A safety early warning method and system based on mine mining data analysis

Abstract

The present application discloses a safety early warning method and system based on mine mining data analysis, which belongs to the field of data processing technology. The method includes: obtaining a mine mining database; constructing a list of safety event monitoring indicators to obtain event mapping indicator information; traversing and extracting indicator information from the mine mining database to obtain event monitoring data; performing feature analysis and identification to determine the feature analysis results; judging whether there is a risk event in the feature analysis results, and if so, sending feature safety early warning information; if not, performing trend analysis and identification based on the event monitoring data to obtain trend analysis results; and sending trend safety early warning information when there is a risk event in the trend analysis results. The present application solves the technical problem in the prior art that the mine data analysis is not deep enough and cannot accurately warn of safety situations, and achieves the technical effect of deeply mining the potential information of the data and accurately identifying the risk hazards of the mine.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a safety early warning method and system based on mine mining data analysis. Background Art

[0002] To accelerate the transformation of China's energy consumption structure, the mining industry is continuously developing and applying new technologies, driving production towards reduced or even unmanned operations. Promoting research into intelligent mining is crucial for improving mine safety in my country.

[0003] Currently, my country's mines are shifting from primarily underground mining to intelligent production using intelligent technologies and equipment. This approach prioritizes automated working face control, supplemented by remote intervention from a centralized control center, thereby improving mining efficiency. For example, remote centralized control of major coal flow, drainage, and other production systems within mines has been implemented on the surface.

[0004] However, while automated mining has improved efficiency and reduced labor costs, it also generates a large amount of data. The inability to accurately analyze this data in a timely manner has led to frequent safety incidents, resulting in serious safety hazards and economic losses. Existing technologies lack the depth of mine data analysis to accurately provide safety warnings. Summary of the Invention

[0005] The purpose of this application is to provide a safety warning method and system based on mine mining data analysis to solve the technical problem in the existing technology that the mine data analysis is not deep enough and cannot accurately warn of safety situations.

[0006] In view of the above problems, the present application provides a safety early warning method and system based on mine mining data analysis.

[0007] In the first aspect, the present application provides a safety warning method based on mine mining data analysis, wherein the method includes: obtaining a mine mining database; constructing a safety event monitoring indicator list, and obtaining event mapping indicator information based on the safety event monitoring indicator list; traversing and extracting indicator information from the mine mining database based on the event mapping indicator information to obtain event monitoring data; performing feature analysis and identification on the event monitoring data to determine the feature analysis results; judging whether there is a risk event in the feature analysis results, and if so, sending feature safety warning information; if not, performing trend analysis and identification based on the event monitoring data to obtain trend analysis results; when there is a risk event in the trend analysis results, sending trend safety warning information.

[0008] On the other hand, the present application also provides a safety warning system based on mine mining data analysis, wherein the system includes: a database acquisition module, the database acquisition module is used to obtain a mine mining database; a mapping indicator acquisition module, the mapping indicator acquisition module is used to construct a safety event monitoring indicator list, and obtain event mapping indicator information according to the safety event monitoring indicator list; a monitoring data acquisition module, the monitoring data acquisition module is used to traverse and extract indicator information from the mine mining database according to the event mapping indicator information, and obtain event monitoring data; an analysis result determination module, the analysis result determination module is used to perform feature analysis and identification on the event monitoring data to determine the feature analysis results; a warning information sending module, the warning information sending module is used to determine whether there is a risk event in the feature analysis result, and when so, send feature safety warning information; a trend analysis identification module, the trend analysis identification module is used to perform trend analysis and identification according to the event monitoring data when not present, and obtain trend analysis results; a safety information sending module, the safety information sending module is used to send trend safety warning information when there is a risk event in the trend analysis result.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] This application obtains a mine mining database, then constructs a list of safety event monitoring indicators, and obtains event mapping indicator information based on the corresponding relationship between the indicators in the safety event monitoring indicator list and the safety events. Then, the data in the mine mining database is traversed and extracted according to the indicator information in combination with the event mapping indicator information to obtain event monitoring data. Then, feature analysis and identification are performed on the event monitoring data to determine the feature analysis results, and then it is determined whether there is a risk event in the feature analysis results. If so, a feature safety warning message is sent. If not, trend analysis and identification are performed on the event monitoring data to obtain trend analysis results. Then, an in-depth analysis is performed on the trend analysis results. When there is a risk event in the trend analysis results, a trend safety warning message is sent. In this way, the technical effect of in-depth analysis of mining data, mining potential information in the data, and early warning of risks in the mine is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in this application or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely exemplary, and a person of ordinary skill in the art can obtain other drawings based on the provided drawings without any creative work.

[0012] Figure 1A flowchart of a safety early warning method based on mine mining data analysis provided in an embodiment of the present application;

[0013] Figure 2 A schematic diagram of the process of obtaining a mine mining database in a safety warning method based on mine mining data analysis provided in an embodiment of the present application;

[0014] Figure 3 A schematic diagram of a process for constructing a list of safety event monitoring indicators in a safety early warning method based on mine mining data analysis provided in an embodiment of the present application;

[0015] Figure 4 This is a structural diagram of a safety early warning system based on mine mining data analysis in this application.

[0016] Explanation of the accompanying symbols: database acquisition module 11, mapping indicator acquisition module 12, monitoring data acquisition module 13, analysis result determination module 14, early warning information sending module 15, trend analysis and identification module 16, safety information sending module 17. DETAILED DESCRIPTION

[0017] This application provides a safety warning method and system based on mine mining data analysis, solving the technical problem of insufficient depth in mine data analysis and inability to accurately provide safety warnings. It achieves the technical effect of deeply mining potential information in the data and accurately identifying risks and hidden dangers in the mine.

[0018] The acquisition, storage, use, and processing of data in this application's technical solution comply with relevant national laws and regulations.

[0019] Below, the technical solutions in this application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this application, rather than all the embodiments of this application. It should be understood that this application is not limited to the example embodiments described herein. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. It should also be noted that, for the convenience of description, only the parts related to this application, rather than all of them, are shown in the accompanying drawings.

[0020] Example 1

[0021] like Figure 1 As shown, the present application provides a safety early warning method based on mine mining data analysis, wherein the method includes:

[0022] Step S100: obtaining a mine mining database;

[0023] Further, such as Figure 2As shown, a mine mining database is obtained, and step S100 of the embodiment of the present application further includes:

[0024] Step S110: monitoring the air quality in the mine through air quality monitoring equipment to obtain mine air quality information;

[0025] Step S120: monitoring the gas concentration in the mine using gas concentration monitoring equipment to obtain mine gas concentration information;

[0026] Step S130: monitoring the wind speed in the mine by using wind speed monitoring equipment to obtain mine wind speed information;

[0027] Step S140: monitoring electromagnetic radiation in the mine using electromagnetic radiation monitoring equipment to obtain electromagnetic radiation information of the mine;

[0028] Step S150: monitoring the sound in the mine through sound monitoring equipment to obtain mine sound information;

[0029] Step S160: constructing a mine monitoring data set based on the mine air quality information, mine gas concentration information, mine wind speed information, mine electromagnetic radiation information, mine sound information and their corresponding monitoring time;

[0030] Step S170: obtaining personnel positioning data and mining equipment operation data, and constructing the mine mining database according to the time correspondence between the personnel positioning data, mining equipment operation data and the mine monitoring data set.

[0031] Specifically, the mine mining database is obtained by summarizing the data generated by mining activities during the mining process. The air quality monitoring equipment refers to a device that monitors the air conditions in the mine, including particulate dust monitors, gas detectors, etc. The mine air quality information reflects the air quality conditions in the mine, and can further reflect whether the air environment in the mine meets production requirements, including: PM2.5 conditions, sulfur dioxide content, nitrogen dioxide content, carbon monoxide content, etc. The mine gas concentration information reflects the real-time gas concentration conditions in the mine. The mine wind speed information refers to the wind speed conditions in the mine during the mining process, including wind speed magnitude, wind speed change rate, etc. The mine electromagnetic radiation information reflects the real-time changes in electromagnetic radiation in the mine, including radiation power density, radiation intensity, directivity coefficient, etc. The mine sound information refers to the sound information obtained from the mine in real time during the mining process, including sound frequency, sound amplitude, etc. Through real-time monitoring, the mine's air quality information, mine gas concentration information, mine wind speed information, mine electromagnetic radiation information, and mine sound information are obtained. Each piece of information has a corresponding monitoring time. Based on the correspondence between the information and the monitoring time, a mine monitoring dataset reflecting the mine's mining conditions can be obtained. Each monitoring time in the mine monitoring dataset has corresponding monitoring data, and the types of monitoring data include air quality, gas concentration, wind speed, electromagnetic radiation, and sound. By constructing the mine monitoring dataset and obtaining the correspondence between the data and the monitoring time, the technical effect of providing basic analytical data for subsequent mine mining safety analysis is achieved.

[0032] Specifically, the personnel positioning data refers to the real-time location of the staff in the mine, including the number of personnel and the coordinates of the personnel's location. The personnel positioning data can be used to monitor the total number of people currently underground in real time, thereby providing data for subsequent searches for the personnel's location at the current moment or a specified moment. For example, based on the personnel positioning data, a certain area or a certain substation can be selected, and the personnel information at that location at a historical moment can be obtained. The mining equipment operation data refers to the real-time data of the mining equipment in the mine during operation. For example, the operation data of the intelligent swing gate includes the working temperature, relative humidity, traffic flow, etc. The mine mining database is obtained by matching the time stamp of the real-time positioning data in the personnel positioning data and the time stamp in the mining equipment operation data with the time of the mine monitoring data set summary. Among them, the mine mining database reflects the personnel situation, equipment operation status and mine environment conditions corresponding to each moment in the mine mining process. In this way, the technical effect of real-time collection of the mining situation of the mine is achieved.

[0033] Furthermore, before constructing the mine mining database based on the time correspondence between the personnel positioning data, the mining equipment operation data, and the mine monitoring data set, step S170 of the embodiment of the present application further includes:

[0034] Step S171: performing transmission channel analysis on the personnel positioning data, mining equipment operation data, and mine monitoring data set to determine the credibility of each transmission channel;

[0035] Step S172: performing data identification analysis on monitoring data whose transmission channel credibility does not meet the preset requirements, and determining the data identification analysis result;

[0036] Step S173: Using the data recognition and analysis results, the personnel positioning data, mining equipment operation data, and mine monitoring data set are corrected, and the mine mining database is constructed using the corrected personnel positioning data, mining equipment operation data, and mine monitoring data set.

[0037] Furthermore, step S171 of the embodiment of the present application further includes:

[0038] Step S1711: Obtain transmission channel attributes;

[0039] Step S1712: performing transmission interference analysis based on the transmission channel attributes to determine channel transmission interference;

[0040] Step S1713: Determine the credibility of each transmission channel based on the channel transmission interference.

[0041] Specifically, during the data transmission of personnel location data, mining equipment operation data, and data from mine monitoring data sets, the transmission environment can interfere with signal transmission, resulting in data transmission delays and, in turn, impacting data reliability. Therefore, by analyzing the transmission process of the transmission channel and evaluating the credibility of each transmission channel, the credibility of each transmission channel is determined. The transmission channel refers to the data path for transmitting information and the means by which each control system receives feedback signals and issues control signals. The transmission channel attributes refer to the construction method of the transmission channel and the means by which signal transmission relies, optionally including optical cables, network cables, and electrical cables. Based on the transmission channel attributes and in combination with the underground environment, each transmission channel is analyzed for transmission interference. Preferably, each transmission channel is tested for its electromagnetic interference resistance. The transmission interference resistance of each transmission channel is tested by performing a Level 2A pulse group immunity test, a Level 2A electromagnetic radiation immunity test, a Level 3A electrostatic discharge immunity test, and a Level 2A surge (impact) immunity test on the DC power supply and signal ports, to determine the channel transmission interference resistance of each channel. Then, based on the experimental test results of each channel, the credibility of each transmission channel is determined. The preset requirement is that the credibility of the transmission channel can meet the requirement of transmitting accurate data. When the credibility of the transmission channel does not meet the preset requirement, the accuracy of the transmission data of the transmission channel cannot meet the requirement. Therefore, it is necessary to perform data identification and analysis on the monitoring data to obtain the data identification and analysis results. Among them, the data identification and analysis results are obtained by determining the items represented by the data. According to the items in the data identification and analysis results, the relevant personnel positioning data, mining equipment operation data and mine monitoring data sets are corrected to obtain data that can accurately reflect personnel positioning, equipment operation and mine environment after correction, and the mine mining database is constructed. In this way, the technical effect of improving the accuracy of the data and thus improving the reliability of data analysis is achieved.

[0042] Step S200: constructing a security event monitoring indicator list, and obtaining event mapping indicator information according to the security event monitoring indicator list;

[0043] Further, such as Figure 3 As shown, the construction of the security event monitoring indicator list, step S200 of the embodiment of the present application further includes:

[0044] Step S210: Obtain historical safety accident record information;

[0045] Step S220: classifying security events based on the historical security incident record information and establishing a security event classification indicator cluster;

[0046] Step S230: performing a multi-event indicator correlation analysis on the security event classification indicator cluster to determine indicator correlation;

[0047] Step S240: Based on the indicator correlation, security event correlation mapping is performed on each indicator in the security event classification indicator cluster to construct the security event monitoring indicator list.

[0048] Specifically, the safety event monitoring indicator list refers to a table of indicators that need to be considered when monitoring safety events that may occur during mining operations. The historical safety accident record information is information obtained by recording safety events that occurred in the mine over a historical period, including the type of safety event, time of occurrence, cause, and equipment involved. Safety events are classified according to the type of the historical safety accident record information to obtain the safety event classification indicator cluster. The safety event classification indicator cluster refers to the indicators corresponding to each safety event obtained after classifying different safety time periods. For example, when the mine water level rises beyond the safe range, a mine safety accident is more likely to occur. The relevant indicator cluster includes indicators such as surface water level, water temperature, water inflow point, monitoring point location, and water level. Correlated indicators are established for different types of safety events to obtain the safety event classification indicator cluster. The multi-event indicator correlation of the indicators in the safety event classification indicator cluster is then analyzed to determine the degree of correlation between the indicators and obtain the indicator correlation. By analyzing the indicators corresponding to multiple safety events, the shared indicators are determined, and the degree of correlation between the individual indicators is then determined. Then, according to the indicator correlation, the correlation degree of the security events corresponding to each indicator in the security time classification indicator cluster is matched to obtain the security event monitoring indicator list.

[0049] For example, during the mining process, a gas outburst in a mine causes a safety accident. Therefore, it is necessary to look for relevant monitoring indicators, such as gas concentration, dust concentration, gas outburst volume, electromagnetic radiation signals, etc. These indicators are directly related to gas outburst mine accidents, but gas outburst mines can also cause a series of related safety accidents, such as worker safety and whether the ventilation system is operating normally. Relevant indicators are determined based on the degree of relevance, including personnel positioning data, wind speed indicators, etc. Therefore, the list of monitoring indicators related to gas outburst mine accidents is determined to include: gas concentration, dust concentration, gas outburst volume, electromagnetic radiation signals, personnel positioning data, wind speed indicators, etc.

[0050] Step S300: traversing and extracting indicator information from the mine mining database according to the event mapping indicator information to obtain event monitoring data;

[0051] Specifically, the event mapping indicator information reflects the monitoring indicators corresponding to the safety event. The data in the mine mining database is searched and collected one by one according to the indicators to obtain monitoring data related to the event. The event monitoring data reflects the changes in indicators related to the event during the monitoring period, providing analytical data for subsequent analysis of whether the event poses a safety hazard. By extracting data based on the mapping indicators, not only is the efficiency of data collection improved, but since relevant data is collected based on the event correspondence, the accuracy of the data reflecting the event situation can be improved.

[0052] Step S400: performing feature analysis and identification on the event monitoring data to determine feature analysis results;

[0053] Furthermore, feature analysis and identification are performed on the event monitoring data to determine feature analysis results. In this embodiment of the application, step S400 further includes:

[0054] Step S410: Identify and classify the environmental indicators and mining equipment operation data of the event monitoring data to obtain event monitoring-environmental indicator data and event monitoring-equipment monitoring data;

[0055] Step S420: performing data feature recognition and analysis on the event monitoring-environmental indicator data and the event monitoring-equipment monitoring data to determine environmental indicator features and equipment data features;

[0056] Step S430: Obtaining event data feature thresholds based on the security event monitoring indicator list;

[0057] Step S440: Based on the environmental indicator threshold and the device parameter threshold corresponding to the event data feature threshold, the environmental indicator feature and the device data feature are compared respectively to determine the feature analysis result.

[0058] Specifically, during the analysis of security incidents, due to the clear characteristics of the risk of security incidents determined by standards, industry specifications, and other relevant regulations, for example, clear numerical limits are set for indicators. When the indicator data exceeds the data limit range, it can be determined that there is a risk. The feature analysis and identification refers to the identification of relevant features in the event monitoring data that have clear risk situation limits. The feature analysis results are the results obtained by analyzing and determining the feature conditions in the event monitoring data and determining whether the features exceed the threshold.

[0059] Specifically, the event monitoring data is classified according to environmental indicators and mining equipment operating data, resulting in the event monitoring-environmental indicator data and the event monitoring-equipment monitoring data. The event monitoring-environmental indicator data refers to environmentally relevant data from the safety event monitoring data, illustratively including PM2.5 levels, sulfur dioxide content, nitrogen dioxide content, carbon monoxide content, etc. The event monitoring-equipment monitoring data refers to relevant data from monitoring equipment operating conditions, including operating time, operating power, etc. Furthermore, data feature recognition is performed on the event monitoring-environmental indicator data and the event monitoring-equipment monitoring data, identifying features with clear data limits, to obtain the environmental indicator features and the equipment data features. The environmental indicator features are monitoring features that reflect the relevant conditions of the mine environment. The equipment data features are monitoring features that reflect the relevant conditions of the mine's operating equipment. Event data features are searched from the safety event monitoring indicator list to obtain thresholds corresponding to the event data features. The event data feature thresholds refer to the allowable data value ranges for each indicator data during normal mining operations in the mine. Furthermore, based on the environmental indicator thresholds and equipment parameter thresholds within the event data feature thresholds, they are compared against the environmental indicator features and equipment data features, respectively, to determine whether the environmental indicator features are within the environmental indicator threshold range, and whether the equipment data features are within the equipment parameter threshold range. Based on the comparison results, the feature analysis results are obtained. This achieves the technical effect of identifying and comparing indicator features with clear warning ranges during mining, thereby determining the safety status of the mining process.

[0060] Step S500: Determine whether there is a risk event in the feature analysis result, and if so, send feature safety warning information;

[0061] Specifically, based on the characteristic analysis results, it is determined whether any data in the characteristic analysis results exceeds a specified threshold, that is, whether a risk event exists. Based on the results of the analysis and judgment, when a risk event exists, it can be directly determined that there is a safety risk in the current mining process and that the characteristic safety warning information needs to be sent. The characteristic safety warning information refers to information used to provide safety warnings to staff, reminding them of the presence of safety hazards in the current mining process. This achieves the technical effect of identifying risk situations in the mining process and improving the timeliness and accuracy of safety warnings.

[0062] Step S600: when it does not exist, performing trend analysis and identification based on the event monitoring data to obtain trend analysis results;

[0063] Furthermore, trend analysis and identification are performed based on the event monitoring data to obtain trend analysis results. In this embodiment of the application, step S600 further includes:

[0064] Step S610: performing trend risk indicator analysis based on the historical safety accident record information to determine the trend risk indicator and its trend indicator characteristics;

[0065] Step S620: traversing the event monitoring data and the trend risk indicator to determine a matching trend risk indicator, and performing trend indicator feature analysis based on the matching trend risk indicator to obtain a trend indicator period feature and a trend indicator trend feature;

[0066] Step S630: obtaining period-related event monitoring data based on the trend indicator period characteristics and the event monitoring data;

[0067] Step S640: Utilizing the trend characteristics of the trend indicators and the period-related event monitoring data, a trend coincidence analysis is performed to obtain the trend analysis result.

[0068] Specifically, when it does not exist, it indicates that there are no obvious safety hazards in the mining process at this time. Then, by further mining the event monitoring data, analyzing the development trend of the data, judging whether there is a risk trend, and obtaining the trend analysis result. By analyzing the safety accident record data that occurred in historical situations based on the historical safety accident record information, and analyzing the risk trend indicators before the accident, the trend risk indicators and trend indicator characteristics that may lead to the occurrence of safety accidents are obtained. Among them, the trend risk indicator is an indicator of the trend change of data before the safety accident occurs. The trend indicator characteristics refer to the specific characteristics manifested when the trend risk indicator undergoes a trend change. For example, before a mine safety accident occurs, the acoustic emission index will show an increasing trend.

[0069] Specifically, the event monitoring data is matched against the trend risk indicators one by one to obtain a matching trend risk indicator associated with each security event. The matching trend risk indicator refers to an indicator associated with the precursor to each security event. The trend indicator periodic characteristics and trend indicator trend characteristics are analyzed prior to the security event. The trend indicator periodic characteristics refer to the changing characteristics of the matching trend risk indicator within a certain period. The trend indicator trend characteristics refer to the development trend of the matching trend risk indicator prior to the security incident. For example, the indicator exhibits a cyclical growth and fluctuation trend within a certain period, and then exhibits an increasing trend within a short period prior to the security incident. Then, based on the trend indicator periodic characteristics and the event monitoring data, monitoring data within the trend indicator periodic variation is collected to obtain the period-related event monitoring data. Furthermore, a trend overlap analysis is performed based on the trend indicator trend characteristics and the period-related event monitoring data. The overlap between the development trend of the monitoring data and the trend characteristics is analyzed to obtain the trend analysis results. This provides a basis for subsequent analysis of whether the event presents a risk based on the trend analysis results.

[0070] Step S700: When a risk event occurs in the trend analysis result, a trend safety warning message is sent.

[0071] Specifically, when there is a risk event in the trend analysis results, it indicates that there is a hidden risk in the mine mining at this time, and the staff needs to be reminded of the risk and the trend safety warning information is sent, thereby achieving the technical effect of monitoring the mine mining situation and issuing a warning on the mining safety situation by analyzing the data.

[0072] In summary, the safety early warning method based on mine mining data analysis provided by this application has the following technical effects:

[0073] 1. This application establishes a mine mining database to monitor the mining situation and provide data for subsequent analysis of mine mining safety. Then, by establishing a list of safety event monitoring indicators, the mapping indicators related to safety events and events are determined, thereby traversing and extracting indicator information from the mine mining database to obtain event monitoring data. The monitoring data corresponding to the safety events are analyzed, and then feature analysis and identification are performed on the event monitoring data to determine whether there are features with clearly restricted numerical ranges in the event monitoring data. The feature data is then analyzed to determine whether there are risk events. If so, a feature safety warning message is sent to the staff to remind them. If not, a trend analysis is performed based on the event monitoring data to analyze whether there are risk trends during mine mining. When the trend analysis results indicate a risk event, a trend safety warning message is sent. The technical effect of improving the accuracy of safety warnings is achieved.

[0074] Example 2

[0075] Based on the same inventive concept as the safety early warning method based on mine mining data analysis in the above embodiment, Figure 4 As shown, the present application also provides a safety early warning system based on mine mining data analysis, wherein the system includes:

[0076] A database acquisition module 11, wherein the database acquisition module 11 is used to obtain a mine mining database;

[0077] A mapping indicator acquisition module 12 is used to construct a security event monitoring indicator list and obtain event mapping indicator information according to the security event monitoring indicator list;

[0078] A monitoring data acquisition module 13 is configured to perform index information traversal and extraction on the mine mining database according to the event mapping index information to obtain event monitoring data;

[0079] An analysis result determination module 14 is used to perform feature analysis and identification on the event monitoring data to determine feature analysis results;

[0080] The warning information sending module 15 is used to determine whether there is a risk event in the feature analysis result, and if so, send feature safety warning information;

[0081] A trend analysis and identification module 16, wherein the trend analysis and identification module 16 is configured to perform trend analysis and identification based on the event monitoring data when no trend analysis occurs, to obtain a trend analysis result;

[0082] The safety information sending module 17 is used to send trend safety warning information when there is a risk event in the trend analysis result.

[0083] Furthermore, the system further comprises:

[0084] An air quality information obtaining unit, the air quality information obtaining unit being used to monitor the air quality in the mine through air quality monitoring equipment to obtain mine air quality information;

[0085] a gas concentration information obtaining unit, the gas concentration information obtaining unit being used to monitor the gas concentration in the mine through a gas concentration monitoring device to obtain mine gas concentration information;

[0086] a wind speed information obtaining unit, the wind speed information obtaining unit being used to monitor the wind speed in the mine through a wind speed monitoring device to obtain the mine wind speed information;

[0087] an electromagnetic radiation information obtaining unit, the electromagnetic radiation information obtaining unit being used to monitor electromagnetic radiation in the mine through electromagnetic radiation monitoring equipment to obtain electromagnetic radiation information of the mine;

[0088] a mine sound information obtaining unit, the mine sound information obtaining unit being used to monitor the sound in the mine through a sound monitoring device to obtain mine sound information;

[0089] A monitoring data set construction unit, the monitoring data set construction unit being configured to construct a mine monitoring data set based on the mine air quality information, mine gas concentration information, mine wind speed information, mine electromagnetic radiation information, mine sound information, and corresponding monitoring time relationships;

[0090] A mining data set construction unit is used to obtain personnel positioning data, mining equipment operation data, and construct the mine mining database according to the time correspondence between the personnel positioning data, mining equipment operation data and the mine monitoring data set.

[0091] Furthermore, the system further comprises:

[0092] An accident record information obtaining unit, the accident record information obtaining unit being used to obtain historical safety accident record information;

[0093] An indicator cluster establishment unit, configured to classify security incidents based on the historical security incident record information and establish a security incident classification indicator cluster;

[0094] An indicator correlation determination unit, configured to perform a multi-event indicator correlation analysis on the security event classification indicator cluster to determine indicator correlation;

[0095] A monitoring indicator list construction unit is used to perform security event correlation mapping on each indicator in the security event classification indicator cluster based on the indicator correlation, and construct the security event monitoring indicator list.

[0096] Furthermore, the system further comprises:

[0097] A data identification and classification unit is used to identify and classify the environmental indicators and mining equipment operation data of the event monitoring data to obtain event monitoring-environmental indicator data and event monitoring-equipment monitoring data;

[0098] A data feature recognition unit, configured to perform data feature recognition analysis on the event monitoring-environmental indicator data and the event monitoring-equipment monitoring data, respectively, to determine environmental indicator features and equipment data features;

[0099] A data feature threshold obtaining unit, configured to obtain an event data feature threshold based on the security event monitoring indicator list;

[0100] A feature comparison unit is used to compare the environmental indicator features and the device data features based on the environmental indicator thresholds and the device parameter thresholds corresponding to the event data feature thresholds, and determine the feature analysis results.

[0101] Furthermore, the system further comprises:

[0102] a trend risk indicator analysis unit, configured to perform trend risk indicator analysis based on the historical safety accident record information, and determine trend risk indicators and trend indicator characteristics;

[0103] An indicator feature analysis unit, the indicator feature analysis unit is used to traverse the event monitoring data and the trend risk indicator to determine a matching trend risk indicator, and perform trend indicator feature analysis based on the matching trend risk indicator to obtain a trend indicator period feature and a trend indicator trend feature;

[0104] a correlation event detection data obtaining unit, the correlation event detection data obtaining unit being configured to obtain periodic correlation event monitoring data based on the trend indicator periodic characteristics and the event monitoring data;

[0105] A trend analysis result obtaining unit is used to perform trend coincidence analysis using the trend characteristics of the trend indicators and the period-related event monitoring data to obtain the trend analysis result.

[0106] Furthermore, the system further comprises:

[0107] a credibility determination unit, configured to perform transmission channel analysis on the personnel positioning data, the mining equipment operation data, and the mine monitoring data set, respectively, to determine the credibility of each transmission channel;

[0108] an identification and analysis result obtaining unit, configured to perform data identification and analysis on monitoring data whose credibility of the transmission channel does not meet preset requirements, and determine a data identification and analysis result;

[0109] A mine database acquisition unit is used to use the data recognition and analysis results to correct the personnel positioning data, mining equipment operation data, and mine monitoring data set, and use the corrected personnel positioning data, mining equipment operation data, and mine monitoring data set to construct the mine mining database.

[0110] Furthermore, the system further comprises:

[0111] A channel attribute obtaining unit, configured to obtain transmission channel attributes;

[0112] a transmission interference analysis unit, configured to perform transmission interference analysis based on the transmission channel attributes to determine channel transmission interference;

[0113] A channel credibility determination unit is configured to determine the credibility of each transmission channel based on the channel transmission interference.

[0114] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. Figure 1 The safety warning method based on mine mining data analysis and the specific examples in Example 1 are also applicable to the safety warning system based on mine mining data analysis in this embodiment. Through the above detailed description of the safety warning method based on mine mining data analysis, those skilled in the art can clearly understand the safety warning system based on mine mining data analysis in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0115] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one 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 present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A safety early warning method based on mine mining data analysis, characterized in that: The method comprises: Access to mine mining database; Constructing a security event monitoring indicator list, and obtaining event mapping indicator information according to the security event monitoring indicator list; Traversing and extracting indicator information from the mine mining database according to the event mapping indicator information to obtain event monitoring data; Performing feature analysis and identification on the event monitoring data to determine feature analysis results; Determine whether there is a risk event in the feature analysis result, and if so, send a feature safety warning message; If not present, performing trend analysis and identification based on the event monitoring data to obtain trend analysis results; When there is a risk event in the trend analysis result, send trend safety warning information; Access to mine development databases, including: Monitor the air quality in the mine through air quality monitoring equipment to obtain mine air quality information; Monitor the gas concentration in the mine through gas concentration monitoring equipment to obtain mine gas concentration information; Monitor the wind speed in the mine through wind speed monitoring equipment to obtain mine wind speed information; Monitor the electromagnetic radiation in the mine through electromagnetic radiation monitoring equipment to obtain the mine electromagnetic radiation information; Monitor the sound in the mine through sound monitoring equipment to obtain mine sound information; Constructing a mine monitoring data set based on the mine air quality information, mine gas concentration information, mine wind speed information, mine electromagnetic radiation information, mine sound information and their corresponding monitoring time; Obtaining personnel positioning data, mining equipment operation data, and constructing the mine mining database according to the time correspondence between the personnel positioning data, mining equipment operation data and the mine monitoring data set; The construction of the security event monitoring indicator list includes: Obtain historical safety accident records; Classify security incidents based on the historical security incident record information and establish a security incident classification indicator cluster; Performing a multi-event indicator correlation analysis on the security event classification indicator cluster to determine indicator correlation; Based on the indicator correlation, security event correlation mapping is performed on each indicator in the security event classification indicator cluster to construct the security event monitoring indicator list.

2. The method according to claim 1, wherein Performing feature analysis and identification on the event monitoring data to determine feature analysis results, including: Identifying and classifying the environmental indicators and mining equipment operation data of the event monitoring data to obtain event monitoring-environmental indicator data and event monitoring-equipment monitoring data; Performing data feature recognition and analysis on the event monitoring-environmental indicator data and the event monitoring-equipment monitoring data respectively to determine the environmental indicator features and the equipment data features; Obtaining event data feature thresholds based on the security event monitoring indicator list; Based on the environmental indicator threshold and the device parameter threshold corresponding to the event data feature threshold, the environmental indicator feature and the device data feature are compared respectively to determine the feature analysis result.

3. The method according to claim 1, wherein Perform trend analysis and identification based on the event monitoring data to obtain trend analysis results, including: Conduct trend risk indicator analysis based on the historical safety accident record information to determine trend risk indicators and their trend indicator characteristics; Traversing the event monitoring data and the trend risk indicator to determine a matching trend risk indicator, and performing trend indicator feature analysis based on the matching trend risk indicator to obtain a trend indicator period feature and a trend indicator trend feature; Based on the trend indicator periodic characteristics and the event monitoring data, obtaining period-related event monitoring data; The trend characteristics of the trend indicators and the period-related event monitoring data are used to perform trend coincidence analysis to obtain the trend analysis results.

4. The method according to claim 1, wherein Before constructing the mine mining database based on the time correspondence between the personnel positioning data, the mining equipment operation data and the mine monitoring data set, the following steps are included: Performing transmission channel analysis on the personnel positioning data, mining equipment operation data, and mine monitoring data set to determine the credibility of each transmission channel; For monitoring data whose credibility of the transmission channel does not meet the preset requirements, data identification and analysis are carried out to determine the data identification and analysis results; The data identification and analysis results are used to correct the personnel positioning data, mining equipment operation data, and mine monitoring data set, and the corrected personnel positioning data, mining equipment operation data, and mine monitoring data set are used to construct the mine mining database.

5. The method according to claim 4, wherein The method comprises: Get the transmission channel properties; Performing a transmission interference analysis based on the transmission channel attributes to determine the channel transmission interference; Based on the channel transmission interference, the credibility of each transmission channel is determined.

6. A safety early warning system based on mine mining data analysis, characterized in that: The system comprises: A database acquisition module, wherein the database acquisition module is used to obtain a mine mining database; A mapping indicator acquisition module, which is used to construct a security event monitoring indicator list and obtain event mapping indicator information based on the security event monitoring indicator list; A monitoring data acquisition module, configured to traverse and extract indicator information from the mine mining database according to the event mapping indicator information to obtain event monitoring data; An analysis result determination module, configured to perform feature analysis and identification on the event monitoring data to determine feature analysis results; An early warning information sending module is used to determine whether there is a risk event in the feature analysis result, and if so, send a feature safety early warning message; A trend analysis and identification module, wherein the trend analysis and identification module is used to perform trend analysis and identification based on the event monitoring data when no trend analysis exists, and obtain a trend analysis result; A safety information sending module, configured to send a trend safety warning message when a risk event occurs in the trend analysis result; Furthermore, the system further comprises: An air quality information obtaining unit, the air quality information obtaining unit being used to monitor the air quality in the mine through air quality monitoring equipment to obtain mine air quality information; a gas concentration information obtaining unit, the gas concentration information obtaining unit being used to monitor the gas concentration in the mine through a gas concentration monitoring device to obtain mine gas concentration information; a wind speed information obtaining unit, the wind speed information obtaining unit being used to monitor the wind speed in the mine through a wind speed monitoring device to obtain the mine wind speed information; an electromagnetic radiation information obtaining unit, the electromagnetic radiation information obtaining unit being used to monitor electromagnetic radiation in the mine through electromagnetic radiation monitoring equipment to obtain electromagnetic radiation information of the mine; a mine sound information obtaining unit, the mine sound information obtaining unit being used to monitor the sound in the mine through a sound monitoring device to obtain mine sound information; A monitoring data set construction unit, the monitoring data set construction unit being configured to construct a mine monitoring data set based on the mine air quality information, mine gas concentration information, mine wind speed information, mine electromagnetic radiation information, mine sound information, and corresponding monitoring time relationships; a mining data set construction unit, the mining data set construction unit being used to obtain personnel positioning data, mining equipment operation data, and construct the mine mining database according to the time correspondence between the personnel positioning data, mining equipment operation data and the mine monitoring data set; An accident record information obtaining unit, the accident record information obtaining unit being used to obtain historical safety accident record information; An indicator cluster establishment unit, configured to classify security incidents based on the historical security incident record information and establish a security incident classification indicator cluster; An indicator correlation determination unit, configured to perform a multi-event indicator correlation analysis on the security event classification indicator cluster to determine indicator correlation; A monitoring indicator list construction unit is used to perform security event correlation mapping on each indicator in the security event classification indicator cluster based on the indicator correlation, and construct the security event monitoring indicator list.

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