Method and device for determining deformation of surrounding rock and surrounding rock deformation detection system

Abstract

The application provides a surrounding rock deformation determination method and device and a surrounding rock deformation detection system. The method comprises the following steps: performing data fusion on multiple optical fiber data to obtain fused optical fiber data; and determining whether the surrounding rock of a coal mine tunnel is deformed according to at least the fused optical fiber data, and determining the deformation degree of the surrounding rock of the coal mine tunnel in the case that the surrounding rock of the coal mine tunnel is deformed. In the scheme, the optical fiber sensor is used to obtain the optical fiber data, which can effectively avoid vibration interference caused by vehicle passing, drilling construction and the like, and the multiple optical fiber data is fused to obtain the fused optical fiber data. Since the fused optical fiber data is the optical fiber data collected by the optical fiber sensors of multiple measuring points, the reliability of the fused optical fiber data is high, the fused optical fiber data can better reflect the deformation of the surrounding rock, and thus it can be ensured that the deformation of the surrounding rock can be accurately determined, and the deformation degree of the surrounding rock can be accurately determined in the case that the surrounding rock is deformed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of surrounding rock deformation detection, in particular to a surrounding rock deformation determination method and device, a computer readable storage medium and a surrounding rock deformation detection system. BACKGROUND

[0002] The exploitation and utilization of coal resources have greatly promoted the development of the national economy. According to incomplete statistics, coal resources still account for about 57% of primary energy consumption, and will remain the main energy source for a long time to come. During the process of underground coal mining, due to the loading and unloading effect caused by the advance of the coal mining face, the stress of the surrounding rock mass is redistributed, and roadway collapse, roof falling and rib spalling often occur, which seriously affects the safety production of the mine and threatens the safety of the workers, and also increases the maintenance cost in the later period.

[0003] In order to ensure the safe operation of coal mining, it is of great significance to determine the deformation law of the surrounding rock of the roadway. However, in the current scheme, the accuracy of the surrounding rock deformation detection of the roadway is low. SUMMARY

[0004] The main purpose of the present application is to provide a surrounding rock deformation determination method and device, a computer readable storage medium and a surrounding rock deformation detection system, so as to at least solve the problem of low accuracy of the surrounding rock deformation detection of the roadway in the prior art.

[0005] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a surrounding rock deformation determination method is provided, comprising: acquiring a plurality of optical fiber data, wherein the optical fiber data is the data of the optical signal collected by the optical fiber sensor, the optical fiber data is used to represent the intensity of the spectrum reflected by the surrounding rock of the coal mine roadway, a plurality of optical fiber sensors are distributedly installed in the coal mine roadway, and one optical fiber data corresponds to one optical fiber sensor; data fusion is performed on a plurality of optical fiber data to obtain fused optical fiber data, wherein the fused optical fiber data is used to represent the stress change of the surrounding rock of the coal mine roadway; at least according to the fused optical fiber data, it is determined whether the surrounding rock of the coal mine roadway has deformed, and in the case that the surrounding rock of the coal mine roadway has deformed, the deformation degree of the surrounding rock of the coal mine roadway is determined.

[0006] Optionally, the data fusion of a plurality of optical fiber data to obtain fused optical fiber data comprises: acquiring a first weight coefficient, wherein the first weight coefficient is used to represent the importance of one optical fiber data in the fused optical fiber data, and the first weight coefficient is obtained according to the cross-correlation of the target optical fiber data and any one non-target optical fiber data; the product sum of each optical fiber data and the first weight coefficient is used to obtain the fused optical fiber data.

[0007] Optionally, the first weight coefficient is obtained by calculating all target cross-correlation data, the target cross-correlation data being a cross-correlation coefficient of the target fiber data and any one of the non-target fiber data; and calculating a sum of all the target cross-correlation data to obtain the first weight coefficient.

[0008] Optionally, the deformation of the surrounding rock of the coal mine tunnel is determined according to at least the fused fiber data, and in the case that the deformation of the surrounding rock of the coal mine tunnel occurs, the deformation degree of the surrounding rock of the coal mine tunnel is determined, including: obtaining a second weight coefficient, wherein the second weight coefficient is used to represent the importance of one of the fiber sensors in the plurality of fiber sensors, and the second weight coefficient is determined according to a factor parameter, the factor parameter including at least one of the following: position, stability, working environment, the importance of the fiber sensor located at an important position in the coal mine tunnel is higher than that of the fiber sensor outside the important position in the coal mine tunnel, and the important position includes at least one of the following: the position of the roof center of the coal mine tunnel, the position of the intersection of the roof and the wall of the coal mine tunnel; obtaining a preset threshold value, wherein the preset threshold value is calculated according to historical first weight coefficients, historical second weight coefficients and historical fused fiber data; obtaining a current to-be-detected value according to a current first weight coefficient, a current second weight coefficient and a current fused fiber data; comparing the size relationship between the preset threshold value and the current to-be-detected value; in the case that the preset threshold value and the current to-be-detected value are the same, it is determined that the surrounding rock of the coal mine tunnel does not deform; in the case that the preset threshold value and the current to-be-detected value are not the same, and the difference between the preset threshold value and the current to-be-detected value is less than a difference threshold value, it is determined that the surrounding rock of the coal mine tunnel deforms, and the deformation degree is determined as a first deformation degree; in the case that the preset threshold value and the current to-be-detected value are not the same, and the difference between the preset threshold value and the current to-be-detected value is greater than or equal to the difference threshold value, it is determined that the surrounding rock of the coal mine tunnel deforms, and the deformation degree is determined as a second deformation degree, wherein the first deformation degree is less than the second deformation degree.

[0009] Optionally, the second weight coefficient is obtained by: constructing a target model, wherein the target model comprises a target layer, a criterion layer and a scheme layer, the target layer is the selected optical fiber sensor, the criterion layer is the factor parameter of each optical fiber sensor, and the scheme layer is a plurality of optical fiber sensors; constructing a target matrix, wherein an element in the target matrix is an importance degree of a target optical fiber sensor relative to a non-optical fiber sensor, and the importance degree of the target optical fiber sensor relative to the non-optical fiber sensor is obtained according to a correlation measurement scale table; determining a first weight value of each factor parameter in the criterion layer according to the target matrix, and determining a second weight value of each optical fiber sensor in the scheme layer under the influence of each factor parameter in the criterion layer according to the target matrix; and calculating a second product of the first weight value and the second weight value to obtain the second weight coefficient.

[0010] Optionally, the preset threshold is obtained by: determining the preset threshold according to a target formula wherein HI represents the preset threshold, n represents the number of optical fiber sensors in a historical time period, ω Bi represents the historical second weight coefficient, D x represents the historical first weight coefficient, represents an average value of a plurality of historical fusion optical fiber data under a condition that the surrounding rock of the coal mine tunnel does not deform.

[0011] Optionally, the optical fiber data is obtained by: obtaining original optical fiber data, wherein the original optical fiber data is original data of an optical signal collected by the optical fiber sensor; and preprocessing the original optical fiber data to obtain the optical fiber data, wherein the preprocessing comprises at least one of downsampling, noise reduction and partial data extraction.

[0012] According to another aspect of the present application, a surrounding rock deformation determination device is provided, comprising: an acquisition unit configured to acquire a plurality of optical fiber data, wherein the optical fiber data is data of an optical signal collected by an optical fiber sensor, and the optical fiber data is used to represent the intensity of the spectrum reflected by the surrounding rock of a coal mine tunnel, a plurality of optical fiber sensors are distributedly installed in the coal mine tunnel, and one optical fiber data corresponds to one optical fiber sensor; a fusion unit configured to perform data fusion on the plurality of optical fiber data to obtain fusion optical fiber data, wherein the fusion optical fiber data is used to represent the stress change of the surrounding rock of the coal mine tunnel; and a determination unit configured to determine whether the surrounding rock of the coal mine tunnel deforms according to at least the fusion optical fiber data, and determine the deformation degree of the surrounding rock of the coal mine tunnel in the case that the surrounding rock of the coal mine tunnel deforms.

[0013] According to still another aspect of the present application, a computer readable storage medium is provided, the computer readable storage medium comprising a stored program, wherein the computer readable storage medium is caused to perform any one of the methods when the program is run.

[0014] According to still another aspect of the present application, a surrounding rock deformation detection system is provided, comprising one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs comprise instructions for performing any one of the methods.

[0015] According to the technical solution of the present application, firstly, a plurality of optical fiber data is acquired, then the plurality of optical fiber data is fused to obtain fused optical fiber data, and finally, at least according to the fused optical fiber data, it is determined whether the surrounding rock of the coal mine tunnel has deformed, and in the case that the surrounding rock of the coal mine tunnel has deformed, the deformation degree of the surrounding rock of the coal mine tunnel is determined. In this scheme, the optical fiber sensor is used to acquire the optical fiber data, which can effectively avoid the vibration interference caused by the passing of vehicles, drilling construction and the like, and the plurality of optical fiber data is fused to obtain the fused optical fiber data. Since the fused optical fiber data is the optical fiber data collected by the optical fiber sensors of a plurality of measuring points, the fused optical fiber data has high reliability, and the fused optical fiber data can better reflect the deformation of the surrounding rock, thereby ensuring that the deformation of the surrounding rock can be accurately determined, and the deformation degree of the surrounding rock can be accurately determined in the case that the surrounding rock has deformed. BRIEF DESCRIPTION OF DRAWINGS

[0016] The drawings accompanying the specification of the present application are used to provide further understanding of the present application, the illustrative embodiments of the present application and the description thereof are used to explain the present application, and do not constitute improper limitations on the present application. In the drawings:

[0017] Figure 1 A hardware structure block diagram of a mobile terminal for performing a surrounding rock deformation determination method according to an embodiment of the present application is shown;

[0018] Figure 2 A flowchart of a surrounding rock deformation determination method according to an embodiment of the present application is shown;

[0019] Figure 3 A schematic diagram of the installation position of the optical fiber sensor is shown;

[0020] Figure 4 A schematic diagram of the reflected spectrum curve collected by the optical fiber sensor is shown;

[0021] Figure 5 A schematic diagram of the stress change curve of the surrounding rock is shown;

[0022] Figure 6 A flowchart of another method for determining deformation of surrounding rock is shown.

[0023] Figure 7 A structural block diagram of a device for determining deformation of surrounding rock according to an embodiment of the present application is shown.

[0024] Wherein, the above figures include the following reference signs:

[0025] 102, processor; 104, memory; 106, transmission device; 108, input and output device; 10, optical fiber sensor; 11, roadway roof; 12, roadway wall; 13, optical fiber sensor demodulator; 14, coal mine roadway. DETAILED DESCRIPTION

[0026] It should be noted that the embodiments and features in the present application can be combined with each other without conflict. The technical solutions in the embodiments of the present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0027] In order to enable persons skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by persons skilled in the art without creative labor should be within the scope of protection of the present application.

[0028] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily limit to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0029] In order to ensure the safety of coal mining, it is of great significance to effectively and accurately monitor the deformation of roadway surrounding rock, obtain the displacement data of roadway surrounding rock and obtain the deformation law of roadway surrounding rock. In recent years, many scholars at home and abroad have carried out extensive research on the deformation law of roadway, the failure mechanism and control of roadway surrounding rock, and through various technical means, the deformation data of roadway surrounding rock are monitored, and the deformation law of roadway surrounding rock is analyzed to provide theoretical basis and data support for the safety production of coal mining. In some schemes, the equipment for monitoring the deformation of roadway surrounding rock mainly includes total station, borehole stress meter, digital display convergence meter, ultrasonic surrounding rock crack detector and the like. The above measurement technical means can be mainly divided into displacement data acquisition and stress data acquisition according to the type of data acquired, but ultimately the coal mining is the power of rock mass movement, and the external performance result of rock mass movement.

[0030] At present, total station, digital convergence and other measurement means have been widely used in the deformation monitoring or stress monitoring of roadway surrounding rock in coal mine. For example, the borehole stress meter can be arranged in the roadway surrounding rock by drilling, and the stress change in the rock mass is monitored during the mining process. By analyzing the change law of a large amount of stress data, the change characteristics of the stress of roadway surrounding rock are summarized, and the stress concentration area of roadway, the influence distance of advanced mining, the deformation law of roadway and other conclusions are obtained. However, like other conventional measurement methods, this method can only arrange stress meters at several special positions of the roadway, which belongs to "point" observation data, and cannot obtain the displacement field or stress field of the whole roadway. The deformation of the whole monitored object is reflected by the change law of a limited number of points, that is, the error of the "point" instead of "surface" monitoring method is large.

[0031] As introduced in the background art, the accuracy of the deformation detection of roadway surrounding rock in the prior art is low. In order to solve the above problems, the embodiments of the present application provide a determination method, device, computer readable storage medium and surrounding rock deformation detection system.

[0032] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application.

[0033] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking the running on the mobile terminal as an example, Figure 1 is a hardware structure block diagram of a mobile terminal of a determination method of surrounding rock deformation of the embodiments of the present application. As Figure 1 shown, the mobile terminal can include one or more Figure 1The mobile terminal can further include a transmission device 106 for communication function and an input / output device 108. Those skilled in the art can understand that, Figure 1 The structure shown is only schematic and does not limit the structure of the mobile terminal. For example, the mobile terminal can include more or less components than those shown, or have a different configuration or arrangement of the components. Figure 1 The mobile terminal can include more or less components than those shown, or have a different configuration or arrangement of the components. Figure 1 The mobile terminal can include more or less components than those shown, or have a different configuration or arrangement of the components.

[0034] The memory 104 is used for storing computer programs, such as software programs of application software and modules, for example, the computer program corresponding to the device information display method in the embodiments of the present application. The processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, that is, implements the method described above. The memory 104 can include a high-speed random access memory, and can further include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory 104 can further include a memory remotely arranged with respect to the processor 102, and these remote memories can be connected to the mobile terminal through a network. Examples of the network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The transmission device 106 is used for receiving or sending data via a network. The specific examples of the network can include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used for communicating with the Internet in a wireless manner.

[0035] In the embodiments, a method for determining deformation of surrounding rock is provided, which is run on a mobile terminal, a computer terminal or similar computing device. It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0036] Figure 2 FIG. 1 is a flowchart of a method for determining deformation of surrounding rock according to an embodiment of the present application. As shown in the figure, the method includes the following steps: Figure 2 ​

[0037] Step S201, obtain a plurality of optical fiber data, wherein the optical fiber data is the data of the optical signal collected by the optical fiber sensor, the optical fiber data is used to represent the intensity of the spectrum reflected by the surrounding rock of the coal mine roadway, a plurality of optical fiber sensors are distributedly installed in the coal mine roadway, and one optical fiber data corresponds to one optical fiber sensor;

[0038] Specifically, the optical fiber data obtained by the scheme is the data of the optical signal collected by the optical fiber sensor. Since the optical fiber sensor is less disturbed by the vibration caused by the passing of vehicles and drilling construction, the accuracy of subsequent use of the optical fiber data to realize surrounding rock deformation detection is also higher

[0039] Specifically, as shown in Figure 3 The optical fiber sensor 10 can be integrated in the armored sheath in a distributed manner, and is pre-buried in the zigzag shape on the roadway roof 11 and the roadway wall 12, and the optical fiber sensor demodulator 13 is connected to each 3km long optical fiber sensor 10, so as to realize online monitoring of the small strain of the monitored roadway roof and the two side walls. The optical fiber sensor 10 is arranged around the coal mine roadway 14, and the coal mine roadway is below the coal mine floor.

[0040] Specifically, the optical fiber sensor demodulator transmits a pulse light from the distributed optical fiber, and simultaneously receives the echo light reflected from different positions of the distributed optical fiber sensor. The received echo is subjected to spectral analysis, and the spectral waveform of the reflected echo light can be obtained, as shown in Figure 4 The peak position change of the spectral waveform can be used to quantitatively measure the roadway strain change amount of the measured position.

[0041] Specifically, the surrounding rock monitoring of the roof deformation in the coal mine roadway is one of the research focuses of coal mine safety monitoring. The traditional roadway roof deformation is mainly measured by artificial or mechanical roof separation instrument. The technical personnel records the data by using the method of field observation and manual transcription. There are disadvantages such as inconvenient observation, large error, poor real-time data, etc. The scheme can use the optical fiber sensor to automatically detect the intensity of the spectrum reflected by the surrounding rock of the coal mine roadway, improve the automatic monitoring level, and improve the coal mine safety guarantee ability.

[0042] Step S202, data fusion is performed on a plurality of optical fiber data to obtain fused optical fiber data, wherein the fused optical fiber data is used to represent the stress change of the surrounding rock of the coal mine roadway;

[0043] Specifically, the multiple optical fiber data collected by the multiple optical fiber sensors are multiple, and the multiple optical fiber data can be fused to reduce the redundancy of the optical fiber data of different measuring points, avoid the low measurement reliability of the optical fiber sensor of a single measuring point, improve the reliability of the data, and further ensure that the fused optical fiber data has high data quality, so that the deformation of the surrounding rock can be more accurately determined subsequently.

[0044] In step S203, whether the surrounding rock of the coal mine tunnel deforms is determined according to at least the fused optical fiber data, and the deformation degree of the surrounding rock of the coal mine tunnel is determined in the case that the surrounding rock of the coal mine tunnel deforms.

[0045] Specifically, since the fused optical fiber data has high data quality, the accuracy of detecting the deformation of the surrounding rock according to the accurate fused optical fiber data is also high, and not only whether the surrounding rock deforms can be determined, but also the deformation degree of the surrounding rock can be accurately determined.

[0046] According to the embodiment, multiple optical fiber data are first acquired, then the multiple optical fiber data are fused to obtain fused optical fiber data, and finally whether the surrounding rock of the coal mine tunnel deforms is determined according to at least the fused optical fiber data, and the deformation degree of the surrounding rock of the coal mine tunnel is determined in the case that the surrounding rock of the coal mine tunnel deforms. In the scheme, the optical fiber sensor is used to acquire the optical fiber data, which can effectively avoid the vibration interference caused by the passing of vehicles, drilling construction and the like, and the multiple optical fiber data are fused to obtain the fused optical fiber data. Since the fused optical fiber data is fused with the optical fiber data collected by the optical fiber sensors of multiple measuring points, the fused optical fiber data has high reliability, and the fused optical fiber data can well reflect the deformation of the surrounding rock, so that whether the surrounding rock deforms can be accurately determined, and the deformation degree of the surrounding rock can be accurately determined in the case that the surrounding rock deforms.

[0047] In addition, since the optical fiber sensor has the advantages of high measurement accuracy, high measurement sensitivity, convenient and fast measurement and the like, the accuracy of the measured optical fiber data and the fused optical fiber data can be ensured to be high in the scheme, and thus the accuracy of the surrounding rock deformation detection can be ensured to be high.

[0048] The multiple optical fiber data have different influences on the fused optical fiber data, so the weights of the multiple optical fiber data can be limited. In the specific implementation process, the multiple optical fiber data are fused to obtain the fused optical fiber data, which can be realized by the following steps: a first weight coefficient is acquired, wherein the first weight coefficient is used to represent the importance of one optical fiber data in the fused optical fiber data, and the first weight coefficient is obtained according to the cross-correlation between the target optical fiber data and any one non-target optical fiber data; and the fused optical fiber data is obtained according to the sum of the products of each optical fiber data and the first weight coefficient.

[0049] In this scheme, the cross-correlation algorithm can be used to determine the first weight coefficient of different fiber data, which can reduce the redundancy of the fiber data collected by the fiber sensors at different measuring points, and then the fusion can be performed according to each fiber data and the first weight coefficient corresponding to each fiber data, so as to ensure that the fusion efficiency is high, and the accuracy of the fused fiber data is high, thereby further ensuring that the accuracy of detecting the surrounding rock deformation through the fused fiber data is high.

[0050] The first weight coefficient can be calculated according to the cross-correlation fusion algorithm. Since the fiber sensors at different positions have correlation, the first weight coefficient can be determined according to the fiber data collected by the fiber sensors at different positions. In the specific implementation process, the first weight coefficient can be obtained by the following steps: calculating all target cross-correlation data, which is the cross-correlation coefficient of the target fiber data and any one non-target fiber data; calculating the sum of all target cross-correlation data to obtain the first weight coefficient.

[0051] In this scheme, the cross-correlation coefficient of the target fiber data and any one non-target fiber data (target cross-correlation data) can be calculated first, and then the sum of all target cross-correlation data corresponding to the target fiber data is accumulated, so that the first weight coefficient of the fiber data collected by the fiber sensors at different positions can be obtained. The first weight coefficient can reflect the importance of the fiber data collected by the fiber sensors at different positions in the fused fiber data, so as to further reduce the redundancy of the fiber data collected by the fiber sensors at different measuring points.

[0052] Specifically, the fiber data can be represented as x z (k), z represents the number of fiber sensors, k represents the number of fiber data, and the formula for calculating the target cross-correlation data is: wherein E ij represents the target cross-correlation data, R ij is calculated as:

[0053]

[0054] wherein l represents the sliding amount (sliding window), which is obtained according to the convolution operation, and the formula for calculating the first weight coefficient is E i represents the first weight coefficient.

[0055] In another implementation, the sum of the plurality of target cross-correlation data can also be simplified to obtain the ratio between the plurality of target cross-correlation data, and the ratio obtained by simplifying is used as the first weight coefficient, for example: α1:α2:Λ:α zE1:E2:...:E z , a i is a first weight coefficient of the fiber data detected by the i-th fiber sensor.

[0056] In the case where the first weight coefficient is obtained, a formula for calculating the fused fiber data is X = a1x1 + a2x2 +... + a z x z , wherein X represents the fused fiber data.

[0057] In order to further ensure that the detection result of the present scheme is accurate, at least according to the above fused fiber data, the present application determines whether the surrounding rock of the coal mine tunnel deforms, and in the case where the surrounding rock of the coal mine tunnel deforms, determines the deformation degree of the surrounding rock of the coal mine tunnel, which can be achieved by the following steps: obtaining a second weight coefficient, wherein the second weight coefficient is used to represent the importance of one fiber sensor in a plurality of fiber sensors, and the second weight coefficient is determined according to factor parameters, the factor parameters include at least one of the following: position, stability, working environment, the importance of the fiber sensor located in the important position of the coal mine tunnel is higher than that of the fiber sensor outside the important position of the coal mine tunnel, the important position includes at least one of the following: the position of the roof center of the coal mine tunnel, the position of the intersection of the roof and the wall of the coal mine tunnel; obtaining a preset threshold, wherein the preset threshold is calculated according to historical first weight coefficients, historical second weight coefficients and historical fused fiber data; according to the current first weight coefficient, the current second weight coefficient and the current fused fiber data, a current to-be-detected value is calculated; compare the size relationship between the preset threshold and the current to-be-detected value; in the case where the preset threshold and the current to-be-detected value are the same, it is determined that the surrounding rock of the coal mine tunnel does not deform; in the case where the preset threshold and the current to-be-detected value are not the same, and the difference between the preset threshold and the current to-be-detected value is less than the difference threshold, it is determined that the surrounding rock of the coal mine tunnel deforms, and the deformation degree is determined as a first deformation degree; in the case where the preset threshold and the current to-be-detected value are not the same, and the difference between the preset threshold and the current to-be-detected value is greater than or equal to the difference threshold, it is determined that the surrounding rock of the coal mine tunnel deforms, and the deformation degree is determined as a second deformation degree, wherein the first deformation degree is less than the second deformation degree.

[0058] In the scheme, the second weight coefficient of each optical fiber sensor can also be determined, the current to-be-detected value is calculated according to the current first weight coefficient, the second weight coefficient and the current fused optical fiber data, and the preset threshold value is obtained when the surrounding rock of the coal mine tunnel does not deform, so that the current to-be-detected value is directly compared with the preset threshold value, and the difference obtained can be used to accurately determine whether the surrounding rock of the coal mine tunnel deforms, and the size of the deformation can also be determined according to the relationship between the difference and the difference threshold value when the surrounding rock of the coal mine tunnel deforms.

[0059] Specifically, the way of calculating the preset threshold value and calculating the current to-be-detected value can be the same, except that the parameters calculated are different.

[0060] The stress change curve of the surrounding rock is as shown in Figure 5 As can be seen from Figure 5 , the tunnel strain parameters (the current to-be-detected value, the strain in Figure 5 ) calculated by the scheme can reflect the state of the tunnel roof and the two side walls in real time, and the real-time measured strain parameters can provide an effective monitoring means for support failure, roof fall, collapse and other accidents.

[0061] The second weight coefficient of the optical fiber sensor can be obtained by the AHP algorithm. Since the positions of different optical fiber sensors are different, the importance of different optical fiber sensors is also different, and therefore the AHP algorithm is used to construct a pairwise comparison matrix to ensure that the second weight coefficient is relatively accurate. In some embodiments, the second weight coefficient can be obtained by the following steps: constructing a target model, wherein the target model includes a target layer, a criterion layer and a scheme layer, the target layer is the selected optical fiber sensor, the criterion layer is the factor parameter of each optical fiber sensor, and the scheme layer is a plurality of optical fiber sensors; constructing a target matrix, wherein the elements in the target matrix are the importance of the target optical fiber sensor relative to the non-optical fiber sensor, and the importance of the target optical fiber sensor relative to the non-optical fiber sensor is obtained according to a relevant measurement scale table; determining the first weight value of each factor parameter in the criterion layer according to the target matrix, and determining the second weight value of each optical fiber sensor in the scheme layer under the influence of each factor parameter in the criterion layer according to the target matrix; calculating the second product of the first weight value and the second weight value to obtain the second weight coefficient.

[0062] In the scheme, the target model is an AHP algorithm model, and the AHP algorithm can be used to set the second weight coefficient for each optical fiber sensor, construct the target layer, the criterion layer and the scheme layer, and compare the weights between different optical fiber sensors by establishing a pairwise comparison matrix (target matrix), thereby ensuring that the accuracy of the obtained second weight coefficient is relatively high.

[0063] Specifically, the second weight coefficient is calculated as follows:

[0064] The target layer is designed as "selection of optical fiber sensor", the criterion layer is designed as "position of optical fiber sensor", "stability of optical fiber sensor", "working environment of optical fiber sensor", and the scheme layer is designed as "optical fiber sensor 1", "optical fiber sensor 2", …, "optical fiber sensor n";

[0065] The pairwise comparison matrix is established, and the pairwise comparison matrix established by the criterion layer and the scheme layer is obtained according to Table 1,

[0066] Table 1: Related measurement scale table

[0067] Numerical Preferences 1 Equal preference 3 Slightly preferred 5 Moderately preferred 7 Much preferred 9 Very much preferred 2,4,6,8 Intermediate value

[0068] wherein the first weight value of each factor in the criterion layer is The second weight value of each factor in the scheme layer under the influence of each factor Aj (j = 1, 2, …, m) in the criterion layer is Specifically, the square root method formula is:

[0069]

[0070] and the standardization formula is:

[0071]

[0072] The weight vector (first weight value and second weight value) is obtained, and the consistency index CI and the consistency ratio CR of the pairwise comparison matrix established by the criterion layer and the scheme layer are calculated. The CR does not exceed 0.1 to pass the consistency test, otherwise the comparison matrix is redesigned, wherein the formula for calculating the consistency index is:

[0073]

[0074] The formula for calculating the consistency ratio is:

[0075] λ max represents the maximum eigenvalue, n represents the order of the matrix, RI is obtained by Table 2, and depends on the order of the elements in the target matrix,

[0076] Table 2: Random index value table

[0077]

[0078] Finally, the formula for calculating the second weight coefficient is: wherein ω Bi represents the second weight coefficient, and ω Aj represents the first weight value, represents the second weight value, m represents the number of factor parameters in the criterion layer, and j represents the number of factors in the solution layer.

[0079] In some embodiments, obtaining the preset threshold value can be achieved by the following steps: Determine the preset threshold, where HI represents the preset threshold, n represents the number of the optical fiber sensors in the historical time period, ω Bi Denotes the second historical weight coefficient, D x represents the above-mentioned historical first weight coefficient, The above formula is only exemplary, and any variation of the formula falls within the scope of protection of this application.

[0080] In this scheme, the preset threshold value can be calculated by the target formula. Since the preset threshold value is calculated when the surrounding rock has not been deformed, the accuracy of the preset threshold value is guaranteed to be high. Subsequently, the preset threshold value can be directly compared with the current data to be detected to determine whether the surrounding rock has been deformed.

[0081] In order to ensure the high data quality of the optical fiber data and thus ensure that accurate optical fiber data is subsequently used to detect surrounding rock deformation, the acquisition of optical fiber data in the present application can be specifically achieved through the following steps: obtaining original optical fiber data, wherein the above-mentioned original optical fiber data is the original data of the optical signal collected by the above-mentioned optical fiber sensor; preprocessing the above-mentioned original optical fiber data to obtain the above-mentioned optical fiber data, wherein the above-mentioned preprocessing includes at least one of the following: downsampling, noise reduction, and extraction of partial data.

[0082] In this solution, the acquired original optical fiber data can be preprocessed to improve the data quality of the original optical fiber data, thereby obtaining optical fiber data. The optical fiber data obtained in this way is more accurate, thereby ensuring a high accuracy rate when using accurate optical fiber data to detect surrounding rock deformation.

[0083] Specifically, the continuous signal can be converted into discrete signals x1(k), x2(k), ..., x z (k), a discrete signal corresponds to optical fiber data obtained after preprocessing the original optical fiber data to remove abnormal data and interference signals in the original optical fiber data.

[0084] In order to enable those skilled in the art to more clearly understand the technical solution of the present application, the implementation process of the method for determining surrounding rock deformation of the present application will be described in detail below with reference to specific embodiments.

[0085] This embodiment relates to a specific method for determining surrounding rock deformation, such asFigure 6 As shown, the method comprises the following steps:

[0086] Step S1: obtaining original optical fiber data;

[0087] Step S2: preprocessing the original optical fiber data to obtain optical fiber data;

[0088] Step S3: obtaining a first weight coefficient, and obtaining fused optical fiber data according to the first weight coefficient;

[0089] Step S4: obtaining a second weight coefficient;

[0090] Step S5: obtaining a preset threshold, wherein the preset threshold is calculated according to historical first weight coefficients, historical second weight coefficients, and historical fused optical fiber data;

[0091] Step S6: calculating a current to-be-detected value according to a current first weight coefficient, a current second weight coefficient, and a current fused optical fiber data, determining whether the surrounding rock of the coal mine tunnel deforms according to a size relationship between the preset threshold and the current to-be-detected value, and determining a deformation degree of the surrounding rock of the coal mine tunnel in the case that the surrounding rock of the coal mine tunnel deforms.

[0092] The embodiment of the present application also provides a surrounding rock deformation determination device. It should be noted that the surrounding rock deformation determination device of the embodiment of the present application can be used to execute the surrounding rock deformation determination method provided by the embodiment of the present application. The device is used to realize the above-mentioned embodiments and preferred embodiments, and details are not repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware, or a combination of software and hardware can also be implemented and conceived.

[0093] The surrounding rock deformation determination device provided by the embodiment of the present application is introduced below.

[0094] Figure 7 is a structural block diagram of a surrounding rock deformation determination device according to the embodiment of the present application. As Figure 7 shown, the device comprises:

[0095] The acquisition unit 100 is configured to acquire a plurality of optical fiber data, wherein the optical fiber data is data of an optical signal collected by an optical fiber sensor, the optical fiber data is used to represent the intensity of the spectrum reflected by the surrounding rock of a coal mine tunnel, a plurality of optical fiber sensors are distributedly installed in the coal mine tunnel, and one optical fiber data corresponds to one optical fiber sensor;

[0096] Specifically, the optical fiber data obtained by the scheme is the data of the optical signal collected by the optical fiber sensor. Since the optical fiber sensor is less disturbed by vibrations caused by vehicle passing and drilling construction, the accuracy of subsequent use of the optical fiber data to realize deformation detection of the surrounding rock is also higher.

[0097] Specifically, as shown in Figure 3 , the optical fiber sensor 10 can be integrated in the armored sheath in a distributed manner, and is pre-buried in a zigzag manner on the roadway roof 11 and the roadway wall 12, and an optical fiber sensor demodulator 13 is connected to each 3km long optical fiber sensor 10 to realize online monitoring of the micro-strain of the monitored roadway roof and the two side walls. The optical fiber sensor 10 is arranged around the coal mine roadway 14, and the coal mine roadway is below the coal mine floor.

[0098] Specifically, the optical fiber sensor demodulator transmits a pulse light to the distributed optical fiber sensor, and simultaneously receives the echo light reflected from different positions of the distributed optical fiber sensor. The received echo is subjected to spectral analysis, and the spectral waveform of the reflected echo light can be obtained, as shown in Figure 4 , the peak position change of the spectral waveform can be used to quantitatively measure the roadway strain change at the measured position.

[0099] Specifically, the surrounding rock monitoring of the roof deformation in the coal mine roadway is one of the research focuses of coal mine safety monitoring. The traditional roadway roof deformation is mainly measured by manual or mechanical roof separation instrument. The technical personnel records the data by on-site observation and manual transcription. There are disadvantages such as inconvenient observation, large error, poor real-time data, etc. The scheme can use the optical fiber sensor to automatically detect the intensity of the reflected spectrum of the surrounding rock of the coal mine roadway, improve the automatic monitoring level, and improve the coal mine safety guarantee capability.

[0100] The fusion unit 200 is configured to fuse a plurality of optical fiber data to obtain fused optical fiber data, wherein the fused optical fiber data is used to represent the stress change of the surrounding rock of the coal mine roadway.

[0101] Specifically, the optical fiber data collected by the plurality of optical fiber sensors has multiple, and the scheme can fuse the multiple optical fiber data to reduce the redundancy of the optical fiber data of different measuring points, avoid the low measurement reliability of the optical fiber sensor of a single measuring point, improve the data credibility, and further ensure that the fused optical fiber data has high data quality, and the subsequent deformation of the surrounding rock can be more accurately determined.

[0102] The determination unit 300 is configured to determine whether the surrounding rock of the coal mine roadway deforms according to at least the fused optical fiber data, and determine the deformation degree of the surrounding rock of the coal mine roadway when the surrounding rock of the coal mine roadway deforms.

[0103] Specifically, since the data quality of the fused optical fiber data is high, the accuracy of detecting the surrounding rock deformation according to the accurate fused optical fiber data is also high, and not only whether the surrounding rock deforms can be determined, but also the deformation degree of the surrounding rock can be accurately determined.

[0104] Through the embodiment, the acquisition unit acquires a plurality of optical fiber data, the fusion unit fuses the plurality of optical fiber data to obtain fused optical fiber data, and the determination unit determines whether the surrounding rock of the coal mine tunnel deforms according to at least the fused optical fiber data, and determines the deformation degree of the surrounding rock of the coal mine tunnel in the case that the surrounding rock of the coal mine tunnel deforms. In the scheme, the optical fiber sensor is used to acquire the optical fiber data, which can effectively avoid the vibration interference caused by the passing of vehicles, drilling construction and the like, and the plurality of optical fiber data is fused to obtain the fused optical fiber data. Since the fused optical fiber data is the optical fiber data collected by the optical fiber sensors of a plurality of measuring points, the reliability of the fused optical fiber data is high, and the fused optical fiber data can well reflect the deformation of the surrounding rock, thereby ensuring that whether the surrounding rock deforms can be accurately determined, and the deformation degree of the surrounding rock can be accurately determined in the case that the surrounding rock deforms.

[0105] In addition, since the optical fiber sensor has the advantages of high measurement accuracy, high measurement sensitivity, convenient and fast measurement and the like, the scheme can also ensure that the measurement accuracy of the optical fiber data and the fused optical fiber data is high, thereby ensuring that the accuracy of the surrounding rock deformation detection is high.

[0106] The plurality of optical fiber data has different influences on the fused optical fiber data, so the weight of the plurality of optical fiber data can be limited. In the specific implementation process, the fusion unit includes a first acquisition module and a fusion module. The first acquisition module is used to acquire a first weight coefficient. The first weight coefficient is used to represent the importance of one optical fiber data in the fused optical fiber data. The first weight coefficient is obtained according to the cross-correlation between the target optical fiber data and any non-target optical fiber data. The fusion module is used to obtain the fused optical fiber data according to the sum of the products of each optical fiber data and the first weight coefficient.

[0107] In the scheme, the cross-correlation algorithm can be used to determine the first weight coefficient of different optical fiber data, which can reduce the redundancy of the optical fiber data collected by the optical fiber sensors of different measuring points, thereby fusing according to each optical fiber data and the corresponding first weight coefficient of each optical fiber data. It can be ensured that the fusion efficiency is high, and the accuracy of the fused optical fiber data obtained after fusion is high, thereby further ensuring that the accuracy of detecting the surrounding rock deformation through the fused optical fiber data is high.

[0108] The first weight coefficient can be calculated according to a fusion algorithm of cross-correlation, and the first weight coefficient can be determined according to the fiber data collected by the fiber sensors at different positions, because the fiber sensors at different positions have correlation. In a specific implementation process, the first acquisition module includes a first calculation submodule and a second calculation submodule. The first calculation submodule is configured to calculate all target cross-correlation data, and the target cross-correlation data is the cross-correlation coefficient of the target fiber data and any one of the non-target fiber data. The second calculation submodule is configured to calculate the sum of all target cross-correlation data to obtain the first weight coefficient.

[0109] In this scheme, the cross-correlation coefficient (target cross-correlation data) of the target fiber data and any one of the non-target fiber data can be calculated first, and then the sum of all target cross-correlation data corresponding to the target fiber data is accumulated. In this way, the first weight coefficient of the fiber data collected by the fiber sensors at different positions can be obtained. The first weight coefficient can reflect the importance of the fiber data collected by the fiber sensors at different positions in the fused fiber data, so as to further reduce the redundancy of the fiber data collected by the fiber sensors at different measuring points.

[0110] Specifically, the fiber data can be represented as x z (k), z represents the number of fiber sensors, k represents the number of fiber data, and the formula for calculating the target cross-correlation data is: wherein E ij represents the target cross-correlation data, R ij is calculated according to the formula:

[0111]

[0112] wherein l represents a sliding amount (sliding window), which is obtained according to a convolution operation, and the formula for calculating the first weight coefficient is E i represents the first weight coefficient.

[0113] In another implementation, the sum of the plurality of target cross-correlation data can also be simplified to obtain the ratio between the plurality of target cross-correlation data, and the ratio obtained by simplifying is used as the first weight coefficient. For example: α1:α2:Λ:α z =E1:E2:Λ:E z , and α i is the first weight coefficient of the fiber data detected by the i-th fiber sensor.

[0114] After obtaining the first weight coefficient, the formula for calculating the fused fiber data is X=α1x1+α2x2+Λ+α z x z , wherein X represents the fused fiber data.

[0115] In order to further ensure that the detection result of the scheme is high in accuracy, the determination unit comprises a second acquisition module, a third acquisition module, a calculation module, a comparison module, a first determination module, a second determination module and a third determination module. The second acquisition module is configured to acquire a second weight coefficient, wherein the second weight coefficient is used to represent the importance of one of the optical fiber sensors in the plurality of optical fiber sensors, and the second weight coefficient is determined according to a factor parameter, and the factor parameter comprises at least one of the following: position, stability, working environment, and the importance of the optical fiber sensor at an important position in the coal mine tunnel is higher than that of the optical fiber sensor outside the important position in the coal mine tunnel, and the important position comprises at least one of the following: the position of the center of the roof of the coal mine tunnel, and the position where the roof of the coal mine tunnel intersects with the wall; the third acquisition module is configured to acquire a preset threshold value, wherein the preset threshold value is calculated according to historical first weight coefficients, historical second weight coefficients and historical fused optical fiber data; the calculation module is configured to calculate a current to-be-detected value according to a current first weight coefficient, a current second weight coefficient and a current fused optical fiber data; the comparison module is configured to compare the size relationship between the preset threshold value and the current to-be-detected value; the first determination module is configured to determine that the surrounding rock of the coal mine tunnel has not deformed in the case that the preset threshold value and the current to-be-detected value are the same; the second determination module is configured to determine that the surrounding rock of the coal mine tunnel has deformed and the deformation degree is a first deformation degree in the case that the preset threshold value and the current to-be-detected value are different, and the difference between the preset threshold value and the current to-be-detected value is less than a difference threshold value; and the third determination module is configured to determine that the surrounding rock of the coal mine tunnel has deformed and the deformation degree is a second deformation degree in the case that the preset threshold value and the current to-be-detected value are different, and the difference between the preset threshold value and the current to-be-detected value is greater than or equal to the difference threshold value, wherein the first deformation degree is less than the second deformation degree.

[0116] In the scheme, the second weight coefficient of each optical fiber sensor can also be determined, the current to-be-detected value is calculated according to the current first weight coefficient, the second weight coefficient and the current fused optical fiber data, and the preset threshold value is obtained when the surrounding rock of the coal mine tunnel has not deformed. In this way, the current to-be-detected value and the preset threshold value are directly compared, and the difference obtained can accurately determine whether the surrounding rock of the coal mine tunnel has deformed. In addition, in the case that the surrounding rock of the coal mine tunnel has deformed, the size of the deformation can be determined according to the relationship between the difference and the difference threshold value.

[0117] Specifically, the way of calculating the preset threshold value and calculating the current to-be-detected value can be the same, except that the parameters for calculation are different.

[0118] The curve of stress change of surrounding rock is as follows Figure 5 As shown, from Figure 5 It can be seen from the figure that the tunnel strain parameters (current value to be detected, Figure 5 The strain in the tunnel can reflect the status of the tunnel roof and the walls on both sides in real time. The real-time measured strain parameters can provide an effective monitoring method for accidents such as support failure, roof collapse, and side collapse.

[0119] The second weight coefficient of the optical fiber sensor can be obtained by the AHP algorithm. Since the positions of different optical fiber sensors are different, the importance of different optical fiber sensors is also different. Therefore, the use of the AHP algorithm to construct a pairwise comparison matrix can ensure that the second weight coefficient is obtained more accurately. In some embodiments, the second acquisition module includes a first construction submodule, a second construction submodule, a first determination submodule and a third calculation submodule. The first construction submodule is used to construct a target model, wherein the target model includes a target layer, a criterion layer and a solution layer. The target layer is the selected optical fiber sensor, the criterion layer is the factor parameters of each optical fiber sensor, and the solution layer is for a plurality of the above-mentioned optical fiber sensors; the second construction submodule is used to construct a target matrix, wherein the elements in the above-mentioned target matrix are the importance of the target optical fiber sensor relative to the non-optical fiber sensor, and the importance of the above-mentioned target optical fiber sensor relative to the above-mentioned non-optical fiber sensor is obtained by looking up the relevant measurement scale table; the first determination submodule is used to determine the first weight value of each of the above-mentioned factor parameters in the above-mentioned criterion layer according to the above-mentioned target matrix, and determine the second weight value of each of the above-mentioned optical fiber sensors in the above-mentioned scheme layer under the influence of each of the above-mentioned factor parameters in the above-mentioned criterion layer according to the above-mentioned target matrix; the third calculation submodule is used to calculate the second product of the above-mentioned first weight value and the above-mentioned second weight value to obtain the above-mentioned second weight coefficient.

[0120] In this scheme, the target model is the AHP algorithm model. The AHP algorithm can be used to set a second weight coefficient for each optical fiber sensor, construct the target layer, criterion layer and scheme layer, and establish a pairwise comparison matrix (target matrix) to compare the weights between different optical fiber sensors, thereby ensuring that the accuracy of the obtained second weight coefficient is high.

[0121] Specifically, the second weight coefficient is calculated as follows:

[0122] The goal layer is designed as "Optical fiber sensor selection", the criterion layer is designed as "Optical fiber sensor location", "Optical fiber sensor stability", "Optical fiber sensor working environment", and the solution layer is designed as "Optical fiber sensor 1", "Optical fiber sensor 2" ... "Optical fiber sensor n";

[0123] The pairwise comparison matrix is established, the pairwise comparison matrix of the criterion layer and the scheme layer is obtained according to Table 1, wherein the first weight value of each factor in the criterion layer is The second weight value of each factor in the scheme layer under the influence of each factor Aj (j = 1, 2, …, m) in the criterion layer is Specifically, the square root method formula is:

[0124]

[0125] And the standardization formula is:

[0126]

[0127] The weight vector (first weight value and second weight value) is obtained, the consistency index CI and the consistency ratio CR of the pairwise comparison matrix established by the criterion layer and the scheme layer are calculated, the CR does not exceed 0.1 to pass the consistency test, otherwise the comparison matrix is redesigned, wherein the formula for calculating the consistency index is:

[0128]

[0129] The formula for calculating the consistency ratio is:

[0130] λ max represents the maximum eigenvalue, n represents the order of the matrix, RI is obtained by Table 2, and depends on the order of the elements in the target matrix, and finally the formula for calculating the second weight coefficient is: wherein ω Bi represents the second weight coefficient, ω Aj represents the first weight value, represents the second weight value, m represents the number of factor parameters in the criterion layer, and j represents the number of factors in the scheme layer. In some embodiments, the third obtaining module includes a second determining submodule, the second determining submodule is configured to determine the above-mentioned preset threshold according to the target formula wherein HI represents the above-mentioned preset threshold, n represents the number of the above-mentioned optical fiber sensors in the historical time period, ω Bi represents the above-mentioned historical second weight coefficient, D x represents the above-mentioned historical first weight coefficient, represents the average value of a plurality of the above-mentioned historical fusion optical fiber data under the condition that the above-mentioned surrounding rock of the coal mine tunnel does not deform. The above-mentioned formula is only exemplary, and any deformation of the formula falls within the protection scope of the present application.

[0131] In the scheme, the preset threshold value can be calculated by the target formula, and since the preset threshold value is calculated when the surrounding rock is not deformed, the accuracy of the preset threshold value is high, and the preset threshold value and the current to-be-detected data can be directly compared to determine whether the surrounding rock is deformed.

[0132] In order to ensure that the data quality of the optical fiber data is high, and then ensure that the accurate optical fiber data is used to detect the surrounding rock deformation, the acquisition unit includes a fourth acquisition module and a preprocessing module, the fourth acquisition module is used to acquire original optical fiber data, wherein the original optical fiber data is the original data of the optical signal collected by the optical fiber sensor; the preprocessing module is used to preprocess the original optical fiber data to obtain the optical fiber data, wherein the preprocessing includes at least one of the following: downsampling, noise reduction, and extracting part of the data.

[0133] In the scheme, the original optical fiber data obtained can be preprocessed to improve the data quality of the original optical fiber data, and then the optical fiber data is obtained, so that the optical fiber data obtained is more accurate, and then the accuracy of using the accurate optical fiber data to detect the surrounding rock deformation is high.

[0134] Specifically, according to the Nyquist sampling theorem, the continuous signal can be changed into discrete signals x1(k), x2(k), …, x z (k), a discrete signal corresponds to an optical fiber data obtained after preprocessing of the original optical fiber data, so as to remove abnormal data and interference signals in the original optical fiber data.

[0135] The surrounding rock deformation determination device includes a processor and a memory, the acquisition unit, the fusion unit, and the determination unit are all stored in the memory as program units, and the corresponding functions are realized by the processor executing the program units stored in the memory. The modules are all located in the same processor; or the modules are located in different processors in any combination.

[0136] The processor includes a core, and the core retrieves the corresponding program unit from the memory. The core can be set to one or more, and the accuracy of the surrounding rock deformation detection in the tunnel can be improved by adjusting the core parameters.

[0137] The memory can include a non-persistent memory in a computer readable medium, a random access memory (RAM), and / or a non-volatile memory such as a read-only memory (ROM) or a flash memory (flash RAM), and the memory includes at least one memory chip.

[0138] The embodiment of the present application provides a computer readable storage medium, the computer readable storage medium comprises a stored program, wherein the program controls a device where the computer readable storage medium is located to perform the surrounding rock deformation determination method when the program is run.

[0139] The present application also provides a surrounding rock deformation detection system, comprising one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs comprise programs for executing any of the above methods.

[0140] The embodiment of the present application provides a processor, the processor is used for running a program, wherein the program performs the surrounding rock deformation determination method when the program is run.

[0141] The embodiment of the present application provides a device, the device comprises a processor, a memory and a program stored in the memory and capable of running on the processor, and the processor performs the steps of the surrounding rock deformation determination method when the program is run.

[0142] The device herein can be a server, a PC, a PAD, a mobile phone or the like.

[0143] The present application also provides a computer program product, when executed on a data processing device, is suitable for executing the program initialized with the steps of the surrounding rock deformation determination method:

[0144] Obviously, those skilled in the art should understand that the modules or steps of the present application described above can be realized by general computing devices, which can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, which can be realized by program codes executable by computing devices, so that they can be stored in storage devices and executed by computing devices, and in some cases, the steps shown or described can be executed in different order, or they can be manufactured into individual integrated circuit modules, or multiple modules or steps can be manufactured into a single integrated circuit module. Therefore, the present application is not limited to any specific combination of hardware and software.

[0145] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can be in the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can be in the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program codes.

[0146] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.

[0147] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.

[0148] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.

[0149] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0150] The memory can include non-persistent memory, Random Access Memory (RAM), and / or non-volatile memory, e.g., Read Only Memory (ROM) or flash memory, among others in a computer readable medium. The memory is an example of computer readable media.

[0151] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology for information storage. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer-readable media does not include transitory media such as modulated data signals and carriers.

[0152] It should also be noted that the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that processes, methods, articles or devices including a series of elements not only include those elements, but also include other elements not explicitly listed or inherent to such processes, methods, articles or devices. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or device including the element.

[0153] From the above description, it can be seen that the above-mentioned embodiments of the present application achieve the following technical effects:

[0154] 1) The surrounding rock deformation determination method of the present application first acquires a plurality of optical fiber data, then performs data fusion on the plurality of optical fiber data to obtain fused optical fiber data, and finally determines whether the surrounding rock of the coal mine tunnel has deformed according to at least the fused optical fiber data, and determines the deformation degree of the surrounding rock of the coal mine tunnel in the case that the surrounding rock of the coal mine tunnel has deformed. In this scheme, optical fiber sensors are used to acquire optical fiber data, which can effectively avoid vibration interference caused by vehicle passing, drilling construction, etc., and the plurality of optical fiber data is fused to obtain fused optical fiber data. Since the fused optical fiber data is the optical fiber data collected by the optical fiber sensors of a plurality of measurement points, the reliability of the fused optical fiber data is high, and the fused optical fiber data can better reflect the deformation of the surrounding rock, thereby ensuring that the deformation of the surrounding rock can be accurately determined, and the deformation degree of the surrounding rock can be accurately determined in the case that the surrounding rock has deformed.

[0155] 2) The surrounding rock deformation determination device of the present application, the acquisition unit acquires multiple optical fiber data, the fusion unit fuses the multiple optical fiber data to obtain fused optical fiber data, and the determination unit determines whether the surrounding rock of the coal mine tunnel is deformed based on at least the fused optical fiber data, and determines the degree of deformation of the surrounding rock of the coal mine tunnel when the surrounding rock of the coal mine tunnel is deformed. In this solution, the use of optical fiber sensors to acquire optical fiber data can effectively avoid vibration interference caused by vehicle passing, drilling construction, etc., and the fusion of multiple optical fiber data to obtain fused optical fiber data. Since the fused optical fiber data is the optical fiber data collected by optical fiber sensors at multiple measurement points, the reliability of the fused optical fiber data is high, and the fused optical fiber data can better reflect the deformation of the surrounding rock, thereby ensuring that it can accurately determine whether the surrounding rock is deformed, and can also accurately determine the degree of deformation of the surrounding rock when the surrounding rock is deformed.

[0156] The above description is merely a preferred embodiment of the present application and is not intended to limit the present application. Various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A method for determining surrounding rock deformation, characterized in that: include: Acquire multiple optical fiber data, wherein the optical fiber data is data of an optical signal collected by an optical fiber sensor, the optical fiber data is used to characterize the intensity of a spectrum reflected by surrounding rock in a coal mine tunnel, and multiple optical fiber sensors are distributedly installed in the coal mine tunnel, with one optical fiber data corresponding to one optical fiber sensor; Performing data fusion on the plurality of optical fiber data to obtain fused optical fiber data, wherein the fused optical fiber data is used to characterize stress changes in the surrounding rock of the coal mine tunnel; determining whether the surrounding rock of the coal mine roadway is deformed based on at least the fused optical fiber data, and if the surrounding rock of the coal mine roadway is deformed, determining the degree of deformation of the surrounding rock of the coal mine roadway; Performing data fusion on the plurality of optical fiber data to obtain fused optical fiber data, comprising: obtaining a first weight coefficient, wherein the first weight coefficient is used to characterize the importance of a piece of optical fiber data in the fused optical fiber data, and the first weight coefficient is obtained based on the cross-correlation between the target optical fiber data and any non-target optical fiber data; obtaining the fused optical fiber data based on the sum of the products of each optical fiber data and the first weight coefficient, At least based on the fused optical fiber data, determining whether the surrounding rock of the coal mine tunnel is deformed, and in the case that the surrounding rock of the coal mine tunnel is deformed, determining the degree of deformation of the surrounding rock of the coal mine tunnel, including: obtaining a second weight coefficient, wherein the second weight coefficient is used to characterize the importance of one optical fiber sensor among multiple optical fiber sensors, and the second weight coefficient is determined according to factor parameters, and the factor parameters include at least one of the following: position, stability, working environment, the importance of the optical fiber sensor located at an important position in the coal mine tunnel is higher than the importance of the optical fiber sensor outside the important position in the coal mine tunnel, and the important position includes at least one of the following: the position of the center of the roof of the coal mine tunnel, the position where the roof of the coal mine tunnel intersects with the wall; obtaining a preset threshold, wherein the preset threshold is determined based on the historical first weight coefficient, the historical second weight coefficient and the historical The method is calculated based on the fused optical fiber data; the current value to be detected is calculated according to the current first weight coefficient, the current second weight coefficient and the current fused optical fiber data; the size relationship between the preset threshold and the current value to be detected is compared; when the preset threshold and the current value to be detected are the same, it is determined that the surrounding rock of the coal mine tunnel has not been deformed; when the preset threshold and the current value to be detected are not the same, and the difference between the preset threshold and the current value to be detected is less than the difference threshold, it is determined that the surrounding rock of the coal mine tunnel has been deformed, and the deformation degree is determined to be the first deformation degree; when the preset threshold and the current value to be detected are not the same, and the difference between the preset threshold and the current value to be detected is greater than or equal to the difference threshold, it is determined that the surrounding rock of the coal mine tunnel has been deformed, and the deformation degree is determined to be the second deformation degree, wherein the first deformation degree is less than the second deformation degree.

2. The method according to claim 1, characterized in that Obtaining the first weight coefficient includes: Calculating all target cross-correlation data, where the target cross-correlation data is a cross-correlation coefficient between the target optical fiber data and any one of the non-target optical fiber data; The sum of all the target cross-correlation data is calculated to obtain the first weight coefficient.

3. The method according to claim 1, characterized in that Obtaining the second weight coefficient includes: Constructing a target model, wherein the target model includes a target layer, a criterion layer, and a solution layer, the target layer is the selected optical fiber sensor, the criterion layer is the factor parameters of each optical fiber sensor, and the solution layer is a plurality of optical fiber sensors; Constructing a target matrix, wherein the elements in the target matrix are the importance of the target optical fiber sensor relative to the non-optical fiber sensor, and the importance of the target optical fiber sensor relative to the non-optical fiber sensor is obtained by looking up a relevant measurement scale table; Determine a first weight value of each factor parameter in the criterion layer according to the target matrix, and determine a second weight value of each optical fiber sensor in the solution layer under the influence of each factor parameter in the criterion layer according to the target matrix; A second product of the first weight value and the second weight value is calculated to obtain the second weight coefficient.

4. The method according to claim 1, wherein Get preset thresholds, including: According to the target formula Determine the preset threshold, wherein, represents the preset threshold, represents the number of optical fiber sensors in the historical time period, represents the second historical weight coefficient, represents the first historical weight coefficient, It represents the average value of a plurality of the historical fused optical fiber data when the surrounding rock in the coal mine tunnel is not deformed.

5. The method according to claim 1, wherein Obtain fiber data, including: Acquiring raw optical fiber data, wherein the raw optical fiber data is raw data of the optical signal collected by the optical fiber sensor; The original optical fiber data is preprocessed to obtain the optical fiber data, wherein the preprocessing includes at least one of the following: downsampling, noise reduction, and partial data extraction.

6. A device for determining surrounding rock deformation, characterized in that: include: an acquisition unit, configured to acquire a plurality of optical fiber data, wherein the optical fiber data is data of an optical signal collected by an optical fiber sensor, and the optical fiber data is used to characterize the intensity of a spectrum reflected by surrounding rock in a coal mine roadway, and a plurality of the optical fiber sensors are distributedly installed in the coal mine roadway, and one optical fiber data corresponds to one optical fiber sensor; a fusion unit, configured to fuse the plurality of optical fiber data to obtain fused optical fiber data, wherein the fused optical fiber data is used to characterize stress changes in the surrounding rock of the coal mine tunnel; a determining unit, configured to determine whether the surrounding rock of the coal mine roadway is deformed based at least on the fused optical fiber data, and if the surrounding rock of the coal mine roadway is deformed, determine the degree of deformation of the surrounding rock of the coal mine roadway; The fusion unit includes a first acquisition module and a fusion module, wherein the first acquisition module is used to obtain a first weight coefficient, wherein the first weight coefficient is used to characterize the importance of a piece of optical fiber data in the fused optical fiber data, and the first weight coefficient is obtained based on the cross-correlation between the target optical fiber data and any non-target optical fiber data; the fusion module is used to obtain the fused optical fiber data based on the sum of the products of each piece of optical fiber data and the first weight coefficient. The determination unit includes a second acquisition module, a third acquisition module, a calculation module, a comparison module, a first determination module, a second determination module and a third determination module, the second acquisition module is used to obtain a second weight coefficient, wherein the second weight coefficient is used to characterize the importance of one of the optical fiber sensors among the multiple optical fiber sensors, and the second weight coefficient is determined according to factor parameters, and the factor parameters include at least one of the following: position, stability, working environment, the importance of the optical fiber sensor located at an important position in the coal mine tunnel is higher than the importance of the optical fiber sensor outside the important position in the coal mine tunnel, and the important position includes at least one of the following: the position of the center of the roof of the coal mine tunnel, the position where the roof of the coal mine tunnel intersects with the wall; the third acquisition module is used to obtain a preset threshold, wherein the preset threshold is calculated based on the historical first weight coefficient, the historical second weight coefficient and the historical fused optical fiber data; the calculation module is used to obtain a preset threshold based on the current first weight coefficient, the historical second weight coefficient and the historical fused optical fiber data. a first weight coefficient, a current second weight coefficient and current fused optical fiber data, and calculates the current value to be detected; the comparison module is used to compare the size relationship between the preset threshold and the current value to be detected; the first determination module is used to determine that the surrounding rock of the coal mine tunnel has not been deformed when the preset threshold and the current value to be detected are the same; the second determination module is used to determine that the surrounding rock of the coal mine tunnel has been deformed and the deformation degree is determined to be a first deformation degree when the preset threshold and the current value to be detected are different and the difference between the preset threshold and the current value to be detected is less than a difference threshold; the third determination module is used to determine that the surrounding rock of the coal mine tunnel has been deformed and the deformation degree is determined to be a second deformation degree when the preset threshold and the current value to be detected are different and the difference between the preset threshold and the current value to be detected is greater than or equal to the difference threshold, wherein the first deformation degree is less than the second deformation degree.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 5.

8. A surrounding rock deformation detection system, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing the method of any one of claims 1 to 5.

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