Coal mine water hazard monitoring and early warning system and method

Abstract

The present invention relates to the technical field of water hazard monitoring, and discloses a coal mine water hazard monitoring and early warning system and method, comprising an acquisition end and a service end, wherein the acquisition end comprises a ground hydrological monitoring module, an underground hydrological monitoring module and a data transmission module; the service end comprises a data receiving module, a data preprocessing module, a preliminary screening module, a data multivariate correlation analysis module, a data multivariate dimensionality reduction processing module, an early warning strategy setting module, and a data trend prediction and early warning module; the data trend prediction and early warning module is used to predict the trend change of the second monitoring data source in the risk area involved in this early warning task according to the strategy of early warning and warning cancellation rules, and to perform early warning for this early warning task; this solution can solve the problem of low accuracy of water hazard monitoring and early warning caused by the mutual independence of various monitoring contents in the existing underground and ground.

Description

Technical Field

[0001] The present invention relates to the technical field of water hazard monitoring, and in particular to a coal mine water hazard monitoring and early warning system and method. Background Art

[0002] With the rapid development of the national economy, coal demand will continue to grow in the process of industrialization, informatization, urbanization, and agricultural modernization. However, my country's complex coal mine geological conditions and natural disasters can cause coal mine accidents. Water hazards, one of the five major coal mine hazards, often cause various water bodies such as pore water, fissure water, karst water, old goaf water, and surface water to intrude into the mine during coal mine construction and production, resulting in mine water inrush accidents. Establishing a coal mine water hazard monitoring and early warning system is crucial to understanding the distribution characteristics of mine water inrush and providing reliable basic data for coal mine prevention and control work and accurate decision-making.

[0003] However, the traditional coal mine water hazard monitoring and early warning system has the following problems: there are few data sources, and the underground monitoring and early warning system and the ground monitoring and early warning system are independent of each other. This leads to the corresponding results of the underground water hazard risk analysis not being consistent with reality, that is, the accuracy of water hazard monitoring and early warning is not high. Summary of the Invention

[0004] The present invention aims to provide a coal mine water hazard monitoring and early warning system and method, which can solve the problem of low accuracy of water hazard monitoring and early warning caused by the independence of existing underground and ground monitoring.

[0005] To achieve the above-mentioned object, the present invention adopts the following technical solution: a coal mine water hazard monitoring and early warning system, comprising a service end and a collection end;

[0006] The acquisition end includes a surface hydrological monitoring module, a downhole hydrological monitoring module, and a data transmission module;

[0007] The surface hydrological monitoring module is used to wirelessly monitor and collect data on the ground corresponding to the current coal mine and generate corresponding surface hydrological monitoring data;

[0008] The underground hydrological monitoring module is used to perform online monitoring and collection of underground data corresponding to the current coal mine and generate corresponding underground hydrological monitoring data;

[0009] The data transmission module is used to upload the collected underground hydrological monitoring data to the early warning system server through the industrial ring network; it is also used to transmit the collected surface hydrological monitoring data to the early warning system server in the industrial ring network through the 4G network using the cloud server and the transfer server;

[0010] The server includes:

[0011] Data receiving module, used to obtain surface hydrological monitoring data and underground hydrological monitoring data from the early warning system server in real time;

[0012] Data preprocessing module, used for preprocessing surface hydrological monitoring data and underground hydrological monitoring data;

[0013] A preliminary screening module is used to determine the corresponding business type according to business needs, and to perform preliminary screening of the surface hydrological monitoring data and the downhole hydrological monitoring data according to the business type to generate the corresponding first monitoring data source;

[0014] a data multivariate correlation analysis module for analyzing, based on the preliminarily screened first monitoring data source, the spatiotemporal correlation of the various types of data corresponding to the surface hydrological monitoring data and the various types of data corresponding to the downhole hydrological monitoring data in the first monitoring data source;

[0015] A data multivariate dimensionality reduction processing module is used to select and analyze multiple types of data whose spatiotemporal correlation corresponding to the current business type exceeds a preset correlation threshold, and generate a corresponding second monitoring data source;

[0016] The early warning strategy setting module is used to determine the corresponding specific early warning task according to the business type, and determine the risk area involved in this early warning task and the strategy setting of early warning and warning cancellation rules based on the second monitoring data source;

[0017] The data trend prediction and warning module is used to predict the trend changes of the second monitoring data source in the risk area involved in this warning task and to issue an early warning for this warning task according to the strategy of early warning and warning cancellation rules.

[0018] The principles and advantages of this solution are: in this solution, first, the data collection of the surface hydrological conditions and underground hydrological conditions corresponding to the current coal mine is completed through the collection end, and in order to ensure the unified preservation of the underground hydrological monitoring data and the surface hydrological monitoring data, specifically, the collected underground hydrological monitoring data is uploaded to the early warning system server through the industrial ring network; it is also used to transmit the collected surface hydrological monitoring data to the early warning system server in the industrial ring network through the 4G network using the cloud server and the transit server, that is, to realize the unified management of underground data and surface data, not only the data type is more diversified and comprehensive, but also the data format is more unified, which is convenient for data call and processing, and greatly improves the convenience of data use.

[0019] After completing the data collection in the coal mine, considering that the data currently collected in the coal mine may be cumbersome and complex, the data required for a certain early warning task may only be a part of the collected data. In order to ensure the accurate implementation of the early warning task, it is necessary to screen the collected data. Specifically, the data will be preprocessed first so that the data can be more unified and formatted, thereby saving the processing time for subsequent data use and greatly improving the convenience of subsequent data mobilization.

[0020] Then, the corresponding business needs will be determined, so as to determine the business type. For example, if an early warning is required for a goaf, based on this business type, the ground hydrological monitoring data and underground hydrological monitoring data can be preliminarily screened to select a portion of data related to this business type. After that, a multivariate correlation analysis is performed on the first monitoring data source after the preliminary screening, that is, the corresponding spatiotemporal correlation degree is analyzed. Based on this spatiotemporal correlation degree, a secondary screening can be performed on the first monitoring data source to obtain a second monitoring data source. At this time, the corresponding second monitoring data source is very relevant to this early warning task, that is, the correlation is extremely high. Through these data, it is possible to make an accurate and effective judgment on the early warning of this business type.

[0021] After that, the specific early warning task is determined according to the business type, and the risk area involved in this early warning task and the strategy of early warning and lifting early warning rules are set according to the second monitoring data source. Subsequently, the trend changes of the second detection data source in the risk area can be predicted and risk warnings can be issued based on the second monitoring data source and the corresponding early warning and lifting early warning rules.

[0022] 1. This solution collects a wide variety of data types, which makes subsequent predictions or judgments more accurate. At the same time, the data is transmitted in a cloud-edge-end manner, which realizes the unified management of underground data and ground data, making the use of data faster after call, greatly improving the data processing efficiency of the system.

[0023] 2. Considering that the data types corresponding to coal mines are relatively numerous and complex, preliminary screening and subsequent judgment of the degree of spatiotemporal correlation are performed to achieve accurate determination of the data, and to determine whether the selected data can meet the requirements corresponding to this early warning task, so as to better ensure the authenticity and accuracy of this early warning. When making predictions, not only the underground hydrological data is considered, but also the hydrological data on the ground, so as to associate the underground water hazard data with the water data on the ground. Compared with the existing technology in which the underground and ground monitoring contents are independent of each other, this application combines the underground and ground monitoring contents to make the early warning more accurate. That is, it can solve the problem of low accuracy of water hazard monitoring and early warning caused by the independence of the existing underground and ground monitoring contents.

[0024] Preferably, as an improvement, the ground hydrological monitoring data includes rainfall monitoring data, long-hole monitoring data, river water level and flow monitoring data, temperature and humidity monitoring data, and wind speed and direction monitoring data;

[0025] The underground hydrological monitoring data includes water inflow monitoring data of the working face and the main tunnel, flow and pressure monitoring data of the closed goaf, water tank liquid level and temperature monitoring data, exploration and release water flow monitoring data, exploration and release water drilling trajectory monitoring data, and mining progress monitoring data.

[0026] Beneficial effects: The detection of surface hydrological and underground hydrological data is more comprehensive, which greatly improves the comprehensiveness of early data collection, which can help to realize the diversification of subsequent early warning tasks.

[0027] Preferably, as an improvement, the data receiving module in the server includes:

[0028] The acquisition module is used to collect surface hydrological monitoring data and underground hydrological monitoring data, as well as the location coordinates and other attribute information of each corresponding acquisition device;

[0029] The setting module is used to set the address information and receiving frequency of each acquisition device;

[0030] The control module is used to issue control instructions and scheduled tasks to each acquisition device;

[0031] The detection module is used to detect the status of each acquisition device.

[0032] Beneficial effects: In this solution, not only the data of the collection equipment corresponding to the collection end is obtained, but also the effective management and control of these collection equipment are achieved, which greatly improves the collection speed and accuracy of the collection equipment.

[0033] Preferably, as an improvement, the data preprocessing module includes:

[0034] Data cleaning module, used to clean surface hydrological monitoring data and underground hydrological monitoring data;

[0035] Data denoising module, used to denoise the cleaned surface hydrological monitoring data and underground hydrological monitoring data;

[0036] The aggregation module is used to aggregate the denoised surface hydrological monitoring data and underground hydrological monitoring data into strictly equal time interval data.

[0037] Beneficial effects: In this solution, cleaning, denoising, and aggregation operations are performed on the collected surface hydrological monitoring data and underground hydrological monitoring data, which greatly improves the effectiveness of the data and can reduce the storage of useless data.

[0038] Preferably, as an improvement, the data multivariate correlation analysis module in the server is used to select the first monitoring data source related to the specific early warning task, perform partial correlation analysis and complex correlation analysis, PCA principal component analysis, and determine the corresponding spatiotemporal correlation degree of each data in the first monitoring data source based on the analysis results.

[0039] Beneficial effects: In this solution, by performing partial correlation analysis and multiple correlation analysis, PCA principal component analysis on the first monitoring data source, the multivariate correlation analysis function of the data is realized, and the degree of spatiotemporal correlation of each data in the first monitoring data source can be quickly determined in a timely manner, that is, the weight of each data can be determined. In this way, the degree of correlation between each data and the corresponding early warning task can be known, providing an effective and accurate basis for subsequent screening.

[0040] Preferably, as an improvement, the early warning strategy setting module in the server is used to retrieve the corresponding static evaluation data from the database according to the current second monitoring data source, and set and determine the early warning strategy corresponding to this early warning task based on the second monitoring data source and the static evaluation data; the static evaluation data include water storage structure properties, water blocking structure properties, aquifer thickness, water richness, mining design parameters, drainage design parameters, goaf location range, geophysical evaluation indicators, drainage evaluation indicators.

[0041] Beneficial effects: In this solution, the early warning strategy for this early warning task is determined and set based on static evaluation data and the current second monitoring data source. This greatly improves the selection of early warning strategies and enables early warning strategies to better adapt to the use of the second monitoring data source.

[0042] Preferably, as an improvement, the data trend prediction and warning module in the server includes:

[0043] A data trend prediction module is used to perform time series prediction on the corresponding second monitoring data source according to the current specific warning task to obtain the predicted trend information of the corresponding data. The time series prediction includes differential integrated moving average autoregressive model time series prediction and multivariate neural network time series prediction;

[0044] The early warning prediction module is used to determine the current early warning status, the location and the cause of the early warning and publish the warning according to the second monitoring data source and the determined early warning strategy.

[0045] Beneficial effects: The corresponding data trend forecast and early warning forecast are carried out simultaneously, which can realize data trend forecast and early warning forecast more quickly, greatly improving the authenticity and accuracy of the forecast, and are independent of each other and do not interfere with each other.

[0046] Preferably, as an improvement, the server further includes a dynamic display module for selecting a certain warning task and retrieving the data prediction trend information and warning status of the second monitoring data corresponding to the warning task for dynamic display.

[0047] Beneficial effects: This solution can dynamically display the data forecast trend information and warning status corresponding to any warning task, realizing the visualization of the warning.

[0048] The present invention also provides a coal mine water hazard monitoring and early warning method, which applies the above-mentioned coal mine water hazard monitoring and early warning system. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is a logic block diagram of the coal mine water hazard monitoring and early warning system in Example 1 of the present invention.

[0050] Figure 2 This is a specific transmission logic block diagram of the data transmission module in Example 1 of the present invention. DETAILED DESCRIPTION

[0051] The following is further described in detail through specific implementation methods:

[0052] The embodiment is basically as shown in the attached Figure 1 Shown: A coal mine water hazard monitoring and early warning system, including a service end and a collection end;

[0053] The acquisition end includes a surface hydrological monitoring module, a downhole hydrological monitoring module, and a data transmission module;

[0054] The surface hydrological monitoring module is used to wirelessly monitor and collect data on the ground corresponding to the current coal mine and generate corresponding surface hydrological monitoring data;

[0055] The underground hydrological monitoring module is used to perform online monitoring and collection of underground data corresponding to the current coal mine to generate corresponding underground hydrological monitoring data; in this embodiment, the ground hydrological monitoring data includes rainfall monitoring data, long observation hole monitoring data, river water level and flow monitoring data, temperature and humidity monitoring data, and wind speed and direction monitoring data; the underground hydrological monitoring data includes water inflow monitoring data of working faces and main tunnels, closed flow and pressure monitoring data of goafs, water tank liquid level and temperature monitoring data, exploration and discharge water flow monitoring data, exploration and discharge water drilling trajectory monitoring data, and mining progress monitoring data.

[0056] The data transmission module is used to upload the collected underground hydrological monitoring data to the early warning system server through the industrial ring network; it is also used to transmit the collected ground hydrological monitoring data to the early warning system server in the industrial ring network through the 4G network using the cloud server and the transfer server. Figure 2 shown.

[0057] The server includes:

[0058] Data receiving module, used to obtain surface hydrological monitoring data and underground hydrological monitoring data from the early warning system server in real time;

[0059] The data receiving module includes:

[0060] The acquisition module is used to collect surface hydrological monitoring data and underground hydrological monitoring data, as well as the location coordinates and other attribute information of each corresponding acquisition device;

[0061] The setting module is used to set the address information and receiving frequency of each acquisition device;

[0062] The control module is used to issue control instructions and scheduled tasks to each acquisition device;

[0063] The detection module is used to detect the status of each acquisition device.

[0064] Data preprocessing module, used for preprocessing surface hydrological monitoring data and underground hydrological monitoring data;

[0065] The data preprocessing module includes:

[0066] Data cleaning module, used to clean surface hydrological monitoring data and underground hydrological monitoring data;

[0067] Data denoising module, used to denoise the cleaned surface hydrological monitoring data and underground hydrological monitoring data;

[0068] The aggregation module is used to aggregate the denoised surface hydrological monitoring data and underground hydrological monitoring data into strictly equal time interval data.

[0069] The preliminary screening module is used to determine the corresponding business type according to business needs, and to perform preliminary screening of the ground hydrological monitoring data and the underground hydrological monitoring data according to the business type to generate the corresponding first monitoring data source; for example, in a certain business type, it only requires exploration and release water flow monitoring data, exploration and release water drilling trajectory monitoring data, mining footage monitoring data, rainfall monitoring data, long observation hole monitoring data, and river water level flow monitoring data. Then, during the preliminary screening, these data will be matched and searched in the ground hydrological monitoring data and underground hydrological monitoring data of the entire coal mine, and other data will be eliminated, and only these required data will be selected to form the corresponding first monitoring data source.

[0070] The data multivariate correlation analysis module is used to analyze the spatiotemporal correlation of various types of data corresponding to the surface hydrological monitoring data and the various types of data corresponding to the downhole hydrological monitoring data in the first monitoring data source based on the first monitoring data source after preliminary screening; in this embodiment, specifically, the first monitoring data source related to the specific early warning task is selected to perform partial correlation analysis and complex correlation analysis, PCA principal component analysis, and according to the analysis results, the spatiotemporal correlation degree of each data in the first monitoring data source is determined.

[0071] The data multi-dimensionality reduction processing module is used to select and analyze multiple types of data whose spatiotemporal correlation corresponding to the current business type exceeds a preset correlation threshold, and generate a corresponding second monitoring data source; in this embodiment, after completing the judgment of the spatiotemporal correlation of each data direction in the first monitoring data source, the weight of each data is determined, and then it can be sorted according to the weight. When performing dimensionality reduction, it can be selected according to the preset correlation threshold.

[0072] In this embodiment, for a certain business type, the data preliminarily screened out are related to the business type, but the degree of correlation is different, some correlations are relatively large, and some correlations are relatively small. In order to better monitor the early warning task corresponding to the business type, it is necessary to select data with relatively large correlation to perform data early warning. For example, the spatiotemporal correlation degrees of exploration and discharge water flow monitoring data, exploration and discharge water drilling trajectory monitoring data, excavation footage monitoring data, rainfall monitoring data, long-distance observation hole monitoring data, and river water level and flow monitoring data are A, B, C, D, E, and F, respectively, and the size is sorted by A, C, E, B, F, and D, respectively. If the first five are selected according to the corresponding needs, for example, the preset spatiotemporal correlation threshold is greater than G, and G is less than B, then when determining the second monitoring data source, the data corresponding to the spatiotemporal correlation degrees of A, C, E, and B will be selected, namely, exploration and discharge water flow monitoring data, exploration and discharge water drilling trajectory monitoring data, excavation footage monitoring data, and long-distance observation hole monitoring data, thereby achieving accurate determination of the data and improving the accuracy of the early warning.

[0073] The early warning strategy setting module is used to determine the corresponding specific early warning task according to the business type, and determine the risk area involved in this early warning task and the strategy setting of early warning and warning cancellation rules based on the second monitoring data source;

[0074] In this embodiment, specifically, according to the current second monitoring data source, the corresponding static evaluation data is retrieved from the database, and based on the second monitoring data source and the static evaluation data, the early warning strategy corresponding to this early warning task is set and determined; the static evaluation data includes water storage structure properties, water blocking structure properties, aquifer thickness, water richness, mining design parameters, drainage design parameters, goaf location range, geophysical evaluation indicators, drainage evaluation indicators.

[0075] The data trend prediction and warning module is used to predict the trend changes of the second monitoring data source in the risk area involved in this warning task and to issue an early warning for this warning task according to the strategy of early warning and warning cancellation rules.

[0076] The data trend prediction and warning module includes:

[0077] The data trend prediction module is used to perform time series prediction on the corresponding second monitoring data source according to the current specific warning task to obtain the prediction trend information of the corresponding data. The time series prediction includes differential integrated moving average autoregressive model time series prediction and multivariate neural network time series prediction.

[0078] The early warning prediction module is used to determine the current early warning status, the location and the cause of the early warning and publish the warning according to the second monitoring data source and the determined early warning strategy.

[0079] The server also includes a dynamic display module for selecting a warning task and retrieving the data prediction trend information and warning status of the second monitoring data corresponding to the warning task for dynamic display.

[0080] This embodiment also provides a coal mine water hazard monitoring and early warning method, which applies the above-mentioned coal mine water hazard monitoring and early warning system.

[0081] The above is only an embodiment of the present invention, and the common knowledge such as the specific technical solutions and / or characteristics in the solution are not described in detail here. It should be pointed out that for those skilled in the art, without departing from the technical solution of the present invention, several variations and improvements can be made, which should also be regarded as the scope of protection of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the description can be used to interpret the content of the claims.

Claims

1. A coal mine water hazard monitoring and early warning system, characterized by: Including server and collection end; The acquisition end includes a surface hydrological monitoring module, a downhole hydrological monitoring module, and a data transmission module; The surface hydrological monitoring module is used to wirelessly monitor and collect data on the ground corresponding to the current coal mine and generate corresponding surface hydrological monitoring data; The underground hydrological monitoring module is used to perform online monitoring and collection of underground data corresponding to the current coal mine and generate corresponding underground hydrological monitoring data; Data transmission module, used to upload the collected underground hydrological monitoring data to the early warning system server through the industrial ring network; It is also used to transmit the collected ground hydrological monitoring data to the early warning system server in the industrial ring network through the 4G network using the cloud server and the transfer server; The server includes: Data receiving module, used to obtain surface hydrological monitoring data and underground hydrological monitoring data from the early warning system server in real time; Data preprocessing module, used for preprocessing surface hydrological monitoring data and underground hydrological monitoring data; A preliminary screening module is used to determine the corresponding business type according to business needs, and to perform preliminary screening of the surface hydrological monitoring data and the downhole hydrological monitoring data according to the business type to generate the corresponding first monitoring data source; a data multivariate correlation analysis module for analyzing, based on the preliminarily screened first monitoring data source, the spatiotemporal correlation of the various types of data corresponding to the surface hydrological monitoring data and the various types of data corresponding to the downhole hydrological monitoring data in the first monitoring data source; A data multivariate dimensionality reduction processing module is used to select and analyze multiple types of data whose spatiotemporal correlation corresponding to the current business type exceeds a preset correlation threshold, and generate a corresponding second monitoring data source; The early warning strategy setting module is used to determine the corresponding specific early warning task according to the business type, and determine the risk area involved in this early warning task and the strategy setting of early warning and warning cancellation rules based on the second monitoring data source; The data trend prediction and warning module is used to predict the trend changes of the second monitoring data source in the risk area involved in this warning task and to issue an early warning for this warning task according to the strategy of early warning and warning cancellation rules.

2. A coal mine water hazard monitoring and early warning system according to claim 1, characterized in that: The ground hydrological monitoring data includes rainfall monitoring data, long observation hole monitoring data, river water level and flow monitoring data, temperature and humidity monitoring data, and wind speed and direction monitoring data; the underground hydrological monitoring data includes water inflow monitoring data of the working face and the main tunnel, closed flow and pressure monitoring data of the goaf, water tank liquid level and temperature monitoring data, exploration and release water flow monitoring data, exploration and release water drilling trajectory monitoring data, and mining progress monitoring data.

3. A coal mine water hazard monitoring and early warning system according to claim 2, characterized in that: The data receiving module in the server includes: an acquisition module for collecting surface hydrological monitoring data and underground hydrological monitoring data, as well as the location coordinates and other attribute information of each corresponding acquisition device; a setting module for setting the address information and receiving frequency of each acquisition device; a control module for issuing control instructions and timed tasks to each acquisition device; and a detection module for detecting the status of each acquisition device.

4. A coal mine water hazard monitoring and early warning system according to claim 3, characterized in that: The data preprocessing module includes: a data cleaning module for cleaning the surface hydrological monitoring data and the downhole hydrological monitoring data; a data denoising module for denoising the cleaned surface hydrological monitoring data and the downhole hydrological monitoring data; and an aggregation module for aggregating the denoised surface hydrological monitoring data and the downhole hydrological monitoring data into strictly equal time interval data.

5. A coal mine water hazard monitoring and early warning system according to claim 4, characterized in that: The data multivariate correlation analysis module in the server is used to select the first monitoring data source related to the specific early warning task, perform partial correlation analysis and complex correlation analysis, PCA principal component analysis, and determine the corresponding spatiotemporal correlation degree of each data in the first monitoring data source based on the analysis results.

6. A coal mine water hazard monitoring and early warning system according to claim 5, characterized in that: The early warning strategy setting module in the server is used to retrieve the corresponding static evaluation data from the database according to the current second monitoring data source, and set and determine the early warning strategy corresponding to this early warning task based on the second monitoring data source and the static evaluation data; the static evaluation data includes water storage structure properties, water blocking structure properties, aquifer thickness, water richness, mining design parameters, drainage design parameters, goaf location range, geophysical evaluation indicators, and drainage evaluation indicators.

7. A coal mine water hazard monitoring and early warning system according to claim 6, characterized in that: The data trend prediction and warning module in the server includes: a data trend prediction module, which is used to perform time series prediction on the corresponding second monitoring data source according to the current specific warning task to obtain the prediction trend information of the corresponding data, and the time series prediction includes differential integrated moving average autoregressive model time series prediction and multivariate neural network time series prediction; an early warning prediction module, which is used to judge the current early warning status, the location and the cause of the warning and publish it according to the second monitoring data source and the determined early warning strategy.

8. A coal mine water hazard monitoring and early warning system according to claim 7, characterized in that: The server also includes a dynamic display module for selecting a warning task and retrieving the data prediction trend information and warning status of the second monitoring data corresponding to the warning task for dynamic display.

9. A coal mine water hazard monitoring and early warning method, characterized by: A coal mine water hazard monitoring and early warning system according to any one of claims 1 to 8 is used.

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