A coal rock pre-fracture warning method based on electromagnetic radiation energy characteristic factor

Abstract

The application discloses a coal and rock loaded fracture precursor warning method based on electromagnetic radiation energy characteristic factors, and belongs to the technical field of disaster warning. The method first extracts the components related to coal and rock deformation in original electromagnetic radiation by using an ICEEMDAN-K-Means-IP algorithm, and calculates electromagnetic radiation energy increments in combination with the average value of the unloading environment electric field intensity; then, the electromagnetic radiation energy increments are accumulated and the first-order derivatives and Hilbert transforms thereof are respectively calculated, so as to construct loaded coal and rock electromagnetic radiation energy characteristic factors; in combination with the time-varying law of the electromagnetic radiation energy characteristic factors, the nature of the extreme points is cyclically judged to seek the starting time of the warning interval; the amplitude of the characteristic factors near the maximum points is analyzed, and the starting time of the warning interval is continuously corrected until the cutoff time is met, so that the coal and rock fracture precursor warning interval is finally obtained. The loaded fracture precursor warning method disclosed by the application can fully utilize the electromagnetic radiation energy characteristics in the coal and rock fracture process, quantize the precursor warning interval judgment method, effectively improve the coal and rock dynamic disaster prevention level, and plays a positive role in ensuring safety production.

Description

Technical Field

[0001] This invention relates to the field of early warning technology for coal and rock fracture under load, and in particular to an early warning method for coal and rock fracture under load based on electromagnetic radiation energy characteristic factors. Background Technology

[0002] The rapid development of modern society has led to a continuous increase in energy demand, resulting in a sustained increase in coal mining, a major component of the energy structure. Against this backdrop, coal mining in various countries is increasingly moving from shallow surface layers to deeper underground layers. Mining in deep environments is more prone to coal and rock dynamic disasters, which are essentially the process of coal and rock fracturing under load until they reach their compressive strength limit. To reduce the losses caused by such disasters, a two-pronged approach is needed: firstly, understanding their mechanisms; and secondly, developing disaster early warning methods. The latter is the engineering practice of the former. Only effective and concise early warning methods for coal and rock fracturing under load can better achieve the intended purpose.

[0003] Currently, there are numerous hypotheses and theories regarding the mechanism of coal and rock fracture under load, mainly including the "three-factor" theory, the impact initiation theory, and the disturbance instability theory. Although they elaborate from different perspectives, their essence is inseparable from the internal energy coupling and evolution of coal and rock. Based on these theories, scholars have proposed many early warning methods for coal and rock, most of which describe the coal and rock damage process from the perspective of mechanical parameters or their corresponding energy. While these methods have strong theoretical significance, their drawbacks in field application are also particularly significant. Therefore, in recent years, physical quantities that change with coal and rock damage and can be monitored non-contactly have also received widespread attention, especially electromagnetic radiation, whose precursor characteristics and advantages of continuous dynamic monitoring are more suitable for practical applications. However, the current explanation of the generation and energy mechanism of electromagnetic radiation is still insufficient, and the original electromagnetic radiation is affected by its inherent characteristics and includes environmental interference components. As a result, most existing related results are still only at the level of surface change laws or qualitative descriptions of physical quantities, which to some extent reduces the practical application effect of its precursor characteristics. In summary, to improve the prevention and control of coal and rock dynamic disasters, it is very important to propose an early warning method based on energy theory that quantitatively describes the precursor characteristics of coal and rock fracture under load by electromagnetic radiation changes. Summary of the Invention

[0004] To address the shortcomings of the existing technologies, this invention provides a method for early warning of coal and rock fracture under load based on electromagnetic radiation energy characteristic factors.

[0005] The technical solution adopted in this invention is a method for early warning of coal and rock fracture under load based on electromagnetic radiation energy characteristic factors. The overall process includes the following 6 steps.

[0006] Step 1: Construct the characteristic factor EF of electromagnetic radiation energy of loaded coal and rock as it varies with time t to characterize the damage development rate of loaded coal and rock. The magnitude of this factor is directly proportional to the damage development rate of coal and rock, and it can be expressed by equation (1).

[0007] EF(t) = |K(t) + jK * (t)| (1)

[0008] In the formula, K(t) is the growth rate of electromagnetic radiation energy density; K * (t) represents the growth rate of electromagnetic radiation energy density after Hilbert transformation.

[0009] Furthermore, the electromagnetic radiation energy density growth rate K(t) described in equation (1) is essentially the cumulative electromagnetic radiation energy density U. e The first derivative of can be expressed by equation (2).

[0010]

[0011] Furthermore, the cumulative electromagnetic radiation energy density U described in equation (2) e It is expressed by equation (3).

[0012]

[0013] In the formula, w e ε is the electromagnetic radiation energy density; ε is the dielectric constant of the coal and rock; E(t) is the electric field strength related to the deformation of the coal and rock; E e The value is the average electric field strength in the environment when the coal and rock are not loaded. It is obtained by collecting the spatial electric field strength data for at least 1 minute using an electromagnetic radiation meter and then calculating the average value.

[0014] Furthermore, the electric field intensity E(t) related to coal and rock deformation mentioned in equation (3) is obtained by denoising the original electric field intensity E0(t) directly collected by the electromagnetic radiation meter during the coal and rock loading process using the ICEEMDAN-K-Means-IP algorithm. This algorithm can be divided into four steps: ICEEMDAN decomposition to generate mode functions, K-Means clustering of mode functions, determination of classification attributes based on improved Pearson coefficients, and signal reconstruction. Among them, the method of determining classification attributes based on improved Pearson coefficients includes the following two strategies:

[0015] 1) The components with the largest, most maximal, and smallest Pearson coefficients should all be considered as environmental noise (noise mainly comes from sampling devices, mechanical equipment, power systems, changes in the spatial environment, etc.) and should be discarded.

[0016] 2) The component with the Pearson coefficient close to the minimum (generally the component with the second smallest Pearson coefficient) is identified as an electromagnetic radiation signal related to coal and rock deformation and should be retained.

[0017] Furthermore, the growth rate K of the electromagnetic radiation energy density after the Hilbert transformation described in equation (1) * (t) can be expressed by equation (4).

[0018]

[0019] Step 2: During the loading process of composite coal and rock, use an electromagnetic radiation instrument to monitor the change of electric field intensity in space in real time, and calculate the characteristic factor EF of electromagnetic radiation energy in real time and determine whether each time is a stationary point of the EF curve, that is, whether EF satisfies condition (5). When the condition is met at time t, time t is considered to be a stationary point of EF.

[0020]

[0021] Step 3: Determine whether the electromagnetic radiation energy characteristic factor EF at the stationary point meets the maximum value condition. If the condition is met, record the time and its corresponding EF value. Otherwise, continue to wait until the first maximum value appears. The condition that the maximum value needs to meet is shown in Equation (6).

[0022]

[0023] Step 4: Continue to determine whether EF is a stationary point at each time point until a second maximum point appears.

[0024] Step 5: Compare the EF of the first maximum point with the EF of the second maximum point, and calculate the difference between them.

[0025] Step 6: If the second EF is greater than the first EF and the difference between the two is between 0.1 and 0.25, then the time interval between these two moments can be considered as the early warning interval for coal and rock fracturing, and the loaded composite coal and rock is about to fracture. If the above conditions are not met, it proves that the first recorded moment does not belong to the early warning interval. The second maximum moment is used to replace the first maximum moment, and the above steps are continued until the early warning conditions are met, and finally the early warning interval for coal and rock fracturing is clearly defined.

[0026] The beneficial effects of adopting the above technical solution are as follows: This invention provides a method for early warning of coal and rock fracture under load based on electromagnetic radiation energy characteristic factors. It uses the ICEEMDAN-K-Means-IP algorithm to denoise the electromagnetic radiation directly collected by the electromagnetic radiation meter, thereby increasing the proportion of coal and rock related signals. It obtains the cumulative amount of electromagnetic radiation energy density by combining the average value of the electric field intensity in the environment when the coal and rock are not loaded. It constructs the characteristic factor of electromagnetic radiation energy of loaded coal and rock using the first derivative of the cumulative amount and its Hilbert transform, thereby characterizing the damage development rate of loaded coal and rock. By combining the difference between two adjacent maximum points on the time variation curve of the characteristic factor of electromagnetic radiation energy of composite coal and rock, the early warning interval of coal and rock fracture is clarified, highlighting the early warning characteristics of loaded coal and rock fracture. Attached Figure Description

[0027] Figure 1This is a flowchart of a method for early warning of coal and rock fracture under load based on electromagnetic radiation energy characteristic factors according to the present invention.

[0028] Figure 2 This is a flowchart of the method for constructing characteristic factors of electromagnetic radiation energy of loaded coal and rock according to the present invention.

[0029] Figure 3 This is a comparison chart of the noise reduction effects of the ICEEMDAN-K-Means-IP electromagnetic radiation according to an embodiment of the present invention.

[0030] Figure 4 This is a curve showing the cumulative change in electromagnetic radiation energy density of loaded coal and rock in an embodiment of the present invention.

[0031] Figure 5 This is a curve showing the variation of the electromagnetic radiation energy characteristic factor in an embodiment of the present invention.

[0032] Figure 6 This is a schematic diagram illustrating the warning effect of an embodiment of the present invention. Detailed Implementation

[0033] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0034] This embodiment takes the coal and rock fracturing process under load at a loading rate of 0.4 mm / min as an example, and utilizes the electric field strength data monitored during the loading process, according to... Figure 1 The flowchart illustrates the construction of electromagnetic radiation energy characteristic factors and the early warning method for coal and rock fracture precursors, thereby demonstrating the effectiveness of the method. The specific explanation is as follows:

[0035] Step 1: Construct the characteristic factor EF of electromagnetic radiation energy of loaded coal and rock as a function of time t. The construction process is as follows: Figure 2 As shown, the magnitude of this factor is directly proportional to the rate of coal and rock damage development, and it can be expressed by equation (1).

[0036] EF(t) = |K(t) + jK * (t)| (1)

[0037] In the formula, K(t) is the growth rate of electromagnetic radiation energy density; K * (t) represents the growth rate of electromagnetic radiation energy density after Hilbert transformation.

[0038] Furthermore, the electromagnetic radiation energy density growth rate K(t) described in equation (1) is essentially the cumulative electromagnetic radiation energy density U. e The first derivative of can be expressed by equation (2).

[0039]

[0040] Furthermore, the cumulative electromagnetic radiation energy density U described in equation (2) e It is expressed by equation (3).

[0041]

[0042] In the formula, w e ε is the electromagnetic radiation energy density; ε is the dielectric constant of the coal and rock, which is taken as 4 for ease of calculation; E(t) is the electric field strength related to the deformation of the coal and rock; E e The value is the average electric field strength in the environment when the coal and rock are not loaded. It is obtained by collecting the spatial electric field strength data for at least 1 minute using an electromagnetic radiation meter and then calculating the average value. According to the data collected and analyzed by the electromagnetic radiation meter, the average value is 163mV / m.

[0043] Furthermore, the electric field intensity E(t) related to coal and rock deformation mentioned in equation (3) is obtained by denoising the original electric field intensity E0(t) directly collected by the electromagnetic radiation meter during the coal and rock loading process using the ICEEMDAN-K-Means-IP algorithm. This algorithm can be divided into four steps: ICEEMDAN decomposition to generate mode functions, K-Means clustering of mode functions, determination of classification attributes based on improved Pearson coefficients, and signal reconstruction. Among them, the method of determining classification attributes based on improved Pearson coefficients includes the following two strategies:

[0044] 1) The components with the largest, most maximal, and smallest Pearson coefficients should all be considered as environmental noise (noise mainly comes from sampling devices, mechanical equipment, power systems, changes in the spatial environment, etc.) and should be discarded.

[0045] 2) The component with the Pearson coefficient close to the minimum (generally the component with the second smallest Pearson coefficient) is identified as an electromagnetic radiation signal related to coal and rock deformation and should be retained.

[0046] The electromagnetic radiation intensity curves of coal and rock before and after noise reduction are as follows: Figure 3 As shown, by Figure 3 It is evident that the ICEEMDAN-K-Means-IP algorithm has a good denoising effect on electromagnetic radiation and can effectively restore the original signal, which is beneficial for obtaining the value of electromagnetic radiation energy more accurately.

[0047] Figure 4 The cumulative energy density of electromagnetic radiation, U e The curves showing the change over time reveal that the cumulative amount of electromagnetic radiation energy increases continuously over time at different rates.

[0048] Furthermore, the growth rate K of the electromagnetic radiation energy density after the Hilbert transformation described in equation (1) * (t) can be expressed by equation (4).

[0049]

[0050] Figure 5 The figure shows the variation curve of the characteristic factor EF of electromagnetic radiation energy of loaded coal and rock. As can be seen from the figure, the variation is complex and the damage development rate of coal and rock is different at different times. The maximum value of EF is 0.4131 at the end of the loading period of coal and rock, which is 217s. At this time, the damage development rate of coal and rock is the largest and the coal and rock are close to fracturing.

[0051] Step 2: During the composite coal and rock loading process, the change in electric field intensity in space is monitored in real time using an electromagnetic radiation meter, and the characteristic factor EF of electromagnetic radiation energy is calculated in real time. It is then determined whether each time point is a stationary point of the EF curve, i.e., whether EF satisfies condition (5). If the condition is met at time t, then time t is considered a stationary point of EF. Figure 5 It can be seen that there are a total of 6 outposts.

[0052]

[0053] Step 3: Determine whether the electromagnetic radiation energy characteristic factor EF at the stationary point satisfies the maximum condition. If the condition is met, record the time and its corresponding EF value; otherwise, continue waiting until the first maximum value appears. The condition for the maximum value to be satisfied is shown in equation (6). Figure 5 As can be seen, the first maximum value is at 95s, and the EF value is 0.0438.

[0054]

[0055] Step 4: Continue to determine whether EF is a stationary point at each time until the second maximum point appears. The second maximum point is at 141s, at which time EF is 0.3018.

[0056] Step 5: Compare the EF of the first maximum point with the EF of the second maximum point, and calculate the difference between them. The difference is 0.2580.

[0057] Step 6: If the second EF is greater than the first EF and the difference between the two is between 0.1 and 0.25, then the time interval between these two moments can be considered as the early warning interval for coal and rock fracturing, and the loaded composite coal and rock is about to fracture. If the above conditions are not met, it proves that the first recorded moment does not belong to the early warning interval. The second maximum moment is used to replace the first maximum moment, and the above steps are continued until the early warning conditions are met, and finally the early warning interval for coal and rock fracturing is clearly defined.

[0058] Depend on Figure 5It can be seen that the difference between the first and second maximum points is greater than 0.25, so this period is not a warning period. The difference between the second and third maximum points (at 217s) is 0.1113, which is between 0.1 and 0.25. Therefore, the period between the second and third maximum points is a warning interval, and the warning period is from 141s to 217s, a total of 76s.

[0059] Figure 6 The diagram shows the corresponding early warning time on the stress curve. It can be seen that the early warning interval is significantly earlier than the 225s of coal and rock fracturing, and the warning time width is reasonable, which can better achieve the expected goal. This also verifies the effectiveness of the electromagnetic radiation energy characteristic factor EF constructed in this invention for early warning of loaded coal and rock fracturing.

[0060] Although the present invention has been disclosed above with reference to preferred embodiments, these are not intended to limit the invention. Any person skilled in the art can make various changes or modifications without departing from the spirit and scope of the invention. Therefore, the scope of protection of the present invention should be defined by the scope of the claims of this application.

Claims

1. A method for early warning of coal and rock fracture under load based on electromagnetic radiation energy characteristic factors, characterized in that, This method includes the following 6 steps: Step 1: Use the ICEEMDAN-K-Means-IP algorithm to denoise the original electric field intensity E0(t) directly collected by the electromagnetic radiation meter during the coal and rock loading process to obtain the electric field intensity E(t) related to the deformation of coal and rock. Construct the characteristic factor EF of electromagnetic radiation energy of loaded coal and rock that varies with time t to characterize the damage development rate of loaded coal and rock. The magnitude of this factor is directly proportional to the damage development rate of coal and rock, and it is expressed by equation (1). EF(t)=|K(t)+jK * (t)| (1) In the formula, K(t) is the growth rate of electromagnetic radiation energy density; K * (t) represents the growth rate of electromagnetic radiation energy density after Hilbert transformation; Step 2: During the loading process of composite coal and rock, use an electromagnetic radiation instrument to monitor the change of electric field intensity in space in real time, and calculate the characteristic factor EF of electromagnetic radiation energy in real time and determine whether each time is a stationary point of the EF curve, that is, whether EF satisfies condition (5). When the condition is met at time t, it is determined that time t is a stationary point of EF. Step 3: Determine whether the electromagnetic radiation energy characteristic factor EF at the stationary point meets the maximum value condition. If the condition is met, record the time and its corresponding EF value. Otherwise, continue to wait until the first maximum value appears. The maximum value needs to meet the condition shown in Equation (6). Step 4: Continue to determine whether EF is a stationary point at each time point until a second maximum point appears; Step 5: Compare the EF of the first maximum point with the EF of the second maximum point, and calculate the difference between them; Step 6: Determine the early warning range for coal and rock fracture under load through difference characteristics; The electromagnetic radiation energy density growth rate K(t) in step 1 is essentially the cumulative electromagnetic radiation energy density U. e The first derivative of is expressed by equation (2), and the growth rate of electromagnetic radiation energy density after Hilbert transformation is K. * (t) is expressed by equation (4); In the formula, U e The cumulative amount of electromagnetic radiation energy density is expressed by equation (3); In the formula, w e ε is the electromagnetic radiation energy density; E is the dielectric constant of the coal and rock; e The value is the average electric field strength in the environment when the coal and rock are not loaded. It is obtained by collecting the spatial electric field strength data for at least 1 minute using an electromagnetic radiation meter and then calculating the average value.

2. The method for early warning of coal and rock fracture under load based on electromagnetic radiation energy characteristic factors according to claim 1, characterized in that, The ICEEMDAN-K-Means-IP algorithm consists of four steps: ICEEMDAN decomposition to generate mode functions, K-Means clustering of mode functions, determination of classification attributes based on improved Pearson coefficients, and signal reconstruction. The method for determining classification attributes based on improved Pearson coefficients includes the following two strategies: 1) The components with the largest, most maximal, and smallest Pearson coefficients should all be considered as environmental noise (noise mainly comes from sampling devices, mechanical equipment, power systems, and changes in the spatial environment) and should be discarded; 2) The component with the Pearson coefficient closest to the minimum (the second smallest component of the Pearson coefficient) is identified as an electromagnetic radiation signal related to coal and rock deformation and should be retained.

3. The method for early warning of coal and rock fracture under load based on electromagnetic radiation energy characteristic factors according to claim 1, characterized in that, The method for determining the early warning interval in step 6 is as follows: The maximum points at both ends of the warning interval must satisfy the condition that the second electromagnetic radiation energy characteristic factor EF is greater than the first EF and the difference between the two is between 0.1 and 0.

25. If these two times are considered to be the warning interval for coal and rock fracturing, and the loaded composite coal and rock is about to fracture, then the warning interval is considered to be between these two times. If the above conditions are not met, it is proven that the time of the first record does not belong to the warning interval. The second maximum time is used to replace the first maximum time to continue to find the second maximum point until the warning conditions are met and the warning interval is clearly defined.

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