Abnormal clue analysis method and system for environment online data

Abstract

The invention relates to the technical field of water environment data monitoring, in particular to an abnormal clue analysis method and system for environment online data, and the method comprises the steps: receiving the uploaded environment online data in a collection period, screening out first-level abnormal data in the environment online data, selecting the screening standard of the abnormal data, and obtaining the abnormal clue of the abnormal data; counting and sorting the screened environment online data, generating a time node-pollutant concentration curve, drawing a tangent line at each time node in the curve, determining node slopes, marking nodes of which the node slopes are greater than a preset node slope as abnormal nodes, and judging the environment online data based on the abnormal nodes. And generating a corresponding processing instruction based on the judgment result or finishing abnormal clue analysis on the environment online data, and re-determining the operation parameters of the corresponding parts based on the received processing instruction. According to the method and the device, the obtained environment online data can be quickly and accurately analyzed, and the use efficiency of the environment online data is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of water environment data monitoring, and particularly to a method and system for analyzing abnormal clues of environmental online data. Background Art

[0002] Environmental online data refers to the real-time collection, transmission, storage, and analysis of various elements and indicators in the environment through various online monitoring devices and systems. The analysis of abnormal clues in environmental online data refers to the in-depth study and interpretation of the data obtained through environmental online monitoring, which can identify abnormal data caused by reasons such as monitoring equipment failures, ensuring the accuracy and reliability of the data, and providing scientific support for environmental management and decision-making. The analysis of abnormal clues in environmental online data in water bodies is of great significance for timely and accurately detecting environmental pollution, monitoring ecological changes, and ensuring the health of residents.

[0003] Chinese Patent Publication No.: CN118780478A, discloses a water environment data intelligent analysis system, including: a first acquisition module for acquiring river images and river information of rivers in a city; a river analysis module for analyzing the main river area and river branch area according to the river information and river images; a second acquisition module for periodically acquiring river water quality information and monitoring point positions of river water quality monitoring points in the city; a numbering construction module for constructing branch numbers, monitoring point numbers, and main monitoring point numbers; a water quality analysis module for analyzing the water quality parameters of monitoring points, main water quality parameters, and main fluctuation parameters; a monitoring analysis module for analyzing the water quality status of monitoring points and also for analyzing abnormal positions; an output module for outputting abnormal positions. The present invention realizes the precise monitoring and analysis of water environment anomalies in urban rivers.

[0004] It can be seen that the above solution can accurately analyze the water environment anomalies in urban rivers through the water environment data intelligent analysis system, and can analyze and output the abnormal positions. However, the above solution cannot quickly and accurately analyze the acquired environmental online data, thus unable to ensure the usage efficiency of environmental online data. Summary of the Invention

[0005] Therefore, the present invention provides a method and system for analyzing abnormal clues of environmental online data to overcome the problem in the prior art that the acquired environmental online data cannot be quickly and accurately analyzed, resulting in low usage efficiency of environmental online data.

[0006] On the one hand, the present invention provides a method for analyzing abnormal clues of environmental online data, including:

[0007] Receive the environmental online data within the collected period uploaded, where the environmental online data includes time nodes, pollutant concentrations, and flow rates;

[0008] Mark the primary abnormal data in the environmental online data and perform screening and elimination processing;

[0009] Select the numerical range of the environmental online data after the screening and elimination processing as the screening criterion for abnormal data;

[0010] Statistically analyze and organize the environmental online data after the screening and elimination to generate a time node - pollutant concentration curve;

[0011] Draw a tangent at each time node in the curve and record the absolute value of the slope of the drawn tangent as the node slope;

[0012] Mark the nodes with each node slope greater than the preset node slope as abnormal nodes;

[0013] Make a determination on the environmental online data based on the abnormal nodes;

[0014] Generate corresponding processing instructions based on the determination result,

[0015] Or, complete the analysis of abnormal clues for the environmental online data;

[0016] Among them, the determination includes determining whether the environmental online data meets the standards and the reasons for not meeting the standards;

[0017] Redetermine the operating parameters of the corresponding components based on the received processing instructions.

[0018] Furthermore, the process of making a determination on the environmental online data based on the abnormal nodes includes:

[0019] Count the number of the abnormal nodes and record the obtained number as the abnormal quantity;

[0020] Calculate the ratio of the abnormal quantity to the total number of the time nodes and record the obtained ratio as the abnormal ratio;

[0021] When the abnormal ratio is less than the first preset abnormal ratio, determine that the environmental online data meets the standards and complete the analysis of abnormal clues for the environmental online data;

[0022] When the abnormal ratio is greater than or equal to the first preset abnormal ratio and less than the second preset abnormal ratio, determine that the environmental online data does not meet the standards and determine whether the preset node slope meets the standards based on the abnormal nodes;

[0023] When the abnormal ratio is greater than or equal to the second preset abnormal ratio, it is determined that the environmental online data does not meet the standard, and the reason why the environmental online data does not meet the standard is determined based on the node slope of the abnormal node.

[0024] Further, the process of determining whether the preset node slope meets the standard based on the abnormal node includes:

[0025] Determine the abnormal distribution degree of each abnormal node;

[0026] When the abnormal distribution degree is less than or equal to the preset abnormal distribution degree, it is determined that the preset node slope meets the standard, it is determined that the environmental online data does not meet the standard, and the reason why the environmental online data does not meet the standard is determined based on the node slope of the abnormal node;

[0027] When the abnormal distribution degree is greater than the preset abnormal distribution degree, it is determined that the preset node slope does not meet the standard, and the preset node slope is corrected based on the abnormal ratio.

[0028] Further, the process of correcting the preset node slope based on the abnormal ratio includes:

[0029] Calculate the difference between the abnormal ratio and the first preset abnormal ratio, and record the obtained difference as the abnormal ratio difference;

[0030] Increase the preset node slope based on the abnormal ratio difference, and the increase amplitude of the preset node slope is proportional to the abnormal ratio difference.

[0031] Further, the process of determining the reason why the environmental online data does not meet the standard based on the node slope of the abnormal node includes:

[0032] Calculate the variance of the node slopes of each abnormal node, and record the obtained variance as the slope variance;

[0033] Determine the reason why the environmental online data does not meet the standard based on the slope variance;

[0034] When the slope variance is less than or equal to the first preset slope variance, it is determined that the reason why the environmental online data does not meet the standard is that the number of environmental online data to be uploaded needs to be increased, and the acquisition period of the uploaded environmental online data is corrected based on the slope variance;

[0035] When the slope variance is greater than the first preset slope variance and less than or equal to the second preset slope variance, determine the reason why the environmental online data does not meet the standard based on the flow rate;

[0036] When the slope variance is greater than the second preset slope variance, the interval of the screening criteria for the abnormal data is corrected based on the node slope of the abnormal node.

[0037] Further, the process of correcting the collection period of the uploaded environmental online data based on the slope variance includes:

[0038] Calculate the difference between the first preset slope variance and the slope variance, and record the obtained difference as the slope covariance.

[0039] Based on the slope covariance, increase the collection period of the uploaded environmental online data and issue a corresponding notice, and the increase amplitude of the collection period of the uploaded environmental online data is proportional to the slope covariance.

[0040] Further, the process of correcting the preset abnormal ratio based on the increase amplitude after the collection period of the uploaded environmental online data is increased includes:

[0041] Increase the abnormal ratio based on the increase amplitude of the collection period of the uploaded environmental online data, and the increase amplitude of the abnormal ratio is proportional to the increase amplitude of the collection period of the uploaded environmental online data.

[0042] Further, the process of determining the reason why the environmental online data does not meet the standard based on the flow rate includes:

[0043] Calculate the actual flow rate according to the flow rate, and record the obtained flow rate as the actual flow rate.

[0044] Calculate the ratio of the actual flow rate to the expected flow rate, and record the obtained ratio as the flow rate ratio.

[0045] When the flow rate ratio is less than or equal to the first preset flow rate ratio, it is determined that the reason why the environmental online data does not meet the standard is that the quantity of the uploaded environmental online data needs to be increased, and the collection period of the uploaded environmental online data is corrected based on the slope variance.

[0046] When the flow rate ratio is greater than the first preset flow rate ratio and less than or equal to the second preset flow rate ratio, the interval of the screening criteria for the abnormal data is corrected based on the node slope of the abnormal node.

[0047] When the flow rate ratio is greater than the second preset flow rate ratio, a tampering notice is issued and manual verification is required.

[0048] Further, the process of correcting the interval of the screening criteria for the abnormal data based on the node slope of the abnormal node includes:

[0049] Calculate the average value of the node slopes of each of the abnormal nodes, and denote the obtained average value as the abnormal average value;

[0050] Based on the abnormal average value, reduce the interval of the screening criteria for the abnormal data, and the reduction amplitude of the interval of the screening criteria for the abnormal data is inversely proportional to the abnormal average value.

[0051] On the other hand, the present invention also provides an abnormal clue analysis system for environmental online data using the above method, including:

[0052] A data collection module, which is used to receive the uploaded environmental online data within the collection period. The environmental online data includes time nodes, pollutant concentrations, and flow rates;

[0053] A data cleaning module, which is connected to the data collection module and is used to mark the primary abnormal data in the environmental online data and perform screening and elimination processing;

[0054] A statistics module, which is connected to the data cleaning module and is used to select the numerical range of the environmental online data after the screening and elimination processing as the screening criteria for the abnormal data; the statistics module is also used to perform statistics and sorting on the environmental online data after the screening and elimination to generate a time node - pollutant concentration curve;

[0055] A feature extraction module, which is connected to the statistics module and is used to draw a tangent line at each time node in the curve and denote the absolute value of the slope of the drawn tangent line as the node slope; the feature extraction module is also used to denote the nodes with each node slope greater than the preset node slope as abnormal nodes;

[0056] An analysis module, which is connected to the feature extraction module and is used to determine the environmental online data based on the abnormal nodes; the analysis module is also used to generate corresponding processing instructions based on the determination result, or complete the abnormal clue analysis of the environmental online data; wherein, the determination includes determining whether the environmental online data meets the standard and the reasons for not meeting the standard;

[0057] A processing module, which is respectively connected to the statistics module, the feature extraction module, and the analysis module and is used to re - determine the operating parameters of the corresponding components based on the received processing instructions.

[0058] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention screens out primary abnormal data for statistics and collation, generates a time node-pollutant concentration curve, obtains the node slope, and determines the environmental online data based on the abnormal nodes, which can timely and accurately determine whether the environmental online data meets the standards, effectively realizes the rapid and accurate analysis of the obtained environmental online data, generates corresponding processing instructions based on the determination results, re-determines the operating parameters of the corresponding components based on the received processing instructions, effectively ensures the operating efficiency of the system, further realizes the rapid and accurate analysis of the obtained environmental online data, effectively ensures the accurate environmental evaluation results obtained based on the environmental online data, and effectively improves the utilization efficiency of the environmental online data.

[0059] Further, the present invention calculates the abnormal ratio based on the number of abnormal nodes, and determines whether the environmental online data meets the standards based on the abnormal ratio, which can accurately determine whether the environmental online data meets the standards according to the uploaded environmental data, while further realizing the rapid and accurate analysis of the obtained environmental online data, and further improving the utilization efficiency of the environmental online data.

[0060] Further, when the abnormal ratio is greater than or equal to the first preset abnormal ratio and less than the second preset abnormal ratio, the present invention determines whether the preset node slope meets the standards based on the abnormal distribution degree, effectively determines whether the situation where the abnormal ratio is greater than or equal to the first preset abnormal ratio and less than the second preset abnormal ratio is caused by the non-compliance of the preset node slope, while further realizing the rapid and accurate analysis of the obtained environmental online data, and further improving the utilization efficiency of the environmental online data.

[0061] Further, the present invention increases the preset node slope based on the abnormal ratio difference, effectively avoids the situation where the abnormal ratio is greater than or equal to the first preset abnormal ratio and less than the second preset abnormal ratio caused by the non-compliance of the preset node slope, can effectively ensure the determination accuracy of the system for the environmental online data, further ensures the operating efficiency of the system, while further realizing the rapid and accurate analysis of the obtained environmental online data, and further improving the utilization efficiency of the environmental online data.

[0062] Further, the present invention determines the reason why the environmental online data does not meet the standards based on the slope variance, which can timely and accurately determine whether the environmental online data meets the standards, and avoids the occurrence of misjudgment, while further realizing the rapid and accurate analysis of the obtained environmental online data, and further improving the utilization efficiency of the environmental online data.

[0063] Furthermore, the present invention increases the acquisition cycle of the uploaded environmental online data based on the covariance and issues corresponding notifications, avoiding the situation where the environmental online data is determined to be non-compliant due to the acquisition cycle of the uploaded environmental online not meeting the standard, further ensuring the operation efficiency of the system. While further realizing the rapid and accurate analysis of the acquired environmental online data, the utilization efficiency of the environmental online data is further improved.

[0064] Furthermore, after the increase in the acquisition cycle of the uploaded environmental online data is completed, the present invention corrects the preset abnormal ratio based on the increase amplitude, effectively ensuring the coordination between the quantity of the environmental online data and the preset abnormal ratio, further ensuring the operation efficiency of the system. While further realizing the rapid and accurate analysis of the acquired environmental online data, the utilization efficiency of the environmental online data is further improved.

[0065] Furthermore, when the slope variance is greater than the first preset slope variance and less than or equal to the second preset slope variance, the present invention determines the reason for the non-compliance of the environmental online data based on the flow ratio. Combining the flow velocity with the slope variance can more accurately determine the reason for the non-compliance of the environmental online data, avoiding misjudgment. While further realizing the rapid and accurate analysis of the acquired environmental online data, the utilization efficiency of the environmental online data is further improved.

[0066] Furthermore, the present invention reduces the interval of the abnormal data screening standard based on the abnormal average value, effectively ensuring that the interval of the abnormal data screening standard can guarantee the accuracy of the judgment on the uploaded environmental online data, further ensuring the operation efficiency of the system. While further realizing the rapid and accurate analysis of the acquired environmental online data, the utilization efficiency of the environmental online data is further improved. Description of the Drawings

[0067] Figure 1 It is a structural block diagram of the abnormal clue analysis system for environmental online data in an embodiment of the present invention;

[0068] Figure 2 It is a flowchart of the abnormal clue analysis method for environmental online data in an embodiment of the present invention;

[0069] Figure 3 It is a flowchart of determining whether the environmental online data meets the standard and whether the preset node slope meets the standard in an embodiment of the present invention;

[0070] Figure 4 It is a flowchart of determining the reason for the non-compliance of the environmental online data in an embodiment of the present invention. Detailed Embodiments

[0071] In order to make the objectives and advantages of the present invention more clearly understood, the present invention will be further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only for explaining the present invention and are not used to limit the present invention.

[0072] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention and do not limit the protection scope of the present invention.

[0073] In addition, it should also be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installation", "connection", and "connection" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, and it can be the communication inside two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0074] Please refer to Figure 1 As shown, it is a structural block diagram of an abnormal clue analysis system for environmental online data in an embodiment of the present invention. The structure of the embodiment of the present invention includes a data collection module, a data cleaning module, a statistics module, a feature extraction module, an analysis module, and a processing module; among them,

[0075] The data collection module is used to receive the environmental online data within the collection period uploaded, and the environmental online data includes time nodes, pollutant concentrations, and flow rates;

[0076] The data cleaning module is connected to the data collection module and is used to mark the first-level abnormal data in the environmental online data and perform screening and removal processing;

[0077] Specifically, the first-level abnormal data is the environmental online data less than or equal to zero and the abnormal environmental online data greater than zero in the environmental online data. Mark the environmental online data less than or equal to zero, calculate the 95th percentile of other data in the marked environmental online data less than or equal to zero, and record the environmental online data greater than this percentile as the abnormal environmental online data greater than zero, and mark the environmental online data greater than zero and abnormal, and record the marked environmental online data as the first-level abnormal data;

[0078] The statistics module is connected to the data cleaning module and is used to select the numerical range of the environmental online data after screening and removal as the screening criterion for abnormal data; the statistics module is also used to statistically analyze and organize the environmental online data after screening to generate a time node - pollutant concentration curve;

[0079] The feature extraction module is connected to the statistics module, and is used to draw a tangent line at each time node in the curve, and record the absolute value of the slope of the drawn tangent line as the node slope; the feature extraction module is also used to record the nodes with each node slope greater than the preset node slope as abnormal nodes;

[0080] The analysis module is connected to the feature extraction module, and is used to determine the environmental online data based on the abnormal nodes; the analysis module is also used to generate corresponding processing instructions based on the determination result, or complete the analysis of abnormal clues of the environmental online data; wherein, the determination includes determining whether the environmental online data meets the standard and the reason for not meeting the standard;

[0081] The processing module is respectively connected to the statistics module, the feature extraction module and the analysis module, and is used to re-determine the operating parameters of the corresponding components based on the received processing instructions.

[0082] Please refer to Figure 2 as shown, which is a flowchart of the method for analyzing abnormal clues of environmental online data according to an embodiment of the present invention. The method according to an embodiment of the present invention includes:

[0083] Receiving the uploaded environmental online data within the collection period, where the environmental online data includes time nodes, pollutant concentrations, and flow rates;

[0084] Marking the primary abnormal data in the environmental online data and performing screening and processing;

[0085] Selecting the numerical range of the environmental online data after screening and processing as the screening criterion for abnormal data;

[0086] Statistically processing and organizing the environmental online data after screening to generate a time node - pollutant concentration curve;

[0087] Drawing a tangent line at each time node in the curve, and recording the absolute value of the slope of the drawn tangent line as the node slope;

[0088] Recording the nodes with each node slope greater than the preset node slope K as abnormal nodes, where the preset node slope K = 0.32 in the embodiment of the present invention;

[0089] Determining the environmental online data based on the abnormal nodes;

[0090] Generating corresponding processing instructions based on the determination result,

[0091] or, completing the analysis of abnormal clues of the environmental online data;

[0092] wherein, the determination includes determining whether the environmental online data meets the standard and the reason for not meeting the standard;

[0093] Redetermine the operating parameters of the corresponding component based on the received processing instruction.

[0094] Please refer to Figure 3 As shown, it is a flowchart for determining whether the environmental online data meets the standard and whether the slope of the preset node meets the standard in an embodiment of the present invention. The process of determining the environmental online data based on the abnormal node in the embodiment of the present invention includes:

[0095] Count the number of the abnormal nodes, and record the obtained number as the abnormal quantity;

[0096] Calculate the ratio of the abnormal quantity to the total number of the time nodes, and record the obtained ratio as the abnormal ratio;

[0097] Compare the abnormal ratio with a preset abnormal ratio;

[0098] When the abnormal ratio is less than the first preset abnormal ratio R1, it is determined that the environmental online data meets the standard, and the analysis of the abnormal clues of the environmental online data is completed. In this embodiment, the first preset abnormal ratio R1 = 1.1%;

[0099] When the abnormal ratio is greater than or equal to the first preset abnormal ratio R1 and less than the second preset abnormal ratio R2, it is determined that the environmental online data does not meet the standard, and it is determined whether the slope of the preset node meets the standard based on the abnormal node. In this embodiment, the second preset abnormal ratio R2 = 20%;

[0100] When the abnormal ratio is greater than or equal to the second preset abnormal ratio R2, it is determined that the environmental online data does not meet the standard, and the reason why the environmental online data does not meet the standard is determined based on the node slope of the abnormal node.

[0101] Please continue to refer to Figure 3 As shown, the process of determining whether the slope of the preset node meets the standard based on the abnormal node in the embodiment of the present invention includes:

[0102] Determine the abnormal distribution degree of each of the abnormal nodes. Among them, select a single abnormal node as the first abnormal node, obtain the abnormal node with the closest straight-line distance to the first abnormal node as the second abnormal node, calculate the distance between the first abnormal node and the second abnormal node, and record the obtained distance as the first distance. Obtain the abnormal node with the closest straight-line distance to the second abnormal node as the third abnormal node, calculate the distance between the second abnormal node and the third abnormal node, and record the obtained distance as the second distance. Sequentially complete the acquisition of the straight-line distances between each pair of abnormal nodes, calculate the average value of each straight-line distance, select the abscissa range of the time nodes within the acquisition period of the curve, calculate the abscissa distance between the maximum value of the abscissa of the time nodes and the minimum value of the abscissa of the time nodes within the abscissa range, calculate the ratio of the average value of each straight-line distance to the abscissa distance, and record the obtained ratio as the abnormal distribution degree;

[0103] Determine whether the slope of the preset node meets the standard based on the abnormal distribution degree;

[0104] When the abnormal distribution degree is less than or equal to the preset abnormal distribution degree D, it is determined that the slope of the preset node meets the standard, it is determined that the environmental online data does not meet the standard, and the reason why the environmental online data does not meet the standard is determined based on the node slope of the abnormal node. Among them, in this embodiment, the preset abnormal distribution degree D = 18%;

[0105] When the abnormal distribution degree is greater than the preset abnormal distribution degree D, it is determined that the slope of the preset node does not meet the standard, and the slope of the preset node is corrected based on the abnormal ratio.

[0106] Please continue to refer to Figure 3 As shown, the process of correcting the slope of the preset node based on the abnormal ratio in the embodiment of the present invention includes:

[0107] Calculate the difference between the abnormal ratio and the first preset abnormal ratio, and record the obtained difference as the abnormal ratio difference;

[0108] Increase the slope of the preset node based on the abnormal ratio difference;

[0109] When the abnormal ratio difference is greater than the second preset abnormal ratio difference △A2, increase the slope of the preset node to 1.23 times the initial preset node slope. Among them, in this embodiment, the second preset abnormal ratio difference △A2 = 13.1%;

[0110] When the abnormal ratio difference is less than or equal to the second preset abnormal ratio difference △A2 and greater than the first preset abnormal ratio difference A1, increase the slope of the preset node to 1.17 times the initial preset node slope. Among them, in this embodiment, the first preset abnormal ratio difference △A1 = 7.9%;

[0111] When the abnormal ratio difference is less than or equal to the first preset abnormal ratio difference △A1, increase the preset node slope to 1.09 times the initial preset node slope.

[0112] Please refer to Figure 4 As shown, it is a flowchart of the reasons for determining that the environmental online data in the embodiments of the present invention does not meet the standards. The process of determining the reasons for the environmental online data not meeting the standards based on the node slope of the abnormal node in the embodiments of the present invention includes:

[0113] Calculate the variance of the node slopes of each abnormal node, and record the obtained variance as the slope variance;

[0114] Determine the reasons for the environmental online data not meeting the standards based on the slope variance;

[0115] When the slope variance is less than or equal to the first preset slope variance C1, determine that the reason for the environmental online data not meeting the standards is that the quantity of environmental online data to be uploaded needs to be increased, and correct the acquisition period of the uploaded environmental online data based on the slope variance. In this embodiment, the first preset slope variance C1 = 0.21;

[0116] When the slope variance is greater than the first preset slope variance C1 and less than or equal to the second preset slope variance C2, determine the reasons for the environmental online data not meeting the standards based on the flow velocity. In this embodiment, the second preset angle variance C2 = 0.58;

[0117] When the slope variance is greater than the second preset slope variance C2, correct the interval of the screening criteria for the abnormal data based on the node slope of the abnormal node.

[0118] Please continue to refer to Figure 4 As shown, the process of correcting the acquisition period of the uploaded environmental online data based on the slope variance in the embodiments of the present invention includes:

[0119] Calculate the difference between the first preset slope variance and the slope variance, and record the obtained difference as the slope covariance;

[0120] Increase the acquisition period of the uploaded environmental online data based on the slope covariance and issue a corresponding notice;

[0121] When the slope covariance is greater than the second preset slope covariance △S2, increase the acquisition period of the uploaded environmental online data to 1.38 times the acquisition period of the initially uploaded environmental online data, and issue a corresponding notice. In this embodiment, the second preset slope covariance △S2 = 0.15;

[0122] When the covariance is less than or equal to the second preset covariance △S2 and greater than the first preset covariance △S1, increase the collection period of the uploaded environmental online data to 1.26 times the collection period of the initially uploaded environmental online data, and issue a corresponding notice. Here, in this embodiment, the first preset slope difference △S1 = 0.08;

[0123] When the covariance is less than or equal to the first preset covariance △S1, increase the collection period of the uploaded environmental online data to 1.11 times the collection period of the initially uploaded environmental online data, and issue a corresponding notice.

[0124] Please continue to refer to Figure 4 As shown, the process of correcting the preset abnormal ratio based on the increase amplitude after the increase of the collection period of the uploaded environmental online data in the embodiment of the present invention includes:

[0125] Increase the abnormal ratio based on the increase amplitude of the collection period of the uploaded environmental online data;

[0126] When the collection period of the uploaded environmental online data is increased to 1.38 times the collection period of the initially uploaded environmental online data, increase the preset abnormal ratio to 1.12 times the initial preset abnormal ratio;

[0127] When the collection period of the uploaded environmental online data is increased to 1.26 times the collection period of the initially uploaded environmental online data, increase the preset abnormal ratio to 1.09 times the initial preset abnormal ratio;

[0128] When the collection period of the uploaded environmental online data is increased to 1.11 times the collection period of the initially uploaded environmental online data, increase the preset abnormal ratio to 1.05 times the initial preset abnormal ratio.

[0129] Please continue to refer to Figure 4 As shown, the process of determining the reason why the environmental online data does not meet the standard based on the flow rate in the embodiment of the present invention includes:

[0130] Calculate the actual flow rate according to the flow rate, and record the obtained flow rate as the actual flow rate;

[0131] Calculate the ratio of the actual flow rate to the expected flow rate, and record the obtained ratio as the flow rate ratio;

[0132] Determine the reason why the environmental online data does not meet the standard based on the flow rate ratio;

[0133] When the flow ratio is less than or equal to the first preset flow ratio Q1, it is determined that the reason for the non - compliance of the environmental online data with the standard is the need to increase the quantity of the uploaded environmental online data, and the quantity of the uploaded environmental online data is corrected based on the slope variance. Here, in this embodiment, the first preset flow ratio Q1 = 0.92;

[0134] When the flow ratio is greater than the first preset flow ratio Q1 and less than or equal to the second preset flow ratio Q2, the interval of the screening criteria for the abnormal data is corrected based on the node slope of the abnormal node. Here, in this embodiment, the second preset flow ratio Q2 = 1;

[0135] When the flow ratio is greater than the second preset flow ratio Q2, a tampering notice is issued and manual verification is required;

[0136] Specifically, when calculating the actual flow rate according to the flow velocity, the actual flow rate is the product of the flow velocity and the cross - sectional area of water during the flowing process.

[0137] Please continue to refer to Figure 4 As shown, the process of correcting the interval of the screening criteria for the abnormal data based on the node slope of the abnormal node in the embodiment of the present invention includes:

[0138] Calculate the average value of the node slopes of each abnormal node, and denote the obtained average value as the abnormal average value;

[0139] Reduce the interval of the screening criteria for the abnormal data based on the abnormal average value;

[0140] When the abnormal average value is greater than the second preset abnormal average value V2, reduce the interval of the screening criteria to 0.97 times of the initial screening criteria interval. Here, in this embodiment, the second preset abnormal average value V2 = 0.81;

[0141] When the abnormal average value is less than or equal to the second preset abnormal average value V2 and greater than the first preset abnormal average value V1, reduce the interval of the screening criteria to 0.94 times of the initial screening criteria interval. Here, in this embodiment, the first preset abnormal average value V1 = 0.53;

[0142] When the abnormal average value is less than or equal to the first preset abnormal average value V1, reduce the interval of the screening criteria to 0.91 times of the initial screening criteria interval.

[0143] So far, the technical solution of the present invention has been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easily understood by those skilled in the art that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0144] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An abnormal clue analysis method for environmental online data, characterized in that, Including: Receiving the on-line environmental data within the collected period of time uploaded, where the on-line environmental data includes time nodes, pollutant concentrations, and flow rates; Marking the primary abnormal data in the on-line environmental data and performing screening and elimination processing; Selecting the numerical range of the on-line environmental data after the screening and elimination processing as the screening criterion for abnormal data; Statistically analyzing and sorting out the on-line environmental data after the screening to generate a time node - pollutant concentration curve; Drawing a tangent line at each time node in the curve and recording the absolute value of the slope of the drawn tangent line as the node slope; Marking the nodes with the node slope greater than the preset node slope as abnormal nodes; Judging the on-line environmental data based on the abnormal nodes; Generating corresponding processing instructions based on the judgment result, or, completing the analysis of abnormal clues for the on-line environmental data; wherein, the judgment includes judging whether the on-line environmental data meets the standard and the reasons for not meeting the standard; Re-determining the operating parameters of the corresponding components based on the received processing instructions.

2. The method for analyzing abnormal clues of environmental online data according to claim 1, wherein The process of judging the on-line environmental data based on the abnormal nodes includes: Counting the number of the abnormal nodes and recording the obtained number as the abnormal quantity; Calculating the ratio of the abnormal quantity to the total number of the time nodes and recording the obtained ratio as the abnormal ratio; When the abnormal ratio is less than the first preset abnormal ratio, judging that the on-line environmental data meets the standard and completing the analysis of abnormal clues for the on-line environmental data; When the abnormal ratio is greater than or equal to the first preset abnormal ratio and less than the second preset abnormal ratio, judging that the on-line environmental data does not meet the standard and judging whether the preset node slope meets the standard based on the abnormal nodes; When the abnormal ratio is greater than or equal to the second preset abnormal ratio, judging that the on-line environmental data does not meet the standard and judging the reasons for the on-line environmental data not meeting the standard based on the node slope of the abnormal nodes.

3. The method for analyzing abnormal clues of environmental online data according to claim 2, characterized in that, The process of judging whether the preset node slope meets the standard based on the abnormal nodes includes: Determining the abnormal distribution degree of each of the abnormal nodes; When the abnormal distribution degree is less than or equal to the preset abnormal distribution degree, judging that the preset node slope meets the standard, judging that the on-line environmental data does not meet the standard, and judging the reasons for the on-line environmental data not meeting the standard based on the node slope of the abnormal nodes; When the abnormal distribution degree is greater than the preset abnormal distribution degree, judging that the preset node slope does not meet the standard and correcting the preset node slope based on the abnormal ratio.

4. The method for analyzing abnormal clues of environmental online data according to claim 3, wherein The process of correcting the preset node slope based on the abnormal ratio includes: Calculating the difference between the abnormal ratio and the first preset abnormal ratio and recording the obtained difference as the abnormal ratio difference; Increasing the preset node slope based on the abnormal ratio difference, and the increasing amplitude of the preset node slope is proportional to the abnormal ratio difference.

5. The method for analyzing abnormal clues of environmental online data according to claim 3, wherein The process of judging the reasons for the on-line environmental data not meeting the standard based on the node slope of the abnormal nodes includes: Calculating the variance of the node slope of each of the abnormal nodes and recording the obtained variance as the slope variance; Determine the reason why the environmental online data does not meet the standard based on the slope variance; When the slope variance is less than or equal to the first preset slope variance, determine that the reason why the environmental online data does not meet the standard is that the number of environmental online data to be uploaded needs to be increased, and correct the collection period of the uploaded environmental online data based on the slope variance; When the slope variance is greater than the first preset slope variance and less than or equal to the second preset slope variance, determine the reason why the environmental online data does not meet the standard based on the flow velocity; When the slope variance is greater than the second preset slope variance, correct the interval of the screening criteria of the abnormal data based on the node slope of the abnormal node.

6. The method for analyzing abnormal clues of environmental online data according to claim 5, wherein The process of correcting the collection period of the uploaded environmental online data based on the slope variance includes: Calculate the difference between the first preset slope variance and the slope variance, and record the obtained difference as the slope covariance; Based on the slope covariance, increase the collection period of the uploaded environmental online data and issue a corresponding notice, and the increase amplitude of the collection period of the uploaded environmental online data is proportional to the slope covariance.

7. The method for analyzing abnormal clues of environmental online data according to claim 6, wherein The process of correcting the preset abnormal ratio based on the increase amplitude after the collection period of the uploaded environmental online data is increased includes: Increase the abnormal ratio based on the increase amplitude of the collection period of the uploaded environmental online data, and the increase amplitude of the abnormal ratio is proportional to the increase amplitude of the collection period of the uploaded environmental online data.

8. The method for analyzing abnormal clues of environmental online data according to claim 5, characterized in that The process of determining the reason why the environmental online data does not meet the standard based on the flow velocity includes: Calculate the actual flow rate according to the flow velocity, and record the obtained flow rate as the actual flow rate; Calculate the ratio of the actual flow rate to the expected flow rate, and record the obtained ratio as the flow rate ratio; When the flow rate ratio is less than or equal to the first preset flow rate ratio, determine that the reason why the environmental online data does not meet the standard is that the number of environmental online data to be uploaded needs to be increased, and correct the collection period of the uploaded environmental online data based on the slope variance; When the flow rate ratio is greater than the first preset flow rate ratio and less than or equal to the second preset flow rate ratio, correct the interval of the screening criteria of the abnormal data based on the node slope of the abnormal node; When the flow rate ratio is greater than the second preset flow rate ratio, issue a tampering notice and manual verification is required.

9. The method for analyzing abnormal clues of environmental online data according to claim 5, characterized in that The process of correcting the interval of the screening criteria of the abnormal data based on the node slope of the abnormal node includes: Calculate the average value of the node slopes of each abnormal node, and record the obtained average value as the abnormal average value; Based on the abnormal average value, reduce the interval of the screening criteria of the abnormal data, and the reduction amplitude of the interval of the screening criteria of the abnormal data is inversely proportional to the abnormal average value.

10. An abnormal clue analysis system for environmental online data using the method according to any one of claims 1-9, characterized in that, Include: A data collection module for receiving environmental online data within the uploaded collection period, where the environmental online data includes time nodes, pollutant concentrations, and flow velocities; A data cleaning module connected to the data collection module for marking the primary abnormal data in the environmental online data and performing screening and elimination processing; A statistical module, which is connected to the data cleaning module and is used to select the numerical range of the processed environmental online data as the screening criterion for abnormal data; the statistical module is also used to statistically analyze and organize the screened environmental online data to generate a time node - pollutant concentration curve; A feature extraction module, which is connected to the statistical module and is used to draw a tangent line at each time node in the curve and record the absolute value of the slope of the drawn tangent line as the node slope; the feature extraction module is also used to mark the nodes with node slopes greater than the preset node slope as abnormal nodes; An analysis module, which is connected to the feature extraction module and is used to determine the environmental online data based on the abnormal nodes; the analysis module is also used to generate corresponding processing instructions based on the determination result, or to complete the analysis of abnormal clues for the environmental online data; wherein, the determination includes determining whether the environmental online data meets the standard and the reasons for not meeting the standard; A processing module, which is respectively connected to the statistical module, the feature extraction module and the analysis module and is used to re - determine the operating parameters of the corresponding components based on the received processing instructions.

Images