condition, proceed to step S6 for dynamic threshold judgment; if there is a failed parameter, remove the failed parameter, return to step S4, reallocate the dynamic weights based on the remaining valid parameters, and adjust the redundancy judgment condition; where, a parameter that is valid in state but abnormal in parameter refers to a parameter whose corresponding acquisition module is valid in state and whose risk value meets the preset abnormal judgment condition. S6. Dynamic threshold judgment and graded triggering: The dynamic threshold is determined based on the preset basic threshold and the comprehensive environmental noise. If the comprehensive risk score is greater than or equal to the dynamic threshold, the self-destruct response level is determined based on the comprehensive risk score and the number of parameters that are valid and abnormal, and the self-destruct operation corresponding to the self-destruct response level is triggered. If the comprehensive risk score is less than the dynamic threshold, the process returns to step S1 to continue parameter acquisition. S7. Response Execution: Execute the self-destruct operation that matches the self-destruct response level, generate a self-destruct execution report, and upload or store it locally; S8. False trigger feedback and self-learning optimization: Record relevant data for the entire process of hierarchical triggering, and determine false triggering results for hierarchical triggering; when determined to be a false trigger, initiate feedback correction, adjust decision parameters, and store the entire process data of this hierarchical triggering into the false alarm pattern library to achieve decision self-learning optimization.

[0030] In step S2, the process of normalizing each parameter according to a preset risk threshold is as follows: The risk value of the location coordinates is determined based on the preset geofence. If the location enters the preset geofence, the risk value is 1; otherwise, it is 0. The risk value of water pressure is determined based on the preset water outlet threshold. If the water pressure value is lower than the preset water outlet threshold, the risk value is 1, and it is 0 at normal depth. The risk value of vacuum is determined based on a preset deviation threshold. If the deviation of the internal air pressure of the shell from the normal sealing air pressure reaches the preset deviation threshold, the risk value is 1; otherwise, it is 0. The risk value of the communication signal strength is determined based on the status of the communication signal. If the communication signal is lost, the risk value is 1; otherwise, it is 0. The risk value of the hatch opening and closing status is determined based on the hatch opening signal. If the opening signal is high, the risk value is 1; otherwise, it is 0.

[0031] The confidence assessment process in step S3 is as follows: A real-time confidence coefficient is set for the parameters of each acquisition module. Its value ranges from [0,1], with an initial value of 1, to reflect the reliability of the current reading of the acquisition module; and the confidence coefficient The system dynamically adjusts its settings based on the recent output variance of the data acquisition module, its self-test status, and environmental conditions. The specific rules are as follows: If the drift speed exceeds a preset speed threshold of 3 m / s compared to the position coordinates of the previous cycle, the confidence coefficient of the position coordinates will be reduced. If the position coordinates, vacuum degree, and water pressure exceed the normal measurement values, it is determined that the air pressure sensor and pressure sensor have a hardware failure, and the corresponding confidence coefficient is set to zero. If the buoy terminal is located outside the coverage area of ​​the BeiDou satellite communication link, the confidence coefficient of the communication signal strength will be reduced. If the hatch is detected to be in the open state and the duration of the open state does not exceed the preset anti-shake time threshold, it is determined to be an instantaneous interference caused by mechanical vibration, and the confidence coefficient of the hatch opening and closing state is reduced.

[0032] Step S4 employs a dynamic weighted voting algorithm for weighted fusion calculation, and the specific process is as follows: No. i Dynamic weights of each parameter The calculation formula is as follows: , in, For the first i The preset base weights of each parameter, For the first i The confidence coefficients of each parameter Comprehensive Risk Score S The calculation formula is as follows: , in, For the firsti The risk values ​​of each parameter after normalization, and the comprehensive risk score. S The value range is [0,1], and the higher the value, the greater the risk.

[0033] In this embodiment, a vector composed of preset basic weights is used. ,in, These represent the preset base weights for position coordinates, water pressure, vacuum level, communication signal strength, and hatch opening / closing status, respectively. The weight allocation reflects the importance and priority of each parameter (position and water pressure are the most important, while hatch opening, as direct evidence, has the lowest weight).

[0034] In step S5, the preset anomaly judgment condition is that if the current risk value of a parameter is greater than 0.5, then the parameter is judged to be abnormal; the preset redundancy judgment condition is that the number of abnormal parameters is greater than or equal to 3. In this embodiment, the specific process of step S5 is as follows: when calculating S, the number N of parameters with a current risk value greater than 0.5 is counted, and a redundancy check of "at least three signals triggered" is performed: only when N≥3 is it allowed to enter the subsequent dynamic threshold judgment; if N=1 or 2, even if the comprehensive risk score is high, it is considered to be a single / dual acquisition module failure or interference, and self-destruction is not triggered, but an alarm of "suspected acquisition module failure" is reported. If an acquisition module is judged to be completely failed (C i If the value is approximately 0, the system automatically enters the single acquisition module failure mode: In step S5, the failed parameter is removed, and its basic weight is re-normalized and allocated among the remaining valid parameters. The condition of "at least three signals triggering" is adjusted to "at least a certain proportion (e.g., 2 / 3) of the remaining valid signals are abnormal." This ensures that the entire device still has decision-making capabilities when the acquisition module fails.

[0035] In step S6, the dynamic threshold The calculation formula is as follows: , in, The preset basic threshold is adjusted according to the risk level of the sea area, set at 0.6 in nearshore or sensitive sea areas, and at 0.8 in open high seas; For real-time estimation of the overall environmental noise, and , For the first i The standard deviation of the readings of each parameter within a preset time window.

[0036] In step S6, the self-destruct response level and the corresponding self-destruct operation are as follows: When the comprehensive risk score meets the first threshold condition, it is determined to be a suspected risk scenario, and a level 1 response is executed, which only involves data security destruction. When the number of parameters that are valid and abnormal meets the second threshold condition, it is determined to be a clear risk scenario, and a level-two response is executed to perform data security destruction and remote communication termination. When the number of parameters that are valid and abnormal meets the third threshold condition, it is determined to be a high-risk scenario, and a three-level response is executed, including data security destruction, communication remote shutdown, and buoy terminal self-sinking.

[0037] In this embodiment, the first threshold condition is that the comprehensive risk score is greater than the first preset threshold. Specifically, when the comprehensive risk score just exceeds the first preset threshold, it is a suspected risk scenario (such as a brief communication interruption). The DoD 5220.22-M standard triple overwrite algorithm is used to trigger only the data security destruction. The second threshold condition is that the number of parameters with valid status and abnormal parameters is greater than or equal to 3, including abnormal water pressure and communication signal interruption, which is suspected of being salvaged. At this time, a secondary response is performed. While the data is being destroyed, the Beidou communication module is destroyed by a high-voltage discharge circuit to remotely kill the communication, while the hydraulic drive module is preserved. The third threshold condition is that the number of parameters with valid status and abnormal parameters is greater than or equal to 4. On the basis of data security destruction and remote communication destruction, the hydraulic oil in the bladder is drawn back by the hydraulic drive module, causing the buoy terminal to sink to the seabed at a depth of 1,000 meters.

[0038] Specifically, in this embodiment, the control module performs secure data destruction on the storage module, and the data destruction overwrite algorithm is as follows: First overwrite: all 0x00, verifying write integrity; Second overwrite: all 0xFF, to verify read consistency; Third overwrite: Random numbers generated by a hardware true random number generator; Final verification: Randomly read 10 storage blocks to confirm irrecoverability, with a data retention rate of ≤0.001%.

[0039] After performing the self-destruct operation in step S7, an execution report is generated. If the communication link is available, the execution report is uploaded; if it is unavailable, the execution report is stored locally.

[0040] In step S8, the data collected by the acquisition module, environmental parameters, and decision logs are recorded for a period of time before and after each graded trigger. When the host computer and the buoy terminal resume communication and issue a command to cancel the alarm, it is determined that the triggering condition has been met and feedback correction is initiated. When a false trigger occurs, the preset basic weights and preset basic thresholds of each parameter are adjusted and stored in the false alarm pattern library to optimize subsequent triggering decisions.

[0041] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An automatic profile buoy self-destruct device based on multi-parameter fusion decision-making, characterized in that: This includes buoy terminals and ground-based host computers; The buoy terminal includes a shell and a hatch connected to the opening of the shell, as well as a control module, a power module, a Beidou communication module, a hydraulic drive module, a storage module, and a data acquisition module installed inside the shell. The data acquisition module is used to collect data on the water pressure outside the buoy terminal, the vacuum level inside the hull, the position coordinates, the communication signal strength, and the opening and closing status of the hatch. The control module is connected to the power module, Beidou communication module, hydraulic drive module, storage module, and acquisition module respectively; and is configured to acquire the parameters of the acquisition module, calculate the confidence coefficient and comprehensive risk score of each parameter, and perform dynamic threshold judgment; trigger self-destruct operation in stages according to the comparison result of comprehensive risk score and dynamic threshold, and control the storage module, hydraulic drive module, and Beidou communication module to perform corresponding self-destruct actions. The host computer communicates with the buoy terminal via the BeiDou satellite communication link; The Beidou communication module is used to establish a Beidou satellite communication link between the buoy terminal and the host computer, enabling data uploading, command reception, and execution of remote communication operations; The storage module is used to perform data security destruction operations under the control of the control module, and is also used to store related data; The hydraulic drive module is used to perform the self-sinking operation of the buoy terminal under the control of the control module.

2. An automatic profiling buoy self-destruction method based on multi-parameter fusion decision-making, implemented by the automatic profiling buoy self-destruction device based on multi-parameter fusion decision-making as described in claim 1, characterized in that, Includes the following steps: S1. Parameter acquisition: The buoy terminal's acquisition module periodically acquires the corresponding raw parameter data, including position coordinates, water pressure, vacuum degree, communication signal strength, and hatch opening and closing status. S2. Preprocessing: The raw data of each parameter is filtered and denoised, and normalized according to the preset risk threshold to map the parameter to a risk value of 0 or 1. The risk value is 0 when the parameter is in a safe state and 1 when the parameter is in an abnormal risk state. S3. Confidence assessment: Calculate the confidence coefficient for each parameter; S4. The weighted fusion calculation of the comprehensive risk score uses the confidence coefficient of each parameter as an adjustment factor to normalize and redistribute the preset basic weights of each parameter to obtain the dynamic weights of each parameter. Then, the comprehensive risk score at the current moment is calculated by weighted summation based on the risk value of each parameter and the corresponding dynamic weight. S5. Redundancy check: Based on the parameters participating in the weighted fusion in step S4, count the number of parameters that are valid in state but abnormal in parameter. When the number of parameters meets the preset redundancy judgment condition, proceed to step S6 for dynamic threshold judgment; if there is a failed parameter, remove the failed parameter, return to step S4, reallocate the dynamic weights based on the remaining valid parameters, and adjust the redundancy judgment condition; where, a parameter that is valid in state but abnormal in parameter refers to a parameter whose corresponding acquisition module is valid in state and whose risk value meets the preset abnormal judgment condition. S6. Dynamic threshold judgment and graded triggering: The dynamic threshold is determined based on the preset basic threshold and the comprehensive environmental noise. If the comprehensive risk score is greater than or equal to the dynamic threshold, the self-destruct response level is determined based on the comprehensive risk score and the number of parameters that are valid and abnormal, and the corresponding self-destruct operation is triggered. If the comprehensive risk score is less than the dynamic threshold, the process returns to step S1 to continue parameter acquisition. S7. Response Execution: Execute the self-destruct operation that matches the self-destruct response level, generate a self-destruct execution report, and upload or store it locally; S8. False trigger feedback and self-learning optimization: Record relevant data for the entire process of hierarchical triggering, and determine false triggering results for hierarchical triggering; when determined to be a false trigger, initiate feedback correction, adjust decision parameters, and store the entire process data of this hierarchical triggering into the false alarm pattern library to achieve decision self-learning optimization.

3. The automatic profile buoy self-destruction method based on multi-parameter fusion decision-making according to claim 2, characterized in that, In step S2, the process of normalizing each parameter according to a preset risk threshold is as follows: The risk value of the location coordinates is determined based on the preset geofence. If the location enters the preset geofence, the risk value is 1; otherwise, it is 0. The risk value of water pressure is determined based on the preset water outlet threshold. If the water pressure value is lower than the preset water outlet threshold, the risk value is 1, and it is 0 at normal depth. The risk value of vacuum is determined based on a preset deviation threshold. If the deviation of the internal air pressure of the shell from the normal sealing air pressure reaches the preset deviation threshold, the risk value is 1; otherwise, it is 0. The risk value of the communication signal strength is determined based on the status of the communication signal. If the communication signal is lost, the risk value is 1; otherwise, it is 0. The risk value of the hatch opening and closing status is determined based on the hatch opening signal. If the opening signal is high, the risk value is 1; otherwise, it is 0.

4. The automatic profile buoy self-destruction method based on multi-parameter fusion decision-making according to claim 2, characterized in that, The confidence assessment process in step S3 is as follows: A real-time confidence coefficient is set for the parameters of each acquisition module. Its value range is [0,1], and its initial value is 1; and the confidence coefficient The specific rules are as follows: If the drift speed exceeds a preset speed threshold compared to the position coordinates of the previous cycle, the confidence coefficient of the position coordinates will be reduced. If the location coordinates, vacuum degree, and water pressure exceed the normal measurement values, the corresponding confidence coefficient will be set to zero. If the buoy terminal is located outside the coverage area of ​​the BeiDou satellite communication link, the confidence coefficient of the communication signal strength will be reduced. If the hatch is detected to be in the open state and the duration of the open state does not exceed the preset anti-shake time threshold, it is determined to be an instantaneous interference caused by mechanical vibration, and the confidence coefficient of the hatch opening and closing state is reduced.

5. The automatic profile buoy self-destruction method based on multi-parameter fusion decision-making according to claim 2, characterized in that, Step S4 employs a dynamic weighted voting algorithm for weighted fusion calculation, and the specific process is as follows: No. i Dynamic weights of each parameter The calculation formula is as follows: ， in, For the first i The preset base weights of each parameter, For the first i The confidence coefficients of each parameter Comprehensive Risk Score S The calculation formula is as follows: ， in, For the first i The risk values ​​of each parameter after normalization.

6. The automatic profile buoy self-destruction method based on multi-parameter fusion decision-making according to claim 2, characterized in that: In step S5, the preset anomaly determination condition is that if the current risk value of a parameter is greater than 0.5, then the parameter is determined to be abnormal. The default redundancy judgment condition is that the number of abnormal parameters is greater than or equal to 3.

7. The automatic profile buoy self-destruction method based on multi-parameter fusion decision-making according to claim 2, characterized in that, In step S6, the dynamic threshold The calculation formula is as follows: ， in, The preset base threshold; As a comprehensive environmental noise, and , For the first i The standard deviation of the readings of each parameter within a preset time window.

8. The automatic profile buoy self-destruction method based on multi-parameter fusion decision-making according to claim 2, characterized in that, In step S6, the self-destruct response level and the corresponding self-destruct operation are as follows: When the comprehensive risk score meets the first threshold condition, a Level 1 response is executed, which only involves data security destruction. When the number of parameters that are valid and abnormal meets the second threshold condition, a level 2 response is executed to perform data security destruction and remote communication termination. When the number of parameters that are valid and abnormal meets the third threshold condition, a three-level response is executed, including data security destruction, remote communication termination, and self-sinking of the buoy terminal.

9. The automatic profile buoy self-destruction method based on multi-parameter fusion decision-making according to claim 2, characterized in that: In step S8, the data collected by the acquisition module, environmental parameters, and decision logs are recorded for a period of time before and after each graded trigger. When the host computer and the buoy terminal resume communication and issue a command to cancel the alarm, it is determined that the triggering condition has been met and feedback correction is initiated. When a false trigger occurs, the preset basic weights and preset basic thresholds of each parameter are adjusted and stored in the false alarm pattern library to optimize subsequent triggering decisions.

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