CN-122021059-A - Hydraulic support peak value checking and staged selection parameter determining method under dynamic load effect

CN122021059ACN 122021059 ACN122021059 ACN 122021059ACN-122021059-A

Abstract

The invention relates to the technical field of fully-mechanized mining of coal mines, in particular to a method for checking a peak value of a hydraulic support under the action of dynamic load and determining a staged selection parameter, which comprises the following steps of S1, acquiring and preprocessing support, ledge and microseism monitoring data before pressure relief or treatment; the method comprises the steps of S2, counting the resistance of a bracket and the valve opening rate according to a fixed time window, fusing the ledge depth and the microseismic intensity to form a statistical table, S3, calculating a dynamic load coefficient, constructing a dynamic load intensity index, identifying a dynamic load event, extracting a peak value, S4, grading and counting the resistance peak value and the dynamic load coefficient peak value of each stage according to the propelling distance, S5, calculating the rated working resistance of the stage according to the resistance peak value of the stage and the safety coefficient, and S6, screening candidate brackets meeting the condition and having the minimum rated resistance as recommended selection. According to the invention, the dynamic load peak value check and the quantitative determination of the staged model selection parameters of the hydraulic support are realized, and the safety and the economical efficiency of the model selection of the support are improved.

Inventors

WU FENGFENG
PAN YUHAO
He Xirun
GU HAOYUAN
GAO ZHIQIANG
Niu Dengyun
SONG JIWEI
ZHAO JIAHUI
ZHANG WEI
GAO JIAXIANG
DING ZIJIE

Assignees

中国矿业大学

Dates

Publication Date: 20260512
Application Date: 20260401

Claims (9)

1. The method for checking the peak value of the hydraulic support under the action of dynamic load and determining the staged selection parameters is characterized by comprising the following steps of: S1, multi-source monitoring data in a state before pressure relief or treatment is obtained, wherein the multi-source monitoring data comprises bracket monitoring data, ledge monitoring data and microseismic monitoring data, and field standardization processing, time alignment processing and missing value processing are carried out on the multi-source monitoring data; S2, counting and resampling the bracket monitoring data according to a fixed time window, calculating window-level bracket resistance and window-level valve opening rate, and fusing the counted window-level bracket resistance, window-level valve opening rate, the ledge depth in the ledge monitoring data and the microseismic intensity formed by the microseismic monitoring data to construct a window counting table; S3, calculating a dynamic load coefficient based on the window statistical table, carrying out standardized processing on the dynamic load coefficient, the valve opening rate and the microseismic intensity, constructing a dynamic load intensity index, identifying a dynamic load event according to a quantile threshold triggering rule of the dynamic load intensity index, and extracting an event peak value corresponding to the dynamic load event; S4, dividing the propulsion process in stages according to the preset stage length by taking the propulsion distance as a main line, and counting a bracket resistance peak value and a dynamic load coefficient peak value in each propulsion stage so as to represent dynamic load response characteristics of different propulsion stages; S5, calculating the peak value of the obtained stent resistance according to the statistics of each propulsion stage, and calculating the rated working resistance required by the corresponding propulsion stage by combining the safety coefficient; S6, inputting a rated working resistance set of the candidate hydraulic support, carrying out feasibility screening on each candidate support, selecting a candidate support with rated working resistance not smaller than rated working resistance required by the stage, and selecting a support with the minimum rated working resistance from candidate supports meeting the condition as a recommended model selection result of the corresponding propulsion stage.
2. The method for determining the peak value checking and staged model selection parameters of the hydraulic support under the action of dynamic load according to claim 1, wherein the step S1 comprises the following steps: S11, multi-source monitoring data in a state before pressure relief or treatment is obtained, wherein the multi-source monitoring data comprise bracket monitoring data, ledge monitoring data and microseismic monitoring data, the bracket monitoring data comprise bracket time stamps, bracket numbers, bracket resistance, unloading valve opening amounts and pushing distances, the ledge monitoring data comprise ledge time stamps and ledge depths, and the microseismic monitoring data comprise event time and event energy; s12, performing field standardization processing on the bracket monitoring data, the ledge monitoring data and the microseismic monitoring data, wherein the bracket monitoring data are standardized uniformly as bracket time stamps Bracket numbering Resistance of the stent Opening amount of unloading valve Distance of propulsion The lasting monitoring data are unified standardized into lasting time stamps And the depth of the upper Microseismic monitoring data is unified and standardized into event time And event energy ; S13, performing time alignment processing on the standardized multi-source monitoring data, converting time fields of different source data into standard time values under a unified time axis, and constructing the unified time axis to enable the bracket monitoring data, the ledge monitoring data and the microseismic monitoring data to correspond under a unified time reference; S14, carrying out missing value identification on the multisource monitoring data after field standardization and time alignment are completed, marking missing or invalid records, and carrying out missing value processing according to adjacent valid data.
3. The method for determining the peak value checking and staged model selection parameters of the hydraulic support under the action of dynamic load according to claim 2, wherein the step S2 comprises the following steps: s21, setting a fixed time window width on a unified time axis Dividing according to time sequence to obtain multiple continuous time windows Wherein, the first The corresponding time ranges of the time windows are recorded as The system is used for carrying out window statistics on the support structure monitoring data, the ledge monitoring data and the microseismic monitoring data; S22, with respect to the first Time window The stent monitoring data in the window extracts the resistance record of each stent in the time window, and takes the maximum value of the stent resistance in the window as the window-level stent resistance Expressed as: ; s23, for the first Time window The monitoring data of the bracket in the time window is extracted, the opening amount record of each unloading valve in the time window is extracted, and the average value of the opening amounts of the unloading valves in the window is used as the opening rate of the window level valve Expressed as: ; Wherein, the Is the first Time window The number of valve opening records participating in statistics; s24, with respect to the first Time window The ledge monitoring data in the window is used for extracting the depth record of each ledge in the time window, and the maximum value of the ledge depth in the window is used as the ledge depth of the window level Expressed as: ; S25, for the first Time window The microseismic monitoring data in the time window is extracted, the energy of all microseismic events in the time window is extracted, and the window energy sum are calculated And counting event energy not less than Event count of (a) Event energy is not less than Event count of (a) Constructing original microseismic intensity And normalizing to obtain microseismic intensity Expressed as: ; ; ; ; ; Wherein, the Is the first A set of microseismic events within a single time window, Is event energy; s26, the first Window level support resistance corresponding to each time window Window step valve opening ratio Window level ledge depth Intensity of microseismic And fusing to construct a window statistical table.
4. The method for determining the peak value checking and staged model selection parameters of the hydraulic support under the action of dynamic load according to claim 3, wherein the step S3 comprises the following steps: s31, resistance to the window level bracket in the window statistics table Counting quantiles, and taking 0.2 quantiles of window-level bracket resistance as baseline resistance And calculating dynamic load coefficients corresponding to each time window Expressed as: ; ; Wherein, the As a 0.2 quantile function; S32, opening rate of window level valve in window statistics table Normalization processing is carried out, and the opening rate of a normalization valve is calculated Expressed as: ; s33, carrying out standardized treatment on the dynamic load coefficient, the normalized valve opening rate and the microseismic intensity, and superposing the dynamic load coefficient, the normalized valve opening rate and the microseismic intensity to construct dynamic load intensity indexes corresponding to each time window ; S34, dynamic load intensity indexes corresponding to all time windows Counting quantiles and taking it Fractional number as dynamic load event trigger threshold Expressed as: ; Wherein, the Is that A quantile function; s35, the dynamic load intensity index of each time window is calculated And dynamic load event trigger threshold Comparing when meeting When the corresponding time window is judged to enter the dynamic load event triggering state, when the adjacent time window continuously meets the following conditions When the trigger state is finished, the trigger state is regarded as the end of the live load event segment, so that a plurality of live load event segments are obtained; S36, for each identified driving load event section, respectively extracting a driving load coefficient peak value, a valve opening rate peak value, a microseismic intensity peak value, a ledge depth peak value and a window resistance peak value in all time windows corresponding to the driving load event section.
5. The method for checking and determining the staged model selection parameters of the hydraulic support under the action of dynamic load according to claim 4, wherein the peak value of the dynamic load coefficient is expressed as: ; Wherein, the Is the first A dynamic load coefficient peak value of the dynamic load event segment; the valve opening rate peak is expressed as: ; Wherein, the Is the first A peak valve opening rate for the individual dynamic load event segment; the microseismic intensity peak is expressed as: ; Wherein, the First, the A microseismic intensity peak of the individual dynamic load event segment; the ledge depth peak is expressed as: ; Wherein, the Is the first A ledge depth peak of the individual dynamic load event segment; the window resistance peak is expressed as: ; Wherein, the Is the first Window resistance peak for individual live event segments.
6. The method for determining the peak value checking and staged model selection parameters of the hydraulic support under the action of dynamic load according to claim 5, wherein the step S4 comprises: s41, setting a preset stage length And determining the initial propulsion distance of the propulsion process ; S42, according to the advancing distance of each time window Initial propulsion distance Stage length Calculating the stage number of each time window Expressed as: ; S43, according to the stage number Grouping all time windows, collecting the time windows with the same stage number into the same propelling stage to form window data sets corresponding to the propelling stages, wherein each propelling stage comprises window stage bracket resistance corresponding to the stage Coefficient of dynamic load Distance of propulsion First, the The set of time windows corresponding to the individual propulsion phases is represented as: ; Wherein, the Numbered as stage number Is a set of time windows; S44, for each propulsion stage, corresponding time window set Traversing to extract all window-level stent resistance in the stage And takes the maximum value as the peak value of the stent resistance in the propulsion stage Expressed as: ; s45, for each propulsion stage, corresponding time window set Traversing, extracting all dynamic load coefficients in the stage And takes the maximum value as the peak value of dynamic load coefficient of the propulsion stage Expressed as: ; S46, summarizing a phase number, a propulsion distance range, a stent resistance peak value and a dynamic load coefficient peak value corresponding to each propulsion phase to form a phase peak value statistical result, wherein the propulsion distance range is expressed as: ; ; Wherein, the Is the first The starting propulsion distance of the individual propulsion stages, Is the first End of each propulsion phase.
7. The method for determining the peak value checking and staged model selection parameters of the hydraulic support under the action of dynamic load according to claim 6, wherein the step S5 comprises: S51, the first Time window set corresponding to each propulsion stage Window level stent resistance in (a) Statistics are carried out to determine the peak value of the stent resistance in the propulsion stage ; S52, setting a safety factor The device is used for covering measurement errors, load uncertainty and design allowance; S53, the first Peak stent resistance for each propulsion stage And safety factor of In combination, the nominal operating resistance required for the propulsion phase is calculated Expressed as: 。
8. The method for determining the peak value checking and staged model selection parameters of the hydraulic support under the action of dynamic load according to claim 7, wherein the step S6 comprises: s61, inputting a rated working resistance set of the candidate hydraulic support , wherein, Is the first Rated operating resistance of the candidate hydraulic supports; S62, with respect to the first Rated working resistance of each candidate hydraulic support is calculated in each propulsion stage And rated working resistance required in the stage Comparing, when the candidate hydraulic support meets When the candidate stent is judged to be a feasible candidate scheme, the first step is The feasible candidate sets for the individual propulsion phases are expressed as: ; Wherein, the Is the first A feasible candidate set of individual propulsion phases; S63, for the first A step of advancing, in the feasible candidate set In the step, the candidate hydraulic support with the minimum rated working resistance is selected as a recommended model selection result in the stage, and the recommended model selection result is expressed as: ; Wherein, the Is the first Recommending candidate stent numbers in each propulsion stage; s64 according to the first Recommended candidate stent numbering for individual stages of advancement Reading rated working resistance of corresponding recommended bracket ; S65, after determining the recommended candidate stent, calculating the allowance index corresponding to the advancing stage 。
9. The method for determining the peak value checking and staged model selection parameters of the hydraulic support under the action of dynamic load according to claim 8, wherein the allowance index is expressed as: 。

Description

Hydraulic support peak value checking and staged selection parameter determining method under dynamic load effect Technical Field The invention relates to the technical field of fully-mechanized coal mining, in particular to a hydraulic support peak value checking and staged selection parameter determining method under the action of dynamic load. Background Along with the continuous improvement of the mining intensity of the fully mechanized mining face of the coal mine, the hydraulic support is used as key equipment for the control and the safety support of the top plate of the working face, and the bearing capacity of the hydraulic support is directly related to the production safety and stability of the working face. Under the action of factors such as mining stress, roof period pressing and geological structure, the roof of the working face often generates obvious dynamic load response, and the phenomenon of abrupt change or peak value of the support resistance is caused. In order to accurately grasp the stress state of the support of the working face, the running state of the working face is monitored in real time usually through a support monitoring system, a ledge monitoring device and a microseismic monitoring system on site, a large amount of multi-source monitoring data reflecting the movement of the top plate and the stress characteristics of the support are accumulated, and a data base is provided for analyzing the action rule of dynamic load and optimizing the support model selection. However, the existing hydraulic support type selection method is based on static load conditions or single monitoring indexes, and is generally used for overall type selection through an empirical formula or historical engineering experience, so that the dynamic load change characteristics of the fully mechanized mining face in the propelling process are difficult to fully reflect. Meanwhile, the data acquired by different monitoring systems are diverse in sources and nonuniform in time scale, a comprehensive analysis method for multi-source information such as support resistance, ledge depth and microseismic energy is lacked, and a loading event and a peak value thereof are difficult to accurately identify. In addition, the prior art often uses the whole working surface as an object to perform unified parameter configuration, lacks a mechanism for performing sectional analysis and support parameter checking on dynamic load characteristics in different stages based on the propulsion distance, and is easy to cause the problems of insufficient support capacity in local stages or redundant support configuration. Disclosure of Invention The invention provides a method for determining peak value check and staged type selection parameters of a hydraulic support under the action of dynamic load, which comprises the steps of carrying out fusion analysis on support resistance, valve opening rate, ledge depth and microseismic intensity by acquiring multisource monitoring data in a state before pressure relief or treatment, constructing window statistics indexes in a fixed time window and identifying dynamic load event, further carrying out staged division on a working surface propulsion process by taking a propulsion distance as a main line, counting support resistance peaks in each stage and calculating rated working resistance required by the stage, and screening a minimum rated working resistance support meeting the conditions from a candidate support set as a recommended type, thereby realizing the hydraulic support dynamic load peak value check and staged optimal type selection, and improving the safety and economical efficiency of support type selection. The hydraulic support peak value checking and staged model selection parameter determining method under the action of dynamic load comprises the following steps: S1, multi-source monitoring data in a state before pressure relief or treatment is obtained, wherein the multi-source monitoring data comprises bracket monitoring data, ledge monitoring data and microseismic monitoring data, and field standardization processing, time alignment processing and missing value processing are carried out on the multi-source monitoring data; S2, counting and resampling the bracket monitoring data according to a fixed time window, calculating window-level bracket resistance and window-level valve opening rate, and fusing the counted window-level bracket resistance, window-level valve opening rate, the ledge depth in the ledge monitoring data and the microseismic intensity formed by the microseismic monitoring data to construct a window counting table; S3, calculating a dynamic load coefficient based on the window statistical table, carrying out standardized processing on the dynamic load coefficient, the valve opening rate and the microseismic intensity, constructing a dynamic load intensity index, identifying a dynamic load event according to a quantile threshold triggering rule of