A method for processing observation data of ocean hydrological observation buoy

Abstract

The present invention discloses an observation data processing method for an ocean hydrological observation buoy, and specifically relates to the technical field of ocean hydrological observation buoys. By acquiring receiving sensitivity information, receiving signal amplification information, observation data integrity information and power supply stability information of an acoustic communication receiver, an acoustic communication receiver state evaluation model is constructed, and an acoustic communication receiver state evaluation index is generated. The potential receiving hidden danger risks existing during the operation of the acoustic communication receiver are evaluated to avoid loss or error of observation data due to failure to be discovered in time, and the potential receiving hidden danger risks existing in the acoustic communication receiver at the current moment are classified. According to the classification results of the potential receiving hidden danger risks, an advance warning is given to the operating state of the acoustic communication receiver, and a warning signal is generated before the potential hidden danger risks increase significantly, so as to effectively prevent observation data errors and losses caused by equipment failures. When the warning signal is generated, the observation data received in the corresponding period is marked as risk data.

Description

Technical Field

[0001] The present invention relates to the technical field of ocean hydrological observation buoys, and more specifically, to an observation data processing method of an ocean hydrological observation buoy. Background Art

[0002] Marine hydrological observation is the basic work of marine engineering construction, ship navigation safety and marine environmental protection. It refers to the systematic monitoring and recording of hydrological elements such as water temperature, salinity, currents and waves in the ocean through various equipment and technical means. These observation data are of great significance for understanding global climate change, preventing and responding to marine disasters, and ensuring maritime transportation and fisheries.

[0003] The ocean hydrological observation buoy is a commonly used ocean observation tool, which plays a connecting role in the ocean hydrological observation system. The ocean hydrological observation buoy is usually equipped with an acoustic communication receiver to receive observation data transmitted from the underwater observation platform. The ocean hydrological observation buoy equipped with an acoustic communication receiver is usually distributed in a large range of sea areas, and the difficulty of its fault repair is greatly increased compared with inland areas. Due to the complex and remote marine environment, maintenance work often requires a lot of time and resources. Therefore, staff are usually arranged to repair it only when the acoustic communication receiver sends out an obvious fault signal. However, the stability of the operating state of the acoustic communication receiver may have been continuously declining before the acoustic communication receiver sends out an obvious fault signal. When receiving the observation data, the acoustic communication receiver may have reception risks, resulting in loss or errors in the received observation data, thereby affecting the effect of ocean hydrological observation and reducing the reliability of the ocean hydrological observation system and the accuracy of the data.

[0004] In order to solve the above defects, a technical solution is now provided. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an observation data processing method of an ocean hydrological observation buoy to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A method for processing observation data of an ocean hydrological observation buoy comprises the following steps:

[0008] Step S1, obtaining receiving sensitivity information, receiving signal amplification information, observation data integrity information and power supply stability information of the sound communication receiver when it is in operation;

[0009] Step S2, constructing a sound communication receiver state assessment model based on the receiving sensitivity information, the receiving signal amplification information, the observation data integrity information and the power supply stability information, generating a sound communication receiver state assessment index, and assessing the potential receiving hidden danger risks existing during the operation of the sound communication receiver;

[0010] Step S3, comparing the sound communication receiver state evaluation index with a preset sound communication receiver state evaluation index threshold, and classifying the potential reception risk of the sound communication receiver at the current moment;

[0011] Step S4, according to the classification result of the potential receiving hidden danger risk, the operation status of the acoustic communication receiver is warned in advance. When the warning signal is generated, the observation data received in the corresponding period is marked as risk data.

[0012] In a preferred embodiment, the receiving sensitivity information includes a receiving response abnormality coefficient, the receiving signal amplification information includes a signal amplification strength fluctuation coefficient, the observation data integrity information includes an observation data integrity verification success rate, and the power supply stability information includes a lithium battery discharge stability coefficient;

[0013] The receiving response anomaly coefficient, signal amplification intensity fluctuation coefficient, observation data integrity verification success rate, and lithium battery discharge stability coefficient are marked as YC, FD, WZ, and LD, respectively.

[0014] In a preferred embodiment, the logic for obtaining the abnormal coefficient of the received response is as follows:

[0015] Record the time when each observation data signal is sent from the transmitter within the T time period, and mark it as t1; record the time when each observation data signal is received by the acoustic communication receiver, and mark it as t2; calculate the single response time, tresponse = t2-t1;

[0016] Set a response time baseline threshold, and mark the response time baseline threshold as tbaseline;

[0017] When tresponse>tbaseline, the response duration of the abnormal response when the acoustic communication receiver receives the observation data signal is marked as tyc i , i represents the number of times when the response duration tresponse>tbaseline, i={1, 2, ..., n}, n is a positive integer;

[0018] Calculate the receiving response anomaly coefficient, the expression is as follows

[0019] In a preferred embodiment, the logic for obtaining the signal amplification intensity fluctuation coefficient is as follows:

[0020] Obtain the observed data signal strength value Q after the sound communication receiver amplifies the observed data signal through the amplifier circuit every time within the T time period j , j represents the order number of the observation data signal amplified by the acoustic communication receiver through the amplification circuit, j = {1, 2, ..., m}, m is a positive integer;

[0021] Calculate the fluctuation error of the observed data signal strength value. The expression is as follows In the formula, BD represents the fluctuation error of the observed data signal strength value, E j represents the expected value of the strength of the observation data signal amplified by the j-th acoustic communication receiver through the amplifier circuit;

[0022] Compare the fluctuation error of the observed data signal strength value with the error threshold, count the number of times the fluctuation error of the observed data signal strength value is greater than the error threshold C1, count the number of times the fluctuation error of the observed data signal strength value is less than or equal to the error threshold C2, and calculate the signal amplification intensity fluctuation coefficient. The expression is as follows

[0023] In a preferred embodiment, the calculation expression of the success rate of the observation data integrity check is as follows: Where Y1 represents the number of times the acoustic communication receiver correctly verifies that the observed data is lost within the time period T, and Y2 represents the number of times the acoustic communication receiver fails to correctly verify that the observed data is lost within the time period T.

[0024] In a preferred embodiment, the logic for obtaining the lithium battery discharge stability coefficient is as follows:

[0025] Obtain the discharge voltage value of the lithium battery within the T time period and mark the discharge voltage value as V q , q represents the sequence number of different moments in the time period T, q = {1, 2, ..., p}, p is a positive integer;

[0026] Calculate the average voltage, the expression is as follows Where, vavg represents the average voltage;

[0027] Calculate the average value of the absolute deviation between the discharge voltage value and the average voltage at different times within the T time period. The expression is as follows

[0028] Calculate the discharge stability coefficient of lithium battery, the expression is as follows

[0029] In a preferred embodiment, the reception response anomaly coefficient, the signal amplification strength fluctuation coefficient, the observation data integrity verification success rate, and the lithium battery discharge stability coefficient are normalized, and a sound communication receiver state evaluation model is constructed according to the normalized reception response anomaly coefficient, the signal amplification strength fluctuation coefficient, the observation data integrity verification success rate, and the lithium battery discharge stability coefficient to generate a sound communication receiver state evaluation index stzs. The model is based on the following formula: Wherein a1, a2, a3, and a4 represent preset proportional coefficients of the receiving response anomaly coefficient, the signal amplification strength fluctuation coefficient, the observation data integrity verification success rate, and the lithium battery discharge stability coefficient, respectively, and a1, a2, a3, and a4 are all greater than 0.

[0030] In a preferred embodiment, the sound communication receiver state evaluation index is compared with a preset sound communication receiver state evaluation index threshold, and the potential reception risk of the sound communication receiver at the current moment is classified, and the classification is as follows:

[0031] If the sound communication receiver state evaluation index is greater than the sound communication receiver state evaluation index threshold, a potential receiving hidden danger risk signal is generated;

[0032] If the sound communication receiver state evaluation index is less than or equal to the sound communication receiver state evaluation index threshold, an operation steady-state signal is generated.

[0033] In a preferred embodiment, each time a potential receiving hidden danger risk signal is generated, the acoustic communication receiver state evaluation index generated in the corresponding period is obtained, a data analysis set is established, and the data analysis set is marked as alk={stzs z}, where z = {1, 2, 3…b}, b is a positive integer;

[0034] Calculate the abnormal value of the acoustic receiver state evaluation index in the data analysis set in turn, the expression is as follows In the formula, ycz z represents the abnormal value of the state evaluation index of the zth acoustic receiver in the data analysis set, and zm represents the average value of the state evaluation index of the acoustic receiver in the data analysis set. The expression is as follows zv represents the standard deviation of the acoustic receiver state evaluation index in the data analysis set, and the expression is as follows

[0035] In a preferred embodiment, the abnormal value of the sound communication receiver state evaluation index is compared with a preset abnormal threshold value to provide an advance warning of the operation state of the sound communication receiver, and the classification is as follows:

[0036] If the abnormal value of the acoustic receiver status evaluation index is greater than the abnormal threshold, a warning signal is generated and the observation data received in the corresponding period is marked as risk data;

[0037] If the abnormal value of the acoustic receiver status evaluation index is less than or equal to the abnormal threshold, there is no need to generate an early warning signal.

[0038] Technical effects and advantages of the present invention:

[0039] 1. The present invention obtains the receiving sensitivity information, receiving signal amplification information, observation data integrity information and power supply stability information of the acoustic communication receiver, constructs an acoustic communication receiver status evaluation model, generates an acoustic communication receiver status evaluation index, and evaluates the potential receiving hidden dangers during the operation of the acoustic communication receiver, thereby avoiding the loss or error of observation data due to failure to be discovered in time, reducing the system downtime and maintenance costs caused by acoustic communication receiver failures, and improving the overall reliability of the ocean hydrological observation system.

[0040] 2. The present invention classifies the potential reception hidden danger risks of the sound communication receiver at the current moment, and issues an advance warning of the operating status of the sound communication receiver according to the classification results of the potential reception hidden danger risks, and generates a warning signal before the potential hidden danger risks increase significantly, thereby effectively preventing observation data errors and losses caused by equipment failure. When the warning signal is generated, the observation data received in the corresponding period is marked as risk data, which helps to identify and filter the observation data that may have errors in the subsequent observation data processing and analysis process, thereby ensuring the accuracy of the final observation data. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0042] Figure 1 Schematic diagram of the structure of the method of the embodiment of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] Example

[0045] Figure 1 The present invention provides an observation data processing method of an ocean hydrological observation buoy, comprising the following steps:

[0046] Step S1, obtaining receiving sensitivity information, receiving signal amplification information, observation data integrity information and power supply stability information of the sound communication receiver when it is in operation;

[0047] The receiving sensitivity information includes the receiving response anomaly coefficient, the receiving signal amplification information includes the signal amplification intensity fluctuation coefficient, the observation data integrity information includes the observation data integrity verification success rate, and the power supply stability information includes the lithium battery discharge stability coefficient;

[0048] The receiving response anomaly coefficient, signal amplification intensity fluctuation coefficient, observation data integrity verification success rate, and lithium battery discharge stability coefficient are marked as YC, FD, WZ, and LD respectively;

[0049] The reception response anomaly coefficient is used to measure the degree of abnormal response of the sound communication receiver when receiving the observation data signal. This coefficient can indicate the speed and accuracy of the response generated by the sound communication receiver after receiving the signal, as well as the processing after receiving the signal. Abnormal reception response may cause delays in observation data reception, loss of observation data, or errors in observation data processing, thereby affecting the real-time and accuracy of the observation data. It can also be used to reflect the operating status of the sound communication receiver. The following is the impact of the abnormal response when the sound communication receiver receives the observation data signal on the operation of the sound communication receiver:

[0050] Increased data reception delay: Abnormal response may cause the acoustic receiver to process the observation data signal more slowly, delaying the reception of the observation data and affecting the real-time performance and response speed of the system;

[0051] Data loss: Abnormal reception response may cause the sound communication receiver to be unable to receive all data packets in time or correctly, resulting in loss of observation data and affecting the integrity of the observation data;

[0052] Data processing errors: Abnormal reception responses may cause errors in the sound communication receiver when processing the received observation data, such as observation data decoding errors or observation data parsing failures, affecting the accuracy and reliability of the observation data;

[0053] Increased energy consumption: Processing abnormal responses may cause the sound communication receiver to perform additional calculations and retries, increasing the energy consumption of the device, affecting battery life and device operating time;

[0054] Signal interference: Abnormal responses may increase the retransmission and processing time of observation data signals, resulting in waste of spectrum resources and interference with other devices;

[0055] The logic for obtaining the abnormal coefficient of the receiving response is as follows:

[0056] Record the time when each observation data signal is sent from the transmitter within the T time period, and mark it as t1; record the time when each observation data signal is received by the acoustic communication receiver, and mark it as t2; calculate the single response time, tresponse = t2-t1;

[0057] Set a response time baseline threshold, and mark the response time baseline threshold as tbaseline;

[0058] When tresponse≤tbaseline, it indicates that the response time of the acoustic receiver to receive the observation data signal is within the normal time range. When tresponse>tbaseline, it indicates that the response time of the acoustic receiver to receive the observation data signal is abnormal, and the response time of the acoustic receiver to receive the observation data signal is marked as tyc. i , i represents the number of times when the response duration tresponse>tbaseline, i={1, 2, ..., n}, n is a positive integer;

[0059] Calculate the receiving response anomaly coefficient, the expression is as follows

[0060] From the above calculation, it can be seen that the larger the reception response abnormality coefficient is, the worse the stability of the operation state of the sound communication receiver is, and the greater the probability of the existence of potential reception hidden danger risk. On the contrary, the smaller the reception response abnormality coefficient is, the higher the stability of the operation state of the sound communication receiver is, and the smaller the probability of the existence of potential reception hidden danger risk is.

[0061] After receiving the observation data signal, the sound communication receiver usually amplifies the observation data signal through the amplifier circuit. The signal amplification strength fluctuation coefficient is used to measure the stability of the change of the signal strength during the signal amplification process of the sound communication receiver. This coefficient can indicate the degree of fluctuation of the signal strength when the sound communication receiver amplifies the signal through the amplifier circuit after receiving the signal. Under normal circumstances, the signal strength should change stably within a certain range. If the signal strength fluctuation exceeds the set threshold, it may indicate that there is an abnormality in the amplifier circuit.

[0062] After receiving the signal, when the sound communication receiver amplifies the signal through the amplifier circuit, the abnormal fluctuation of the signal strength may cause the following effects on the operation of the sound communication receiver:

[0063] Data distortion: Abnormal fluctuations in signal strength may reflect that the amplifier circuit has improperly amplified the signal, which in turn causes distortion or deformation of the observed data, affecting the accuracy and reliability of the observed data;

[0064] Signal interference: Abnormal signal strength fluctuations may cause interference signals in the circuit to increase, which in turn affects the clarity and stability of the signal and may interfere with the received signal;

[0065] Reduced data quality: Abnormal signal strength fluctuations may cause data distortion, loss or interference, thereby reducing the quality of observation data and affecting the accuracy of subsequent data analysis and application;

[0066] The logic for obtaining the signal amplification intensity fluctuation coefficient is as follows:

[0067] Obtain the observed data signal strength value Q after the sound communication receiver amplifies the observed data signal through the amplifier circuit every time within the T time period j , j represents the order number of the observation data signal amplified by the acoustic communication receiver through the amplification circuit, j = {1, 2, ..., m}, m is a positive integer;

[0068] Calculate the fluctuation error of the observed data signal strength value. The expression is as follows In the formula, BD represents the fluctuation error of the observed data signal strength value, E j represents the expected value of the strength of the observation data signal amplified by the j-th acoustic communication receiver through the amplifier circuit;

[0069] Compare the fluctuation error of the observed data signal strength value with the error threshold, count the number of times the fluctuation error of the observed data signal strength value is greater than the error threshold C1, count the number of times the fluctuation error of the observed data signal strength value is less than or equal to the error threshold C2, and calculate the signal amplification intensity fluctuation coefficient. The expression is as follows

[0070] It should be noted that if the fluctuation error of the observed data signal strength value is greater than the error threshold, it means that a large intensity fluctuation occurs during the observation data signal amplification process, which exceeds the preset normal range; if the fluctuation error of the observed data signal strength value is less than or equal to the error threshold, it means that the fluctuation of the signal strength during the observation data signal amplification process is within an acceptable range and meets the preset normal range;

[0071] From the above calculation, it can be seen that the larger the signal amplification strength fluctuation coefficient is, the worse the stability of the sound communication receiver's operating state is, and the greater the probability of its potential reception risk is. On the contrary, the smaller the signal amplification strength fluctuation coefficient is, the higher the stability of the sound communication receiver's operating state is, and the smaller the probability of its potential reception risk is.

[0072] The success rate of observation data integrity verification is used to measure whether the sound communication receiver can successfully verify the proportion of observation data loss or damage after receiving the observation data. Specifically, it indicates how many proportions of observation data packets received by the sound communication receiver within the T time period can successfully pass the verification to confirm that they are not lost, reflecting the probability of successful verification of the sound communication receiver; the smaller the success rate of observation data integrity verification, the worse the stability of the operation state of the sound communication receiver, and the smaller the probability of potential reception hidden dangers. Conversely, the greater the success rate of observation data integrity verification, the higher the stability of the operation state of the sound communication receiver, and the greater the probability of potential reception hidden dangers.

[0073] The calculation expression of the success rate of observation data integrity verification is as follows Where, Y1 represents the number of times the acoustic receiver correctly verifies that the observed data is lost within the time period T, and Y2 represents the number of times the acoustic receiver fails to correctly verify that the observed data is lost within the time period T;

[0074] Ocean hydrological observation buoys equipped with acoustic receivers are usually distributed in a large sea area. In a large sea area, especially in deep sea areas far away from land, it is difficult to lay and maintain external power lines. The wiring cost is high, and there are problems such as corrosion and marine biological attachment. The external power supply is easily affected by the external environment, such as storms, waves, ship collisions, etc., and it is easy to have power outages or cable damage, affecting the operation of the equipment. Therefore, lithium batteries are usually used to power acoustic receivers, which do not rely on external power supplies and do not need to consider the laying and maintenance of power lines.

[0075] The lithium battery discharge stability coefficient is used to measure the voltage stability of lithium batteries during discharge. This coefficient can reflect the voltage fluctuation of lithium batteries under different working conditions, especially in long-term continuous use, to ensure a continuous and stable power supply for ocean hydrological observation buoys and their acoustic communication receivers.

[0076] The logic for obtaining the lithium battery discharge stability coefficient is as follows:

[0077] Obtain the discharge voltage value of the lithium battery within the T time period and mark the discharge voltage value as V q , q represents the sequence number of different moments in the time period T, q = {1, 2, ..., p}, p is a positive integer;

[0078] Calculate the average voltage, the expression is as follows Where, vavg represents the average voltage;

[0079] Calculate the average value of the absolute deviation between the discharge voltage value and the average voltage at different times within the T time period. The expression is as follows

[0080] Calculate the discharge stability coefficient of lithium battery, the expression is as follows

[0081] From the above calculation, it can be seen that the smaller the lithium battery discharge stability coefficient is, the worse the stability of the sound communication receiver's operating state is, and the greater the probability of its potential reception risk. On the contrary, the larger the lithium battery discharge stability coefficient is, the higher the stability of the sound communication receiver's operating state is, and the smaller the probability of its potential reception risk is.

[0082] Step S2, constructing a sound communication receiver state assessment model based on the receiving sensitivity information, the receiving signal amplification information, the observation data integrity information and the power supply stability information, generating a sound communication receiver state assessment index, and assessing the potential receiving hidden danger risks existing during the operation of the sound communication receiver;

[0083] The receiving response anomaly coefficient, signal amplification strength fluctuation coefficient, observation data integrity verification success rate, and lithium battery discharge stability coefficient are normalized. According to the normalized receiving response anomaly coefficient, signal amplification strength fluctuation coefficient, observation data integrity verification success rate, and lithium battery discharge stability coefficient, a sound communication receiver state evaluation model is constructed to generate a sound communication receiver state evaluation index stzs. The model is based on the following formula: Wherein a1, a2, a3, and a4 represent the preset proportional coefficients of the receiving response anomaly coefficient, the signal amplification strength fluctuation coefficient, the observation data integrity verification success rate, and the lithium battery discharge stability coefficient, respectively, and a1, a2, a3, and a4 are all greater than 0;

[0084] It can be seen from the above calculation expression that the larger the reception response anomaly coefficient, the larger the signal amplification strength fluctuation coefficient, the smaller the observation data integrity verification success rate, and the smaller the lithium battery discharge stability coefficient, the larger the sound communication receiver state evaluation index, indicating that the stability of the sound communication receiver's operating state is worse, and the probability of its potential reception hidden danger risk is greater. Conversely, the smaller the reception response anomaly coefficient, the smaller the signal amplification strength fluctuation coefficient, the larger the observation data integrity verification success rate, and the larger the lithium battery discharge stability coefficient, the smaller the sound communication receiver state evaluation index, indicating that the stability of the sound communication receiver's operating state is higher, and the probability of its potential reception hidden danger risk is smaller;

[0085] Step S3, comparing the sound communication receiver state evaluation index with a preset sound communication receiver state evaluation index threshold, and classifying the potential reception risk of the sound communication receiver at the current moment;

[0086] The sound communication receiver status evaluation index is compared with the preset sound communication receiver status evaluation index threshold, and the potential reception risk of the sound communication receiver at the current moment is classified as follows:

[0087] If the sound communication receiver state evaluation index is greater than the sound communication receiver state evaluation index threshold, it indicates that the stability of the operation state of the sound communication receiver is worse, and a potential receiving hidden danger risk signal is generated;

[0088] If the sound communication receiver state evaluation index is less than or equal to the sound communication receiver state evaluation index threshold, it indicates that the stability of the operation state of the sound communication receiver is higher, and an operation steady-state signal is generated;

[0089] Step S4, according to the classification result of the potential receiving hidden danger risk, the operation status of the acoustic communication receiver is warned in advance, and when the warning signal is generated, the observation data received in the corresponding period is marked as risk data;

[0090] Each time a potential receiving hidden danger risk signal is generated, the acoustic communication receiver state evaluation index generated in the corresponding period is obtained, a data analysis set is established, and the data analysis set is marked as alk = {stzs z}, where z = {1, 2, 3…b}, b is a positive integer;

[0091] Calculate the abnormal value of the acoustic receiver state evaluation index in the data analysis set in turn, the expression is as follows In the formula, ycz z represents the abnormal value of the state evaluation index of the zth acoustic receiver in the data analysis set, and zm represents the average value of the state evaluation index of the acoustic receiver in the data analysis set. The expression is as follows zv represents the standard deviation of the acoustic receiver state evaluation index in the data analysis set, and the expression is as follows

[0092] The abnormal value of the sound communication receiver status evaluation index is compared with the preset abnormal threshold value to provide an advance warning of the operation status of the sound communication receiver. The classification is as follows:

[0093] If the abnormal value of the sound communication receiver status evaluation index is greater than the abnormal threshold, it means that the operating status of the sound communication receiver is continuously declining, and an early warning signal is generated, and the observation data received in the corresponding period is marked as risk data;

[0094] If the abnormal value of the sound communication receiver status evaluation index is less than or equal to the abnormal threshold, it means that the operation status of the sound communication receiver has not shown an obvious downward trend, and there is no need to generate an early warning signal;

[0095] The present invention acquires the receiving sensitivity information, receiving signal amplification information, observation data integrity information and power supply stability information of the acoustic communication receiver, constructs an acoustic communication receiver state evaluation model, generates an acoustic communication receiver state evaluation index, and evaluates the potential receiving hidden danger risks during the operation of the acoustic communication receiver, thereby avoiding the loss or error of observation data due to the failure to discover the fault in time, reducing the system downtime and maintenance cost caused by the acoustic communication receiver failure, and improving the overall reliability of the ocean hydrological observation system.

[0096] The present invention classifies the potential reception hidden danger risks of the sound communication receiver at the current moment, and issues an advance warning of the operating status of the sound communication receiver according to the classification results of the potential reception hidden danger risks, and generates a warning signal before the potential hidden danger risks increase significantly, thereby effectively preventing observation data errors and losses caused by equipment failure. When the warning signal is generated, the observation data received in the corresponding period is marked as risk data, which helps to identify and filter the observation data that may have errors in the subsequent observation data processing and analysis process, thereby ensuring the accuracy of the final observation data.

[0097] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0098] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0099] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for processing observation data of an ocean hydrological observation buoy, characterized in that: The steps include: Step S1, obtaining receiving sensitivity information, receiving signal amplification information, observation data integrity information and power supply stability information of the sound communication receiver when it is in operation; Step S2, constructing a sound communication receiver state assessment model based on the receiving sensitivity information, the receiving signal amplification information, the observation data integrity information and the power supply stability information, generating a sound communication receiver state assessment index, and assessing the potential receiving hidden danger risks existing during the operation of the sound communication receiver; Step S3, comparing the sound communication receiver state evaluation index with a preset sound communication receiver state evaluation index threshold, and classifying the potential reception risk of the sound communication receiver at the current moment; Step S4, according to the classification result of the potential receiving hidden danger risk, the operation status of the acoustic communication receiver is warned in advance, and when the warning signal is generated, the observation data received in the corresponding period is marked as risk data; The receiving sensitivity information includes the receiving response anomaly coefficient, the receiving signal amplification information includes the signal amplification intensity fluctuation coefficient, the observation data integrity information includes the observation data integrity verification success rate, and the power supply stability information includes the lithium battery discharge stability coefficient; The receiving response anomaly coefficient, signal amplification intensity fluctuation coefficient, observation data integrity verification success rate, and lithium battery discharge stability coefficient are marked as YC, FD, WZ, and LD respectively; The logic for obtaining the abnormal coefficient of the receiving response is as follows: Record the time when each observation data signal is sent from the transmitter within the T time period, and mark it as t1; record the time when each observation data signal is received by the acoustic communication receiver, and mark it as t2; calculate the single response time, tresponse = t2-t1; Set a response time baseline threshold, and mark the response time baseline threshold as tbaseline; When tresponse>tbaseline, the response duration of the abnormal response when the acoustic communication receiver receives the observation data signal is marked as tyc i , i represents the number of times the response duration tresponse>tbaseline, i={1, 2, ..., n}, n is a positive integer; Calculate the receiving response anomaly coefficient, the expression is as follows The logic for obtaining the signal amplification intensity fluctuation coefficient is as follows: Obtain the observed data signal strength value Q after the sound communication receiver amplifies the observed data signal through the amplifier circuit every time within the T time period j , j represents the order number of the observation data signal amplified by the acoustic communication receiver through the amplification circuit, j = {1, 2, ..., m}, m is a positive integer; Calculate the fluctuation error of the observed data signal strength value. The expression is as follows Where BD represents the fluctuation error of the observed data signal strength value, E j represents the expected value of the strength of the observation data signal amplified by the j-th acoustic communication receiver through the amplifier circuit; Compare the fluctuation error of the observed data signal strength value with the error threshold, count the number of times the fluctuation error of the observed data signal strength value is greater than the error threshold C1, count the number of times the fluctuation error of the observed data signal strength value is less than or equal to the error threshold C2, and calculate the signal amplification intensity fluctuation coefficient. The expression is as follows The calculation expression of the success rate of observation data integrity verification is as follows Where, Y1 represents the number of times the acoustic receiver correctly verifies that the observed data is lost within the time period T, and Y2 represents the number of times the acoustic receiver fails to correctly verify that the observed data is lost within the time period T; The logic for obtaining the lithium battery discharge stability coefficient is as follows: Obtain the discharge voltage value of the lithium battery within the T time period and mark the discharge voltage value as V q , q represents the sequence number of different moments in the time period T, q = {1, 2, ..., p}, p is a positive integer; Calculate the average voltage, the expression is as follows Where, vavg represents the average voltage; Calculate the average value of the absolute deviation between the discharge voltage value and the average voltage at different times within the T time period. The expression is as follows Calculate the discharge stability coefficient of lithium battery, the expression is as follows The receiving response anomaly coefficient, signal amplification strength fluctuation coefficient, observation data integrity verification success rate, and lithium battery discharge stability coefficient are normalized. According to the normalized receiving response anomaly coefficient, signal amplification strength fluctuation coefficient, observation data integrity verification success rate, and lithium battery discharge stability coefficient, a sound communication receiver state evaluation model is constructed to generate a sound communication receiver state evaluation index stzs. The model is based on the following formula: Wherein a1, a2, a3, and a4 represent preset proportional coefficients of the receiving response anomaly coefficient, the signal amplification strength fluctuation coefficient, the observation data integrity verification success rate, and the lithium battery discharge stability coefficient, respectively, and a1, a2, a3, and a4 are all greater than 0.

2. The method for processing observation data of an ocean hydrological observation buoy according to claim 1, characterized in that: The sound communication receiver status evaluation index is compared with the preset sound communication receiver status evaluation index threshold, and the potential reception risk of the sound communication receiver at the current moment is classified as follows: If the sound communication receiver state evaluation index is greater than the sound communication receiver state evaluation index threshold, a potential receiving hidden danger risk signal is generated; If the sound communication receiver state evaluation index is less than or equal to the sound communication receiver state evaluation index threshold, an operation steady-state signal is generated.

3. The method for processing observation data of an ocean hydrological observation buoy according to claim 2, characterized in that: Each time a potential receiving hidden danger risk signal is generated, the acoustic communication receiver state evaluation index generated in the corresponding period is obtained, a data analysis set is established, and the data analysis set is marked as alk=stzs z }, where z = {1, 2, 3…b}, b is a positive integer; Calculate the abnormal value of the state evaluation index of the acoustic communication receiver in the data analysis set in turn. The expression is as follows In the formula, ycz z represents the abnormal value of the state evaluation index of the zth acoustic receiver in the data analysis set, and zm represents the average value of the state evaluation index of the acoustic receiver in the data analysis set. The expression is as follows zv represents the standard deviation of the acoustic receiver state evaluation index in the data analysis set, and the expression is as follows 4. The method for processing observation data of an ocean hydrological observation buoy according to claim 3, characterized in that: The abnormal value of the sound communication receiver status evaluation index is compared with the preset abnormal threshold value to provide an advance warning of the operation status of the sound communication receiver. The classification is as follows: If the abnormal value of the acoustic receiver status evaluation index is greater than the abnormal threshold, a warning signal is generated and the observation data received in the corresponding period is marked as risk data; If the abnormal value of the acoustic receiver status evaluation index is less than or equal to the abnormal threshold, there is no need to generate an early warning signal.

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