Marine pollution survey data recording method and system based on big data

Abstract

The invention discloses a big data-based marine pollution survey data recording method and system, and relates to the technical field of data processing, and the method comprises the steps: firstly carrying out the real-time monitoring and analysis of the measurement data of a sensor in each sampling point and the storage and transportation data of a marine pollution survey sample, and correcting the measurement deviation of equipment in time; therefore, the authenticity and the stability of the data are ensured, the sensor is corrected, the sample storage environment is regulated and controlled, and the accuracy and the reliability of the data are ensured. Through combination of the data, a generated marine pollution survey data conformity characterization value is obtained, pollution data is comprehensively analyzed, regulated and controlled, the problem of data precision reduction or drifting of monitoring equipment is effectively solved, and the problem of data change caused by external pollution in the sample collection, transfer or storage process is effectively solved. And the accuracy of marine pollution survey data can be ensured, so that a reliable basis is provided for pollution abatement.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and system for recording marine pollution survey data based on big data. Background Art

[0002] Marine pollution investigation is an important task in the field of environmental protection. In recent years, with the development of big data technology, by deploying sensors and collection equipment at various monitoring points, combined with real-time data transmission, cloud storage and data analysis, it is possible to achieve comprehensive and real-time monitoring of marine pollution. It can not only improve the frequency and accuracy of data collection, but also reveal the trends and influencing factors of pollutant changes through big data analysis, providing more accurate and effective decision-making basis for marine pollution control.

[0003] The prior art, such as the invention patent with publication number: CN118312738A, discloses a marine water pollution monitoring system based on big data, wherein the monitoring system comprises: a marine water sampling module, a water pollution detection module, a pollution source tracing module and a partitioned collaborative filtering module; the marine water collection module is used to extract samples of different depths from the marine water in the region; the water pollution detection module is used to perform pollution detection on the sample data to obtain the degree of pollution of the sample data; the pollution source tracing module is used to locate the pollution source of the polluted water sample and the time when the pollution occurred; the partitioned collaborative filtering module is used to perform collaborative filtering calculations on other regions based on big data technology to find similar pollution sources and the time when the pollution occurred in other regions.

[0004] Prior art, such as the invention patent with publication number: CN116975574A, discloses a method for evaluating heavy metal pollution in the marine environment, comprising: obtaining a historical monitoring data set, establishing a distribution characteristic function of the historical monitoring data; obtaining the heavy metal content monitoring value of the marine test point and the covariance matrix of the historical monitoring data; establishing an initial joint distribution function of the marine test point and the historical data set; based on the true value of the marine pollution value of the marine test point, determining the correlation measurement value in the covariance matrix between the heavy metal content monitoring value of the marine test point and the correlation measurement value, the parameters for controlling the degree of correlation and the interference data difference, and then obtaining the final joint distribution function of the marine test point and the historical data set, so as to obtain the marine pollution value of the marine monitoring point to be evaluated and evaluate the marine environment.

[0005] At present, there are several problems in the recording of marine pollution survey data. On the one hand, the aging of monitoring instruments and equipment leads to a decrease in data accuracy or drift. On the other hand, samples may be contaminated by the outside world during collection, transfer or storage. For example, during the transportation of samples, samples may be exposed to non-target substances and environmental factors, which may affect the stability of pollutants, resulting in changes in the sampling data and affecting the authenticity of the data. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a method and system for recording marine pollution survey data based on big data, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method and system for recording marine pollution survey data based on big data, including obtaining and analyzing the measurement data of each sensor in each sampling point in the marine pollution survey data, obtaining the measurement stability compliance value of each sensor in each sampling point, and correcting the sensor at each sampling point according to the measurement stability compliance value of each sensor in each sampling point.

[0008] Preset each monitoring cycle, monitor and obtain the marine pollution investigation sample preservation and transportation data and analyze them, obtain the marine pollution investigation sample preservation and transportation compliance value in each monitoring cycle, regulate the sample preservation environment according to the marine pollution investigation sample preservation and transportation compliance value in each monitoring cycle, and save and record the marine pollution investigation sample preservation and transportation data transmission.

[0009] According to the measurement stability compliance value of each sensor in each sampling point and the storage and transportation compliance value of the marine pollution investigation samples in each monitoring period, the marine pollution investigation data compliance characterization value is obtained, and the marine pollution investigation data analysis is regulated according to the marine pollution investigation data compliance characterization value.

[0010] Furthermore, the measurement data of each sensor at each sampling point in the marine pollution survey data is obtained and analyzed to obtain the measurement stability compliance value of each sensor at each sampling point. The specific process is:

[0011] The measurement data of each sensor in each sampling point is extracted, including the usage time of each sensor, the drift rate of each sensor, the average response time of each sensor, and the current reading of each sensor. The historical average reading of each sensor stored in the large data set is extracted, and the measurement stability compliance value of each sensor in each sampling point is obtained after processing. The measurement stability compliance value of each sensor in each sampling point is used to indicate the degree of data deviation of the sensor during use.

[0012] Further, the sensor at each sampling point is corrected according to the measurement stability compliance value of each sensor at each sampling point. The specific process is: according to the measurement stability compliance value of each sensor at each sampling point, it is compared with the measurement stability compliance threshold of the sensor at each sampling point stored in the database. If the measurement stability compliance value of each sensor at each sampling point is higher than or equal to the measurement stability compliance threshold of the sensor at each sampling point, there is no need to correct the sensor at each sampling point. If the measurement stability compliance value of a sensor at a certain sampling point is lower than the measurement stability compliance threshold of the sensor at each sampling point, the reading of the sensor at each sampling point is corrected.

[0013] Furthermore, the monitoring obtains marine pollution investigation sample preservation and transportation data and performs analysis, and the specific process is: in each monitoring cycle, the concentration of sample pollutants at each sampling point at the initial monitoring time point and the concentration of sample pollutants at each sampling point at the termination monitoring time point are counted, and the concentration of sample pollutants at each sampling point at the initial monitoring time point and the concentration of sample pollutants at each sampling point at the termination monitoring time point are differenced to obtain the concentration change of sample pollutants in each monitoring cycle.

[0014] The sample storage temperature was extracted in each monitoring period, and the sample storage and transportation data of each sampling point were extracted, including pH value and sample decomposition rate.

[0015] Furthermore, the marine pollution investigation sample preservation and transportation compliance values ​​in each monitoring period are obtained by extracting the concentration changes of sample pollutants and sample preservation temperature in each monitoring period, and extracting the pH value and sample decomposition rate, and obtaining the marine pollution investigation sample preservation and transportation compliance values ​​in each monitoring period after processing. The marine pollution investigation sample preservation and transportation compliance values ​​in each monitoring period are used to evaluate the degree to which the transportation and preservation of samples comply with the standards.

[0016] Furthermore, the sample storage environment is regulated according to the marine pollution investigation sample storage and transportation compliance value in each monitoring period, and the marine pollution investigation sample storage and transportation data transmission is stored and recorded. The specific process is: according to the marine pollution investigation sample storage and transportation compliance value in each monitoring period, and compared with the marine pollution investigation sample storage and transportation compliance threshold stored in the database, if the marine pollution investigation sample storage and transportation compliance value in a certain monitoring period is higher than or equal to the marine pollution investigation sample storage and transportation compliance threshold, there is no need to regulate the sample storage environment; if the marine pollution investigation sample storage and transportation compliance value in a certain monitoring period is lower than the marine pollution investigation sample storage and transportation compliance threshold, the sample storage environment in the monitoring period is regulated, and the marine pollution investigation sample storage and transportation data transmission is stored and recorded.

[0017] Furthermore, the marine pollution survey data obtained conforms to the characterization value, and the specific process is as follows:

[0018] The sampling frequency, abnormal value ratio and transportation time of each sampling point in the marine pollution investigation data are obtained in each monitoring cycle, and the number of sensor corrections at each sampling point and the number of sample storage environment adjustments are counted. The marine pollution investigation data conformity characterization value is obtained after processing. The marine pollution investigation data conformity characterization value is used to reflect the overall conformity of the data.

[0019] Furthermore, the marine pollution survey data analysis is regulated according to the marine pollution survey data conforming to the characterization value. The specific process is: the marine pollution survey data conforming to the characterization value is compared with the set marine pollution survey data conforming to the characterization threshold. If the marine pollution survey data conforming to the characterization value is higher than or equal to the marine pollution survey data conforming to the characterization threshold, there is no need to regulate the marine pollution survey data analysis. If the marine pollution survey data conforming to the characterization value is lower than the marine pollution survey data conforming to the characterization threshold, the marine pollution survey data analysis is regulated.

[0020] Furthermore, the marine pollution survey data meets the characterization value, and the specific analysis conditions are:

[0021]

[0022] In the formula, S means that the marine pollution survey data meets the characterization value, c k→i represents the sampling frequency of the i-th sampling point in the K-th monitoring cycle, Z k→i represents the proportion of outliers at the i-th sampling point in the K-th monitoring cycle, t1 represents the transportation time of the marine pollution survey sample, XZ k→i represents the number of sensor corrections at the i-th sampling point in the K-th monitoring cycle, TK k represents the number of sample storage environment control times in the Kth monitoring cycle, Δc represents the reference sampling frequency of the set sampling point, ΔZ represents the defined abnormal value ratio of the set sampling point, ΔXZ represents the defined correction number of the set sensor, Δt represents the reference transportation time of the set ocean pollution investigation sample, ΔTK represents the defined control number of the set sample storage environment, μ1 represents the correction factor corresponding to the set sampling frequency, μ2 represents the correction factor corresponding to the set abnormal value ratio, μ3 represents the correction factor corresponding to the set transportation time, μ4 represents the correction factor corresponding to the set sensor correction number, μ5 represents the correction factor corresponding to the set sample storage environment control number, k represents the number of each monitoring cycle, k=1,2,3,...,h, h represents the total number of monitoring cycles, i represents the number of each sampling point, i=1,2,3,,,m, m represents the total number of sampling points.

[0023] The second aspect of the present invention also provides a recording system for marine pollution survey data based on big data, including: a sampling point analysis module, which is used to obtain and analyze the measurement data of each sensor in each sampling point in the marine pollution survey data, obtain the measurement stability compliance value of each sensor in each sampling point, and correct the sensor at each sampling point according to the measurement stability compliance value of each sensor in each sampling point.

[0024] The sample preservation and transportation data analysis module is used to preset each monitoring period, monitor and obtain the marine pollution investigation sample preservation and transportation data and analyze it, obtain the marine pollution investigation sample preservation and transportation compliance value in each monitoring period, regulate the sample preservation environment according to the marine pollution investigation sample preservation and transportation compliance value in each monitoring period, and transmit the marine pollution investigation sample preservation and transportation data for preservation and record.

[0025] The control module is used to obtain the marine pollution survey data compliance characterization value according to the measurement stability compliance value of each sensor in each sampling point and the marine pollution survey sample storage and transportation compliance value in each monitoring period, and to regulate the marine pollution survey data analysis according to the marine pollution survey data compliance characterization value.

[0026] The present invention has the following beneficial effects:

[0027] (1) The present invention provides a method and system for recording marine pollution survey data based on big data. First, the measurement data of sensors at each sampling point and the storage and transportation data of marine pollution survey samples are monitored and analyzed in real time, and the measurement deviation of the equipment is corrected in time to ensure the authenticity and stability of the data, and the measurement stability compliance value and the sample storage and transportation compliance value are obtained, and then the sensor is corrected and the sample storage environment is regulated, which helps to ensure the accuracy and reliability of the data. And by combining these data, the marine pollution survey data compliance characterization value is obtained, and the pollution data is comprehensively analyzed and regulated, which effectively solves the problem of data accuracy reduction or drift of the monitoring equipment, and the data change problem caused by external pollution during sample collection, transfer or storage, which helps to ensure the accuracy of marine pollution survey data, thereby providing a reliable basis for pollution control.

[0028] (2) The present invention helps to correct the sensor data by obtaining the measurement stability compliance value of each sensor at each sampling point, thereby ensuring the accuracy and reliability of the data, and can promptly correct measurement errors caused by equipment aging or other factors, ensuring the authenticity and stability of the monitoring data, and can effectively solve errors caused by sensor deviation or data drift, improve data reliability, and provide a more accurate and reliable basis for pollution control.

[0029] (3) The present invention helps the system to automatically adjust the storage environment of samples by obtaining the storage and transportation compliance values ​​of marine pollution survey samples, thereby ensuring sample quality, effectively identifying and correcting changes in pollutant concentrations caused by non-compliance with transportation or storage environments, thereby improving data accuracy and reliability, helping to ensure the authenticity of marine pollution survey data, and providing more accurate and effective decision-making support for subsequent pollution control.

[0030] (4) The present invention helps to analyze and regulate the marine pollution survey data by deriving the compliance characterization value of the marine pollution survey data, thereby effectively ensuring the quality and accuracy of the data. Through real-time monitoring and automatic adjustment, it can effectively identify and correct possible data problems, improve the reliability of the data, and provide a more accurate decision-making basis for marine pollution control.

[0031] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic diagram of the method flow of the present invention;

[0033] Figure 2 It is a schematic diagram of the system module of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] In the description of the present invention, it should be understood that the terms "opening", "upper", "lower", "thickness", "top", "middle", "length", "inside", "all around" and the like indicating orientation or positional relationship are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the components or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0036] See also Figure 1 As shown, an embodiment of the present invention provides a method and system technical solution for recording marine pollution survey data based on big data: a method and system for recording marine pollution survey data based on big data, including obtaining and analyzing the measurement data of each sensor in each sampling point in the marine pollution survey data, obtaining the measurement stability compliance value of each sensor in each sampling point, and correcting the sensor at each sampling point according to the measurement stability compliance value of each sensor in each sampling point.

[0037] Preset each monitoring cycle, monitor and obtain the marine pollution investigation sample preservation and transportation data and analyze them, obtain the marine pollution investigation sample preservation and transportation compliance value in each monitoring cycle, regulate the sample preservation environment according to the marine pollution investigation sample preservation and transportation compliance value in each monitoring cycle, and save and record the marine pollution investigation sample preservation and transportation data transmission.

[0038] According to the measurement stability compliance value of each sensor in each sampling point and the storage and transportation compliance value of the marine pollution investigation samples in each monitoring period, the marine pollution investigation data compliance characterization value is obtained, and the marine pollution investigation data analysis is regulated according to the marine pollution investigation data compliance characterization value.

[0039] Specifically, the measurement data of each sensor in each sampling point in the marine pollution survey data is obtained and analyzed to obtain the measurement stability compliance value of each sensor in each sampling point. The specific process is: extract the measurement data of each sensor in each sampling point, including the usage time of each sensor, the drift rate of each sensor, the average response time of each sensor, and the current reading of each sensor, and extract the historical average reading of each sensor stored in the large data set, and obtain the measurement stability compliance value of each sensor in each sampling point after processing. The measurement stability compliance value of each sensor in each sampling point is used to indicate the degree of data deviation of the sensor during use.

[0040] It should be noted that the measurement stability of each sensor at each sampling point meets the value, and the analysis conditions are:

[0041]

[0042] Among them, Q i→j represents the measurement stability compliance value of the ith sampling point in the ith sampling point, W i→j represents the usage time of the jth sensor in the i-th sampling point, E i→j represents the drift rate of the jth sensor in the i-th sampling point, T i→j represents the average response time of the jth sensor in the ith sampling point, R i→ represents the current reading of the jth sensor in the i-th sampling point, represents the historical average reading of the jth sensor in the ith sampling point, ΔW represents the set defined usage time, ΔE represents the set defined drift rate, ΔT represents the set defined response time, ΔU represents the set defined data deviation coefficient, A1 represents the correction factor corresponding to the set usage time, A2 represents the correction factor corresponding to the set drift rate, A3 represents the correction factor corresponding to the set average response time, a1 represents the weight factor corresponding to the set historical average reading of the sensor, a2 represents the weight factor corresponding to the set current average reading of the sensor, i represents the number of each sampling point, i=1,2,3,,,m, m represents the total number of sampling points, j represents the number of each sensor, j=1,2,3,,,n, n represents the total number of sensors.

[0043] In a specific embodiment, the usage time, drift rate, average response time, current reading and historical average reading of each sensor do not exist in isolation, but are interdependent and closely related. First, the usage time of the sensor directly affects the change of its drift rate. As the usage time increases, the drift rate of the sensor may gradually increase, resulting in a decrease in the accuracy of the measurement data, thereby affecting the reliability of the current reading. Secondly, the average response time of the sensor is closely related to the stability of the measurement data. A longer average response time may delay the capture of data changes, thereby affecting the real-time and accuracy of the current reading, especially when the environment changes rapidly. Furthermore, the comparison between the current reading and the historical average reading provides a basis for the calculation of the measurement stability compliance value. The presence of a large deviation may indicate that the performance of the sensor is degraded or the data is abnormal, affecting the stability of the overall measurement. The stability of the historical average reading and the deviation of the current measurement data reflect whether the sensor is within its normal operating range, providing an assessment of data consistency and long-term reliability.

[0044] In a specific embodiment, the value range of the correction factor corresponding to the sensor usage time is generally between 0 and 1. When in use, the correction factor corresponding to the sensor usage time can be directly obtained from the database. The correspondence between the sensor usage time and its corresponding correction factor is determined by a pre-set mapping table. For example, by analyzing the drift rate and measurement error change trend of the sensor under different usage times, a mapping table between the sensor usage time and the correction factor is constructed. The sensor usage time value detected in real time can be input into the mapping table to quickly obtain the corresponding correction factor, thereby helping to evaluate the sensor performance and determine whether calibration or replacement is needed.

[0045] In a specific embodiment, the correction factor corresponding to the sensor drift rate generally ranges from 0 to 1. When in use, the correction factor corresponding to the sensor drift rate can be directly obtained from the database. The correspondence between the sensor drift rate and its corresponding correction factor is determined by a pre-set mapping table. For example, by analyzing the deviation amplitude of the sensor measurement data under different drift rate conditions, a mapping table between the sensor drift rate and the correction factor is constructed. The sensor drift rate value detected in real time can be input into the mapping table to quickly obtain the corresponding correction factor, which is used to compensate for the influence of drift on the measurement data or prompt the sensor to be calibrated.

[0046] In a specific embodiment, the correction factor corresponding to the average response time of the sensor generally ranges from 0 to 1. When in use, the correction factor corresponding to the average response time of the sensor can be directly obtained from the database. The correspondence between the average response time of the sensor and its corresponding correction factor is determined by a pre-set mapping table. For example, by analyzing the impact of different response times on the measurement accuracy of the sensor in a rapidly changing environment, a mapping table between the average response time of the sensor and the correction factor is constructed. The average response time value of the sensor detected in real time is input into the mapping table to quickly obtain the corresponding correction factor.

[0047] Specifically, the sensor at each sampling point is corrected according to the measurement stability compliance value of each sensor at each sampling point. The specific process is: according to the measurement stability compliance value of each sensor at each sampling point, it is compared with the measurement stability compliance threshold of the sensor at each sampling point stored in the database. If the measurement stability compliance value of each sensor at each sampling point is higher than or equal to the measurement stability compliance threshold of the sensor at each sampling point, it is not necessary to correct the sensor at each sampling point. If the measurement stability compliance value of a sensor at a certain sampling point is lower than the measurement stability compliance threshold of the sensor at each sampling point, the reading of the sensor at each sampling point is corrected.

[0048] It should be noted that the specific process of correcting the readings of the sensors at each sampling point is to perform difference processing on the measurement stability compliance threshold of the sensor at each sampling point and the measurement stability compliance value of the sensor at the sampling point to obtain the measurement stability compliance deviation value of the sensor at the sampling point, and compare it with the reading correction value of the sensor corresponding to each interval of the measurement stability compliance deviation value stored in the database to obtain the reading correction value of the sensor at the sampling point, and add the current sensor reading and the reading correction value of the sensor at the sampling point for correction.

[0049] Specifically, the marine pollution investigation sample preservation and transportation data are monitored and analyzed. The specific process is: in each monitoring cycle, the concentration of sample pollutants at each sampling point at the initial monitoring time point and the concentration of sample pollutants at each sampling point at the termination monitoring time point are counted, and the concentration of sample pollutants at each sampling point at the initial monitoring time point and the concentration of sample pollutants at each sampling point at the termination monitoring time point are differenced to obtain the concentration change of sample pollutants in each monitoring cycle.

[0050] The sample storage temperature was extracted in each monitoring period, and the sample storage and transportation data of each sampling point were extracted, including pH value and sample decomposition rate.

[0051] Specifically, the compliance value of the marine pollution survey sample storage and transportation in each monitoring period is obtained. The specific process is as follows:

[0052] The concentration changes of pollutants in the samples and the sample storage temperature in each monitoring period are extracted, and the pH value and sample decomposition rate are extracted. After processing, the marine pollution investigation sample storage and transportation compliance values ​​in each monitoring period are obtained. The marine pollution investigation sample storage and transportation compliance values ​​in each monitoring period are used to evaluate the degree to which the transportation and storage of the samples comply with the standards.

[0053] It should be noted that the storage and transportation of marine pollution survey samples in each monitoring period meet the values. The specific analysis conditions are as follows:

[0054]

[0055] Where P k It represents the compliance value of marine pollution survey sample storage and transportation in the Kth monitoring cycle, represents the concentration change of sample pollutants in the Kth monitoring cycle, represents the sample storage temperature of the sample contaminant in the Kth monitoring cycle, represents the pH value of the sample pollutant in the Kth monitoring cycle, represents the pH value of the sample pollutant in the K-1th monitoring cycle, represents the sample decomposition rate of the sample pollutant in the K-1th monitoring cycle, ΔC represents the set reference change in the concentration of the pollutant, ΔT represents the set sample reference storage temperature of the sample pollutant, ΔPH represents the set sample reference pH change value of the sample pollutant, ΔB represents the set reference sample decomposition rate, β1 represents the correction factor corresponding to the set pollutant concentration, β2 represents the correction factor corresponding to the set sample storage temperature, β represents the correction factor corresponding to the set pH value, β4 represents the correction factor corresponding to the set sample decomposition rate, k represents the number of each monitoring cycle, k=1,2,3,...,h, h represents the total number of monitoring cycles.

[0056] In a specific embodiment, the parameters such as the change in sample pollutant concentration, sample storage temperature, pH value, and sample decomposition rate in each monitoring cycle do not exist in isolation, but are interdependent and closely related. First, the change in sample pollutant concentration is directly affected by the sample storage temperature. When the sample storage temperature deviates from the optimal range (such as higher or lower than the recommended value), the pollutant may accelerate decomposition due to chemical or biological reactions, resulting in a significant change in concentration. Secondly, there is an important coupling relationship between the sample storage temperature and the pH value. The acid-base balance of the sample may be broken, resulting in fluctuations in the pH value, and the fluctuation in the pH value may further affect the sample decomposition rate. For example, a lower pH value (acidic) may accelerate the degradation of certain organic pollutants, while a higher pH value (alkaline) may promote other chemical reactions. In addition, the change in the sample decomposition rate reflects the degree of chemical or biological degradation of the sample during storage and transportation, and this degree of decomposition is closely related to the change in pollutant concentration. When the decomposition rate is high, the actual concentration of the pollutant may be significantly reduced, affecting the reliability of the measurement results.

[0057] In a specific embodiment, the correction factor corresponding to the concentration of the pollutant generally ranges from 0 to 1. When in use, the correction factor corresponding to the pollutant concentration can be directly obtained from the database. The correspondence between the pollutant concentration and its corresponding correction factor is determined by a pre-set mapping table, for example, by constructing a mapping table between the pollutant concentration and the correction factor. The real-time detected pollutant concentration value is input into the mapping table to quickly obtain the corresponding correction factor, thereby optimizing the sample analysis and preservation strategy.

[0058] In a specific embodiment, the correction factor corresponding to the sample storage temperature generally ranges from 0 to 1. When in use, the correction factor corresponding to the sample storage temperature can be directly obtained from the database. The correspondence between the sample storage temperature and its corresponding correction factor is determined by a pre-set mapping table, for example, by constructing a mapping table between the sample storage temperature and the correction factor. When the sample storage temperature is monitored in real time, the corresponding correction factor can be obtained by inputting it into the mapping table, which is used to adjust the storage conditions or correct the sample concentration measurement value.

[0059] In a specific embodiment, the correction factor corresponding to the pH value generally ranges from 0 to 1. When in use, the correction factor corresponding to the pH value can be directly obtained from the database. The correspondence between the pH value and its corresponding correction factor is determined by a pre-set mapping table. For example, by constructing a mapping table between the pH value and the correction factor. After the pH value of the sample is detected in real time, the corresponding correction factor can be quickly obtained by inputting it into the mapping table.

[0060] In a specific embodiment, the value range of the correction factor corresponding to the sample decomposition rate is usually between 0 and 1. When in use, the correction factor corresponding to the sample decomposition rate can be directly obtained from the database. The correspondence between the sample decomposition rate and its corresponding correction factor is determined by a pre-set mapping table. For example, by constructing a mapping table between the sample decomposition rate and the correction factor. The sample decomposition rate value detected in real time can be input into the mapping table to quickly obtain the corresponding correction factor to compensate for the impact of decomposition on data accuracy.

[0061] Specifically, the storage environment of the samples is regulated according to the marine pollution investigation sample storage and transportation compliance value in each monitoring period, and the marine pollution investigation sample storage and transportation data transmission is stored and recorded. The specific process is: according to the marine pollution investigation sample storage and transportation compliance value in each monitoring period, and compared with the marine pollution investigation sample storage and transportation compliance threshold stored in the database, if the marine pollution investigation sample storage and transportation compliance value in a certain monitoring period is higher than or equal to the marine pollution investigation sample storage and transportation compliance threshold, there is no need to regulate the sample storage environment; if the marine pollution investigation sample storage and transportation compliance value in a certain monitoring period is lower than the marine pollution investigation sample storage and transportation compliance threshold, then the sample storage environment in the monitoring period is regulated, and the marine pollution investigation sample storage and transportation data transmission is stored and recorded.

[0062] It should be noted that the specific process of regulating the storage environment of the samples during the monitoring period is to first obtain the sample storage temperature. If the sample storage temperature is too high or too low, a gradual approach is adopted to gradually adjust the temperature to the pre-set sample storage temperature to reduce the impact on the sample. Similarly, if the pH value needs to be regulated, a buffer solution is added to maintain the pH value of the sample within a stable range to prevent drastic fluctuations caused by environmental changes. Excessive decomposition rate is usually caused by excessive temperature, light or oxygen exposure, so a gradual approach is also required to gradually adjust the temperature to the pre-set sample storage temperature.

[0063] It should be noted that the preservation and transportation compliance values ​​of marine pollution survey samples in each monitoring cycle compress multi-dimensional data into a single indicator, which is convenient for real-time monitoring and decision-making.

[0064] Specifically, the marine pollution survey data conformity characterization value is obtained, and the specific process is: in each monitoring period, the sampling frequency, the proportion of abnormal values ​​and the transportation time of the marine pollution survey samples of each sampling point in the marine pollution survey data are obtained, and the number of sensor corrections at each sampling point and the number of sample storage environment adjustments are counted, and the marine pollution survey data conformity characterization value is obtained after processing. The marine pollution survey data conformity characterization value is used to reflect the overall conformity of the data.

[0065] Specifically, the analysis of the marine pollution survey data is regulated according to the marine pollution survey data conforming to the characterization value. The specific process is: the marine pollution survey data conforming to the characterization value is compared with the set marine pollution survey data conforming to the characterization threshold. If the marine pollution survey data conforming to the characterization value is higher than or equal to the marine pollution survey data conforming to the characterization threshold, there is no need to regulate the analysis of the marine pollution survey data. If the marine pollution survey data conforming to the characterization value is lower than the marine pollution survey data conforming to the characterization threshold, the analysis of the marine pollution survey data is regulated.

[0066] It should be noted that the specific process of regulating and controlling the analysis of marine pollution survey data is to inspect and maintain the equipment at each sampling point and strengthen the transportation control of samples. For example, once abnormal environmental conditions such as excessive temperature or excessive humidity are found, the system automatically triggers an early warning and notifies the operator to take remedial measures, such as activating backup cold chain equipment and adjusting transportation routes.

[0067] Specifically, the marine pollution survey data meets the characterization values, and the specific analysis conditions are:

[0068]

[0069] In the formula, S means that the marine pollution survey data meets the characterization value, c k→i represents the sampling frequency of the i-th sampling point in the K-th monitoring cycle, Z k→i represents the proportion of outliers at the i-th sampling point in the K-th monitoring cycle, t1 represents the transportation time of the marine pollution survey sample, XZ k→i represents the number of sensor corrections at the i-th sampling point in the K-th monitoring cycle, TK k represents the number of sample storage environment control times in the Kth monitoring cycle, Δc represents the reference sampling frequency of the set sampling point, ΔZ represents the defined abnormal value ratio of the set sampling point, ΔXZ represents the defined correction number of the set sensor, Δt represents the reference transportation time of the set ocean pollution investigation sample, ΔTK represents the defined control number of the set sample storage environment, μ1 represents the correction factor corresponding to the set sampling frequency, μ2 represents the correction factor corresponding to the set abnormal value ratio, μ3 represents the correction factor corresponding to the set transportation time, μ4 represents the correction factor corresponding to the set sensor correction number, μ5 represents the correction factor corresponding to the set sample storage environment control number, k represents the number of each monitoring cycle, k=1,2,3,...,h, h represents the total number of monitoring cycles, i represents the number of each sampling point, i=1,2,3,,,m, m represents the total number of sampling points.

[0070] In a specific embodiment, parameters such as the sampling frequency of each sampling point in each monitoring cycle, the proportion of outliers, the transportation time of marine pollution survey samples, the number of sensor corrections at each sampling point, and the number of sample storage environment regulation are not isolated, but are interdependent and closely related. First, the sampling frequency directly affects the timeliness and coverage of the data. When the sampling frequency is low, some environmental pollution change trends may not be fully captured, thereby reducing the overall credibility of the data. In addition, too low a sampling frequency may also make it difficult to stably estimate the changes in the proportion of outliers. Secondly, there is an indirect connection between the proportion of outliers and the sampling frequency. An increase in the sampling frequency may increase the sensitivity to sudden changes in a short period of time, thereby increasing the frequency of identifying outliers. At the same time, an increase in the proportion of outliers may lead to an increase in the number of sensor corrections to maintain the accuracy and consistency of the data. In addition, the transportation time of the sample is closely related to the number of storage environment regulation. Too long transportation time may aggravate the change or decomposition of sample pollutant concentration, which in turn leads to an increase in the demand for storage environment regulation. Finally, the number of sensor corrections is not only affected by the proportion of outliers, but may also increase due to the cumulative impact of transportation time on the equipment status. Therefore, the mutual influence of sampling frequency, outlier ratio and sensor correction times reflects the dynamic adjustment process of data quality, while the coupling effect of transportation time and storage environment regulation times reflects the control of external interference during sample preservation.

[0071] In a specific embodiment, the correction factor corresponding to the sampling frequency generally ranges from 0 to 1. When in use, the correction factor corresponding to the sampling frequency can be directly obtained from the database. The relationship between the sampling frequency and its corresponding correction factor is determined by a pre-set mapping table. For example, by analyzing the changes in data timeliness and integrity under different sampling frequencies, a mapping table between the sampling frequency and the correction factor is constructed. The sampling frequency value detected in real time can be input into the mapping table to quickly obtain the corresponding correction factor, thereby helping to optimize the monitoring plan and improve data reliability.

[0072] In a specific embodiment, the correction factor corresponding to the outlier ratio generally ranges from 0 to 1. When in use, the correction factor corresponding to the outlier ratio can be directly obtained from the database. The relationship between the outlier ratio and its correction factor is determined by pre-analyzing the mapping table constructed by the degree of influence of the outlier ratio on the data quality. For example, according to the degree of influence of the outlier ratio on the overall data stability, the outlier ratio can be input into the mapping table to obtain the corresponding correction factor, so as to compensate for the data quality problem during statistical analysis.

[0073] In a specific embodiment, the value range of the correction factor corresponding to the transportation time is usually between 0 and 1. The relationship between the transportation time and the correction factor is determined by a mapping table constructed by a preset sample stability model. For example, the relationship between the transportation time and the correction factor is established by experimentally analyzing the impact of the sample transportation time on the change in pollutant concentration or decomposition rate. The transportation time data obtained in real time can be input into the mapping table to quickly obtain the correction factor to help evaluate the credibility of the sample.

[0074] In a specific embodiment, the correction factor corresponding to the number of sensor corrections usually ranges from 0 to 1. The relationship between the number of sensor corrections and the correction factor is determined by analyzing the influence of the correction frequency on the sensor accuracy recovery effect and constructing a mapping table. For example, a high number of corrections may indicate that the sensor performance has deteriorated seriously and further intervention is required, while a moderate number of corrections indicates that the sensor maintains good performance. By obtaining the number of corrections and inputting it into the mapping table, the correction factor can be quickly obtained to adjust the weight of the monitoring data.

[0075] In a specific embodiment, the correction factor corresponding to the number of sample storage environment regulation times generally ranges from 0 to 1. The relationship between the number of storage environment regulation times and the correction factor is constructed by analyzing the impact of the regulation frequency on sample stability. For example, frequent regulation may indicate that the sample is subject to more external interference, and the reliability of the stored data needs to be treated with caution. The number of regulation times monitored in real time can be input into the mapping table to obtain the corresponding correction factor to reflect the impact of the stability of the sample storage conditions on the data quality.

[0076] The second aspect of the present invention also provides a recording system for marine pollution investigation data based on big data, including: a sampling point analysis module, which obtains and analyzes the measurement data of each sensor in each sampling point in the marine pollution investigation data, obtains the measurement stability compliance value of each sensor in each sampling point, and corrects the sensor at each sampling point according to the measurement stability compliance value of each sensor in each sampling point.

[0077] The sample preservation and transportation data analysis module is used to preset each monitoring period, monitor and obtain the marine pollution investigation sample preservation and transportation data and analyze it, obtain the marine pollution investigation sample preservation and transportation compliance value in each monitoring period, regulate the sample preservation environment according to the marine pollution investigation sample preservation and transportation compliance value in each monitoring period, and transmit the marine pollution investigation sample preservation and transportation data for preservation and record.

[0078] The control module is used to obtain the marine pollution survey data compliance characterization value according to the measurement stability compliance value of each sensor in each sampling point and the marine pollution survey sample storage and transportation compliance value in each monitoring period, and to regulate the marine pollution survey data analysis according to the marine pollution survey data compliance characterization value.

[0079] It should be noted that a recording system for marine pollution survey data based on big data also includes a database for storing the measurement stability compliance threshold of sensors in each sampling point, the marine pollution survey sample storage and transportation compliance threshold, the reference sampling frequency of the sampling point, the defined abnormal value ratio of the sampling point, the defined correction number of the sensor, the reference transportation time of the marine pollution survey sample, the defined control number of the sample storage environment, the correction factor corresponding to the sampling frequency, the correction factor corresponding to the abnormal value ratio, the correction factor corresponding to the transportation time, the correction factor corresponding to the correction number of the sensor, the correction factor corresponding to the control number of the sample storage environment, the reference change in the concentration of pollutants, the sample reference storage temperature of the sample pollutants, the sample reference pH change value of the sample pollutants, the reference sample decomposition rate, the correction factor corresponding to the concentration of the pollutants, the correction factor corresponding to the sample storage temperature, the correction factor corresponding to the pH value, the correction factor corresponding to the sample decomposition rate, the defined use time, the defined drift rate, the defined response time, the defined data deviation coefficient, the correction factor corresponding to the use time, the correction factor corresponding to the drift rate, the correction factor corresponding to the average response time, the weight factor corresponding to the historical average reading of the sensor, the weight factor corresponding to the current average reading of the sensor, etc.

[0080] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0081] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for recording marine pollution survey data based on big data, characterized in that: include: Obtain and analyze the measurement data of each sensor at each sampling point in the marine pollution survey data, obtain the measurement stability compliance value of each sensor at each sampling point, and correct the sensor at each sampling point according to the measurement stability compliance value of each sensor at each sampling point; Preset each monitoring cycle, monitor and obtain the marine pollution investigation sample storage and transportation data and analyze them, obtain the marine pollution investigation sample storage and transportation compliance value in each monitoring cycle, regulate the sample storage environment according to the marine pollution investigation sample storage and transportation compliance value in each monitoring cycle, and transmit the marine pollution investigation sample storage and transportation data for storage and record; According to the measurement stability compliance value of each sensor in each sampling point and the storage and transportation compliance value of the marine pollution investigation samples in each monitoring period, the marine pollution investigation data compliance characterization value is obtained, and the marine pollution investigation data analysis is regulated according to the marine pollution investigation data compliance characterization value.

2. The method for recording marine pollution survey data based on big data according to claim 1, characterized in that: The measurement data of each sensor at each sampling point in the marine pollution survey data is obtained and analyzed to obtain the measurement stability compliance value of each sensor at each sampling point. The specific process is: The measurement data of each sensor in each sampling point is extracted, including the usage time of each sensor, the drift rate of each sensor, the average response time of each sensor, and the current reading of each sensor. The historical average reading of each sensor stored in the large data set is extracted, and the measurement stability compliance value of each sensor in each sampling point is obtained after processing. The measurement stability compliance value of each sensor in each sampling point is used to indicate the degree of data deviation of the sensor during use.

3. The method for recording marine pollution survey data based on big data according to claim 1, characterized in that: The sensor at each sampling point is corrected according to the measurement stability compliance value of each sensor at each sampling point. The specific process is as follows: According to the measurement stability compliance value of each sensor in each sampling point, it is compared with the measurement stability compliance threshold of the sensor in each sampling point stored in the database. If the measurement stability compliance value of each sensor in each sampling point is higher than or equal to the measurement stability compliance threshold of the sensor in each sampling point, there is no need to correct the sensor at each sampling point. If the measurement stability compliance value of a sensor in a certain sampling point is lower than the measurement stability compliance threshold of the sensor in each sampling point, the reading of the sensor in each sampling point is corrected.

4. The method for recording marine pollution survey data based on big data according to claim 1, characterized in that: The monitoring and acquisition of marine pollution survey samples, preservation of transportation data and analysis are as follows: In each monitoring cycle, the concentration of sample pollutants at each sampling point at the initial monitoring time point and the concentration of sample pollutants at each sampling point at the end monitoring time point are counted, and the concentration of sample pollutants at each sampling point at the initial monitoring time point and the concentration of sample pollutants at each sampling point at the end monitoring time point are processed by difference to obtain the concentration change of sample pollutants in each monitoring cycle; The sample storage temperature was extracted in each monitoring period, and the sample storage and transportation data of each sampling point were extracted, including pH value and sample decomposition rate.

5. The method for recording marine pollution survey data based on big data according to claim 4 is characterized by: The specific process of obtaining the marine pollution survey sample storage and transportation compliance value in each monitoring period is as follows: The concentration changes of pollutants in the samples and the sample storage temperature in each monitoring period are extracted, and the pH value and sample decomposition rate are extracted. After processing, the marine pollution investigation sample storage and transportation compliance values ​​in each monitoring period are obtained. The marine pollution investigation sample storage and transportation compliance values ​​in each monitoring period are used to evaluate the degree to which the transportation and storage of the samples comply with the standards.

6. The method for recording marine pollution survey data based on big data according to claim 1, characterized in that: The storage environment of the samples is regulated according to the storage and transportation compliance values ​​of the marine pollution survey samples in each monitoring cycle, and the storage and transportation data of the marine pollution survey samples are transmitted and recorded. The specific process is as follows: According to the marine pollution investigation sample storage and transportation compliance value in each monitoring period, and compared with the marine pollution investigation sample storage and transportation compliance threshold stored in the database, if the marine pollution investigation sample storage and transportation compliance value in a certain monitoring period is higher than or equal to the marine pollution investigation sample storage and transportation compliance threshold, there is no need to adjust the sample storage environment; if the marine pollution investigation sample storage and transportation compliance value in a certain monitoring period is lower than the marine pollution investigation sample storage and transportation compliance threshold, the sample storage environment in the monitoring period shall be adjusted, and the marine pollution investigation sample storage and transportation data transmission shall be saved and recorded.

7. The method for recording marine pollution survey data based on big data according to claim 6 is characterized by: The marine pollution survey data obtained above meets the characterization value, and the specific process is as follows: The sampling frequency, abnormal value ratio and transportation time of each sampling point in the marine pollution investigation data are obtained in each monitoring cycle, and the number of sensor corrections at each sampling point and the number of sample storage environment adjustments are counted. The marine pollution investigation data conformity characterization value is obtained after processing. The marine pollution investigation data conformity characterization value is used to reflect the overall conformity of the data.

8. The method for recording marine pollution survey data based on big data according to claim 6 is characterized by: The specific process of regulating the analysis of marine pollution survey data according to the marine pollution survey data conforming to the characterization value is as follows: According to the marine pollution survey data compliance characterization value and compared with the set marine pollution survey data compliance characterization threshold, if the marine pollution survey data compliance characterization value is higher than or equal to the marine pollution survey data compliance characterization threshold, there is no need to adjust the marine pollution survey data analysis; if the marine pollution survey data compliance characterization value is lower than the marine pollution survey data compliance characterization threshold, the marine pollution survey data analysis will be adjusted.

9. The method for recording marine pollution survey data based on big data according to claim 6, characterized in that: The marine pollution survey data meets the characterization value, and the specific analysis conditions are: In the formula, S means that the marine pollution survey data meets the characterization value, c k→i represents the sampling frequency of the i-th sampling point in the K-th monitoring cycle, Z k→i represents the proportion of outliers at the i-th sampling point in the K-th monitoring cycle, t1 represents the transportation time of the marine pollution survey sample, XZ k→i represents the number of sensor corrections at the i-th sampling point in the K-th monitoring cycle, TK k represents the number of sample storage environment control times in the Kth monitoring cycle, Δc represents the reference sampling frequency of the set sampling point, ΔZ represents the defined abnormal value ratio of the set sampling point, ΔXZ represents the defined correction number of the set sensor, Δt represents the reference transportation time of the set ocean pollution investigation sample, ΔTK represents the defined control number of the set sample storage environment, μ1 represents the correction factor corresponding to the set sampling frequency, μ2 represents the correction factor corresponding to the set abnormal value ratio, μ3 represents the correction factor corresponding to the set transportation time, μ4 represents the correction factor corresponding to the set sensor correction number, μ5 represents the correction factor corresponding to the set sample storage environment control number, k represents the number of each monitoring cycle, k=1,2,3,...,h, h represents the total number of monitoring cycles, i represents the number of each sampling point, i=1,2,3,,,m, m represents the total number of sampling points.

10. A recording system for marine pollution survey data based on big data, characterized by: include: The sampling point analysis module is used to obtain and analyze the measurement data of each sensor at each sampling point in the marine pollution survey data, obtain the measurement stability compliance value of each sensor at each sampling point, and correct the sensor at each sampling point according to the measurement stability compliance value of each sensor at each sampling point; The sample preservation and transportation data analysis module is used to preset each monitoring period, monitor and obtain the marine pollution survey sample preservation and transportation data and analyze it, obtain the marine pollution survey sample preservation and transportation compliance value in each monitoring period, regulate the sample preservation environment according to the marine pollution survey sample preservation and transportation compliance value in each monitoring period, and transmit the marine pollution survey sample preservation and transportation data for preservation and record; The control module is used to obtain the marine pollution survey data compliance characterization value according to the measurement stability compliance value of each sensor in each sampling point and the marine pollution survey sample storage and transportation compliance value in each monitoring period, and to regulate the marine pollution survey data analysis according to the marine pollution survey data compliance characterization value.

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