A geoelectric station network comprehensive management and online output service system

Abstract

This invention discloses a comprehensive management and online output service system for geoelectric radio networks, relating to the field of geoelectric radio network informatization. It includes: a data layer that acquires and stores multi-source geoelectric observation data from various radio stations; a monitoring layer that monitors the data quality of the multi-source geoelectric observation data; an output layer that automatically generates products online based on the multi-source geoelectric observation data; a management layer that manages the network and the system; and an application layer that provides network product services based on the products generated by the output layer, and provides network information services to the management layer. This invention not only solves the core challenges of digital and networked management of geoelectric radio networks from a technical architecture perspective, but also comprehensively improves the management level, quality accuracy, and application value of geoelectric observation data through the organic combination of full-process quality control, efficient collaboration, diversified output, and standardized services. It provides strong technical support for disaster monitoring and forecasting, and related scientific research, possessing significant practical value and promotional significance.

Description

Technical Field

[0001] This invention relates to the field of information technology for local radio networks, and more specifically to a comprehensive management and online output service system for local radio networks. Background Technology

[0002] Geoelectric observation is an important means of obtaining data related to the electrical properties of the Earth's interior. Geoelectric observation data provides key support for disaster monitoring and forecasting, scientific research, and is of great significance for ensuring public safety and advancing research in related disciplines.

[0003] my country has established a massive fixed geoelectric observation network, encompassing numerous stations of various types. These stations generate a vast amount of observational data daily, providing crucial support for related monitoring, forecasting, and scientific research. However, the rational and standardized management of these stations and their data still faces many challenges. Traditional management methods rely on manual processing, making data quality assessment, station operation monitoring, and product output time-consuming, labor-intensive, and inefficient, failing to meet the high demands for data quality and service timeliness. Even with the digital and network-based transformation of the geoelectric network, challenges remain regarding the management of the vast number of stations, station operation, observation system operation, online management of collected data, and especially the evaluation of observational data.

[0004] Therefore, how to build an efficient integrated management and online output service system for local radio networks is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] In view of this, the present invention provides a comprehensive management and online output service system for local radio networks to solve the above problems.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: This invention discloses a comprehensive management and online output service system for a local radio network, comprising: a data layer, a monitoring layer, an output layer, a management layer, and an application layer; The data layer acquires and stores multi-source geoelectric observation data from radio stations in various locations; The monitoring layer performs data quality monitoring on the multi-source geoelectric observation data; The output layer automatically produces products online based on the multi-source geoelectric observation data. The management layer is responsible for network management and system management of the system. The application layer provides network product services based on the products created by the output layer, and provides network information services to the management layer.

[0007] Furthermore, the multi-source geoelectric observation data includes: raw geoelectric observation data, preprocessed data, data products, basic information, observation logs, work logs, detection reports, earthquake catalogs, and DST information from various radio stations.

[0008] Furthermore, the data quality monitoring of the multi-source geoelectric observation data specifically includes: daily monitoring, monthly monitoring, and annual monitoring; The daily monitoring includes: automatically detecting multi-source geoelectric observation data based on data evaluation indicators or evaluation models, and automatically generating and sending daily reports. The monthly monitoring includes: calculating quality indicators for multi-source geoelectric observation data each month, monthly review, monthly evaluation of monitoring reports, regional quality evaluation, data tracking and analysis, dynamic curve evaluation, monthly evaluation results, and production of monthly operation reports; The annual monitoring includes: annual quality assessment of multi-source geoelectric observation data, manual review, correction of review items, and summary and report generation of overall quality evaluation.

[0009] Furthermore, the automatic detection of multi-source geoelectric observation data specifically includes: Error data detection: The system automatically reads raw ground resistivity data or preprocessed hourly observation data, and automatically detects error data based on the error data judgment index; Gross error detection: The system automatically reads raw ground resistivity data or preprocessed hourly observation data, and uses a gross error detection model to detect gross error data; Abrupt change data detection: The system automatically reads raw resistivity data or preprocessed hourly observation data and uses the abrupt change data detection model to detect abrupt change data.

[0010] Furthermore, the calculation of the quality indicators includes: monthly timed relative mean square error of earth resistivity, monthly accuracy, monthly dispersion, integrity rate, continuity rate, as well as automatic calculation of correlation coefficient, difference, continuity rate, integrity rate, and curve dynamic indicators of the earth electric field.

[0011] Furthermore, the online automatic product creation based on the multi-source geoelectric observation data specifically includes: Station products: Calculate and generate hourly average, weighted daily average, daily average, five-day average, monthly average, annual average, accuracy, correlation coefficient, and difference based on preprocessed data; Network products: Calculate product data based on data processing models, including: spatial distribution of relative changes in ground resistivity, emergency products, ground electric field vector mode and azimuth, ground current field vector mode and azimuth, and complete image product production.

[0012] Furthermore, the aforementioned network management specifically includes: basic information management, standards and specifications management, and station management; The system management specifically includes: access control, notifications and announcements, user management, log management, access statistics, and data backup.

[0013] Furthermore, the aforementioned network product services specifically include: display of product images and product data services, sharing services for network operation reports and earthquake event briefings, and support for external data service interfaces; The aforementioned network information service specifically includes: querying and displaying site distribution, network management information, and quality monitoring information.

[0014] As can be seen from the above technical solution, compared with the prior art, this invention provides a comprehensive management and online output service system for geoelectric radio networks. Through online collaborative operation, it improves the timeliness and efficiency of geoelectric station network management, data output, and services, saving manpower and material costs. Furthermore, it proposes daily, monthly, and annual monitoring models for observation data, significantly improving the accuracy of data quality. A diversified product system outputs, including spatial distribution maps of relative changes in resistivity, emergency products, geoelectric field vector models and azimuths, geocurrent field vector models and azimuths, annual analysis of resistivity, and annual analysis of geoelectric fields, meets the core needs of multiple scenarios. This invention not only solves the core challenges of digital and networked management of geoelectric radio networks from a technical architecture perspective, but also comprehensively improves the management level, quality accuracy, and application value of geoelectric observation data through the organic combination of full-process quality control, efficient collaboration, diversified outputs, and standardized services. It provides strong technical support for disaster monitoring and forecasting, and related scientific research, possessing significant practical value and promotional significance. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the overall structure of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] This invention discloses a comprehensive management and online output service system for local radio networks, such as... Figure 1 As shown, it includes: data layer, monitoring layer, output layer, management layer and application layer; The data layer acquires and stores multi-source geoelectric observation data from radio stations in various locations; The monitoring layer monitors the data quality of multi-source geoelectric observation data; The production layer automatically generates products online based on multi-source geoelectric observation data. The management team is responsible for network management and system management of the system. The application layer provides network product services based on the products created by the output layer, and provides network information services to the management layer.

[0019] In one specific embodiment, the multi-source geoelectric observation data includes: raw geoelectric observation data, preprocessed data, data products, basic information, as well as observation logs, work logs, detection reports, earthquake catalogs, and DST information from various geoelectric stations.

[0020] In one specific embodiment, data quality monitoring is performed on multi-source geoelectric observation data, specifically including: daily monitoring, monthly monitoring, and annual monitoring; Routine monitoring includes: automatically detecting multi-source geoelectric observation data based on data evaluation indicators or evaluation models, and automatically generating and sending daily reports.

[0021] Monthly monitoring includes: calculating quality indicators for multi-source geoelectric observation data each month, monthly review, monthly evaluation of monitoring reports, regional quality evaluation, data tracking and analysis, dynamic curve evaluation, monthly evaluation results, and production of monthly operation reports.

[0022] Annual monitoring includes: annual quality assessment of multi-source geoelectric observation data, manual review, correction of review items, and summary and report generation of overall quality evaluation.

[0023] In one specific embodiment, automatic detection of multi-source geoelectric observation data includes: error data detection, gross error data detection, and abrupt data detection. Specifically, multi-source geoelectric observation data includes various geoelectric observation data from multiple geoelectric observation stations, such as raw geoelectric observation data including georesistivity, geoelectric field, and electromagnetic disturbance data. The following explanation uses georesistivity as an example to illustrate error data detection, gross error data detection, and abrupt data detection.

[0024] Error data detection: The system automatically reads raw ground resistivity data or preprocessed hourly observation data, and automatically detects error data based on the error data judgment index.

[0025] Specifically, the system automatically reads raw or preprocessed data from the database, and if any... , , If erroneous data is found, check whether the observation log has been filled in and whether preprocessing has been performed. If preprocessing has not been performed or the observation log for the reason for the data change has not been filled in, it should be automatically marked and recorded in the monitoring list.

[0026] Gross error detection: The system automatically reads raw ground resistivity data or preprocessed hourly observation data and uses a gross error detection model to detect gross error data.

[0027] Specifically, the system automatically reads raw or pre-processed hourly observation data of ground resistivity. Data that meets the following conditions is considered gross error data, and the program automatically determines that the data is not gross error data: The relative standard deviation of hourly values Data, ; or data where the absolute value of the difference between the hourly value and the normal value within a consecutive 4-hour period (excluding 4 hours) is greater than 5% of the normal value (the average of the previous two days' daily averages). ; in For the i-th observation, This is the average value of the previous day (the average value of the previous - 1 day after preprocessing). This is the daily average of the previous two days (daily average after preprocessing for the previous two days). The above is the automatic resistivity processing algorithm. If... After removal, the corresponding mean squared error and natural potential difference It is also automatically removed. This automatic processing algorithm is mandatory. If the daily average of the previous two days is not available, the daily average of the previous day will be used. Even if the daily average of the previous two days or the previous day exists, if it is not available, the out-of-tolerance calculation will not be performed. Data detected as gross errors, if not removed in the preprocessed data, should be stored in the monitoring list.

[0028] Abrupt change data detection: The system automatically reads raw resistivity data or preprocessed hourly observation data and uses the abrupt change data detection model to detect abrupt change data.

[0029] Specifically, data that meets the following conditions is considered mutation data and should be labeled accordingly: 4 consecutive hours (inclusive) or more The data.

[0030] Alternatively, the resistivity values ​​of each land surface observed over 4 consecutive hours (including 4 hours or more). (i=1, 2, 3, 4) Relative to the daily average resistivity of the previous day The changes were all greater than 2%, that is... and Exceeding the monthly average of the daily average resistivity and the monthly average of the root mean square deviation of the local area for the past month 3 times, that is The data in question is mutation data.

[0031] This also includes step correction for preprocessed data after abrupt change labeling. Specifically, steps caused by changes in instrument parameters, calibration, etc., result in a quantitative additive or subtractive constant relationship between the data before and after the step. Based on the difference between the data before and after the step, the data before the step is corrected to eliminate the step. In resistivity step correction, only when calculating the relative change distribution map, the additive or subtractive constant is applied to the step of the monthly average. This can be done interactively on the dynamic curve, with the computer automatically calculating the step amount, and then fine-tuning is performed manually.

[0032] Automatic daily report creation and delivery feedback, specifically including: Daily verification: Based on the station's basic information, observation environment information, observation device information, observation logs, etc., the local radio network's resistivity and geoelectric field observation data are reviewed. Curves, logs and data tracking and analysis records, previous monitoring daily reports, etc. can be retrieved at will. Daily Report Feedback: Based on the daily monitoring report information, the station can provide online station feedback and subject confirmation functions.

[0033] It allows for visual operations of the above-mentioned daily quality checks, reviews, and feedback, and has convenient functions such as downloading, adding, deleting, saving, and querying; as well as DST real-time data collection and display.

[0034] In one specific embodiment, the quality index calculation includes: monthly timed relative mean square error of ground resistivity, monthly accuracy, monthly dispersion, integrity rate, as well as correlation coefficient, difference, continuity rate, integrity rate, curve dynamics of the ground electric field, and other quantitative quality indicators are automatically calculated, and can be queried and downloaded at any time.

[0035] The following uses land resistivity as an example to explain integrity rate, relative root mean square error, monthly accuracy, and monthly dispersion, specifically including: (1) Calculate the completeness rate of preprocessed data for each site monthly; (2) Calculate the relative mean square error of the hourly resistivity each month to obtain the monthly average value; (3) Calculate the daily resistivity of the earth for 24 hours each month and obtain the monthly average value; (4) Calculate the monthly dispersion of the daily average resistivity of the land.

[0036] (1) Calculate the completeness rate of preprocessed data for each site monthly, using the following formula: ; Where m is the number of test items. Numerator: Includes data with variance less than 10%.

[0037] (2) Calculate the relative mean square error of the hourly resistivity each month to obtain the monthly average value. The specific formula is as follows: ; Where: N refers to the number of channels at the station, D refers to the number of days in the month, and H is the number of hourly observation data in one day; It is the mean square error of the resistivity measurements taken on the j-th track, the i-th day, and the k-th decimal place of the month. It represents the resistivity measurement values ​​for the j-th track, the i-th day, and the k-th hour of the current month.

[0038] (3) Calculate the daily resistivity of the land over 24 hours each month to obtain the monthly average value. The specific steps are as follows: Step 1: The system queries the preprocessed hourly resistivity data for that day and night, first removing erroneous and gross error data. Step 2: Calculate the initial daily average value and initial mean square deviation ; The formula for calculating the initial daily average is: (Calculate the mean of the data after removing erroneous and outlier data); The formula for calculating the initial mean square error is: ,in The number of hourly values ​​included in the daily average calculation.

[0039] Step 3: Discard hourly values Compared with the initial daily average The difference is greater than twice the initial mean square error (i.e.) Discard data that is greater than twice the mean squared error.

[0040] Step 4: Daily accuracy calculation steps: The formula for calculating the weighted daily average resistivity is: ,in These are hourly observations. This represents the number of remaining hour values ​​to be included in the calculation after step three above. Let be the mean squared error of the i-th observation; The formula for calculating the mean squared error is: (The mean squared error of the remaining data is calculated using the same formula). The accuracy calculation formula is as follows: (Directly divide the newly generated mean square error value by the square root of n); Relative daily accuracy: (Daily average accuracy divided by the weighted daily average of resistivity).

[0041] (4) Check the monthly dispersion of the daily average resistivity of the land every month. The specific steps are as follows: Step 1: Query the daily weighted average resistivity for the current month; Step 2: Calculate the weighted monthly average The average of the daily weighted averages is the monthly average. Step 3: Calculate the monthly mean variance, using the following formula: ;in, Daily weighted average The number of land resistivity values ​​included in the weighted daily average calculation for the current month. This is the monthly average.

[0042] Step 4: Calculate the monthly dispersion, using the following formula: ,in This is the monthly average of the weighted daily averages for the current month.

[0043] Monthly review in monitoring includes: reviewing the monthly monitoring report, tracking and analysis records, work logs, data quality, dynamic curves, retrieving weekly review results and daily report feedback results and quality indicator data, etc., for monthly review.

[0044] The monthly monitoring report evaluation includes: regular, automatic scoring of the daily monitoring reports across the entire network according to scoring rules. The scoring rules can be modified at any time, and include functions such as deletion, modification, addition, download, and update.

[0045] The monthly monitoring of regional quality evaluation includes: automatically scoring the quality of the regional surveillance network periodically according to scoring rules. The scoring rules can be modified at any time, with functions such as deletion, modification, addition, download, and update.

[0046] Monthly monitoring data tracking and analysis includes: providing data tracking and analysis record query and statistical functions under various combinations of conditions; retrieving problem records, querying curves, logs and previous records and review status; automatically retrieving the monthly review results of subjects in the data tracking and analysis records, and supporting online score correction on the page.

[0047] The monthly monitoring and evaluation results and operation report generation include: comprehensive evaluation of each station's quality indicators, daily operation, data tracking and analysis, dynamic curves, and work logs based on scoring rules. This can be achieved online automatically or through human-computer interaction, and includes functions such as deletion, modification, addition, download, and updating. It also generates the previous month's report online based on the station network overview, network operation, typical events, outputs and services, and other issues, and allows modification, addition, deletion, download, and updating of any module. The comprehensive monthly quality monitoring system includes functions for importing, statistically analyzing, automatically scoring, exporting, and displaying regional station network quality results from different disciplines; it also supports multiple methods for generating relevant evaluation results and reports, including scheduled generation, online recalculation, online review, and online editing.

[0048] In one specific embodiment, annual monitoring includes: annual quality assessment of multi-source geoelectric observation data, manual review, correction of review items, and overall quality summary and report generation. Specifically: Annual Quality Assessment: The system has functions such as modifying scoring rules, automatically calculating, querying, reviewing, summarizing, and exporting annual evaluation indicators.

[0049] Manual review: The system has online scoring and review functions for monthly reports, quarterly reports, temporary reports, annual reports, data tracking, and annual reports.

[0050] Key items for review and correction: The system can modify observation environment and device information online, and query relevant data, logs, tracking analysis records, and historical quality evaluation records online to assist in better manual review.

[0051] Summary and report generation: The system can automatically obtain evaluation results such as basic information, daily maintenance, data tracking, and observation reports, and generate evaluation reports. It can also statistically analyze and download the calculation results of network data quality indicators and various report documents.

[0052] In one specific embodiment, product creation is performed online automatically based on multi-source geoelectric observation data, specifically including: Station products: Calculate and generate hourly average, weighted daily average, daily average, five-day average, monthly average, annual average, accuracy, correlation coefficient, and difference based on preprocessed data; Network products: Calculate product data based on data processing models, including: spatial distribution of relative changes in ground resistivity, emergency products, ground electric field vector mode and azimuth, ground current field vector mode and azimuth, and complete image product production.

[0053] In a specific embodiment, network management includes: basic information management, standards and specifications management, and station management. System management specifically includes: access control, notifications and announcements, user management, log management, access statistics, and data backup.

[0054] Specifically, the network management functions mainly include basic information, notices and announcements, standards and specifications, network technical requirements, station management, and earthquake information browsing.

[0055] Basic information includes: station information, instrument information, measuring point information, observation site information, and measurement item information. Basic information is the cornerstone of interpreting station observation data; every change in data relies on accurate and clear basic information. This platform allows for convenient and quick filling, modification, uploading, and review of basic information.

[0056] Standards and Specifications: The operation of a good geostationary network cannot be separated from the guidance of standards and specifications. This section covers various standards and specifications, including geostationary network design specifications, instrument network access specifications, geostation construction specifications, observation method standards, national standards for electromagnetic observation environments, and technical requirements documents such as evaluation methods and operational details. This section can be viewed on its homepage.

[0057] Station Management: Provides near real-time checks on the distribution and operational quality of the geostationary power grid for the previous day and current month, and allows quick access to information from any station. It also provides near real-time access to the national earthquake catalog for subsequent quality monitoring; rapidly generates emergency geostationary power products for a certain area within two hours of an earthquake; and provides near real-time alarm reminders for special events (geostationary storms, high-voltage direct current transmission events).

[0058] Notices and announcements: mainly publishes business notices and information releases for the disciplines.

[0059] In a specific embodiment, the network product services specifically include: display and product data services of product maps (monthly / annual relative changes in earth resistivity, regional distribution maps of earth electric field, regional distribution maps of earth current field, annual reports on earth resistivity observation, annual reports on earth electric field observation, high-voltage direct current transmission event reports, earth storm event reports, daily distribution maps of earth electric field variation, and spectral characteristic maps of earth electric field, etc.), sharing services of network operation reports and earthquake event briefings, and support for external data service interfaces; The information service for the monitoring network specifically includes: querying and displaying information on site distribution, network management (environmental interference information, observation device information, basic information, daily operation and maintenance information, observation reports, site change information, etc.), and quality monitoring information.

[0060] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0061] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A comprehensive management and online output service system for a local radio network, characterized in that, include: Data layer, monitoring layer, output layer, management layer, and application layer; The data layer acquires and stores multi-source geoelectric observation data from radio stations in various locations; The monitoring layer performs data quality monitoring on the multi-source geoelectric observation data; The output layer automatically produces products online based on the multi-source geoelectric observation data. The management layer is responsible for network management and system management of the system. The application layer provides network product services based on the products created by the output layer, and provides network information services to the management layer.

2. The integrated management and online output service system for a local radio network according to claim 1, characterized in that, The multi-source geoelectric observation data includes: raw geoelectric observation data, preprocessed data, data products, basic information, observation logs, work logs, detection reports, earthquake catalogs, and DST information from various radio stations.

3. The integrated management and online output service system for a local radio network according to claim 1, characterized in that, The data quality monitoring of the multi-source geoelectric observation data specifically includes: daily monitoring, monthly monitoring, and annual monitoring; The daily monitoring includes: automatically detecting multi-source geoelectric observation data based on data evaluation indicators or evaluation models, and automatically generating and sending daily reports. The monthly monitoring includes: calculating quality indicators for multi-source geoelectric observation data each month, monthly review, monthly evaluation of monitoring reports, regional quality evaluation, data tracking and analysis, dynamic curve evaluation, monthly evaluation results, and production of monthly operation reports; The annual monitoring includes: annual quality assessment of multi-source geoelectric observation data, manual review, correction of review items, and summary and report generation of overall quality evaluation.

4. The integrated management and online output service system for a local radio network according to claim 3, characterized in that, The automatic detection of multi-source geoelectric observation data specifically includes: Error data detection: The system automatically reads raw ground resistivity data or preprocessed hourly observation data, and automatically detects error data based on the error data judgment index; Gross error detection: The system automatically reads raw ground resistivity data or preprocessed hourly observation data, and uses a gross error detection model to detect gross error data; Abrupt change data detection: The system automatically reads raw resistivity data or preprocessed hourly observation data and uses the abrupt change data detection model to detect abrupt change data.

5. The integrated management and online output service system for a local radio network according to claim 3, characterized in that, The quality index calculations include: monthly timed relative mean square error, monthly accuracy, monthly dispersion, and integrity rate of the ground resistivity, as well as the automatic calculation of the correlation coefficient, difference, continuity rate, integrity rate, and dynamic index of the ground electric field.

6. The integrated management and online output service system for a local radio network according to claim 3, characterized in that, The online automatic product creation based on the multi-source geoelectric observation data specifically includes: Station products: Calculate and generate hourly average, weighted daily average, daily average, five-day average, monthly average, annual average, accuracy, correlation coefficient, and difference based on preprocessed data; Network products: Based on the data processing model, calculate product data, including: spatial distribution of relative changes in ground resistivity, emergency products, ground electric field vector mode and azimuth, ground current field vector mode and azimuth, and complete the production of image products.

7. The integrated management and online output service system for a local radio network according to claim 1, characterized in that, The aforementioned network management specifically includes: basic information management, standards and specifications management, and station management; The system management specifically includes: access control, notifications and announcements, user management, log management, access statistics, and data backup.

8. The integrated management and online output service system for a local radio network according to claim 1, characterized in that, The aforementioned network product services specifically include: display of product images and product data services, sharing services for network operation reports and earthquake event briefings, and support for external data service interfaces; The aforementioned network information service specifically includes: querying and displaying site distribution, network management information, and quality monitoring information.

Images