Coal mine mine pressure data processing method, device and electronic equipment

Abstract

This application provides a method, apparatus, and electronic device for processing coal mine pressure data. The method includes: acquiring coal mine pressure data; acquiring the target average value of multiple coal mine pressure data corresponding to multiple hydraulic supports at each step distance; determining the boosting data corresponding to the step distance based on the target average value; determining the boosting level corresponding to the boosting data; and determining the step distance for the next boosting data based on the boosting data. In this scheme, the target average value corresponding to multiple step distances can be determined based on the hydraulic data of the hydraulic supports, and then the boosting data corresponding to multiple step distances can be determined based on the relatively accurate target average value. This allows for accurate determination of the pattern of coal mine pressure changes, classification of the boosting data to determine the boosting intensity, and accurate prediction of the next boosting data, thereby solving the problem of low accuracy in coal mine pressure data processing in existing technologies.

Description

Technical Field

[0001] This application relates to the field of coal mine pressure technology, and more specifically, to a method, apparatus, and electronic device for processing coal mine pressure data. Background Technology

[0002] With the deepening adjustment of the energy structure, the coal mining industry is gradually entering a stage of unmanned and intelligent operation. Hydraulic supports, as one of the basic pieces of equipment for safe coal mine production, will inevitably be among the first to achieve automation and intelligence. If hydraulic supports enter the intelligent stage, the monitoring and analysis of mine pressure, which has a significant impact on the working status of hydraulic supports, must also become intelligent. However, current solutions have relatively low accuracy in processing mine pressure data. Summary of the Invention

[0003] The main objective of this application is to provide a method, apparatus, and electronic device for processing coal mine pressure data, so as to at least solve the problem of low accuracy in the processing of coal mine pressure data in the prior art.

[0004] To achieve the above objectives, according to one aspect of this application, a method for processing coal mine pressure data is provided, comprising: acquiring mine pressure data, wherein the mine pressure data is force data generated by rock displacement movement during coal mining on hydraulic supports, and the hydraulic supports correspond one-to-one with the mine pressure data; acquiring a target average value of multiple mine pressure data corresponding to multiple hydraulic supports for each step distance, wherein the step distance is the duration of the hydraulic support from the start of fluid injection to the depressurization time; determining pressure boosting data corresponding to the step distance based on the target average value, wherein the pressure boosting data refers to the data on the increase in pressure of the hydraulic supports caused by mine pressure caused by the coal mining face; determining the pressure boosting level corresponding to the pressure boosting data; and determining the step distance of the next pressure boosting data based on the pressure boosting data.

[0005] Optionally, obtaining the target average value of the multiple mine pressure data corresponding to the multiple hydraulic supports for each step distance includes: obtaining the first average value corresponding to the multiple mine pressure data within each target time period, wherein the step distance includes multiple target time periods; obtaining the second average value corresponding to the multiple first average values ​​of a hydraulic support within each step distance; and obtaining the target average value corresponding to the multiple second average values ​​of the multiple hydraulic supports within each step distance.

[0006] Optionally, obtaining the first average value corresponding to multiple mining pressure data within each target time period includes: dividing the collection time corresponding to the multiple mining pressure data into multiple target time periods according to a predetermined time interval, wherein a target time period includes multiple mining pressure data; obtaining the first sum of the multiple mining pressure data within the target time period; and obtaining the quotient of the first sum and the number of mining pressure data within the target time period to obtain the first average value.

[0007] Optionally, obtaining the second average value corresponding to the plurality of first average values ​​of a hydraulic support within each step distance includes: obtaining the second sum of the plurality of first average values ​​of a hydraulic support within the step distance; obtaining the quotient of the second sum and the number of first average values ​​within the step distance to obtain the second average value.

[0008] Optionally, obtaining the target average value corresponding to the multiple second average values ​​of the multiple hydraulic supports within each step distance includes: obtaining a third sum of the multiple second average values ​​of the multiple hydraulic supports within a step distance; obtaining the quotient of the third sum within a step distance and the number of hydraulic supports to obtain the target average value within a step distance.

[0009] Optionally, determining the pressure boosting data corresponding to the step distance based on the target average value includes: comparing the target average value corresponding to the current mine pressure data with multiple historical average values ​​to obtain a comparison result, wherein the historical average value is the average value obtained based on historical mine pressure data within a historical time period; determining the target historical average value based on the comparison result, and determining the pressure boosting data corresponding to the target historical average value as the target pressure boosting data corresponding to the current mine pressure data.

[0010] Optionally, determining the boost level corresponding to the boost data includes: when the boost data is less than or equal to a first threshold, determining the boost level corresponding to the boost data as a first boost level; when the boost data is greater than the first threshold and less than or equal to a second threshold, determining the boost level corresponding to the boost data as a second boost level, wherein the first threshold is less than the second threshold, and the boost intensity corresponding to the first boost level is less than the boost intensity of the second boost level; when the boost data is greater than the second threshold and less than or equal to a third threshold, determining the boost level corresponding to the boost data as a third boost level, wherein the second threshold is less than the third threshold, and the boost intensity corresponding to the second boost level is less than the boost intensity of the third boost level; when the boost data is greater than the third threshold and less than or equal to a fourth threshold, determining the boost level corresponding to the boost data as a fourth boost level, wherein the third threshold is less than the fourth threshold, and the boost intensity corresponding to the third boost level is less than the boost intensity of the fourth boost level.

[0011] Optionally, determining the step size for the next boost data based on the boost data includes: obtaining the step size corresponding to the Nth boost data, the step size corresponding to the (N-1)th boost data, and the step size corresponding to the (N-2)th boost data, where N is greater than or equal to 2; obtaining a first weighting coefficient, a second weighting coefficient, and a third weighting coefficient for the step size corresponding to the Nth boost data, where the first weighting coefficient is less than the second weighting coefficient, and the second weighting coefficient is less than the third weighting coefficient; obtaining a first product of the step size corresponding to the Nth boost data and the first weighting coefficient, a second product of the step size corresponding to the (N-1)th boost data and the second weighting coefficient, and a third product of the step size corresponding to the (N-2)th boost data and the third weighting coefficient; obtaining a fourth sum of the first product, the second product, and the third product, and determining the fourth sum as the step size corresponding to the (N+1)th boost data.

[0012] According to another aspect of this application, a coal mine pressure data processing device is provided, comprising: a first acquisition unit for acquiring mine pressure data, wherein the mine pressure data is the force data generated by rock displacement movement on hydraulic supports during coal mining, and the hydraulic supports correspond one-to-one with the mine pressure data; a second acquisition unit for acquiring a target average value of multiple mine pressure data corresponding to multiple hydraulic supports for each step distance, wherein the step distance is the duration of the hydraulic support from the start of injection to the depressurization time; a first determination unit for determining pressurization data corresponding to the step distance based on the target average value, wherein the pressurization data refers to the data on the pressure increase of the hydraulic supports caused by mine pressure caused by the coal mining face; and a second determination unit for determining the pressurization level corresponding to the pressurization data and determining the step distance of the next pressurization data based on the pressurization data.

[0013] According to another aspect of this application, an electronic device is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including methods for performing any one of the methods described.

[0014] By applying the technical solution of this application, the target average value corresponding to multiple step distances can be determined based on the hydraulic data of the hydraulic support. Then, the pressurization data corresponding to multiple step distances can be determined based on the relatively accurate target average value. That is, the law of mine pressure change can be accurately determined. At the same time, the pressurization data of mine pressure can be classified into levels to determine the intensity of pressurization. The next pressurization data can also be accurately predicted, thereby solving the problem of low accuracy in the processing of mine pressure data in coal mines in the prior art. Attached Figure Description

[0015] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0016] Figure 1 A hardware structure block diagram of a mobile terminal for performing a method for processing coal mine pressure data according to an embodiment of this application is shown.

[0017] Figure 2 A flowchart illustrating a method for processing mine pressure data in a coal mine according to an embodiment of this application is shown.

[0018] Figure 3 A schematic diagram showing the data of the first and second average values ​​within the step size is presented;

[0019] Figure 4A schematic diagram illustrating the effect of step pressure is shown;

[0020] Figure 5 A flowchart illustrating the revision process is shown;

[0021] Figure 6 A schematic diagram of the interval division profile is shown;

[0022] Figure 7 A schematic plan view showing the division of the coal mining face into sections is shown;

[0023] Figure 8 A flowchart illustrating the data calculation process within the interval is shown;

[0024] Figure 9 A flowchart illustrating the process of determining the boost step within a given interval is shown.

[0025] Figure 10 A schematic diagram of the overall pressurization curve of the working face is shown;

[0026] Figure 11 A flowchart illustrating another method for processing mine pressure data in coal mines is shown.

[0027] Figure 12 A schematic diagram illustrating the data relationships between multiple mining pressure data points is shown.

[0028] Figure 13 A structural block diagram of a coal mine pressure data processing apparatus provided according to an embodiment of this application is shown.

[0029] The above figures include the following reference numerals:

[0030] 102. Processor; 104. Memory; 106. Transmission device; 108. Input / output device. Detailed Implementation

[0031] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0032] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0033] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0034] For ease of description, the following explains some of the nouns or terms used in the embodiments of this application:

[0035] (1) Longwall mining: This method mainly involves mining along the strike direction of the coal seam. The mining method is to mine from the boundary towards the mining area in the direction of going uphill (or downhill).

[0036] (2) Opening cut: The starting point for the advance of the coal mining face. That is, the position of the coal mining face when the advance is 0 is called the opening cut.

[0037] (3) Advance: The distance the working face advances is called the advance, which is the distance between the current working face and the opening.

[0038] (4) Upper (Lower) Roadway: In coal mines, roadways specifically refer to the intake or return airways of the longwall face. The upper roadway is the upper roadway, and the lower roadway is the lower roadway. The upper roadway is the track roadway, used for personnel to walk or transport materials. The lower roadway is the belt conveyor roadway, used to install belt conveyors to transport coal.

[0039] After coal mining, the original stress of the rock mass surrounding the goaf is inevitably disrupted, causing a redistribution of stress and reaching a new equilibrium. During this process, continuous movement, deformation, and discontinuous damage (cracking, collapse, etc.) occur in the rock strata and surface, leading to subsidence, collapse, and increased pressure in the mine and roadway roofs, endangering the safety of underground personnel and equipment. Taking roof collapse accidents as an example, roof collapse accidents have consistently been the leading cause of death in coal mines. Since 1990, roof collapse accidents have accounted for over 45% of all coal mine fatalities. While this number has decreased with advancements in support technology, effectively controlling roof collapse and ensuring the safety of underground personnel remains a key area for future research. Moreover, with the continuous increase in mining depth in my country's coal mines, more and more mines are entering deep-well mining, making this dynamic disaster increasingly serious. Mining accidents are characterized by their suddenness, diversity, destructiveness, and complexity. When a roof collapse occurs, it often causes the movement and damage of various underground equipment, as well as the collapse and blockage of roadways. This not only affects the normal production of the mine, but also poses a serious threat to the life safety of underground workers.

[0040] With the deepening adjustment of the energy structure, the coal mining industry is gradually entering a stage of unmanned and intelligent operation. Hydraulic supports, as one of the basic pieces of equipment for safe coal mine production, will inevitably be among the first to achieve automation and intelligence. If hydraulic supports enter the intelligent stage, the monitoring and analysis of mine pressure, which has a significant impact on the working state of hydraulic supports, must also become intelligent. Therefore, conducting intelligent analysis research on mine pressure data from the coal mine roof is the foundation for the intelligentization of hydraulic supports.

[0041] Currently, coal mine pressure data processing is limited to data acquisition, transmission, storage, and basic data display. In-depth, automated analysis of pressure data is lacking. This includes refining the true structure of the overlying strata of the coal face, the basic motion parameters of each rock beam (initial and periodic pressure increments), the distribution patterns of supporting pressure, and the prediction and forecasting of roof pressure during mining. For a long time, mine pressure research has relied primarily on observation, using the processing and analysis of observational data to determine the pressure situation ahead of the coal face. However, due to the inability to obtain analytical data in real time and the significant simplifications in data analysis, current conventional mine pressure analysis methods—the Pt curve method and linear regression-based methods—both have their limitations in practice.

[0042] Commonly used methods for analyzing and processing mine pressure data include:

[0043] (1) Pt curve method for mine pressure analysis. The Pt curve method is a commonly used data analysis method for mine pressure analysis for many years. This method has the advantages of being simple and clear, easy to operate, and requiring relatively little data. The biggest drawback of this method is that it can only analyze the line data formed by a single hydraulic support. It is somewhat lacking in how to combine and analyze the data of multiple hydraulic supports, especially when the curves of multiple hydraulic supports are inconsistent.

[0044] (2) Mine pressure analysis methods based on linear regression mainly include multiple linear regression analysis, adaptive regression prediction, and ridge regression prediction. This method has the advantages of comprehensive consideration of the problem and high consistency between the analysis results and the actual situation. However, since the linear regression analysis method involves a variety of influencing factors, the model and parameter system are not the same for different working faces. There is a lack of corresponding solutions for mine pressure data of multiple hydraulic supports, hydraulic data of multiple steps, and massive hydraulic data.

[0045] The following conclusions can be drawn from the analysis of various conventional mine pressure analysis methods:

[0046] (1) Traditional analysis methods are based on traditional manual or intermittent data collection. They have the advantages of requiring less data and being easy to operate, but they have limitations in judging the movement law of the top plate, especially the local movement law and the working state of the hydraulic support.

[0047] (2) With the widespread adoption of electro-hydraulic control systems, real-time monitoring of the stress on hydraulic support columns is now possible. Up to 10 million pressure readings can be collected per day from a single working face. Coal mine safety management requires not only analysis of the overall movement of the working face roof, but also analysis of local roof conditions and even the condition of the coal seam's top and bottom. The era of big data necessitates new data analysis methods.

[0048] As described in the background section, the accuracy of coal mine pressure data processing in the prior art is low. To solve the problem of low accuracy of coal mine pressure data processing, embodiments of this application provide a coal mine pressure data processing method, apparatus, and electronic device.

[0049] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0050] The methods and embodiments provided in this application can be executed on a mobile terminal, computer terminal, or similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for a method of processing coal mine pressure data according to an embodiment of the present invention. Figure 1As shown, a mobile terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0051] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the device information display method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The transmission device 106 is used to receive or send data via a network. Specific examples of the aforementioned networks may include wireless networks provided by the mobile terminal's communication provider. In one example, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0052] This embodiment provides a method for processing mine pressure data in a coal mine that runs on a mobile terminal, computer terminal, or similar computing device. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0053] Figure 2 This is a flowchart illustrating a method for processing mine pressure data in a coal mine according to an embodiment of this application. Figure 2 As shown, the method includes the following steps:

[0054] Step S201: Obtain mine pressure data, wherein the mine pressure data is the force data generated by rock displacement movement during coal mining on the hydraulic support, and the hydraulic support corresponds one-to-one with the mine pressure data.

[0055] Specifically, mine pressure data can be collected through sensors, or through other means.

[0056] Specifically, mine pressure data can be collected through the downhole electro-hydraulic control system. This data includes current and historical mine pressure data, which can be uploaded to a storage system (such as a database or distributed cache). This allows for the storage of mine pressure data for all hydraulic supports and the construction of a detection data sample library (Data[i] containing mine pressure data samples).

[0057] Step S202: Obtain the target average value of the multiple mine pressure data corresponding to the multiple hydraulic supports for each step distance, wherein the step distance is the duration of the hydraulic support from the start of injection to the depressurization time.

[0058] Specifically, the coal mining face can be divided into multiple steps, and each step corresponds to multiple hydraulic supports and multiple mining pressure data. The target average value can be obtained based on the multiple mining pressure data corresponding to multiple hydraulic supports, and the target average value can be used to determine the pressure boosting data within the step.

[0059] Step S203: Determine the pressure increase data corresponding to the step distance based on the above target average value, wherein the above pressure increase data refers to the data on the increase in pressure of the above hydraulic support caused by the mine pressure caused by the coal mining face;

[0060] Specifically, the pressure increase within the step distance can be determined based on the target average value of the accurate step distance of the coal mining face, thus accurately determining the pattern of mine pressure changes.

[0061] Step S204: Determine the boost level corresponding to the above boost data, and determine the step size of the next boost data based on the above boost data.

[0062] Specifically, the pressure boosting data of the mine can be classified into levels to determine the intensity of the boosting, and the next boosting data can be accurately predicted.

[0063] This embodiment allows for the determination of target average values ​​corresponding to multiple step distances based on the hydraulic data of the hydraulic support. Furthermore, based on these relatively accurate target average values, the pressure boosting data corresponding to multiple step distances can be determined, thus accurately determining the pattern of mine pressure changes. Additionally, the pressure boosting data can be categorized to determine the intensity of the boosting, and the next pressure boosting data can be accurately predicted. This solves the problem of low accuracy in processing coal mine pressure data in existing technologies.

[0064] This solution can reveal the overall movement pattern of the coal seam roof, realize the automatic analysis and decision-making of mine pressure data, predict the movement pattern of the overlying strata, avoid the occurrence of safety accidents at the production site, ensure the normal production of the mine, and protect the lives of underground workers. On the other hand, it also represents an innovative step towards the unmanned and intelligent operation stage of the coal mining industry.

[0065] This solution can also solve the data errors caused by inaccurate footage, significant influence of the on-site environment, and non-standard operation by front-line operators in traditional mine pressure analysis. It can also adapt to situations such as rapid deformation of hydraulic supports and abnormal movement of the roof due to local changes in the roof structure.

[0066] To obtain a more accurate target average, the step distance can be further divided into time periods to improve the accuracy of the target average. Specifically, to obtain the target average of multiple mining pressure data corresponding to multiple hydraulic supports within each step distance, the following steps can be taken: obtaining the first average value corresponding to multiple mining pressure data within each target time period, where the step distance includes multiple target time periods; obtaining the second average value corresponding to multiple first average values ​​of one hydraulic support within each step distance; and obtaining the target average value corresponding to multiple second average values ​​of multiple hydraulic supports within each step distance.

[0067] In this scheme, since the working environment at the working face is relatively complex, it cannot be guaranteed that all the collected mine pressure data are valid. Therefore, the target average value can be obtained by averaging. First, the step distance is divided again to obtain multiple relatively accurate first average values ​​for multiple target time periods within the step distance. Then, the average value of multiple first average values ​​is calculated again to obtain multiple second average values. Finally, the average value of multiple second average values ​​is calculated to obtain a relatively accurate target average value, avoiding the situation where the target average value is inaccurate due to invalid data.

[0068] Specifically, the data for the first and second average values ​​within the step are as follows: Figure 3 As shown, a single step includes multiple target time periods, and each target time period includes multiple mining pressure data points. Figure 3The height of the rectangle represents the size of the first average data point, the width of the rectangle represents the duration of the target time period, and the second average is obtained based on multiple first averages. Figure 3 The circle in the diagram represents the data size of the second average.

[0069] Specifically, this solution further explains the step distance. Step distance refers to the time period from the start of fluid injection, when the hydraulic support is in a pressure-holding state, until the pressure-holding state ends during the depressurization period. This time of pressure-holding operation is typically called a step distance. The initial support force and final resistance of the step distance can also be obtained from the step distance, such as... Figure 4 As shown, the initial support force P0 refers to the initial working resistance of the hydraulic support after it is moved; the final resistance P... m It refers to the working resistance before the last frame movement within the step distance. Under normal circumstances, the resistance at the end of the step distance is the maximum working resistance within the step distance.

[0070] This plan involves multiple variables, which are explained below:

[0071] (1) i: The mine pressure data on the hydraulic support is sorted by time point, and this value represents the i-th value;

[0072] (2)t: The mine pressure data on the hydraulic support is cut into equal time intervals. This value represents the TimeInterval[t] (first average value) of the t-th target time period;

[0073] (3) k: The mine pressure data on the hydraulic support is split according to the step distance. This value represents the StepLength[k] (second average value) of the kth step distance, or the StepPhase[k] (second average value) of the kth step distance in the interval;

[0074] (4) w: The working face is divided into intervals according to requirements. This value represents the wth interval.

[0075] (5) a: An ordinary integer variable, which takes the value 1, 2, or other values;

[0076] (6)n t : Represents the number of mine pressure data Data[i] in the t-th time interval on the hydraulic support;

[0077] (7)n k : Represents the number of the first average value TimeInterval[i] within the k-th movement step of the hydraulic support;

[0078] (8) u: Represents the number of all hydraulic supports in this interval;

[0079] (9) n: represents the number of all step stages in the interval.

[0080] Due to the complex working environment at the working face, it cannot be guaranteed that all collected mine pressure data are valid. To save storage space, existing mine pressure data collection can adopt a "sampling only when there is a large fluctuation" approach, meaning that mine pressure data is only recorded when there is a significant fluctuation. Therefore, there is no valid data at some points in time. In such cases, it is necessary to perform standardized analysis and processing on the mine pressure data. The method of obtaining the first average value corresponding to multiple mine pressure data within each target time period can be achieved through the following steps: dividing the collection time corresponding to multiple mine pressure data into multiple target time periods according to a predetermined time interval, wherein each target time period includes multiple mine pressure data; obtaining the first sum of multiple mine pressure data within the target time period; obtaining the quotient of the first sum and the number of mine pressure data within the target time period to obtain the first average value.

[0081] In this scheme, the mine pressure data corresponding to all hydraulic supports on the working face can be divided into the same predetermined time interval (such as 1 minute, 2 minutes, etc.). Then, the quotient of the first sum and the number of mine pressure data can be extracted to obtain a relatively accurate first average value, thereby ensuring that a relatively accurate target average value can be obtained based on the first average value in the future.

[0082] Specifically, the formula for calculating the first average value can be:

[0083] TimeInterval[t].AVG_Data=(1 / n t )∑n t i = 1 / Data[i], where TimeInterval[t].AVG_Data represents the first average value within the t-th target time period, TimeInterval[t] represents the t-th target time period of the mine pressure data, and Data[i] represents the mine pressure data. The above formula is merely exemplary, and any variation of the formula falls within the protection scope of this application.

[0084] Since the hydraulic support operation process (lowering, moving, raising) generally takes 10 to 40 seconds, there may be differences between the real-time and phased nature of the mine pressure data. In order to eliminate the difference between the real-time mine pressure data and the mine pressure data entered on site during data analysis, the present application obtains the second average value corresponding to the multiple first average values ​​of a hydraulic support within each of the above-mentioned step distances through the following steps: obtaining the second sum of the multiple first average values ​​of a hydraulic support within the above-mentioned step distances; obtaining the quotient of the second sum and the number of the first average values ​​within the above-mentioned step distances to obtain the second average value.

[0085] In this scheme, based on obtaining multiple first average values, the mine pressure data can be divided into steps. The multiple first average values ​​corresponding to the hydraulic support can be sorted according to time sequence. If the current time is greater than the initial support force designed for the hydraulic support (i.e., the time when the hydraulic support begins to support the roof), it is marked as the start of a step, and this step ends when the current time exceeds the minimum threshold value for step selection. The mine pressure data on the hydraulic support within this time range constitutes the mine pressure data within a step. Then, by calculating the average value, the second average value corresponding to the multiple first average values ​​within the step is obtained. This ensures that the obtained second average value reflects the average change of the mine pressure data within that step, thus guaranteeing that a relatively accurate target average value can be obtained subsequently based on the second average value.

[0086] Specifically, the formula for calculating the second average can be:

[0087] StepLength[k].AVG_Data = (1 / n) k )∑n k i=1TimeInterval[i].AVG_Data,

[0088] Where StepLength[k].AVG_Data represents the second average value within the k-th step, and StepLength[k] represents the k-th step. The above formula is merely exemplary, and any variation of the formula falls within the protection scope of this application.

[0089] This scheme can also revise the upper cog UCH_FA(t) and lower cog DCH_FA(t), such as... Figure 5 As shown, the process of revising the upper channel UCH_FA(t) is as follows:

[0090] If the measured advance at the j-th and s-th step distances were measured on-site, now we revise the cumulative advance (j) at a certain step distance between j and s. <t<s),

[0091] First step: Mark the data, let UCH_FA_S(j) represent the measured advance of the j-th step of the upper feedway, and let UCH_FA_S(s) represent the measured advance of the s-th step of the upper feedway;

[0092] The second step: Calculate the single step advance value used in the current section. The formula is as follows:

[0093] OC_FA(1)=(UCH_FA_S(s)-UCH_FA(j)) / (s-j+1);

[0094] Third step: Calculate the cumulative advance of the upper roadway at the t-th step distance. The formula is as follows:

[0095] UCH_FA(t)=UCH_FA(j)+OC_FA(1)*(tj);

[0096] Fourth step: When UCH_FA(j) = UCH_FA_S(j), the cumulative advance and measured advance data are revised.

[0097] The process of revising the downgate DCH_FA(t) is as follows:

[0098] Assuming the measured advance at the j-th and s-th step distances were measured on-site, we now want to revise the cumulative advance (j) at a certain step distance between j and s. <t<s),

[0099] First step: Mark the data, let: DCH_FA_S(j) represent the measured advance of the j-th step of the lower roadway, and DCH_FA_S(s) represent the measured advance of the s-th step of the lower roadway;

[0100] The second step: Calculate the single step advance value used in the current section. The formula is as follows:

[0101] OC_FA(2)=(DCH_FA_S(s)-DCH_FA(j)) / (s-j+1);

[0102] Third step: Calculate the cumulative advance of the upper roadway at the t-th step distance. The formula is as follows:

[0103] DCH_FA(t)=DCH_FA(j)+OC_FA(2)*(tj);

[0104] Fourth step: When DCH_FA(j) = DCH_FA_S(j), the cumulative advance and measured advance data are revised.

[0105] After revising the upper roadway UCH_FA(t) and lower roadway DCH_FA(t), the overall working face Sum_FA(i) needs to be calculated. The formula used to determine the cumulative advance at the i-th step can be...

[0106] Sum_FA(t) = (UCH_FA(t) + DCH_FA(t)) / 2, meaning the advance of the working face is the average of the advances of the upper and lower roadways.

[0107] The meanings of each parameter in the above revision process are as follows:

[0108] (1) UCH_FA(k): represents the cumulative advance of the k-th step distance in the upper feedway;

[0109] (2) DCH_FA(k): represents the cumulative advance of the k-th step in the lower feed roadway;

[0110] (3) UCH_FA_S(k): Represents the measured advance of the kth step of the upper feed groove;

[0111] (4)DCH_FA_S(k): Represents the measured advance of the k-th step of the lower feed roadway;

[0112] (5) OC_FA(a): Temporary variable for single step advance (OC_FA(1) for upper groove, OC_FA(2) for lower groove);

[0113] (6) Sum_FA(k): represents the cumulative advance of the working face at the kth step.

[0114] This solution can also divide the hydraulic support's mine pressure data into different processing intervals along the working face's inclination direction. The working face can be divided into multiple intervals (e.g., 5-7 intervals) using the inclination direction as the transverse direction, to analyze the pressure state of different sections of the working face within the same time period. A cross-sectional view of the working face divided into multiple intervals is shown below. Figure 6 As shown, it can be divided into the original stress zone, compression zone, decompression zone, collision zone, and pressure recovery zone.

[0115] The process of dividing the coal face into intervals is as follows: Measure the length L of the coal face, and set the number of intervals. The number of intervals can be odd, and a division table can be used for specific division.

[0116] Table 1: Reference Table for Interval Division

[0117] Length L of the coal mining face (unit: meters) Number of intervals 0<L<＝150 3 150<L<＝350 5 350<L 7

[0118] The coal mining face can be divided based on the number of the hydraulic supports. The distance between the first and last intervals is the same. The width of the interval is calculated by converting the center distance of the hydraulic supports. The width of the interval is equal to 1-1.5 times the periodic pressure increase step distance of the coal mining face. Each interval contains multiple hydraulic supports. The length of the other intervals is divided into the first and last intervals, and the length of the remaining intervals is divided equally according to the number of remaining intervals.

[0119] The plan view of the coal mining face is shown below. Figure 7 As shown, the horizontal line represents the strike length of the coal mining face, and the vertical line represents the dip length of the coal mining face. The coal mining face can be divided into 5 sections, and the rectangle in the middle represents the hydraulic support.

[0120] After dividing the intervals, a certain interval of the working face can be used as the analysis subject, or all intervals of the working face can be used as the analysis subject. Data analysis is carried out in the working face advancement direction. Since the data of each interval can be analyzed independently, and an interval includes the mine pressure data corresponding to multiple hydraulic supports, the data of multiple hydraulic supports can be integrated to obtain the target average value. The target average value corresponding to the multiple second average values ​​of multiple hydraulic supports within each step distance can be achieved through the following steps: obtaining the third sum of the multiple second average values ​​of multiple hydraulic supports within a step distance; obtaining the quotient of the third sum within a step distance and the number of hydraulic supports to obtain the target average value within a step distance.

[0121] In this scheme, the target average value can be obtained from multiple second average values ​​within each step, which can ensure that the obtained target average value can reflect the average change of the mine pressure data within that step, thus ensuring that the obtained target average value is relatively accurate.

[0122] Specifically, such as Figure 8 As shown, the process of calculating the target average value can also be as follows:

[0123] First step: Data partitioning. The hydraulic supports are divided into their respective intervals SuppPhase according to the support number, or sorted according to the time series. Each interval dataset SuppPhase[w] contains the mine pressure data of multiple hydraulic supports Support[k]. The data from the start support to the end support in the interval are traversed once. The cumulative step distance sequence number in the interval is taken as the support number between the start and the end.

[0124] The second step: Determine the working status of the hydraulic support. If...

[0125] StepLength[k]_WorkIngState = True, meaning the hydraulic support is in normal working condition, and data in abnormal working condition will not be included in subsequent data calculations;

[0126] Third step: Extract the target average value AVG_Data for each step phase StepPhase[k] of all hydraulic supports within the interval SuppPhase[w]. This can be calculated using the following formula:

[0127] SuppPhase[w].StepPhase[k].AVG_Data=(1 / u)∑ui=1Support[i].StepLength[k].AVG_Data

[0128] Fourth step: Horizontal integration of data. Based on the average value of each target, the data of numerous hydraulic supports in this interval are organized into a data signal change curve to obtain SuppPhase[w].StepPhase[k].AVG_Data, which is the step stage average value change curve of the w-th interval, and the pressure state of different areas in the inclined direction of the working face is obtained.

[0129] The meanings of the above parameters are as follows:

[0130] (1)Support[i]: represents the i-th hydraulic support in this interval;

[0131] (2)Support[i].StepLength[k]: Represents the i-th hydraulic support that is simultaneously in the k-th step length of the interval;

[0132] (3)Support[i].StepLength[k].AVG_Data: Represents the target average value of the i-th hydraulic support that is simultaneously in the k-th step length of the interval;

[0133] (4)SuppPhase[w]: Represents the data generated in the w-th interval;

[0134] (5)SuppPhase[w].StartsupBh: Represents the starting bracket number of the w-th interval;

[0135] (6) SuppPhase[w].EndSupBh: Represents the end support number of the w-th interval.

[0136] (7)SuppPhase[w].OC_Number: Represents the sequence number of the cumulative step size in the w-th interval;

[0137] (8)StepLength[k]_WorkingState: The working state of the hydraulic support within the kth step distance on the support;

[0138] (9)Support[i].StepLength[k].AVG_Data: Represents the target average value of the k-th step length of the i-th support in the interval;

[0139] (10)SuppPhase[w]: Represents the w-th interval on the working face of the mine pressure;

[0140] (11)StepPhase[k]: Process the data of all supports in the interval that are simultaneously at the kth step distance Support[i].StepLength[k] into a single value, which represents the kth interval step distance of the interval;

[0141] (12)SuppPhase[w].StepPhase[k].AVG_Data: Represents the target average value of the k-th interval step distance on the w-th interval of the mining pressure working face.

[0142] In some embodiments, the pressure boosting data corresponding to the step distance is determined based on the target average value. Specifically, this can be achieved through the following steps: comparing the target average value corresponding to the current mine pressure data with multiple historical average values ​​to obtain a comparison result, wherein the historical average value is the average value obtained based on historical mine pressure data within a historical time period; determining the target historical average value based on the comparison result, and determining the pressure boosting data corresponding to the target historical average value as the target pressure boosting data corresponding to the current mine pressure data.

[0143] In this scheme, the historical average values ​​are relatively accurate data within the historical time period, and the average values ​​of the historical mine pressure data within the historical time period all have corresponding pressure boosting data. The method of directly determining the target pressure boosting data by comparing the results is relatively simple and direct, which can avoid complex calculation processes and ensure that this scheme can determine the target pressure boosting data relatively quickly and accurately.

[0144] In some embodiments, determining the boost level corresponding to the boost data can be achieved through the following steps: when the boost data is less than or equal to a first threshold, the boost level corresponding to the boost data is determined to be a first boost level; when the boost data is greater than the first threshold and less than or equal to a second threshold, the boost level corresponding to the boost data is determined to be a second boost level, wherein the first threshold is less than the second threshold, and the boost intensity corresponding to the first boost level is less than the boost intensity corresponding to the second boost level; when the boost data is greater than the second threshold... If the boost data is less than or equal to the third threshold, the boost level corresponding to the boost data is determined to be the third boost level, wherein the second threshold is less than the third threshold, and the boost intensity corresponding to the second boost level is less than the boost intensity of the third boost level; if the boost data is greater than the third threshold, and the boost data is less than or equal to the fourth threshold, the boost level corresponding to the boost data is determined to be the fourth boost level, wherein the third threshold is less than the fourth threshold, and the boost intensity corresponding to the third boost level is less than the boost intensity of the fourth boost level.

[0145] In this scheme, there are multiple thresholds related to the boost data. This allows for comparison of the boost data with the magnitude of multiple thresholds, and thus the boost level corresponding to the boost data can be determined more accurately based on the magnitude of the boost data with the multiple thresholds.

[0146] Specifically, the process of determining the boost step is as follows: Figure 9 As shown, 5-7 intervals of the working face can be used as the main body of analysis. Data analysis can be carried out in the direction of working face advancement. Through the self-learning function of the roof movement law and processing threshold, the extreme point of the curve in the time axis direction can be found, thereby determining the basic movement law of the roof.

[0147] The parameters involved in determining the boost step distance are as follows:

[0148] (1)SuppPhase[w]: represents the w-th interval on the working face of the mine pressure;

[0149] (2) StepPhase[k]: Simultaneously place all hydraulic supports in the interval at the kth step distance.

[0150] The data of Support[i].StepLength[k] is processed into a single value, representing the kth interval step distance of that interval;

[0151] (3)SuppPhase[w].StepPhase[k].AVG_Data: Represents the target average value of the k-th interval step distance on the w-th interval of the mining pressure working face;

[0152] (4)EightHourAVG: The average value within 8 hours (historical average value), that is, the average value of data within 8 hours within the interval;

[0153] Value selection method: the average step size within 8 hours. If there is only one step size within 8 hours, the value is the average of that step size. If there are multiple step sizes, the value is the average of the multiple step sizes.

[0154] (5) OneDayAVG: The average value within one day (historical average value), that is, the average value of data within 24 hours within the interval;

[0155] Value retrieval method: The average step distance within 24 hours. If there is only one step distance within 24 hours, the value is the average of this step distance. If there are multiple step distances, the value is the average of the multiple step distances.

[0156] (6) ThreeDayAVG: The average value over 3 days (historical average value), that is, the average value of data within 72 hours within the interval;

[0157] Value selection method: the average step size within 72 hours. If there is only one step size within 72 hours, the value is the average of this step size. If there are multiple step sizes, the value is the average of the multiple step sizes.

[0158] (7) FiveDayAVG: The average value over 5 days (historical average value), that is, the average value of data within 120 hours within the interval;

[0159] Value selection method: the average step size within 120 hours. If there is only one step size within 120 hours, the value is the average of that step size. If there are multiple step sizes, the value is the average of the multiple step sizes.

[0160] (8)TenDayAVG: The average value over 10 days (historical average value), that is, the average value of data within 240 hours within the interval;

[0161] Value selection method: the average step size within 240 hours. If there is only one step size within 240 hours, the value is the average of that step size. If there are multiple step sizes, the value is the average of the multiple step sizes.

[0162] (9) FifteenDayAVG: The average value over 15 days (historical average value), that is, the average value of data within 360 hours within the interval;

[0163] Value selection method: the average step size over 360 hours. If there is only one step size within 360 hours, the value is the average of that step size. If there are multiple step sizes, the value is the average of the multiple step sizes.

[0164] (10) TwentyDayAVG: The average value over 20 days (historical average value), that is, the average value of data within 480 hours within the interval;

[0165] Value selection method: the average step size within 480 hours. If there is only one step size within 480 hours, the value is the average of that step size. If there are multiple step sizes, the value is the average of the multiple step sizes.

[0166] (11)Prev_ThreeOC_AVG: The mean of the first 3 steps (historical average), that is, the mean of the first 3 steps within the interval (historical average).

[0167] Value selection method: Take the average of the first 3 step distances. If the first 3 step distances are less than 3, then take the average of all step distances (historical average).

[0168] (12)Prev_FiveOC_AVG: The average of the first 5 steps (historical average), that is, the average of the first 5 steps within the interval;

[0169] Value selection method: Take the average of the first 5 step distances; if the first step distance is less than 5, then take the average of all step distances.

[0170] (13)Prev_TenOC_AVG: The mean of the first 10 steps (historical average), that is, the mean of the first 10 steps within the interval;

[0171] Value selection method: Take the average of the first 10 step distances; if the first 10 step distances are less than 10, then take the average of all step distances.

[0172] (14)Prev_FifteenOC_AVG: The mean of the first 15 steps (historical average), that is, the mean of the first 15 steps within the interval;

[0173] Value selection method: Take the average of the first 15 step distances; if the first 15 step distances are less than 15, then take the average of all step distances.

[0174] (15)Prev_TwentyOC_AVG: The mean of the first 20 steps (historical average), that is, the mean of the first 20 steps within the interval;

[0175] Value selection method: Take the average of the first 20 step distances; if the first 20 step distances are less than 20, then take the average of all step distances.

[0176] (16)PressWeight[i]: Represents the pressurization data of the i-th pressurization step in this interval;

[0177] (17)Prev_AVG_PressWeight: The average value of PressWeight for all steps before the current step in this interval;

[0178] Prev_AVG_PressWeight=(1 / n)∑ni=1PressWeight[i],

[0179] (18)AVG_Data = SuppPhase[t].AVG_Data: Represents the second average value within the i-th boost step in this interval;

[0180] (19)Prev_AVG_Data: Represents the average pressure data of SuppPhase[k].AVG_Data for all step phases prior to the current step phase in this interval;

[0181] Prev_AVG_Data=(1 / n)∑ni=1SuppPhase[w].StepPhase[k].AVG_Data.

[0182] Based on this, AVG_Data for each interval can be obtained and processed separately. The AVG_Data is compared with the historical average. Each historical average corresponds to a pressure weight, which is a coefficient used to evaluate whether the current stride is a pressure-increasing stride. Within each interval, the AVG_Data for each stride is compared with the historical average ***_AGV. The judgment criteria in Table 2 can be used to determine the pressure weight of that pressure-increasing stride.

[0183] Table 2: Comparison of Target Average and Historical Average

[0184]

[0185]

[0186] Next, determine the roof pressure level (ComePress) within the step distance. The ComePress value indicates the roof pressure level within that step distance. Within the interval, compare the Press Weight value of each step distance with the threshold value using Table 3 to determine the pressure level within that step distance.

[0187] Table 3: Boost Level Judgment Table

[0188] Data judgment ComePress PressWeigh<=Prev_AVG_PressWeight 0 PressWeigh>Prev_AVG_PressWeight 1 PressWeigh>Prev_AVG_PressWeight*1.2 2 PressWeigh>Prev_AVG_PressWeight*1.5 3

[0189] The meanings of ComePress are as follows:

[0190] ① A value of 1 indicates that the top plate is pressurized and its strength is average;

[0191] ② A value of 2 indicates that the top plate is pressurized and has relatively high strength;

[0192] ③ A value of 3 indicates that the top plate is pressurized and has high strength. The hydraulic support at the working face should be carefully protected.

[0193] To reassess whether the working face is truly pressurized, if the working face meets one of the following three conditions, it can be considered that the working face in that section is in a pressurized roof state:

[0194] (1) If ComePress = 3, then the working face can be considered pressurized.

[0195] (2) If ComePress = 2, there must be two or more consecutive step distances ComePress >= 1 for the working face to be considered pressurized;

[0196] (3) If ComePress = 1, there must be 3 or more consecutive step distances ComePress = 1 for the working face to be considered pressurized;

[0197] (4) Once it is determined that the working face is pressurized, if multiple step distances in the area are in the state of ComePres>=1, and if one or multiple discontinuous step distances ComePres<1 appear in the middle, then the ComePres of that step distance is modified to 1. The main purpose is to maintain the integrity and stability of pressurization.

[0198] During the face advancement process, the pressurization step distance of the face can also be determined, and the specific classifications are as follows:

[0199] (1) Significant movement step distance: If the working face is under pressure, all step distances with ComePress>0 are significant movement step distances, and their cumulative advance is the significant movement step distance.

[0200] (2) Stable stride length: The cumulative advance from the end of the last significant stride length in this interval to the beginning of the current significant stride length is the stable stride length.

[0201] (3) Step distance for this cycle: the step distance of the last significant movement + the adjacent stable movement step distance, that is, the cycle movement step distance of the current working face.

[0202] This solution can not only determine the current boost level and boost increment, but also predict the increment for the next boost and even the one after that. Specifically, determining the increment for the next boost based on the aforementioned boost data can be achieved through the following steps: Obtain the increment corresponding to the Nth boost data, the (N-1)th boost data, and the (N-2)th boost data, where N is greater than or equal to 2; Obtain the first weighting coefficient of the increment corresponding to the Nth boost data, the second weighting coefficient of the increment corresponding to the (N-1)th boost data, and the third weighting coefficient of the increment corresponding to the (N-2)th boost data. The third weighting coefficient of the step distance corresponding to the boost data, wherein the first weighting coefficient is less than the second weighting coefficient, and the second weighting coefficient is less than the third weighting coefficient; the first product of the step distance corresponding to the Nth boost data and the first weighting coefficient, the second product of the step distance corresponding to the (N-1)th boost data and the second weighting coefficient, and the third product of the step distance corresponding to the (N-2)th boost data and the third weighting coefficient; the fourth sum of the first product, the second product, and the third product, and the fourth sum is determined to be the step distance corresponding to the (N+1)th boost data.

[0203] In this scheme, the step distance for the next pressurization can be determined relatively accurately based on the current step distance and the historical step distance. This not only enables real-time processing of mine pressure data at the mining face, but also allows for real-time prediction of the pressurization step distance of the roof and the transfer law of support pressure. This allows for advance judgment of the future pressurization situation of the mine, facilitating subsequent prediction of whether the roof will be pressurized and providing corresponding processing results.

[0204] If the pressure increase in this interval is greater than 3 times, the formula for determining the pressure increase step size for the next time can be:

[0205] step(N+1): = 0.2*step(N-2) + 0.3*step(N-1) + 0.5*step(N), where step(N+1) represents the step size for the next boost data, step(N-2) represents the step size for the (N-2)th boost data, step(N-1) represents the step size for the (N-1)th boost data, and step(N) represents the step size for the Nth boost data.

[0206] If the cycle boost is less than 3 times in this interval, the formula for determining the boost step size for the next boost can be:

[0207] step(N+1):=0.4*step(N-1)*0.6*step(N).

[0208] The overall pressurization curve of the working face is as follows Figure 10 As shown, the boost data for step 1 is 8, the boost data for step 2 is 12, the boost data for step 3 is 11, the boost data for step 4 is 18, and the boost data for step 5 is 13.

[0209] To enable those skilled in the art to better understand the technical solution of this application, the implementation process of the coal mine pressure data processing method of this application will be described in detail below with reference to specific embodiments.

[0210] This embodiment relates to a specific method for processing mine pressure data in a coal mine, such as... Figure 11 As shown, it includes the following steps:

[0211] Step S1: Obtain the mine pressure data of the hydraulic support and build a sample library of detection data;

[0212] Step S2: Data standardization (obtaining the first average);

[0213] Step S3: Ensure real-time and effective data processing for advance (obtain the second average value);

[0214] Step S4: The hydraulic support pressure is divided into processing zones along the inclination direction of the working surface;

[0215] Step S5: Extract patterns from different intervals along the vertical time axis (obtain the target average value);

[0216] Step S6: Fuzzy analysis of the working face top plate pattern (determine the boosting level corresponding to the boosting data);

[0217] Step S7: Predict the movement pattern of the roof during the working face advance (determine the step size of the next pressurization data);

[0218] In fact, it can also include three steps: real-time data collection, automatic analysis, and intelligent prediction. Real-time data collection corresponds to step S1 above, automatic analysis corresponds to steps S2 to S5 above, and intelligent prediction corresponds to steps S6 and S7 above.

[0219] The data relationships between multiple mining pressure data are as follows: Figure 12 As shown, for fully mechanized mining faces, the obtained mine pressure data includes the following categories: interval-type mine pressure data, support-type mine pressure data, step-range-type mine pressure data, target time period-type mine pressure data, and single mine pressure data.

[0220] The data is sorted by time series to obtain a single mine pressure data point, and the first average value corresponding to multiple mine pressure data points within the target time period is obtained.

[0221] The second average value corresponding to the multiple first average values ​​of a hydraulic support within the step distance is obtained based on multiple first average values;

[0222] The target average value corresponding to the multiple second average values ​​of multiple hydraulic supports within the step distance is obtained based on multiple second average values;

[0223] The average pressure value of all steps (i.e., the average pressure value of the fully mechanized mining face) is determined based on the average values ​​of multiple targets.

[0224] Determine the corresponding boost data based on the average pressure of all steps, determine the boost level corresponding to the boost data, and determine the step size for determining the next boost data based on the boost data.

[0225] The proposed scheme is a method for processing mine pressure data based on interval advantage. The so-called interval advantage means that based on the mine pressure data, displacement data and roadway borehole stress variation data of hydraulic supports, the mine pressure data is divided into 7 major steps according to the law of mine pressure variation. Then, relevant analysis indicators are formulated for each step according to its characteristics. Through the optimization of different steps, mine pressure data that conforms to engineering practice is finally found. This analysis method has guiding significance for revealing the overall movement law of the roof.

[0226] The above-described scheme is applicable to longwall mining faces with a certain inclination length. This method divides the mining face into odd-numbered intervals along the inclination direction. Data within each interval undergoes multi-step processing, including step-by-step segmentation, lateral combination, and vertical optimization. Utilizing a progressive dimensionality reduction and multi-objective filtering approach, it achieves real-time acquisition, automatic analysis, and intelligent decision-making of mine pressure data for hydraulic supports. Through seven-step data analysis, this method accurately judges the roof movement patterns within each interval and accurately predicts upcoming roof movements. This method aims to address the characteristics of current mine pressure big data and overcome the shortcomings of traditional mine pressure analysis methods—the Pt curve method and linear regression method.

[0227] This application also provides a coal mine pressure data processing apparatus. It should be noted that the coal mine pressure data processing apparatus of this application can be used to execute the coal mine pressure data processing method provided in this application. This apparatus is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0228] The following describes the coal mine pressure data processing device provided in the embodiments of this application.

[0229] Figure 13 This is a structural block diagram of a coal mine pressure data processing device according to an embodiment of this application. Figure 13 As shown, the device includes:

[0230] The first acquisition unit 10 is used to acquire mine pressure data, wherein the mine pressure data is the force data generated by rock displacement movement caused during coal mining on the hydraulic support, and the hydraulic support corresponds one-to-one with the mine pressure data.

[0231] The second acquisition unit 20 is used to acquire the target average value of the multiple mining pressure data corresponding to the multiple hydraulic supports for each step distance, wherein the step distance is the duration of the hydraulic support from the start of injection to the depressurization time.

[0232] The first determining unit 30 is used to determine the pressure increase data corresponding to the step distance based on the above target average value, wherein the above pressure increase data refers to the data on the increase in pressure of the above hydraulic support caused by the mine pressure caused by the coal mining face.

[0233] The second determining unit 40 is used to determine the boost level corresponding to the above boost data, and to determine the step size of the next boost data based on the above boost data.

[0234] This embodiment allows for the determination of target average values ​​corresponding to multiple step distances based on the hydraulic data of the hydraulic support. Furthermore, based on these relatively accurate target average values, the pressure boosting data corresponding to multiple step distances can be determined, thus accurately determining the pattern of mine pressure changes. Additionally, the pressure boosting data can be categorized to determine the intensity of the boosting, and the next pressure boosting data can be accurately predicted. This solves the problem of low accuracy in processing coal mine pressure data in existing technologies.

[0235] To obtain a more accurate target average value, the step distance can be further divided. This division can be done by using time periods to improve the accuracy of the target average value. Specifically, the second acquisition unit includes a first acquisition module, a second acquisition module, and a third acquisition module. The first acquisition module is used to acquire the first average value corresponding to multiple of the aforementioned mine pressure data within each target time period, where the step distance includes multiple target time periods. The second acquisition module is used to acquire the second average value corresponding to multiple of the aforementioned first average values ​​for one of the aforementioned hydraulic supports within each step distance. The third acquisition module is used to acquire the target average value corresponding to multiple of the aforementioned second average values ​​for multiple of the aforementioned hydraulic supports within each step distance.

[0236] In this scheme, since the working environment at the working face is relatively complex, it cannot be guaranteed that all the collected mine pressure data are valid. Therefore, the target average value can be obtained by averaging. First, the step distance is divided again to obtain multiple relatively accurate first average values ​​for multiple target time periods within the step distance. Then, the average value of multiple first average values ​​is calculated again to obtain multiple second average values. Finally, the average value of multiple second average values ​​is calculated to obtain a relatively accurate target average value, avoiding the situation where the target average value is inaccurate due to invalid data.

[0237] Due to the complex working environment at the working face, it cannot be guaranteed that all collected mine pressure data are valid. To save storage space, existing mine pressure data collection can adopt a "collect as needed" approach, meaning that mine pressure data is only recorded when there are significant fluctuations. Therefore, there is no valid data at some points in time, requiring standardized analysis and processing of the mine pressure data. The first acquisition module of this application includes a division submodule, a first acquisition submodule, and a second acquisition submodule. The division submodule is used to divide the collection time corresponding to multiple mine pressure data into multiple target time periods according to a predetermined time interval, wherein each target time period includes multiple mine pressure data. The first acquisition submodule is used to obtain a first sum of the multiple mine pressure data within the target time period. The second acquisition submodule is used to obtain the quotient of the first sum and the number of mine pressure data within the target time period to obtain the first average value.

[0238] In this scheme, the mine pressure data corresponding to all hydraulic supports on the working face can be divided into the same predetermined time interval (such as 1 minute, 2 minutes, etc.). Then, the quotient of the first sum and the number of mine pressure data can be extracted to obtain a relatively accurate first average value, thereby ensuring that a relatively accurate target average value can be obtained based on the first average value in the future.

[0239] Since the hydraulic support operation process (lowering, moving, raising) generally takes 10 to 40 seconds, there may be differences between the real-time and phased nature of the mine pressure data. In order to eliminate the difference between the real-time mine pressure data and the mine pressure data entered on site during data analysis, the second acquisition module of this application includes a third acquisition submodule and a fourth acquisition submodule. The third acquisition submodule is used to acquire the second sum of multiple first average values ​​of one hydraulic support within the above-mentioned step distance; the fourth acquisition submodule is used to acquire the quotient of the second sum and the number of first average values ​​within the above-mentioned step distance to obtain the second average value.

[0240] In this scheme, based on obtaining multiple first average values, the mine pressure data can be divided into steps. The multiple first average values ​​corresponding to the hydraulic support can be sorted according to time sequence. If the current time is greater than the initial support force designed for the hydraulic support (i.e., the time when the hydraulic support begins to support the roof), it is marked as the start of a step, and this step ends when the current time exceeds the minimum threshold value for step selection. The mine pressure data on the hydraulic support within this time range constitutes the mine pressure data within a step. Then, by calculating the average value, the second average value corresponding to the multiple first average values ​​within the step is obtained. This ensures that the obtained second average value reflects the average change of the mine pressure data within that step, thus guaranteeing that a relatively accurate target average value can be obtained subsequently based on the second average value.

[0241] After dividing the intervals, a certain interval of the working face can be used as the analysis subject, or all intervals of the working face can be used as the analysis subject. Data analysis is performed in the direction of working face advancement. Since the data of each interval can be analyzed independently, and an interval includes the mine pressure data corresponding to multiple hydraulic supports, the data of multiple hydraulic supports can be integrated to obtain the target average value. The third acquisition module of this application includes a fifth acquisition submodule and a sixth acquisition submodule. The fifth acquisition submodule is used to obtain the third sum of the multiple second average values ​​of multiple hydraulic supports within a step distance. The sixth acquisition submodule is used to obtain the quotient of the third sum within a step distance and the number of hydraulic supports to obtain the target average value within a step distance.

[0242] In this scheme, the target average value can be obtained from multiple second average values ​​within each step, which can ensure that the obtained target average value can reflect the average change of the mine pressure data within that step, thus ensuring that the obtained target average value is relatively accurate.

[0243] In some embodiments, the first determining unit includes a comparison module and a first determining module. The comparison module is used to compare the target average value corresponding to the current mine pressure data with multiple historical average values ​​to obtain a comparison result. The historical average value is the average value obtained from historical mine pressure data within a historical time period. The first determining module is used to determine the target historical average value based on the comparison result and determine the pressure boosting data corresponding to the target historical average value as the target pressure boosting data corresponding to the current mine pressure data.

[0244] In this scheme, the historical average values ​​are relatively accurate data within the historical time period, and the average values ​​of the historical mine pressure data within the historical time period all have corresponding pressure boosting data. The method of directly determining the target pressure boosting data by comparing the results is relatively simple and direct, which can avoid complex calculation processes and ensure that this scheme can determine the target pressure boosting data relatively quickly and accurately.

[0245] In some embodiments, the second determining unit includes a second determining module, a third determining module, a fourth determining module, and a fifth determining module. The second determining module is used to determine the boost level corresponding to the boost data as a first boost level when the boost data is less than or equal to a first threshold. The third determining module is used to determine the boost level corresponding to the boost data as a second boost level when the boost data is greater than the first threshold and less than or equal to a second threshold, wherein the first threshold is less than the second threshold, and the boost intensity corresponding to the first boost level is less than the boost intensity of the second boost level. The fourth determining module is used to... When the boost data is greater than the second threshold and less than or equal to the third threshold, the boost level corresponding to the boost data is determined to be the third boost level, wherein the second threshold is less than the third threshold and the boost intensity corresponding to the second boost level is less than the boost intensity of the third boost level; the fifth determining module is used to determine the boost level corresponding to the boost data as the fourth boost level when the boost data is greater than the third threshold and less than or equal to the fourth threshold, wherein the third threshold is less than the fourth threshold and the boost intensity corresponding to the third boost level is less than the boost intensity of the fourth boost level.

[0246] In this scheme, there are multiple thresholds related to the boost data. This allows for comparison of the boost data with the magnitude of multiple thresholds, and thus the boost level corresponding to the boost data can be determined more accurately based on the magnitude of the boost data with the multiple thresholds.

[0247] This solution can not only determine the current boost level and boost increment, but also predict the increment for the next boost and even the boost after that. Specifically, the second determining unit includes a fourth acquisition module, a fifth acquisition module, a sixth acquisition module, and a sixth determining module. The fourth acquisition module is used to acquire the increment corresponding to the Nth boost data, the (N-1)th boost data, and the (N-2)th boost data, where N is greater than or equal to 2. The fifth acquisition module is used to acquire the first weighting coefficient of the increment corresponding to the Nth boost data, the second weighting coefficient of the increment corresponding to the (N-1)th boost data, and the second weighting coefficient of the (N-2)th boost data. The third weighting coefficient of the step distance corresponding to the above boost data, wherein the first weighting coefficient is less than the second weighting coefficient, and the second weighting coefficient is less than the third weighting coefficient; the sixth acquisition module is used to acquire the first product of the step distance corresponding to the Nth boost data and the first weighting coefficient, the second product of the step distance corresponding to the N-1th boost data and the second weighting coefficient, and the third product of the step distance corresponding to the N-2th boost data and the third weighting coefficient; the sixth determination module is used to acquire the fourth sum of the first product, the second product and the third product, and determine the fourth sum as the step distance corresponding to the N+1th boost data.

[0248] In this scheme, the step distance for the next pressurization can be determined relatively accurately based on the current step distance and the historical step distance. This not only enables real-time processing of mine pressure data at the mining face, but also allows for real-time prediction of the pressurization step distance of the roof and the transfer law of support pressure. This allows for advance judgment of the future pressurization situation of the mine, facilitating subsequent prediction of whether the roof will be pressurized and providing corresponding processing results.

[0249] The aforementioned coal mine pressure data processing device includes a processor and a memory. The first acquisition unit, second acquisition unit, first determination unit, and second determination unit are all stored as program units in the memory. The processor executes these program units stored in the memory to achieve their respective functions. All of the above modules are located in the same processor; alternatively, the modules may be located in different processors in any combination.

[0250] The processor contains a kernel, which retrieves the corresponding program units from memory. One or more kernels can be configured, and adjusting kernel parameters can improve the accuracy of coal mine pressure data processing.

[0251] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0252] This invention provides a computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device containing the computer-readable storage medium to perform a method for processing coal mine pressure data.

[0253] This invention provides a processor for running a program, wherein the program executes a method for processing coal mine pressure data.

[0254] This invention provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs at least the following steps:

[0255] The devices mentioned in this article can be servers, PCs, tablets, mobile phones, etc.

[0256] This application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program having at least the following method steps:

[0257] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0258] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0259] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0260] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0261] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0262] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0263] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0264] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0265] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0266] As can be seen from the above description, the embodiments of this application achieve the following technical effects:

[0267] 1) The coal mine pressure data processing method of this application can determine the target average value corresponding to multiple step distances based on the hydraulic data of the hydraulic support, and then determine the pressure boosting data corresponding to multiple step distances based on the relatively accurate target average value. That is, it can accurately determine the law of coal mine pressure change, and can also classify the pressure boosting data of coal mine to determine the pressure boosting intensity. It can also accurately predict the pressure boosting data of the next time, thereby solving the problem of low accuracy of coal mine pressure data processing in the prior art.

[0268] 2) The coal mine pressure data processing device of this application can determine the target average value corresponding to multiple step distances based on the hydraulic data of the hydraulic support, and then determine the pressure boosting data corresponding to multiple step distances based on the relatively accurate target average value. That is, it can accurately determine the law of coal mine pressure change, and can also classify the pressure boosting data of coal mine to determine the pressure boosting intensity. It can also accurately predict the pressure boosting data of the next time, thereby solving the problem of low accuracy of coal mine pressure data processing in the prior art.

[0269] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for processing mine pressure data in a coal mine, characterized in that, include: Obtain mine pressure data, wherein the mine pressure data is the force data generated by rock displacement movement caused during coal mining on hydraulic supports, and the hydraulic supports correspond one-to-one with the mine pressure data; Obtain the target average value of multiple mine pressure data corresponding to multiple hydraulic supports for each step distance, wherein the step distance is the duration of the hydraulic support from the start of injection to the depressurization time; The pressure boosting data corresponding to the step distance is determined based on the target average value, wherein the pressure boosting data refers to the data on the increase in pressure of the hydraulic support caused by the mine pressure caused by the coal mining face; Determine the boost level corresponding to the boost data, and determine the step size of the next boost data based on the boost data; Obtaining the target average value of multiple mine pressure data corresponding to multiple hydraulic supports for each step distance includes: obtaining the first average value corresponding to multiple mine pressure data within each target time period, wherein the step distance includes multiple target time periods; obtaining the second average value corresponding to multiple first average values ​​of a hydraulic support within each step distance; and obtaining the target average value corresponding to multiple second average values ​​of multiple hydraulic supports within each step distance. Obtaining the first average value corresponding to multiple mining pressure data within each target time period includes: dividing the collection time corresponding to the multiple mining pressure data into multiple target time periods according to a predetermined time interval, wherein a target time period includes multiple mining pressure data; obtaining the first sum of the multiple mining pressure data within the target time period; obtaining the quotient of the first sum and the number of mining pressure data within the target time period to obtain the first average value; Obtaining a second average value corresponding to multiple first average values ​​of a hydraulic support within each step distance includes: obtaining a second sum of multiple first average values ​​of a hydraulic support within the step distance; obtaining the quotient of the second sum and the number of first average values ​​within the step distance to obtain the second average value; Obtaining the target average value corresponding to the multiple second average values ​​of multiple hydraulic supports within each step distance includes: obtaining a third sum of the multiple second average values ​​of multiple hydraulic supports within a step distance; obtaining the quotient of the third sum within a step distance and the number of hydraulic supports to obtain the target average value within a step distance.

2. The method according to claim 1, characterized in that, Determining the boost data corresponding to the step size based on the target average value includes: The target average value corresponding to the current mine pressure data is compared with multiple historical average values ​​to obtain a comparison result, wherein the historical average value is the average value obtained from historical mine pressure data within a historical time period; Based on the comparison results, a target historical average value is determined, and the pressure boosting data corresponding to the target historical average value is determined as the target pressure boosting data corresponding to the current mine pressure data.

3. The method according to claim 1, characterized in that, Determining the boost level corresponding to the boost data includes: If the boost data is less than or equal to a first threshold, the boost level corresponding to the boost data is determined to be the first boost level; When the boost data is greater than the first threshold and the boost data is less than or equal to the second threshold, the boost level corresponding to the boost data is determined to be the second boost level, wherein the first threshold is less than the second threshold and the boost intensity corresponding to the first boost level is less than the boost intensity of the second boost level; If the boost data is greater than the second threshold and the boost data is less than or equal to the third threshold, the boost level corresponding to the boost data is determined to be the third boost level, wherein the second threshold is less than the third threshold and the boost intensity corresponding to the second boost level is less than the boost intensity of the third boost level; If the boost data is greater than the third threshold and the boost data is less than or equal to the fourth threshold, the boost level corresponding to the boost data is determined to be the fourth boost level, wherein the third threshold is less than the fourth threshold and the boost intensity corresponding to the third boost level is less than the boost intensity of the fourth boost level.

4. The method according to claim 1, characterized in that, Determining the step size for the next boost data based on the boost data includes: Obtain the step size corresponding to the Nth boost data, the step size corresponding to the (N-1)th boost data, and the step size corresponding to the (N-2)th boost data, respectively, where N is greater than or equal to 2; The first weighting coefficient, the second weighting coefficient, and the third weighting coefficient of the step distance corresponding to the Nth boost data, are obtained respectively. The first weighting coefficient is less than the second weighting coefficient, and the second weighting coefficient is less than the third weighting coefficient. Obtain the first product of the step size corresponding to the Nth boost data and the first weight coefficient, the second product of the step size corresponding to the (N-1)th boost data and the second weight coefficient, and the third product of the step size corresponding to the (N-2)th boost data and the third weight coefficient; Obtain the fourth sum of the first product, the second product, and the third product, and determine that the fourth sum is the step size corresponding to the (N+1)th boost data.

5. A coal mine pressure data processing device, characterized in that, include: The first acquisition unit is used to acquire mine pressure data, wherein the mine pressure data is the force data generated by rock displacement movement caused during coal mining on the hydraulic support, and the hydraulic support corresponds one-to-one with the mine pressure data; The second acquisition unit is used to acquire the target average value of multiple mine pressure data corresponding to multiple hydraulic supports for each step distance, wherein the step distance is the duration of the hydraulic support from the start of injection to the depressurization time; The first determining unit is used to determine the pressure boosting data corresponding to the step distance based on the target average value, wherein the pressure boosting data refers to the data on the increase in pressure of the hydraulic support caused by the mine pressure caused by the coal mining face; The second determining unit is used to determine the boost level corresponding to the boost data, and to determine the step size of the next boost data based on the boost data; The second acquisition unit includes a first acquisition module, a second acquisition module, and a third acquisition module. The first acquisition module is used to acquire a first average value corresponding to multiple mine pressure data within each target time period, and the step distance includes multiple target time periods. The second acquisition module is used to acquire a second average value corresponding to multiple first average values ​​of a hydraulic support within each step distance. The third acquisition module is used to acquire a target average value corresponding to multiple second average values ​​of multiple hydraulic supports within each step distance. The first acquisition module includes a division submodule, a first acquisition submodule, and a second acquisition submodule. The division submodule is used to divide the collection time corresponding to multiple mining pressure data according to a predetermined time interval to obtain multiple target time periods, wherein a target time period includes multiple mining pressure data. The first acquisition submodule is used to obtain a first sum of multiple mining pressure data within the target time period. The second acquisition submodule is used to obtain the quotient of the first sum and the number of mining pressure data within the target time period to obtain the first average value. The second acquisition module includes a third acquisition submodule and a fourth acquisition submodule. The third acquisition submodule is used to acquire a second sum of multiple first average values ​​of a hydraulic support within the step distance. The fourth acquisition submodule is used to acquire the second average value by taking the quotient of the second sum and the number of first average values ​​within the step distance. The third acquisition module includes a fifth acquisition submodule and a sixth acquisition submodule. The fifth acquisition submodule is used to acquire a third sum of multiple second average values ​​of multiple hydraulic supports within a step distance. The sixth acquisition submodule is used to acquire the quotient of the third sum within a step distance and the number of hydraulic supports to obtain the target average value within a step distance.

6. An electronic device, characterized in that, include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising methods for performing any one of claims 1 to 4.

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