Deep coal and rock mass instability dynamic multi-parameter evaluation method and device based on microseism

Abstract

The invention relates to the technical field of mine coal and rock dynamic disaster prevention and control, in particular to a micro-seismic-based deep coal and rock mass instability dynamic multi-parameter evaluation method. The method comprises the following steps: acquiring waveform data of each micro-seismic event of a deep coal and rock mass through a mine micro-seismic system; according to the waveform data, acquiring a micro-seismic characteristic index set of each micro-seismic event; according to the seismic source position and the micro-seismic characteristic index set of each micro-seismic event, acquiring an energy-based micro-seismic magnitude; according to the micro-seismic magnitude, obtaining a micro-seismic b value corresponding to a preset duration, and according to the micro-seismic characteristic index set, obtaining a micro-fracture type and change trend information of accumulated energy of each micro-seismic event; and according to the micro-seismic energy, the change trend information of the accumulated energy, the frequency, the ringing count, the micro-fracture type and the micro-seismic b value, the dynamic instability fracture risk information of the deep coal and rock mass is obtained. According to the invention, the determination accuracy and efficiency of the instability and fracture risk information can be improved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of mine coal rock dynamic disaster prevention, and particularly relates to a deep coal rock mass instability dynamic multi-parameter evaluation method based on microseism. BACKGROUND

[0002] The increasing mining depth and mining intensity of a mine lead to a very poor ground stress field environment of a coal rock mass, and the mining of deep high-quality coal resources faces a high-risk coal rock mass dynamic instability, and a safe and efficient mining problem is increasingly highlighted. Once the risk assessment is inaccurate, the coal rock mass instability is extremely likely to be induced, and inestimable damage and loss are caused. Therefore, the evaluation and early warning of the deep coal rock mass instability are crucial to the safety production of a coal mine. SUMMARY

[0003] The present disclosure provides a deep coal rock mass instability dynamic multi-parameter evaluation method based on microseism, which can improve the determination accuracy and efficiency of instability and fracture risk information, and further improve the accuracy of providing early warning information for the prevention and control of dynamic disasters in the process of coal mining. The technical solution of the present disclosure is as follows:

[0004] According to a first aspect of an embodiment of the present disclosure, a deep coal rock mass instability dynamic multi-parameter evaluation method based on microseism is provided, comprising:

[0005] Waveform data of each microseismic event of a deep coal rock mass is obtained through a mine microseismic system;

[0006] According to the waveform data, a microseismic characteristic index set of each microseismic event is obtained, wherein the microseismic characteristic index set includes a ringing count, an amplitude, a duration, a rise time, an energy, and a frequency of a microseismic signal;

[0007] According to the hypocenter location of each microseismic event and the microseismic characteristic index set, an energy-based microseismic magnitude is obtained;

[0008] According to the microseismic magnitude and the frequency, a microseismic b value corresponding to a preset time length is obtained, and according to the microseismic characteristic index set, a microfracture type and change trend information of cumulative energy are obtained;

[0009] According to the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type, and the microseismic b value, dynamic instability and fracture risk information of the deep coal rock mass is obtained.

[0010] According to some embodiments, the method further comprises:

[0011] Long-time waveform data recorded by a plurality of measuring devices for a deep coal rock mass is obtained, wherein the measuring devices include a probe and a geophone;

[0012] The waveform data in the long-time waveform data that meets the data requirement is taken as the waveform data of each microseismic event;

[0013] According to the waveform data of each microseismic event, the arrival time corresponding to each probe is obtained;

[0014] According to the probe position of each probe and the arrival time corresponding to each probe, the hypocenter position of the microseismic event is obtained.

[0015] According to some embodiments, the obtaining of the microseismic characteristic index set of each microseismic event according to the waveform data comprises:

[0016] The amplitude corresponding to the waveform data is obtained;

[0017] The ring count is obtained according to the threshold value corresponding to the waveform data and the waveform data;

[0018] The rising time is obtained according to the first time point corresponding to the amplitude and the second time point in the waveform data, wherein the second time point is the time point at which the threshold value is reached for the first time in the waveform data;

[0019] The duration is obtained according to the second time point and the third time point in the waveform data, wherein the third time point is the time point at which the threshold value is reached for the last time in the waveform data;

[0020] The energy is obtained according to the distance between the hypocenter position of the microseismic event and the probe in the mine microseismic system, the information of the deep coal rock mass, and the particle vibration velocity time history;

[0021] The frequency is obtained according to the waveform data, wherein the frequency includes the microseismic frequency and the peak frequency.

[0022] According to some embodiments, the obtaining of the energy-based microseismic magnitude according to the hypocenter position of each microseismic event and the microseismic characteristic index set comprises:

[0023] The hypocentral distance of each microseismic event is obtained according to the hypocenter position of each microseismic event and the energy;

[0024] The energy-based microseismic magnitude is obtained according to the hypocentral distance.

[0025] According to some embodiments, the obtaining of the microseismic b value corresponding to a preset time and the microfracture type according to the microseismic characteristic index set comprises:

[0026] The number of microseismic magnitudes greater than a preset magnitude in the monitoring range of the deep coal rock mass is obtained, and the number is taken as the frequency;

[0027] According to the number of microseisms with magnitudes greater than a preset magnitude and the preset magnitude, a microseismic b value corresponding to a preset time length is obtained;

[0028] An AF value and an RA value are obtained, and a microfracture type is obtained according to the AF value and the RA value, wherein the AF value is a ratio of the ringing count and the duration, and the RA value is a ratio of the rise time and the amplitude.

[0029] According to some embodiments, the deep coal rock mass dynamic instability rupture risk information is obtained according to the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type and the microseismic b value, comprising:

[0030] In a case where the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type and the microseismic b value all meet the risk requirement, it is determined that the deep coal rock mass dynamic instability rupture risk information is less than a first preset risk value;

[0031] In a case where the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type and the microseismic b value all do not meet the risk requirement, it is determined that the deep coal rock mass dynamic instability rupture risk information is greater than a second preset risk value, wherein the first preset risk value is less than the second preset risk value;

[0032] In a case where part of the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type and the microseismic b value do not meet the risk requirement, it is determined that the deep coal rock mass dynamic instability rupture risk information is between the first preset risk value and the second preset risk value, and a fuzzy comprehensive algorithm is used to obtain a deep coal rock mass dynamic instability rupture risk level.

[0033] According to some embodiments, the deep coal rock mass dynamic instability rupture risk level is obtained by using the fuzzy comprehensive algorithm, comprising:

[0034] According to the information of the deep coal rock mass, a weight set is obtained, wherein the weight set includes a first weight corresponding to the energy of the microseism, a second weight corresponding to the change trend information of the cumulative energy, a third weight corresponding to the frequency, a fourth weight corresponding to the ringing count, a fifth weight corresponding to the microfracture type and a sixth weight corresponding to the microseismic b value;

[0035] According to the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ring count, the microfracture type, and the microseismic b value, and the weight set, a dynamic instability fracture risk level of the deep coal rock mass is obtained.

[0036] According to a second aspect of the embodiments of the present disclosure, a device for evaluating deep coal rock mass instability based on microseism is provided, comprising:

[0037] A data acquisition unit is configured to acquire waveform data of each microseismic event of the deep coal rock mass through a mine microseismic system.

[0038] A set acquisition unit is configured to acquire a microseismic characteristic index set of each microseismic event according to the waveform data, wherein the microseismic characteristic index set comprises a ring count, an amplitude, a duration, a rise time, an energy, and a frequency of a microseismic signal.

[0039] A magnitude acquisition unit is configured to acquire an energy-based microseismic magnitude according to a hypocenter location of each microseismic event and the microseismic characteristic index set.

[0040] The data acquisition unit is further configured to acquire a microseismic b value corresponding to a preset time length according to the microseismic magnitude and a frequency, and to acquire a microfracture type and change trend information of cumulative energy according to the microseismic characteristic index set.

[0041] A risk evaluation unit is configured to acquire dynamic instability fracture risk information of the deep coal rock mass according to the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ring count, the microfracture type, and the microseismic b value.

[0042] According to a third aspect of the embodiments of the present disclosure, an electronic device is provided, comprising:

[0043] A processor;

[0044] A memory for storing instructions executable by the processor;

[0045] The processor is configured to execute the instructions to implement the method for evaluating deep coal rock mass instability based on microseism according to any one of the preceding aspects.

[0046] According to a fourth aspect of the embodiments of the present disclosure, a storage medium is provided, when instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method for evaluating deep coal rock mass instability based on microseism according to any one of the preceding aspects.

[0047] According to a fifth aspect of the embodiments of the present disclosure, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the method of any one of the preceding aspects.

[0048] The technical solutions provided by the embodiments of the present disclosure bring at least the following beneficial effects:

[0049] In some or related embodiments, waveform data of each microseismic event of a deep coal rock mass is acquired by a mine microseismic system; a microseismic characteristic index set of each microseismic event is acquired according to the waveform data, wherein the microseismic characteristic index set includes ringing count, amplitude, duration, rise time, energy, and frequency of a microseismic signal; an energy-based microseismic magnitude is acquired according to the hypocenter location of each microseismic event and the microseismic characteristic index set; a microseismic b value corresponding to a preset time length is acquired according to the microseismic magnitude and frequency, and a microfracture type and change trend information of cumulative energy are acquired according to the microseismic characteristic index set; and dynamic instability and fracture risk information of the deep coal rock mass is acquired according to the energy of the microseismic event, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type, and the microseismic b value. Therefore, the dynamic instability and fracture risk information of the deep coal rock mass can be determined by the acquired parameters, the evaluation inaccuracy caused by the evaluation only from the pressure appearance feature in the macroscopic characteristics can be reduced, the situation that the precursor feature of the coal rock instability is not obvious can be reduced, the situation that the data acquisition is not timely leads to a large delay of early warning or risk evaluation can be reduced, real-time evaluation can be performed by the waveform data of the microseismic event, the evaluation efficiency can be improved, the cost, time length, and steps of determining the instability and fracture risk information can be reduced, the determination accuracy and efficiency of the instability and fracture risk information can be improved, and thus the accuracy of providing early warning information for the dynamic disaster prevention in the process of coal mining can be improved.

[0050] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and do not limit the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0051] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure and do not limit the present disclosure.

[0052] Figure 1 is a flowchart of a first deep coal rock mass instability dynamic multi-parameter evaluation method based on microseismic events provided by the embodiments of the present disclosure;

[0053] Figure 2 is a flowchart of a second deep coal rock mass instability dynamic multi-parameter evaluation method based on microseismic events provided by the embodiments of the present disclosure;

[0054] Figure 3 is a flowchart of a third microseismic-based deep coal rock mass instability dynamic multi-parameter evaluation method provided by the embodiments of the present disclosure;

[0055] Figure 4 is an example schematic diagram of waveform data provided by the embodiments of the present disclosure;

[0056] Figure 5 is a block diagram of a microseismic-based deep coal rock mass instability dynamic multi-parameter evaluation device according to an exemplary embodiment;

[0057] Figure 6 is an example schematic diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0058] In order for those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be described clearly and completely below with reference to the drawings.

[0059] The embodiments of the present disclosure propose a microseismic-based deep coal rock mass instability dynamic multi-parameter evaluation method, device, electronic device and storage medium. In some embodiments, the microseismic-based deep coal rock mass instability dynamic multi-parameter evaluation method and the information processing method, communication method and other terms can be mutually replaced, the microseismic-based deep coal rock mass instability dynamic multi-parameter evaluation device and the information processing device, communication device and other terms can be mutually replaced, and the information processing system, communication system and other terms can be mutually replaced.

[0060] The embodiments of the present disclosure are not exhaustive, but only illustrate some embodiments, and are not specific limitations on the protection scope of the present disclosure. In the case of no contradiction, each step in an embodiment can be implemented as an independent embodiment, and the steps can be combined arbitrarily, for example, the scheme after removing some steps in an embodiment can also be implemented as an independent embodiment, and the order of the steps in an embodiment can be exchanged arbitrarily, in addition, the optional implementation manners in an embodiment can be combined arbitrarily; in addition, the embodiments can be combined arbitrarily, for example, the steps of different embodiments or part of the steps of different embodiments can be combined arbitrarily, and an embodiment can be combined with the optional implementation manners of other embodiments.

[0061] In each embodiment of the present disclosure, the terms and / or descriptions between the embodiments are consistent if there is no special description and logical conflict, and can be referred to each other, and the technical features in different embodiments can be combined to form new embodiments according to their inherent logical relationship.

[0062] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments, and not as a limitation on the present disclosure.

[0063] In the embodiments of the present disclosure, an element expressed in singular form, such as "a", "an", "the", "said", "the aforementioned", "the foregoing", "this", and the like, unless otherwise specified, can represent "one and only one", or can represent "one or more", "at least one", and the like. For example, in the case of using an article such as "a", "an", "the" in English, the noun after the article can be understood as a singular expression, or can be understood as a plural expression.

[0064] In the embodiments of the present disclosure, "plurality" refers to two or more.

[0065] In some embodiments, the terms "at least one of", "one or more", "a plurality of", "multiple", and the like can be replaced with each other.

[0066] The prefix words "first", "second", and the like in the embodiments of the present disclosure are merely used to distinguish different description objects, and do not constitute a limitation on the position, order, priority, quantity, or content of the description objects. The description of the description objects should be referred to the description in the claims or embodiments, and should not be limited by the prefix words. For example, the description objects are "fields", and the ordinal words before "fields" in "first field" and "second field" do not limit the position or order between "fields", and "first" and "second" do not limit whether the "fields" modified thereby are in the same message, or limit the order of "first field" and "second field". For another example, the description objects are "levels", and the ordinal words before "levels" in "first level" and "second level" do not limit the priority between "levels". For another example, the quantity of the description objects is not limited by the ordinal words, and can be one or more. For example, "first device" is taken as an example, and the quantity of "devices" can be one or more. In addition, the objects modified by different prefix words can be the same or different, for example, the description objects are "devices", and "first device" and "second device" can be the same device or different devices, and the types thereof can be the same or different. For another example, the description objects are "information", and "first information" and "second information" can be the same information or different information, and the content thereof can be the same or different.

[0067] In some embodiments, a "terminal" or "terminal device" can be referred to as a "user equipment" (UE), a "user terminal," a "mobile station" (MS), a "mobile terminal" (MT), a subscriber station, a mobile unit, a subscriber unit, a wireless unit, a remote unit, a mobile device, a wireless device, a wireless communication device, a remote device, a mobile subscriber station, an access terminal, a mobile terminal, a wireless terminal, a remote terminal, a handset, a user agent, a mobile client, a client, etc.

[0068] In some embodiments, data, information, etc. can be acquired after consent from a user is obtained.

[0069] It should be noted that the terms "first", "second", and the like, herein do not necessarily have an ordinal, sequential, or chronologic implication, but are used to differentiate one element from another. It is to be understood that the terms so used in the description and the claims are interchangeable under appropriate circumstances. The embodiments described herein are not meant to limit the application of the present disclosure to any particular embodiments described. Rather, the embodiments are intended to cover all applications of the present disclosure, whether or not they are within the scope of the embodiments described herein. The following exemplary embodiments are described in terms of exemplary implementations, procedures, and techniques. These implementations, procedures, and techniques, as well as others, are meant to encompass all suitable methods of accomplishing the described functions and steps. Other embodiments of the present disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the present disclosure.

[0070] According to some embodiments, the evaluation of dynamic instability of coal rock mass in coal mines mainly includes theoretical analysis, mine pressure monitoring and electromagnetic monitoring method. Theoretical analysis refers to a method of estimating pressure behavior characteristics and evaluating the risk of instability of coal rock mass through key stratum theory; mine pressure monitoring refers to a method of evaluating mine pressure behavior characteristics and predicting the risk of impact by monitoring parameters such as roadway deformation, roof and floor convergence, support resistance, etc., and mine pressure monitoring is one of the most widely used methods due to its convenient testing; electromagnetic monitoring is a method of monitoring ground sound, seismic wave tomography, microseismicity, etc., and the current coal mine uses a single system to evaluate a small number of parameters.

[0071] Among them, the evaluation result obtained by theoretical calculation is a rough estimate based on a wide range of mine, which is difficult to evaluate the real-time dynamic instability of coal rock mass. The roadway deformation and roof pressure of mine pressure monitoring are macroscopic characteristics, and the precursor characteristics of coal rock instability are not obvious, and the regular statistical process is relatively complicated, so that effective early warning information cannot be obtained in time. Electromagnetic monitoring can obtain a large number of micro activity characteristics and available early warning information of coal rock mass by monitoring physical parameters such as ground sound, acoustic wave and microseismicity during mining process, so as to evaluate the risk of instability and fracture of coal rock, but the evaluation parameters are single and the early warning effect is poor.

[0072] Figure 1 is a flow chart of a first deep coal rock mass instability dynamic multi-parameter evaluation method based on microseismicity provided by the embodiment of the present disclosure, as shown in Figure 1 The deep coal rock mass instability dynamic multi-parameter evaluation method based on microseismicity can be used in the scene of dynamic instability evaluation of deep high-quality coal resources in the process of coal mining, including the following steps:

[0073] In step S11, the waveform data of each microseismic event of the deep coal rock mass is obtained through the mine microseismic system;

[0074] In some embodiments, the execution subject of the embodiment of the present disclosure can be an electronic device, for example. The electronic device is not specific to a fixed electronic device. For example, when the device identity changes, the electronic device can also change accordingly. For example, when the structure of the electronic device changes, the electronic device can also change accordingly. Among them, the execution subject of the embodiment of the present disclosure can also be a server, which can be a single server or a server cluster, and the present disclosure does not limit it.

[0075] In some embodiments, the mine microseismic system may, for example, be a system for monitoring and data acquisition of deep coal rock mass. The mine microseismic system may, for example, be composed of a plurality of measuring devices. The measuring device may, for example, include a plurality of probes and a seismometer. The seismometer may, for example, also be referred to as a seismograph. The location of the plurality of measuring devices may, for example, be referred to as a station, i.e., the station is a place where a strong motion accelerometer is arranged for strong motion monitoring. The mine microseismic system does not refer to a specific fixed system. For example, when the number of measuring devices corresponding to the mine microseismic system changes, the mine microseismic system may also change accordingly. For example, when any probe included in the mine microseismic system changes, the mine microseismic system may also change accordingly.

[0076] According to some embodiments, the deep coal rock mass may, for example, be a coal rock mass to be monitored. The monitored part may, for example, be the entire coal rock mass, or a coal rock mass within a preset range. For example, the near-field coal rock mass range may be monitored.

[0077] In some embodiments, each microseismic event may, for example, be an event in which microseismicity is monitored. The microseismicity may, for example, refer to a small vibration caused by rock rupture or fluid disturbance. The microseismicity in the embodiments of the present disclosure may, for example, be a case where a small vibration occurs in the deep coal rock mass. The microseismic event may, for example, also be referred to as a microfracture event or a fracture event. The embodiments of the present disclosure do not limit this.

[0078] According to some embodiments, the microseismic data may, for example, be data collected when each microseismic event occurs. The microseismic data does not refer to a specific fixed data. For example, when the deep coal rock mass changes, the microseismic data may also change accordingly. For example, when the time point of monitoring the microseismic event changes, the microseismic data may also change accordingly.

[0079] According to some embodiments, the waveform data may, for example, be data obtained in the form of a waveform corresponding to each microseismic event. The waveform data does not refer to a specific fixed data. For example, when the shape of the waveform data changes, the waveform data may also change accordingly. For example, when a certain data in the waveform data changes, the waveform data may also change accordingly.

[0080] In some embodiments, the waveform data of each microseismic event of the deep coal rock mass may be obtained through the mine microseismic system.

[0081] In step S12, according to the waveform data, a microseismic characteristic index set of each microseismic event is obtained, wherein the microseismic characteristic index set includes a ringing count, an amplitude, a duration, a rise time, an energy, and a frequency of the microseismic signal;

[0082] In some embodiments, the microseismic feature index set may, for example, be a collection aggregated from at least one microseismic feature index. The microseismic feature index set does not refer to a fixed set. For example, when the index type corresponding to the microseismic feature index set changes, the microseismic feature index set may also change accordingly. For example, when the value of an index in the microseismic feature index set changes, the microseismic feature index set may also change accordingly.

[0083] In some examples, the microseismic feature index set may, for example, include the ring count, amplitude, duration, rise time, energy, and frequency of the microseismic signal. The ring count may, for example, be the number of times the acoustic emission signal crosses a threshold value. The ring count does not refer to a fixed value. For example, when the waveform data or the threshold value changes, the ring count may also change accordingly. The amplitude may, for example, be the maximum absolute value of the acoustic emission signal. The duration may, for example, be the duration of the acoustic emission signal that exceeds the threshold value. The rise time may, for example, be the time between the first time the acoustic emission signal reaches the threshold value and the amplitude. The energy may, for example, be the energy corresponding to the acoustic emission signal.

[0084] In some embodiments, the microseismic feature index set of each microseismic event may, for example, be obtained according to the waveform data, wherein the microseismic feature index set includes the ring count, amplitude, duration, rise time, energy, and frequency of the microseismic signal.

[0085] The specific indexes included in the microseismic feature index set may, for example, be determined according to the current measurement scene or an index setting instruction. The measurement scene may, for example, include the measurement range or the measured coal rock mass.

[0086] In step S13, an energy-based microseismic magnitude is obtained according to the source location of each microseismic event and the microseismic feature index set.

[0087] According to some embodiments, the source location of the microseismic event may, for example, refer to the location of the source of the current microseismic event. The source location of the microseismic event does not refer to a fixed location. For example, when the collected waveform data changes, the source location of the microseismic event may also change accordingly. For example, when the determination method of the source location of the microseismic event changes, the source location of the microseismic event may also change accordingly.

[0088] In some embodiments, the microseismic magnitude may, for example, be used to indicate the level of the current microseismic event. The microseismic magnitude does not refer to a fixed magnitude. For example, when the data used to determine the microseismic magnitude changes, the microseismic magnitude may also change accordingly. For example, when the setting parameters corresponding to the microseismic magnitude change, the microseismic magnitude may also change accordingly.

[0089] According to some embodiments, an energy-based microseismic magnitude can be obtained according to the hypocenter location and the microseismic characteristic index set of each microseismic event.

[0090] In step S14, a microseismic b value corresponding to a preset time length is obtained according to the microseismic magnitude and the frequency, and a microfracture type and change trend information of cumulative energy are obtained according to the microseismic characteristic index set.

[0091] According to some embodiments, the microseismic b value may, for example, be a b value calculated by microseismic monitoring data, used to describe the statistical characteristics of seismic activity. The microseismic b value does not specifically refer to a fixed value. For example, when the acquisition method corresponding to the microseismic b value changes, the microseismic b value can also change accordingly. For example, when the microseismic magnitude or the frequency changes, the microseismic b value can also change accordingly. The frequency may, for example, be the number of microseismic magnitudes greater than a preset magnitude.

[0092] In some embodiments, the microfracture type may, for example, be used to indicate the type of the current microfracture, that is, the fracture type of the deep coal rock mass corresponding to the current microseismic event. The microfracture type may, for example, be determined by the energy release and sound wave propagation mechanism of tensile-shear fracture, and the microfracture type may, for example, include the damage types of tensile cracks and shear cracks. Specifically, the microfracture type may, for example, include a tensile-dominant microfracture type, a tensile-shear composite microfracture type, and a shear fracture microfracture type.

[0093] In some embodiments, the change trend information of cumulative energy may, for example, be the change information of the cumulative energy of the energy of some microseismic events.

[0094] In some embodiments, a microseismic b value corresponding to a preset time length is obtained according to the microseismic magnitude and the frequency, and a microfracture type and change trend information of cumulative energy are obtained according to the microseismic characteristic index set.

[0095] In step S15, dynamic instability fracture risk information of the deep coal rock mass is obtained according to the energy of the microseismic, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type, and the microseismic b value.

[0096] In some embodiments, dynamic instability fracture risk information of the deep coal rock mass can be obtained according to the energy of the microseismic, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type, and the microseismic b value. The dynamic instability fracture risk information of the deep coal rock mass is used to indicate the risk information of the fracture of the deep coal rock mass. The dynamic instability fracture risk information of the deep coal rock mass does not specifically refer to a fixed information. For example, when any one of the energy of the microseismic, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type, and the microseismic b value changes, the risk information of the fracture of the deep coal rock mass can also change accordingly.

[0097] In some or related embodiments, waveform data of each microseismic event of the deep coal rock mass is acquired by a mine microseismic system; a microseismic characteristic index set of each microseismic event is acquired according to the waveform data, wherein the microseismic characteristic index set includes ringing count, amplitude, duration, rise time, energy, and frequency of the microseismic signal; an energy-based microseismic magnitude is acquired according to the hypocenter location and the microseismic characteristic index set of each microseismic event; a microseismic b value corresponding to a preset time length is acquired according to the microseismic magnitude and frequency, and a microfracture type and a change trend information of cumulative energy are acquired according to the microseismic characteristic index set; and dynamic instability and fracture risk information of the deep coal rock mass is acquired according to the energy, the change trend information of cumulative energy, the frequency, the ringing count, the microfracture type, and the microseismic b value of the microseismic event. Therefore, the dynamic instability and fracture risk information of the deep coal rock mass can be determined by the acquired parameters, the evaluation inaccuracy caused by the evaluation only from the pressure appearance feature in the macroscopic characteristics can be reduced, the situation that the precursor feature of the coal rock instability is not obvious and the data collection is not timely to cause a large delay in the early warning or risk evaluation can be reduced, the real-time evaluation can be performed by the waveform data of the microseismic event, the evaluation efficiency can be improved, the cost, time length, and steps of the instability and fracture risk information determination can be reduced, the determination accuracy and efficiency of the instability and fracture risk information can be improved, and thus the accuracy of the early warning information provided for the dynamic disaster prevention in the process of the coal mining can be improved.

[0098] Figure 2 is a flowchart of a second microseismic-based deep coal rock mass instability dynamic multi-parameter evaluation method provided by the embodiments of the present disclosure, as shown in Figure 2 The microseismic-based deep coal rock mass instability dynamic multi-parameter evaluation method can be used in the evaluation scene of the microfracture characteristics around the coal rock mass in the mining area, and includes the following steps:

[0099] In step S21, waveform data of each microseismic event of the deep coal rock mass is acquired by a mine microseismic system;

[0100] The related descriptions are as described above, and will not be repeated here.

[0101] According to some embodiments, Figure 3 is a flowchart of a third microseismic-based deep coal rock mass instability dynamic multi-parameter evaluation method provided by the embodiments of the present disclosure, as shown in Figure 3As shown, the micro-fracture characteristics of the coal rock mass can be monitored by the mine microseismic system, and the microseismic data of the coal rock mass can be acquired, recorded and stored. The microseismic data may, for example, be waveform data. The mine with a dynamic disaster risk has, for example, installed a mine seismic monitoring system, i.e., a mine microseismic system, the analysis of the mine seismic data includes global monitoring and local early warning, and the embodiments of the present disclosure may, for example, be described by taking the stope with a high dynamic disaster risk and the near-field range around the stope as examples. In the case of clearly monitoring the deep coal rock mass, the seismometer and the sensor probe can be placed at the corresponding coordinate positions, the microseismic waveform characteristic information induced by the coal body fracture in the mining process can be monitored by the mine microseismic system, and the waveform data of each microseismic event can be recorded and stored.

[0102] According to some embodiments, the method further comprises:

[0103] acquiring long-time waveform data recorded by the plurality of measuring devices for the deep coal rock mass, wherein the measuring devices include probes and seismometers;

[0104] taking each waveform data in the long-time waveform data that meets the data requirement as the waveform data of each microseismic event;

[0105] acquiring the arrival time corresponding to each probe according to the waveform data of each microseismic event;

[0106] acquiring the hypocenter position of the microseismic event according to the probe position of each probe and the arrival time corresponding to each probe. Therefore, the hypocenter position can be determined according to the data corresponding to the plurality of probes, the accuracy of the determination of the hypocenter position is improved, and the accuracy of the dynamic determination of the instability of the deep coal rock mass is improved.

[0107] In some embodiments, the first arrival time of the microseismic signal can be acquired according to the positions of the seismometer and the plurality of probes and the coal rock mass wave velocity characteristics calibrated by the mine, and the hypocenter position can be located based on the time difference method according to the first arrival times among the plurality of probes. For example, the following can be included:

[0108] According to the long-time waveform data of the deep coal rock mass recorded by the plurality of stations (probes and seismometers) and the set passive acoustic signal threshold value, when the amplitude of the waveform data exceeds the set threshold value, it is considered that an effective microseismic activity event, i.e., a microseismic event, is generated. According to the waveform characteristics of each effective microseismic event, the arrival time of the monitoring waveform of each probe is identified, and the coordinate values (x, y, z) of the hypocenter position of the microseismic event are calculated according to the probe position and the time difference method algorithm.

[0109]

[0110] In the formula, x i , y i , and z irespectively, is the coordinate point of the i th station; v is the calibrated wave velocity of the coal body, and the source position of the microseismic event is inversely calculated by minimizing the time difference through a plurality of position and wave velocity relationships.

[0111] In step S22, a microseismic feature index set of each microseismic event is obtained according to the waveform data, wherein the microseismic feature index set includes the ring count, amplitude, duration, rise time, energy and frequency of the microseismic signal.

[0112] The related descriptions are as described above, and will not be repeated here.

[0113] In some embodiments, Figure 4 is an example schematic diagram of waveform data provided by the embodiments of the present disclosure, as Figure 4 As shown, a microseismic feature index set of each microseismic event can be obtained according to the waveform data. That is, according to the waveform features, the ring count, amplitude, duration, rise time, energy and peak frequency of the microseismic signal can be picked up.

[0114] According to some embodiments, obtaining a microseismic feature index set of each microseismic event includes:

[0115] Obtaining the amplitude corresponding to the waveform data;

[0116] Obtaining the ring count according to the threshold value corresponding to the waveform data and the waveform data;

[0117] Obtaining the rise time according to the first time point corresponding to the amplitude and the second time point in the waveform data, wherein the second time point is the time point at which the threshold value is first reached in the waveform data;

[0118] Obtaining the duration according to the second time point and the third time point in the waveform data, wherein the third time point is the time point at which the threshold value is last reached in the waveform data;

[0119] Obtaining the energy according to the distance between the source position of the microseismic event and the probe in the mine microseismic system, the information of the deep coal rock mass and the particle vibration velocity time history;

[0120] Obtaining the frequency according to the waveform data, wherein the frequency includes the microseismic frequency and the peak frequency. Therefore, the accuracy of the microseismic feature index set acquisition can be improved, and the accuracy of the determination of the dynamic instability and fracture risk information of the deep coal rock mass can be improved.

[0121] In some embodiments, the first time point corresponding to the amplitude may, for example, be the time point at which the waveform data first crosses the threshold value. The first in the first time point is used to distinguish from the remaining time points, and does not specifically refer to a fixed time point.

[0122] In some embodiments, the waveform amplitude, duration and propagation attenuation model of the elastic wave energy released by the microseismic event are back calculated, for example, as shown in equation (2):

[0123]

[0124] wherein p is the density of the coal rock mass, v is the calibrated wave speed of the coal rock mass, r is the distance from the source position to the sensor, is the time history of the particle vibration velocity. In the case of multiple sensors, i.e., in the case of multiple probes, r can be the average of multiple distances or a weighted sum of multiple distances. The present disclosure does not limit this.

[0125] According to some embodiments, the microseismic frequency generally refers to the energy distribution characteristics of the microseismic signal in the frequency domain, the peak frequency is the frequency point with the maximum amplitude in the frequency spectrum, representing the frequency component with the most concentrated energy in the signal. The change of the microseismic event frequency is closely related to the size of the fracture and the coal sample fracture mechanism. High-frequency microseismic signals are often accompanied by micro-fracture, and low-frequency signals are accompanied by large-scale crack propagation and unstable failure.

[0126] In step S23, an energy-based microseismic magnitude is obtained according to the source position of each microseismic event and the microseismic characteristic index set;

[0127] The relevant description is as described above, and will not be repeated here.

[0128] According to some embodiments, as shown in Figure 3 , the source distance of the microseismic event can be calculated according to the source position and the microseismic characteristic index, and then the energy-based microseismic magnitude is converted.

[0129] According to some embodiments, the energy-based microseismic magnitude is obtained according to the source position of each microseismic event and the microseismic characteristic index set, including:

[0130] The source distance of each microseismic event is obtained according to the source position and the energy of each microseismic event;

[0131] The energy-based microseismic magnitude is obtained according to the source distance.

[0132] According to some embodiments, the relationship between the amplitude microseismic magnitude is an important index for quantitatively describing the energy scale and the fracture scale of the event, and the change of the microseismic b value can reflect the microseismic magnitude scale characteristics. The microseismic energy and the velocity amplitude can be calculated by the empirical relationship formula representing the magnitude, for example, as shown in equation (3):

[0133] log 10 E=a+blog 10 V+clog 10 r(3)

[0134] In the formula, r is the source distance, V is the velocity amplitude, a, b, and c are empirical coefficients.

[0135] According to some embodiments, the microseismic magnitude M e may be obtained according to the microseismic energy, for example, as shown in formula (4):

[0136]

[0137] In step S24, the microseismic b value corresponding to the preset time length is obtained according to the microseismic magnitude and the frequency, and the microfracture type and the change trend information of the cumulative energy are obtained according to the microseismic characteristic index set.

[0138] The related description is as described above, and will not be repeated here.

[0139] According to some embodiments, the microseismic b value corresponding to the preset time length is obtained according to the relationship between the microseismic magnitude and the frequency, and the microfracture type and the change trend information of the cumulative energy are obtained according to the microseismic characteristic index set. That is, the microseismic b value of a certain stage and the change of the whole process can be calculated according to the relationship between the magnitude and the frequency.

[0140] According to the Gutenberg-Richter law, the least square fitting method or the maximum likelihood estimation method can be selected to fit and calculate the microseismic statistical parameter b value, which is used as a statistical parameter for evaluating the microseismic intensity characteristics, for example, as shown in formula (5).

[0141] log(N m>M )=a-bM(5)

[0142] In the formula, N m>M represents the number of magnitudes greater than M in the statistical area, and the calculation of the microseismic b value can be as shown in formula (6).

[0143]

[0144] According to some embodiments, the microseismic b value corresponding to the preset time length is obtained according to the relationship between the microseismic magnitude and the frequency, and the microfracture type and the change trend information of the cumulative energy are obtained according to the microseismic characteristic index set. That is, the microseismic b value of a certain stage and the change of the whole process can be calculated according to the relationship between the magnitude and the frequency.

[0145] The number of microseismic magnitudes greater than the preset magnitude in the monitoring range of the deep coal rock mass is obtained, and the number is used as the frequency;

[0146] The microseismic b value corresponding to the preset time length is obtained according to the number of microseismic magnitudes greater than the preset magnitude and the preset magnitude;

[0147] Obtain the AF value and RA value, and determine the micro-fracture type based on the AF value and RA value, where the AF value is the ratio of ring count to duration, and the RA value is the ratio of rise duration to amplitude.

[0148] According to some embodiments, the trend of changes in cumulative microseismic energy, the trend of changes in cumulative ring count, and the characteristics of microfracture types can be statistically obtained. The energy release and sound wave propagation mechanism of tensile-shear fracture can be utilized. The average frequency AF value represents the frequency characteristics of the microseismic signal. The ratio of ring count to duration is usually used to analyze the high-frequency or low-frequency characteristics of the signal. The ratio of rise time to amplitude (RA value) reflects the relationship between the amplitude characteristics of the signal and the rise time. Equation (7) is used to distinguish the failure modes of tensile cracks and shear cracks.

[0149]

[0150] In the formula, CR AE The ring count is indicated by the number of rings; DUR is the signal duration in microseconds (μs); RT is the signal rise time in microseconds (μs); A AE This indicates the signal amplitude, measured in m / s.

[0151] In step S25, if the energy of the microseismic event, the trend of cumulative energy, frequency, ringing count, microfracture type, and microseismic b-value all meet the risk requirements, it is determined that the risk information of dynamic instability and fracture of the deep coal and rock mass is less than the first preset risk value.

[0152] The relevant descriptions are as described above and will not be repeated here.

[0153] According to some embodiments, the dynamic instability and fracturing risk of deep coal and rock masses can be assessed and determined by comprehensively analyzing the energy of the microseismic events, the trend of cumulative energy changes, frequency, ringing count, microfracture type, and microseismic b-value.

[0154] According to some embodiments, warning characteristics can be determined by calculating b-values, energy, ringing counts, and crack types. A coal and rock mass hazard warning type evaluation table is defined, and different parameters can be used to assess the dynamic instability risk information of coal and rock masses. For example, it can be shown in Table 1.

[0155] Table 1

[0156]

[0157] According to some embodiments, the risk requirement may, for example, be a requirement for determining whether there is a risk, wherein satisfying the risk requirement may, for example, be a determination that the deep coal rock mass has a small risk of dynamic instability and fracture, i.e., the first preset risk value may, for example, be used to indicate that the deep coal rock mass has no or a low risk of fracture. The first preset risk value is used to distinguish from the remaining preset risk values.

[0158] For example, when the energy, the change trend information of the cumulative energy, the frequency, the ring count, the micro-fracture type, and the microseismic b value of the microseism each satisfy the corresponding requirement, it may be determined that the dynamic instability and fracture risk information of the deep coal rock mass is less than the first preset risk value.

[0159] In step S26, when the energy, the change trend information of the cumulative energy, the frequency, the ring count, the micro-fracture type, and the microseismic b value of the microseism each do not satisfy the risk requirement, it is determined that the dynamic instability and fracture risk information of the deep coal rock mass is greater than a second preset risk value, wherein the first preset risk value is less than the second preset risk value.

[0160] The related descriptions are as described above, and will not be repeated here.

[0161] The first preset risk value may, for example, be a requirement for determining whether there is a risk, wherein not satisfying the risk requirement may, for example, be a determination that the deep coal rock mass has a large risk of dynamic instability and fracture, i.e., the second preset risk value may, for example, be used to indicate that the deep coal rock mass has a risk of fracture.

[0162] For example, when the energy, the change trend information of the cumulative energy, the frequency, the ring count, the micro-fracture type, and the microseismic b value of the microseism each do not satisfy the corresponding requirement, it may be determined that the dynamic instability and fracture risk information of the deep coal rock mass is greater than the second preset risk value.

[0163] In step S27, when there are some of the energy, the change trend information of the cumulative energy, the frequency, the ring count, the micro-fracture type, and the microseismic b value of the microseism that do not satisfy the risk requirement, it is determined that the dynamic instability and fracture risk information of the deep coal rock mass is between the first preset risk value and the second preset risk value, and a fuzzy comprehensive algorithm is used to obtain a dynamic instability and fracture risk grade of the deep coal rock mass.

[0164] The related descriptions are as described above, and will not be repeated here.

[0165] For example, when there are some of the energy, the change trend information of the cumulative energy, the frequency, the ring count, the micro-fracture type, and the microseismic b value of the microseism that satisfy the corresponding requirement, a fuzzy comprehensive algorithm may be used to obtain a dynamic instability and fracture risk grade of the deep coal rock mass, and a prompt information is issued according to a prompt mode corresponding to the dynamic instability and fracture risk grade.

[0166] According to some embodiments, a fuzzy comprehensive algorithm is adopted to obtain the dynamic instability and fracture risk level of the deep coal rock mass, comprising:

[0167] According to the information of the deep coal rock mass, a weight set is obtained, wherein the weight set includes a first weight corresponding to the energy of the microseism, a second weight corresponding to the change trend information of the cumulative energy, a third weight corresponding to the frequency, a fourth weight corresponding to the ringing count, a fifth weight corresponding to the micro fracture type, and a sixth weight corresponding to the microseismic b value;

[0168] According to the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the micro fracture type, the microseismic b value, and the weight set, the dynamic instability and fracture risk level of the deep coal rock mass is obtained. Therefore, the dynamic instability and fracture risk level can be determined according to the weight information and the corresponding parameters, improving the accuracy of the dynamic instability and fracture risk level determination and improving the early warning accuracy of the deep coal rock mass fracture.

[0169] According to some embodiments, the final dynamic instability and fracture risk level of the coal rock mass can be evaluated based on the fuzzy comprehensive algorithm and the multi-parameter early warning index at a certain moment. Specifically, based on the fuzzy comprehensive algorithm, the frequency, energy, cumulative energy, ringing count, crack type, and b value of the microseism are used as multi-source indexes for influencing the stability of the rock mass. The impact risk level of the coal rock mass can be defined as three types of micro fracture, crack penetration, and instability fracture. The attribution degree of each factor to the three types of early warning is quantified as 0.1, 0.4, and 1, respectively. The relative importance of each factor is considered as 0.2, 0.2, 0.1, 0.2, 0.1, and 0.2, respectively. Finally, the comprehensive membership degree is calculated to determine the final dynamic instability and fracture risk level of the coal rock mass.

[0170] In the embodiment, in a case that the energy, the trend information of the cumulative energy, the frequency, the ring count, the micro-fracture type and the microseismic b value of the microseism all meet the risk requirements, it is determined that the dynamic instability and fracture risk information of the deep coal rock mass is less than a first preset risk value; in a case that the energy, the trend information of the cumulative energy, the frequency, the ring count, the micro-fracture type and the microseismic b value of the microseism all do not meet the risk requirements, it is determined that the dynamic instability and fracture risk information of the deep coal rock mass is greater than a second preset risk value, wherein the first preset risk value is less than the second preset risk value; in a case that part of the energy, the trend information of the cumulative energy, the frequency, the ring count, the micro-fracture type and the microseismic b value of the microseism do not meet the risk requirements, it is determined that the dynamic instability and fracture risk information of the deep coal rock mass is between the first preset risk value and the second preset risk value, and a fuzzy comprehensive algorithm is used to obtain the dynamic instability and fracture risk grade of the deep coal rock mass, so that different dynamic instability and fracture risk information of the deep coal rock mass can be determined according to different parameters and risk requirements, the accuracy of the determination of the dynamic instability and fracture risk information of the deep coal rock mass can be improved, and the accuracy of the dynamic instability and fracture risk warning of the deep coal rock mass can be improved.

[0171] A block diagram of a deep coal rock mass instability dynamic multi-parameter evaluation device based on microseism is shown according to an example embodiment. Referring to Figure 5 The device 500 comprises:

[0172] A data acquisition unit 501 is configured to acquire waveform data of each microseismic event of the deep coal rock mass through a mine microseismic system.

[0173] A set acquisition unit 502 is configured to acquire a microseismic characteristic index set of each microseismic event according to the waveform data, wherein the microseismic characteristic index set comprises a ring count, an amplitude, a duration, a rise time, an energy and a frequency of the microseismic signal.

[0174] A magnitude acquisition unit 503 is configured to acquire an energy-based microseismic magnitude according to a hypocenter location and the microseismic characteristic index set of each microseismic event.

[0175] The data acquisition unit 501 is further configured to acquire a microseismic b value corresponding to a preset time length according to the microseismic magnitude and the frequency, and to acquire a micro-fracture type and trend information of cumulative energy according to the microseismic characteristic index set.

[0176] A risk evaluation unit 504 is configured to acquire dynamic instability and fracture risk information of the deep coal rock mass according to the energy, the trend information of the cumulative energy, the frequency, the ring count, the micro-fracture type and the microseismic b value of the microseism.

[0177] According to some embodiments, the data acquisition unit 501 is further configured to:

[0178] Obtain long-time waveform data recorded by a plurality of measuring devices for deep coal rock mass, wherein the measuring device comprises a probe and a geophone;

[0179] Take each waveform data in the long-time waveform data meeting the data requirement as the waveform data of each microseismic event;

[0180] According to the waveform data of each microseismic event, obtain the arrival time corresponding to each probe;

[0181] According to the probe position of each probe and the arrival time corresponding to each probe, obtain the source position of the microseismic event.

[0182] According to some embodiments, the set acquisition unit 502 is configured to, when acquiring the microseismic characteristic index set of each microseismic event according to the waveform data, specifically configured to:

[0183] Obtain the amplitude corresponding to the waveform data;

[0184] According to the threshold value corresponding to the waveform data and the waveform data, obtain the ring count;

[0185] According to the first time point corresponding to the amplitude and the second time point in the waveform data, obtain the rising time, wherein the second time point is the time point at which the threshold value is first reached in the waveform data;

[0186] According to the second time point and the third time point in the waveform data, obtain the duration, wherein the third time point is the time point at which the threshold value is last reached in the waveform data;

[0187] According to the distance between the source position of the microseismic event and the probe in the mine microseismic system, the information of the deep coal rock mass, and the particle vibration velocity time history, obtain the energy;

[0188] According to the waveform data, obtain the frequency, wherein the frequency includes the microseismic frequency and the peak frequency.

[0189] According to some embodiments, the magnitude acquisition unit 503 is configured to, when acquiring the energy-based microseismic magnitude according to the source position of each microseismic event and the microseismic characteristic index set, specifically configured to:

[0190] According to the source position of each microseismic event and the energy, obtain the source distance of each microseismic event;

[0191] According to the source distance, obtain the energy-based microseismic magnitude.

[0192] According to some embodiments, the data acquisition unit 501 is configured to, when acquiring the microseismic b value corresponding to a preset time length according to the microseismic magnitude and the frequency, and acquiring the microfracture type according to the microseismic characteristic index set, specifically configured to:

[0193] obtain the number of microseisms with a magnitude greater than the preset magnitude in the monitoring range of the deep coal rock mass, and use the number as a frequency;

[0194] obtain a preset time length corresponding microseismic b value according to the number of microseisms with a magnitude greater than the preset magnitude and the preset magnitude;

[0195] obtain the AF value and the RA value, and obtain the microfracture type according to the AF value and the RA value, wherein the AF value is a ratio of the ringing count and the duration, and the RA value is a ratio of the rising duration and the amplitude.

[0196] According to some embodiments, the risk evaluation unit 504 is configured to obtain the dynamic instability and fracture risk information of the deep coal rock mass according to the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type, and the microseismic b value.

[0197] In a case where the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type, and the microseismic b value all meet the risk requirements, it is determined that the dynamic instability and fracture risk information of the deep coal rock mass is less than a first preset risk value.

[0198] In a case where the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type, and the microseismic b value all do not meet the risk requirements, it is determined that the dynamic instability and fracture risk information of the deep coal rock mass is greater than a second preset risk value, wherein the first preset risk value is less than the second preset risk value.

[0199] In a case where some of the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type, and the microseismic b value do not meet the risk requirements, it is determined that the dynamic instability and fracture risk information of the deep coal rock mass is between the first preset risk value and the second preset risk value, and a fuzzy comprehensive algorithm is used to obtain the dynamic instability and fracture risk level of the deep coal rock mass.

[0200] According to some embodiments, the risk evaluation unit 504 is configured to use the fuzzy comprehensive algorithm to obtain the dynamic instability and fracture risk level of the deep coal rock mass.

[0201] obtain a weight set according to the information of the deep coal rock mass, wherein the weight set includes a first weight corresponding to the energy of the microseism, a second weight corresponding to the change trend information of the cumulative energy, a third weight corresponding to the frequency, a fourth weight corresponding to the ringing count, a fifth weight corresponding to the microfracture type, and a sixth weight corresponding to the microseismic b value;

[0202] obtain the dynamic instability and fracture risk level of the deep coal rock mass according to the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type, the microseismic b value, and the weight set.

[0203] With regard to the apparatus in the above-described embodiments, in which the specific manner in which each module performs operations has been described in detail in the embodiments relating to the method, no detailed elaboration will be made here.

[0204] In some or related embodiments, by the data acquisition unit, waveform data of each microseismic event of the deep coal rock mass is acquired through the mine microseismic system; by the set acquisition unit, a microseismic characteristic index set of each microseismic event is acquired according to the waveform data, wherein the microseismic characteristic index set includes ringing count, amplitude, duration, rise time, energy, and frequency of the microseismic signal; by the magnitude acquisition unit, an energy-based microseismic magnitude is acquired according to the hypocenter location and the microseismic characteristic index set of each microseismic event; by the data acquisition unit, a microseismic b value corresponding to a preset time length is acquired according to the microseismic magnitude and the frequency, and a microfracture type and a change trend information of cumulative energy are acquired according to the microseismic characteristic index set; by the risk evaluation unit, dynamic instability and fracture risk information of the deep coal rock mass is acquired according to the energy, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type, and the microseismic b value of the microseismic. Therefore, the dynamic instability and fracture risk information of the deep coal rock mass can be determined by the acquired parameters, the inaccuracy of the evaluation caused by the evaluation only from the pressure appearance characteristics in the macroscopic characteristics can be reduced, the situation that the precursor characteristics of the coal rock instability are not obvious can be reduced, the situation that the data acquisition is not timely leading to a large delay of the early warning or risk evaluation can be reduced, the real-time evaluation can be performed through the waveform data of the microseismic, the evaluation efficiency can be improved, the cost, time length, and steps of the determination of the instability and fracture risk information can be reduced, the determination accuracy and efficiency of the instability and fracture risk information can be improved, and thus the accuracy of the early warning information provided for the dynamic disaster prevention in the process of the coal mining can be improved.

[0205] Figure 6 A schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure is shown. The electronic device 600 is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices such as personal digital assistants, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present disclosure described and / or claimed in this document.

[0206] As Figure 6As shown, the electronic device 600 includes a computing unit 601 that can perform various appropriate actions and processes in accordance with a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. Various programs and data required for the operation of the electronic device 600 can also be stored in the RAM 603. The computing unit 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0207] A plurality of components in the electronic device 600 are connected to the I / O interface 605, including an input unit 606 such as a keyboard, a mouse, and the like, an output unit 607 such as various types of displays, a speaker, and the like, a storage unit 608 such as a magnetic disk, an optical disk, and the like, and a communication unit 609 such as a network card, a modem, a wireless communication transceiver, and the like. The communication unit 609 allows the electronic device 600 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0208] The computing unit 601 can be various general and / or special-purpose processing components having processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, and the like. The computing unit 601 performs the various methods and processes described above. For example, in some embodiments, the above-described methods can be implemented as a computer software program that is tangibly embodied in a machine-readable medium, such as the storage unit 608. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 600 via the ROM 602 and / or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of the above-described methods described above can be performed. Alternatively, in other embodiments, the computing unit 601 can be configured to perform the above-described methods by any other appropriate means, such as by means of firmware.

[0209] The various embodiments of the systems and techniques described above can be implemented in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a load programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0210] Program code for carrying out methods of the present disclosure can be written in any combination of one or more programming languages. The program code can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the program code, when executed by the processor or controller, produces the functions / operations specified in the flowcharts and / or the block diagrams. The program code can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package, or entirely on a remote machine or server.

[0211] In the context of the present disclosure, a machine-readable medium can be a tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include but is not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine-readable storage medium will include one or more lines of electrical conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0212] To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0213] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), the Internet, and a blockchain network.

[0214] The computer system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service ("Virtual Private Server", or simply "VPS"). The server can also be a server of a distributed system, or a server combined with a blockchain.

[0215] It should be understood that various forms of flow shown above can be used with orders of steps reordered, added to, or removed. For example, the steps recited in the present disclosure can be performed in parallel, in series, or in a different order, without limitation herein, as long as the desired results of the technology disclosed in the present disclosure are achieved.

[0216] The above detailed description does not limit the scope of the disclosure. Various modifications, combinations, sub-combinations and alternatives can be made to the detailed description. Any modification, equivalent replacement and improvement etc. made within the spirit and principle of the disclosure shall be included in the scope of the disclosure.

Claims

1. A microseismic-based deep coal rock mass instability dynamic multi-parameter evaluation method, characterized in that, The method comprises the steps of: obtaining waveform data of each microseismic event of a deep coal rock mass through a mine microseismic system; obtaining a microseismic characteristic index set of each microseismic event according to the waveform data, wherein the microseismic characteristic index set comprises ringing count, amplitude, duration, rise time, energy and frequency of a microseismic signal; obtaining an energy-based microseismic magnitude according to the hypocenter location of each microseismic event and the microseismic characteristic index set; obtaining a microseismic b value corresponding to a preset time length according to the microseismic magnitude and frequency, and obtaining microfracture type and change trend information of cumulative energy according to the microseismic characteristic index set; obtaining dynamic instability and fracture risk information of the deep coal rock mass according to the energy of the microseismic event, the change trend information of the cumulative energy, the frequency, the ringing count, the microfracture type and the microseismic b value.

2. The method of claim 1, wherein, The method further comprises the steps of: obtaining long-time waveform data recorded by a plurality of measuring devices for the deep coal rock mass, wherein the measuring devices comprise probes and geophones; taking each waveform data in the long-time waveform data meeting data requirements as waveform data of each microseismic event; obtaining a corresponding arrival time of each probe according to the waveform data of each microseismic event; obtaining a hypocenter location of the microseismic event according to the probe location of each probe and the corresponding arrival time of each probe.

3. The method of claim 1, wherein, The step of obtaining a microseismic characteristic index set of each microseismic event according to the waveform data comprises the steps of: obtaining an amplitude corresponding to the waveform data; obtaining a ringing count according to a threshold value corresponding to the waveform data and the waveform data; obtaining a rise time according to a first time point corresponding to the amplitude and a second time point in the waveform data, wherein the second time point is a time point at which the threshold value is reached for the first time in the waveform data; obtaining a duration according to the second time point and a third time point in the waveform data, wherein the third time point is a time point at which the threshold value is reached for the last time in the waveform data; obtaining the energy according to a distance between the hypocenter location of each microseismic event and a probe in the mine microseismic system, information of the deep coal rock mass and particle vibration velocity time history; obtaining a frequency according to the waveform data, wherein the frequency comprises microseismic frequency and peak frequency.

4. The method of claim 1, wherein, The step of obtaining an energy-based microseismic magnitude according to the hypocenter location of each microseismic event and the microseismic characteristic index set comprises the steps of: obtaining a hypocentral distance of each microseismic event according to the hypocenter location of each microseismic event and the energy; obtaining an energy-based microseismic magnitude according to the hypocentral distance.

5. The method of claim 1, wherein, The step of obtaining a microseismic b value corresponding to a preset time length according to the microseismic magnitude and frequency, and obtaining microfracture type according to the microseismic characteristic index set comprises the steps of: obtaining a number of microseismic magnitudes greater than a preset magnitude in a monitoring range of the deep coal rock mass, and taking the number as frequency; obtaining a microseismic b value corresponding to a preset time length according to the number of microseismic magnitudes greater than the preset magnitude and the preset magnitude; The AF value and the RA value are obtained, and a micro-fracture type is obtained according to the AF value and the RA value, wherein the AF value is a ratio of the ringing count and the duration, and the RA value is a ratio of the rising duration and the amplitude.

6. The method of claim 1, wherein, The dynamic instability and fracture risk information of the deep coal rock mass is obtained according to the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the micro-fracture type and the microseismic b value, and comprises: In a case where the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the micro-fracture type and the microseismic b value all meet the risk requirement, it is determined that the dynamic instability and fracture risk information of the deep coal rock mass is less than a first preset risk value; In a case where the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the micro-fracture type and the microseismic b value all do not meet the risk requirement, it is determined that the dynamic instability and fracture risk information of the deep coal rock mass is greater than a second preset risk value, wherein the first preset risk value is less than the second preset risk value; In a case where part of the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the micro-fracture type and the microseismic b value do not meet the risk requirement, it is determined that the dynamic instability and fracture risk information of the deep coal rock mass is between the first preset risk value and the second preset risk value, and a fuzzy comprehensive algorithm is used to obtain a dynamic instability and fracture risk grade of the deep coal rock mass.

7. The method of claim 6, wherein, The fuzzy comprehensive algorithm is used to obtain the dynamic instability and fracture risk grade of the deep coal rock mass, and comprises: According to the information of the deep coal rock mass, a weight set is obtained, wherein the weight set comprises a first weight corresponding to the energy of the microseism, a second weight corresponding to the change trend information of the cumulative energy, a third weight corresponding to the frequency, a fourth weight corresponding to the ringing count, a fifth weight corresponding to the micro-fracture type and a sixth weight corresponding to the microseismic b value; According to the energy of the microseism, the change trend information of the cumulative energy, the frequency, the ringing count, the micro-fracture type and the microseismic b value and the weight set, the dynamic instability and fracture risk grade of the deep coal rock mass is obtained.

8. A microseismic-based deep coal rock mass instability dynamic multi-parameter evaluation device, characterized in that, Comprise: A data acquisition unit is configured to acquire waveform data of each microseismic event of a deep coal rock mass through a mine microseismic system; A set acquisition unit is configured to acquire a microseismic characteristic index set of each microseismic event according to the waveform data, wherein the microseismic characteristic index set comprises a ringing count, an amplitude, a duration, a rising duration, an energy and a frequency of a microseismic signal; A magnitude acquisition unit is configured to acquire an energy-based microseismic magnitude according to a hypocenter location of each microseismic event and the microseismic characteristic index set; The data acquisition unit is further configured to acquire a microseismic b value corresponding to a preset time duration according to the microseismic magnitude and a frequency, and to acquire a micro-fracture type and change trend information of cumulative energy according to the microseismic characteristic index set; A risk evaluation unit is configured to obtain the dynamic instability and fracture risk information of the deep coal rock mass according to the microseismic energy, the change trend information of the cumulative energy, the frequency, the ring count, the microfracture type and the microseismic b value.

9. An electronic device, comprising: Comprise: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the microseismic-based deep coal rock mass instability dynamic multi-parameter evaluation method according to any one of claims 1 to 7.

10. A storage medium, the storage medium storing instructions, wherein, When the instructions run on an electronic device, the electronic device is caused to perform the microseismic-based deep coal rock mass instability dynamic multi-parameter evaluation method according to any one of claims 1 to 7.

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