Hydrology and water resource detection data analysis system

Abstract

The invention belongs to the field of hydrological data analysis, relates to a data processing technology, is used for solving the problem that the operation condition of terminal equipment in a hydrological detection region cannot be analyzed according to abnormal data in the prior art, and particularly relates to a hydrological water resource detection data analysis system, which comprises a verification analysis module, a region management module and a fault analysis module, the verification analysis module is used for periodically receiving the hydrological redundant data of the hydrological station network and sending the hydrological redundant data to the regional management module; the regional management module is used for performing regional management on the hydrological station network according to the hydrological redundant data and obtaining a fine set, a fault set and a neglect set; according to the method, regional management can be carried out on a hydrological station network, an invalid set composed of invalid values is screened, data support is provided for equipment fault state and data acquisition precision analysis according to a fault set and a fine set, and abnormal data in hydrological data is fully utilized.

Description

Technical Field

[0001] The invention belongs to the field of hydrological data analysis, relates to data processing technology, and specifically is a hydrological and water resources detection data analysis system. Background Art

[0002] Hydrological and water resources detection refers to the general term for technical work of systematically collecting and organizing hydrological data. In a narrow sense, hydrological information collection refers to the observation of hydrological elements. Hydrological information collection is the basis of hydrology. Hydrological information work is divided into two parts: information collection and information transmission. Hydrological information collection is completed by various types of mature sensors.

[0003] The hydrological and water resources detection data analysis system in the prior art generally removes abnormal data by data cleaning, and then retains valid data for statistics and analysis; the authorized invention patent with announcement number CN112330197B discloses a meteorological and hydrological data quality control and evaluation method, which completes data quality evaluation and value replacement through preset quality control and evaluation parameters, and finally outputs meteorological and hydrological data containing original data, data quality and corrected values; however, this method does not make use of abnormal data, that is, it is impossible to analyze the operation of terminal equipment in the hydrological detection area based on abnormal data, and the detection terminal of hydrological and water resources detection data cannot be optimized, which in turn affects the accuracy of hydrological detection data and the base of valid hydrological data for statistics.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide a hydrological and water resources detection data analysis system to solve the problem that the prior art cannot analyze the operation status of terminal equipment in the hydrological detection area based on abnormal data; The technical problem to be solved by the present invention is: how to provide a hydrological and water resources detection data analysis system that can analyze the operation status of terminal equipment in a hydrological detection area based on abnormal data.

[0006] The purpose of the present invention can be achieved by the following technical solutions: A hydrological and water resources detection data analysis system, comprising a verification analysis module, a regional management module and a fault analysis module; The verification and analysis module is used to periodically receive the hydrological redundant data of the hydrological station network and send the hydrological redundant data to the regional management module; The regional management module is used to perform regional management of the hydrological station network according to the hydrological redundant data and obtain the optimal set, the fault set and the neglected set; and send the optimal set, the fault set and the neglected set to the fault analysis module; The fault analysis module is used to analyze the equipment fault status of the hydrological station, generate an equipment supplement signal when the management area has equipment fault characteristics and send the equipment supplement signal to the mobile phone terminal of the manager; generate a verification optimization signal when the management area has necessary optimization characteristics and send the verification optimization signal to the mobile phone terminal of the manager.

[0007] As a preferred embodiment of the present invention, the hydrological redundant data includes duplicate data, erroneous data and abnormal data obtained through data cleaning and equipment verification; the data cleaning process includes: missing value cleaning: including identifying missing values ​​and processing them, and the processing methods include deletion, mean, median, mode filling, etc.; format content cleaning: such as converting strings to numbers, or formatting numbers into specific string forms, etc.; logical error cleaning: identifying possible erroneous data or abnormal data through statistical analysis methods, such as using common sense rules, business-specific rules, etc. to check data values; duplicate data cleaning: identifying and deleting duplicate or redundant entries in the data set; data normalization: standardizing the data into a data set with the same dimension and relative size relationship. Equipment verification is the process of regularly verifying the data collection accuracy, data transmission timeliness and integrity of the hydrological data collection terminal.

[0008] As a preferred embodiment of the present invention, the specific process of the regional management module performing regional management on the hydrological station network includes: generating a management cycle, marking the coverage area of ​​the hydrological stations in the hydrological station network as the management area of ​​the hydrological station, marking the hydrological redundant data corresponding to the management area within the management cycle as invalid data, marking the terminal devices corresponding to the invalid data as abnormal devices, marking the number of invalid data corresponding to the abnormal devices as invalid values ​​of the abnormal devices, forming an invalid set from the invalid values ​​of all abnormal devices, performing fault screening on the invalid set and obtaining a fault set, an optimized set and a neglected set.

[0009] As a preferred embodiment of the present invention, the specific process of fault screening processing for invalid sets includes: summing and averaging all elements in the invalid set to obtain the fault processing value of the invalid set, marking abnormal devices whose invalid values ​​are not less than the fault processing value as prominent objects, marking abnormal devices whose invalid values ​​are less than the fault processing value as ignored objects, marking the ratio of the number of prominent objects to ignored objects as the prominent coefficient of the invalid set, comparing the prominent coefficient with the preset prominent threshold and marking the prominent set, the optimal set and the ignored set according to the comparison results.

[0010] As a preferred embodiment of the present invention, the specific process of comparing the protrusion coefficient with the preset protrusion threshold includes: if the protrusion coefficient is greater than or equal to the protrusion threshold, the element with the largest value and the element with the smallest value in the invalid set are respectively classified into the fault set and the neglect set, the protrusion coefficient of the invalid set is recalculated and compared with the protrusion threshold, and so on, until the protrusion coefficient is less than the protrusion threshold; If the prominence coefficient is less than the prominence threshold, the filtered invalid set is marked as an excellent set.

[0011] As a preferred embodiment of the present invention, the specific process of determining whether a management area has equipment failure characteristics includes: marking the ratio of the number of elements in the fault set to the number of abnormal devices as the fault manifestation value of the management area, and comparing the fault manifestation value with a preset fault manifestation threshold: if the fault manifestation value is greater than or equal to the fault manifestation threshold, then it is determined that the management area has equipment failure characteristics, and a device supplement signal is generated and sent to the mobile phone terminal of the management personnel; if the fault manifestation value is less than the fault manifestation threshold, then it is determined that the management area does not have equipment failure characteristics.

[0012] As a preferred embodiment of the present invention, the specific process of determining whether a management area has the necessary features for optimization includes: summing and averaging all elements in the optimal set to obtain the necessary optimization value of the management area, and comparing the necessary optimization value with a preset necessary optimization threshold: if the necessary optimization value is less than the necessary optimization threshold, then it is determined that the management area does not have the necessary optimization features; if the necessary optimization value is greater than or equal to the necessary optimization threshold, then it is determined that the management area has the necessary optimization features, generating a verification optimization signal and sending the verification optimization signal to the mobile phone terminal of the management personnel.

[0013] As a preferred embodiment of the present invention, it also includes a regional planning module and a class sequence generation module, wherein the regional planning module is used to perform planning management analysis on the management area of ​​the hydrological station network to obtain a planning interval and a matching area of ​​the planning interval, and send the planning interval and the matching area of ​​the planning interval to the class sequence generation module; The class sequence generation module is used to perform equipment type sequence analysis on the management area of ​​the hydrological station network and obtain the equipment type sequence of the planned interval, and send the equipment type sequence of all planned intervals to the mobile phone terminal of the management personnel.

[0014] As a preferred embodiment of the present invention, the process of obtaining the planning interval and the matching area of ​​the planning interval includes: marking the ratio of the water area value of the management area to the total area value of the management area as the planning coefficient of the management area, forming a planning range by the maximum planning coefficient and the minimum planning coefficient of the management area of ​​the hydrological station network, dividing the planning range into several planning intervals, and marking the management area whose planning coefficient is within the planning interval as the matching area of ​​the planning interval.

[0015] As a preferred embodiment of the present invention, the process of obtaining the device type sequence includes: counting the abnormal devices in all matching areas within the planning interval, marking the number of abnormal devices corresponding to the same device type as the abnormal value of the device type, and arranging the device types in order from large to small according to the abnormal values ​​to obtain the device type sequence of the planning interval.

[0016] The present invention has the following beneficial effects: The regional management module can be used to manage the hydrological station network regionally, screen out invalid sets consisting of invalid values, provide data support for equipment fault status and data acquisition accuracy analysis based on fault sets and optimized sets, process redundant data in the coverage area of ​​each hydrological station in the hydrological station network in a regional analysis manner, and make full use of abnormal data in the hydrological data; The fault analysis module can be used to analyze the equipment fault status of the hydrological station, and the abnormal frequency of the overall detection terminal in the management area can be fed back through the proportion of the fault set elements in the abnormal equipment, so as to supplement the terminal equipment in the management area with equipment fault characteristics, to prevent the high failure rate of the collection terminals in the same area from causing insufficient valid data to be provided by the normally operating collection terminals. For the management area with the necessary optimization characteristics, the equipment operation status can be guaranteed by increasing the verification frequency; Through the regional planning module and the class sequence generation module, the management area can be planned and analyzed and an equipment type sequence can be generated. The equipment type sequence can provide a decision-making reference for the degree of replenishment and calibration frequency optimization of different types of equipment. Since the water areas of different management areas are different, their sensor working environments are also different, so the replenishment needs and calibration optimization needs of different types of equipment are also different. According to the equipment type sequence, targeted collection terminal operation optimization can be carried out for different management areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 A system block diagram of the present invention as a whole; Figure 2 This is a system block diagram of a data verification subsystem and an abnormality analysis subsystem in Embodiment 1 of the present invention; Figure 3 This is a flow chart of regional management in Embodiment 1 of the present invention; Figure 4 This is a system block diagram of the type optimization subsystem in Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0019] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than 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.

[0020] Hydrological and water resources detection data analysis is the process of in-depth processing, analysis, and mining of hydrological and water resources related data, aiming to extract valuable information from the data and provide a basis for water resources management and decision-making; generally, statistics are conducted from aspects such as data collection and preprocessing, descriptive statistical analysis, correlation analysis and evaluation, trend analysis and prediction, spatial distribution and difference analysis, pollution source identification and evaluation, regression analysis and modeling, result visualization and reporting; however, the above methods can only be applied and analyzed to valid data in hydrological and water resources data, and abnormal data obtained through data cleaning and equipment calibration cannot be applied. In fact, abnormal data has a high research value in improving the operating status of acquisition terminals and the base of valid data.

[0021] like Figure 1 As shown, a hydrological and water resources detection data analysis system includes a data verification subsystem, an abnormality analysis subsystem and a type optimization subsystem, and the data verification subsystem, the abnormality analysis subsystem and the type optimization subsystem are communicatively connected in sequence. Example

[0022] like Figure 2As shown, the data verification subsystem includes a verification analysis module; the abnormality analysis subsystem includes a regional management module and a fault analysis module, and the verification analysis module, the regional management module and the fault analysis module are communicatively connected in sequence.

[0023] The verification and analysis module is used to regularly receive redundant hydrological data from the hydrological station network and send the redundant hydrological data to the abnormal analysis subsystem. The redundant hydrological data includes duplicate data, erroneous data and abnormal data obtained through data cleaning and equipment verification. The data cleaning process generally includes: Missing value cleaning: including identifying missing values ​​and processing them. The processing methods include deletion, mean, median, mode filling, etc.; Format content cleaning: such as converting strings to numbers, or formatting numbers into specific string forms, etc.; Logical error cleaning: identifying possible erroneous data or abnormal data through statistical analysis methods, such as using common sense rules, business-specific rules, etc. to check data values; Duplicate data cleaning: identifying and deleting duplicate or redundant entries in the data set; Data normalization: standardizing data into data sets with the same dimension and relative size relationship. Equipment verification is the process of regularly verifying the data collection accuracy, data transmission timeliness and integrity of the hydrological data collection terminal.

[0024] It should be noted that the process of abnormal feature analysis of hydrological redundant data in hydrological and water resources detection data in the present application does not conflict with the processes of descriptive statistical analysis (basic statistical quantity calculation and data distribution pattern description), correlation analysis and evaluation (correlation coefficient calculation and significance test) and trend analysis and prediction (time series analysis and prediction model construction) for effective data in traditional hydrological and water resources detection data analysis systems. The processing of hydrological redundant data is based on the processing of effective data and is an analysis process of the operating status of hydrological data detection terminal equipment under different water characteristics and different operating environments.

[0025] like Figure 3 As shown in FIG. 1 , the regional management module is used to perform regional management of the hydrological station network. The regional management process includes the following steps: Step S1: Generate a management cycle, mark the coverage area of ​​the hydrological station in the hydrological station network as the management area of ​​the hydrological station, mark the hydrological redundant data corresponding to the management area within the management cycle as invalid data, and mark the terminal device corresponding to the invalid data as an abnormal device; Step S2: Mark the number of invalid data corresponding to the abnormal device as the invalid value of the abnormal device, and the invalid values ​​of all abnormal devices constitute an invalid set. The invalid value indicates the frequency of abnormal operation of the abnormal device during the management period. The larger the value of the invalid value, the higher the frequency of abnormal operation of the abnormal device during the management period, and the greater the probability of failure. It should be noted that since different types of sensors collect different parameters, their installation and operation environments are also different. For example, a water level sensor that runs on the water surface for a long time is prone to equipment failure due to corrosion and rust. For example, a rainfall sensor is easily hit by rain during heavy rain, resulting in reduced data collection accuracy. Step S3: Perform fault screening on the invalid set: sum and average all elements in the invalid set to obtain the fault handling value of the invalid set, mark the abnormal devices whose invalid values ​​are not less than the fault handling value as prominent objects, mark the abnormal devices whose invalid values ​​are less than the fault handling value as neglected objects, and mark the ratio of the number of prominent objects to neglected objects as the prominent coefficient of the invalid set; Step S4: Compare the prominence coefficient with the preset prominence threshold: if the prominence coefficient is greater than or equal to the prominence threshold, the element with the largest value and the element with the smallest value in the invalid set are respectively classified into the fault set and the neglect set, and step S3 is performed again; if the prominence coefficient is less than the prominence threshold, the screened invalid set is marked as the refined set; Step S5: Send the optimized set, the faulty set and the ignored set to the fault analysis module; Carry out regional management of the hydrological station network, screen out invalid sets consisting of invalid values, provide data support for equipment failure status and data acquisition accuracy analysis based on fault sets and optimized sets, process redundant data of the coverage area of ​​each hydrological station in the hydrological station network in a regional analysis manner, and make full use of abnormal data in the hydrological data.

[0026] The fault analysis module is used to analyze the equipment fault status of the hydrological station: the ratio of the number of elements in the fault set to the number of abnormal devices is marked as the fault performance value of the management area. It should be noted that the number of elements in the fault set represents the number of detection terminal devices with high frequency of operation abnormalities in the management area. That is to say, the larger the value of the fault performance value, the greater the number of detection terminal devices with high frequency of operation abnormalities in the management area. In order to ensure that there is sufficient effective data for hydrological and water resources management, statistics and prediction, the demand for equipment replenishment in the management area is higher. The fault performance value is compared with the preset fault performance threshold: if the fault performance value is greater than or equal to the fault performance threshold, it is determined that the management area has equipment failure characteristics, and an equipment replenishment signal is generated and sent to the mobile phone terminal of the management personnel; if the fault performance value is less than the fault performance threshold, it is determined that the management area does not have equipment failure characteristics.

[0027] Perform precision analysis on the management area: sum and average all elements in the precision set to obtain the optimization necessary value of the management area. It should be noted that the optimization necessary value is compared with the preset optimization necessary threshold: if the optimization necessary value is less than the optimization necessary threshold, the management area is judged not to have the optimization necessary characteristics; if the optimization necessary value is greater than or equal to the optimization necessary threshold, the management area is judged to have the optimization necessary characteristics, generate a verification optimization signal and send the verification optimization signal to the mobile phone terminal of the manager; analyze the equipment failure status of the hydrological station, and feedback the abnormal frequency of the overall detection terminal of the management area through the proportion of the number of fault set elements in the abnormal equipment, so as to supplement the terminal equipment for the management area with equipment failure characteristics, so as to prevent the failure rate of the collection terminal in the same area from being too high, resulting in insufficient effective data provided by the normally operating collection terminal. For the management area with the optimization necessary characteristics, the equipment operation status can be guaranteed by increasing the verification frequency. Example

[0028] like Figure 4 As shown, the type optimization subsystem includes a regional planning module and a class sequence generation module; the regional planning module is communicatively connected with the class sequence generation module.

[0029] The regional planning module is used to conduct planning and management analysis on the management area of ​​the hydrological station network: the ratio of the water area value of the management area to the total area value of the management area is marked as the planning coefficient of the management area, the planning range is composed of the maximum planning coefficient and the minimum planning coefficient of the management area of ​​the hydrological station network, the planning range is divided into several planning intervals, the management area whose planning coefficient is within the planning interval is marked as the matching area of ​​the planning interval, and the matching area is sent to the class sequence generation module.

[0030] For example, there are ten management areas (AJ) whose planning coefficients (two decimal places) are 0.22, 0.47, 0.36, 0.42, 0.27, 0.33, 0.58, 0.39, 0.30 and 0.43 respectively. Then the planning range is composed of the minimum planning coefficient 0.22 and the maximum planning coefficient 0.58. When the number of planning intervals is five, the five planning intervals are [0.22, 0.292], (0.292, 0.364], (0.364, 0.436], (0.436, 0.508] respectively. and (0.508, 0.58]. The planning interval is only the interval range composed of planning coefficients. Its purpose is to cluster the management areas with similar water area ratios. The matching areas corresponding to these five planning intervals are (A, E), (C, F, I), (D, H, J), (B) and (G). It should be noted that all the hydrological redundant data corresponding to the matching areas (with similar water area ratios) within the same planning interval can be comprehensively analyzed, and the equipment type sequence corresponding to the obtained planning area can also be applied to all matching areas within the planning area.

[0031] The class sequence generation module is used to perform equipment type sequence analysis on the management area of ​​the hydrological station network: count the abnormal equipment in all matching areas within the planning interval, mark the number of abnormal equipment corresponding to the same equipment type as the abnormal value of the equipment type, arrange the equipment types in descending order of the abnormal values ​​to obtain the equipment type sequence of the planning interval, and send the equipment type sequences of all planning intervals to the mobile phone terminals of the managers.

[0032] The terminal equipment types for hydrological and water resources data include at least: Water level sensor, one of the most commonly used hydrological monitoring sensors, is used to measure the height of the water level. According to its working principle, water level sensors are divided into float type, pressure type, acoustic wave type, optical type and other types; Flow sensors are used to measure water flow. They can be divided into two types: direct method and indirect method. Direct methods include rotating blade type, electromagnetic type, ultrasonic type, etc., which are simple and easy to use; indirect methods include pressure difference method, thermal conductivity method, etc., which indirectly calculate the flow rate by measuring the physical quantity of water flow, and are suitable for some complex occasions or occasions that require high precision. Water temperature sensor is a sensor used to measure water temperature. It is widely used in temperature detection of water bodies such as ponds, lakes, and rivers. According to the measurement principle, water temperature sensors are divided into two types: contact and non-contact. Contact sensors require the sensor to contact the surface of the water body, while non-contact sensors use infrared, microwave and other principles to measure the temperature of the water surface. pH sensor, a sensor used to measure the pH value of water, can be used to monitor the pH value changes of drinking water, industrial wastewater and other water bodies; Turbidity sensor is a sensor used to measure the concentration of suspended matter in water. It can be used in water quality monitoring, drinking water purification and other fields. According to the working principle of the sensor, turbidity sensors are divided into scattered light method, transmitted light method, spectral scattering method and other types.

[0033] The operating environment and accuracy requirements of the above sensors are different. When they are installed and tested in different management areas, the probability of failure is also different. Therefore, it is necessary to find the corresponding equipment type sequence through the planning interval to make optimization decisions on equipment replenishment and calibration frequency. The specific equipment replenishment decision process can be set by the management personnel according to the equipment type sequence, or the replenishment quantity can be automatically set according to the proportion.

[0034] Conduct planning and management analysis on the management area and generate an equipment type sequence. The equipment type sequence provides a decision reference for the degree of replenishment and calibration frequency optimization of different types of equipment. Due to the different water areas in different management areas, the working environment of the sensors is also different. Therefore, there are differences in the replenishment needs and calibration optimization needs of different types of equipment. According to the equipment type sequence, targeted collection terminal operation optimization can be carried out for different management areas.

[0035] A hydrological and water resources detection data analysis system, when working, regularly receives hydrological redundant data from a hydrological station network and sends the hydrological redundant data to an abnormal analysis subsystem, generates a management cycle, marks the hydrological station coverage area in the hydrological station network as the management area of ​​the hydrological station, marks the hydrological redundant data corresponding to the management area within the management cycle as invalid data, marks the terminal equipment corresponding to the invalid data as abnormal equipment; marks the number of invalid data corresponding to the abnormal equipment as the invalid value of the abnormal equipment, and the invalid values ​​of all abnormal equipment constitute an invalid set; performs fault screening processing on the invalid set and obtains an optimized set, a fault set and a neglected set, and performs optimization decision analysis on the management area through the optimized set, the fault set and the neglected set.

[0036] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0037] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0038] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. 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 hydrological and water resources detection data analysis system, characterized in that: Including verification and analysis module, area management module and fault analysis module; The verification and analysis module is used to periodically receive the hydrological redundant data of the hydrological station network and send the hydrological redundant data to the regional management module; The regional management module is used to perform regional management of the hydrological station network according to the hydrological redundant data and obtain the optimal set, the fault set and the neglected set; and send the optimal set, the fault set and the neglected set to the fault analysis module; The fault analysis module is used to analyze the equipment fault status of the hydrological station, generate an equipment supplement signal when the management area has equipment fault characteristics and send the equipment supplement signal to the mobile phone terminal of the manager; generate a verification optimization signal when the management area has necessary optimization characteristics and send the verification optimization signal to the mobile phone terminal of the manager.

2. A hydrological and water resources detection data analysis system according to claim 1, characterized in that: The hydrological redundant data includes duplicate data, erroneous data and abnormal data obtained through data cleaning and equipment verification; The data cleaning process includes missing value cleaning, format content cleaning, logical error cleaning, duplicate data cleaning and data normalization.

3. A hydrological and water resources detection data analysis system according to claim 2, characterized in that: The specific process of regional management of the hydrological station network by the regional management module includes: generating a management cycle, marking the coverage area of ​​the hydrological stations in the hydrological station network as the management area of ​​the hydrological station, marking the hydrological redundant data corresponding to the management area within the management cycle as invalid data, marking the terminal devices corresponding to the invalid data as abnormal devices, marking the number of invalid data corresponding to the abnormal devices as the invalid value of the abnormal devices, forming an invalid set from the invalid values ​​of all abnormal devices, performing fault screening on the invalid set and obtaining a fault set, an optimized set and a neglected set.

4. A hydrological and water resources detection data analysis system according to claim 3, characterized in that: The specific process of fault screening for invalid sets includes: summing up and averaging all elements in the invalid set to obtain the fault handling value of the invalid set, marking abnormal devices whose invalid values ​​are not less than the fault handling value as prominent objects, marking abnormal devices whose invalid values ​​are less than the fault handling value as ignored objects, marking the ratio of the number of prominent objects to the number of ignored objects as the prominent coefficient of the invalid set, comparing the prominent coefficient with the preset prominent threshold and marking the prominent set, the excellent set and the ignored set through the comparison results.

5. A hydrological and water resources detection data analysis system according to claim 4, characterized in that: The specific process of comparing the protrusion coefficient with the preset protrusion threshold includes: if the protrusion coefficient is greater than or equal to the protrusion threshold, the element with the largest value and the element with the smallest value in the invalid set are respectively classified into the fault set and the neglect set, and the protrusion coefficient of the invalid set is recalculated and compared with the protrusion threshold, and so on, until the protrusion coefficient is less than the protrusion threshold; If the prominence coefficient is less than the prominence threshold, the filtered invalid set is marked as an excellent set.

6. A hydrological and water resources detection data analysis system according to claim 5, characterized in that: The specific process of determining whether a management area has equipment failure characteristics includes: marking the ratio of the number of elements in the fault set to the number of abnormal devices as the fault manifestation value of the management area, and comparing the fault manifestation value with a preset fault manifestation threshold: if the fault manifestation value is greater than or equal to the fault manifestation threshold, then the management area is determined to have equipment failure characteristics, and an equipment supplement signal is generated and sent to the mobile phone terminal of the management personnel; if the fault manifestation value is less than the fault manifestation threshold, then the management area is determined not to have equipment failure characteristics.

7. A hydrological and water resources detection data analysis system according to claim 6, characterized in that: The specific process of determining whether a management area has the necessary features for optimization includes: summing and averaging all elements in the optimization set to obtain the necessary optimization value for the management area, and comparing the necessary optimization value with the preset necessary optimization threshold: if the necessary optimization value is less than the necessary optimization threshold, then the management area is determined not to have the necessary optimization features; if the necessary optimization value is greater than or equal to the necessary optimization threshold, then the management area is determined to have the necessary optimization features, generating a verification optimization signal and sending the verification optimization signal to the mobile phone terminal of the management personnel.

8. A hydrological and water resources detection data analysis system according to claim 7, characterized in that: It also includes a regional planning module and a class sequence generation module, wherein the regional planning module is used to perform planning management analysis on the management area of ​​the hydrological station network to obtain a planning interval and a matching area of ​​the planning interval, and send the planning interval and the matching area of ​​the planning interval to the class sequence generation module; The class sequence generation module is used to perform equipment type sequence analysis on the management area of ​​the hydrological station network and obtain the equipment type sequence of the planned interval, and send the equipment type sequence of all planned intervals to the mobile phone terminal of the management personnel.

9. A hydrological and water resources detection data analysis system according to claim 8, characterized in that: The process of obtaining the planning interval and the matching area of ​​the planning interval includes: marking the ratio of the water area value of the management area to the total area value of the management area as the planning coefficient of the management area, forming a planning range with the maximum planning coefficient and the minimum planning coefficient of the hydrological station network management area, dividing the planning range into several planning intervals, and marking the management area whose planning coefficient is within the planning interval as the matching area of ​​the planning interval.

10. A hydrological and water resources detection data analysis system according to claim 9, characterized in that: The process of obtaining the device type sequence includes: counting the abnormal devices in all matching areas within the planning interval, marking the number of abnormal devices corresponding to the same device type as the abnormal value of the device type, and arranging the device types in descending order of the abnormal values ​​to obtain the device type sequence of the planning interval.

Images