Space-time monitoring and early warning device and method for coal seam stress-dominated dynamic disaster

Abstract

The invention discloses a coal seam stress-dominated dynamic disaster time-space monitoring and early warning device and method. The coal seam stress-dominated dynamic disaster time-space monitoring and early warning device comprises a DAS host, a DSS host, a plurality of first armored optical fibers, a plurality of second armored optical fibers and an alarm. A DAS host and a first armored optical fiber are utilized to realize long-term and full-coverage coal seam stress inversion of a coal seam working face through large-range and long-term monitoring of vibration signals of the coal seam working face; meanwhile, a DSS host and a second armored optical fiber are utilized, long-term stress value monitoring of different positions of the coal seam working face is achieved by collecting strain data of the different positions of the coal seam working face, and real-time, dynamic, intelligent and non-contact continuous monitoring of the coal seam working face can be achieved through combination of the DSS host and the second armored optical fiber; finally, stress field distribution of the coal seam working face at each moment is obtained, and if an area exceeding a set threshold value is found, early warning prompt can be directly carried out; in this way, accurate, rapid and full-time-space monitoring and early warning of deep stress-dominated coal rock dynamic disasters are achieved.

Description

Technical Field

[0001] The present invention belongs to the field of monitoring and early warning of coal and rock dynamic disasters, and particularly relates to a device and method for spatio-temporal monitoring and early warning of coal seam stress-dominated dynamic disasters. Background Art

[0002] With the continuous increase of coal mining depth and intensity, the geological conditions faced are becoming increasingly complex. Under the conditions of deep mining, the occurrence mechanisms of coal and rock dynamic disasters such as coal and gas outburst and rock burst are more complex. Among them, the action mechanisms of factors such as gas content, in-situ stress distribution, and coal body structure and their coupling effects become more difficult to predict. Especially for coal and rock gas dynamic disasters dominated by in-situ stress, their occurrence frequency and disaster degree show a significant upward trend, seriously threatening the safe mining of coal mine engineering.

[0003] At present, the stress testing methods for coal mine underground working faces mainly include direct testing methods and indirect testing methods. Direct testing methods such as hydraulic pillow method, stress injection capsule method, and stress relief method can accurately measure the local stress state, but their measuring points are limited, and the construction difficulty is large, the cost is high, and it is difficult to comprehensively reflect the stress distribution of the entire working face. Indirect testing methods such as microseismic monitoring method, rheological stress recovery method, and hydraulic fracturing method can be used to infer the stress state of the entire working face, but their accuracy is limited. In addition, the above existing testing methods are all difficult to achieve full spatio-temporal monitoring of dynamic disasters (that is, continuous monitoring of each position).

[0004] Under this background, there is an urgent need to develop a real-time, dynamic, intelligent, non-contact continuous prediction technology suitable for deep mining conditions to make up for the deficiencies of existing direct and indirect stress field testing methods, and be able to adapt to the complex and harsh environment of the mine underground, so as to achieve accurate, rapid, full spatio-temporal monitoring and early warning of deep stress-dominated coal and rock dynamic disasters, which is the research direction required by the present invention. Summary of the Invention

[0005] Aiming at the problems existing in the above-mentioned prior art, the present invention provides a device and method for spatio-temporal monitoring and early warning of coal seam stress-dominated dynamic disasters. By laying armored optical fibers, the working face under deep mining conditions is continuously monitored in real time, dynamically, intelligently, and non-contact, so as to achieve accurate, rapid, full spatio-temporal monitoring and early warning of deep stress-dominated coal and rock dynamic disasters.

[0006] To achieve the above object, the technical solution adopted by the present invention is: a device for spatio-temporal monitoring and early warning of coal seam stress-dominated dynamic disasters, including a DAS host (i.e., a distributed optical fiber acoustic wave monitoring system), a DSS host (i.e., a distributed optical fiber strain monitoring system), a plurality of first armored optical fibers, a plurality of second armored optical fibers, and an alarm;

[0007] Multiple first armored optical fibers are arranged along the strike of the coal seam working face in the coal seam working face to obtain seismic wave signals at different positions of the coal seam working face and feedback them to the DAS host; multiple second armored optical fibers are arranged along the dip of the coal seam working face in the coal seam working face to obtain strain data at the positions around each of the second armored optical fibers and feedback them to the DSS host;

[0008] The DSS host is used to analyze the received strain data to obtain the stress values at the positions around each of the second armored optical fibers; the DAS host is used to perform inversion processing on the received seismic wave signals and correct them in combination with the stress values analyzed by the DSS host, and finally obtain the overall stress field distribution of the coal seam working face; and control the alarm to issue a warning prompt according to the stress field distribution.

[0009] Furthermore, the number of the first armored optical fibers is two, and the two first armored optical fibers are respectively 2m to 4m away from the nearest roadway. Such an arrangement can ensure more accurate data collection.

[0010] Furthermore, multiple of the second armored optical fibers are arranged parallel to each other and at equal intervals. Such an arrangement can ensure more accurate data collection.

[0011] Furthermore, an active seismic source is further included, and the active seismic source is arranged in one of the roadways on one side of the coal seam working face to excite seismic wave signals. This device can directly receive the seismic wave signals generated by the passive seismic source for subsequent processing. By adding an active seismic source to actively excite seismic wave signals, the overall wave velocity field of the coal seam working face can be obtained more quickly, which is convenient for subsequent overall analysis.

[0012] Furthermore, each spatial resolution unit in the first armored optical fiber serves as a vibration signal receiver, and each spatial resolution unit in the second armored optical fiber serves as a strain signal receiver, and their spatial resolutions are both 1m to 2m.

[0013] Furthermore, the DAS host is based on receives and processes the Rayleigh scattering signals fed back by each first armored optical fiber, and then obtains the seismic wave signals at different positions; the DSS host receives and processes the Brillouin scattering signals fed back by each second armored optical fiber based on BOTDA, and then obtains the strain data at different positions; in addition, during the process of obtaining the strain data, it is necessary to ensure that the temperature of the coal seam working face is stable, that is, the front-back change range does not exceed 5°C. At this time, the influence of temperature can be not considered and the strain can be directly calculated. If the temperature change range of the coal seam working face exceeds 5°C, then the temperature correction should be considered when calculating the strain information, which can further ensure the accuracy of data acquisition.

[0014] The working method of the above-mentioned coal seam stress-dominated dynamic disaster spatio-temporal monitoring and early warning device is specifically as follows:

[0015] A. Installing a dynamic disaster spatio-temporal monitoring and early warning device: Along the strike of the coal seam working face, at least two first bedding boreholes are arranged. A first armored optical fiber is placed in each first bedding borehole, and the first armored optical fiber is in pressing contact with the first bedding borehole; Multiple second bedding boreholes are constructed from the roadway on one side of the coal seam working face into the coal seam working face along its dip. A second armored optical fiber is placed in each second bedding borehole, and the second armored optical fiber is in pressing contact with the second bedding borehole; Then, both the DSS host and the DAS host are evenly arranged in the underground power distribution room, and each first armored optical fiber is connected to the DAS host, and each second armored optical fiber is connected to the DSS host;

[0016] B. Data acquisition: Turn on the DAS host and the DSS host. The DAS host uses each first armored optical fiber to obtain the vibration wave signals generated by seismic sources around the coal seam working face in real time; The DSS host uses the second armored optical fiber to obtain the strain data of its respective surrounding positions in real time;

[0017] C. Data analysis: After the DSS host calculates the strain data received at a certain moment, the stress values at the same moment at different positions are obtained; Furthermore, the strain values at different positions at the same moment are interpolated to generate a stress distribution map; The DAS host uses the elastic vibration wave inversion technology to process the vibration wave signals received at the same moment, obtains the wave velocity field of the coal seam working face at this moment, and then uses the wave velocity field to invert the stress field of the coal seam working face; Finally, the stress distribution map generated by the DSS host at the same moment is used to correct the stress field inverted by the DAS host, and finally the stress field distribution of the coal seam working face at this moment is obtained;

[0018] D. Full spatio-temporal monitoring and early warning: Set an alarm threshold, continuously repeat steps B and C, conduct long-term monitoring on the stress-strain spatio-temporal distribution data of the coal seam working face, determine the stress concentration area and the area with a large stress gradient of the coal seam working face. When a certain position exceeds the alarm threshold, early warning of high-risk coal and rock dynamic disasters is carried out through an alarm.

[0019] Furthermore, the specific method of using the wave velocity field to invert the stress field of the coal seam working face in step C is as follows: The coal body is a typical porous medium. The change of in-situ stress will compact the coal body, causing a change in the density of the target coal seam. The change of coal seam density will affect the wave velocity in this area. Then, there is a positive correlation between stress and wave velocity. By establishing a relationship function between stress and wave velocity:

[0020]

[0021] In the formula, V P represents the longitudinal wave velocity, σ represents the stress, \(\xi\) and \(\psi\) are constants. By using this function, the stress field of the coal seam working face can be inversely obtained from the wave velocity field, and according to the dynamic change of the wave velocity field, the dynamic evolution of the stress field of the coal seam working face can be inversely obtained in real time.

[0022] Furthermore, in step C, the stress value is calculated from the strain data, specifically as follows:

[0023] A relationship function between stress and strain is established:

[0024] \(\sigma = f(\varepsilon)\)

[0025] In the formula, \(\varepsilon\) represents strain, and \(f\) represents the relationship function between strain and stress. Through this function, the corresponding stress value can be calculated from the strain data at each position.

[0026] Furthermore, the interpolation calculation in step C is specifically as follows: The stress values at different positions at the same moment are sorted into a numerical matrix and imported into MATLAB software, and the griddata function in MATLAB software is used to complete the interpolation calculation to generate a stress distribution map.

[0027] Compared with the prior art, the present invention adopts a combination of direct monitoring and indirect monitoring, and has the following advantages:

[0028] 1. The present invention uses the DAS host and the first armored optical fiber to realize the long-term and full-coverage coal seam stress inversion of the coal seam working face through the large-range and long-term monitoring of the vibration signals of the coal seam working face; at the same time, the DSS host and the second armored optical fiber are used to realize the long-term stress value monitoring of different positions of the coal seam working face through the acquisition of strain data at different positions of the coal seam working face. The combination of the two can realize the real-time, dynamic, intelligent and non-contact continuous monitoring of the coal seam working face.

[0029] 2. In the present invention, the DAS host and the first armored optical fiber are in the indirect monitoring mode, and the DSS host and the second armored optical fiber are in the direct monitoring mode. The indirect monitoring mode can obtain the overall stress distribution of the coal seam working face through inversion, and its range is wide; while the direct monitoring mode can only obtain the stress value at the position where the second armored optical fiber passes, but its accuracy is high. The stress distribution map generated by the direct monitoring mode at each moment is used to correct the stress field inversed by the indirect monitoring mode, and finally the stress field distribution of the coal seam working face at each moment is obtained. If an area exceeding the set threshold is found, an early warning prompt can be directly given; this method realizes the accurate, rapid, full-time and space monitoring and early warning of deep stress-dominated coal and rock dynamic disasters; it has important practical significance for improving the safety production level of coal mines and reducing the risk of coal and rock dynamic disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 is a layout schematic diagram of the device of the present invention;

[0031] Figure 2 It is a schematic diagram of indirectly monitoring the stress field by the DAS host and the first armored optical fiber in the present invention;

[0032] Figure 3 It is a schematic diagram of directly monitoring the stress field by the DSS host and the second armored optical fiber in the present invention;

[0033] Figure 4 It is a schematic diagram of inverting the stress distribution by the seismic wave on the working face in the present invention;

[0034] In the figure: 1. DAS host, 2. DSS host, 3. First armored optical fiber, 4. Second armored optical fiber, 5. Distribution room, 6. Intake airway, 7. Return airway, 8. Coal seam working face, 9. Seismic source. Specific implementation manners

[0035] The present invention will be further described below.

[0036] As Figure 1 shown, a spatio-temporal monitoring and early warning device for coal seam stress-dominated dynamic disasters includes a DAS host 1 (i.e., a distributed optical fiber acoustic wave monitoring system), a DSS host 2 (i.e., a distributed optical fiber strain monitoring system), a plurality of first armored optical fibers 3, a plurality of second armored optical fibers 4, and an alarm;

[0037] As Figure 2 shown, a plurality of first armored optical fibers 3 are arranged in the coal seam working face 8 along the strike of the coal seam working face, and are used to acquire the seismic wave signals at different positions of the coal seam working face 8 and feed them back to the DAS host 1; As Figure 3 shown, a plurality of second armored optical fibers 4 are arranged in the coal seam working face 8 along the dip of the coal seam working face, and are used to acquire the strain data at the positions around each of the second armored optical fibers 4 and feed them back to the DSS host 2; Each spatial resolution unit in the first armored optical fiber 3 serves as a seismic signal receiver, and each spatial resolution unit in the second armored optical fiber 4 serves as a strain signal receiver, and their spatial resolutions are both 1 m to 2 m.

[0038] The DSS host 2 is used to analyze the received strain data to obtain the stress values at the positions around each of the second armored optical fibers 4; the DAS host 1 is used to perform inversion processing on the received seismic wave signals, and correct them in combination with the stress values analyzed by the DSS host 2, and finally obtain the overall stress field distribution of the coal seam working face; and control the alarm to issue an early warning prompt according to the stress field distribution; The DAS host 1 is based on Receive and process the Rayleigh scattering signals fed back by each first armored optical fiber 3, and then obtain the vibration wave signals at different positions; the DSS host 2 receives and processes the Brillouin scattering signals fed back by each second armored optical fiber 4 based on BOTDA, and then obtains the strain data at different positions; during the process of obtaining the strain data, it is necessary to ensure that the temperature of the coal seam working face is stable, that is, the front-back change range does not exceed 5 °C. At this time, the influence of temperature can be ignored and the strain can be directly calculated. If the temperature change range of the coal seam working face 8 exceeds 5 °C, the temperature correction should be considered when calculating the strain information, which can further ensure the accuracy of data acquisition. In addition, when using the DSS host 2 to monitor stress, several hollow inclusion stress gauges are arranged near the position where the second armored optical fiber 4 extends from the coal seam working face 8, and the test results of the hollow inclusion stress gauges are used to calibrate the test results of the DSS host 2. After calibration, the measurement results of the DSS host 2 can be converted into more real stress values using the calibration curve or formula.

[0039] As an improvement of the present invention, the number of the first armored optical fibers 3 is two, and the two first armored optical fibers 3 are respectively 2 m to 4 m away from their nearest roadways. Such an arrangement can ensure more accurate data collection. The multiple second armored optical fibers 4 are arranged parallel to each other and at equal intervals. Such an arrangement can ensure more accurate data collection.

[0040] As another improvement of the present invention, it further includes an active seismic source, which is arranged in one of the roadways on the coal seam working face 8 and is used to excite vibration wave signals. This device can directly receive the seismic wave signals generated by the passive seismic source for subsequent processing. By adding an active seismic source to actively excite vibration wave signals, the wave velocity field of the whole coal seam working face can be obtained more quickly, which is convenient for subsequent overall analysis.

[0041] As Figure 4 shown, the working method of the above-mentioned coal seam stress-dominated dynamic disaster spatio-temporal monitoring and early warning device is specifically as follows:

[0042] A. Installation of dynamic disaster spatio-temporal monitoring and early warning devices: Before installation, the first armored optical fiber 3 and the second armored optical fiber 4 are respectively detected by the DAS mainframe 1 and the DSS mainframe 2 on the ground to ensure that the quality of the optical fiber meets the normal working requirements; two first bedding holes are arranged along the strike in the coal seam working face 8, and a first armored optical fiber 3 is placed in each first bedding hole, and cement mortar is injected into the hole, and wait for it to solidify so that the first armored optical fiber 3 is in close contact with the first bedding hole to form a stable coupling; eight second bedding holes are constructed from the return airway 7 to the intake airway 6 in the coal seam working face 8 and along its dip, and a second armored optical fiber 4 is placed in each second bedding hole, and cement mortar is injected into the hole, and wait for it to solidify so that the second armored optical fiber 4 is in close contact with the second bedding hole to form a stable coupling; then the DSS mainframe 1 and the DAS mainframe 2 are both arranged in the underground power distribution room 5, and each first armored optical fiber 3 is connected to the DAS mainframe 1, and each second armored optical fiber 4 is connected to the DSS mainframe 2;

[0043] B. Data acquisition: Turn on the DAS mainframe 1 and the DSS mainframe 2. Among them, the DAS mainframe 1 uses each first armored optical fiber 3 to obtain the vibration wave signals generated by the seismic sources around the coal seam working face 8 in real time; the seismic sources 9 include active seismic sources (such as blasting, hammering, etc.) and passive seismic sources (such as roof and floor rupture, etc.) excited in the coal seam working face 8; the DSS mainframe 2 uses the second armored optical fiber 4 to obtain the strain data of its respective surrounding positions in real time;

[0044] C. Data analysis: The DSS mainframe 2 calculates the stress values at the same moment at different positions after calculating the strain data received at a certain moment. Specifically:

[0045] Establish a relationship function between stress and strain:

[0046] σ = f(ε)

[0047] In the formula, ε represents strain, f represents the relationship function between strain and stress, and through this function, the corresponding stress values can be calculated through the strain data at each position; this is a direct monitoring method; furthermore, the stress values at different positions at the same moment are sorted into a numerical matrix and imported into the MATLAB software, and the griddata function in the MATLAB software is used to complete the interpolation calculation to generate a stress distribution map, and the interpolation type is selected as v4, where v4 is a biharmonic spline extrapolation method, which can perform good interpolation on unstructured scattered data.

[0048] The DAS host 1 uses the elastic shock wave inversion technology to process the shock wave signals received at the same moment, obtains the wave velocity field of the coal seam working face at this moment, and then uses the wave velocity field to inversely obtain the stress field of the coal seam working face. Specifically: The coal body is a typical porous medium. The change of in-situ stress will compact the coal body, causing a change in the density of the target coal seam. The change in the coal seam density will affect the wave velocity in this area. Therefore, there is a positive correlation between stress and wave velocity. By establishing a relationship function between stress and wave velocity:

[0049]

[0050] In the formula, V P represents the longitudinal wave velocity, σ represents the stress, and ψ are constants. Using this function, the stress field of the coal seam working face can be inversely obtained through the wave velocity field, and according to the dynamic change of the wave velocity field, the dynamic evolution of the stress field of the coal seam working face can be inversely obtained in real time. This is an indirect monitoring method.

[0051] Finally, use the stress distribution map generated by the DSS host 2 at the same moment to correct the stress field inversed by the DAS host 1, that is, map the stress distribution map generated by the DSS host 2 to the stress field inversed by the DAS host 1, and correct the stress values at each position. Finally, the stress field distribution of the coal seam working face at this moment is obtained as Figure 4 shown.

[0052] D. Full-time and full-space monitoring and early warning: Set an alarm threshold, continuously repeat steps B and C, long-term monitor the stress-strain spatio-temporal distribution data of the coal seam working face 8, determine the stress concentration area and the area with a large stress gradient of the coal seam working face 8. When a certain position exceeds the alarm threshold, an early warning of high-risk coal and rock dynamic disasters is given through an alarm.

[0053] The above is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and retouches can be made, and these improvements and retouches should also be regarded as the protection scope of the present invention.

Claims

1. A device for spatio-temporal monitoring and early warning of coal seam stress-dominated dynamic disasters, characterized in that, It includes a DAS host, a DSS host, multiple first armored optical fibers, multiple second armored optical fibers, and an alarm device; The multiple first armored optical fibers are arranged in the coal seam working face along the strike of the coal seam working face, and are used to acquire the vibration wave signals at different positions in the coal seam working face and feed them back to the DAS host; the multiple second armored optical fibers are arranged in the coal seam working face along the dip of the coal seam working face, and are used to acquire the strain data at the positions around each of the second armored optical fibers and feed them back to the DSS host; The DSS host is used to analyze the received strain data to obtain the stress values at the positions around each of the second armored optical fibers; the DAS host is used to perform inversion processing on the received vibration wave signals, and correct them in combination with the stress values analyzed by the DSS host, and finally obtain the overall stress field distribution of the coal seam working face; and control the alarm device to issue a warning prompt according to the stress field distribution.

2. The spatio-temporal monitoring and early warning device for coal seam stress-dominated dynamic disasters according to claim 1, wherein, The number of the first armored optical fibers is two, and the two first armored optical fibers are respectively 2m to 4m away from the nearest roadway.

3. The device for spatio-temporal monitoring and early warning of coal seam stress-dominated dynamic disasters according to claim 1, characterized in that The multiple second armored optical fibers are arranged parallel to each other and at equal intervals.

4. The spatio-temporal monitoring and early warning device for coal seam stress-dominated dynamic disasters according to claim 1, wherein It further includes an active seismic source, which is arranged in one of the roadways in the coal seam working face and is used to generate vibration wave signals.

5. The coal seam stress-dominated dynamic disaster spatio-temporal monitoring and early warning device according to claim 1, characterized in that, Each spatial resolution unit in the first armored optical fiber serves as a vibration signal receiver, and each spatial resolution unit in the second armored optical fiber serves as a strain signal receiver, and their spatial resolutions are both 1m to 2m.

6. The spatio-temporal monitoring and early warning device for coal seam stress-dominated dynamic disasters according to claim 1, characterized in that The DAS host is based on receiving and processing the Rayleigh scattering signals fed back by each first armored optical fiber, and then obtaining vibration wave signals at different positions; the DSS host receives and processes the Brillouin scattering signals fed back by each second armored optical fiber based on BOTDA, and then obtains strain data at different positions.

7. A working method of the device for spatio-temporal monitoring and early warning of coal seam stress-dominated dynamic disasters according to any one of claims 1 to 6, characterized in that, The specific steps are as follows: A. Install the dynamic disaster spatio-temporal monitoring and early warning device: At least two first bedding holes are arranged along the strike in the coal seam working face, and a first armored optical fiber is placed in each first bedding hole, and the first armored optical fiber is in close contact with the first bedding hole; Multiple second bedding holes are drilled from one of the roadways in the coal seam working face into the coal seam working face and along its dip, and a second armored optical fiber is placed in each second bedding hole, and the second armored optical fiber is in close contact with the second bedding hole; Then, both the DSS host and the DAS host are installed in the underground power distribution room, and each first armored optical fiber is connected to the DAS host, and each second armored optical fiber is connected to the DSS host; B. Data acquisition: Turn on the DAS host and the DSS host. The DAS host uses each first armored optical fiber to acquire the vibration wave signals generated by the seismic sources around the coal seam working face in real time; the DSS host uses the second armored optical fibers to acquire the strain data at the positions around each of them in real time; C. Data analysis: The DSS host calculates the received strain data at a certain moment to obtain the stress values at the same moment at different positions; and then interpolates the strain values at different positions at the same moment to generate a stress distribution map; the DAS host uses the elastic vibration wave inversion technology to process the received vibration wave signals at the same moment to obtain the wave velocity field of the coal seam working face at that moment, and then uses the wave velocity field to invert the stress field of the coal seam working face; finally, use the stress distribution map generated by the DSS host at the same moment to correct the stress field inverted by the DAS host, and finally obtain the stress field distribution of the coal seam working face at that moment; D. Full-time and full-space monitoring and early warning: Set the alarm threshold, continuously repeat steps B and C, conduct long-term monitoring on the stress-strain spatio-temporal distribution data of the coal seam working face, determine the stress concentration area and the area with a large stress gradient of the coal seam working face, and when a certain position exceeds the alarm threshold, conduct early warning of high-risk coal and rock dynamic disasters through an alarm.

8. The working method according to claim 7, characterized in that, In step C, the stress field of the coal seam working face obtained by wave velocity field inversion is specifically as follows: The coal body is a typical porous medium. The change in in-situ stress will compact the coal body, causing a change in the density of the target coal seam. The change in coal seam density will affect the wave velocity in this area, so there is a positive correlation between stress and wave velocity. By establishing a relationship function between stress and wave velocity: Wherein, V P represents the longitudinal wave velocity, σ represents the stress, and ψ are constants. By using this function, the stress field of the coal seam working face can be inversely obtained from the wave velocity field, and according to the dynamic change of the wave velocity field, the dynamic evolution of the stress field of the coal seam working face can be inversely obtained in real time.

9. The working method according to claim 7, characterized in that, In step C, the stress value is calculated based on the strain data, specifically as follows: Establish a relationship function between stress and strain: σ = f(ε) In the formula, ε represents strain, f represents the relationship function between strain and stress, and through this function, the corresponding stress value can be calculated from the strain data at each position.

10. The working method according to claim 7, characterized in that, In step C, the interpolation calculation is specifically as follows: Organize the stress values at different positions at the same moment into a numerical matrix and import it into MATLAB software. Use the griddata function in MATLAB software to complete the interpolation calculation to generate a stress distribution map.

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