Coal rock impact intensity evaluation method, device and product

Abstract

This application relates to the field of coal and rock impact mechanics testing and evaluation technology, and provides a method, device, and product for evaluating coal and rock impact intensity. The method includes: acquiring the voltage time-series matrix of a thin-film pressure sensor array after a coal and rock sample is damaged by pressure loading; transforming the voltage time-series matrix according to a preset voltage-pressure mapping relationship to obtain a pressure time-series matrix; performing impact event detection and pseudo-impact removal based on the pressure time-series matrix to determine the target impact windows for multiple target measuring points; performing spatiotemporal inversion based on the pressure time-series data of the target impact windows for multiple target measuring points to obtain inversion data corresponding to each target measuring point; determining multiple macroscopic impact events based on the inversion data corresponding to each target measuring point; extracting multidimensional feature parameters from the multiple macroscopic impact events, and determining the impact intensity index of the coal and rock sample based on the multidimensional feature parameters. Based on the scheme of this application, accurate evaluation of coal and rock impact intensity can be achieved.

Description

Technical Field

[0001] This invention relates to the field of coal and rock impact mechanics testing and evaluation technology, and in particular to a method, device and product for evaluating coal and rock impact intensity. Background Technology

[0002] The assessment of coal and rock impact intensity is a crucial research area in deep coal mining and rock mechanics. It is commonly used to evaluate the intensity of energy release during the ejection of coal and rock during loading and failure, providing a basis for the prediction and prevention of mine rockburst disasters. In practical applications, due to the highly nonlinear and transient nature of the coal and rock impact failure process, relevant assessment methods often rely on indirect mechanical parameter testing or simple statistical processing of surface contact pressure. However, this approach is easily affected by complex loading environments and the dynamic collision characteristics of fragments, leading to evaluation indicators that fail to accurately reflect the physical nature of the failure process. Distortion or insufficient discrimination in the evaluation results directly impacts the accurate assessment of coal and rock impact hazards, thus limiting its reliability in practical engineering disaster early warning. Therefore, accurately assessing coal and rock impact intensity has become an urgent problem to be solved. Summary of the Invention

[0003] This application provides a method, apparatus, and product for evaluating the impact intensity of coal and rock, in order to solve the technical problem of how to accurately evaluate the impact intensity of coal and rock.

[0004] In a first aspect, embodiments of this application provide a method for evaluating the intensity of coal and rock impact, including: The voltage timing matrix of the thin-film pressure sensor array after the coal and rock sample was damaged by pressure loading was obtained. The thin-film pressure sensor array was distributed around the periphery of the coal and rock sample, and the thin-film pressure sensor in the thin-film pressure sensor array corresponded one-to-one with the measuring point. The voltage time series matrix is ​​transformed according to the preset voltage-pressure mapping relationship to obtain the pressure time series matrix; Impact event detection and false impact elimination are performed based on the pressure time series matrix to determine the target impact window for multiple target measurement points. Spatiotemporal inversion is performed based on the pressure time series data of the target impact window of multiple target measuring points to obtain the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection for each target measuring point in the multiple target measuring points. Multiple macroscopic impact events are determined based on the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection corresponding to each target measuring point. Multidimensional characteristic parameters were extracted from multiple macroscopic impact events, and the impact intensity index of the coal and rock samples was determined based on the multidimensional characteristic parameters.

[0005] In conjunction with the first aspect, in some possible implementations, the voltage timing matrix is ​​transformed according to a preset voltage-pressure mapping relationship to obtain the pressure timing matrix, including: Based on the preset voltage-pressure mapping relationship, the voltage values ​​of each measuring point in the voltage time sequence matrix are converted to obtain the pressure values ​​corresponding to each measuring point; A pressure time series matrix is ​​constructed based on the pressure values ​​corresponding to each measuring point.

[0006] Combining the first aspect and the above implementation methods, in some possible implementation methods, impact event detection and false impact elimination are performed based on the pressure time series matrix to determine the target impact window for multiple target measurement points, including: Impact event detection is performed based on the pressure time series matrix to obtain the effective impact window for multiple effective measurement points; False impacts are eliminated based on the effective impact windows of multiple effective measuring points to determine multiple target measuring points from multiple effective measuring points, and target impact windows of multiple target measuring points are determined from the effective impact windows of multiple target measuring points.

[0007] Combining the first aspect and the above implementation methods, in some possible implementation methods, spatiotemporal inversion is performed based on the pressure time series data of the target impact window of multiple target measuring points to obtain the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of the projectile corresponding to each target measuring point among the multiple target measuring points, including: Based on the pressure time series data of the target impact window of multiple target measuring points and the preset effective area of ​​a single measuring point, the single measuring point impact impulse of each target measuring point is determined. The equivalent impact kinetic energy corresponding to each target measuring point is determined based on the single-point impact impulse of each target measuring point, the peak pressure of each target measuring point within the target impact window, the effective duration of the target impact window of each target measuring point, and the preset device calibration coefficient. Based on the single-point impact impulse of each target measuring point, the equivalent impact kinetic energy corresponding to each target measuring point, the preset air resistance attenuation coefficient, and the preset sample-sensor gap, the equivalent mass of the fragments corresponding to each target measuring point is determined. Based on the equivalent mass of the fragments corresponding to each target measuring point and the preset sample density, determine the equivalent diameter of the fragments corresponding to each target measuring point. The initial launch velocity of each target measuring point is determined based on the equivalent impact kinetic energy and the equivalent mass of the fragments at each target measuring point.

[0008] Combining the first aspect and the above implementation methods, in some possible implementation methods, multiple macroscopic impact events are determined based on the equivalent impact kinetic energy, equivalent mass of the fragments, equivalent diameter of the fragments, and initial velocity of the ejection corresponding to each target measuring point, including: Based on the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, initial velocity of ejection, and spatial and temporal information of each target measuring point, a spatiotemporal feature tensor is constructed. Based on the spatiotemporal feature tensor and the preset density clustering algorithm, and using the preset spatiotemporal neighborhood radius and minimum number of measurement points as clustering conditions, multiple spatiotemporally adjacent target measurement points are clustered and merged to obtain multiple macroscopic impact events.

[0009] Combining the first aspect and the above-mentioned implementation methods, in some possible implementation methods, multidimensional feature parameters are extracted based on multiple macroscopic impact events, and the impact intensity index of the coal and rock sample is determined based on the multidimensional feature parameters, including: Based on multiple macroscopic impact events, at least two of the following are extracted as multidimensional feature parameters: total equivalent impact work, spatial distribution fractal dimension, maximum instantaneous energy release power, b-value of energy-frequency distribution, skewness of fragment velocity distribution, normalized spatial information entropy, spatiotemporal aggregation index, superkurtosis of fragment velocity distribution, temporal nonuniformity of energy release, and spatial nonuniformity of energy release. The impact intensity index of the coal and rock samples was determined based on multidimensional characteristic parameters.

[0010] Combining the first aspect and the above implementation methods, in some possible implementation methods, the impact intensity index of the coal and rock sample is determined based on multidimensional characteristic parameters, including any one of the following: The impact intensity index of the coal and rock sample is determined by a pre-set weighted power exponent model based on the total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power among the multidimensional characteristic parameters. Based on the total equivalent impact energy, the b-value of the energy-frequency distribution, and the normalized spatial information entropy in the multidimensional characteristic parameters, the impact intensity index of the coal and rock sample is determined by a pre-set probabilistic risk model. Based on the total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power in the multidimensional characteristic parameters, the impact intensity index of the coal and rock sample is determined by a preset principal component analysis adaptive model. The impact intensity index of the coal and rock sample is determined by using the total equivalent impact energy, spatial distribution fractal dimension, maximum instantaneous energy release power, skewness of fragment velocity distribution, spatiotemporal aggregation index, supercluster degree of fragment velocity distribution, temporal nonuniformity of energy release, and spatial nonuniformity of energy release from the multidimensional characteristic parameters.

[0011] Secondly, embodiments of this application provide a coal and rock impact intensity evaluation device, comprising: The coal and rock impact intensity evaluation device includes an impact box, a thin-film pressure sensor array, and a data processing terminal; The punch box is a cylindrical box with an opening at the top, used to hold coal and rock samples; A thin-film pressure sensor array is distributed around the inner wall of the impact box and is connected to the data processing terminal. It is used to collect voltage timing signals during the failure process of coal and rock samples and provide voltage timing signals to the data processing terminal. The data processing terminal is used to execute the coal and rock impact intensity evaluation method of the first aspect.

[0012] Thirdly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the steps of the coal and rock impact intensity evaluation method of the first aspect.

[0013] The coal and rock impact intensity evaluation method, apparatus, and product provided in this application first obtain the voltage time series matrix of a thin-film pressure sensor array after the coal and rock sample is damaged by pressure loading. The thin-film pressure sensor array is distributed around the periphery of the coal and rock sample, and each thin-film pressure sensor in the array corresponds to a measuring point. Then, the voltage time series matrix is ​​transformed according to a preset voltage-pressure mapping relationship to obtain the pressure time series matrix. Next, impact event detection and false impact removal are performed based on the pressure time series matrix to determine the target impact window for multiple target measuring points. Based on this, spatiotemporal inversion is performed on the pressure time series data of the target impact windows for multiple target measuring points to obtain the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection for each target measuring point. Then, based on the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection for each target measuring point... Multiple macroscopic impact events are determined by the block's equivalent diameter and initial ejection velocity. Finally, multidimensional feature parameters are extracted from these macroscopic impact events, and the impact intensity index of the coal and rock sample is determined based on these parameters. Through this process, a comprehensive voltage time series matrix is ​​obtained using a distributed array of thin-film pressure sensors that corresponds one-to-one with the measuring points. After being converted into a pressure time series matrix, interference from non-impact signals is eliminated through impact event detection and pseudo-impact removal. Based on the pressure time series data of the actual target impact window, spatiotemporal inversion is performed, converting the contact pressure into equivalent impact kinetic energy, equivalent mass of the fragments, equivalent diameter of the fragments, and initial ejection velocity, reflecting the physical nature of the damage. By determining multiple macroscopic impact events and extracting multidimensional feature parameters, the final determined impact intensity index is based on a comprehensive quantitative foundation of multidimensional physical characteristics, thus achieving an accurate evaluation of the coal and rock impact intensity. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a flowchart illustrating the coal and rock impact intensity evaluation method provided in the embodiments of this application; Figure 2 This is a schematic diagram of the structure of a coal and rock impact intensity evaluation device provided in an embodiment of this application; Figure 3 This is a schematic diagram of another coal and rock impact intensity evaluation device provided in the embodiments of this application; Figure 4 This is a schematic diagram of the structure of another coal and rock impact intensity evaluation device provided in the embodiments of this application. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0017] The assessment of coal and rock impact intensity is an important research topic in deep coal mining and rock mechanics. It is often used to evaluate the severity of energy release during the ejection of coal and rock under load, providing a basis for the prediction and prevention of mine rockburst disasters. In practical applications, due to the highly nonlinear and transient nature of the coal and rock impact failure process, the relevant assessment methods mostly rely on indirect mechanical parameter testing or simple statistical processing of surface contact pressure.

[0018] For example, in some related technologies, the indirect mechanical parameter test results of coal and rock during the loading failure process are obtained, and the indirect mechanical parameter test results are used to characterize the coal and rock impact intensity evaluation results; or, the surface contact pressure of coal and rock during the loading failure process is obtained, and the surface contact pressure is subjected to simple statistical processing, and the simple statistical processing results are used to characterize the coal and rock impact intensity evaluation results.

[0019] It is evident that the aforementioned technologies have shortcomings: For the indirect mechanical parameter testing method, the physical meaning of the test results is weakly correlated with the intensity of energy release during the loading and failure of coal and rock, making it difficult to accurately reflect the true physical nature of the coal and rock impact intensity evaluation. For the method of simple statistical processing of surface contact pressure, the process fails to distinguish between the time of generation and duration of surface contact pressure. Furthermore, surface contact pressure is a contact force, not the kinetic energy carried by fragments. Equating surface contact pressure directly with the energy released during ejection ignores momentum exchange and energy dissipation during the collision, leading to physical distortion in the results and consequently, poor accuracy in the coal and rock impact intensity evaluation.

[0020] Therefore, how to accurately evaluate the impact intensity of coal and rock has become an urgent problem to be solved.

[0021] To address the aforementioned problems, the solution provided in this application mainly includes: First, obtaining the voltage time series matrix of the thin-film pressure sensor array after pressure loading and damage to the coal and rock sample, wherein the thin-film pressure sensor array is distributed around the periphery of the coal and rock sample, and the thin-film pressure sensors in the thin-film pressure sensor array correspond one-to-one with the measuring points; then, transforming the voltage time series matrix according to a preset voltage-pressure mapping relationship to obtain the pressure time series matrix; next, performing impact event detection and false impact removal based on the pressure time series matrix to determine the target impact window of multiple target measuring points; based on this, performing spatiotemporal inversion based on the pressure time series data of the target impact window of multiple target measuring points to obtain the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection corresponding to each target measuring point; and then, based on the equivalent impact kinetic energy, equivalent mass of fragments, and equivalent diameter of fragments corresponding to each target measuring point... Multiple macroscopic impact events are determined by the equivalent diameter and initial ejection velocity. Finally, multidimensional feature parameters are extracted from these events, and the impact intensity index of the coal and rock sample is determined based on these parameters. Through this process, a comprehensive voltage time series matrix is ​​obtained using a distributed array of thin-film pressure sensors corresponding to each measuring point. After conversion to a pressure time series matrix, interference from non-impact signals is eliminated through impact event detection and pseudo-impact removal. Based on the pressure time series data of the actual target impact window, spatiotemporal inversion is performed, transforming the contact pressure into equivalent impact kinetic energy, equivalent fragment mass, equivalent fragment diameter, and initial ejection velocity, reflecting the physical nature of the damage. By determining multiple macroscopic impact events and extracting multidimensional feature parameters, the final impact intensity index is established on a comprehensive quantitative basis of multidimensional physical characteristics, thus achieving an accurate evaluation of the impact intensity of coal and rock.

[0022] The coal and rock impact intensity evaluation method provided in the embodiments of this application will be described in detail below.

[0023] Please see Figure 1 , Figure 1 This is a flowchart illustrating a method for evaluating the impact intensity of coal and rock, provided as an embodiment of this application. Figure 1 As shown, the method in this application embodiment may include the following steps S101~S106: S101, Obtain the voltage timing matrix of the thin-film pressure sensor array after the coal and rock sample is damaged by pressure loading. The thin-film pressure sensor array is distributed around the periphery of the coal and rock sample, and the thin-film pressure sensor in the thin-film pressure sensor array corresponds one-to-one with the measuring point. S102, the voltage timing matrix is ​​transformed according to the preset voltage-pressure mapping relationship to obtain the pressure timing matrix; S103, based on the pressure time series matrix, performs impact event detection and pseudo-impact elimination to determine the target impact window for multiple target measurement points; S104. Based on the pressure time series data of the target impact window of multiple target measuring points, perform spatiotemporal inversion to obtain the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection for each target measuring point in the multiple target measuring points. S105, based on the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection corresponding to each target measuring point, multiple macroscopic impact events are determined; S106. Multidimensional feature parameters are extracted based on multiple macroscopic impact events, and the impact intensity index of the coal and rock sample is determined based on the multidimensional feature parameters.

[0024] Specifically, the first step is to obtain the voltage time-series matrix of the thin-film pressure sensor array after the coal and rock sample has been damaged by pressure loading. The thin-film pressure sensor array is distributed around the periphery of the coal and rock sample, and each thin-film pressure sensor in the array corresponds one-to-one with a measurement point. Here, "thin-film pressure sensor array" refers to a sensor network composed of multiple thin-film pressure sensors arranged in a specific spatial pattern; "thin-film pressure sensor array distributed around the periphery of the coal and rock sample" means that the thin-film pressure sensor array forms a ring-shaped enclosure around the side surface of the coal and rock sample; "coal and rock sample" refers to a standard coal and rock specimen used for impact tendency or impact intensity testing under pressure loading conditions; "voltage time-series matrix" refers to a data matrix composed of the voltage signal values ​​corresponding to all measurement points in the thin-film pressure sensor array at different sampling times, arranged in chronological order and spatial position; "measurement point" refers to the smallest spatial sensing unit in the thin-film pressure sensor array that can independently sense pressure signals; and "one-to-one correspondence between thin-film pressure sensors and measurement points" means that each thin-film pressure sensor in the array is responsible for collecting the voltage signal of a uniquely corresponding measurement point.

[0025] Regarding this step, in some possible implementations, the voltage signals of all measuring points in the thin-film pressure sensor array can be synchronously acquired according to a preset sampling frequency, and the acquired voltage signals can be stored in a matrix according to timestamps and measuring point spatial indices to obtain the voltage time sequence matrix of the thin-film pressure sensor array after the coal and rock sample is damaged by pressure loading.

[0026] Furthermore, the voltage time series matrix is ​​transformed according to the preset voltage-pressure mapping relationship to obtain the pressure time series matrix. Here, the voltage-pressure mapping relationship refers to the mathematical model or calibration curve that characterizes the correspondence between the output voltage signal of the thin-film pressure sensor and the actual contact pressure it withstands; the pressure time series matrix refers to the data matrix containing the pressure signal values ​​of all measuring points at different sampling times, obtained by transforming the voltage time series matrix through the voltage-pressure mapping relationship.

[0027] Regarding this step, in some possible implementations, the voltage signals of each measurement point in the voltage time sequence matrix can be input into a preset voltage-pressure mapping relationship, and the corresponding pressure signals can be obtained through relevant mathematical operations. All pressure signals can then be combined in the same arrangement as the voltage time sequence matrix to obtain the pressure time sequence matrix.

[0028] Furthermore, impact event detection and pseudo-impact rejection are performed based on the pressure time series matrix to determine the target impact window for multiple target measuring points. Impact event detection refers to identifying abnormal fluctuations in the pressure signal exceeding a preset trigger threshold from the pressure time series matrix; pseudo-impact rejection refers to filtering and removing interference signals caused by high-speed ejection of non-fragment fragments during the abnormal fluctuations detected by impact event detection; target measuring points refer to measuring points confirmed to have genuine fragment impact signals after pseudo-impact rejection; and the target impact window for a target measuring point refers to the continuous time period corresponding to the effective impact signal of the target measuring point in the pressure time series matrix.

[0029] Regarding this step, in some possible implementations, a relevant trigger threshold can be determined based on the noise floor data in the pressure time series matrix. The pressure time series matrix is ​​then traversed based on the relevant trigger threshold to detect impact events, resulting in effective impact windows for multiple effective measurement points. Subsequently, pseudo-impacts are removed from the effective impact windows of multiple effective measurement points based on relevant feature parameters. The remaining effective measurement points after removal are used as multiple target measurement points, and the effective impact windows of the multiple target measurement points are used as the target impact windows of the multiple target measurement points.

[0030] Furthermore, spatiotemporal inversion is performed based on the pressure time series data of the target impact window of multiple target measuring points to obtain the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection for each target measuring point among the multiple target measuring points. Among them, the pressure time series data of the target impact window of the target measuring point refers to the data sequence of the pressure value recorded by the target measuring point as a function of time within the continuous time period corresponding to the target impact window of the target measuring point; spatiotemporal inversion refers to the process of inversely deducing the physical motion parameters of the fragment that generated the contact pressure before the impact based on the time evolution process and spatial distribution characteristics of the contact pressure; equivalent impact kinetic energy refers to the kinetic energy carried by the fragment before impacting the sensor, calculated based on the pressure time history data of the target impact window of the target measuring point; fragment equivalent mass refers to the equivalent mass of the fragment that generated the impact signal, calculated based on the equivalent impact kinetic energy and the movement velocity of the fragment; fragment equivalent diameter refers to the characteristic size of the fragment calculated based on the fragment equivalent mass and the preset sample density when assuming the fragment is spherical; and ejection initial velocity refers to the initial velocity of the fragment when it flies out of the surface of the coal and rock sample.

[0031] Regarding this step, in some possible implementations, the pressure time series data of the target impact window of multiple target measuring points can be integrated to obtain relevant impulse data. Based on the relevant impulse data and relevant calibration parameters, relevant mathematical operations are performed to perform spatiotemporal inversion, thereby obtaining the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection for each target measuring point among multiple target measuring points.

[0032] Furthermore, multiple macroscopic impact events are determined based on the equivalent impact kinetic energy, equivalent mass of the fragments, equivalent diameter of the fragments, and initial velocity of the ejection corresponding to each target measuring point. Among them, macroscopic impact events refer to the set of impact behaviors of multiple target measuring points that are spatially adjacent and synchronous in occurrence.

[0033] Regarding this step, in some possible implementations, the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, initial velocity of the projectile, and spatial and temporal information of each target measuring point can be constructed as relevant spatiotemporal feature data. Based on relevant spatial clustering algorithms, the spatiotemporal feature data can be clustered, and each cluster obtained after clustering can be regarded as a macroscopic impact event, thereby determining multiple macroscopic impact events.

[0034] Furthermore, multidimensional feature parameters are extracted from multiple macroscopic impact events, and the impact intensity index of the coal and rock samples is determined based on these multidimensional feature parameters. Here, the multidimensional feature parameters refer to the set of quantitative indicators extracted from the macroscopic impact event set, capable of characterizing the severity of impact damage to the coal and rock samples from different dimensions; the impact intensity index refers to the final quantitative value calculated based on the multidimensional feature parameters using a pre-defined fusion model, used to comprehensively evaluate the severity of impact damage to the coal and rock samples.

[0035] Regarding this step, in some possible implementations, relevant statistical analysis can be performed on multiple macroscopic impact events to extract multidimensional feature parameters. Subsequently, the multidimensional feature parameters are input into a preset fusion model, and relevant mathematical operations are performed through the preset fusion model to determine the impact intensity index of the coal and rock sample.

[0036] In this embodiment, firstly, the voltage time series matrix of the thin-film pressure sensor array after pressure loading damage to the coal and rock sample is obtained. The thin-film pressure sensor array is distributed around the periphery of the coal and rock sample, and the thin-film pressure sensors in the array correspond one-to-one with the measuring points. Then, the voltage time series matrix is ​​transformed according to a preset voltage-pressure mapping relationship to obtain the pressure time series matrix. Next, impact event detection and false impact elimination are performed based on the pressure time series matrix to determine the target impact window of multiple target measuring points. On this basis, spatiotemporal inversion is performed based on the pressure time series data of the target impact window of multiple target measuring points to obtain the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection corresponding to each target measuring point. Then, based on the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection corresponding to each target measuring point, the following parameters are used to determine the target impact window of multiple target measuring points: Multiple macroscopic impact events were identified. Multidimensional feature parameters were then extracted from these events, and the impact intensity index of the coal and rock samples was determined based on these parameters. Through this process, a comprehensive voltage time series matrix was obtained using a distributed array of thin-film pressure sensors, each corresponding to a specific measuring point. After conversion to a pressure time series matrix, interference from non-impact signals was eliminated through impact event detection and pseudo-impact removal. This allowed for spatiotemporal inversion based on the pressure time series data of the actual target impact window. The contact pressure was transformed into equivalent impact kinetic energy, equivalent fragment mass, equivalent fragment diameter, and initial ejection velocity, reflecting the physical nature of the damage. By identifying multiple macroscopic impact events and extracting multidimensional feature parameters, the final impact intensity index was established on a comprehensive quantitative basis of multidimensional physical characteristics, thus achieving an accurate evaluation of the impact intensity of coal and rock samples.

[0037] In one embodiment, the step of "converting the voltage time series matrix according to the preset voltage-pressure mapping relationship to obtain the pressure time series matrix" can be further refined and may include the following steps: Based on the preset voltage-pressure mapping relationship, the voltage values ​​of each measuring point in the voltage time sequence matrix are converted to obtain the pressure values ​​corresponding to each measuring point; A pressure time series matrix is ​​constructed based on the pressure values ​​corresponding to each measuring point.

[0038] Specifically, considering that the signal form directly acquired by the thin-film pressure sensor array is inconsistent with the mechanical parameter form on which subsequent impact event detection and false impact elimination depend, this embodiment proposes to unify the original acquired signal by using a pre-established conversion relationship.

[0039] First, based on a preset voltage-pressure mapping relationship, the voltage values ​​at each measuring point in the voltage time series matrix need to be converted to obtain the corresponding pressure values ​​for each measuring point. Here, the voltage value refers to the quantized value of the electrical signal output by each measuring point in the thin-film pressure sensor array at different sampling times; the pressure value refers to the quantized value of the contact pressure actually felt by each measuring point at different sampling times; and the voltage-pressure mapping relationship refers to a mathematical model characterizing the correspondence between the quantized values ​​of the electrical signal and the quantized values ​​of the contact pressure. In some possible implementations, the voltage-pressure mapping relationship can be expressed as a linear fitting function or a multi-order polynomial fitting function; this embodiment does not limit this.

[0040] Regarding this step, in some possible implementations, the voltage values ​​of each measuring point in the voltage timing matrix can be input into a preset voltage-pressure mapping relationship, and the pressure value corresponding to each measuring point can be obtained by calculation through this voltage-pressure mapping relationship.

[0041] Furthermore, a pressure time series matrix is ​​constructed based on the pressure values ​​corresponding to each measuring point.

[0042] Regarding this step, in some possible implementations, the pressure values ​​corresponding to each measuring point can be matrix-reorganized according to the arrangement order of the voltage values ​​of each measuring point in the voltage time series matrix to construct the pressure time series matrix.

[0043] For example, the voltage values ​​at each measuring point in the voltage time series matrix can be converted according to a preset voltage-pressure mapping relationship to obtain the pressure value corresponding to each measuring point. This can be achieved based on the following formula: ; in, This indicates the pressure value corresponding to each measuring point. This indicates a preset voltage-pressure mapping relationship. This represents the voltage value at each measurement point in the voltage time series matrix.

[0044] In this embodiment, the voltage values ​​at each measuring point in the voltage time series matrix are converted using a preset voltage-pressure mapping relationship to obtain the pressure values ​​corresponding to each measuring point. A pressure time series matrix is ​​then constructed based on these pressure values. This process uniformly converts the original electrical signals into mechanical parameters, enabling the constructed pressure time series matrix to directly reflect the contact stress state at each measuring point during the failure of the coal and rock sample. This provides a data foundation for subsequent impact event detection and false impact removal based on the pressure time series matrix.

[0045] In one embodiment, the above step of "performing impact event detection and false impact removal based on the pressure time series matrix to determine the target impact window for multiple target measurement points" can be further refined and may include the following steps: Impact event detection is performed based on the pressure time series matrix to obtain the effective impact window for multiple effective measurement points; False impacts are eliminated based on the effective impact windows of multiple effective measuring points to determine multiple target measuring points from multiple effective measuring points, and target impact windows of multiple target measuring points are determined from the effective impact windows of multiple target measuring points.

[0046] Specifically, considering that the pressure time series matrix may contain environmental noise and non-impact static extrusion signals that may be generated during the sample loading process, this embodiment proposes a processing mechanism for signal identification and filtering in stages.

[0047] First, impact event detection needs to be performed based on the pressure time series matrix to obtain the effective impact window of multiple valid measurement points. Here, a valid measurement point refers to a measurement point in the pressure time series matrix where the pressure signal exceeds a preset trigger threshold, and multiple valid measurement points are a subset of all measurement points corresponding to the thin-film pressure sensor array. The effective impact window of a valid measurement point refers to the continuous time period during which the pressure signal of the valid measurement point exceeds the preset trigger threshold and continuously meets the preset time condition.

[0048] Regarding this step, in some possible implementations, an adaptive trigger threshold can be calculated based on the noise data at the initial stage of loading using the pressure time series matrix. The time series of each measuring point in the pressure time series matrix is ​​traversed. When the pressure signal of the measuring point is greater than or equal to the adaptive trigger threshold, it is marked as the start of the impact. When the pressure signal of the measuring point is less than the adaptive trigger threshold and remains below the adaptive trigger threshold for more than a preset holding time, it is marked as the end of the impact. This is used to detect impact events, thereby obtaining multiple effective measuring points and multiple effective impact windows for the effective measuring points.

[0049] Furthermore, pseudo-impact rejection is performed based on the effective impact windows of multiple effective measuring points to determine multiple target measuring points from the multiple effective measuring points, and target impact windows of multiple target measuring points are determined from the effective impact windows of the multiple target measuring points. It can be understood that multiple target measuring points are subsets of multiple effective measuring points, and the target impact windows of target measuring points are subsets of the effective impact windows of target measuring points. That is, through the pseudo-impact rejection operation, measuring points containing interference signals and their corresponding effective impact windows are eliminated from the multiple effective measuring points, while retaining the true impact signals caused by the high-speed ejection of fragments.

[0050] Regarding this step, in some possible implementations, the pulse index within the effective impact window of multiple effective measuring points can be calculated. The pulse index is defined as the ratio of the peak pressure to the average pressure within the effective impact window. If the pulse index of the effective impact window is less than a preset pulse index threshold and the duration of the effective impact window is greater than a preset duration threshold, then the effective impact window is determined to be a false impact. The measuring point corresponding to the effective impact window is removed from the multiple effective measuring points. The remaining measuring points after removal are used as multiple target measuring points, and the effective impact windows of the multiple target measuring points that are not determined to be false impacts are used as the target impact windows of the multiple target measuring points, thereby completing the false impact removal.

[0051] For example, the adaptive trigger threshold can be calculated based on the noise floor data at the initial stage of loading using the pressure time series matrix, according to the following formula: ; in, Indicates the adaptive trigger threshold. This represents the average pressure during the initial quiescent period of the pressure time series matrix. This represents the standard deviation of pressure in the pressure time series matrix during the initial quiescent period of loading. This indicates the preset threshold coefficient.

[0052] For example, the pulse index within the effective impact window of multiple effective measurement points can be calculated based on the following formula: ; in, Indicates the pulse index. This indicates the peak pressure within the effective impact window. This represents the average pressure within the effective impact window.

[0053] Furthermore, determining whether the effective impact window is a spurious impact can be based on the following conditions: Condition A: and ; in, This indicates the preset pulse exponential threshold. Indicates the duration of the effective impact window. Indicates the preset duration threshold; Condition B: and ; in, This represents the cross-correlation coefficient between the pressure signal within the effective impact window and the signals at adjacent measuring points. This indicates a preset threshold for the cross-correlation coefficient. This indicates the number of measurement points affecting the effective impact window. This indicates the preset threshold for the number of measurement points affected.

[0054] If the effective impact window satisfies either condition A or condition B, it is determined to be a false impact, and the measurement point corresponding to the effective impact window is removed from the multiple effective measurement points; if the effective impact window does not satisfy condition A or condition B, it is determined to be a real impact signal, and the effective impact window is retained as the target impact window of the target measurement point.

[0055] In this embodiment, effective impact windows of multiple effective measuring points are obtained by impact event detection based on the pressure time series matrix. Furthermore, false impacts are eliminated based on the effective impact windows of multiple effective measuring points to determine the target impact windows of multiple target measuring points. The effective impact windows are quantified and identified using pulse exponent and duration, eliminating interference from non-impact static load compression signals. This ensures that the target impact windows of multiple target measuring points retain only the pressure signals generated by the high-speed ejection of fragments, thus providing an accurate pressure data foundation for subsequent spatiotemporal inversion based on the pressure time series data of the target impact windows of multiple target measuring points.

[0056] In one embodiment, the above step of "performing spatiotemporal inversion based on the pressure time-series data of the target impact window of multiple target measuring points to obtain the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection corresponding to each target measuring point among multiple target measuring points" can be further refined and may include the following steps: Based on the pressure time series data of the target impact window of multiple target measuring points and the preset effective area of ​​a single measuring point, the single measuring point impact impulse of each target measuring point is determined. The equivalent impact kinetic energy corresponding to each target measuring point is determined based on the single-point impact impulse of each target measuring point, the peak pressure of each target measuring point within the target impact window, the effective duration of the target impact window of each target measuring point, and the preset device calibration coefficient. Based on the single-point impact impulse of each target measuring point, the equivalent impact kinetic energy corresponding to each target measuring point, the preset air resistance attenuation coefficient, and the preset sample-sensor gap, the equivalent mass of the fragments corresponding to each target measuring point is determined. Based on the equivalent mass of the fragments corresponding to each target measuring point and the preset sample density, determine the equivalent diameter of the fragments corresponding to each target measuring point. The initial launch velocity of each target measuring point is determined based on the equivalent impact kinetic energy and the equivalent mass of the fragments at each target measuring point.

[0057] Specifically, this embodiment proposes a spatiotemporal inversion mechanism based on the momentum theorem and the principle of energy conservation, in order to convert contact pressure into fragment motion parameters that reflect the physical nature of destruction.

[0058] First, the impact impulse of each target measuring point needs to be determined based on the pressure time-series data of the target impact window of multiple target measuring points and the preset effective area of ​​each measuring point. The pressure time-series data of the target impact window refers to the data sequence of pressure values ​​recorded at the target measuring point as a function of time within the continuous time period corresponding to the target impact window. The effective area of ​​a single measuring point refers to the effective area of ​​a single pressure sensing unit in the thin-film pressure sensor array that senses pressure. The impact impulse of a single measuring point is the product of the integral of the contact pressure over time during the effective duration of the target impact window and the effective area of ​​the single measuring point, used to characterize the momentum change generated when a fragment impacts the target measuring point.

[0059] Regarding this step, in some possible implementations, the pressure time series data of the target impact window of multiple target measuring points can be integrated over time to obtain the pressure integral value of each target measuring point. Then, the pressure integral value of each target measuring point is multiplied by the preset effective area of ​​a single measuring point to determine the single measuring point impact impulse of each target measuring point.

[0060] Furthermore, based on the single-point impact impulse of each target measuring point, the peak pressure of each target measuring point within the target impact window, the effective duration of the target impact window for each target measuring point, and the preset device calibration coefficient, the equivalent impact kinetic energy corresponding to each target measuring point is determined. Here, the peak pressure of the target measuring point within the target impact window refers to the maximum pressure value recorded at the target measuring point within the continuous time period corresponding to the target impact window; the effective duration of the target impact window refers to the continuous time length during which the pressure signal of the target measuring point exceeds the adaptive trigger threshold and then falls back to the adaptive trigger threshold; the device calibration coefficient refers to the calibration parameter used to correct the deviation between the theoretical calculation model and the actual physical collision process. The device refers to the coal and rock impact intensity evaluation device that performs the coal and rock impact intensity evaluation method. The device calibration coefficient can be obtained by impacting the thin-film pressure sensor array in the coal and rock impact intensity evaluation device with a standard sphere of known mass and known velocity, and then back-calculating based on the actual kinetic energy of the standard sphere and the pressure data collected by the coal and rock impact intensity evaluation device, or by simulating the collision process through finite element simulation and fitting the theoretical formula with the simulation data.

[0061] Regarding this step, in some possible implementations, the square of the single-point impact impulse of each target measuring point can be calculated, and the square of the single-point impact impulse of each target measuring point can be divided by the product of the peak pressure of each target measuring point within the target impact window and the effective duration of the target impact window of each target measuring point to obtain the intermediate value of the kinetic energy of each target measuring point. Then, the intermediate value of the kinetic energy of each target measuring point is multiplied by the preset device calibration coefficient to determine the equivalent impact kinetic energy corresponding to each target measuring point.

[0062] Furthermore, based on the single-point impact impulse, the equivalent impact kinetic energy corresponding to each target measuring point, the preset air resistance attenuation coefficient, and the preset sample-sensor gap, the equivalent mass of the fragment corresponding to each target measuring point is determined. The air resistance attenuation coefficient is a physical parameter characterizing the rate of velocity decay of the fragment during flight in the air, and is related to aerodynamic viscosity, fragment characteristic size, and fragment density. The sample-sensor gap refers to the radial distance from the outer surface of the coal / rock sample to the surface of the thin-film pressure sensor array.

[0063] Regarding this step, in some possible implementations, the velocity attenuation index term can be calculated based on the preset air resistance attenuation coefficient and the preset sample-sensor gap. Then, the square of the single-point impact impulse of each target measuring point is divided by the product of the equivalent impact kinetic energy corresponding to each target measuring point and the velocity attenuation index term to determine the equivalent mass of the fragments corresponding to each target measuring point.

[0064] Furthermore, based on the equivalent mass of the fragments corresponding to each target measuring point and the preset sample density, the equivalent diameter of the fragments corresponding to each target measuring point is determined. Here, sample density refers to the ratio of the mass to the volume of the coal and rock sample.

[0065] Regarding this step, in some possible implementations, the equivalent mass of the fragments corresponding to each target measuring point can be divided by the preset sample density to obtain the equivalent volume of the fragments at each target measuring point. Then, based on the geometric conversion relationship between the equivalent volume of the fragments and the equivalent sphere diameter, the equivalent diameter of the fragments corresponding to each target measuring point can be calculated.

[0066] Furthermore, based on the equivalent impact kinetic energy corresponding to each target measuring point and the equivalent mass of the fragments corresponding to each target measuring point, the initial ejection velocity corresponding to each target measuring point is determined.

[0067] Regarding this step, in some possible implementations, the equivalent impact kinetic energy corresponding to each target measuring point can be multiplied by a preset constant two, and the product can be divided by the equivalent mass of the fragments corresponding to each target measuring point. Then, the square root operation is performed on the division result to determine the initial ejection velocity corresponding to each target measuring point.

[0068] For example, the preset sample-sensor gap can be achieved based on the following formula: ; in, This indicates the preset sample-sensor gap. This indicates the diameter of the inner wall of the impact box. This indicates the diameter of the coal and rock sample.

[0069] For example, the drag model used to calculate the velocity attenuation index based on a preset air resistance attenuation coefficient and a preset sample-sensor gap can be implemented based on the following formula: ; in, This indicates the impact velocity when the fragment hits the target measuring point. This represents the initial launch velocity corresponding to the equivalent mass of the fragments. This represents the preset air resistance attenuation coefficient. This indicates the preset sample-sensor gap.

[0070] For example, the preset device calibration coefficients can be calculated by using a standard ball impacting a thin-film pressure sensor array, and can be implemented based on the following formula: ; in, This indicates the preset device calibration coefficient. This represents the true kinetic energy of a standard sphere. This represents the peak pressure recorded by the sensor when a standard sphere is impacted. This indicates the effective duration of a standard sphere impact. This represents the impact impulse recorded by the sensor at a single measurement point when a standard sphere is struck.

[0071] For example, the single-point impact impulse of the target measuring point can be realized based on the following formula: ; in, This represents the impact impulse at a single measuring point of the target measuring point. This represents the preset effective area of ​​a single measuring point. Indicates the start time of the target impact window. Indicates the effective duration of the target impact window. This represents the pressure time series data of the target impact window at the target measuring point.

[0072] The equivalent impact kinetic energy corresponding to the target measuring point can be realized based on the following formula: ; in, This represents the equivalent impact kinetic energy corresponding to the target measuring point. This indicates the preset device calibration coefficient. This represents the impact impulse at a single measuring point of the target measuring point. This indicates the peak pressure at the target measuring point within the target impact window. Indicates the effective duration of the target impact window.

[0073] The equivalent mass of the fragment corresponding to the target measuring point can be realized based on the following formula: ; in, This represents the equivalent mass of the fragment corresponding to the target measuring point. This represents the impact impulse at a single measuring point of the target measuring point. This represents the equivalent impact kinetic energy corresponding to the target measuring point. This represents the preset air resistance attenuation coefficient. This indicates the preset sample-sensor gap.

[0074] The equivalent diameter of the fragment corresponding to the target measuring point can be calculated based on the following formula: ; in, This indicates the equivalent diameter of the fragment corresponding to the target measuring point. This represents the equivalent mass of the fragment corresponding to the target measuring point. This indicates the preset sample density.

[0075] The initial launch velocity corresponding to the target measuring point can be obtained based on the following formula: ; in, This indicates the initial launch velocity corresponding to the target measuring point. This represents the equivalent impact kinetic energy corresponding to the target measuring point. This represents the equivalent mass of the fragment corresponding to the target measuring point.

[0076] In this embodiment, the single-point impact impulse of each target measuring point is determined based on the pressure time series data of the target impact window of multiple target measuring points and the preset effective area of ​​the single measuring point. Furthermore, mathematical calculations are performed by combining the peak pressure of each target measuring point within the target impact window, the effective duration of the target impact window of each target measuring point, the preset device calibration coefficient, the preset air resistance attenuation coefficient, the preset sample-sensor gap, and the preset sample density to convert the contact pressure into the equivalent impact kinetic energy, equivalent mass of the fragment, equivalent diameter of the fragment, and initial ejection velocity corresponding to each target measuring point. This eliminates the physical distortion of contact pressure caused by momentum exchange and energy dissipation during the collision process, and provides fragment motion parameters that reflect the physical nature of destruction for subsequent determination of multiple macroscopic impact events based on the equivalent impact kinetic energy, equivalent mass of the fragment, equivalent diameter of the fragment, and initial ejection velocity corresponding to each target measuring point.

[0077] In one embodiment, the above step of "determining multiple macroscopic impact events based on the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of the ejection corresponding to each target measuring point" can be further refined and may include the following steps: Based on the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, initial velocity of ejection, and spatial and temporal information of each target measuring point, a spatiotemporal feature tensor is constructed. Based on the spatiotemporal feature tensor and the preset density clustering algorithm, and using the preset spatiotemporal neighborhood radius and minimum number of measurement points as clustering conditions, multiple spatiotemporally adjacent target measurement points are clustered and merged to obtain multiple macroscopic impact events.

[0078] Specifically, considering that a single measuring point can only reflect the local fragment impact state and is difficult to represent the overall damage event, this embodiment proposes a clustering and merging mechanism based on spatiotemporal correlation to integrate discrete measuring point responses into a set with spatiotemporal consistency.

[0079] First, a spatiotemporal feature tensor needs to be constructed based on the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, initial velocity of the projectile, and spatial and temporal information corresponding to each target measuring point. Spatial location information refers to parameters characterizing the distribution position of the target measuring point in the spatial coordinate system. For example, spatial location information can include the azimuth and height coordinates of the target measuring point on the inner wall of the impact chamber. Temporal information refers to parameters characterizing the moment of the target impact window. The spatiotemporal feature tensor is a high-dimensional data structure formed by arranging and combining the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of the projectile corresponding to each target measuring point according to the corresponding spatial and temporal information.

[0080] Regarding this step, in some possible implementations, the equivalent impact kinetic energy, equivalent mass of the fragments, equivalent diameter of the fragments, and initial velocity of the ejection corresponding to each target measuring point can be used as feature values, and the spatial location information and time information corresponding to each target measuring point can be used as index dimensions to perform multi-dimensional data recombination in order to construct a spatiotemporal feature tensor.

[0081] Furthermore, based on the spatiotemporal feature tensor and a preset density clustering algorithm, using preset spatiotemporal neighborhood radius and minimum number of measurement points as clustering conditions, multiple spatiotemporally adjacent target measurement points are clustered and merged to obtain multiple macroscopic impact events. Here, the density clustering algorithm refers to a clustering method that divides regions with sufficiently high density into clusters and can discover clusters of arbitrary shapes in noisy spatial databases; the spatiotemporal neighborhood radius refers to the distance threshold in the spatiotemporal feature tensor used to determine whether different target measurement points are adjacent in the spatial and temporal dimensions; the minimum number of measurement points refers to the minimum number of target measurement points required to form an effective cluster in the spatiotemporal feature tensor; and cluster merging refers to the operation of grouping multiple target measurement points that meet the conditions of spatiotemporal neighborhood radius and minimum number of measurement points into the same set.

[0082] Regarding this step, in some possible implementations, the spatiotemporal feature tensor can be input into a preset density clustering algorithm, with a preset spatiotemporal neighborhood radius as the search range and a preset minimum number of measurement points as the core point determination condition. This algorithm identifies spatiotemporally adjacent target measurement points among multiple target measurement points that meet the density requirements in the spatiotemporal feature tensor, and performs clustering and merging on the identified multiple target measurement points. The clusters obtained after clustering and merging are then treated as multiple macroscopic impact events.

[0083] For example, after receiving multiple macroeconomic shock events, regarding the first... The comprehensive parameters of a macroeconomic shock event can be derived based on the following formula: ; ; ; ; ; ; in, Indicates the first The overall momentum of a macroeconomic shock event Indicates the first The set of target measurement points included in a macroeconomic shock event. This represents the equivalent impact kinetic energy corresponding to the target measuring point. Indicates the first The coverage area of ​​a macroeconomic shock event. Indicates the first The number of target measurement points included in a macroeconomic shock event. This represents the preset effective area of ​​a single measuring point. Indicates the first The equivalent total mass of fragments from a macro-level shock event. This represents the equivalent mass of the fragment corresponding to the target measuring point. Indicates the first The weighted average ejection velocity of a macroeconomic shock event. This indicates the initial launch velocity corresponding to the target measuring point. , Indicates the first The spatial centroid coordinates of a macro-level shock event , These represent the azimuth coordinates and altitude coordinates in the spatial location information corresponding to the target measurement point, respectively.

[0084] For example, the spatial distance between two target measurement points involved in constructing the spatiotemporal feature tensor can be achieved based on the following formula: ; in, This represents the spatial distance between two target measurement points. Indicates the radius of the coal and rock sample. This represents the azimuth difference between two target measurement points. This represents the height difference between two target measurement points.

[0085] For example, the spatial location information in the spatiotemporal feature tensor can be constructed based on the following formula: ; ; in, This indicates the azimuth coordinates of the target measuring point on the inner wall of the impact box. This indicates the column index corresponding to the target measurement point. This indicates the number of columns in the thin-film pressure sensor array. This indicates the height coordinates of the target measuring point on the inner wall of the impact box. This indicates the row index corresponding to the target measurement point. Indicates the height of the coal and rock sample; The spatiotemporal feature tensor can be constructed based on the following formula: ; in, Represents the spatiotemporal feature tensor. This represents the azimuth coordinates in spatial location information. This represents the altitude coordinates in spatial location information. Indicates time information, This represents the equivalent impact kinetic energy corresponding to the target measurement point. When the target measurement point has no impact at the time corresponding to the time information, the element value of the spatiotemporal feature tensor is 0. The preset spatiotemporal neighborhood radius can be achieved based on the following formula: ; in, This represents the preset spatiotemporal neighborhood radius. Indicates the angular distance between adjacent target measurement points. , This indicates the height difference between adjacent target measurement points. , This represents the function that takes the maximum value. Indicates the row number of the thin-film pressure sensor array; The preset minimum number of measurement points can be achieved based on the following formula: ; in, This indicates the preset minimum number of measurement points. The value "3" above is only an example and does not constitute a limit. The value restrictions, in fact The value of can be any positive integer.

[0086] In this embodiment, a spatiotemporal feature tensor is constructed based on the equivalent impact kinetic energy, equivalent mass, equivalent diameter, initial velocity of the ejection, spatial location information, and temporal information of each target measuring point. Furthermore, based on the spatiotemporal feature tensor and a preset density clustering algorithm, using a preset spatiotemporal neighborhood radius and a minimum number of measuring points as clustering conditions, spatiotemporally adjacent target measuring points are clustered and merged to obtain multiple macroscopic impact events. This integrates the discrete measuring point responses into a set with spatiotemporal consistency, providing an event-level data foundation for the subsequent extraction of multidimensional feature parameters based on multiple macroscopic impact events.

[0087] In one embodiment, the above step of "extracting multidimensional feature parameters based on multiple macroscopic impact events and determining the impact intensity index of the coal and rock sample based on the multidimensional feature parameters" can be further refined and may include the following steps: Based on multiple macroscopic impact events, at least two of the following are extracted as multidimensional feature parameters: total equivalent impact work, spatial distribution fractal dimension, maximum instantaneous energy release power, b-value of energy-frequency distribution, skewness of fragment velocity distribution, normalized spatial information entropy, spatiotemporal aggregation index, superkurtosis of fragment velocity distribution, temporal nonuniformity of energy release, and spatial nonuniformity of energy release. The impact intensity index of the coal and rock samples was determined based on multidimensional characteristic parameters.

[0088] Specifically, considering that a single impact intensity evaluation parameter is insufficient to fully characterize the complex nonlinear dynamic characteristics exhibited by coal and rock samples during the failure process, this embodiment proposes an impact intensity evaluation mechanism based on the fusion of multidimensional characteristic parameters.

[0089] First, based on multiple macroscopic impact events, at least two of the following should be extracted as multidimensional feature parameters: total equivalent impact work, spatial distribution fractal dimension, maximum instantaneous energy release power, b-value of energy-frequency distribution, skewness of fragment velocity distribution, normalized spatial information entropy, spatiotemporal aggregation index, superkurtosis of fragment velocity distribution, temporal nonuniformity of energy release, and spatial nonuniformity of energy release. Among them, the total equivalent impact energy refers to the quantitative index characterizing the total kinetic energy released by the coal and rock sample in the form of fragment ejection during the entire loading and failure process; the spatial distribution fractal dimension refers to the geometric characteristic parameter characterizing the degree of concentration of the spatial distribution of macroscopic impact events on the surface of the coal and rock sample; the maximum instantaneous energy release power refers to the quantitative index characterizing the intensity of energy release per unit time; the b-value of the energy-frequency distribution refers to the statistical parameter characterizing the proportional relationship of the frequency of macroscopic impact events at different energy levels; the skewness of the fragment velocity distribution refers to the statistical characteristic quantity characterizing the asymmetry of the probability distribution of fragment ejection velocity corresponding to the macroscopic impact event; the normalized spatial information entropy refers to the quantitative index characterizing the degree of disorder in the spatial distribution of macroscopic impact events on the surface of the coal and rock sample; the spatiotemporal aggregation index refers to the quantitative index characterizing the aggregation characteristics of macroscopic impact events in the time and space dimensions; the superkurtosis of the fragment velocity distribution refers to the statistical characteristic quantity characterizing the tail thickness of the probability distribution of fragment ejection velocity corresponding to the macroscopic impact event; the temporal nonuniformity of energy release refers to the quantitative index characterizing the degree of fluctuation in the time interval between adjacent macroscopic impact events; and the spatial nonuniformity of energy release refers to the quantitative index characterizing the degree of fluctuation in the spatial distance between adjacent macroscopic impact events. It should be noted that the above "at least two" means any combination of two or more of the listed multidimensional characteristic parameters. The limitation of "at least two" is because a single characteristic parameter can only reflect one aspect of the impact failure process. For example, using only the total equivalent impact energy cannot distinguish whether the energy release is concentrated locally or diffused throughout the whole. By combining at least two multidimensional characteristic parameters, cross-validation and complementary constraints can be formed from multiple dimensions such as total energy, release rate, spatiotemporal distribution, and velocity statistics, thereby effectively improving the discriminability and robustness of the final determined impact intensity index of the coal and rock sample.

[0090] Regarding this step, some possible implementations include: accumulating the total kinetic energy of each macroscopic impact event in multiple macroscopic impact events and using the accumulated result as the total equivalent impact work; fitting the spatial distribution of multiple macroscopic impact events using box counting and using the absolute value of the slope obtained from the fitting calculation as the fractal dimension of the spatial distribution; statistically analyzing the kinetic energy of multiple macroscopic impact events within a preset sliding time window and using the maximum rate of change of kinetic energy obtained from the statistics as the maximum instantaneous energy release power; calculating the energy magnitude frequency distribution of multiple macroscopic impact events based on the maximum likelihood method and using the calculated result as the b-value of the energy-frequency distribution; performing third-order moment statistics on the weighted average velocity sample set of multiple macroscopic impact events and using the statistical result as the skewness of the fragment velocity distribution; and dividing the coal and rock sample surface into... Multiple grids are analyzed, and the impact probability of each grid is statistically calculated. Based on the probability distribution, a normalized information entropy value is calculated and used as the normalized spatial information entropy. The spatiotemporal point-pair density of multiple macroscopic impact events can be integrally calculated based on the spatiotemporal correlation function. The integral result is then compared with a randomly distributed reference value, and the ratio is used as the spatiotemporal aggregation index. Fourth-order moment statistics can be performed on the weighted average velocity sample set of multiple macroscopic impact events, and a preset constant is subtracted. The statistical processing result is used as the superkurtosis of the fragment velocity distribution. The coefficient of variation of the time interval between adjacent events in multiple macroscopic impact events can be calculated, and the calculated coefficient of variation is used as the temporal nonuniformity of energy release. The coefficient of variation of the spatial distance between adjacent events in multiple macroscopic impact events can be calculated, and the calculated coefficient of variation is used as the spatial nonuniformity of energy release.

[0091] In practical applications, the specific selection of which of the ten multidimensional feature parameters to extract can be flexibly configured according to the actual needs of coal and rock impact intensity evaluation. For example, if the actual need focuses on the rapid classification of the severity of impact damage, the total equivalent impact work, maximum instantaneous energy release power, and spatial distribution fractal dimension can be mainly extracted. If the actual need focuses on the in-depth dynamic mechanism analysis of the evolution process of rockburst disasters, the b-value of energy-frequency distribution, the skewness of fragment velocity distribution, normalized spatial information entropy, spatiotemporal aggregation index, superkurtosis of fragment velocity distribution, temporal nonuniformity of energy release, and spatial nonuniformity of energy release can be further extracted. This embodiment does not limit the types and number of multidimensional feature parameters to be extracted.

[0092] Furthermore, the impact intensity index of the coal and rock samples was determined based on the multidimensional characteristic parameters.

[0093] Regarding this step, in some possible implementations, the multidimensional feature parameters can be input into a preset fusion model, and the multidimensional feature parameters can be weighted and fused using the preset fusion model. The weighted fusion calculation result can then be used as the impact intensity index of the coal and rock sample.

[0094] For example, the total equivalent impact work can be achieved based on the following formula: ; in, This represents the total equivalent impact work. Indicates the first The overall momentum of a macroeconomic shock event This represents the total number of multiple macroeconomic shock events; The spatial distribution fractal dimension can be realized based on the following formula: ; in, The fractal dimension represents the spatial distribution. Indicates the side length of the covering grid. Indicates a side length of The number of non-empty cells in the grid. Represents the fitting constant; The maximum instantaneous energy release power can be achieved based on the following formula: ; ; in, Indicates the maximum instantaneous energy release power. This represents the instantaneous energy release power within the sliding time window. This represents the total kinetic energy of all impact events occurring within the sliding time window. Indicates the duration of the sliding time window. This represents the maximum instantaneous power released during the entire process; Before calculating the b-value of the energy-frequency distribution, the energy magnitude for each macroscopic shock event can be defined based on the following formula: ; in, Indicates the first The energy magnitude of a macro-level shock event. Indicates the first The overall momentum of a macroeconomic shock event This represents the preset magnitude constant.

[0095] The b-value of the energy-frequency distribution can be obtained based on the following formula: ; in, The b-value represents the energy-frequency distribution. This represents the average energy magnitude of all macroscopic shock events. This represents the minimum energy magnitude recorded in the complete record. Represents the natural constant; The skewness of the velocity distribution of the fragments can be determined based on the following formula: ; in, Indicates the skewness of the velocity distribution of the fragments. Indicates the number of macroeconomic shock events. Indicates the first The weighted average ejection velocity of a macroeconomic shock event. This represents the weighted average ejection velocity of all macroscopic shock events. The standard deviation of the weighted average ejection velocity for all macroscopic shock events; Normalized spatial information entropy can be achieved based on the following formula: ; ; in, Represents the normalized spatial information entropy. Represents spatial information entropy. This represents the total number of equal-area grids that divide the surface of the coal and rock sample. Indicates the first The probability of a macroscopic shock event occurring in a grid cell; The spatiotemporal correlation function used in calculating the spatiotemporal clustering index can be realized based on the following formula: ; in, Represents the spatiotemporal correlation function. This indicates the time interval between two macroeconomic shock events. This indicates the spatial distance between two macroeconomic shock events. This represents the total number of combinations of macroeconomic shock events. Represents the Dirac function, , They represent the first The and the first The timing of a macroeconomic shock event Indicates the first The and the first Spatial distance between macro-level shock events , They represent the first The and the first The overall momentum of a macroeconomic shock event This represents the average of the total kinetic energy of all macroeconomic shock events.

[0096] The spatiotemporal clustering index can be calculated based on the following formula: ; in, Indicates the spatiotemporal aggregation index. The spatiotemporal correlation function representing macroscopic shock events, This indicates the time interval between two macroeconomic shock events. This indicates the spatial distance between two macroeconomic shock events. This indicates the preset maximum time interval. This indicates the preset maximum spatial distance. Correlation functions representing completely random spatiotemporal point processes; The hyperkurtosis of the fragment velocity distribution can be achieved based on the following formula: ; in, The superkure of the fragment velocity distribution is represented by... Indicates the number of macroeconomic shock events. Indicates the first The weighted average ejection velocity of a macroeconomic shock event. This represents the weighted average ejection velocity of all macroscopic shock events. The standard deviation of the weighted average ejection velocity for all macroscopic shock events; The temporal nonuniformity of energy release can be determined based on the following formula: ; in, This indicates the time non-uniformity of energy release. This indicates the number of time intervals between adjacent macroeconomic shock events. Indicates the first The time interval between two adjacent macroeconomic shock events This represents the average time interval between all adjacent macroscopic shock events; The spatial non-uniformity of energy release can be determined based on the following formula: ; in, This indicates the spatial non-uniformity of energy release. This represents the quantity indicating the spatial distance between adjacent macroscopic shock events. Indicates the first Spatial distance between adjacent macroeconomic shock events This represents the average spatial distance between all adjacent macroscopic shock events.

[0097] In this embodiment, at least two of the following parameters are extracted from multiple macroscopic impact events: total equivalent impact work, spatial distribution fractal dimension, maximum instantaneous energy release power, b-value of energy-frequency distribution, skewness of fragment velocity distribution, normalized spatial information entropy, spatiotemporal aggregation index, superkurtosis of fragment velocity distribution, temporal nonuniformity of energy release, and spatial nonuniformity of energy release. These parameters are then used as multidimensional feature parameters to determine the impact intensity index of the coal and rock sample. By combining the quantitative information of multiple macroscopic impact events in terms of total energy, release rate, spatial distribution, time interval, and velocity statistics, the impact intensity index of the coal and rock sample is established on the basis of cross-constraint of multidimensional feature parameters, thereby accurately reflecting the spatiotemporal evolution characteristics of impact damage in the coal and rock sample.

[0098] In one embodiment, the step of "determining the impact intensity index of the coal and rock sample based on multidimensional characteristic parameters" can be further refined and may include any one of the following: The impact intensity index of the coal and rock sample is determined by a pre-set weighted power exponent model based on the total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power among the multidimensional characteristic parameters. Based on the total equivalent impact energy, the b-value of the energy-frequency distribution, and the normalized spatial information entropy in the multidimensional characteristic parameters, the impact intensity index of the coal and rock sample is determined by a pre-set probabilistic risk model. Based on the total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power in the multidimensional characteristic parameters, the impact intensity index of the coal and rock sample is determined by a preset principal component analysis adaptive model. The impact intensity index of the coal and rock sample is determined by using the total equivalent impact energy, spatial distribution fractal dimension, maximum instantaneous energy release power, skewness of fragment velocity distribution, spatiotemporal aggregation index, supercluster degree of fragment velocity distribution, temporal nonuniformity of energy release, and spatial nonuniformity of energy release from the multidimensional characteristic parameters.

[0099] Specifically, considering that different application scenarios have different focuses on impact intensity evaluation, this embodiment proposes a mechanism for constructing multiple fusion models based on multidimensional feature parameters to determine the impact intensity index of coal and rock samples.

[0100] On the one hand, the impact intensity index of coal and rock samples can be determined by using a pre-defined weighted power exponent model based on the total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power among the multidimensional characteristic parameters. The weighted power exponent model refers to a mathematical model that nonlinearly couples the energy accumulation effect, instantaneous burst intensity, and spatial damage concentration.

[0101] Regarding this step, in some possible implementations, the total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power can be extracted from multidimensional feature parameters. The total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power can be input into a preset weighted power exponent model. The total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power can be nonlinearly weighted by the preset weighted power exponent model. The result of the nonlinear weighted operation is used as the impact intensity index of the coal and rock sample.

[0102] For example, the total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power can be nonlinearly weighted using a pre-defined weighted power exponent model. The result of the nonlinear weighted calculation can be used as the impact intensity index of the coal and rock sample, which can be achieved based on the following formula: ; in, An impact intensity index representing a coal and rock sample. This represents the total equivalent impact work. This represents the normalized reference value for the total equivalent impact work. The weighting index represents the total equivalent impact work. Indicates the maximum instantaneous energy release power. This represents a normalized reference value indicating the maximum instantaneous power released. The weighted index representing the maximum instantaneous energy release power. Represents the natural constant. The weighted index representing the fractal dimension of spatial distribution. It represents the fractal dimension of spatial distribution.

[0103] On the one hand, the impact intensity index of coal and rock samples can be determined by using a pre-defined probabilistic risk model based on the total equivalent impact energy, the b-value of the energy-frequency distribution, and the normalized spatial information entropy among the multidimensional characteristic parameters. The probabilistic risk model refers to a mathematical model that combines the principles of seismic statistics with information entropy theory to assess the probability of system instability.

[0104] Regarding this step, in some possible implementations, the total equivalent impact energy, the b-value of the energy-frequency distribution, and the normalized spatial information entropy can be extracted from the multidimensional feature parameters. The total equivalent impact energy, the b-value of the energy-frequency distribution, and the normalized spatial information entropy can be input into a preset probabilistic risk model. The total equivalent impact energy, the b-value of the energy-frequency distribution, and the normalized spatial information entropy can be fused and calculated through the preset probabilistic risk model. The fused calculation result can be used as the impact intensity index of the coal and rock sample.

[0105] For example, by using a pre-defined probabilistic risk model to fuse the total equivalent impact energy, the b-value of the energy-frequency distribution, and the normalized spatial information entropy, the fused calculation result can be used as the impact intensity index of the coal and rock sample. This can be achieved based on the following formula: ; in, An impact intensity index representing a coal and rock sample. The b-value represents the energy-frequency distribution. Represents the normalized spatial information entropy. Represents the natural logarithm function. It represents the total equivalent impact work.

[0106] On the one hand, the impact intensity index of coal and rock samples can be determined by using a pre-defined principal component analysis adaptive model based on the total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power among the multidimensional characteristic parameters. The principal component analysis adaptive model refers to a statistical learning model that performs dimensionality reduction based on the characteristic distribution of historical sample data and dynamically adjusts the feature weights through a data-driven approach.

[0107] Regarding this step, in some possible implementations, the total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power can be extracted from the multidimensional feature parameters. The total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power are then input into a preset principal component analysis adaptive model. The total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power are then projected and transformed using the preset principal component analysis adaptive model. The projection transformation result is then used as the impact intensity index of the coal and rock sample.

[0108] For example, by using a pre-defined principal component analysis adaptive model to perform a projection transformation on the total equivalent impact energy, the spatial distribution fractal dimension, and the maximum instantaneous energy release power, and using the projection transformation result as the impact intensity index of the coal and rock sample, it can be achieved based on the following formula: ; in, An impact intensity index representing a coal and rock sample. This represents the standardized feature vector of the current coal and rock sample. This represents the first principal component eigenvector calculated based on historical sample data.

[0109] On the one hand, the impact intensity index of coal and rock samples can be determined by using a pre-defined generalized energy index model based on multidimensional characteristic parameters such as total equivalent impact energy, spatial distribution fractal dimension, maximum instantaneous energy release power, skewness of fragment velocity distribution, spatiotemporal aggregation index, superkurtosis of fragment velocity distribution, temporal nonuniformity of energy release, and spatial nonuniformity of energy release. The generalized energy index model refers to a comprehensive evaluation mathematical model that fully integrates total energy, release rate, spatiotemporal distribution nonuniformity, and higher-order characteristics of velocity statistics.

[0110] Regarding this step, in some possible implementations, the total equivalent impact energy, spatial distribution fractal dimension, maximum instantaneous energy release power, fragment velocity distribution skewness, spatiotemporal aggregation index, fragment velocity distribution superkurtosis, energy release temporal nonuniformity, and energy release spatial nonuniformity can be extracted from multidimensional feature parameters. These parameters are then input into a pre-defined generalized energy index model. The model performs multi-factor coupling calculations on these parameters, using the results as the impact intensity index of the coal and rock sample.

[0111] For example, a pre-defined generalized energy index model is used to perform multi-factor coupled calculations on the total equivalent impact energy, spatial distribution fractal dimension, maximum instantaneous energy release power, skewness of fragment velocity distribution, spatiotemporal aggregation index, superkurtosis of fragment velocity distribution, temporal nonuniformity of energy release, and spatial nonuniformity of energy release. The results of the multi-factor coupled calculations are used as the impact intensity index of the coal and rock sample, which can be achieved based on the following formula: ; in, An impact intensity index representing a coal and rock sample. This represents the total equivalent impact work. This represents the normalized reference value for the total equivalent impact work. The weighting index represents the total equivalent impact work. Indicates the maximum instantaneous energy release power. This represents a normalized reference value indicating the maximum instantaneous power released. The weighted index representing the maximum instantaneous energy release power. Represents the natural constant. The weighted index representing the fractal dimension of spatial distribution. The fractal dimension represents the spatial distribution. Indicates the spatiotemporal aggregation index. The weighting index represents the spatiotemporal aggregation index. A weighted index representing the skewness of the velocity distribution of the fragments. Indicates the skewness of the velocity distribution of the fragments. The superkure of the fragment velocity distribution is represented by... A weighted index representing the superkurtosis of the fragment velocity distribution. This indicates the time non-uniformity of energy release. A weighted index representing the temporal nonuniformity of energy release. This indicates the spatial non-uniformity of energy release. A weighted index representing the spatial non-uniformity of energy release.

[0112] In this embodiment, a preset weighted power exponent model, a preset probability risk model, a preset principal component analysis adaptive model, and a preset generalized energy index model are constructed based on different combinations of feature parameters in the multidimensional feature parameters. The corresponding multidimensional feature parameters are then input into the corresponding models for calculation to determine the impact intensity index of the coal and rock sample. This allows the determination of the impact intensity index of the coal and rock sample to be based on multidimensional quantification of total equivalent impact energy, spatial distribution fractal dimension, maximum instantaneous energy release power, b-value of energy-frequency distribution, normalized spatial information entropy, skewness of fragment velocity distribution, spatiotemporal aggregation index, superkurtosis of fragment velocity distribution, temporal nonuniformity of energy release, and spatial nonuniformity of energy release, thereby reflecting the spatiotemporal evolution characteristics of impact damage of the coal and rock sample.

[0113] The following will combine Figure 2 and Figure 3 This application provides a detailed description of the coal and rock impact intensity evaluation device 800 provided in its embodiments. For example... Figure 2 As shown, the coal and rock impact intensity evaluation device 800 and the coal and rock impact intensity evaluation method described above can be referred to each other. Specifically, the coal and rock impact intensity evaluation device 800 may include an impact box 810, a thin-film pressure sensor array 820, and a data processing terminal 830, as detailed below: The punch box 810 is a cylindrical box with an opening at the top, used to place coal and rock samples; A thin-film pressure sensor array 820 is distributed around the inner wall of the impact box 810 and is communicatively connected to the data processing terminal 830. It is used to collect voltage timing signals during the failure process of the coal and rock sample and provide voltage timing signals to the data processing terminal 830. The data processing terminal 830 is used to execute the steps of the above-described embodiments of the coal and rock impact intensity evaluation method.

[0114] Specifically, the impact box 810 is a cylindrical box with an open top, meaning that the impact box 810 has a hollow cylindrical geometric structure with no obstruction at the top, such as a cylindrical shell made of transparent material or metal; the impact box 810 is used to place coal and rock samples, for example, the coal and rock samples can be kept centered and fixed inside the impact box 810.

[0115] The thin-film pressure sensor array 820 is distributed around the inner wall of the impact box 810, meaning that the thin-film pressure sensor array 820 is arranged in a closed circumferential shape along the inner wall of the impact box 810. For example, the thin-film pressure sensor array 820 is attached and fixed to the entire circumference of the inner wall of the impact box 810. The thin-film pressure sensor array 820 is communicatively connected to the data processing terminal 830, meaning that a signal path capable of data transmission is established between the thin-film pressure sensor array 820 and the data processing terminal 830. For example, the thin-film pressure sensor array 820 is connected to the data processing terminal 830 through a data cable or a wireless transmission module.

[0116] The thin-film pressure sensor array 820 is used to acquire voltage timing signals during the failure process of the coal and rock sample. This means that the thin-film pressure sensor array 820 continuously senses and records the sequence of electrical signal changes generated by the impact of fragments during the time period when the coal and rock sample fails. The thin-film pressure sensor array 820 is used to provide voltage timing signals to the data processing terminal 830, which can be manifested as the thin-film pressure sensor array 820 sending the acquired electrical signal change sequence to the data processing terminal 830 in real time or in batches.

[0117] It is understandable that after receiving the voltage timing signal provided by the thin-film pressure sensor array 820, the data processing terminal 830 performs matrix reconstruction of the voltage timing signal according to the spatial arrangement order of each measuring point in the thin-film pressure sensor array 820 and the timestamp corresponding to the voltage timing signal, thereby realizing the step of obtaining the voltage timing matrix of the thin-film pressure sensor array after the coal and rock sample is damaged by pressure loading.

[0118] Optionally, in some embodiments, the data processing terminal 830 can be used for: Based on the preset voltage-pressure mapping relationship, the voltage values ​​of each measuring point in the voltage time sequence matrix are converted to obtain the pressure values ​​corresponding to each measuring point; A pressure time series matrix is ​​constructed based on the pressure values ​​corresponding to each measuring point.

[0119] Optionally, in some embodiments, the data processing terminal 830 can be used for: Impact event detection is performed based on the pressure time series matrix to obtain the effective impact window for multiple effective measurement points; False impacts are eliminated based on the effective impact windows of multiple effective measuring points to determine multiple target measuring points from multiple effective measuring points, and target impact windows of multiple target measuring points are determined from the effective impact windows of multiple target measuring points.

[0120] Optionally, in some embodiments, the data processing terminal 830 can be used for: Based on the pressure time series data of the target impact window of multiple target measuring points and the preset effective area of ​​a single measuring point, the single measuring point impact impulse of each target measuring point is determined. The equivalent impact kinetic energy corresponding to each target measuring point is determined based on the single-point impact impulse of each target measuring point, the peak pressure of each target measuring point within the target impact window, the effective duration of the target impact window of each target measuring point, and the preset device calibration coefficient. Based on the single-point impact impulse of each target measuring point, the equivalent impact kinetic energy corresponding to each target measuring point, the preset air resistance attenuation coefficient, and the preset sample-sensor gap, the equivalent mass of the fragments corresponding to each target measuring point is determined. Based on the equivalent mass of the fragments corresponding to each target measuring point and the preset sample density, determine the equivalent diameter of the fragments corresponding to each target measuring point. The initial launch velocity of each target measuring point is determined based on the equivalent impact kinetic energy and the equivalent mass of the fragments at each target measuring point.

[0121] Optionally, in some embodiments, the data processing terminal 830 can be used for: Based on the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, initial velocity of ejection, and spatial and temporal information of each target measuring point, a spatiotemporal feature tensor is constructed. Based on the spatiotemporal feature tensor and the preset density clustering algorithm, and using the preset spatiotemporal neighborhood radius and minimum number of measurement points as clustering conditions, multiple spatiotemporally adjacent target measurement points are clustered and merged to obtain multiple macroscopic impact events.

[0122] Optionally, in some embodiments, the data processing terminal 830 can be used for: Based on multiple macroscopic impact events, at least two of the following are extracted as multidimensional feature parameters: total equivalent impact work, spatial distribution fractal dimension, maximum instantaneous energy release power, b-value of energy-frequency distribution, skewness of fragment velocity distribution, normalized spatial information entropy, spatiotemporal aggregation index, superkurtosis of fragment velocity distribution, temporal nonuniformity of energy release, and spatial nonuniformity of energy release. The impact intensity index of the coal and rock samples was determined based on multidimensional characteristic parameters.

[0123] Optionally, in some embodiments, the data processing terminal 830 can be used for: The impact intensity index of the coal and rock sample is determined by a pre-set weighted power exponent model based on the total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power among the multidimensional characteristic parameters. Based on the total equivalent impact energy, the b-value of the energy-frequency distribution, and the normalized spatial information entropy in the multidimensional characteristic parameters, the impact intensity index of the coal and rock sample is determined by a pre-set probabilistic risk model. Based on the total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power in the multidimensional characteristic parameters, the impact intensity index of the coal and rock sample is determined by a preset principal component analysis adaptive model. The impact intensity index of the coal and rock sample is determined by using the total equivalent impact energy, spatial distribution fractal dimension, maximum instantaneous energy release power, skewness of fragment velocity distribution, spatiotemporal aggregation index, supercluster degree of fragment velocity distribution, temporal nonuniformity of energy release, and spatial nonuniformity of energy release from the multidimensional characteristic parameters.

[0124] like Figure 3 As shown, in some embodiments, the coal and rock impact intensity evaluation device 800 further includes a rock press 840, which includes a worktable 841, a loading cylinder 842, and a loading plate 843. Workbench 841 is used to place punch box 810; The lower part of the loading cylinder 842 is connected to the loading plate, which is used to drive the loading plate 843 to move and make the loading plate 843 generate pressure on the coal and rock sample; The center of the loading plate 843 coincides with the center of the impact box 810.

[0125] Specifically, the worktable 841 provides a horizontal support surface for the rock press 840, and the impact box 810 is placed on this horizontal support surface; the loading cylinder 842 serves as the power output source for the rock press 840, and the loading plate 843 connected to its lower part moves downward in the vertical direction under the drive of the loading cylinder 842 until the loading plate 843 contacts the coal and rock sample located in the impact box 810 and applies a continuously increasing axial pressure; by aligning the center of the loading plate 843 with the center of the impact box 810, it can be ensured that the coal and rock sample is subjected to uniform force during uniaxial compression, and the eccentric loading can be avoided from interfering with the voltage timing signal collected by the thin film pressure sensor array 820.

[0126] The effects achievable in this embodiment can be found in the relevant embodiments of the coal and rock impact intensity evaluation method described above, and will not be repeated here.

[0127] In one embodiment, please refer to Figure 4The coal and rock impact intensity evaluation device includes a rock press 840, an impact box 810, a thin-film pressure sensor array 820, and a data processing terminal 830. The rock press 840 includes a worktable 841, a loading cylinder 842, and a loading plate 843. A double-arrow connecting line indicates a communication connection between the thin-film pressure sensor array 820 and the data processing terminal 830. The worktable 841 is used to place the impact box 810, which is a cylindrical box with an open top. The coal and rock sample 900 is placed inside the impact box 810. The thin-film pressure sensor array 820 is distributed around the inner wall of the impact box 810 and is used to collect voltage timing signals during the failure process of the coal and rock sample 900. The thin-film pressure sensor array 820 and the data processing terminal 830 are communicatively connected via the double-arrow connecting line. The thin-film pressure sensor array 820 provides voltage timing signals to the data processing terminal 830, which executes the coal and rock impact intensity evaluation method. The lower part of the loading cylinder 842 is connected to the loading plate 843. The loading cylinder 842 is used to drive the loading plate 843 to move and make the loading plate 843 generate pressure on the coal and rock sample 900. The center of the loading plate 843 coincides with the center of the impact box 810.

[0128] In this embodiment, a rock press 840 applies pressure to a coal and rock sample 900 placed in a punching box 810, causing the coal and rock sample 900 to break. A thin-film pressure sensor array 820 distributed around the inner wall of the punching box 810 collects voltage timing signals during the breaking process of the coal and rock sample 900, and transmits the voltage timing signals to a data processing terminal 830 through a double-arrow connection line. The data processing terminal 830 processes the received voltage timing signals to execute the coal and rock impact intensity evaluation method, thereby achieving an accurate evaluation of the impact intensity of the coal and rock sample 900.

[0129] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can perform the steps of the coal and rock impact intensity evaluation method provided in the above embodiments, such as including: The voltage timing matrix of the thin-film pressure sensor array after the coal and rock sample was damaged by pressure loading was obtained. The thin-film pressure sensor array was distributed around the periphery of the coal and rock sample, and the thin-film pressure sensor in the thin-film pressure sensor array corresponded one-to-one with the measuring point. The voltage time series matrix is ​​transformed according to the preset voltage-pressure mapping relationship to obtain the pressure time series matrix; Impact event detection and false impact elimination are performed based on the pressure time series matrix to determine the target impact window for multiple target measurement points. Spatiotemporal inversion is performed based on the pressure time series data of the target impact window of multiple target measuring points to obtain the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection for each target measuring point in the multiple target measuring points. Multiple macroscopic impact events are determined based on the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection corresponding to each target measuring point. Multidimensional characteristic parameters were extracted from multiple macroscopic impact events, and the impact intensity index of the coal and rock samples was determined based on the multidimensional characteristic parameters.

[0130] The effects achievable in this embodiment can be found in the relevant embodiments of the coal and rock impact intensity evaluation method described above, and will not be repeated here.

[0131] Non-transitory computer-readable storage media can be any available medium or data storage device that can be accessed by a processor, including but not limited to magnetic storage (e.g., floppy disks, hard disks, magnetic tapes, magneto-optical disks (MOs), etc.), optical storage (e.g., CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (e.g., ROMs, EPROMs, EEPROMs, non-volatile memory (NAND flash), solid-state drives (SSDs)).

[0132] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0133] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of various embodiments or some parts of embodiments.

[0134] All actions involving the acquisition of signal information or data in this application were carried out in compliance with the relevant data protection laws and policies of the country where the application is located, and with the authorization granted by the owner of the relevant device. Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for evaluating the impact intensity of coal and rock, characterized in that, include: The voltage timing matrix of the thin-film pressure sensor array after the coal and rock sample is damaged by pressure loading is obtained. The thin-film pressure sensor array is distributed around the periphery of the coal and rock sample, and the thin-film pressure sensor in the thin-film pressure sensor array corresponds one-to-one with the measuring point. The voltage timing matrix is ​​transformed according to the preset voltage-pressure mapping relationship to obtain the pressure timing matrix; Impact event detection and false impact elimination are performed based on the pressure time series matrix to determine the target impact window for multiple target measurement points. Spatiotemporal inversion is performed based on the pressure time series data of the target impact window of the multiple target measuring points to obtain the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection for each target measuring point among the multiple target measuring points. Multiple macroscopic impact events are determined based on the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of ejection corresponding to each target measuring point. Multidimensional feature parameters are extracted based on the multiple macroscopic impact events, and the impact intensity index of the coal and rock sample is determined based on the multidimensional feature parameters.

2. The method for evaluating the impact intensity of coal and rock according to claim 1, characterized in that, The step of transforming the voltage time series matrix according to a preset voltage-pressure mapping relationship to obtain the pressure time series matrix includes: Based on the preset voltage-pressure mapping relationship, the voltage values ​​of each measuring point in the voltage time series matrix are converted to obtain the pressure values ​​corresponding to each measuring point; Based on the pressure values ​​corresponding to each measuring point, a pressure time series matrix is ​​constructed.

3. The method for evaluating the impact intensity of coal and rock according to claim 1, characterized in that, The step of detecting impact events and eliminating false impacts based on the pressure time series matrix to determine the target impact window for multiple target measurement points includes: Impact event detection is performed based on the pressure time series matrix to obtain the effective impact window for multiple effective measurement points; False impacts are eliminated based on the effective impact windows of the multiple effective measuring points to determine multiple target measuring points from the multiple effective measuring points, and the target impact windows of the multiple target measuring points are determined from the effective impact windows of the multiple target measuring points.

4. The method for evaluating the impact intensity of coal and rock according to claim 1, characterized in that, The step of performing spatiotemporal inversion based on the pressure time-series data of the target impact window from the multiple target measuring points to obtain the equivalent impact kinetic energy, equivalent mass of the fragments, equivalent diameter of the fragments, and initial velocity of the projectile for each target measuring point includes: Based on the pressure time series data of the target impact window of the multiple target measuring points and the preset effective area of ​​a single measuring point, the single measuring point impact impulse of each target measuring point is determined. The equivalent impact kinetic energy corresponding to each target measuring point is determined based on the single-point impact impulse of each target measuring point, the peak pressure of each target measuring point within the target impact window, the effective duration of the target impact window of each target measuring point, and the preset device calibration coefficient. The equivalent mass of the fragments corresponding to each target measuring point is determined based on the single-point impact impulse of each target measuring point, the equivalent impact kinetic energy corresponding to each target measuring point, the preset air resistance attenuation coefficient, and the preset sample-sensor gap. Based on the equivalent mass of the fragments corresponding to each target measuring point and the preset sample density, the equivalent diameter of the fragments corresponding to each target measuring point is determined. The initial launch velocity corresponding to each target measuring point is determined based on the equivalent impact kinetic energy and the equivalent mass of the fragments corresponding to each target measuring point.

5. The method for evaluating the impact intensity of coal and rock according to claim 1, characterized in that, The determination of multiple macroscopic impact events based on the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, and initial velocity of the projectile corresponding to each target measuring point includes: Based on the equivalent impact kinetic energy, equivalent mass of fragments, equivalent diameter of fragments, initial velocity of ejection corresponding to each target measuring point, as well as the spatial position information and time information corresponding to each target measuring point, a spatiotemporal feature tensor is constructed. Based on the spatiotemporal feature tensor and the preset density clustering algorithm, using the preset spatiotemporal neighborhood radius and minimum number of measurement points as clustering conditions, spatiotemporally adjacent target measurement points among the multiple target measurement points are clustered and merged to obtain multiple macroscopic impact events.

6. The method for evaluating the impact intensity of coal and rock according to claim 1, characterized in that, The step of extracting multidimensional feature parameters based on the multiple macroscopic impact events and determining the impact intensity index of the coal and rock sample based on the multidimensional feature parameters includes: Based on the aforementioned multiple macroscopic impact events, at least two of the following are extracted as multidimensional feature parameters: total equivalent impact work, spatial distribution fractal dimension, maximum instantaneous energy release power, b-value of energy-frequency distribution, skewness of fragment velocity distribution, normalized spatial information entropy, spatiotemporal aggregation index, superkurtosis of fragment velocity distribution, temporal nonuniformity of energy release, and spatial nonuniformity of energy release. The impact intensity index of the coal and rock sample is determined based on the multidimensional characteristic parameters.

7. The method for evaluating the impact intensity of coal and rock according to claim 6, characterized in that, The determination of the impact intensity index of the coal and rock sample based on the multidimensional characteristic parameters includes any one of the following: Based on the total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power in the multidimensional characteristic parameters, the impact intensity index of the coal and rock sample is determined by a preset weighted power exponent model. Based on the total equivalent impact energy, the b-value of the energy-frequency distribution, and the normalized spatial information entropy in the multidimensional characteristic parameters, the impact intensity index of the coal and rock sample is determined by a preset probability risk model. Based on the total equivalent impact energy, spatial distribution fractal dimension, and maximum instantaneous energy release power in the multidimensional characteristic parameters, the impact intensity index of the coal and rock sample is determined by a preset principal component analysis adaptive model. The impact intensity index of the coal and rock sample is determined by a preset generalized energy index model based on the total equivalent impact energy, spatial distribution fractal dimension, maximum instantaneous energy release power, skewness of fragment velocity distribution, spatiotemporal aggregation index, supercluster degree of fragment velocity distribution, temporal nonuniformity of energy release, and spatial nonuniformity of energy release among the multidimensional characteristic parameters.

8. A device for evaluating the impact intensity of coal and rock, characterized in that, The coal and rock impact intensity evaluation device includes an impact box, a thin-film pressure sensor array, and a data processing terminal. The receiving box is a cylindrical box with an opening at the top, used to place coal and rock samples; The thin-film pressure sensor array is distributed around the inner wall of the impact box and is communicatively connected to the data processing terminal. It is used to collect voltage timing signals during the failure process of the coal and rock sample and to provide the voltage timing signals to the data processing terminal. The data processing terminal is used to execute the coal and rock impact intensity evaluation method according to any one of claims 1 to 7.

9. The coal and rock impact intensity evaluation device according to claim 8, characterized in that, The coal and rock impact intensity evaluation device also includes a rock press, which includes a worktable, a loading cylinder and a loading plate. The workbench is used to place the punch box; The lower part of the loading cylinder is connected to the loading plate, which is used to drive the loading plate to move and make the loading plate exert pressure on the coal and rock sample; The center of the loading plate coincides with the center of the impact box.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the coal and rock impact intensity evaluation method according to any one of claims 1 to 7.

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