CN116698628A - Characterization method, device, equipment and storage medium of dynamic load response characteristics of anchor rod - Google Patents

Abstract

The invention provides a characterization method, a device, equipment and a storage medium of dynamic load response characteristics of an anchor rod, which are implemented by acquiring a preprocessed test data set; the preprocessed test data set comprises the rod body load and the accumulated rod body elongation of the anchor rod; calculating through a moving average algorithm, a standard deviation algorithm, a confidence interval algorithm, a maximum and minimum value algorithm or a quantile algorithm to obtain a target data set; drawing a target curve corresponding to the target data set by taking the accumulated elongation of the rod body as an abscissa and the load of the rod body as an ordinate; the target curve includes an upper envelope, a lower envelope, and a median. The method can obtain the target curve of the dynamic load response characteristic of the anchor rod, can intuitively reflect the trend and the fluctuation of test data through the target curve, is favorable for detecting abnormal values, and can provide key basic data support in aspects of anchor rod support selection of a mine tunnel, tunnel support scheme optimization, tunnel rock burst disaster prevention and control and the like.

Description

Characterization method, device, equipment and storage medium of dynamic load response characteristics of bolt

technical field

The invention relates to the field of bolt support engineering, and in particular to a characterization method, device, equipment and storage medium for dynamic load response characteristics of bolts.

Background technique

Anchor is an important component in the field of engineering construction, which can bear the tension generated by earth pressure, water pressure or wind load, and is used to maintain the stability of structures or strengthen the rock and soil environment. For example, in coal mining, a large number of tunnels are often excavated under the mine, and bolts are installed in the rock formations around the tunnels to form an overall stable rock belt, and the bolts and surrounding rocks work together to maintain the stability of the tunnels. In addition, bolts are also used in civil tunnel construction, slope reinforcement, dam reinforcement and other fields.

As the depth of engineering construction increases year by year, the construction environment is also constantly changing. Due to the high ground stress in deep mines, there is a large strain energy stored in the rock body. When the energy of this part exceeds the support capacity of the bolt support system , prone to "rockburst". The choice of which anchor rod needs to take into account both the safety of construction quality and the cost of engineering construction.

It can be seen that in the face of the difficulty in matching the current construction environment changes and the adaptability of bolts, the study of the response characteristics of bolts under impact loads has become an important issue in the industry in the selection of bolt support.

Contents of the invention

In view of the above technical problems, the present invention provides a characterization method, device, equipment and storage medium for dynamic load response characteristics of bolts.

The invention provides a method for characterizing the dynamic load response characteristics of a bolt, including:

Obtain a preprocessed test data set; the preprocessed test data set includes the rod body load, rod body load, and Cumulative elongation;

Calculate the preprocessed rod body load and the cumulative elongation of the rod body through a preset algorithm to obtain a target data set; wherein the preset algorithm includes a moving average algorithm, a standard deviation algorithm, a confidence interval algorithm, At least one of the max-min algorithm and the quantile algorithm;

Taking the cumulative elongation of the rod body as the abscissa and the rod body load as the ordinate, draw the target curve corresponding to the target data set; the target curve is the dynamic load response characteristic curve of the anchor rod, and the dynamic load response characteristic curve is Including upper envelope, lower envelope and median line.

According to a method for characterizing the dynamic load response characteristics of anchor bolts provided by the present invention, the preset algorithm includes a moving average algorithm; The amount is calculated to obtain the target data set, including:

Sorting the cumulative elongation of the pretreated rods in ascending order to obtain a sequence of cumulative elongation of the rods;

For each sequence value in the cumulative elongation sequence of the rod, obtain the rod load corresponding to each sequence value in the first preset sliding window corresponding to the sequence value, obtain the first rod load set, and calculate the second The average value of a set of rod loads;

Deviate the average value from the preset percentage respectively to obtain the upper bound of the average value of the rod body load and the lower bound of the average value of the rod body load corresponding to each sequence value;

All sequence values in the accumulative elongation sequence of the rod body and their corresponding upper bound and lower bound of the average load value of the rod body are used as the target data set.

According to a method for characterizing the dynamic load response characteristics of bolts provided by the present invention, the preset algorithm includes a standard deviation algorithm; Perform calculations to obtain the target data set, including:

Sorting the cumulative elongation of the pretreated rods in ascending order to obtain a sequence of cumulative elongation of the rods;

For each sequence value in the cumulative elongation sequence of the rod, obtain the rod load corresponding to each sequence value in the second preset sliding window corresponding to the sequence value, obtain a second rod load set, and calculate the first The standard deviation of the set of two rod loads;

Deviate the standard deviation up and down by the second preset percentage respectively to obtain the upper bound of the standard deviation of the rod body load and the lower bound of the standard deviation of the rod body load corresponding to each sequence value;

All sequence values in the cumulative elongation sequence of the rod body and their corresponding upper bounds of the standard deviation of the rod body load and lower bounds of the standard deviation of the rod body load are used as the target data set.

According to a method for characterizing the dynamic load response characteristics of bolts provided by the present invention, the preset algorithm further includes a confidence interval algorithm; The amount is calculated to obtain the target data set, including:

Get the Z value based on the preset reliability level;

For each sequence value in the cumulative elongation sequence of the rod body, the upper bound of the rod body load confidence interval and the lower bound of the rod body load confidence interval corresponding to each sequence value are calculated based on the Z value and the standard deviation;

All sequence values in the cumulative elongation sequence of the rod body and their corresponding upper bound of the confidence interval of the rod body load and lower bound of the confidence interval of the rod body load are taken as the target data set.

According to a method for characterizing the dynamic load response characteristics of anchor bolts provided by the present invention, the preset algorithm includes a maximum and minimum value algorithm; The amount is calculated to obtain the target data set, including:

Sorting the cumulative elongation of the pretreated rods in ascending order to obtain a sequence of cumulative elongation of the rods;

For each sequence value in the cumulative elongation sequence of the rod, obtain the rod load corresponding to each sequence value in the third preset sliding window adjacent to the sequence value, obtain a third rod load set, and calculate the The maximum value of the rod load and the minimum value of the rod load in the third rod load set;

All sequence values in the cumulative elongation sequence of the rod body and their corresponding maximum rod load values and minimum rod load values are taken as the target value set.

According to a method for characterizing the dynamic load response characteristics of anchor bolts provided by the present invention, the preset algorithm includes a quantile algorithm; The amount is calculated to obtain the target data set, including:

Sorting the cumulative elongation of the pretreated rods in ascending order to obtain a sequence of cumulative elongation of the rods;

For each sequence value in the cumulative elongation sequence of the rod body, use the fourth preset sliding window to sequentially select sub-windows on the cumulative elongation sequence of the rod body;

Calculate the maximum value of the rod load and the minimum value of the rod load in each sub-window;

All sequence values in the cumulative elongation sequence of the rod body and their corresponding maximum rod load values and minimum rod load values are taken as the target value set.

The present invention also provides a method for bolt selection, the method comprising:

Obtain the occurrence characteristic data of coal mine strata;

According to the needs of the project, design the roadway excavation scheme of the roadway section, such as: roadway shape and geometric dimensions;

According to the occurrence characteristic data and the roadway excavation scheme, adopt the corresponding support design method to determine the bolting scheme of the roadway; the bolting scheme includes the dynamic parameter requirements of the bolt;

Match the dynamic parameter requirements of the bolt with the dynamic load response characteristic curve of the bolt obtained by applying the characterization method of the dynamic load response characteristic of the bolt above, and determine the optimal characteristic parameters of the bolt according to the matching results, so as to complete the bolt selection.

The present invention also provides a characterization device for dynamic load response characteristics of anchor rods, the device comprising:

The data acquisition module is used to acquire the preprocessed test data set; the preprocessed test data set includes the anchor in each impact collected during the process of the anchor being subjected to one or more impacts until it breaks. Rod body load, rod body cumulative elongation;

The data processing module is used to calculate the preprocessed rod body load and the cumulative elongation of the rod body through a preset algorithm to obtain a target data set; wherein the preset algorithm includes a moving average algorithm, a standard deviation At least one of algorithm, confidence interval algorithm, max-min algorithm and quantile algorithm;

The curve drawing module takes the cumulative elongation of the rod as the abscissa and the load of the rod as the ordinate to draw the target curve corresponding to the target data set; the target curve is the dynamic load response characteristic curve of the anchor rod, and the dynamic The load response characteristic curve includes an upper envelope, a lower envelope and a median line.

The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. Characterization method of load response characteristics.

The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the characterization method for the dynamic load response characteristics of the bolt as described above can be realized.

The present invention also provides a computer program product, including a computer program. When the computer program is executed by a processor, the method for characterization of the dynamic load response characteristics of the bolt as described above can be realized.

The present invention provides a characterization method, device, equipment and storage medium for the dynamic load response characteristics of a bolt, by obtaining a preprocessed test data set; the preprocessed test data set includes During the process until the fracture, the rod body load and the cumulative elongation of the anchor rod in each impact are collected; the pre-processed rod body load and the cumulative elongation of the rod body are calculated by the preset algorithm to obtain the target data set; Wherein, the preset algorithm includes at least one of the moving average algorithm, standard deviation algorithm, confidence interval algorithm, maximum and minimum value algorithm and quantile algorithm; the abscissa is the cumulative elongation of the rod body, and the vertical coordinate is the rod load , draw the target curve corresponding to the target data set; the target curve includes an upper envelope, a lower envelope and a median line. The invention can obtain the target curve of the dynamic load response characteristics of the bolt, through which the trend and fluctuation of the test data can be intuitively reflected, which is helpful to detect abnormal values, and can be used in the selection of bolt support and roadway support in mine roadways. Provide key basic data support for the optimization of protection schemes and the prevention and control of roadway rock burst disasters.

Description of drawings

In order to more clearly illustrate the present invention or the technical solutions in the prior art, the accompanying drawings that need to be used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings in the following description are the present invention. For some embodiments of the invention, those skilled in the art can also obtain other drawings based on these drawings without creative effort.

Fig. 1 is one of schematic flow charts of the characterization method of the bolt dynamic load response characteristic provided by the present invention;

Fig. 2 is the second schematic flow chart of the characterization method of the bolt dynamic load response characteristic provided by the present invention;

Fig. 3 is the schematic diagram of the dynamic load response characteristic curve of the bolt provided by the present invention;

Fig. 4 is the structural schematic diagram of the characterization device of the bolt dynamic load response characteristic provided by the present invention;

Fig. 5 is a schematic structural view of the bolt type selection device provided by the present invention;

Fig. 6 is a schematic structural diagram of an electronic device provided by the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention , but not all examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

It should be noted that, in the description of the embodiments of the present invention, the terms "comprising", "comprising" or any other variant thereof are intended to cover a non-exclusive inclusion, so that a process, method, article or device comprising a series of elements Not only those elements are included, but also other elements not expressly listed or inherent in such process, method, article or apparatus. Without further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article or apparatus comprising said element. The orientation or positional relationship indicated by the terms "upper", "lower", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the referred device or element must Having a particular orientation, being constructed and operating in a particular orientation, and therefore not to be construed as limiting the invention. Unless otherwise clearly specified and limited, the terms "installation", "connection" and "connection" should be interpreted in a broad sense, for example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection, It can also be an electrical connection; it can be a direct connection, or an indirect connection through an intermediary, or an internal communication between two components. Those of ordinary skill in the art can understand the specific meanings of the above terms in the present invention according to specific situations.

The terms "first", "second" and the like in this application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms so used are interchangeable under appropriate circumstances such that the embodiments of the application can be practiced in sequences other than those illustrated or described herein, and that references to "first," "second," etc. distinguish Objects are generally of one type, and the number of objects is not limited. For example, there may be one or more first objects. In addition, "and/or" indicates at least one of the connected objects, and the character "/" generally indicates that the associated objects before and after are in an "or" relationship.

A specific embodiment of the present invention will be described below with reference to FIGS. 1-5 .

In one embodiment, as shown in Figure 1, a method for characterizing the dynamic load response characteristics of a bolt is provided, comprising the following steps:

Step 101, obtain a preprocessed test data set; the preprocessed test data set includes the rod body load of the anchor rod in each impact collected during the process of the anchor rod being subjected to one or more impacts until it breaks , the cumulative elongation of the rod body;

Among them, the rod load refers to various direct actions exerted on the engineering structure to make the engineering structure or components produce effects. The cumulative elongation of the rod body refers to the cumulative algebraic sum of the elongation of the rod body in the previous impact overshoot of the anchor rod.

Specifically, a certain form of bolt dynamic load impact test bench (for example, a drop hammer impact test bench) is used to impact the bolt once or more times with a certain energy (higher than the energy threshold of the bolt impact deformation), until the bolt eventually broke. During each impact process, real-time collection of index data such as the load of the anchor rod body and the elongation of the rod body. Among them, the starting point of the elongation of the rod body in the latter impact is the elongation amount of the rod body after the end of the previous impact. Based on this point, the elongation increment of this impact is superimposed algebraically, and then the dynamic accumulation during the impact process is obtained. Elongation. In this way, the load of the rod body and the cumulative elongation of the rod body in the previous impact process of the bolt are obtained. Using this data pair as a sample, a data set of the dynamic load impact response of the bolt is obtained, which is used as a data sample for drawing the envelope in the next step.

Before the algorithm processing of the test data set, preprocessing is also required. The preprocessing process includes: data preprocessing operations such as data cleaning and missing value filling for the test data to ensure the reliability and integrity of the test data. Among them, data cleaning includes eliminating interference data. Eliminate the interference points in the original data, retain the valid data, and improve the accuracy of the analysis sample. This is because: in the previous impact tests of the bolt, two parts of data need to be eliminated in each impact process: one is the moment when the falling weight hits the pallet, the impact load rises sharply from 0kN to the yield load, but the value during the increase process is far from The second is that the rod body rebounded at the end of the impact, and the impact load caused by the rebound dropped sharply from above 200kN to below 100kN, and the value during the steep drop process was much lower than that in the yield and strengthening stage load value. If these data are retained, it will affect the accuracy of the analysis results and reduce the credibility of the envelope. Therefore, it is necessary to eliminate load abnormal points.

After removing abnormal data points, the preprocessed test data set is obtained.

Step 102, calculate the preprocessed rod body load and the cumulative elongation of the rod body through a preset algorithm to obtain a target data set; wherein, the preset algorithm includes a moving average algorithm, a standard deviation algorithm, a confidence At least one of interval algorithm, maximum-minimum algorithm and quantile algorithm.

Specifically, for the preprocessed test data, a variety of data analysis algorithms can be used, such as moving average method, standard deviation method, maximum and minimum value method, confidence interval method, quantile method, etc., to obtain the data corresponding to the algorithm Set, and then get the data set of the envelope. The data set includes a collection of data pairs required for the upper envelope, lower envelope, and median line.

Step 103, taking the cumulative elongation of the rod as the abscissa and the load of the rod as the ordinate, draw the target curve corresponding to the target data set; the target curve is the dynamic load response characteristic curve of the bolt, and the dynamic load The response characteristic curve includes an upper envelope, a lower envelope, and a median line.

Specifically, with the cumulative elongation of the rod body as the abscissa and the rod load as the ordinate, the target curve corresponding to the above target data set is drawn; the target curve is the dynamic load response characteristic curve of the above anchor rod, and the dynamic load response The characteristic curve includes an upper envelope, a lower envelope or a median line.

In the above embodiment, the preprocessed test data set is processed by the moving average algorithm, the standard deviation algorithm, the confidence interval algorithm, the maximum minimum algorithm or the quantile algorithm, and the target curve of the dynamic load response characteristic of the bolt is obtained. The target curve can intuitively reflect the trend and volatility of the test data, help to detect outliers, and provide key information in the selection of bolt support in mine roadways, optimization of roadway support schemes, prevention and control of roadway rock burst disasters, etc. basic data support.

In one embodiment, the above-mentioned preset algorithm includes a moving average algorithm; the above-mentioned step 102 includes: sorting the pre-processed cumulative elongation of the rod body in order from small to large to obtain the sequence of the cumulative elongation of the rod body; For each sequence value in the elongation sequence, obtain the rod body load corresponding to each sequence value in the preset sliding window corresponding to the sequence value, obtain the first rod body load set, and calculate the average value of the first rod body load set; Deviate from the preset percentage respectively to obtain the upper bound of the average value of the rod load and the lower bound of the average value of the rod body load corresponding to each sequence value; combine all the sequence values in the rod load sequence and their corresponding upper bound of the average value of the rod body load and the average value of the rod body load The lower bound serves as the target dataset.

Among them, the moving average algorithm is used to calculate the average value of the data set. In this algorithm, for any data point, a certain number of data points in its neighborhood window are used for averaging. Traverse each data point in the data set to get a set of mean values.

Specifically, the moving average algorithm in this embodiment mainly includes:

① Local description results of scattered points: take the cumulative elongation of the rod body as the abscissa, and the rod load as the ordinate, select the fixed number of points W _points in the sliding window, and divide the preprocessed test data set according to the cumulative elongation of the rod body (that is, the abscissa ) are sorted from small to large, and for the i-th point, its vertical coordinate adopts the to /> The average value of the ordinate of each record is described, and the result of the ordinate description of any scattered point can be obtained:

In the formula, is the average value of the vertical coordinates of the neighborhood of the i-th point in the cumulative elongation sequence of the rod body; _{W points} is the number of sliding window points; The corresponding abscissa is x _i .

②Setting deviation: In order to obtain the upper and lower bound envelopes, it is necessary to perform offset processing on the local description results of scattered points. The moving average method is in the form of a percentage, so it is necessary to set the deviation percentage Deviation.

In the formula, is the average ordinate value of the neighborhood of the i-th point in the accumulative elongation sequence of the rod body, u _i is the upper bound of the average value of the rod body load at the i-th point, l _i is the lower bound of the average value of the rod body load at the i-th point, Deviation is the upper and lower bounds deviation percentage.

In the above embodiment, the upper bound and lower bound of the average load value of each rod body corresponding to the cumulative elongation of each rod body are calculated through the moving average algorithm, which is beneficial to provide a data basis for subsequent detection of abnormality of the anchor rod.

In one embodiment, the above preset algorithm includes a standard deviation algorithm, and the above step 102 includes: sorting the preprocessed cumulative elongation of the rod body in order from small to large to obtain the sequence of the cumulative elongation of the rod body; For each sequence value in the long sequence, obtain the rod body load corresponding to each sequence value in the preset sliding window corresponding to the sequence value, obtain the second rod body load set, and calculate the standard deviation of the second rod body load set; Deviate from the second preset percentage up and down to obtain the upper bound of the standard deviation of the rod load and the lower bound of the standard deviation of the rod load corresponding to each sequence value; combine all the sequence values in the rod load sequence and their corresponding upper bound of the standard deviation of the rod load and the rod load The standard deviation lower bound is used as the target data set.

Among them, the standard deviation algorithm is a statistical algorithm to measure the degree of dispersion of the data series, which is used to analyze the degree of dispersion and volatility of the data. The algorithm calculates the mean of the data set and the sum of squares of the difference between each data point and the mean, and finally divides the sum of squares of the difference by the number of data points to obtain the standard deviation value. The larger the standard deviation value, the more dispersed the distribution of the data set, and vice versa.

Specifically, the envelope of the data series can be obtained by using the concept of standard deviation. The envelope of a data series can be calculated by adding and subtracting the mean and standard deviation of the data series appropriately. Specifically, the upper limit envelope of the data series can add a certain multiple of the standard deviation to the average value, and the multiple needs to be determined according to the volatility of the data. In the same way, the lower limit envelope of the data series can subtract a certain multiple of the standard deviation from the mean. The mathematical description of the algorithm is as follows:

① Scattered local description results: the sliding window selects a fixed width, and the original data set is sorted by the value of the abscissa. For the kth window, the vertical coordinate adopts the horizontal coordinate range in to /> The mean value of the vertical coordinates of the scattered points in the window is described, so the description result of any scattered point can be obtained.

In the formula, and /> Respectively represent the calculated average and standard deviation of all calculated sequence scatter points in the kth window, mean(y _i ) represents the mean function, and std(y _i ) represents the standard deviation function.

②Setting deviation: In order to obtain the upper and lower boundary envelopes, it is necessary to perform offset processing on the local description results of scattered points. The algorithm uses the multiple α of the standard deviation to set.

In the formula, To calculate the ordinate of the kth window of the upper bound sequence of the data set, /> To calculate the ordinate of the k-th window of the lower bound sequence of the data set, the corresponding abscissa is k·W _width , and α is the multiple of the standard deviation of the upper and lower bounds.

In the above embodiments, the upper bound of the standard deviation of the rod load and the lower bound of the standard deviation of the rod load corresponding to the cumulative elongation of each rod body are calculated through the standard deviation algorithm, which is beneficial to provide a data basis for subsequent detection of abnormalities in the bolt.

In one embodiment, the above-mentioned preset algorithm also includes a confidence interval algorithm; the above-mentioned step 102 also includes:

The Z value is obtained based on the preset reliability level; for each sequence value in the cumulative elongation sequence of the rod body, the upper bound of the rod load confidence interval and the lower bound of the rod load confidence interval corresponding to each sequence value are calculated based on the Z value and standard deviation ; Take all sequence values in the rod load sequence and their corresponding upper bound of the rod load confidence interval and lower bound of the rod load confidence interval as the target data set.

Among them, the confidence interval method is a statistical interval estimation method, which uses an interval to estimate an unknown overall parameter, such as the overall mean, overall proportion, etc. The meaning of the confidence interval is that in the case of repeated sampling, there is a certain probability (confidence level) to ensure that this interval contains the real overall parameters, that is, the statistical parameters of this interval can be used to represent the probability of the overall statistical parameters.

Similar to the idea of obtaining the envelope of the data series by the standard deviation method, its description of the scattered points in the interval includes two parts, the mean and the variance. The upper and lower envelopes of the data series are respectively replaced by the upper and lower bounds of the scatter confidence interval within the window range W _width . The mathematical description of the algorithm is as follows:

In the formula, To calculate the ordinate of the kth window of the upper bound sequence of the data set, /> In order to calculate the ordinate of the kth window of the lower bound sequence of the data set, Z(β) represents the statistical Z value corresponding to the confidence level β.

In the above embodiment, the upper bound of the rod load confidence interval and the lower bound of the rod load confidence interval corresponding to the cumulative elongation of each rod body are calculated through the confidence interval algorithm, which is beneficial to provide a data basis for subsequent detection of abnormality of the bolt.

In one embodiment, the aforementioned preset algorithm includes a maximum and minimum value algorithm; the aforementioned step 102 includes:

Sorting the pretreated cumulative elongation of the rods in ascending order to obtain the cumulative elongation sequence of the rods; for each sequence value in the cumulative elongation sequence of the rods, obtain the third preset Set the rod load corresponding to each sequence value in the sliding window to obtain the third rod load set, and calculate the maximum rod load and the minimum rod load in the third rod load set; combine all the sequence values in the rod load sequence and their corresponding The maximum value of the rod load and the minimum value of the rod load are used as a set of target values.

Specifically, in order to ensure that all sample points are included in the envelope, the maximum and minimum method uses the maximum and minimum values of all sampling points within the specified sliding window points W _points or window size W _width as the upper envelope and Lower envelope, the advantage of this method is that the calculation is simple, and at the same time, it ensures that all scattered points are enveloped. Correspondingly, due to the lack of statistical analysis of the sampling points, the representative ability of the data is insufficient. If there are fewer sampling points, the representativeness and accuracy of the obtained envelope are insufficient, and the smoothness of the curve is insufficient. The mathematical description of the algorithm is as follows:

① Sliding window points W _points acquisition: select a fixed number of points in the sliding window, sort the original data according to the abscissa, and for the i-th point, select to /> The scatter point description of any scatter point can be described by the upper and lower bounds of any scatter point.

In the formula, u _i is the ordinate of the i-th point in the upper bound sequence of the calculation data set, l _i is the ordinate of the i-th point in the lower bound sequence of the calculation data set, max(...), min(...) represent the maximum value and minimum function.

②Fixed window size W _width acquisition: respectively describe the abscissa as W _width , 2W _width , and the upper bound ordinate of the position corresponding to nW _width and the lower bound ordinate />

In the formula, To calculate the ordinate of the kth window of the upper bound sequence of the data set, /> It is the vertical coordinate of the kth window of the lower bound sequence of the calculation data set.

In the above embodiment, the maximum and minimum load values of the rod body corresponding to the accumulated elongation of each rod body are calculated through the maximum value and minimum value algorithm, which is beneficial to provide a data basis for subsequent detection of abnormality of the bolt.

In one embodiment, the aforementioned preset algorithm includes a quantile algorithm; the aforementioned step 102 includes:

Sorting the pretreated cumulative elongation of rods in ascending order to obtain the cumulative elongation sequence of rods; for each sequence value in the cumulative elongation sequence of rods, using the fourth preset sliding window, Select sub-windows sequentially on the cumulative elongation sequence; calculate the maximum value of the rod load and the minimum value of the rod load in each sub-window; combine all sequence values in the cumulative elongation sequence of the rod and their corresponding maximum rod load and rod load The minimum value is used as the set of target values.

Specifically, the algorithm uses the quantile indicator to describe the original data set, which divides the data into quarters, medians, three quarters, etc., to reflect the distribution of the data. According to the set upper and lower quantiles, the position of a sample data in the whole data set can be determined, so as to obtain the envelope of the data. This algorithm is very useful when dealing with dynamic data and can quickly understand the trends and changes in the data. The mathematical description of the algorithm is as follows:

Finding method: select a fixed width for the sliding window, sort the original data according to the abscissa, and for the kth window, obtain the abscissa within to /> The scatter sequence of the new sequence is sorted from small to large according to the vertical coordinate, and the horizontal and vertical coordinates of the new sequence are respectively recorded as /> There are a total of M scattered points. Determine the upper and lower bounds of the envelope according to the following formula:

In the formula, To calculate the ordinate of the kth window of the upper bound sequence of the data set, /> To calculate the ordinate of the kth window of the lower bound sequence of the data set, W _width is the window size, P _u and P _l are the upper and lower quantiles respectively, M is the number of sampling points in this interval, k _u and k _l represent the upper and lower quantiles respectively The sort subscript position of the digit.

In the above-mentioned embodiment, the maximum value and minimum load value of the rod body corresponding to the cumulative elongation of each rod body are obtained by calculating the quantile algorithm, which is beneficial to provide a data basis for subsequent detection of abnormality of the anchor rod.

The present application also provides a bolt type selection method, including: obtaining the occurrence characteristic data of the coal mine stratum; , use the corresponding support design method to determine the bolt support scheme of the roadway, and propose the dynamic parameter requirements of the bolt; combine the dynamic parameter requirements of the bolt with the dynamic load response characteristics of the bolt recorded in the above examples The dynamic load response characteristic curve of the bolt obtained by the characterization method is matched, and the characteristic parameters of the bolt are determined according to the matching result.

Among them, the occurrence characteristic data of the coal mine strata refer to the stratum conditions where the construction project is located, including rock strength, fracture development degree, ground stress, etc., which can be flexibly selected according to the actual situation, and are not limited in this paper.

Specifically, when construction operations are required, such as the construction of an underground roadway, it is necessary to detect the local stratum conditions first, and obtain the occurrence characteristic data of the coal mine stratum through different measuring devices; Excavation plan, which includes roadway shape and roadway geometric dimensions and other information; according to the existing characteristic data and roadway excavation plan, determine the bolt support plan of the roadway, and propose the dynamic parameter requirements of the bolt; The parameter requirements are compared and matched with the above dynamic load response characteristic curve of the anchor, and finally the characteristic parameters of the required anchor are obtained, including the thickness, length, spacing, yield strength, etc. of the anchor.

In the above-mentioned embodiment, the dynamic load response characteristic curve of the bolt is obtained through prior tests, wherein the dynamic load response characteristic curves of different types of bolts are unique. The characteristic curves of the dynamic load response of the bolt are compared and matched, and finally the best characteristic parameters of the bolt are obtained. Compared with the traditional method of determining the characteristic parameters of bolts through tests based on actual conditions, this method can improve the efficiency of bolt selection, save the cost of repeated tests, and provide an effective data basis for subsequent maintenance and replacement of bolts. .

The characterization device for the dynamic load response characteristics of the anchor rod provided by the present invention is described below, and the characterization device for the dynamic load response characteristics of the anchor rod described below and the characterization method for the dynamic load response characteristics of the anchor rod described above can be referred to each other.

In one embodiment, as shown in FIG. 4 , a characterization device for dynamic load response characteristics of a bolt is provided, including: a data acquisition module 401, a data processing module 402, and a curve drawing module 403, wherein,

The data acquisition module 401 is configured to acquire a preprocessed test data set; the preprocessed test data set includes the data described in each impact collected when the bolt is subjected to one or more impacts until it breaks. Rod body load of the anchor rod, cumulative elongation of the rod body;

The data processing module 402 is used to calculate the preprocessed rod body load and the cumulative elongation of the rod body through a preset algorithm to obtain a target data set; wherein the preset algorithm includes a moving average algorithm, a standard At least one of difference algorithm, confidence interval algorithm, maximum and minimum algorithm and quantile algorithm;

The curve drawing module 403 draws the target curve corresponding to the target data set with the cumulative elongation of the rod body as the abscissa and the rod body load as the ordinate; the target curve includes an upper envelope, a lower envelope and a middle envelope. value line.

In one of the embodiments, the preset algorithm includes a moving average algorithm; the above-mentioned data processing module 402 is further used for:

Sorting the pretreated cumulative elongation of rods in ascending order to obtain a sequence of cumulative elongation of rods; for each sequence value in the cumulative elongation of rods, obtaining The rod body load corresponding to each sequence value in the corresponding first preset sliding window is obtained to obtain the first rod body load set, and the average value of the first rod body load set is calculated; the average value is respectively deviated from the preset percentage to obtain each The upper bound of the average value of the rod body load and the lower bound of the average value of the rod body load corresponding to the sequence value; all the sequence values in the cumulative elongation sequence of the rod body and their corresponding upper bound of the average value of the rod body load and the lower bound of the average value of the rod body load are used as the described target dataset.

In one of the embodiments, the preset algorithm includes a standard deviation algorithm; the above-mentioned data processing module 402 is further used for:

Sorting the pretreated cumulative elongation of rods in ascending order to obtain a sequence of cumulative elongation of rods; for each sequence value in the cumulative elongation of rods, obtaining The rod body load corresponding to each sequence value in the corresponding second preset sliding window is obtained to obtain a second rod body load set, and the standard deviation of the second rod body load set is calculated; the standard deviation is respectively deviated from the second preset percentage, Obtain the upper bound of the standard deviation of the rod body load and the lower bound of the standard deviation of the rod body load corresponding to each sequence value; combine all the sequence values in the cumulative elongation sequence of the rod body and their corresponding upper bound of the standard deviation of the rod body load standard deviation and the lower bound of the standard deviation of the rod body load as the target dataset.

In one of the embodiments, the preset algorithm also includes a confidence interval algorithm; the above-mentioned data processing module 402 is further used for:

Obtain the Z value based on the preset reliability level; for each sequence value in the cumulative elongation sequence of the rod body, calculate the upper bound of the confidence interval of the rod body load corresponding to each sequence value based on the Z value and the standard deviation and the lower bound of the rod load confidence interval; all sequence values in the rod cumulative elongation sequence and their corresponding rod load confidence interval upper bounds and rod load confidence interval lower bounds are used as the target data set.

In one of the embodiments, the preset algorithm includes a maximum and minimum value algorithm; the above-mentioned data processing module 402 is further used for:

Sorting the pretreated cumulative elongation of rods in ascending order to obtain a sequence of cumulative elongation of rods; for each sequence value in the cumulative elongation of rods, obtaining The rod body load corresponding to each sequence value in the adjacent third preset sliding window is obtained to obtain a third rod body load set, and the maximum value of the rod body load and the minimum value of the rod body load in the third rod body load set are calculated; All sequence values in the elongation sequence and their corresponding maximum rod load and minimum rod load are used as the set of target values.

In one of the embodiments, the preset algorithm includes a quantile algorithm; the above-mentioned data processing module 402 is further used for:

Sorting the pretreated cumulative elongation of rods in ascending order to obtain a sequence of cumulative elongation of rods; for each sequence value in the cumulative elongation of rods, use the fourth preset slide window, select sub-windows sequentially on the cumulative elongation sequence of the rod body; calculate the maximum value of the rod body load and the minimum value of the rod body load in each sub-window; The maximum value of the rod load and the minimum value of the rod load are used as the set of target values.

In one of the embodiments, as shown in FIG. 5 , a bolt type selection device is provided, including: a formation condition data acquisition module 501, a roadway excavation scheme design module 502, and a bolt characteristic parameter determination module 503, wherein,

The stratum condition data acquisition module 501 is used to acquire the occurrence characteristic data of the coal mine strata;

The roadway excavation scheme design module 502 is used to determine the bolting scheme of the roadway according to the occurrence characteristic data and the roadway excavation scheme, using the corresponding support design method; Including the dynamic parameter requirements of the bolt;

The bolt characteristic parameter determination module 503 is used to match the dynamic parameter requirements of the bolt with the dynamic load response characteristic curve of the bolt obtained by applying the above-mentioned characterization method of the dynamic load response characteristic of the bolt, and determine the bolt according to the matching result The best characteristic parameters, so as to complete the selection of the bolt.

FIG. 6 illustrates a schematic diagram of the physical structure of an electronic device. As shown in FIG. 6, the electronic device may include: a processor (processor) 610, a communication interface (Communications Interface) 620, a memory (memory) 630 and a communication bus 640, Wherein, the processor 610 , the communication interface 620 , and the memory 630 communicate with each other through the communication bus 640 . The processor 610 can call the logic instructions in the memory 630 to execute the method for characterizing the dynamic load response characteristics of the bolt. The method includes: obtaining a preprocessed test data set; the preprocessed test data set includes In the process of multiple impacts or multiple impacts until fracture, the collected rod load and cumulative elongation of the anchor rod in each impact; the pre-processed rod load and the cumulative elongation of the rod are calculated by the preset algorithm to obtain The target data set; wherein, the preset algorithm includes at least one of the moving average algorithm, standard deviation algorithm, confidence interval algorithm, maximum and minimum algorithm and quantile algorithm; the cumulative elongation of the rod is the abscissa, and the rod body The load is the ordinate, and the target curve corresponding to the target data set is drawn; the target curve includes an upper envelope, a lower envelope, and a median line.

In addition, the logic instructions in the above-mentioned memory 630 may be implemented in the form of software functional units and when sold or used as an independent product, may be stored in a computer-readable storage medium. Based on this understanding, the essence of the technical solution of the present invention or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program codes. .

On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can Perform the characterization method or bolt type selection method of the dynamic load response characteristics of the anchor provided by the above methods. The characterization method of the dynamic load response characteristics of the anchor includes: obtaining the preprocessed test data set; the preprocessed test data The collection includes the rod body load and the cumulative elongation of the rod body in each impact collected during the process of the bolt being subjected to one or more impacts until it breaks; The elongation is calculated to obtain the target data set; wherein, the preset algorithm includes at least one of the moving average algorithm, the standard deviation algorithm, the confidence interval algorithm, the maximum and minimum value algorithm, and the quantile algorithm; The quantity is the abscissa, and the rod load is the ordinate, and the target curve corresponding to the target data set is obtained by drawing; the target curve is the dynamic load response characteristic curve of the bolt, and the dynamic load response characteristic curve includes an upper envelope, a lower envelope line and median line. The bolt type selection method includes: obtaining stratum condition data; matching the stratum condition data with the dynamic load response characteristic curve of the bolt obtained by applying the characterization method of the dynamic load response characteristic of the anchor bolt, and determining the anchor bolt according to the matching result. Characteristic parameters of the rod.

In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it is implemented to perform the characterization of the dynamic load response characteristics of the bolt provided by the above-mentioned methods. method or bolt type selection method, the characterization method of the dynamic load response characteristics of the bolt includes: obtaining the preprocessed test data set; Among them, the rod body load and the cumulative elongation of the bolt in each impact are collected; the preprocessed rod load and the cumulative elongation of the rod are calculated by the preset algorithm to obtain the target data set; among them, the preset The algorithm includes at least one of the moving average algorithm, the standard deviation algorithm, the confidence interval algorithm, the maximum and minimum value algorithm and the quantile algorithm; the cumulative elongation of the rod body is taken as the abscissa, and the rod load is used as the ordinate to draw the target The target curve corresponding to the data set; the target curve is the dynamic load response characteristic curve of the bolt, and the dynamic load response characteristic curve includes an upper envelope, a lower envelope and a median line. The bolt type selection method includes: obtaining stratum condition data; matching the stratum condition data with the dynamic load response characteristic curve of the bolt obtained by applying the characterization method of the dynamic load response characteristic of the anchor bolt, and determining the anchor bolt according to the matching result. Characteristic parameters of the rod.

The device embodiments described above are only illustrative, and the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in One place, or it can be distributed to multiple network elements. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. It can be understood and implemented by those skilled in the art without any creative effort.

Through the above description of the implementations, those skilled in the art can clearly understand that each implementation can be implemented by means of software plus a necessary general-purpose hardware platform, and of course also by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the prior art can be embodied in the form of software products, and the computer software products can be stored in computer-readable storage media, such as ROM/RAM, magnetic discs, optical discs, etc., including several instructions to make a computer device (which may be a personal computer, server, or network device, etc.) execute the methods described in various embodiments or some parts of the embodiments.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: it can still be Modifications are made to the technical solutions described in the foregoing embodiments, or equivalent replacements are made to some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims (10)

1. A characterization method for dynamic load response characteristics of anchor bolts, characterized in that, comprising: Obtain a preprocessed test data set; the preprocessed test data set includes the rod body load, rod body load, and Cumulative elongation; Calculate the preprocessed rod body load and the cumulative elongation of the rod body through a preset algorithm to obtain a target data set; wherein the preset algorithm includes a moving average algorithm, a standard deviation algorithm, a confidence interval algorithm, At least one of the max-min algorithm and the quantile algorithm; Taking the cumulative elongation of the rod body as the abscissa and the rod body load as the ordinate, draw the target curve corresponding to the target data set; the target curve is the dynamic load response characteristic curve of the anchor rod, and the dynamic load response characteristic curve is Including upper envelope, lower envelope and median line. 2. the characterization method of bolt dynamic load response characteristic according to claim 1, is characterized in that, described preset algorithm comprises moving average algorithm; The cumulative elongation of the rod body is calculated to obtain the target data set, including: Sorting the cumulative elongation of the pretreated rods in ascending order to obtain a sequence of cumulative elongation of the rods; For each sequence value in the cumulative elongation sequence of the rod, obtain the rod load corresponding to each sequence value in the first preset sliding window corresponding to the sequence value, obtain the first rod load set, and calculate the second The average value of a set of rod loads; Deviate the average value from the preset percentage respectively to obtain the upper bound of the average value of the rod body load and the lower bound of the average value of the rod body load corresponding to each sequence value; All sequence values in the accumulative elongation sequence of the rod body and their corresponding upper bound and lower bound of the average load value of the rod body are used as the target data set. 3. the characterization method of bolt dynamic load response characteristic according to claim 1, is characterized in that, described preset algorithm comprises standard deviation algorithm; Calculate the cumulative elongation of the above-mentioned rod body to obtain the target data set, including: Sorting the cumulative elongation of the pretreated rods in ascending order to obtain a sequence of cumulative elongation of the rods; For each sequence value in the cumulative elongation sequence of the rod, obtain the rod load corresponding to each sequence value in the second preset sliding window corresponding to the sequence value, obtain a second rod load set, and calculate the first The standard deviation of the set of two rod loads; Deviate the standard deviation up and down by the second preset percentage respectively to obtain the upper bound of the standard deviation of the rod body load and the lower bound of the standard deviation of the rod body load corresponding to each sequence value; All sequence values in the cumulative elongation sequence of the rod body and their corresponding upper bounds of the standard deviation of the rod body load and lower bounds of the standard deviation of the rod body load are used as the target data set. 4. the characterization method of bolt dynamic load response characteristic according to claim 3, it is characterized in that, described preset algorithm also comprises confidence interval algorithm; Described bar body load after described pretreatment by preset algorithm, The cumulative elongation of the rod body is calculated to obtain the target data set, including: Get the Z value based on the preset reliability level; For each sequence value in the cumulative elongation sequence of the rod body, the upper bound of the rod body load confidence interval and the lower bound of the rod body load confidence interval corresponding to each sequence value are calculated based on the Z value and the standard deviation; All sequence values in the cumulative elongation sequence of the rod body and their corresponding upper bound of the confidence interval of the rod body load and lower bound of the confidence interval of the rod body load are taken as the target data set. 5. the characterization method of bolt dynamic load response characteristic according to claim 1, it is characterized in that, described preset algorithm comprises maximum and minimum value algorithm; Described bar body load after described pretreatment by preset algorithm, The cumulative elongation of the rod body is calculated to obtain the target data set, including: Sorting the cumulative elongation of the pretreated rods in ascending order to obtain a sequence of cumulative elongation of the rods; For each sequence value in the cumulative elongation sequence of the rod, obtain the rod load corresponding to each sequence value in the third preset sliding window adjacent to the sequence value, obtain a third rod load set, and calculate the The maximum value of the rod load and the minimum value of the rod load in the third rod load set; All sequence values in the cumulative elongation sequence of the rod body and their corresponding maximum rod load values and minimum rod load values are taken as the target value set. 6. the characterizing method of bolt dynamic load response characteristic according to claim 1, it is characterized in that, described preset algorithm comprises quantile algorithm; Described bar body load after described pretreatment by preset algorithm, The cumulative elongation of the rod body is calculated to obtain the target data set, including: Sorting the cumulative elongation of the pretreated rods in ascending order to obtain a sequence of cumulative elongation of the rods; For each sequence value in the cumulative elongation sequence of the rod body, use the fourth preset sliding window to sequentially select sub-windows on the cumulative elongation sequence of the rod body; Calculate the maximum value of the rod load and the minimum value of the rod load in each sub-window; All sequence values in the cumulative elongation sequence of the rod body and their corresponding maximum rod load values and minimum rod load values are taken as the target value set. 7. A bolt type selection method is characterized in that, comprising: Obtain the occurrence characteristic data of coal mine strata; Design the roadway excavation plan for the roadway section according to the project needs; According to the occurrence characteristic data and the roadway excavation scheme, adopt the corresponding support design method to determine the bolting scheme of the roadway; the bolting scheme includes the dynamic parameter requirements of the bolt; Match the dynamic parameter requirements of the bolt with the dynamic load response characteristic curve of the bolt obtained by applying the characterization method of the dynamic load response characteristic of the bolt as claimed in claims 1 to 6, and determine the optimum value of the bolt according to the matching result. The optimal characteristic parameters are used to complete the selection of anchor rods. 8. A characterization device for dynamic load response characteristics of a bolt, characterized in that the device comprises: The data acquisition module is used to acquire the preprocessed test data set; the preprocessed test data set includes the anchor in each impact collected during the process of the anchor being subjected to one or more impacts until it breaks. Rod body load, rod body cumulative elongation; The data processing module is used to calculate the preprocessed rod body load and the cumulative elongation of the rod body through a preset algorithm to obtain a target data set; wherein the preset algorithm includes a moving average algorithm, a standard deviation At least one of algorithm, confidence interval algorithm, max-min algorithm and quantile algorithm; The curve drawing module takes the cumulative elongation of the rod as the abscissa and the load of the rod as the ordinate to draw the target curve corresponding to the target data set; the target curve is the dynamic load response characteristic curve of the anchor rod, and the dynamic The load response characteristic curve includes an upper envelope, a lower envelope and a median line. 9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and operable on the processor, wherein the processor according to claim 1 is implemented when executing the program. The characterization method of the dynamic load response characteristics of the bolt according to any one of the above to 6 or the type selection method of the bolt according to claim 7. 10. A non-transitory computer-readable storage medium, on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the dynamic load response of the bolt as described in any one of claims 1 to 6 is realized The characterization method of the feature or the bolt type selection method as claimed in claim 7.