A method, device and system for intelligent monitoring of marine environment data

Abstract

The present invention relates to the field of ocean monitoring technology based on electrochemistry, and specifically to a method, device and system for intelligent monitoring of marine environmental data. The present invention obtains a skeleton fitting curve for each contour step area, and obtains the abnormal performance of each fitting point on each skeleton fitting curve according to the conductivity distribution of each fitting point between different adjacent skeleton fitting curves; screens out abnormal ocean buoys in the corresponding contour step area according to the abnormal performance of each fitting point on each skeleton fitting curve, and obtains abnormal ocean buoys under all acquisition processes; obtains the service damage index of each abnormal ocean buoy according to the difference in conductivity change of each abnormal ocean buoy in the corresponding acquisition process before and after the alternating electrode potential; and screens out damaged buoys. The present invention analyzes the service loss of each ocean buoy, accurately screens out abnormal monitoring buoys, and improves the reliability of marine environmental monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of ocean monitoring based on electrochemistry, and in particular to a method, device and system for intelligent monitoring of ocean environment data. Background Art

[0002] Marine environmental monitoring technology is an important support for the development and utilization of marine resources. Among them, the salinity of seawater is a key physical and chemical parameter in the marine environment, which has a profound impact on the physical properties, ecosystem and climate change of the ocean. The salinity of seawater has a direct impact on its density, which in turn affects the circulation and movement of water masses in the ocean. The corresponding ocean salinity sensor is a high-end core equipment for obtaining the physical characteristics of the ocean and realizing ocean hydrological observation.

[0003] In the prior art, a salinity sensor is installed on an ocean buoy. The salinity sensor measures the impedance of seawater through electrodes to obtain the conductivity of seawater. Salts of different solubility in seawater will affect the conductivity of seawater. Therefore, the salinity of seawater is monitored through the conductivity between electrodes. However, due to the presence of other inorganic salt components in seawater itself, the electrodes will react with seawater to produce interference potential and chemical corrosion when immersed in seawater under alternating potential for a long time, and the reliability of the monitoring data is poor. Summary of the invention

[0004] In order to solve the technical problem that when monitoring seawater salinity through the conductivity between electrodes, interference potential and chemical corrosion may occur during reaction with seawater, resulting in poor reliability of monitoring data, the purpose of the present invention is to provide a method, device and system for intelligent monitoring of marine environmental data. The technical solutions adopted are as follows:

[0005] The present invention proposes a method for intelligent monitoring of marine environmental data, the method comprising:

[0006] The conductivity of each acquisition process of an ocean buoy including a two-electrode salinity sensor at different positions is acquired in time sequence to form a steady-state conductivity distribution diagram corresponding to the acquisition process;

[0007] For any acquisition process, multiple contour step areas are obtained according to the distribution characteristics of conductivity in the steady-state conductivity distribution map; the skeleton fitting curve of each contour step area is obtained, and the abnormal performance of each fitting point on each skeleton fitting curve is obtained according to the conductivity distribution of each fitting point between different adjacent skeleton fitting curves; according to the abnormal performance of each fitting point on each skeleton fitting curve, the abnormal ocean buoys in the corresponding contour step area are screened out, and the abnormal ocean buoys under all acquisition processes are obtained;

[0008] According to the difference in conductivity change of each abnormal ocean buoy in the corresponding acquisition process before and after the alternating electrode potential, the service damage index of each abnormal ocean buoy is obtained;

[0009] According to the service damage index of each abnormal ocean buoy, the damaged buoy is screened out; the salinity sensor of the damaged buoy is replaced with a normal salinity sensor to carry out intelligent monitoring of the marine environment.

[0010] Furthermore, the method for obtaining the equal-height step area includes:

[0011] The steady-state conductivity distribution map is divided into contour lines to obtain a plurality of contour step regions of the steady-state conductivity distribution map.

[0012] Furthermore, the method for obtaining the abnormal performance includes:

[0013] For any skeleton fitting curve, the fitting points where the perpendicular lines of each fitting point intersect with the adjacent skeleton fitting curves on both sides are used as the comparison fitting points of each fitting point;

[0014] If the conductivity of each fitting point and the comparative fitting point increases or decreases in sequence according to the distribution order, the abnormality judgment parameter is set to a preset first parameter, otherwise it is set to a preset second parameter, and the preset second parameter is greater than the preset first parameter;

[0015] Obtaining the mean difference of conductivity between each fitting point and all comparison fitting points as the first difference; calculating the difference between the first difference corresponding to each fitting point and the mean of the first differences of all fitting points as the second difference;

[0016] According to the abnormal judgment parameter and the second difference, the abnormal expressivity of each fitting point on each skeleton fitting curve is obtained, the abnormal judgment parameter is positively correlated with the abnormal expressivity, and the second difference is negatively correlated with the abnormal expressivity.

[0017] Furthermore, the method for obtaining the abnormal ocean buoy includes:

[0018] If the abnormal expression of each fitting point on each skeleton fitting curve is greater than the preset abnormal threshold, the corresponding fitting point is regarded as a fitting abnormal point;

[0019] All ocean buoys within the neighborhood of the fitted outlier point are obtained as outlier ocean buoys.

[0020] Furthermore, the method for obtaining the service damage index includes:

[0021] According to the difference in conductivity change of each abnormal ocean buoy in the corresponding acquisition process before and after the alternating electrode potential, the matching steady-state moment corresponding to each abnormal ocean buoy is obtained, and the degree of interference anomaly change of each abnormal ocean buoy is obtained;

[0022] The service damage index of each abnormal ocean buoy is obtained according to the conductivity difference of each abnormal ocean buoy at the corresponding matching steady-state moment before and after the alternating electrode potential, as well as the degree of interference anomaly change.

[0023] Furthermore, the obtaining of the matching steady-state moment corresponding to each abnormal ocean buoy and the degree of abnormal interference change of each abnormal ocean buoy includes:

[0024] Obtain the conductivity time series curve of each abnormal ocean buoy before and after the alternating electrode potential, and obtain the curve integral difference between the corresponding conductivity time series curves at each moment;

[0025] If the curve integral difference between each moment and the next moment is the same, or the slope of the conductivity time series curve after alternating the electrode potential at the corresponding moment is 0, the corresponding moment is taken as the matching steady-state moment, and the curve integral difference at the corresponding moment is taken as the degree of abnormal interference change.

[0026] Furthermore, the method for obtaining the service damage index includes:

[0027] Obtain the conductivity difference of each abnormal ocean buoy at the corresponding steady-state moment before and after the alternating electrode potential;

[0028] The product of the abnormal disturbance change degree and the corresponding conductivity difference of each abnormal ocean buoy is calculated, and normalized mapping is performed to obtain the service damage index of each abnormal ocean buoy.

[0029] Furthermore, the method for obtaining the damaged buoy includes:

[0030] If the service damage index of the abnormal ocean buoy is greater than the preset damage threshold, the corresponding abnormal ocean buoy is regarded as a damaged buoy.

[0031] The present invention also proposes an intelligent monitoring device for marine environment data, including a data acquisition module, an abnormal marine buoy screening module, a service damage index calculation module, and a damaged buoy screening module:

[0032] Data acquisition module: acquires the conductivity of each acquisition process of an ocean buoy containing a two-electrode salinity sensor at different positions in a time sequence to form a steady-state conductivity distribution map of the corresponding acquisition process;

[0033] Abnormal ocean buoy screening module: For any acquisition process, multiple contour step areas are obtained according to the distribution characteristics of conductivity in the steady-state conductivity distribution map; the skeleton fitting curve of each contour step area is obtained, and the abnormal performance of each fitting point on each skeleton fitting curve is obtained according to the conductivity distribution of each fitting point between different adjacent skeleton fitting curves; according to the abnormal performance of each fitting point on each skeleton fitting curve, the abnormal ocean buoys in the corresponding contour step area are screened out, and the abnormal ocean buoys under all acquisition processes are obtained;

[0034] Service damage index calculation module: according to the difference in conductivity change of each abnormal ocean buoy in the corresponding acquisition process before and after the alternating electrode potential, the service damage index of each abnormal ocean buoy is obtained;

[0035] Damaged buoy screening and environmental monitoring module: screen out damaged buoys according to the service damage index of each abnormal ocean buoy; replace the salinity sensor of the damaged buoy with a normal salinity sensor to conduct intelligent monitoring of the marine environment.

[0036] The present invention also proposes a marine environment data intelligent monitoring system, wherein the system stores programs or instructions, and when the programs or instructions are executed by a processor, the steps of the marine environment data intelligent monitoring method described above are implemented.

[0037] The present invention has the following beneficial effects:

[0038] The present invention takes into account that the distribution of conductivity usually presents a certain degree of hierarchy and steps. For any acquisition process, a plurality of contour step regions are obtained according to the distribution characteristics of conductivity in a steady-state conductivity distribution diagram, which is helpful to classify regions with similar conductivity into one category. In order to more clearly and concisely express the shape and characteristics of the contour step regions and improve the efficiency of data processing, a skeleton fitting curve of each contour step region is obtained, and the abnormal performance of each fitting point on each skeleton fitting curve is obtained according to the conductivity distribution of each fitting point between different adjacent skeleton fitting curves, which is helpful to identify the abnormal points that may exist on each skeleton fitting curve. According to the abnormal performance of each fitting point on each skeleton fitting curve, the abnormal ocean buoys in the corresponding contour step region are screened out, and the abnormal ocean buoys under all acquisition processes are obtained, which is helpful to timely discover and deal with the abnormal conditions of the buoys. According to the difference in conductivity change of each abnormal ocean buoy in the corresponding acquisition process before and after the alternating electrode potential, the service damage index of each abnormal ocean buoy is obtained, which can more accurately evaluate the damage of the buoy. The damaged buoys are screened out to ensure the normal operation of the ocean monitoring system and improve the accuracy and reliability of the monitoring data. The present invention analyzes the service loss of each ocean buoy, accurately screens out abnormal buoys for monitoring, and improves the reliability of marine environment monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 A flow chart of a method for intelligent monitoring of marine environmental data provided by one embodiment of the present invention;

[0041] Figure 2 A flow chart of a method for obtaining abnormal performance provided by an embodiment of the present invention;

[0042] Figure 3 The present invention provides a structural block diagram of an intelligent marine environment data monitoring device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the method, device and system for intelligent monitoring of marine environmental data proposed by the present invention, its specific implementation, structure, features and effects in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0044] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0045] The specific scheme of a method, device and system for intelligent monitoring of marine environment data provided by the present invention is described in detail below with reference to the accompanying drawings.

[0046] See also Figure 1 , which shows a flow chart of a method for intelligent monitoring of marine environment data provided by an embodiment of the present invention, and the specific method includes:

[0047] Step S1: Acquire the conductivity of each acquisition process of an ocean buoy including a two-electrode salinity sensor at different positions in a time sequence to form a steady-state conductivity distribution diagram of the corresponding acquisition process.

[0048] In the embodiment of the present invention, salinity is one of the most important physical and chemical properties of seawater, which directly reflects the changes in the marine environment. By ensuring accurate monitoring of salinity, the health of the marine environment can be understood. In order to avoid the reaction between the electrode and the seawater, the corrosion phenomenon affects the monitoring of the data, it is necessary to analyze the conductivity change corresponding to the electrode; first, the ocean buoys are placed at different locations such as the two sides of the channel, the river estuary and the area near the island, and fixed by anchoring, and the OSA-54 salinity sensor is installed at the measurement position of the ocean buoy. The salinity sensor includes two electrodes, an excitation electrode outputting an AC excitation signal and a measuring electrode receiving an excitation signal, which are placed in a conductivity cell to form a stable electric field between the electrodes through the flow of seawater, and the conductivity of the ocean buoy containing the two-electrode salinity sensor at different positions of each acquisition process is obtained according to the time sequence, forming a steady-state conductivity distribution diagram of the corresponding acquisition process. Among them, the horizontal and vertical axes of the steady-state conductivity distribution diagram correspond to the longitude and latitude of the location of the ocean buoy, and the steady-state conductivity represents the stable value corresponding to the conductivity not changing with time.

[0049] It should be noted that, in the embodiments of the present invention, the potential difference and the corresponding current after the electric field is energized are obtained to obtain the seawater resistance, the conductivity cell constant is obtained according to the electrode spacing, electrode size, electrode material and temperature, and the ratio of the battery panel constant and the seawater resistance is calculated as the conductivity; in order to avoid the measurement error caused by unstable potential and reflect the true potential difference between the electrodes, the steady-state conductivity of the acquisition process is analyzed.

[0050] It should be noted that, in one embodiment of the present invention, each acquisition process is a process from power-on to reaching a steady-state time, and the time interval between the acquisition processes is 1 hour. In other embodiments of the present invention, the size of the timing interval can be set according to the specific situation, which is not limited or elaborated here.

[0051] Step S2: For any acquisition process, a plurality of contour step areas are obtained according to the distribution characteristics of conductivity in the steady-state conductivity distribution map; a skeleton fitting curve of each contour step area is obtained, and the abnormal performance of each fitting point on each skeleton fitting curve is obtained according to the conductivity distribution of each fitting point between different adjacent skeleton fitting curves; according to the abnormal performance of each fitting point on each skeleton fitting curve, the abnormal ocean buoys in the corresponding contour step area are screened out, and the abnormal ocean buoys under all acquisition processes are obtained.

[0052] In the marine environment, different salinities show regional characteristics. The salinity components in different regions will change with the change of location, and the salinity levels between different salinity regions show obvious step divisions, which will directly affect the conductivity of the ocean and also show step characteristics. Therefore, for any acquisition process, multiple equal-height step areas are obtained according to the distribution characteristics of conductivity in the steady-state conductivity distribution map.

[0053] Preferably, in one embodiment of the present invention, the method for obtaining equal-height step regions includes:

[0054] The steady-state conductivity distribution map is divided into contour lines to obtain a plurality of contour step regions of the steady-state conductivity distribution map.

[0055] It should be noted that the steady-state conductivity distribution map can intuitively display the continuous change of conductivity in different regions by dividing it into contour lines, and classify similar conductivity into one region. The density, shape and value range of the contour lines can reflect the gradient distribution of conductivity. The specific contour line division is a technical means well known to those skilled in the art, and will not be elaborated here.

[0056] The contour step region may have complex shapes and boundaries. It may be difficult to directly process these complex shapes. The skeleton fitting curve can simplify the complex shape into a curve, thereby reducing the difficulty of subsequent processing and facilitating feature extraction and comparison to obtain the skeleton fitting curve of each contour step region.

[0057] It should be noted that, in one embodiment of the present invention, the method for obtaining the skeleton fitting curve includes: obtaining the skeleton of each contour step area based on a morphological skeleton algorithm, fitting the conductivity of the corresponding position of the skeleton, and obtaining the skeleton fitting curve of each contour step area. In the embodiment of the present invention, the existing fitting methods such as least squares fitting and Hough transform can be used for fitting to obtain the skeleton fitting curve. The specific morphological skeleton algorithm, least squares fitting and Hough transform algorithm are technical means well known to those skilled in the art and will not be elaborated here.

[0058] The distribution of conductivity can reflect the relative differences and changing trends between fitting points. By comparing the conductivity distribution of each fitting point between different adjacent skeleton fitting curves, the overall changing trend between the fitting points can be understood. The greater the changing trend, the greater the abnormal expression. Therefore, according to the conductivity distribution of each fitting point between different adjacent skeleton fitting curves, the abnormal expression of each fitting point on each skeleton fitting curve is obtained.

[0059] Preferably, in one embodiment of the present invention, the method for obtaining abnormal performance is as follows Figure 2 , which shows a flow chart of a method for obtaining abnormal performance, including:

[0060] Step S201: For any skeleton fitting curve, the fitting points corresponding to the intersections of the perpendicular lines of each fitting point and the adjacent skeleton fitting curves on both sides are used as comparison fitting points of each fitting point.

[0061] Since the conductivity of a normal buoy is distributed in a step-like manner and changes gradually, if the salinity sensor of the ocean buoy is abnormal, the change trend of the corresponding conductivity will change. Therefore, obtaining the comparison fitting points of each fitting point for comparative analysis will help reflect the conductivity change trend.

[0062] Step S202: If the conductivity of each fitting point and the comparison fitting point increases or decreases in the distribution order, the abnormality judgment parameter is set to the preset first parameter, otherwise it is set to the preset second parameter, and the preset second parameter is greater than the preset first parameter.

[0063] Since the conductivity in adjacent equal-height step areas is distributed in a stepped manner, by analyzing whether the conductivity distribution order of each fitting point and the comparison fitting point increases or decreases in sequence, the abnormal change corresponding to each fitting point is reflected. The more inconsistent the change trend of the conductivity value is, the more the step distribution is destroyed, and the greater the possibility of abnormality. Therefore, the preset second parameter is set to be greater than the preset first parameter.

[0064] It should be noted that, in one embodiment of the present invention, the preset first parameter is 0.5, and the preset second parameter is 1; in other embodiments of the present invention, the sizes of the preset first parameter and the preset second parameter can be set according to specific circumstances, and are not limited or elaborated here.

[0065] Step S203: obtaining the mean difference of the conductivity between each fitting point and all the comparison fitting points as the first difference; calculating the difference between the first difference corresponding to each fitting point and the mean of the first differences of all the fitting points as the second difference.

[0066] The mean difference in conductivity between each fitting point and all adjacent fitting points reflects the change in conductivity between adjacent fitting points. The larger the mean difference, the greater the difference in conductivity between each fitting point and each adjacent fitting point, and the more likely anomalies are to occur. The differences in all fitting points are quantified by the mean method, reflecting the general level of difference changes. Each subsequent fitting point is compared to reflect the difference in each fitting point relative to the overall conductivity change. The larger the difference, the more it deviates from the general level of change, and the more likely anomalies are to occur.

[0067] Step S204: according to the abnormal judgment parameter and the second difference, the abnormal expressivity of each fitting point on each skeleton fitting curve is obtained, the abnormal judgment parameter is positively correlated with the abnormal expressivity, and the second difference is negatively correlated with the abnormal expressivity.

[0068] Among them, the positive correlation relationship indicates that the dependent variable will increase as the independent variable increases, and the dependent variable will decrease as the independent variable decreases, that is, the larger the abnormal judgment parameter is, the more inconsistent the conductivity changes of the corresponding adjacent fitting points are, and the greater the abnormal expression is; the negative correlation relationship indicates that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases, that is, the larger the second difference is, the greater the difference between each fitting point and the adjacent fitting point is, and the greater the abnormal expression is.

[0069] In one embodiment of the present invention, a method for obtaining abnormal performance includes:

[0070] ;

[0071] in, Indicates The skeleton fitting curve of the equal height step area The abnormal performance of the fitting points; Indicates The skeleton fitting curve of the equal height step area Abnormal judgment parameters of fitting points; Indicates The skeleton fitting curve of the equal height step area first differences of fit points; Indicates The first difference mean of all fitting points on the skeleton fitting curve of the equal-height step area; Indicates taking the absolute value.

[0072] In the formula for abnormal performance, Indicates the calculation The skeleton fitting curve of the equal height step area The difference between the first difference of a fitting point and the mean of the first differences of all fitting points. The larger the difference, the larger the first difference of the corresponding fitting point, the larger the change in conductivity between the corresponding adjacent points, the more likely an abnormal situation is to occur, and the greater the abnormal expression.

[0073] Abnormal performance usually refers to the degree of deviation between the fitting point and the overall fitting trend. In the contour step area, if the fitting point of a buoy deviates significantly from the fitting trend of other buoys, the greater the abnormal performance, the more likely it is that the ocean buoy is abnormal. According to the abnormal performance of each fitting point on different skeleton fitting curves, the abnormal ocean buoys in the contour step area are screened out.

[0074] Preferably, in one embodiment of the present invention, the method for obtaining an abnormal ocean buoy comprises:

[0075] If the abnormal expression of each fitting point on each skeleton fitting curve is greater than the preset abnormal threshold, the corresponding fitting point is regarded as a fitting abnormal point;

[0076] All ocean buoys within the neighborhood of the fitted outlier point are obtained as outlier ocean buoys.

[0077] It should be noted that, in one embodiment of the present invention, the size of the preset abnormal threshold is 0.78. In other embodiments of the present invention, the size of the preset abnormal threshold can be set according to specific circumstances, which is not limited or elaborated here.

[0078] It should be noted that, in one embodiment of the present invention, the neighborhood range of the fitting outlier point is within any equal-height stepped area, with each fitting outlier point as the benchmark, and is divided according to the center point of the line connecting each fitting outlier point and the adjacent fitting points on both sides on the skeleton fitting line to obtain two area ranges, and the fitting outlier point and the adjacent area ranges on both sides are merged to form the neighborhood range of each fitting outlier point.

[0079] Step S3: Obtain the service damage index of each abnormal ocean buoy according to the difference in conductivity change of each abnormal ocean buoy in the corresponding collection process before and after the alternating electrode potential.

[0080] Since the salinity sensor of the ocean buoy contains two electrodes, the contact of the electrodes with seawater containing electrolytes will cause a chemical reaction. When the reaction reaches a certain level, the voltage and current emitted by the electrodes will be disturbed, resulting in corrosion anomalies, which will cause interference anomalies in the detected conductivity. For interference anomalies, the potential of the alternating electrodes can be solved to increase the life of the electrodes. However, if the number of alternations is large, as the service time of the buoy in the marine environment increases, the electrodes will be severely corroded, and there will still be large interference anomalies after alternation. Therefore, by analyzing the difference in conductivity changes before and after the alternating electrode potential of each abnormal ocean buoy, the abnormal degree of electrode interference is reflected, and the damage of the corresponding ocean buoy is evaluated. According to the difference in conductivity changes of each abnormal ocean buoy in the corresponding acquisition process before and after the alternating electrode potential, the service damage index of each abnormal ocean buoy is obtained.

[0081] Preferably, in one embodiment of the present invention, the method for obtaining the service damage index includes:

[0082] According to the difference in conductivity change of each abnormal ocean buoy in the corresponding acquisition process before and after the alternating electrode potential, the matching steady-state moment corresponding to each abnormal ocean buoy is obtained, and the degree of interference anomaly change of each abnormal ocean buoy is obtained;

[0083] The service damage index of each abnormal ocean buoy is obtained according to the conductivity difference of each abnormal ocean buoy at the corresponding matching steady-state moment before and after the alternating electrode potential, as well as the degree of interference anomaly change.

[0084] Alternating electrode potential refers to the process of changing the electric field around the buoy by alternating the potential of the electrode, which can stimulate the redistribution of the charge inside the buoy, thereby affecting its conductivity. If there is no interference anomaly and corrosion anomaly in the electrode, the change process of the conductivity time series curve before and after the alternating potential is the same. If there is interference anomaly but no corrosion anomaly in the electrode, the conductivity before and after the alternating potential increases slowly, and the conductivity steady state is the same. If there is interference anomaly and corrosion anomaly in the electrode, there is a large difference in conductivity before and after the alternating potential, and the steady-state time changes greatly. By analyzing the difference in conductivity change and determining the matching steady-state moment, it is helpful to analyze the state of conductivity change before and after the alternating electrode potential, and analyze the degree of interference anomaly change of the ocean buoy. The greater the difference in conductivity change at the corresponding matching steady-state moment, the greater the degree of interference anomaly change.

[0085] According to the difference in conductivity change of each abnormal ocean buoy in the corresponding acquisition process before and after the alternating electrode potential, the matching steady-state moment corresponding to each abnormal ocean buoy is obtained, and the degree of interference anomaly change of each abnormal ocean buoy is obtained.

[0086] Preferably, in one embodiment of the present invention, obtaining the matching steady-state moment corresponding to each abnormal ocean buoy and obtaining the degree of abnormal interference change of each abnormal ocean buoy includes:

[0087] Obtain the conductivity time series curve of each abnormal ocean buoy before and after the alternating electrode potential, and obtain the curve integral difference between the corresponding conductivity time series curves at each moment;

[0088] If the curve integral difference between each moment and the next moment is the same, or the slope of the conductivity time series curve after the alternating electrode potential at the corresponding moment is 0, the corresponding moment is taken as the matching steady-state moment, and the curve integral difference at the corresponding moment is taken as the degree of abnormal interference change. At the matching steady-state moment, the conductivity time series curve before and after the alternating electrode potential does not rise, and the area difference no longer changes, and the slope no longer changes. The corresponding conductivity difference can reflect the abnormal situation caused by the interference.

[0089] The service damage index of each abnormal ocean buoy is obtained according to the conductivity difference of each abnormal ocean buoy at the corresponding matching steady-state moment before and after the alternating electrode potential, as well as the degree of interference anomaly change.

[0090] Preferably, in one embodiment of the present invention, the method for obtaining the service damage index includes:

[0091] The conductivity difference of each abnormal ocean buoy at the corresponding steady-state moment before and after the alternating electrode potential is obtained; the product of the abnormal interference change degree and the corresponding conductivity difference of each abnormal ocean buoy is calculated, and normalized mapping is performed to obtain the service damage index of each abnormal ocean buoy.

[0092] In one embodiment of the present invention, the formula of the service damage index is expressed as:

[0093] ;

[0094] in, Indicates In-service damage index of abnormal ocean buoys; Indicates The degree of abnormal change of interference from abnormal ocean buoys; Indicates An abnormal ocean buoy at a steady state moment conductivity before the lower alternating electrode potential; Indicates An abnormal ocean buoy at a steady state moment conductivity after alternating electrode potential; represents the logistic function.

[0095] In the formula for the service damage index, Indicates the calculation An abnormal ocean buoy at a steady state moment The difference in conductivity before and after the alternating electrode potential is greater, the more inconsistent the conductivity before and after the alternating electrode potential at the steady state moment is, and the greater the service damage index.

[0096] Step S4: Screen out damaged buoys according to the service damage index of each abnormal ocean buoy; replace the salinity sensor of the damaged buoy with a normal salinity sensor to conduct intelligent monitoring of the ocean environment.

[0097] The service damage index can be used to assess the overall damage degree of ocean buoys. By screening out damaged buoys through the service damage index, these buoys can be discovered and repaired or replaced in a timely manner to ensure the accuracy and reliability of the data. The damaged buoys are screened out based on the service damage index of each abnormal ocean buoy.

[0098] Preferably, in a real-time example of the present invention, the method for obtaining a damaged buoy includes:

[0099] If the service damage index of the abnormal ocean buoy is greater than the preset damage threshold, the corresponding abnormal ocean buoy is regarded as a damaged buoy.

[0100] It should be noted that, in one embodiment of the present invention, the preset damage threshold is 0.7. In other embodiments of the present invention, the size of the preset damage threshold is a technical means well known to those skilled in the art and is not limited or elaborated herein.

[0101] After obtaining the damaged buoy, replacing the salinity sensor corresponding to the damaged buoy will help ensure that the ocean buoy can stably provide accurate marine environmental data during long-term monitoring and meet various monitoring needs.

[0102] In summary, the present invention obtains the skeleton fitting curve of each contour step area, obtains the abnormal performance of each fitting point on each skeleton fitting curve according to the conductivity distribution of each fitting point between different adjacent skeleton fitting curves; screens out the abnormal ocean buoys in the corresponding contour step area according to the abnormal performance of each fitting point on each skeleton fitting curve, and obtains the abnormal ocean buoys under all acquisition processes; obtains the service damage index of each abnormal ocean buoy according to the difference in conductivity change of each abnormal ocean buoy in the corresponding acquisition process before and after the alternating electrode potential; and screens out the damaged buoys. The present invention analyzes the service loss of each ocean buoy, accurately screens out the abnormal buoys for monitoring, and improves the reliability of marine environment monitoring.

[0103] Based on the same application concept as the method for intelligent monitoring of marine environment data provided in the embodiment of the present application, the present embodiment also proposes an intelligent monitoring device for marine environment data, such as Figure 3 As shown, the device includes: a data acquisition module 301, an abnormal ocean buoy screening module 302, a service damage index calculation module 303 and a damaged buoy screening and environment monitoring module 304:

[0104] Data acquisition module 301: acquiring the conductivity of each acquisition process of an ocean buoy including a two-electrode salinity sensor at different positions in a time sequence to form a steady-state conductivity distribution diagram corresponding to the acquisition process;

[0105] Abnormal ocean buoy screening module 302: for any acquisition process, a plurality of contour step regions are obtained according to the distribution characteristics of the conductivity in the steady-state conductivity distribution map; a skeleton fitting curve of each contour step region is obtained, and the abnormal performance of each fitting point on each skeleton fitting curve is obtained according to the conductivity distribution of each fitting point between different adjacent skeleton fitting curves; the abnormal ocean buoys in the corresponding contour step region are screened out according to the abnormal performance of each fitting point on each skeleton fitting curve, and the abnormal ocean buoys under all acquisition processes are obtained;

[0106] The service damage index calculation module 303 is used to obtain the service damage index of each abnormal ocean buoy according to the difference in conductivity change of each abnormal ocean buoy in the corresponding acquisition process before and after the alternating electrode potential.

[0107] Damaged buoy screening and environment monitoring module 304: Screen out damaged buoys according to the service damage index of each abnormal ocean buoy; replace the salinity sensor of the damaged buoy with a normal salinity sensor to conduct intelligent monitoring of the ocean environment.

[0108] It should be understood that the marine environment data intelligent monitoring device provided in this embodiment is used to execute the above-mentioned marine environment data intelligent monitoring method, and therefore has the same beneficial effects as the method adopted, run or implemented by the application program stored therein.

[0109] The present invention also provides a marine environment data intelligent monitoring system, wherein the system stores programs or instructions, and when the programs or instructions are executed by a processor, the steps of the above-mentioned marine environment data intelligent monitoring method are implemented.

[0110] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0111] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for intelligent monitoring of marine environment data, characterized in that: The method comprises: The conductivity of each acquisition process of an ocean buoy including a two-electrode salinity sensor at different positions is acquired in time sequence to form a steady-state conductivity distribution diagram corresponding to the acquisition process; For any acquisition process, multiple contour step areas are obtained according to the distribution characteristics of conductivity in the steady-state conductivity distribution map; the skeleton fitting curve of each contour step area is obtained, and the abnormal performance of each fitting point on each skeleton fitting curve is obtained according to the conductivity distribution of each fitting point between different adjacent skeleton fitting curves; according to the abnormal performance of each fitting point on each skeleton fitting curve, the abnormal ocean buoys in the corresponding contour step area are screened out, and the abnormal ocean buoys under all acquisition processes are obtained; According to the difference in conductivity change of each abnormal ocean buoy in the corresponding acquisition process before and after the alternating electrode potential, the service damage index of each abnormal ocean buoy is obtained; According to the service damage index of each abnormal ocean buoy, the damaged buoy is screened out; the salinity sensor of the damaged buoy is replaced with a normal salinity sensor to carry out intelligent monitoring of the marine environment.

2. The method for intelligent monitoring of marine environment data according to claim 1, characterized in that: The method for obtaining the equal-height step area comprises: The steady-state conductivity distribution map is divided into contour lines to obtain a plurality of contour step regions of the steady-state conductivity distribution map.

3. The method for intelligent monitoring of marine environment data according to claim 1, characterized in that: The method for obtaining the abnormal performance includes: For any skeleton fitting curve, the fitting points where the perpendicular lines of each fitting point intersect with the adjacent skeleton fitting curves on both sides are used as the comparison fitting points of each fitting point; If the conductivity of each fitting point and the comparative fitting point increases or decreases in sequence according to the distribution order, the abnormality judgment parameter is set to a preset first parameter, otherwise it is set to a preset second parameter, and the preset second parameter is greater than the preset first parameter; Obtaining the mean difference of conductivity between each fitting point and all comparison fitting points as the first difference; calculating the difference between the first difference corresponding to each fitting point and the mean of the first differences of all fitting points as the second difference; According to the abnormal judgment parameter and the second difference, the abnormal expressivity of each fitting point on each skeleton fitting curve is obtained, the abnormal judgment parameter is positively correlated with the abnormal expressivity, and the second difference is negatively correlated with the abnormal expressivity.

4. The method for intelligent monitoring of marine environment data according to claim 1, characterized in that: The method for obtaining the abnormal ocean buoy comprises: If the abnormal expression of each fitting point on each skeleton fitting curve is greater than the preset abnormal threshold, the corresponding fitting point is regarded as a fitting abnormal point; All ocean buoys within the neighborhood of the fitted outlier point are obtained as outlier ocean buoys.

5. The method for intelligent monitoring of marine environment data according to claim 1, characterized in that: The method for obtaining the service damage index includes: According to the difference in conductivity change of each abnormal ocean buoy in the corresponding acquisition process before and after the alternating electrode potential, the matching steady-state moment corresponding to each abnormal ocean buoy is obtained, and the degree of interference anomaly change of each abnormal ocean buoy is obtained; The service damage index of each abnormal ocean buoy is obtained according to the conductivity difference of each abnormal ocean buoy at the corresponding matching steady-state moment before and after the alternating electrode potential, as well as the degree of interference anomaly change.

6. The method for intelligent monitoring of marine environment data according to claim 5, characterized in that: The step of obtaining the matching steady-state moment corresponding to each abnormal ocean buoy and obtaining the degree of abnormal interference change of each abnormal ocean buoy includes: Obtain the conductivity time series curve of each abnormal ocean buoy before and after the alternating electrode potential, and obtain the curve integral difference between the corresponding conductivity time series curves at each moment; If the curve integral difference between each moment and the next moment is the same, or the slope of the conductivity time series curve after alternating the electrode potential at the corresponding moment is 0, the corresponding moment is taken as the matching steady-state moment, and the curve integral difference at the corresponding moment is taken as the degree of abnormal interference change.

7. The method for intelligent monitoring of marine environment data according to claim 5, characterized in that: The method for obtaining the service damage index includes: Obtain the conductivity difference of each abnormal ocean buoy at the corresponding steady-state moment before and after the alternating electrode potential; The product of the abnormal disturbance change degree and the corresponding conductivity difference of each abnormal ocean buoy is calculated, and normalized mapping is performed to obtain the service damage index of each abnormal ocean buoy.

8. The method for intelligent monitoring of marine environment data according to claim 1, characterized in that: The method for obtaining the damaged buoy comprises: If the service damage index of the abnormal ocean buoy is greater than the preset damage threshold, the corresponding abnormal ocean buoy is regarded as a damaged buoy.

9. An intelligent monitoring device for marine environment data, characterized in that: Including data acquisition module, abnormal ocean buoy screening module, service damage index calculation module, damaged buoy screening module: Data acquisition module: acquires the conductivity of each acquisition process of an ocean buoy containing a two-electrode salinity sensor at different positions in a time sequence to form a steady-state conductivity distribution map of the corresponding acquisition process; Abnormal ocean buoy screening module: For any acquisition process, multiple contour step areas are obtained according to the distribution characteristics of conductivity in the steady-state conductivity distribution map; the skeleton fitting curve of each contour step area is obtained, and the abnormal performance of each fitting point on each skeleton fitting curve is obtained according to the conductivity distribution of each fitting point between different adjacent skeleton fitting curves; according to the abnormal performance of each fitting point on each skeleton fitting curve, the abnormal ocean buoys in the corresponding contour step area are screened out, and the abnormal ocean buoys under all acquisition processes are obtained; Service damage index calculation module: according to the difference in conductivity change of each abnormal ocean buoy in the corresponding acquisition process before and after the alternating electrode potential, the service damage index of each abnormal ocean buoy is obtained; Damaged buoy screening and environmental monitoring module: screen out damaged buoys according to the service damage index of each abnormal ocean buoy; replace the salinity sensor of the damaged buoy with a normal salinity sensor to conduct intelligent monitoring of the marine environment.

10. An intelligent monitoring system for marine environment data, characterized in that: The system stores programs or instructions, and when the programs or instructions are executed by the processor, the steps of the method for intelligent monitoring of marine environment data as described in any one of claims 1 to 8 are implemented.

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