High-precision ocean temperature, salinity and depth sensing system based on data analysis model

Abstract

The present invention discloses a high-precision ocean temperature, salinity and depth sensing system based on a data analysis model, which relates to the field of marine environment detection technology, including a data acquisition and processing module, a measurement influence coefficient generation module, an abnormal measurement intelligent perception module, an abnormal type judgment and processing selection module, and an abnormal prompt module. The present invention comprehensively analyzes the performance characteristic information and dynamic saturation information of the salinity sensor when measuring the dissolved salt content in seawater, so that the system can perceive the measurement accuracy state of the salinity sensor in real time, especially when the measurement accuracy of the salinity sensor deteriorates, through real-time monitoring, the salinity data can be continuously analyzed, the abnormality or performance degradation can be detected in time, and when the abnormality is detected, an early warning signal can be generated in time to notify the relevant staff, which helps to prevent the negative impact of abnormal data on the overall performance of the system and improves the real-time perception capability of the ocean salinity change.

Description

Technical Field

[0001] The present invention relates to the technical field of marine environment detection, and in particular to a high-precision marine temperature, salinity and depth sensing system based on a data analysis model. Background Art

[0002] The high-precision ocean temperature, salinity and depth sensing system is an advanced instrument dedicated to measuring ocean environmental parameters, mainly including temperature, salinity and depth salinity sensors. This system is designed to provide high-precision, high-resolution measurement data of the vertical profile of the ocean to gain a deep understanding of the vertical structure and changes of the ocean. This system usually includes high-precision temperature and salinity sensors to measure the temperature of seawater. These salinity sensors use advanced technologies such as thermocouples or resistance thermometers to provide accurate temperature measurements. Ocean salinity refers to the content of dissolved salt in seawater and is one of the important parameters in the marine environment. Salinity sensors use principles such as conductivity or refractive index to measure the conductivity or optical properties of seawater to calculate the salinity value. The depth salinity sensor in the high-precision ocean temperature, salinity and depth sensing system is usually a pressure salinity sensor. Since water depth is closely related to water pressure, the depth of seawater can be accurately calculated by measuring the water pressure. This salinity sensor is usually able to provide high-resolution depth data over a large depth range.

[0003] The use of high-precision ocean temperature, salinity and depth sensing systems is of great significance for understanding ocean dynamics, climate change and the health of ecosystems. These systems are often used in fields such as oceanographic research, meteorology, environmental monitoring and marine resource management.

[0004] The measurement accuracy of salinity sensors is crucial in high-precision ocean temperature, salinity and depth sensing systems, because the salinity of seawater is a key physical and chemical parameter in the marine environment, which has a profound impact on the physical properties of the ocean, ecosystems and climate change. The salinity of seawater has a direct impact on its density, which in turn affects the circulation of the ocean and the movement of water masses. The salinity gradient is a key factor in the difference in seawater density, affecting the formation, drift and mixing of ocean currents and water masses. Accurate salinity measurements help reveal the salinity gradient in the ocean and provide important information for understanding ocean circulation. Salinity is closely linked to the thermodynamic properties of seawater, and together they determine the thermal salt convection in the ocean.

[0005] The existing technology has the following deficiencies: the existing high-precision ocean temperature, salinity and depth sensing system cannot understand the measurement accuracy status of the salinity sensor in real time. When the salinity sensor deteriorates in measuring the dissolved salt content in seawater, the system cannot perceive it intelligently. Accurate measurement of salinity in seawater is crucial to a deep understanding of the physical and chemical processes of the ocean. Abnormal salinity measurements may mask the salinity gradient in the ocean and affect the understanding of salinity-driven density and current changes, which will not only have a negative impact on the accuracy of climate models, but may also lead to erroneous predictions of changes in the marine environment.

[0006] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0007] The purpose of the present invention is to provide a high-precision ocean temperature, salinity and depth sensing system based on a data analysis model. By comprehensively analyzing the performance characteristic information and dynamic saturation information of the salinity sensor when measuring the dissolved salt content in seawater, the system can perceive the measurement accuracy status of the salinity sensor in real time. In particular, when the measurement accuracy of the salinity sensor deteriorates, the salinity data can be continuously analyzed through real-time monitoring, and anomalies or performance degradation can be detected in time. When anomalies are detected, an early warning signal can be generated in time to notify relevant personnel. This helps prevent the negative impact of abnormal data on the overall performance of the system, improves the real-time perception capability of changes in ocean salinity, and solves the problems in the above-mentioned background technology.

[0008] In order to achieve the above-mentioned object, the present invention provides the following technical solutions: a high-precision ocean temperature, salinity and depth sensing system based on a data analysis model, comprising a data acquisition and processing module, a measurement influence coefficient generation module, an abnormal measurement intelligent perception module, an abnormal type judgment and processing selection module and an abnormal prompt module;

[0009] The data acquisition and processing module acquires a plurality of data information when the salinity sensor measures the dissolved salt content in seawater, including the performance characteristic information and dynamic saturation information of the salinity sensor, and processes the performance characteristic information and dynamic saturation information of the salinity sensor after acquisition;

[0010] The measurement influence coefficient generation module comprehensively analyzes the processed performance characteristic information and dynamic saturation information to generate the measurement influence coefficient, and establishes a real-time accuracy measurement abnormality monitoring mechanism through the measurement influence coefficient;

[0011] The abnormal measurement intelligent perception module analyzes the measurement influence coefficient generated by the salinity sensor when measuring the dissolved salt content in seawater in real time, and intelligently perceives the abnormal measurement of the salinity sensor;

[0012] The abnormal type judgment and processing selection module, when sensing that there are abnormal hidden dangers in the process of the salinity sensor measuring the dissolved salt content in seawater, judges the type of abnormal hidden danger, and intelligently chooses to continue measuring or issue different types of early warning prompts through the abnormal prompt module.

[0013] Preferably, the performance characteristic information of the salinity sensor when measuring the dissolved salt content in seawater includes electrode response time information and linearity information. After acquisition, the electrode response time information is processed to generate an electrode response delay index and a linearity expected deviation index; the performance characteristic information of the salinity sensor when measuring the dissolved salt content in seawater includes salinity range saturation information. After acquisition, the salinity range saturation variation index is generated by processing the obtained salinity range saturation information.

[0014] Preferably, the logic of obtaining the electrode response delay index is as follows:

[0015] In the selected time window H, several actual electrode response times of the salinity sensor in the high-precision ocean temperature, salinity and depth sensing system when measuring the dissolved salt content in seawater are obtained, and the actual electrode response time is calibrated as , x It indicates the number of actual electrode response times obtained within the H time when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater. x =1, 2, 3, 4, ..., p , p is a positive integer;

[0016] When the salinity sensor measures the dissolved salt content in seawater, several actual electrode response times obtained within the H time are compared with the electrode response time reference value, and the actual electrode response time greater than the electrode response time reference value is calibrated as , It indicates the number of the actual electrode response time obtained within the H time when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater, which is greater than the reference value of the electrode response time. , is a positive integer, ;

[0017] Through the actual electrode response time The electrode response delay index is calculated by using the electrode response time reference value. The calculation expression is: , where represents the electrode response delay index, Indicates the reference value of electrode response time, pIt represents the total number of actual electrode response times obtained within the H time when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater.

[0018] Preferably, the logic for obtaining the expected linearity deviation index is as follows:

[0019] In the selected time window H, the actual electrical signal value when the salinity sensor in the high-precision ocean temperature, salinity and depth sensing system measures the dissolved salt content in seawater and the actual seawater salinity value corresponding to the actual electrical signal value are obtained, and the actual electrical signal value and the actual seawater salinity value corresponding to the actual electrical signal value are calibrated as and , y It indicates the number of the actual electrical signal value obtained within H time when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater and the actual seawater salinity value corresponding to the actual electrical signal value. y =1, 2, 3, 4, ..., m , m is a positive integer;

[0020] Calculate the actual linearity of the salinity sensor when measuring the dissolved salt content in seawater. The calculation formula is: , where Indicates the actual linearity, f The number indicating the actual linearity obtained within the H time when the salinity sensor measures the dissolved salt content in seawater. f =1, 2, 3, 4, ..., m , m is a positive integer;

[0021] The actual linearity obtained by the salinity sensor in measuring the dissolved salt content in seawater within the H time is compared with the expected linearity, and the expected linearity deviation is calculated. The calculation expression is: , where represents the expected deviation from linearity, represents the expected linearity, m It indicates the total number of actual linearities obtained within H time when the salinity sensor measures the dissolved salt content in seawater.

[0022] Preferably, the logic for obtaining the salinity range saturation variation index is as follows:

[0023] In the selected time window H, the actual salinity range saturation of the salinity sensor in the high-precision ocean temperature, salinity and depth sensing system at different time periods when measuring the dissolved salt content in seawater is obtained, and the actual salinity range saturation is calibrated as , kIt indicates the actual salinity range saturation number at different time periods during H time when the salinity sensor in the high-precision ocean temperature, salinity and depth sensing system measures the dissolved salt content in seawater. k =1, 2, 3, 4, ..., q , q is a positive integer;

[0024] The actual salinity range saturation obtained within H time when the salinity sensor measures the dissolved salt content in seawater is used to calculate the salinity range saturation standard deviation and the salinity range saturation average value, and the salinity range saturation standard deviation and the salinity range saturation average value are calibrated as and ,but: , ;

[0025] Calculate the salinity range saturation change index, the calculation expression is: , where Indicates the salinity range saturation variation index.

[0026] Preferably, the electrode response delay index generated within H time when the salinity sensor measures the dissolved salt content in seawater is obtained. , expected deviation from linearity , Salinity Range Saturation Variation Index After that, the electrode response delay index , expected deviation from linearity , Salinity Range Saturation Variation Index Perform comprehensive analysis to generate measurement impact coefficients , based on the formula: , where , , Electrode response delay index , expected deviation from linearity , Salinity Range Saturation Variation Index The preset scaling factor of , , Both are greater than 0.

[0027] Preferably, the measurement influence coefficient generated when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater is compared and analyzed with a preset measurement influence coefficient reference threshold, and the results of the comparison and analysis are as follows:

[0028] If the measurement influence coefficient is less than or equal to the measurement influence coefficient reference threshold, a normal signal is generated. When the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater and generates a normal signal, the salinity sensor continues to measure the dissolved salt content in seawater.

[0029] If the measurement influence coefficient is greater than the measurement influence coefficient reference threshold, an influence signal is generated. When the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater and generates an influence signal, the abnormal type of the salinity sensor is further judged.

[0030] Preferably, when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater to generate an influence signal, the measurement influence coefficient corresponding to the moment when the influence signal is generated and several measurement influence coefficients generated subsequently are obtained to establish a data set, and the measurement influence coefficients in the data set are comprehensively analyzed. The analysis process is as follows:

[0031] The average value and standard deviation of the measured influence coefficient are calculated through the measured influence coefficient in the data set, and the average value and standard deviation of the measured influence coefficient are compared with the preset influence coefficient reference threshold and the preset standard deviation reference threshold respectively to determine the type of abnormal hidden danger. The judgment process is as follows:

[0032] If the average value of the influence coefficient is less than or equal to the influence coefficient reference threshold and the standard deviation of the measured influence coefficient is less than or equal to the standard deviation reference threshold, an accidental abnormal signal is generated and transmitted to the abnormal prompt module, and an accidental warning prompt is issued to the accidental abnormal signal through the abnormal prompt module to inform the relevant staff;

[0033] If the average value of the influence coefficient is less than or equal to the reference threshold of the influence coefficient and the standard deviation of the measured influence coefficient is greater than the reference threshold of the standard deviation, an unstable abnormal signal is generated and transmitted to the abnormal prompt module, and an unstable early warning prompt is issued for the unstable abnormal signal through the abnormal prompt module to inform relevant staff members;

[0034] If the average value of the influence coefficient is greater than the reference threshold of the influence coefficient, a continuous abnormal signal is generated and transmitted to the abnormal prompt module. The abnormal prompt module issues a continuous warning prompt for the continuous abnormal signal to inform relevant staff.

[0035] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0036] The present invention introduces a real-time monitoring system and an intelligent perception mechanism. By comprehensively analyzing the performance characteristic information and dynamic saturation information of the salinity sensor when measuring the dissolved salt content in seawater, the system can perceive the measurement accuracy status of the salinity sensor in real time. In particular, when the measurement accuracy of the salinity sensor deteriorates, the salinity data can be continuously analyzed through real-time monitoring, and abnormalities or performance degradation can be detected in time. When an abnormality is detected, an early warning signal is generated in time to notify relevant staff. This helps prevent the negative impact of abnormal data on the overall performance of the system and improves the real-time perception capability of changes in ocean salinity.

[0037] By comprehensively analyzing the measurement influence coefficient, the system of the present invention can intelligently determine the abnormal type of the salinity sensor, identify accidental abnormalities, unstable abnormalities and continuous abnormalities, and take corresponding early warning and processing measures for different types of abnormalities, which helps to reduce the risk of incorrectly predicting changes in the marine environment and avoid the negative impact of abnormal salinity measurements on the accuracy of climate models. By real-time adjustment and optimization of the performance of the salinity sensor, the system can ensure the reliability and accuracy of the data and improve the simulation accuracy of the climate model for marine physical and chemical processes, thereby better serving the research and decision-making in the fields of meteorology, oceanography and environmental science. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0039] Figure 1 This is a module schematic diagram of the high-precision ocean temperature, salinity and depth sensing system based on the data analysis model of the present invention. DETAILED DESCRIPTION

[0040] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of the present disclosure will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art.

[0041] The present invention provides Figure 1 The high-precision ocean temperature, salinity and depth sensing system based on the data analysis model shown includes a data acquisition and processing module, a measurement influence coefficient generation module, an abnormal measurement intelligent perception module, an abnormal type judgment and processing selection module and an abnormal prompt module;

[0042] The data acquisition and processing module acquires a plurality of data information when the salinity sensor measures the dissolved salt content in seawater, including the performance characteristic information and dynamic saturation information of the salinity sensor, and processes the performance characteristic information and dynamic saturation information of the salinity sensor after acquisition;

[0043] The performance characteristic information of the salinity sensor when measuring the dissolved salt content in seawater includes electrode response time information and linearity information. After acquisition, the electrode response time information is processed to generate an electrode response delay index and a linearity expected deviation index.

[0044] When the salinity sensor measures the dissolved salt content in seawater, the electrode response time of the salinity sensor refers to the time required for the salinity sensor electrode system to be exposed to seawater and to stabilize the output in accordance with the actual seawater salinity change when placed in seawater. This time reflects the sensitivity and response speed of the salinity sensor to changes in the dissolved salt content in seawater. The speed of the electrode response time is directly related to the speed and accuracy of the salinity sensor in capturing salinity changes in ocean monitoring. A shorter response time helps to improve real-time performance and data accuracy, ensuring that the salinity sensor can promptly and accurately reflect changes in salinity in seawater.

[0045] In the high-precision ocean temperature, salinity and depth sensing system, when the salinity sensor is used to measure the dissolved salt content in seawater, the electrode response time of the salinity sensor is relatively long, which will seriously affect the measurement accuracy of the salinity sensor. The following are the specific reasons:

[0046] Time lag effect: Long electrode response time will cause the salinity sensor to produce time lag effect when encountering changes in seawater salinity, that is, the output value of the salinity sensor takes a long time to stabilize after the actual salinity changes. This will cause inconsistency between the actual salinity change and the output of the salinity sensor, reducing the timeliness and accuracy of the measurement.

[0047] Dynamic changes are not captured: Salinity in the marine environment may change rapidly, such as changes in salinity gradients caused by tides, seasonal changes, or meteorological events. The long response time of the electrode may fail to capture these dynamic changes, making the measurement of the salinity sensor unable to reflect the real-time salinity conditions in the actual seawater.

[0048] Limited real-time monitoring: The long electrode response time limits the real-time monitoring capability of the salinity sensor. Therefore, in application scenarios where it is necessary to quickly understand changes in seawater salinity, the long response time will limit the system's acquisition of real-time data and affect the effectiveness of the monitoring system.

[0049] Data instability: Long electrode response times can cause the output of salinity sensors to experience dramatic fluctuations in a short period of time as the system is still adapting to changes in salinity in the seawater. Such instability can make the collected data difficult to accurately interpret, reducing the reliability of the measurement.

[0050] Therefore, by monitoring the electrode response time of the salinity sensor when measuring the dissolved salt content in seawater, it is possible to detect the hidden danger that an abnormal electrode response time of the salinity sensor may lead to abnormal measurement accuracy.

[0051] The logic of obtaining the electrode response delay index is as follows:

[0052] In the selected time window H, several actual electrode response times of the salinity sensor in the high-precision ocean temperature, salinity and depth sensing system when measuring the dissolved salt content in seawater are obtained, and the actual electrode response time is calibrated as , x It indicates the number of actual electrode response times obtained within the H time when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater. x =1, 2, 3, 4, ..., p , p is a positive integer;

[0053] It should be noted that by recording the real-time output of the salinity sensor in the actual marine environment and observing the response of the salinity sensor to salinity changes in the marine environment, more realistic and dynamic electrode response time data can be obtained;

[0054] When the salinity sensor measures the dissolved salt content in seawater, several actual electrode response times obtained within the H time are compared with the electrode response time reference value, and the actual electrode response time greater than the electrode response time reference value is calibrated as , It indicates the number of the actual electrode response time obtained within the H time when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater, which is greater than the reference value of the electrode response time. , is a positive integer, ;

[0055] It should be noted that, considering the application scenarios and system sensitivity requirements, some applications may require very high sensitivity to detect the smallest abnormal response, while in other cases, the sensitivity requirement may be relatively low. Therefore, the reference value of the electrode response time when the salinity sensor measures the dissolved salt content in seawater is not specifically limited here and can be adjusted according to actual conditions;

[0056] Through the actual electrode response time The electrode response delay index is calculated by using the electrode response time reference value. The calculation expression is: , where represents the electrode response delay index, Indicates the reference value of electrode response time, p It represents the total number of actual electrode response times obtained within the H time when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater.

[0057] It can be seen from the calculation expression of the electrode response delay index that within the selected time window H, the larger the performance value of the electrode response delay index generated when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater, the greater the hidden danger of abnormal measurement accuracy when the salinity sensor measures the dissolved salt content in seawater. Conversely, the smaller the hidden danger of abnormal measurement accuracy when the salinity sensor measures the dissolved salt content in seawater.

[0058] When the salinity sensor measures the dissolved salt content in seawater, the linearity of the salinity sensor refers to whether the relationship between the salinity sensor output and the actual salinity in seawater is linear. When measuring the dissolved salt content in seawater, ideally, the output of the salinity sensor should be linear with the actual salinity, that is, as the salinity increases, the salinity sensor output increases in proportion. The linearity reflects the sensitivity of the salinity sensor to salinity changes and the output stability. Higher linearity means that the salinity sensor can provide more accurate, reliable and stable output under different salinity conditions, which helps to ensure that the measurement results accurately match the actual salinity value and improves the measurement accuracy and credibility of the salinity sensor.

[0059] The output of a salinity sensor refers to the electrical signal, current, voltage or other measurable physical quantity generated by the salinity sensor, which is used to reflect the stimulus received by the salinity sensor or the information of the measured target property. In the context of a salinity sensor, the output is usually an electrical signal or voltage, the size or change of which is related to the dissolved salt content in the measured seawater. For a salinity sensor, the output can be expressed as a voltage value or electrical signal, which is proportional to the change in seawater salinity sensed by the salinity sensor. The salinity sensor responds to the change in salinity in seawater through its internal measurement mechanism and converts this response into an electrical signal. Ideally, this electrical signal is linearly related to the salinity of seawater, that is, for every unit increase in seawater salinity, the output of the salinity sensor increases a fixed electrical signal accordingly.

[0060] In the high-precision ocean temperature, salinity and depth sensing system, when the salinity sensor is used to measure the dissolved salt content in seawater, the actual linearity of the salinity sensor deviates greatly from the expected linearity. The large deviation between the actual linearity and the expected linearity may have a serious impact on the measurement accuracy of the salinity sensor, as shown below:

[0061] Reduced accuracy: The deviation of actual linearity from expected linearity means that there is a nonlinear change in the relationship between the salinity sensor output and salinity. This nonlinear relationship may cause the output value provided by the salinity sensor to deviate from the actual salinity value in different salinity ranges, reducing the accuracy of the measurement.

[0062] Reduced reliability: Nonlinear response makes the output of the salinity sensor unstable, because the same salinity change may result in different output offsets. This will affect the reliability of the salinity sensor, reduce the consistency of the measurement results under different conditions, and make it difficult to ensure the consistency and reliability of the measurement.

[0063] Nonlinearity causes measurement errors: A large deviation between the actual linearity and the expected linearity will lead to a nonlinear relationship between the salinity sensor output and the actual salinity, which will cause measurement errors. In different salinity ranges, the output of the salinity sensor may show a different trend from the actual salinity value, thus affecting the accuracy of the measurement.

[0064] Inconsistent dynamic response: In marine environments, salinity may change rapidly due to tides, seasonal changes, or meteorological factors. Nonlinear response may cause the salinity sensor to respond inconsistently to dynamic salinity changes, causing the system to lose sensitivity to salinity changes in real-time monitoring.

[0065] Therefore, by monitoring the linearity of the salinity sensor when measuring the dissolved salt content in seawater, it can be perceived that abnormal linearity of the salinity sensor may lead to hidden dangers of abnormal measurement accuracy.

[0066] The logic for obtaining the linearity expected deviation index is as follows:

[0067] In the selected time window H, the actual electrical signal value when the salinity sensor in the high-precision ocean temperature, salinity and depth sensing system measures the dissolved salt content in seawater and the actual seawater salinity value corresponding to the actual electrical signal value are obtained, and the actual electrical signal value and the actual seawater salinity value corresponding to the actual electrical signal value are calibrated as and , y It indicates the number of the actual electrical signal value obtained within H time when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater and the actual seawater salinity value corresponding to the actual electrical signal value. y =1, 2, 3, 4, ..., m , m is a positive integer;

[0068] Calculate the actual linearity of the salinity sensor when measuring the dissolved salt content in seawater. The calculation formula is: , where Indicates the actual linearity, f The number indicating the actual linearity obtained within the H time when the salinity sensor measures the dissolved salt content in seawater. f =1, 2, 3, 4, ..., m , m is a positive integer;

[0069] The actual linearity obtained by the salinity sensor in measuring the dissolved salt content in seawater within the H time is compared with the expected linearity, and the expected linearity deviation is calculated. The calculation expression is: , where represents the expected deviation from linearity, represents the expected linearity, m It indicates the total number of actual linearities obtained within H time when the salinity sensor measures the dissolved salt content in seawater;

[0070] It should be noted that the expected linearity of the salinity sensor refers to the ideal linear relationship expected during the design and manufacturing stage based on the specifications, design principles and theoretical models of the salinity sensor. This theoretical linear relationship describes the expected relationship between the output signal of the salinity sensor and the actual seawater salinity. Here, the expected linearity of the salinity sensor is the ratio between the output signal and the actual seawater salinity.

[0071] It can be seen from the calculation expression of the expected linear deviation that within the selected time window H, the larger the performance value of the expected linear deviation generated by the salinity sensor in the high-precision ocean temperature, salinity and depth sensing system when measuring the dissolved salt content in seawater, the greater the hidden danger of abnormal measurement accuracy when the salinity sensor measures the dissolved salt content in seawater. Conversely, the smaller the hidden danger of abnormal measurement accuracy when the salinity sensor measures the dissolved salt content in seawater.

[0072] The performance characteristic information of the salinity sensor when measuring the dissolved salt content in seawater includes salinity range saturation information. After acquisition, the salinity range saturation information is processed to generate a salinity range saturation change index.

[0073] Salinity range saturation refers to the extent to which a salinity sensor can cover the range of salinity values ​​when measuring salinity. Specifically, it indicates the difference between the maximum and minimum salinity values ​​that the salinity sensor can accurately measure under certain conditions (e.g., temperature, pressure, etc.). This concept is intended to assess whether the salinity sensor can effectively cope with changes in water bodies of different salinities in the actual marine environment.

[0074] In the high-precision ocean temperature, salinity and depth sensing system, when the salinity sensor is used to measure the dissolved salt content in seawater, the large changes in the salinity range saturation at different times may have a serious impact on the measurement accuracy of the salinity sensor. The following is a detailed explanation:

[0075] Nonlinearity of measurement: If the salinity range saturation varies greatly over time, the salinity sensor may exhibit different response characteristics in different salinity ranges. This leads to nonlinearity of measurement, making salinity measurements at different time points or environmental conditions inconsistent. Nonlinearity can make it difficult for scientists to accurately compare measurements from different time periods.

[0076] Difficulty in establishing an accurate calibration model: Salinity sensors usually need to be calibrated under different salinity conditions and a calibration model needs to be established. If the salinity range saturation varies greatly at different times, the calibration model may become complex and difficult to establish. This makes it difficult to predict and correct the salinity measurement errors at different times.

[0077] Loss of adaptability to a specific salinity range: If the salinity sensor cannot adapt to the changes in salinity in seawater, it may lose adaptability to a specific salinity range at certain times. This may result in the inability to provide accurate salinity measurements in certain sea areas or depths, affecting scientific research and environmental monitoring in these areas.

[0078] Sensitivity to changes in the ocean environment: Salinity in the ocean may change due to factors such as season, geographic location, and depth. If the saturation of the salinity sensor cannot adapt to these changes, it will be difficult to perform sensitive and accurate monitoring of changes in the ocean environment.

[0079] Instabilities caused by temperature and pressure changes: Changes in salinity range saturation may be related to changes in temperature and pressure. This instability may cause the performance of the salinity sensor to fluctuate at different times and depths, thus affecting the accuracy of the salinity measurement.

[0080] Therefore, by monitoring the salinity range saturation when the salinity sensor measures the dissolved salt content in seawater, it is possible to perceive that abnormal changes in the salinity range saturation of the salinity sensor may lead to hidden dangers of abnormal measurement accuracy.

[0081] The logic of obtaining the salinity range saturation change index is as follows:

[0082] In the selected time window H, the actual salinity range saturation of the salinity sensor in the high-precision ocean temperature, salinity and depth sensing system at different time periods when measuring the dissolved salt content in seawater is obtained, and the actual salinity range saturation is calibrated as , k It indicates the actual salinity range saturation number at different time periods during H time when the salinity sensor in the high-precision ocean temperature, salinity and depth sensing system measures the dissolved salt content in seawater. k =1, 2, 3, 4, ..., q , q is a positive integer;

[0083] It should be noted that salinity sensors usually output electrical or digital signals, which reflect physical properties such as conductivity or refractive index in seawater, so that salinity can be calculated. By recording the output data of the salinity sensor, the change of salinity can be monitored in real time. These records can be compared and analyzed in different time periods to obtain information on the saturation of the salinity range;

[0084] The actual salinity range saturation obtained within H time when the salinity sensor measures the dissolved salt content in seawater is used to calculate the salinity range saturation standard deviation and the salinity range saturation average value, and the salinity range saturation standard deviation and the salinity range saturation average value are calibrated as and ,but: , ;

[0085] Calculate the salinity range saturation change index, the calculation expression is: , where Indicates the saturation variation index of salinity range;

[0086] It indicates the change of the actual salinity range saturation at different time periods when the salinity sensor measures the dissolved salt content in seawater. The larger the performance value, the greater the change in the actual salinity range saturation at different time periods when the salinity sensor measures the dissolved salt content in seawater, and the worse the stability. The smaller the performance value is, the smaller the change of saturation in the actual salinity range at different time periods when the salinity sensor measures the dissolved salt content in seawater is, and the better the stability is;

[0087] It can be seen from the calculation expression of the salinity range saturation variation index that within the selected time window H, the larger the performance value of the salinity range saturation variation index generated when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater, the greater the hidden danger of abnormal measurement accuracy when the salinity sensor measures the dissolved salt content in seawater. Conversely, the smaller the hidden danger of abnormal measurement accuracy when the salinity sensor measures the dissolved salt content in seawater.

[0088] The measurement influence coefficient generation module comprehensively analyzes the processed performance characteristic information and dynamic saturation information to generate the measurement influence coefficient, and establishes a real-time accuracy measurement abnormality monitoring mechanism through the measurement influence coefficient;

[0089] Obtain the electrode response delay index generated during the H time when the salinity sensor measures the dissolved salt content in seawater , expected deviation from linearity , Salinity Range Saturation Variation Index After that, the electrode response delay index , expected deviation from linearity , Salinity Range Saturation Variation Index Perform comprehensive analysis to generate measurement impact coefficients , based on the formula: , where , , Electrode response delay index , expected deviation from linearity , Salinity Range Saturation Variation Index The preset scaling factor of , , All are greater than 0;

[0090] It can be seen from the calculation formula that within the selected time window H, the smaller the electrode response delay index generated by the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system when measuring the dissolved salt content in seawater, the smaller the expected linear deviation, and the smaller the salinity range saturation variation index, that is, the smaller the performance value of the measurement influence coefficient generated by the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system when measuring the dissolved salt content in seawater, the smaller the hidden danger of abnormal measurement accuracy when the salinity sensor measures the dissolved salt content in seawater, and vice versa, the greater the hidden danger of abnormal measurement accuracy when the salinity sensor measures the dissolved salt content in seawater.

[0091] The abnormal measurement intelligent perception module analyzes the measurement influence coefficient generated by the salinity sensor when measuring the dissolved salt content in seawater in real time, and intelligently perceives the abnormal measurement of the salinity sensor;

[0092] The measurement influence coefficient generated by the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system when measuring the dissolved salt content in seawater is compared and analyzed with the pre-set measurement influence coefficient reference threshold. The results of the comparison and analysis are as follows:

[0093] If the measurement influence coefficient is less than or equal to the measurement influence coefficient reference threshold, a normal signal is generated. When the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater and generates a normal signal, it indicates that the salinity sensor can achieve efficient measurement of the dissolved salt content in seawater, and the dissolved salt content in seawater continues to be measured by the salinity sensor;

[0094] If the measurement influence coefficient is greater than the measurement influence coefficient reference threshold, an influence signal is generated. When the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system generates an influence signal when measuring the dissolved salt content in seawater, it indicates that there is a hidden danger of measurement abnormality in the measurement accuracy of the salinity sensor when measuring the dissolved salt content in seawater. It is necessary to further judge the abnormal type of the salinity sensor and carry out timely maintenance and management after the abnormal type is found out.

[0095] The abnormal type judgment and processing selection module, when sensing that there is an abnormal hidden danger in the process of the salinity sensor measuring the dissolved salt content in seawater, judges the type of abnormal hidden danger, and intelligently chooses to continue measuring or issue different types of early warning prompts through the abnormal prompt module;

[0096] When the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater to generate an influence signal, the measurement influence coefficient corresponding to the moment when the influence signal is generated and several measurement influence coefficients generated subsequently are obtained to establish a data set, and the measurement influence coefficients in the data set are comprehensively analyzed. The analysis process is as follows:

[0097] The average value and standard deviation of the measured influence coefficient are calculated through the measured influence coefficient in the data set, and the average value and standard deviation of the measured influence coefficient are compared with the preset influence coefficient reference threshold and the preset standard deviation reference threshold respectively to determine the type of abnormal hidden danger. The judgment process is as follows:

[0098] If the average value of the influence coefficient is less than or equal to the reference threshold of the influence coefficient and the standard deviation of the measured influence coefficient is less than or equal to the reference threshold of the standard deviation, an accidental abnormal signal is generated, and the accidental abnormal signal is transmitted to the abnormal prompt module, and an accidental early warning prompt is issued for the accidental abnormal signal through the abnormal prompt module to inform relevant staff that when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater and generates an accidental abnormal signal, it indicates that an accidental abnormality occurs when the salinity sensor measures the dissolved salt content in seawater;

[0099] If the average value of the influence coefficient is less than or equal to the reference threshold of the influence coefficient and the standard deviation of the measured influence coefficient is greater than the reference threshold of the standard deviation, an unstable abnormal signal is generated, and the unstable abnormal signal is transmitted to the abnormal prompt module, and an unstable early warning prompt is issued for the unstable abnormal signal through the abnormal prompt module to inform relevant staff that when the salinity sensor in the ocean temperature, salt and depth high-precision sensing system measures the dissolved salt content in seawater and generates an unstable abnormal signal, it indicates that an unstable abnormality occurs when the salinity sensor measures the dissolved salt content in seawater;

[0100] If the average value of the influence coefficient is greater than the reference threshold of the influence coefficient, a continuous abnormal signal is generated and transmitted to the abnormal prompt module. The abnormal prompt module issues a continuous early warning prompt for the continuous abnormal signal to inform relevant personnel that when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater and generates a continuous abnormal signal, it indicates that a continuous abnormality has occurred when the salinity sensor measures the dissolved salt content in seawater.

[0101] The present invention introduces a real-time monitoring system and an intelligent perception mechanism. By comprehensively analyzing the performance characteristic information and dynamic saturation information of the salinity sensor when measuring the dissolved salt content in seawater, the system can perceive the measurement accuracy status of the salinity sensor in real time. In particular, when the measurement accuracy of the salinity sensor deteriorates, the salinity data can be continuously analyzed through real-time monitoring, and abnormalities or performance degradation can be detected in time. When an abnormality is detected, an early warning signal is generated in time to notify relevant staff. This helps prevent the negative impact of abnormal data on the overall performance of the system and improves the real-time perception capability of changes in ocean salinity.

[0102] By comprehensively analyzing the measurement influence coefficient, the system of the present invention can intelligently determine the abnormal type of the salinity sensor, identify accidental abnormalities, unstable abnormalities and continuous abnormalities, and take corresponding early warning and processing measures for different types of abnormalities, which helps to reduce the risk of incorrectly predicting changes in the marine environment and avoid the negative impact of abnormal salinity measurements on the accuracy of climate models. By real-time adjustment and optimization of the performance of the salinity sensor, the system can ensure the reliability and accuracy of the data and improve the simulation accuracy of the climate model for marine physical and chemical processes, thereby better serving the research and decision-making in the fields of meteorology, oceanography and environmental science.

Claims

1. A high-precision ocean temperature, salinity and depth sensing system based on a data analysis model, characterized in that: It includes data acquisition and processing module, measurement influence coefficient generation module, abnormal measurement intelligent perception module, abnormal type judgment and processing selection module and abnormal prompt module; The data acquisition and processing module acquires a plurality of data information when the salinity sensor measures the dissolved salt content in seawater, including the performance characteristic information and dynamic saturation information of the salinity sensor, and processes the performance characteristic information and dynamic saturation information of the salinity sensor after acquisition; The measurement influence coefficient generation module comprehensively analyzes the processed performance characteristic information and dynamic saturation information to generate the measurement influence coefficient, and establishes a real-time accuracy measurement abnormality monitoring mechanism through the measurement influence coefficient; The abnormal measurement intelligent perception module analyzes the measurement influence coefficient generated by the salinity sensor when measuring the dissolved salt content in seawater in real time, and intelligently perceives the abnormal measurement of the salinity sensor; The abnormal type judgment and processing selection module, when sensing that there is an abnormal hidden danger in the process of the salinity sensor measuring the dissolved salt content in seawater, judges the type of abnormal hidden danger, and intelligently chooses to continue measuring or issue different types of early warning prompts through the abnormal prompt module; The performance characteristic information of the salinity sensor when measuring the dissolved salt content in seawater includes electrode response time information and linearity information. After acquisition, the electrode response time information is processed to generate an electrode response delay index and a linearity expected deviation index. The performance characteristic information of the salinity sensor when measuring the dissolved salt content in seawater includes salinity range saturation information. After acquisition, the salinity range saturation information is processed to generate a salinity range saturation variation index. The logic of obtaining the electrode response delay index is as follows: In the selected time window H, several actual electrode response times of the salinity sensor in the high-precision ocean temperature, salinity and depth sensing system when measuring the dissolved salt content in seawater are obtained, and the actual electrode response time is calibrated as λ x , x represents the number of actual electrode response times obtained within the H time when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater, x = 1, 2, 3, 4, ..., p, p is a positive integer; When the salinity sensor measures the dissolved salt content in seawater, several actual electrode response times obtained within the H time are compared with the electrode response time reference value, and the actual electrode response time greater than the electrode response time reference value is calibrated as λλ x′ , x′ represents the number of the actual electrode response time greater than the reference value of the electrode response time obtained within the H time when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater, x′=1, 2, 3, 4, ..., p′, p′ is a positive integer, p′≤p; The actual electrode response time λ x′ The electrode response delay index is calculated by using the electrode response time reference value. The calculation expression is: In the formula, λ 响应 represents the electrode response delay index, λλ 参考 represents the reference value of electrode response time, p represents the total number of actual electrode response times obtained within the H time when the salinity sensor in the high-precision ocean temperature, salinity and depth sensing system measures the dissolved salt content in seawater; The logic for obtaining the linearity expected deviation index is as follows: In the selected time window H, the actual electrical signal value when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater and the actual seawater salinity value corresponding to the actual electrical signal value are obtained, and the actual electrical signal value and the actual seawater salinity value corresponding to the actual electrical signal value are calibrated as ξξ respectively. y and ξξ′ y , y represents the actual electrical signal value obtained during the H time when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater and the number of the actual seawater salinity value corresponding to the actual electrical signal value, y = 1, 2, 3, 4, ..., m, where m is a positive integer; Calculate the actual linearity of the salinity sensor when measuring the dissolved salt content in seawater. The calculation formula is: In the formula, ξ η f represents the actual linearity, f represents the number of the actual linearity obtained by the salinity sensor within the time H when measuring the dissolved salt content in seawater, f = 1, 2, 3, 4, ..., m, where m is a positive integer; The actual linearity obtained by the salinity sensor in measuring the dissolved salt content in seawater within the H time is compared with the expected linearity, and the expected linearity deviation is calculated. The calculation expression is: In the formula, ξ η represents the expected deviation from linearity, ξξ η 预期 represents the expected linearity, and m represents the total number of actual linearities obtained within the time H when the salinity sensor measures the dissolved salt content in seawater; The logic of obtaining the salinity range saturation change index is as follows: In the selected time window H, the actual salinity range saturation of the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system at different time periods when measuring the dissolved salt content in seawater is obtained, and the actual salinity range saturation is calibrated as ψψ k , k represents the number of the actual salinity range saturation of different periods of time during H time when the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater, k = 1, 2, 3, 4, ..., q, q is a positive integer; The actual salinity range saturation obtained within the H time when the salinity sensor measures the dissolved salt content in seawater is used to calculate the salinity range saturation standard deviation and the salinity range saturation average value, and the salinity range saturation standard deviation and the salinity range saturation average value are calibrated as ψψ 标 and ψψ 平 ,but: Calculate the salinity range saturation change index, the calculation expression is: In the formula, ψψ 浮动 Indicates the saturation variation index of salinity range; Obtain the electrode response delay index λλ generated during the H time when the salinity sensor measures the dissolved salt content in seawater 响应 、Linearity expected deviation ξξ n 、Saturation variation index of salinity range ψψ 浮动 After that, the electrode response delay index λλ 响应 、Linearity expected deviation ξξ η 、Saturation variation index of salinity range ψψ 浮动 Perform comprehensive analysis to generate measurement impact coefficients The formula is: ， Where r1, r2, and r3 are the electrode response delay index λλ 响应 、Linearity expected deviation ξξ n 、Saturation variation index of salinity range ψψ 浮动 The preset proportional coefficient, and r1, r2, and r3 are all greater than 0.

2. The high-precision ocean temperature, salinity and depth sensing system based on the data analysis model according to claim 1 is characterized in that: The measurement influence coefficient generated by the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system when measuring the dissolved salt content in seawater is compared and analyzed with the pre-set measurement influence coefficient reference threshold. The results of the comparison and analysis are as follows: If the measurement influence coefficient is less than or equal to the measurement influence coefficient reference threshold, a normal signal is generated. When the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater and generates a normal signal, the salinity sensor continues to measure the dissolved salt content in seawater. If the measurement influence coefficient is greater than the measurement influence coefficient reference threshold, an influence signal is generated. When the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater and generates an influence signal, the abnormal type of the salinity sensor is further judged.

3. The high-precision ocean temperature, salinity and depth sensing system based on the data analysis model according to claim 2 is characterized in that: When the salinity sensor in the ocean temperature, salinity and depth high-precision sensing system measures the dissolved salt content in seawater to generate an influence signal, the measurement influence coefficient corresponding to the moment when the influence signal is generated and several measurement influence coefficients generated subsequently are obtained to establish a data set, and the measurement influence coefficients in the data set are comprehensively analyzed. The analysis process is as follows: The average value and standard deviation of the measured influence coefficient are calculated through the measured influence coefficient in the data set, and the average value and standard deviation of the measured influence coefficient are compared with the preset influence coefficient reference threshold and the preset standard deviation reference threshold respectively to determine the type of abnormal hidden danger. The judgment process is as follows: If the average value of the influence coefficient is less than or equal to the influence coefficient reference threshold and the standard deviation of the measured influence coefficient is less than or equal to the standard deviation reference threshold, an accidental abnormal signal is generated and transmitted to the abnormal prompt module, and an accidental warning prompt is issued to the accidental abnormal signal through the abnormal prompt module to inform the relevant staff; If the average value of the influence coefficient is less than or equal to the reference threshold of the influence coefficient and the standard deviation of the measured influence coefficient is greater than the reference threshold of the standard deviation, an unstable abnormal signal is generated and transmitted to the abnormal prompt module, and an unstable early warning prompt is issued for the unstable abnormal signal through the abnormal prompt module to inform relevant staff members; If the average value of the influence coefficient is greater than the reference threshold of the influence coefficient, a continuous abnormal signal is generated and transmitted to the abnormal prompt module. The abnormal prompt module issues a continuous warning prompt for the continuous abnormal signal to inform relevant staff.

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