CN109815565B - Sectional prediction method for fully-mechanized mining hydraulic support load - Google Patents
Sectional prediction method for fully-mechanized mining hydraulic support load Download PDFInfo
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Abstract
The invention discloses a sectional prediction method for fully-mechanized mining hydraulic support load, which comprises the following steps: collecting working parameters of a hydraulic support of a fully mechanized mining face within a period of time; drawing a relation curve of the load of the hydraulic support and time according to the working parameters, and analyzing each coal mining cycle, and the initial supporting force and the cycle end resistance corresponding to each coal mining cycle according to the relation curve; after fitting analysis is carried out on a relation curve of the hydraulic support load and the time corresponding to each coal mining cycle, a spline curve of the change of the support load of the coal mining cycle along with the time is constructed; and establishing a data fitting window by taking the spline curve as data, fitting and comparing the support load data monitored in real time with the data in the data fitting window, calculating the load increasing speed of the hydraulic support in real time, and predicting the load of the hydraulic support. The method is not only an accurate and reliable hydraulic support load prediction method, but also can realize short-term prediction of the mine pressure.
Description
Technical Field
The invention belongs to the technical field of coal mining, and particularly relates to a sectional prediction method for fully-mechanized coal mining hydraulic support load.
Background
The hydraulic support load is directly reflected by the overlying rock movement of the fully mechanized coal mining face. After the coal seam is mined, the fully mechanized mining face roof is periodically broken, and broken rock blocks are mutually hinged to form a temporary stable structure to bear part of the overlying strata load. When the structure is unstable, the load capacity is reduced, so that the load of the hydraulic support is rapidly increased, the cracks of the overlying strata are further expanded upwards, and the cracks become a gushing channel for roof water and gas. Therefore, abnormal changes in hydraulic mount loading are important prognostic information for coal mine roof, water and gas hazards.
With the rapid development of sensors and electronic information, most coal mines in China adopt an on-line monitoring system for the load of a hydraulic support of a fully mechanized mining face, and massive pressure data of the hydraulic support are collected. However, due to the influences of factors such as complex and variable underground geological conditions of coal mines, different propulsion speeds of fully mechanized coal mining faces, different support working conditions and the like, an effective hydraulic support load prediction method is not available at present, so that the existing data analysis is mainly used for research on mine pressure laws such as pressure step distances, pressure intensity, support coefficients and the like and for evaluation of adaptability of hydraulic supports, and plays a role of 'afterwards Zhuge Liang'. Therefore, an accurate and reliable hydraulic support load prediction method is needed to be developed, so that the prediction and forecast of the top plate incoming pressure are realized, a basis is provided for various disaster prevention and control and surrounding rock control of the fully mechanized mining face, and the safety and high-efficiency extraction of the working face are guaranteed.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention provides a sectional prediction method for the load of a fully-mechanized mining hydraulic support.
The purpose of the invention is realized by the following technical scheme:
a sectional prediction method for the load of a fully-mechanized mining hydraulic support comprises the following steps:
collecting working parameters of the hydraulic support of the fully mechanized mining face within a period of time, wherein the working parameters comprise a measuring moment and a hydraulic support load corresponding to the measuring moment;
drawing a relation curve of the load of the hydraulic support and time according to the working parameters, and analyzing each coal mining cycle, and the initial supporting force and the cycle end resistance corresponding to each coal mining cycle according to the relation curve;
after fitting analysis is carried out on a relation curve of the hydraulic support load and time corresponding to each coal mining cycle, a spline curve of the support load of the coal mining cycle changing along with the time is constructed;
and establishing a data fitting window by taking the spline curve as data, fitting and comparing the support load data monitored in real time with the data in the data fitting window, calculating the load increasing speed of the hydraulic support in real time, and predicting the load of the hydraulic support.
According to the sectional prediction method for the fully-mechanized mining hydraulic support load, massive hydraulic support load data collected by a fully-mechanized mining working face hydraulic support load on-line monitoring system are processed through data sorting and analysis to obtain a spline curve, the support load data monitored in real time are matched and compared with data in a data fitting window, the increase speed of the hydraulic support load is calculated in real time, and then the hydraulic support load is predicted.
Drawings
FIG. 1 is a schematic flow chart of a method for predicting the load of a fully mechanized mining hydraulic support in sections according to an exemplary embodiment of the invention;
FIG. 2 is a graph of hydraulic mount load versus time for an exemplary embodiment of the present invention;
FIG. 3 is a flow chart of another method for predicting the load of the fully mechanized mining hydraulic support in sections according to the exemplary embodiment of the present invention;
FIG. 4 is a graph of logarithmic cradle load versus time for an exemplary embodiment of the invention;
FIG. 5 is a graph of rack load versus time in logarithmic and linear form for an exemplary embodiment of the invention;
FIG. 6 is a graph of stent load versus time in logarithmic and exponential fashion for an exemplary embodiment of the invention;
FIG. 7 is a schematic flow chart of a sectional prediction method for fully mechanized mining hydraulic support load according to another exemplary embodiment of the present invention;
fig. 8 is a flowchart of a sectional prediction method for fully mechanized mining hydraulic support load according to yet another exemplary embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
As shown in fig. 1, a method for predicting load of a fully mechanized mining hydraulic support in sections according to an embodiment of the present invention includes:
s100, collecting working parameters of the hydraulic support of the fully mechanized mining face within a period of time, wherein the working parameters comprise measuring time and hydraulic support load corresponding to the measuring time.
Wherein, when gathering the working parameter of the working face hydraulic support that adopts of combining in a period of time, include:
and (3) rejecting the bracket load data of 0 generated due to sensor failure or interference and the bracket load data which is 50% higher than the rated load of the hydraulic bracket.
S200, drawing a relation curve of the load of the hydraulic support and time according to the working parameters, and analyzing each coal mining cycle and the initial supporting force and the cycle end resistance corresponding to each coal mining cycle according to the relation curve, wherein the relation curve of the load of the hydraulic support and the time is shown in figure 2.
As a preferred embodiment, when analyzing each coal mining cycle and the initial supporting force and the end-of-cycle resistance corresponding to each coal mining cycle according to the relation curve of the hydraulic support load and the time, the method comprises the following steps:
and dividing a plurality of coal mining cycles on a relation curve of the load of the hydraulic support and the time by taking the beginning of the initial supporting force to the end of the cycle resistance as a coal mining cycle, and obtaining the initial supporting force and the cycle end resistance corresponding to each coal mining cycle.
S300, fitting and analyzing a relation curve of the hydraulic support load and time corresponding to each coal mining cycle, and constructing a spline curve of the support load of the coal mining cycle changing along with time.
As shown in fig. 3, when performing fitting analysis on a relation curve between the hydraulic support load and time corresponding to each coal mining cycle, the method includes:
s301, dividing a relation curve of the support load and the time corresponding to each coal mining cycle into 2 stages according to the change characteristics of the relation curve;
s302, a first stage of the relation curve is fit and analyzed by adopting a logarithmic function, and a second stage of the relation curve is fit and analyzed by adopting a linear or exponential function;
wherein the logarithmic function is: p is 1 ＝a 1 +b 1 ×ln(t+c 1 )；
The linear function is: p 3 ＝a 3 +b 3 ×t；
The exponential function is:
for example, FIG. 4 is a first spline type curve comprising a stage from a setting force t 1 Resistance t from time to end of cycle 3 The time sequence curve of the bracket load at the moment accords with a logarithmic function, wherein the logarithmic function is as follows: p 1 ＝a 1 +b 1 ×ln(t+c 1 )；
FIG. 5 comprises a second spline-like curve in two stages, starting from the initial force t 1 Time to intermediate inflection point t 2 The curve at the moment follows the logarithmic function model from t 2 Resistance t from time to end of cycle 3 The curve at the moment accords with a linear function model, wherein the function corresponding to the second spline curve is as follows: the logarithmic function + linear function is: p is 2 ＝a 2 +b 2 ×ln(t+c 2 )、P 3 ＝a 3 +b 3 ×t；
FIG. 6 includes a third class of spline curves in two stages, from the initial force t 1 Time to intermediate inflection point t 2 The curve at time follows a logarithmic function from t 2 End of time cycle resistance t 3 The curve at the moment accords with an exponential function model, wherein the function corresponding to the third spline curve is as follows: the logarithmic function + exponential function is: logarithmic + exponential type: p is 4 ＝a 4 +b 4 ×ln(t+c 4 )、
As shown in fig. 7, when a relation curve between the support load and the time corresponding to each coal mining cycle is divided into 2 stages according to the variation process, the method includes:
s301-1, dividing a stage of gradually reducing the increasing speed of the support load on a relation curve of the support load and time corresponding to each coal mining cycle into a first stage of the curve, and fitting the first stage by adopting a logarithmic function;
s301-2, converting the increasing speed of the support load on a curve of the support load and the time corresponding to each coal mining cycle into a stage which is basically stable, dividing the stage into a second stage of the curve, and fitting the second stage of the curve by adopting a linear function;
s301-3, converting the increasing speed of the support load on the curve of the support load and the time corresponding to each coal mining cycle into a stage of increasing the support load in an accelerating manner, dividing the stage into a second stage of the curve, and fitting the second stage of the curve by adopting an exponential function.
Further, when constructing a spline curve of the support load of the coal mining cycle changing along with time, the method comprises the following steps:
according to the change characteristics of the relation curve of the support load and the time corresponding to the coal mining cycle after fitting treatment, dividing the relation curve in stages;
initializing a starting point of the abscissa of each relation curve divided in stages to 0;
and initializing the relation curve which is processed by stages into 0 to be used as a spline curve.
S400, establishing a data fitting window by taking a spline curve as data, fitting and comparing the support load data monitored in real time with the data in the data fitting window, calculating the load increasing speed of the hydraulic support in real time, and further predicting the load of the hydraulic support.
As a preferred embodiment, as shown in fig. 8, when the spline curve is used as the data to establish the data fitting window, the method includes:
s401, classifying the spline curves according to the change characteristics of the spline curves, and determining the number of data components of the data fitting window according to the types of the spline curves;
s402, carrying out average calculation on the load values corresponding to each abscissa value of the spline curve in the same category, and taking the obtained average as a data point of a data fitting window.
Further, when the real-time monitored support load data and the data in the data fitting window are matched and compared, and the load increase speed of the hydraulic support is calculated in real time, the method comprises the following steps:
and fitting and comparing the support load data monitored in real time with data points of a data fitting window, and determining the change characteristics of a relation curve between the support load monitored in real time and time according to the compared result so as to determine the load increase speed of the hydraulic support.
The method comprises the steps of preprocessing real-time data before drawing real-time monitored support load data into a relation curve of hydraulic support load and time, namely deleting actual measurement data which exceed 50% of a rated value and deleting data of which the actual measurement data are 0 for the support load acquired by the real-time data.
Based on the methods shown in fig. 1, 3, 7 and 8, correspondingly, the embodiment of the invention further provides a storage device, on which a computer program is stored, and the program, when executed by a processor, implements the method for piecewise predicting the load of the fully mechanized mining hydraulic support shown in fig. 1, 3, 7 and 8.
Based on the methods shown in fig. 1, 3, 7 and 8, in order to achieve the above object, an embodiment of the present invention further provides a method for predicting a load of a fully mechanized mining hydraulic support in a segmented manner, where the entity apparatus includes a storage device and a processor; a storage device for storing a computer program; and a processor for executing a computer program to implement the method for predicting the load of the fully mechanized mining hydraulic support in sections as shown in fig. 1, 3, 7 and 8.
According to the sectional prediction method for the fully-mechanized mining hydraulic support load, massive hydraulic support load data collected by a fully-mechanized mining working face hydraulic support load on-line monitoring system are processed through data sorting and analysis to obtain a spline curve, the support load data monitored in real time are matched and compared with data in a data fitting window, the increase speed of the hydraulic support load is calculated in real time, and then the hydraulic support load is predicted.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention and not to limit it; although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art will understand that: modifications to the specific embodiments of the invention or equivalent substitutions for parts of the technical features may be made; without departing from the spirit of the present invention, it is intended to cover all aspects of the invention as defined by the appended claims.
Claims (8)
1. A sectional prediction method for the load of a fully-mechanized mining hydraulic support is characterized by comprising the following steps:
collecting working parameters of the hydraulic support of the fully mechanized mining face within a period of time, wherein the working parameters comprise a measuring moment and a hydraulic support load corresponding to the measuring moment;
drawing a relation curve of the load of the hydraulic support and time according to the working parameters, and analyzing each coal mining cycle, and the initial supporting force and the cycle end resistance corresponding to each coal mining cycle according to the relation curve;
after fitting analysis is carried out on a relation curve of the hydraulic support load and the time corresponding to each coal mining cycle, a spline curve of the change of the support load of the coal mining cycle along with the time is constructed;
establishing a data fitting window by taking a spline curve as data, fitting and comparing the support load data monitored in real time with the data in the data fitting window, calculating the load increasing speed of the hydraulic support in real time, and predicting the load of the hydraulic support;
when the fitting analysis is carried out on the relation curve of the hydraulic support load corresponding to each coal mining cycle and the time, the method comprises the following steps:
dividing a relation curve of the support load and the time corresponding to each coal mining cycle into 2 stages according to the change characteristics of the relation curve;
a first stage of the relationship curve is fit-analyzed by using a logarithmic function, and a second stage of the relationship curve is fit-analyzed by using a linear or exponential function;
wherein the logarithmic function is:
；
the linear function is:
；
the exponential function is:
；
in the formula
、
、
In order to measure the load of the stent actually,
、
、
、
、
、
、
、
are representative of fitting parameters;
when dividing the relation curve of the bracket load corresponding to each coal mining cycle and the time into 2 stages according to the change process, the method comprises the following steps:
dividing the stage of gradually reducing the increasing speed of the support load on a relation curve of the support load and time corresponding to each coal mining cycle into a first stage of the curve, and fitting the first stage by adopting a logarithmic function;
the increasing speed of the support load on a relation curve of the support load and time corresponding to each coal mining cycle is converted into a stage which is basically stable, the stage is divided into a second stage of the curve, and the second stage of the curve is subjected to fitting processing by adopting a linear function;
and (3) converting the increasing speed of the support load on the relation curve of the support load and the time corresponding to each coal mining cycle into a stage of accelerating increase, dividing the stage into a second stage of the curve, and fitting the second stage of the curve by adopting an exponential function.
2. The sectional prediction method for the load of the fully mechanized mining hydraulic support according to claim 1, wherein when acquiring the working parameters of the fully mechanized mining face hydraulic support within a period of time, the method comprises the following steps:
and (3) rejecting the bracket load data of 0 generated due to sensor failure or interference and the bracket load data which is 50% higher than the rated load of the hydraulic bracket.
3. The method for predicting the load of the fully mechanized mining hydraulic support in the subsection manner according to claim 1, wherein when analyzing the initial supporting force and the end-of-cycle resistance corresponding to each coal mining cycle and each coal mining cycle according to a relation curve of the load of the hydraulic support and time, the method comprises the following steps:
dividing a plurality of coal mining cycles on a relation curve of hydraulic support load and time by taking the beginning of the initial supporting force to the end of the cycle resistance as a coal mining cycle, and obtaining the initial supporting force and the cycle end resistance corresponding to each coal mining cycle.
4. The method for predicting the load of the fully mechanized mining hydraulic support in the subsection mode according to claim 1, wherein when a spline curve of the support load of a coal mining cycle changing along with time is constructed, the method comprises the following steps:
according to the change characteristics of the relation curve of the support load and the time corresponding to the coal mining cycle after fitting processing, dividing the relation curve by stages;
initializing a starting point of the abscissa of each relation curve divided in stages to 0;
and initializing the relation curve which is processed by stages into 0 to be used as a spline curve.
5. The method for predicting the load of the fully mechanized mining hydraulic support in the subsection mode according to claim 4, wherein when a spline curve is used as data to establish a data fitting window, the method comprises the following steps:
classifying the spline curves according to the change characteristics of the spline curves, and determining the data composition number of the data fitting window according to the types of the spline curves;
and carrying out average calculation on the load values corresponding to each abscissa value of the spline curve of the same category, and taking the obtained average as a data point of a data fitting window.
6. The sectional prediction method for the fully mechanized mining hydraulic support load according to claim 5, wherein when the support load data monitored in real time is matched and compared with the data in the data fitting window, and the hydraulic support load increase speed is calculated in real time, the method comprises the following steps:
and fitting and comparing the support load data monitored in real time with data points of a data fitting window, and determining the change characteristic of a relation curve between the support load monitored in real time and time according to the compared result so as to determine the load increasing speed of the hydraulic support.
7. A storage medium on which a computer program is stored which, when being executed by a processor, carries out a method for piecewise prediction of fully mechanized mining hydraulic support loads according to any of claims 1 to 6.
8. A method for sectionally predicting a load of a fully mechanized mining hydraulic support, comprising a storage medium, a processor and a computer program stored on the storage medium and operable on the processor, wherein the processor executes the program to implement the method for sectionally predicting a load of a fully mechanized mining hydraulic support according to any one of claims 1 to 6.
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| CN110748365B (en) * | 2019-10-22 | 2021-04-27 | 神华神东煤炭集团有限责任公司 | Method and system for automatically identifying coal mining cycle number based on support load change |
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| CN112906211A (en) * | 2021-02-05 | 2021-06-04 | 神华神东煤炭集团有限责任公司 | Determination method of mine pressure law research data, storage medium and electronic equipment |
| CN114912072B (en) * | 2022-05-11 | 2023-04-07 | 中煤科工开采研究院有限公司 | Fully mechanized coal mining face pressure prediction method, device, equipment and storage medium |
| CN114792177B (en) * | 2022-06-24 | 2022-09-23 | 中煤科工开采研究院有限公司 | Multi-hydraulic support load prediction method and device for fully mechanized mining face and electronic equipment |
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