CN111220305A - Method and system for monitoring stress amplification of coal rock mass - Google Patents
Method and system for monitoring stress amplification of coal rock mass Download PDFInfo
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Abstract
The invention provides a coal rock mass stress amplification monitoring method, which comprises the steps of firstly, sampling data in real time, and sampling data by adopting a coal rock mass stress sensor to serve as a basic data sample; secondly, processing the basic data samples, including removing useless data, merging adjacent values and averaging the previous data and the next data according to the sequence; removing useless data, namely performing data filtration on the basic data sample to obtain a value sample; merging the adjacent numerical values, judging the generation time of data in the value sample by using the value sample, averaging and merging the data with a closer generation time interval to obtain a merged sample; the average value of the front data and the back data is obtained from the second data of the merged sample and the average value of the front data and the back data to form a trend sample; and thirdly, calculating an amplification result. The invention can accurately judge the increasing trend of the coal rock mass stress which is valuable to the anti-scour work under the influence of various complex factors on site, and provides a reliable numerical basis for the anti-scour work.
Description
Technical Field
The invention relates to the technical field of coal-rock mass stress monitoring, in particular to a method and a system for monitoring the stress amplification of a coal-rock mass.
Background
Rock burst has great destructiveness, and the safety of coal mine production operation is threatened all the time. When the method occurs, no obvious precursor generally exists, and the induction factors are complex and difficult to predict and accurately prevent and control.
The monitoring of the stress of the coal rock mass is an important link for preventing and predicting rock burst. The theory and application of monitoring rock burst by combining a vibration field and a stress field published in the coal science report mentions the problem of rock burst, which is actually the problem of coal and rock mass stress. For rock burst monitoring, stress is the most reliable physical quantity. The importance of stress monitoring in rock burst monitoring and early warning and guidance of daily anti-impact work of coal mines is widely accepted.
The method is an effective means for preventing and predicting rock burst by analyzing the stress change process of the coal rock mass. By monitoring the stress change process of the coal rock mass, the spontaneous type rock burst can be effectively pre-warned, and the reliability of the method is repeatedly verified by multiple experts and scholars. The coal rock mass inevitably rises through stress from a stable state of low stress to a dangerous state of high stress, and an increasing process is certainly existed before a stress numerical value reaches a dangerous grade. The monitoring system can predict the occurrence of underground disasters in advance when the obtained coal-rock body stress tends to rise to the early warning value before the coal-rock body stress reaches the early warning value. The stress monitoring system applied to the coal mine can effectively acquire the stress growth condition of the coal rock mass in real time, and has great significance for coal mine anti-impact work.
The existing coal rock mass stress monitoring sensor has a lot of noise interference in the acquired data. The sensor is influenced by technical parameters, instrument quality, use environment and the like, and the phenomenon of inaccurate stress value of the monitored coal rock mass generally exists. The sensor is limited by the measurement precision, the generated data has errors, the measurement errors of sensors on the market are mostly between +/-1% and +/-5%, and the error value is between 0.8MPa and 1.5MPa by combining the measuring range; some types of sensors have abnormal conditions of fluctuation of numerical values due to quality problems when working normally; in the production process, the influence of other factors such as excavation disturbance or micro-shock on the coal body can also cause the numerical value to suddenly jump abnormally.
The following is an example of stress monitoring data in a coal mine stress monitoring system in a certain time period, and after a large amount of data is analyzed, several typical data types are summarized, as shown in fig. 12, the data are jumping type data, most of the data have no change in size, and a large-scale jump suddenly appears at a certain time. As shown in fig. 13, in the case of jitter-type data, the value appears to continuously jitter, which may be caused by the downhole mining work, and may also be a measurement error caused by the accuracy of the instrument. As shown in fig. 14, in the floating data, the value of the data continuously and irregularly changes in a floating manner, and the internal stress may change after the coal rock mass is disturbed by mining. As shown in fig. 15, the stable data has stable overall trend of values, obvious change, no noise data and better quality.
In the existing literature data, no independent amplification monitoring method specially aiming at a coal rock body stress system exists. The stress amplification monitoring method mentioned in part of the comprehensive schemes also does not draw a conclusion about the valuable coal and rock mass stress amplification for coal mine anti-impact work. In patent document No. 201510786271.9, it is pointed out that the multi-parameter comprehensive monitoring and early-warning method for the heading face compares the real-time stress with the initial loading value and reflects the increment between the data and the initial loading value when the stress amplitude early-warning index of the coal body is calculated in step 32. The stress is increased, and the significance of preventing and controlling the daily rock burst of the coal mine is low. In actual coal mine production, the phenomenon that the coal body stress monitoring value is larger than or smaller than the initial loading value generally exists, the coal rock body state is still stable at the moment, and the amplitude compared with the initial loading value is not large for the early warning work value of coal mine rock burst.
The existing stress amplification monitoring can not meet the field requirement, and a large amount of interference data also exist in the monitoring value. The coal mine anti-impact work needs a new amplification which eliminates interference in complex data, can reflect the whole change trend and has guiding value for work. In order to adapt to complex data conditions on site and analyze the overall stress change trend, the invention designs a method for calculating the new increase of the coal rock body stress, which comprises the following steps: and (3) monitoring a numerical sample based on the stress within a period of time (the time is not too long and ranges from 1 hour to 2 hours), screening and processing to remove useless data and interference data, forming a new stress sample, and subtracting a minimum numerical value from a latest numerical value in the new sample to obtain a difference value, wherein the difference value is the stress amplification of the coal rock mass. The amplification has real-time performance and continuity, and can accurately reflect the stress increase trend of the coal rock body at the current moment. Thus, the method is valuable for coal mine anti-impact work through eliminating interference, avoiding error and accurately reflecting stress amplification of the trend.
Disclosure of Invention
In order to solve the problems, the invention provides a method and a system for monitoring the stress amplification of a coal rock mass, and the technical scheme adopted by the invention is as follows:
a method for monitoring the stress amplification of a coal rock mass comprises the following steps:
the method comprises the following steps: real-time data sampling, adopting a coal rock body stress sensor to perform data sampling as a basic data sample, wherein the characteristics of the original basic data sample are as follows: the value size and the generation time exist in pairs;
step two: carrying out data processing on the basic data sample, wherein the data processing comprises three steps of removing useless data, merging adjacent values and averaging the previous data and the next data according to the sequence;
a. removing useless data, namely performing data filtering on basic data samples; the useless data refers to that in a basic data sample, one numerical value is greatly increased or reduced compared with the previous numerical value, the subsequent numerical value returns to the level similar to the previous numerical value, the data is judged to be useless data, and the useless data and the corresponding generation time are deleted to obtain a value sample;
b. merging the adjacent numerical values, judging the generation time of data in the value sample by using the value sample, averaging and merging the data with a closer generation time interval to obtain a merged sample;
c. the average value of the front data and the back data is obtained from the second data of the merged sample and the average value of the front data and the back data to form a trend sample;
step three: calculating an amplification result, comparing the minimum value of the data of the trend sample with the initial installation value of the coal rock mass stress sensor, taking a large value as a result value to compare with the value of the last data in the trend sample, and judging that no amplification exists if the value of the last data in the trend sample is less than or equal to the result value; and if the value of the last data in the trend sample is greater than the result value, judging that amplification exists.
Preferably, the specific method for sampling real-time data in the first step is as follows:
setting a sampling time period to be delta t, and setting the current time to be tnowThe value set of the basic data sample is recorded as S, the time set of the basic data sample is recorded as T, and (T) is takennow- Δ t) to tnowData collected by one coal rock mass stress sensor in the period of time is used as a basic data sample, the basic data sample comprises numerical values and generation time, the number of the data in the basic data sample is not less than four, the data in the data basic sample are arranged according to time sequence, the numerical values in the basic data sample are sequentially placed into a set S, the generation time is sequentially placed into a set T, and the numerical value positions in the set S correspond to the generation time positions in the set T one by one.
Further, the specific method for removing the useless data in the second step is as follows:
set jitter amplitude as a, a>0, proximity tolerance is denoted as a ', a'>0, respectively recording the value set and the generation time set of the value sample as S 'and T'; a loop set S, the current nth item in the loop is recorded as SnThe former value is Sn-1The latter value is Sn+1(ii) a If Sn-Sn-1If | ≧ a, then S is judgedn-1And Sn+1The size of (d); if Sn+1-Sn-1If | ≦ a', the nth value S is determinednIs a jitter value; when the value of the nth term is notIf the value of the jitter is determined, S is judgednAdding to the set S', SnThe generation time in the set T is also added to the set T'; after circulation is finished, all the jumping data are removed, normal data are stored in the sets S 'and T', the first item and the last item do not participate in the judgment, and the numerical values and the generation time of the first item and the last item are directly stored in the numerical value set S 'and the generation time set T' of the value sample respectively according to the original positions.
Further, the specific method for merging the adjacent numerical values in the second step is as follows:
setting a time proximity criterion as B, merging start time as B ', a merging value set as B, a merging time set as B', and a value set and a generating time set of merging samples as S 'and T' respectively; initializing before circulation, making b ═ T0', will T0'deposit in B', S0' storing in B; the generation time set T' of the cycle value sample, the current nth item value in the cycle is Tn'; if (T)n'-b') < b, then T is addedn'store in B', S corresponding thereton' storing in B; if (T)n′-b′)>B, respectively averaging the values of B and B ', respectively adding the values to the two sets S ' and T ', emptying the two sets B and B ', and making B ' ═ Tn', will Tn'deposit in B', Sn' storing in B; when the circulation is to the last data, the average values in B and B ' are directly and respectively solved and are respectively added into the two sets S ' and T ', then the value of the last data and the corresponding generation time are respectively added into the sets S ' and T ', and after the circulation is finished, the data with similar time can be integrated into the sets in the mode of the average value.
Further, the specific method for calculating the mean value of the previous and subsequent data in the second step is as follows:
set mean as c, trend sample set as Sres(ii) a Starting the loop S 'from the value of the second term of the value set S' of the merged sample, the current nth term value in the loop is Sn", the former value is Sn″-1，c＝(Sn″+Sn″-1) Add c to set SresAfter the circulation is finished, a trend sample set S is obtainedres。
Further, the specific method for calculating the amplification result in the third step is as follows:
set of trend samples SresThe minimum value of the medium data is the starting point of the maximum amplitude change and is marked as dsTaking a trend sample set SresThe last data is the end point, and the corresponding value is marked as de(ii) a Setting the initial value of the coal rock mass stress sensor as dcIf d isc≥dsThen let ds＝dc(ii) a If d iss≥deThere is no amplification, if ds<deIf so, the amplification is judged to exist, and the amplification is marked as dresThen d isres＝(de-ds)。
A coal rock mass stress amplification monitoring system comprises a real-time data sampling module, a data processing module and a calculation amplification result module,
the real-time data sampling module is used for collecting data corresponding to signals sent by the coal rock mass stress sensor and is used as a basic data sample, and the original basic data sample is characterized in that: the value size and the generation time exist in pairs;
the data processing module comprises a useless data removing module, a neighborhood value merging module and a front and back data mean value module;
the useless data removing module is used for carrying out data filtering on the basic data sample, and deleting the useless data and the corresponding generation time to obtain a value sample; the useless data refers to that in a basic data sample, one numerical value is greatly increased or reduced compared with the previous numerical value, and the subsequent numerical value returns to a level similar to the previous numerical value, so that the data is judged to be useless data;
the adjacent numerical value merging module is used for judging the generation time of data in the value sample, averaging and merging the data with a closer generation time interval to obtain a merged sample;
the front and back data mean value module is used for obtaining the mean value of the second data of the combined sample and the previous data to form a trend sample;
the calculation amplification result module is used for comparing the minimum value of the data of the trend sample with the initial installation value of the coal rock body stress sensor, taking the large value as a result value to compare with the numerical value of the last data in the trend sample, and if the numerical value of the last data in the trend sample is smaller than or equal to the result value, judging that no amplification exists; and if the value of the last data in the trend sample is greater than the result value, judging that amplification exists.
The invention can accurately judge the increasing trend of the coal rock mass stress which is valuable to the anti-scour work under the influence of various complex factors on site, and provides a reliable numerical basis for the anti-scour work. The concrete advantages are as follows:
1) high accuracy
a. The interference of useless numerical values is eliminated, the original data is cleaned, valuable data is obtained to be used as a judgment basis, the influence of errors is eliminated, and the accuracy of a judgment result is improved.
b. The whole trend is accurately reflected, data are integrated according to time periods, the influence of numerical value fluctuation in a small range is eliminated, and the data can better reflect the whole change trend.
c. The jitter value generated under the normal state of the sensor is eliminated, the jitter is eliminated, and the response amplification of the result is more accurate.
2) High real-time performance
The real-time data is used as drive, the stress change of the coal rock mass can be reflected in real time, and the method can play an important role in accident prevention.
3) Is highly instructive in anti-impact work
Because the accuracy is high and the real-time performance is strong, the provided result is no longer a numerical value only used for reference, but can guide the daily anti-scour work of the coal mine in real time.
4) High practicability
The invention provides configurable parameters for an amplification calculation method designed for a coal mine stress curve in a targeted manner through characteristic analysis of a large number of data curves, and is suitable for various actual conditions.
5) Simple use and wide application range
The basic data sample of the invention is real-time data of stress monitoring, and is provided with 4 configuration parameters, thus being simple to use. The formed amplification result also has universal applicability in the aspect of numerical value, and can be integrated into most of the existing monitoring systems due to the integrity of the amplification result, and the amplification result is also suitable to be used as a subsystem of a stress part in most of the existing schemes of multi-parameter early warning, microseismic-stress comprehensive early warning and the like.
Drawings
The accompanying drawings are included to provide a further understanding of the invention.
In the drawings:
FIG. 1 is a flow chart of the operation of the method for monitoring the stress amplification of a coal-rock mass according to the invention.
FIG. 2 is a graph of a sample of the underlying data prior to the removal of the unwanted data according to the present invention.
FIG. 3 is a graph of a value sample after the invention removes the garbage.
FIG. 4 is a graph of a sample of the value before merging of neighborhood values according to the present invention.
FIG. 5 is a graph of merged samples after merging of adjacent values according to the present invention.
FIG. 6 is a graph one of the merged samples before and after the mean of the data according to the present invention.
FIG. 7 is a graph one of trend samples after the mean of data before and after the present invention.
FIG. 8 is a second graph of the merged samples before and after averaging of the data according to the present invention.
FIG. 9 is a second graph of a trend sample after the mean of data before and after the present invention.
Fig. 10 is a first graph illustrating a trend sample of the amplification result calculated according to the present invention.
Fig. 11 is a second graph illustrating a trend sample of the amplification result calculated by the present invention.
Fig. 12 is a graph of jump type data.
Fig. 13 is a graph of jitter-type data.
Fig. 14 is a graph of floating type data.
Fig. 15 is a graph of stability data.
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 derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention designs a method which can eliminate useless data and obtain the valuable amplification for anti-scour work and a complete system from data acquisition, data processing to result calculation. Defines a brand new coal and rock mass stress amplification which is more valuable for coal mine anti-impact work, and provides a complete system implementation scheme for excavating the stress amplification.
The method uses real-time monitoring data of the coal rock mass stress sensor as basic data, and sets 4 parameters of sampling time period, jumping amplitude, proximity tolerance and time proximity criterion, so that an expected amplification result can be generated. The amplification formed by the system can accurately reflect the real-time change trend of the coal rock mass stress, so that the stress monitoring can play a greater and better role in the prevention and treatment work of rock burst.
As shown in fig. 1, a method for monitoring the stress amplification of a coal-rock mass comprises the following steps:
the method comprises the following steps: real-time data sampling, adopting a coal rock body stress sensor to perform data sampling as a basic data sample, wherein the characteristics of the original basic data sample are as follows: the value size and the generation time exist in pairs; taking data in a period of time nearest to the current moment as a basic data sample of trend analysis;
the specific method for real-time data sampling comprises the following steps:
setting a sampling time period to be delta t, and setting the current time to be tnowThe value set of the basic data sample is recorded as S, the time set of the basic data sample is recorded as T, and (T) is takennow- Δ t) to tnowData collected by one coal rock mass stress sensor in the period of time is used as a basic data sample, the basic data sample comprises numerical values and generation time, the number of the data in the basic data sample is not less than four, the data in the data basic sample are arranged according to time sequence, the numerical values in the basic data sample are sequentially placed into a set S, the generation time is sequentially placed into a set T, and the numerical value positions in the set S correspond to the generation time positions in the set T one by one.
Step two: carrying out data processing on a basic data sample, wherein the data processing comprises three steps of removing useless data, merging adjacent values and averaging the previous data and the next data according to the sequence, namely, firstly carrying out data filtering and screening to form a new sample capable of accurately reflecting amplification, and then carrying out amplification judgment;
a. removing useless data, namely performing data filtering on basic data samples; the useless data refers to that in a basic data sample, one numerical value is greatly increased or reduced compared with the previous numerical value, and the subsequent numerical value returns to the level similar to the previous numerical value, so that the data is judged to be useless data, the useless data and the corresponding generation time are deleted, a value sample is obtained, and the influence of jumping data on the result is avoided;
the specific method for removing the useless data comprises the following steps:
set jitter amplitude as a, a>0, proximity tolerance is denoted as a ', a'>0, respectively recording the value set and the generation time set of the value sample as S 'and T'; a loop set S, the current nth item in the loop is recorded as SnThe former value is Sn-1The latter value is Sn+1(ii) a If Sn-Sn-1If | ≧ a, then S is judgedn-1And Sn+1The size of (d); if Sn+1-Sn-1If | ≦ a', the nth value S is determinednIs a jitter value; when the nth item value is not judged as a jitter value, S is judgednAdding to the set S', SnThe generation time in the set T is also added to the set T'; after the cycle is completed, all the jumping data are removed, the normal data are stored in the sets S 'and T', the firstAnd the item and the last item do not participate in the judgment, and the numerical values and the generation time of the first item and the last item are directly stored in the numerical value set S 'and the generation time set T' of the value sample according to the original positions.
As shown in FIG. 2, the jumping amplitude is set to be 3MPa, the approach tolerance is set to be 0.4MPa, before useless data are removed, the numerical value is stabilized at 5.5MPa, the data suddenly jump to 9.65MPa and then fall back to 5.8MPa, the numerical value is increased by 4.15 compared with the former one and is larger than the jumping amplitude, the difference between the adjacent numerical values is 0.3, the adjacent numerical value is smaller than the approach tolerance, the data are judged to be jumping data, and the numerical value of 9.65MPa belongs to the useless data. As shown in fig. 3, the jitter data is deleted for the value sample curve after the useless data is deleted.
b. Merging the adjacent numerical values, judging the generation time of data in the value sample by using the value sample, averaging and merging the data with a closer generation time interval to obtain a merged sample; in this way, the interference of the numerical value fluctuation in a short time on the overall trend analysis is eliminated. The coal rock mass stress monitoring data generally has a small-range fluctuation condition, and the small-range data is integrated into one value, so that the influence of frequent small-range data fluctuation on the whole is eliminated;
the concrete method for merging the adjacent numerical values comprises the following steps:
setting a time proximity criterion as B, merging start time as B ', a merging value set as B, a merging time set as B', and a value set and a generating time set of merging samples as S 'and T' respectively; initializing before circulation, making b ═ T0', will T0'deposit in B', S0' storing in B; the generation time set T' of the cycle value sample, the current nth item value in the cycle is Tn'; if (T)n'-b') < b, then T is addedn'store in B', S corresponding thereton' storing in B; if (T)n′-b′)>B, respectively averaging the values of B and B ', respectively adding the values to the two sets S ' and T ', emptying the two sets B and B ', and making B ' ═ Tn', will Tn'deposit in B', Sn' storing in B; when circulating to the last data, directly solving in B and B' respectivelyAnd adding the average value to the two sets S 'and T', adding the value of the last data and the corresponding generation time to the sets S 'and T', respectively, and integrating the data with similar time into the sets in an average value mode after the circulation is finished.
As shown in fig. 4, the time proximity criterion is set to be 7 minutes, and before the time proximity criterion is combined, data fluctuation occurs once in the points 13:56 and 14:17 respectively, and adjacent data fluctuate simultaneously, but most data still keep a stable state, and the fluctuation value affects the amplification judgment. Before the adjacent values are combined, the interval time of the data is about 3 minutes, the time adjacent criterion is 7 minutes, so that every three values can be judged as a group of adjacent values, after the average value is obtained, the adjacent values are combined into one value to form a curve after the adjacent values are combined, as shown in fig. 5, the fluctuation part in the curve is weakened and becomes unobvious, the time adjacent criterion values can be adjusted according to the fluctuation duration, and the basic principle is that: greater than and as close as possible to the majority of the surge duration.
c. The average value of the front data and the back data is obtained from the second data of the merged sample and the average value of the front data and the back data to form a trend sample, so that the integral trend is ensured to be unchanged, and the variation trend of single data is weakened; as shown in fig. 6, the data continuous fluctuation curve has an overall increasing trend, the average of each numerical value and the previous numerical value is calculated as the data of the data, and the trend reflected by the broken line is effectively analyzed, as shown in fig. 7; as shown in fig. 8 and 9, fig. 8 is a curve with more complex changes, and a trend sample curve with a more obvious trend is formed after the data mean processing before and after the data mean processing, as shown in fig. 9.
The specific method for calculating the mean value of the front data and the back data comprises the following steps:
set mean as c, trend sample set as Sres(ii) a Starting the loop S 'from the value of the second term of the value set S' of the merged sample, the current nth term value in the loop is Sn", the former value is Sn″-1，c＝(Sn″+Sn″-1) Add c to set SresAnd after the circulation is finished, obtaining a trend sample setSres。
Step three: calculating an amplification result, comparing the minimum value of the data of the trend sample with the initial installation value of the coal rock mass stress sensor, taking a large value as a result value to compare with the value of the last data in the trend sample, and judging that no amplification exists if the value of the last data in the trend sample is less than or equal to the result value; and if the value of the last data in the trend sample is greater than the result value, judging that amplification exists.
The specific method for calculating the amplification result comprises the following steps:
set of trend samples SresThe minimum value of the medium data is the starting point of the maximum amplitude change and is marked as dsTaking a trend sample set SresThe last data is the end point, and the corresponding value is marked as de(ii) a Setting the initial value of the coal rock mass stress sensor as dcIf d isc≥dsThen let ds＝dc(ii) a If d iss≥deThere is no amplification, if ds<deIf so, the amplification is judged to exist, and the amplification is marked as dresThen d isres＝(de-ds). As shown in fig. 10, the minimum value in the trend sample and the latest value corresponding to the last data are taken as the starting points of the amplification judgment. And subtracting the minimum value from the latest value to obtain an amplification value. As shown in fig. 11, when a plurality of identical minimum values appear in the trend sample, the minimum value corresponding to the most recent data is taken as the starting point.
The 4 setting values of the sampling time period, the jitter amplitude, the proximity tolerance and the time proximity criterion can be configured. The jitter amplification is used for judging the intensity of data change, the proximity tolerance is used for judging whether the data returns to the original similar numerical value after the data changes violently, and the data is judged to be jitter data and then is rejected only if the data reaches the jitter amplitude and also meets the proximity tolerance.
A coal rock mass stress amplification monitoring system is used for realizing the monitoring method and comprises a real-time data sampling module, a data processing module and a calculation amplification result module,
the real-time data sampling module is used for collecting data corresponding to signals sent by the coal rock mass stress sensor and is used as a basic data sample, and the original basic data sample is characterized in that: the value size and the generation time exist in pairs;
the data processing module comprises a useless data removing module, a neighborhood value merging module and a front and back data mean value module;
the useless data removing module is used for carrying out data filtering on the basic data sample, and deleting the useless data and the corresponding generation time to obtain a value sample; the useless data refers to that in a basic data sample, one numerical value is greatly increased or reduced compared with the previous numerical value, and the subsequent numerical value returns to a level similar to the previous numerical value, so that the data is judged to be useless data;
the adjacent numerical value merging module is used for judging the generation time of data in the value sample, averaging and merging the data with a closer generation time interval to obtain a merged sample;
the front and back data mean value module is used for obtaining the mean value of the second data of the combined sample and the previous data to form a trend sample;
the calculation amplification result module is used for comparing the minimum value of the data of the trend sample with the initial installation value of the coal rock body stress sensor, taking the large value as a result value to compare with the numerical value of the last data in the trend sample, and if the numerical value of the last data in the trend sample is smaller than or equal to the result value, judging that no amplification exists; and if the value of the last data in the trend sample is greater than the result value, judging that amplification exists.
The stress in the coal rock body is considered dangerous when the stress rises above a certain value, and if the monitoring value is below the initial value, the monitoring value is considered to be no danger, and the amplification does not need to be calculated. And comparing the minimum value in the trend sample with the initial value, and taking the large value as a starting point numerical value of the amplification calculation, so as to avoid the interference of the monitoring data with the numerical value below the initial value on the judgment of the underground dangerous condition.
Although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that various changes in the embodiments and/or modifications of the invention can be made, and equivalents and modifications of some features of the invention can be made without departing from the spirit and scope of the invention.
Claims (7)
1. A method for monitoring the stress amplification of a coal rock mass is characterized by comprising the following steps: the method comprises the following steps:
the method comprises the following steps: real-time data sampling, adopting a coal rock body stress sensor to perform data sampling as a basic data sample, wherein the characteristics of the original basic data sample are as follows: the value size and the generation time exist in pairs;
step two: carrying out data processing on the basic data sample, wherein the data processing comprises three steps of removing useless data, merging adjacent values and averaging the previous data and the next data according to the sequence;
a. removing useless data, namely performing data filtering on basic data samples; the useless data refers to that in a basic data sample, one numerical value is greatly increased or reduced compared with the previous numerical value, the subsequent numerical value returns to the level similar to the previous numerical value, the data is judged to be useless data, and the useless data and the corresponding generation time are deleted to obtain a value sample;
b. merging the adjacent numerical values, judging the generation time of data in the value sample by using the value sample, averaging and merging the data with a closer generation time interval to obtain a merged sample;
c. the average value of the front data and the back data is obtained from the second data of the merged sample and the average value of the front data and the back data to form a trend sample;
step three: calculating an amplification result, comparing the minimum value of the data of the trend sample with the initial installation value of the coal rock mass stress sensor, taking a large value as a result value to compare with the value of the last data in the trend sample, and judging that no amplification exists if the value of the last data in the trend sample is less than or equal to the result value; and if the value of the last data in the trend sample is greater than the result value, judging that amplification exists.
2. The method for monitoring the stress amplification of the coal rock mass according to claim 1, characterized by comprising the following steps: the specific method for sampling the real-time data in the first step comprises the following steps:
setting a sampling time period to be delta t, and setting the current time to be tnowThe value set of the basic data sample is recorded as S, the time set of the basic data sample is recorded as T, and (T) is takennow- Δ t) to tnowData collected by one coal rock mass stress sensor in the period of time is used as a basic data sample, the basic data sample comprises numerical values and generation time, the number of the data in the basic data sample is not less than four, the data in the data basic sample are arranged according to time sequence, the numerical values in the basic data sample are sequentially placed into a set S, the generation time is sequentially placed into a set T, and the numerical value positions in the set S correspond to the generation time positions in the set T one by one.
3. The method for monitoring the stress amplification of the coal rock mass according to claim 2, characterized by comprising the following steps: the specific method for removing the useless data in the second step is as follows:
set jitter amplitude as a, a>0, proximity tolerance is denoted as a ', a'>0, respectively recording the value set and the generation time set of the value sample as S 'and T'; a loop set S, the current nth item in the loop is recorded as SnThe former value is Sn-1The latter value is Sn+1(ii) a If Sn-Sn-1If | ≧ a, then S is judgedn-1And Sn+1The size of (d); if Sn+1-Sn-1If | ≦ a', the nth value S is determinednIs a jitter value; when the nth item value is not judged as a jitter value, S is judgednAdding to the set S', SnThe generation time in the set T is also added to the set T'; after circulation is finished, all jumping data are removed, normal data are stored in sets S 'and T', the first item and the last item do not participate in the judgment, and the numerical values and the yield of the first item and the last item are directly obtained according to the original positionsThe generation time is respectively stored in the value set S 'and the generation time set T' of the value sample.
4. The method for monitoring the stress amplification of the coal rock mass according to claim 3, characterized by comprising the following steps: the specific method for merging the adjacent numerical values in the second step comprises the following steps:
setting a time proximity criterion as B, merging start time as B ', a merging value set as B, a merging time set as B', and a value set and a generating time set of merging samples as S 'and T' respectively; initializing before circulation, making b ═ T0', will T0'deposit in B', S0' storing in B; the generation time set T' of the cycle value sample, the current nth item value in the cycle is Tn'; if (T)n'-b') < b, then T is addedn'store in B', S corresponding thereton' storing in B; if (T)n′-b′)>B, respectively averaging the values of B and B ', respectively adding the values to the two sets S ' and T ', emptying the two sets B and B ', and making B ' ═ Tn', will Tn'deposit in B', Sn' storing in B; when the circulation is to the last data, the average values in B and B ' are directly and respectively solved and are respectively added into the two sets S ' and T ', then the value of the last data and the corresponding generation time are respectively added into the sets S ' and T ', and after the circulation is finished, the data with similar time can be integrated into the sets in the mode of the average value.
5. The method for monitoring the stress amplification of the coal rock mass according to claim 4, wherein the method comprises the following steps: the specific method for calculating the mean value of the front and back data in the second step is as follows:
set mean as c, trend sample set as Sres(ii) a Starting with the value of the second term of the set S ' of values of the merged sample, the loop S ', where the current nth term has the value S ', isnThe former value is S ″)n-1，c＝(S″n+S″n-1) Add c to set SresAfter the circulation is finished, a trend sample set S is obtainedres。
6. The method for monitoring the stress amplification of the coal rock mass according to claim 5, wherein the method comprises the following steps: the specific method for calculating the amplification result in the third step is as follows:
set of trend samples SresThe minimum value of the medium data is the starting point of the maximum amplitude change and is marked as dsTaking a trend sample set SresThe last data is the end point, and the corresponding value is marked as de(ii) a Setting the initial value of the coal rock mass stress sensor as dcIf d isc≥dsThen let ds＝dc(ii) a If d iss≥deThere is no amplification, if ds<deIf so, the amplification is judged to exist, and the amplification is marked as dresThen d isres＝(de-ds)。
7. A coal rock mass stress amplification monitoring system is characterized in that: comprises a real-time data sampling module, a data processing module and a calculation amplification result module,
the real-time data sampling module is used for collecting data corresponding to signals sent by the coal rock mass stress sensor and is used as a basic data sample, and the original basic data sample is characterized in that: the value size and the generation time exist in pairs;
the data processing module comprises a useless data removing module, a neighborhood value merging module and a front and back data mean value module;
the useless data removing module is used for carrying out data filtering on the basic data sample, and deleting the useless data and the corresponding generation time to obtain a value sample; the useless data refers to that in a basic data sample, one numerical value is greatly increased or reduced compared with the previous numerical value, and the subsequent numerical value returns to a level similar to the previous numerical value, so that the data is judged to be useless data;
the adjacent numerical value merging module is used for judging the generation time of data in the value sample, averaging and merging the data with a closer generation time interval to obtain a merged sample;
the front and back data mean value module is used for obtaining the mean value of the second data of the combined sample and the previous data to form a trend sample;
the calculation amplification result module is used for comparing the minimum value of the data of the trend sample with the initial installation value of the coal rock body stress sensor, taking the large value as a result value to compare with the numerical value of the last data in the trend sample, and if the numerical value of the last data in the trend sample is smaller than or equal to the result value, judging that no amplification exists; and if the value of the last data in the trend sample is greater than the result value, judging that amplification exists.
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