阅读说明：本技术 一种基于声发射信号统计分析的岩石破裂预警方法 (Rock fracture early warning method based on acoustic emission signal statistical analysis ) 是由 张正虎 马克 李迎春 胡李华 马天辉 唐春安 于 2020-11-17 设计创作，主要内容包括：一种基于声发射信号统计分析的岩石破裂预警方法,属于岩石力学与岩土工程领域。首先,对岩石变形破坏过程进行实时声发射监测,记录并获取振铃计数。其次,通过公式计算振铃计数的特征统计量,包括方差和自相关系数,并计算振铃计数的方差和自相关系数的变化率。最后,根据振铃计数的方差和自相关系数的变化率进行预警信号判别。当变化率大于阈值时,系统自动报警,说明岩石即将破裂。如果没有超过阀值,继续监测与判别。本发明的预警方法中,预警信号点易识别和计算稳定,能够确保预警方法的客观性和准确性；计算过程简单,操作简便；可实时跟踪预警,可以在水利水电、交通运输、矿产资源开采、地下空间开发等工程领域的岩石破坏预警中广泛应用。(A rock fracture early warning method based on acoustic emission signal statistical analysis belongs to the field of rock mechanics and geotechnical engineering. Firstly, real-time acoustic emission monitoring is carried out on the deformation and damage process of the rock, and ringing count is recorded and obtained. Secondly, calculating the feature statistics of the ringing count including the variance and the autocorrelation coefficient by a formula, and calculating the variance of the ringing count and the rate of change of the autocorrelation coefficient. And finally, judging the early warning signal according to the variance of the ringing count and the change rate of the autocorrelation coefficient. When the change rate is larger than the threshold value, the system automatically alarms, and the rock is about to break. And if the threshold value is not exceeded, continuing monitoring and judging. In the early warning method, the early warning signal points are easy to identify and stable to calculate, and the objectivity and the accuracy of the early warning method can be ensured; the calculation process is simple, and the operation is simple and convenient; the early warning system can track and early warn in real time, and can be widely applied to rock damage early warning in the engineering fields of water conservancy and hydropower, transportation, mineral resource exploitation, underground space development and the like.)

1. A rock fracture early warning method based on acoustic emission signal statistical analysis is characterized by comprising the following steps:

firstly, carrying out acoustic emission monitoring on a rock deformation and damage process, and recording and acquiring a ringing count of an acoustic emission signal in real time;

secondly, calculating characteristic statistics of ringing count of the acoustic emission signals, including variance and autocorrelation coefficients;

the variance (D) is calculated using the following equation:

in the formula, x_iRepresenting an acoustic emission signal ringing count;an average value representing the ringing count of the acoustic emission signal over a window length; n represents oneThe number of acoustic emission signals in a data sample, corresponding to the window length, is typically taken to be 50-200; s represents a standard deviation;

the autocorrelation coefficient (R) is calculated as follows:

wherein k represents a hysteresis step;

thirdly, calculating the variance of the ringing count of the acoustic emission signal and the change rate of the autocorrelation coefficient; the calculation is as follows:

rate of change of variance with timeCalculated by the following formula:

in the formula, t_m+1Representing the average value of the time corresponding to the acoustic emission signal within the (m + 1) th window length; t is t_mRepresenting the average value of the time corresponding to the acoustic emission signal in the mth window length; d_m+1And D_mThe variances of the ringing counts of the acoustic emission signals representing the m +1 th and m window lengths, respectively; the size of m depends on the quantity of acoustic emission signals released in the rock deformation and damage process;

rate of change of autocorrelation coefficientCalculated by the following formula:

in the formula, R_m+1And R_mAutocorrelation coefficients representing ringing counts of the acoustic emission signal for the (m + 1) th and m-th window lengths, respectively;

fourthly, rolling judgment is carried out on the early warning signal according to the variance of the ringing count of the acoustic emission signal and the change rate of the autocorrelation coefficient, and the specific mode is as follows:

setting a variance change rate threshold value and an autocorrelation coefficient change rate threshold value, wherein the smaller the set threshold value is, the earlier the automatic early warning is, and the more the automatic early warning is in favor of safety; the automatic alarm by adopting the set threshold value can adopt two modes: firstly, when the variance change rate exceeds a variance change rate threshold value or the autocorrelation coefficient change rate exceeds an autocorrelation coefficient change rate threshold value, the system automatically alarms; secondly, when the variance change rate exceeds a variance change rate threshold value and the autocorrelation coefficient change rate exceeds an autocorrelation coefficient change rate threshold value, the system automatically alarms; the user can select a proper mode according to actual requirements; and if the variance change rate or the autocorrelation coefficient change rate does not exceed the corresponding threshold value, continuing monitoring and judging.

2. The method for rock fracture early warning based on acoustic emission signal statistical analysis as claimed in claim 1, wherein in the fourth step, the rolling discrimination of the early warning signal can be performed by the following method: the variance of the ringing count of the acoustic emission signal and the change rate of the autocorrelation coefficient can be calculated in real time through the formulas (3) and (4); and (3) drawing a relation curve between the variance change rate or the autocorrelation coefficient change rate and time by taking the time as a horizontal axis and the variance change rate or the autocorrelation coefficient change rate as a vertical axis, and immediately giving an early warning when obvious violent fluctuation occurs to indicate that the rock is about to break.

3. The method as claimed in claim 1, wherein in the fourth step, the variance change rate threshold is 2000-8000 and the autocorrelation coefficient change rate threshold is 0.1-0.3.

Technical Field

The invention belongs to the field of rock mechanics and geotechnical engineering, and relates to a rock fracture early warning method based on acoustic emission signal statistical analysis, which is suitable for rock fracture forecast and early warning in civil engineering, hydraulic and hydroelectric engineering, mineral engineering and traffic engineering.

Background

With the continuous promotion of mining, tunnel excavation, hydraulic engineering construction and underground space development and utilization, rock mass occurrence geological conditions related to engineering construction and operation are more complex, and engineering stability evaluation is very important. Rock fracture can cause a series of geological disasters such as landslide, rock burst, collapse, large tunnel deformation and the like, and seriously threatens the safety and the service life of engineering. Therefore, the research on rock cracking precursor information and the early warning technology has important significance.

At present, rock destruction is accompanied by phenomena such as increased deformation, increased acoustic emission signals and the like, so that the sites are often used for representing the destruction behavior of the rock. Since rock is a typical heterogeneous brittle material and deformation before damage is not obvious, early warning by adopting deformation and change rate thereof is very difficult. The acoustic emission signals are increased when the rock is damaged, the acoustic emission signals can be directly used as precursor signals of the rock damage through the obvious increase of the acoustic emission quantity and the release rate, and the defect that early warning signal points are difficult to accurately identify exists. And the acoustic emission signals reflect the local strain energy release process of the rock, but do not play a key role in the macroscopic damage of the rock. In view of this, many researchers have studied to perform rock destruction warning by using changes of parameters such as b-value, frequency spectrum, spatial correlation length, fractal dimension, etc., but the changes of these parameters are not significant, and it is difficult to determine warning signal points in actual operation. Due to the complexity of rock destruction and the limitations of research means, no very effective rock fracture warning technology or method has been developed.

Therefore, the invention provides a rock fracture early warning method based on acoustic emission signal statistical analysis to meet the engineering requirements of easy identification, objectivity and effectiveness of early warning signal points and facilitate real-time tracking, early warning and forecasting.

Disclosure of Invention

In order to solve the problems, the invention provides a rock fracture early warning method based on acoustic emission signal statistical analysis, and the method has the advantages of real-time high efficiency and simple and convenient operation.

In order to achieve the purpose, the invention is realized by the following technical scheme:

a rock fracture early warning method based on acoustic emission signal statistical analysis comprises the following steps:

firstly, carrying out acoustic emission monitoring on the deformation and damage process of the rock, and recording and acquiring the ringing count of an acoustic emission signal in real time.

Second, feature statistics, including variance and autocorrelation coefficients, are calculated for the ring count of the acoustic emission signal.

The variance (D) is calculated using the following equation:

in the formula, x_iRepresenting an acoustic emission signal ringing count;an average value representing the ringing count of the acoustic emission signal over a window length; n represents the number of acoustic emission signals in a data sample, corresponding to the window length, typically taken to be 50-200; s represents a standard deviation.

The autocorrelation coefficient (R) is calculated as follows:

in the formula, k represents a hysteresis step.

And thirdly, calculating the variance of the ringing count of the acoustic emission signal and the change rate of the autocorrelation coefficient. The calculation is as follows:

rate of change of variance with timeCalculated by the following formula:

in the formula, t_m+1Representing the average value of the time corresponding to the acoustic emission signal within the (m + 1) th window length; t is t_mRepresenting the average value of the time corresponding to the acoustic emission signal in the mth window length; d_m+1And D_mThe variances of the acoustic emission signal ringing counts for the m +1 th and m window lengths, respectively, are represented. The size of m depends on the number of acoustic emission signals released during the rock deformation failure.

Rate of change of autocorrelation coefficientCalculated by the following formula:

in the formula, R_m+1And R_mAnd the autocorrelation coefficients of the ringing counts of the acoustic emission signals of the (m + 1) th window length and the (m) th window length are respectively represented.

Fourthly, rolling judgment is carried out on the early warning signal according to the variance of the ringing count of the acoustic emission signal and the change rate of the autocorrelation coefficient, and the specific mode is as follows:

the first discrimination method is as follows: the variance of the ringing count of the acoustic emission signal and the change rate of the autocorrelation coefficient can be calculated in real time through the formulas (3) and (4). And (3) drawing a relation curve between the variance change rate or the autocorrelation coefficient change rate and time by taking the time as a horizontal axis and the variance change rate or the autocorrelation coefficient change rate as a vertical axis, and immediately giving an early warning when obvious violent fluctuation occurs to indicate that the rock is about to break.

The second discrimination method is: or setting a variance change rate threshold and an autocorrelation coefficient change rate threshold without drawing, wherein the recommended value of the variance change rate threshold is 2000-8000, and the recommended value of the autocorrelation coefficient change rate threshold is 0.1-0.3. The smaller the set threshold value is, the earlier the automatic early warning is, and the more the safety is biased. The automatic alarm by adopting the set threshold value can adopt two modes: firstly, when the variance change rate exceeds a variance change rate threshold value or the autocorrelation coefficient change rate exceeds an autocorrelation coefficient change rate threshold value, the system automatically alarms; second, the system automatically alarms when the rate of change of variance exceeds a variance rate threshold and the rate of change of autocorrelation coefficients exceeds an autocorrelation coefficient rate threshold. The first mode has earlier automatic early warning time than the second mode and is more safe. The user can select a proper mode according to actual requirements. And if the variance change rate or the autocorrelation coefficient change rate does not exceed the corresponding threshold value, continuing monitoring and judging.

The invention has the beneficial effects that: (1) the early warning signal points are easy to identify and stable to calculate, and the objectivity and accuracy of the early warning method are ensured; (2) the calculation process is simple, and the operation is simple and convenient; (3) the early warning system can track and early warn in real time, and can be widely applied to rock damage early warning in the engineering fields of water conservancy and hydropower, transportation, mineral resource exploitation, underground space development and the like.

Drawings

FIG. 1 is a schematic flow chart of a rock fracture warning method based on acoustic emission signal statistical analysis according to the present invention;

FIG. 2 is a graph of acoustic emission ringing count during rock deformation failure under uniaxial compressive load;

FIG. 3 is a graph of variance and autocorrelation coefficient of acoustic emission ringing counts during rock deformation failure under uniaxial compressive loading; (a) is the variance; (b) is an autocorrelation coefficient;

FIG. 4 is a graph of variance and autocorrelation coefficient change rate of acoustic emission ringing counts during rock deformation failure under uniaxial compressive load; (a) is the rate of variance change; (b) is the rate of change of the autocorrelation coefficient.

Detailed Description

In order to further explain the technical scheme of the invention, the invention is explained in detail by combining the attached drawings and the embodiment.

As shown in fig. 1, a method for rock fracture early warning based on acoustic emission signal statistical analysis includes the following steps:

(1) and (4) carrying out real-time acoustic emission monitoring on the rock deformation and damage process, and automatically recording and acquiring an acoustic emission ringing count. In this embodiment, acoustic emission monitoring is performed on the deformation and damage process of granite under the action of uniaxial compression load, and the relationship curve of the acoustic emission ringing count along with the loading time is shown in fig. 2.

(2) And calculating the variance and autocorrelation coefficient of the acoustic emission ringing counting sequence. In this embodiment, the window length (n) is set to 100, and the hysteresis step (k) is set to 50. In the actual operation process, the window length and the hysteresis step length can be changed, and can be set according to the release quantity of the acoustic emission signals, as long as a good statistical effect is ensured. As the loading time progresses, the variance and autocorrelation coefficients of the acoustic emission ringing count sequence within each window length are calculated according to equations (1) and (2). The variance and autocorrelation coefficient curves of this embodiment are shown in fig. 3.

(3) The variance of the ringing count and the rate of change of the autocorrelation coefficient are calculated. The variance of the acoustic emission ringing count sequence and the rate of change of the autocorrelation coefficients within each window length are calculated according to equations (3) and (4). The variance and the rate of change of the autocorrelation coefficient with load time for this embodiment are shown in fig. 4.

(4) And judging the early warning signal according to the variance of the ringing count and the change rate of the autocorrelation coefficient. When the change rate is larger than the threshold value, the system automatically alarms, and the rock is about to break. And if the threshold value is not exceeded, continuing monitoring and judging. In this embodiment, the threshold value of the variance change rate is set to 5000, and the threshold value of the autocorrelation coefficient change rate is set to 0.1. Beyond these two thresholds, the system automatically warns. As shown in fig. 4, the rate of change of variance exceeds the threshold at 478.83s and the rate of change of autocorrelation coefficient exceeds the threshold at 481.33 s. When a first automatic early warning mode is adopted, namely, if one of the variance change rate and the autocorrelation coefficient change rate exceeds the threshold value, an automatic alarm is given, and the early warning signal point is 478.83 s; when the second automatic early warning mode is adopted, namely the variance change rate and the autocorrelation coefficient change rate exceed corresponding threshold values, the automatic early warning mode automatically gives an alarm, and the early warning signal point is 481.33 s. It can be seen that the first automatic early warning manner is more conservative than the second early warning manner. The granite damage time is 624.32s, and the early warning and forecast of rock fracture are realized through the method.

The above-mentioned embodiments only express the embodiments of the present invention, but not should be understood as the limitation of the scope of the invention patent, it should be noted that, for those skilled in the art, many variations and modifications can be made without departing from the concept of the present invention, and these all fall into the protection scope of the present invention.