A method of continuous mining and filling for breaking thick ore bodies

Abstract

The application provides a kind of continuous excavation and filling mining method for breaking thick ore body, and relates to the technical field of mining engineering.The application determines rock mass grade through basic quality index of rock mass, matches single excavation cycle footage and top temporary support grade, and in the set monitoring window, the current cycle section is shot with geological radar wave and short-range low-frequency sound wave to the roof at equal time intervals, the high-frequency signal proportion and sound wave propagation speed are calculated, the surrounding rock deformation section data, the change degree of two indexes and the DTW distance of the reflected signals of the radar wave in the last two times are comprehensively analyzed at each monitoring time to determine whether it is abnormal;If there is no abnormality, the reflected signal of the radar wave is stored as a standard template according to the rock mass grade;When the number of standard templates is less than N, the data and the preset threshold are optimized to support the grade;When the number of templates is not less than N, the threshold is updated by grouping and counting the mean and standard deviation of the indexes at the monitoring time, and the top temporary support grade is optimized.

Description

Technical Field

[0001] This invention relates to the field of mining engineering technology, specifically to a continuous tunneling and backfilling mining method for fractured, thick ore bodies. Background Technology

[0002] Mining is the core link in mineral resource development. Among them, the mining of fractured and thick ore bodies has always been a key and difficult point in mining engineering due to complex geological conditions, poor surrounding rock stability, and loose ore body structure. It usually requires continuous tunneling and backfilling to achieve safe and efficient mining.

[0003] The conventional process of existing continuous tunneling and backfilling mining technology is as follows: First, the basic characteristics of the rock mass are determined through geological exploration, the rock mass is classified and the corresponding tunneling cycle footage and initial support scheme are matched; during the tunneling process, monitoring sections are set up to collect the deformation data of the surrounding rock surface, and the footage is adjusted or the support is strengthened accordingly; after the tunneling reaches the set length, backfilling operation is carried out in a timely manner to control further deformation of the surrounding rock, and then the next section of tunneling is carried out; this process has been widely used in many mining projects.

[0004] However, existing technologies still have the following prominent problems: most existing monitoring systems rely solely on surface deformation data of the surrounding rock as the core basis for judgment; temporary support procedures for conventional ore bodies are mostly formulated based on the condition of intact rock structure and stable stress environment; support parameters and layout methods emphasize universality and fail to fully consider the strong nonlinear deformation law and dynamic characteristics of rapid crack propagation exhibited by the surrounding rock at the top of fractured and thick ore bodies. In fact, the initiation and propagation of microcracks inside the rock mass, as well as the shear slip of bedding planes, are all gradual evolution processes, with minimal impact on surface deformation in the early stages; by the time surface deformation data shows significant fluctuations or anomalies, internal damage has often entered an irreversible stage, easily triggering sudden engineering geological disasters, leaving support measures in a passive response predicament. In addition, existing support schemes and adjustment thresholds are mostly based on initial geological survey results and engineering experience, which makes it difficult to reflect dynamic changes such as stress redistribution and rock mass integrity decline during tunneling in real time. Fixed support parameters and judgment thresholds cannot be adapted to the actual working conditions of different tunneling stages, which can easily lead to a mismatch between support strength and actual rock mass bearing capacity requirements, resulting in mining safety hazards due to insufficient support.

[0005] Therefore, there is an urgent need for a continuous tunneling and backfilling mining technology for fractured and thick ore bodies that can sense the internal state of the rock mass in advance and dynamically adapt to the support requirements, so as to improve the safety, adaptability and overall efficiency of mining such complex ore bodies.

[0006] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] The purpose of this invention is to provide a continuous tunneling and backfilling mining method for fractured and thick ore bodies to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] A continuous tunneling and backfilling mining method for fractured, thick ore bodies, comprising the following steps:

[0010] The rock mass grade is determined based on the basic quality indicators of the sidewall rock mass in the tunnel. The temporary support grade of the tunnel top is determined based on the rock mass grade. An equal-length monitoring window is set for each circulation section in the tunnel. The surrounding rock deformation cross-sectional data of the corresponding circulation section is obtained in each monitoring window.

[0011] Within the monitoring window, several monitoring times are set at equal time intervals. At each monitoring time, ground-penetrating radar waves and short-range low-frequency sound waves are emitted from the top plate of the corresponding loop segment and the echo signals are received. For each monitoring time, the ground-penetrating radar wave echo signal is subjected to Fourier transform to obtain the high-frequency signal ratio. The sound wave propagation speed is calculated based on the propagation time corresponding to the maximum amplitude energy peak of the short-range low-frequency sound wave. The high-frequency signal ratio and sound wave propagation speed at each monitoring time are used as the waveform detection data for that monitoring time.

[0012] The waveform detection data in each monitoring window is analyzed to obtain the time-domain variation data in that monitoring window. The time-domain variation data includes the proportion of high-frequency signals and the degree of change in sound wave propagation speed. Based on the time-domain variation data, the surrounding rock deformation section data, and the DTW distance of the ground radar echo signal between adjacent monitoring times, it is determined whether the cycle segment is abnormal. For cycle segments that are determined to be normal, they are classified according to rock mass grade, and their ground radar echo signals are stored as standard templates.

[0013] When the number of standard templates corresponding to the rock mass grade of the currently cyclic section is less than N, the DTW distance analysis of the time-domain variation data within the monitoring window and the ground radar echo signal between adjacent monitoring times is used to optimize the level of the top temporary support. When the number of standard templates corresponding to the rock mass grade of the currently cyclic section is not less than N, the DTW distance analysis of the time-domain variation data within the monitoring window, the ground radar echo signal and the standard template of the same rock mass grade is used to optimize the level of the top temporary support.

[0014] Furthermore, the method for determining the level of temporary support for the top of the tunnel based on the rock mass grade is as follows:

[0015] Obtain the uniaxial compressive strength and rock integrity coefficient of the rock mass to be determined. Construct a calculation formula for the basic quality index of the rock mass based on the uniaxial compressive strength and rock integrity coefficient. Based on the calculation results, classify the rock mass into grades 1-5 according to the basic quality classification table of the rock mass, and then assign the corresponding grade 1-5 top temporary support.

[0016] Furthermore, during each monitoring moment, ground-penetrating radar waves and short-range low-frequency acoustic waves are emitted from the roof of the corresponding cycle segment, and echo signals are received. The ground-penetrating radar waves have a center frequency in the range of 100–250MHz, a bandwidth of 100–250MHz, and a single pulse duration of 0.3–1.5μs. The short-range low-frequency acoustic waves have a main frequency band in the range of 1–8kHz and a wave packet length of 2–10ms.

[0017] Furthermore, the method for obtaining the proportion of high-frequency signals by performing Fourier transform on the ground-penetrating radar echo signals is as follows:

[0018] A 50Hz low-pass filter was used to filter the ground-penetrating radar echo signal. Preprocessing was performed using the moving average method. Then, a fast Fourier transform was used to convert the time-domain signal into a frequency-domain spectrum to obtain the frequency distribution and corresponding amplitude information of the signal. Using the center frequency of the selected ground-penetrating radar wave as a reference, the high-frequency band was defined as the interval of 1.2–2.0 times the center frequency. The total energy of the high-frequency band and the total energy of the entire frequency band were calculated. The total energy of the high-frequency band was obtained by integrating the square of the amplitude corresponding to each frequency point in the high-frequency band, and the total energy of the entire frequency band was obtained by integrating the square of the amplitude corresponding to each frequency point in the entire frequency band. Finally, the ratio of the total energy of the high-frequency band to the total energy of the entire frequency band was taken as the proportion of the high-frequency signal.

[0019] Furthermore, the method for calculating the sound wave propagation speed based on the propagation time corresponding to the maximum amplitude energy peak of short-range low-frequency sound waves is as follows:

[0020] The excitation source is fixed at the center of the roof, and two receiving sensors are linearly arranged along the upper part of both sides of the tunnel to obtain the distance from the excitation source to the two receiving sensors. After the sound wave is emitted, a 1kHz high-pass filter is used to filter the collected short-range low-frequency sound wave. In the pre-processed signal time-domain waveform, the maximum amplitude energy peak corresponding to the reflected wave is located, that is, the signal peak point with the largest absolute amplitude is locked. Taking the excitation source triggering time as the time starting point, the time coordinate corresponding to the signal peak point is the propagation time of the sound wave from the excitation source to the corresponding receiving sensor. Based on the corresponding arrival time, the propagation time is determined. The ratio of the distance from the excitation source to the receiving sensor to the corresponding arrival time is taken as the propagation speed of a single sound wave. The arithmetic mean of the propagation speeds of two single sound waves is taken as the propagation speed of the sound wave.

[0021] Furthermore, the method for determining whether the cycle segment is abnormal based on time-domain variation data, surrounding rock deformation cross-sectional data, and the DTW distance of the ground radar echo signal between adjacent monitoring times is as follows:

[0022] exist At monitoring times at equal time intervals, the data on surrounding rock deformation cross-sections, the degree of change in the proportion of high-frequency signals, the degree of change in acoustic wave propagation velocity, and the DTW distance of the ground-penetrating radar echo signals between two consecutive monitoring sessions were analyzed. For positive integers greater than 3, the specific process is as follows:

[0023] The analysis of surrounding rock deformation cross-sectional data shows that the difference between the currently monitored surrounding rock deformation cross-sectional data and the data from the first monitoring of surrounding rock deformation cross-sectional data is used as the ratio of the difference to the data from the first monitoring of surrounding rock deformation cross-sectional data as the relative change rate of the surrounding rock deformation cross-section.

[0024] The analysis of the proportion of high-frequency signals and the speed of sound propagation is based on the initial proportion of high-frequency signals and the initial speed of sound propagation. The ratio of the difference between the current proportion of high-frequency signals and the initial proportion of high-frequency signals to the initial proportion of high-frequency signals is used as the degree of change of the proportion of high-frequency signals, and the ratio of the difference between the current speed of sound propagation and the initial speed of sound propagation to the initial speed of sound propagation is used as the degree of change of the speed of sound propagation.

[0025] For DTW distance analysis of preprocessed ground-penetrating radar echo signals from two consecutive monitoring sessions, the Min-Max normalization method was used to process the two signals, converting them into one-dimensional data sequences. A distance matrix was constructed based on the one-dimensional data sequences. The value at each position in the matrix represents the Euclidean distance between the corresponding data point in the one-dimensional data sequence of the first signal and all data points in the one-dimensional data sequence of the second signal after normalization, i.e., the square root of the square of the difference between the two data points. Then, the optimal matching path was found, starting from the upper left corner of the distance matrix and ending at the lower right corner. The path with the smallest cumulative distance was the optimal matching path. The path movement rules were limited to three types: rightward, downward, and diagonal. Finally, the cumulative distance was obtained by summing all matrix elements on the optimal matching path and dividing it by the sequence length to obtain the DTW distance between the two signals. During the process, the constraint window was set to 10% of the sequence length, which means that the optimal matching path could only move within a range of 10% of the sequence length on both sides of the main diagonal.

[0026] First thresholds for the proportion of high-frequency signals, the velocity of sound waves, and the distance of ground-penetrating radar waves were set. Specifically, for the first threshold for the proportion of high-frequency signals, the threshold was set at 15% to 20% for rock masses of grades 1 to 2, and at 10% to 15% for rock masses of grades 3 to 5. For the first threshold for the velocity of sound waves, the threshold was uniformly set at 10% to 15%. For the first threshold for the distance of ground-penetrating radar waves, the threshold was set at 15% to 25% for rock masses of grades 1 to 2, at 20% to 30% for grade 3, and at 25% to 35% for rock masses of grades 4 to 5.

[0027] At each monitoring time, if the monitoring data of the looped segment meets any of the following conditions, the looped segment is deemed to have an anomaly:

[0028] Among the relative change rates of the deformation cross section of the surrounding rock, any one of the following reaches the warning threshold for the corresponding rock mass grade: roof subsidence, horizontal displacement of the two sides, and cross section convergence value; the degree of change in the proportion of high-frequency signals reaches the first change threshold for the proportion of high-frequency signals; the degree of change in the propagation speed of sound waves reaches the first change threshold for the speed of sound waves; and the DTW distance of the ground radar echo signals from two consecutive monitoring sessions reaches the first threshold for the distance of ground radar waves.

[0029] Furthermore, based on the DTW distance analysis of the temporal variation data within the monitoring window and the ground radar echo signals between adjacent monitoring times, the method for optimizing the level of the top temporary support is as follows:

[0030] Based on the set first threshold for the proportion of high-frequency signals, the first threshold for the change of sound wave velocity, and the first threshold for the distance of ground-penetrating radar waves, if the data monitored in the cyclic section meets any one of the following conditions, the current temporary support level at the top will be upgraded by one level; if the current level is already level 5, an alarm will be triggered directly. The conditions are:

[0031] When the change in the proportion of high-frequency signals reaches the first threshold for change in the proportion of high-frequency signals; when the change in the speed of sound propagation reaches the first threshold for change in the speed of sound; when the distance between the ground-penetrating radar echo signals from two consecutive monitoring sessions reaches the first threshold for distance between ground-penetrating radar waves.

[0032] Furthermore, based on the temporal variation data within the monitoring window, the ground-penetrating radar echo signal, and the DTW distance analysis of the standard template of the same rock mass grade, the method for optimizing the grade of the top temporary support is as follows:

[0033] When the number of standard templates corresponding to the rock mass grade of the currently cyclic segment is not less than N, the threshold update is triggered, and statistics are performed in groups according to the monitoring time. The specific steps are as follows:

[0034] Based on the monitoring time, all standard templates under the same rock mass grade are grouped according to the monitoring time, that is, each group corresponds to one monitoring time;

[0035] For all standard templates within each group, calculate the DTW distance between any two standard templates using ground-penetrating radar echo signals individually.

[0036] Extract the degree of change in the proportion of high-frequency signals, the degree of change in the propagation speed of sound waves, and the DTW distance of the ground radar echo signals in any two standard templates for each group at the corresponding monitoring time. Then, calculate the mean and standard deviation of the degree of change in the proportion of high-frequency signals, the degree of change in the propagation speed of sound waves, and the DTW distance of the ground radar echo signals.

[0037] All three indicators are based on the statistical mean within the corresponding group, and are expanded to both sides by 2-3 times the standard deviation to obtain new thresholds for the proportion of high-frequency signals, the speed of sound propagation, and the distance of ground-penetrating radar waves, and are continuously iterated and updated.

[0038] If the data from the currently monitored section meets any of the following conditions, the current temporary support level at the top will be upgraded by one level; if the current level is already level 5, an alarm will be triggered directly. The conditions are:

[0039] Based on the set new thresholds for the proportion of high-frequency signals, the speed of sound, and the distance of ground-penetrating radar waves, the following conditions are met: when the change in the proportion of high-frequency signals reaches the new threshold for the proportion of high-frequency signals; when the change in the speed of sound propagation reaches the new threshold for the speed of sound; and when the DTW distance between the currently monitored ground-penetrating radar wave echo signal and the ground-penetrating radar wave echo signal of any standard template in the corresponding group exceeds the new threshold for the distance of ground-penetrating radar waves in the corresponding group.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] This invention uses comprehensive monitoring of surrounding rock deformation cross-sectional data, combined with time-domain variation data and the distance between two consecutive monitoring ground radar echo signals (DTW), to determine anomalies in the cyclic section, instead of relying solely on surface deformation data, and to predict in advance whether to optimize the level of top temporary support.

[0042] This invention also constructs standard templates by classifying and storing ground radar echo signals of non-abnormal cycle segments according to rock mass grade and equal time intervals. In the early stages of the project when the number of standard templates is less than N, the invention compares the time-domain variation data and the DTW distance of the ground radar echo signals at adjacent monitoring times with preset thresholds to determine in advance whether to optimize the level of the top temporary support. In the middle and later stages of the project when the number of standard templates is not less than N, the invention statistically analyzes the time-domain variation data and calculates the DTW distance of the ground radar echo signals in any two standard templates at the monitoring times corresponding to the standard templates. Based on the mean and standard deviation of the three indicators, the invention iteratively updates the thresholds of the three indicators to determine in advance whether to optimize the level of the top temporary support, so that the support level is optimized to fit the actual rock mass condition at different tunneling stages. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of the overall method flow of the present invention;

[0044] Figure 2 This is a trend chart showing the optimization of the advance in a single tunneling cycle according to the present invention.

[0045] Figure 3 This is a diagram showing the degree of change in wave velocity and high-frequency signal in this invention;

[0046] Figure 4 This is a schematic diagram of the continuous radar signal monitoring (DTW) of the present invention;

[0047] Figure 5 This is a distribution map of the threshold update in this invention. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0049] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0050] Example:

[0051] Please see Figures 1 to 5 The present invention provides a technical solution:

[0052] A continuous tunneling and backfilling mining method for fractured, thick ore bodies, comprising the following steps:

[0053] S1: Determine the rock mass grade based on the basic quality indicators of the sidewall rock mass in the tunnel, determine the temporary support grade of the tunnel top based on the rock mass grade, set an equal-length monitoring window for each cycle section in the tunnel, and obtain the surrounding rock deformation cross-sectional data of the corresponding cycle section in each monitoring window.

[0054] In the planned continuous tunneling route, the single tunneling cycle advance should be set according to the principle of matching rock mass stability with tunneling advance. The rock mass grade is classified by the basic rock mass quality index, and the specific classification process is as follows:

[0055] The tunneling route was divided into multiple rock mass grading units based on lithology. Standard rock samples were obtained for each unit, and their uniaxial compressive strength under saturated conditions was tested using a pressure testing machine to obtain the uniaxial compressive strength. Intact, undamaged rock cores from the middle section were selected as fresh rock samples, and their P-wave velocities were tested and calibrated as fresh rock P-wave velocities. The P-wave velocities of the corresponding standard rock samples were tested in each grading unit. Based on the fresh rock P-wave velocities and the tested rock P-wave velocities, a formula for calculating the rock mass integrity coefficient was constructed.

[0056]

[0057] In the formula, Indicates the rock mass integrity coefficient. Indicates the longitudinal wave velocity of the rock mass in the graded unit. Indicates the longitudinal wave velocity of fresh rock;

[0058] After obtaining the rock mass integrity coefficient, a formula for calculating the basic quality indicators of the rock mass is constructed based on the uniaxial compressive strength of the rock and the rock mass integrity coefficient:

[0059]

[0060] In the formula, Indicates the basic quality indicators of the rock mass. The table shows the data and results for 40 sets of basic rock mass quality indicators, representing uniaxial compressive strength. The rock mass integrity coefficient is generally between 0.5 and 0.9, and the integrity of most rock masses is at a medium to good level. However, the uniaxial compressive strength varies greatly. The rock mass grade can be obtained based on the final calculated basic rock mass quality indicators.

[0061] Table 1: Summary Table of Basic Quality Indicators of Rock Mass

[0062]

[0063] After obtaining the basic quality indicators of the rock mass, it was classified into five levels according to the basic quality grading table. Level 1 is extremely stable rock mass with strong resistance to deformation and long self-stabilization time, allowing for larger advances. Level 5 is extremely fractured rock mass with extremely short self-stabilization time, requiring shorter advances to reduce the exposure time of the surrounding rock and lower the risk of collapse. Based on reference to domestic mining cases of similar fractured and thick ore bodies, the conventional safe advance range for levels 1-5 is 0.8-4.5 meters. The values ​​selected in this scheme are in the middle of the range corresponding to levels 1-5, balancing safety and mining efficiency. That is, according to the rock mass classification of levels 1-5, the single excavation cycle advance is set to 4 meters, 3.5 meters, 2.5 meters, 1.5 meters, and 1 meter, respectively. The shorter advance can ensure that the support can seal the surrounding rock in time. For example, after 1 meter of advance in level 5 fractured rock mass, the pre-reinforcement and temporary invert arch construction can be completed quickly, avoiding weathering and softening caused by prolonged exposure of the surrounding rock.

[0064] After tunnel excavation, the overhead rock mass loses its original stress balance and is subjected to the combined effects of gravity and overlying strata pressure, making it the area with the highest risk of collapse. For the temporary support level, corresponding levels are set for each of the 1-5 rock mass classifications. Level 1 temporary support includes local point anchoring and thin-layer shotcrete; Level 2 includes system anchor bolts and steel mesh shotcrete; Level 3 includes denser anchor bolts, lattice steel frames, and shotcrete; Level 4 includes a combination of anchor cables and anchor bolts, I-beam arches, and pre-support; Level 5 includes pre-reinforcement, strong support structures, and temporary invert arches. This is because Level 1 rock mass has extremely strong self-stabilizing ability, requiring only local anchoring to control joint expansion and thin-layer shotcrete to prevent surface weathering, without excessive support. Level 2 rock mass has some bedding, and system anchoring... The rods and steel mesh form an integral load-bearing structure. Shotcrete fills surface cracks and improves the overall integrity of the surrounding rock. For Class 3 rock mass with well-developed cracks, denser anchor rods are used to enhance anchoring force. The grid steel frame provides rigid support, and the shotcrete and steel frame work together to bear the load. For Class 4 rock mass with fractures and easy slippage, anchor cables provide deep anchoring force. I-beam arches bear the main load. Advance support reinforces the unexcavated surrounding rock in advance and blocks the transmission of fracture zones. For Class 5 rock mass with extremely fractures and short self-stabilization time, advance pre-reinforcement provides a protective shell. I-beam arches provide strong rigid support. Temporary inverted arches prevent the top plate from becoming unstable due to bottom bulging. Circular support balances stress in all directions. For example, for Class 1 temporary top support, local point anchors use 22mm diameter threaded steel anchor rods, 2.0m long, spaced 2.0m×2.0m, arranged at the locations of local joints in the top plate. Thin-layer shotcrete is set with a strength grade of C20 and a thickness of 50mm and is arranged on the sealed rock mass surface.

[0065] The surrounding rock deformation cross-sectional data are set as the roof settlement, the horizontal displacement of the two sides, and the cross-sectional convergence value. Three monitoring sections are set behind the working face of each cycle section. For example, the entire process of surrounding rock deformation can be captured at 5m, 10m, and 15m after the tunneling is completed.

[0066] Set a monitoring window of equal length. The duration of this monitoring window should be less than the time from the start of collecting data on the deformation section of the surrounding rock to the cementation and filling of the cycle section. Within each monitoring window, the roof subsidence, the horizontal displacement of the two sides, and the cross-sectional convergence value are collected simultaneously for each cross-section. These three are the core indicator combination for monitoring the surrounding rock of the mine. The roof subsidence directly reflects the stability of the top under the action of vertical ground pressure and is a direct manifestation of the risk of roof collapse. The horizontal displacement of the two sides reflects the rock mass slippage caused by the release of lateral stress, which can easily lead to the collapse of the rock mass. The cross-sectional convergence value, by measuring the change in the cross-sectional diameter, comprehensively reflects the overall deformation of the vertical and lateral aspects, avoiding the omission of risks by a single indicator.

[0067] Each surrounding rock deformation section should be continuously monitored at least three times to eliminate random errors, and the average value should be used as the basis for judgment. Based on industry standards, rock mechanics principles, and field practice data, differentiated warning thresholds, over-limit thresholds, and allowable cumulative deformation values ​​should be set for rock mass grades 1-5, with the warning threshold being less than the over-limit threshold and less than the allowable cumulative deformation value. The threshold setting needs to be designed and adjusted according to specific working conditions. For example, domestic mining cases of fractured, thick ore bodies with similar rock mass grades, ore body thickness, and support methods can be collected, and their mature threshold settings can be referenced. For instance, the warning threshold for roof subsidence in grade 3 iron ore can be set at 8 mm / d. If none of the three deformation data reach the threshold... For each rock mass grade corresponding to the warning threshold, the next advance should maintain the initial advance for that grade. If any one of the three deformation data points reaches the warning threshold but does not exceed the limit, it indicates slight deformation of the surrounding rock, and the next advance should be reduced to 70% of the initial advance. If any one of the three deformation data points reaches or exceeds the limit threshold, or if two or more reach the warning threshold, the surrounding rock deformation intensifies, increasing the risk. Excavation should be immediately suspended, and the next advance should be reduced to 50% of the initial advance. If any one of the three deformation data points reaches the allowable cumulative deformation value, to avoid continued deformation leading to instability, the next advance should be directly reduced to 60% of the initial advance. Figure 2 The figure shows the results of classifying the rock mass into 1-5 levels based on the basic rock mass quality indicators, and then optimizing the footage based on the set single tunneling cycle footage and the footage based on the above rules.

[0068] S2: Set several monitoring times at equal time intervals within the monitoring window. At each monitoring time, emit ground-penetrating radar waves and short-range low-frequency sound waves on the top plate of the corresponding loop segment and receive echo signals. For each monitoring time, perform Fourier transform on the ground-penetrating radar wave echo signal to obtain the proportion of high-frequency signals. Calculate the sound wave propagation speed based on the propagation time corresponding to the maximum amplitude energy peak of the short-range low-frequency sound wave. Use the proportion of high-frequency signals and the sound wave propagation speed at each monitoring time as the waveform detection data for that monitoring time.

[0069] Ground-penetrating radar waves are a type of high-frequency pulsed electromagnetic wave. Their propagation characteristics are strongly correlated with the difference in dielectric constant of the medium inside the rock mass. In fractured and thick ore bodies, the dielectric constants of intact rock blocks, micro-fractures, cavities, and air gaps differ significantly. This difference causes electromagnetic waves to be strongly reflected at the interface. The expansion of micro-fractures changes the frequency components and amplitude of the reflected signal. Ground-penetrating radar waves have strong anti-interference capabilities, high detection accuracy, and low penetration attenuation. When the density of fractures inside the rock mass increases, the amplitude of radar wave reflection will increase, and the proportion of high-frequency components will increase significantly.

[0070] The essence of short-range low-frequency sound waves is elastic longitudinal waves. The sound wave velocity is positively correlated with the elastic modulus, density, and integrity of the rock mass. When the micro-cracks inside the rock mass expand, the sound wave velocity decreases significantly. This is the core principle of its ability to quantify the mechanical state of the rock mass, and it can penetrate the surface rock mass.

[0071] Therefore, for the currently circulating section, ground-penetrating radar waves and short-range low-frequency acoustic waves are emitted from the roof at equal time intervals within a pre-set monitoring window. The ground-penetrating radar waves have a center frequency in the range of 100–250 MHz, a detection depth of 1–5 m, covering a critical support area of ​​approximately 3 m on the roof, and a bandwidth of 100–250 MHz. This allows the radar to capture micro-fractures commonly found in fractured, thick ore bodies, where the DTW distance between two consecutive ground-penetrating radar echoes reaches the first threshold of 2–5 mm. The single pulse duration is 0.3–1.5 μs; the 1.5 μs long pulse carries higher energy and attenuates more slowly in the rock mass, allowing for a detection depth of up to 5 m, penetrating shallow fractures. This method uses a fragmentation band to detect the development of fractures in deep, stable rock strata, preventing roof instability caused by undetected deep fracture propagation. While the 0.3μs short pulse has weak energy, it can detect to a depth of approximately 1m, making it suitable for shallow monitoring of Class 5 extremely fractured rock masses. The short-range, low-frequency acoustic wave, with a main frequency band in the 1–8kHz range, attenuates slowly in fractured rock masses, making it suitable for short-range propagation of the ground radar echo signal (DTW) from two consecutive monitoring sessions within a tunnel, reaching the first threshold distance for ground radar waves (3–10m). It effectively penetrates loose surrounding rock, avoiding insufficient signal resolution due to reflection and absorption from rock fractures and air gaps. With a wave packet length of 2–10ms, it improves the signal-to-noise ratio, ensuring accurate identification of reflected wave peaks.

[0072] A 50Hz low-pass filter is used to filter the ground radar echo signal to filter out power frequency interference in the tunnel, such as 50Hz electromagnetic noise from construction machinery, while retaining the effective radar signal. Then, the preprocessing is completed by the moving average method. For example, the mean of 5 consecutive data points is taken to replace the original data points, which can smooth out the reflection interference caused by uneven rock surface in the signal.

[0073] The time-domain signal was then converted into a frequency-domain spectrum using a Fast Fourier Transform (FFT) to obtain the frequency distribution and corresponding amplitude information of the signal, clarifying the energy proportion of each frequency component. The reflection of radar waves from intact rock masses is mainly low-frequency, while the reflection from micro-fractures and fractured interfaces generates high-frequency scattered waves. Therefore, based on engineering experience to fully cover high-frequency signals from fractures of different scales, the high-frequency band was defined as 1.2–2.0 times the center frequency, using the center frequency of the currently selected ground-penetrating radar wave as a benchmark. The total energy of the high-frequency band and the total energy of the entire frequency band were calculated. The total energy of the high-frequency band was obtained by integrating the square of the amplitude corresponding to each frequency point within the high-frequency band, and the total energy of the entire frequency band was obtained by integrating the square of the amplitude corresponding to each frequency point within the entire frequency band. Finally, the ratio of the total energy of the high-frequency band to the total energy of the entire frequency band was taken as the proportion of the high-frequency signal.

[0074] The excitation source is fixed at the center of the roof, and two receiving sensors are linearly arranged along the upper part of both sides of the roadway to obtain the distance from the excitation source to the two receiving sensors. A single sensor is easily affected by local rock mass inhomogeneity. The two sensors are symmetrically arranged, and the average value can be taken to offset the random error of local defects. After the sound wave is emitted, a 1kHz high-pass filter is used to filter the collected short-range low-frequency sound waves. Mechanical vibration noise, including the operating vibration of equipment such as tunneling machines, anchor bolting machines, and loaders, has a frequency of mostly 50-500Hz and is easily superimposed on the sound wave signal. Only signals above 1kHz are allowed to pass through, avoiding confusion between noise and target sound waves with frequencies of 1-8kHz from the source, thereby accurately locating the propagation time of the maximum amplitude energy peak of the reflected wave. When the sound wave propagates in the rock mass, it will generate direct waves, reflected waves, and scattered waves. Among them, the direct wave has the largest energy and corresponds to the maximum amplitude peak in the time domain waveform. To avoid time misjudgment caused by reflected waves and scattered waves, and to ensure the accuracy of velocity measurement, the time domain waveform of the preprocessed signal is filtered. In the process, the maximum amplitude energy peak corresponding to the reflected wave is located, that is, the signal peak point with the largest absolute amplitude is locked. Taking the excitation source triggering time as the time starting point, the time coordinate corresponding to the signal peak point is the propagation time of the sound wave from the excitation source to the corresponding receiving sensor. Based on the corresponding arrival time, the propagation time is determined. The ratio of the distance from the excitation source to the receiving sensor to the corresponding arrival time is taken as the single sound wave propagation speed. The arithmetic mean of the two single sound wave propagation speeds is taken as the sound wave propagation speed. The high frequency signal ratio and sound wave propagation speed at each monitoring moment are taken as the waveform detection data at that monitoring moment. The high frequency signal ratio and sound wave propagation speed calculated for the first time are defined as the initial high frequency signal ratio and initial sound wave propagation speed, thereby establishing the baseline of the initial stable state of the rock mass. After the excavation of the broken thick ore body is completed, although the rock mass is disturbed by the excavation during the first monitoring, no significant deformation or crack expansion occurs. At this time, the signal indicators can represent the initial stable state of the cycle section.

[0075] S3: Analyze the waveform detection data in each monitoring window to obtain the time-domain change data in that monitoring window. The time-domain change data includes the proportion of high-frequency signals and the degree of change in sound wave propagation speed. Based on the time-domain change data, the surrounding rock deformation cross-section data, and the DTW distance of the geological radar echo signal between adjacent monitoring times, determine whether the cycle segment is abnormal. For cycle segments that are determined to be normal, classify them according to rock mass grade and store their geological radar echo signals as standard templates.

[0076] exist At each monitoring time point within equal time intervals, the analysis included data on surrounding rock deformation cross-sections, changes in the proportion of high-frequency signals, changes in acoustic wave propagation velocity, and DTW distance analysis of the ground-penetrating radar echo signals between consecutive monitoring intervals. For each time interval, the interval is a positive integer greater than 3, ranging from 1 to 24 hours (e.g., 4 hours). The deformation of a fractured, thick ore body after excavation exhibits a trend of rapid change followed by slow stabilization. Multiple time intervals are used to avoid missing data from the stable phase. For example, for… The value is set to 6, taking into account the time period from rapid change to slow stabilization. The specific process of analyzing the DTW distance of the surrounding rock deformation cross-section data, the degree of change in the proportion of high-frequency signals, the degree of change in the sound wave propagation speed, and the ground radar echo signals between two consecutive monitoring intervals is as follows:

[0077] Analysis of surrounding rock deformation cross-sectional data: The difference between the currently monitored surrounding rock deformation cross-sectional data and the first monitored surrounding rock deformation cross-sectional data, and the ratio of the difference to the first monitored surrounding rock deformation cross-sectional data, is used as the relative change rate of the surrounding rock deformation cross-section. The core purpose of support is to constrain surrounding rock deformation, so this relative change rate can intuitively reflect whether the current support matches the deformation trend.

[0078] The analysis of high-frequency signal proportion and sound wave propagation speed uses the initial high-frequency signal proportion and initial sound wave propagation speed as benchmarks. The ratio of the difference between the current high-frequency signal proportion and the initial high-frequency signal proportion to the initial high-frequency signal proportion is used as the degree of change in the high-frequency signal proportion, and the ratio of the difference between the current sound wave propagation speed and the initial sound wave propagation speed to the initial sound wave propagation speed is used as the degree of change in the sound wave propagation speed. The deformation of different initial states is uniformly quantified as a percentage, thereby providing timely early warning.

[0079] The core advantage of Dynamic Time Warping (DTW) is its ability to measure the similarity of non-rigid signals. Consecutive comparisons can focus on short-term differences in ground-penetrating radar (GPR) signals, such as rapid expansion of microfractures or sudden slippage in localized fracture zones, which cause signal abrupt changes. This is synchronized with the dynamic evolution of defects within the rock mass. Consecutive comparisons reflect the real-time trend of defect changes, rather than just cumulative changes, providing more timely evidence for anomaly detection. In the DTW distance analysis of pre-processed GPR echo signals from each consecutive pair of monitoring sessions, the Min-Max normalization method is used to process the GPR echo signals from the two monitoring sessions, eliminating interference factors in signal amplitude and ensuring consistent signal quality. The morphological differences between the two monitored signals become the core of distance calculation. Both signals are converted into one-dimensional data sequences of equal length. A distance matrix is ​​constructed based on these one-dimensional data sequences. The value at each position in the matrix represents the Euclidean distance between the corresponding data point in the standardized one-dimensional data sequence of the first signal and all data points in the standardized one-dimensional data sequence of the second signal. This distance is the square root of the square of the difference between the two data points, indicating the similarity between any sampling point in the first signal and any sampling point in the second signal; the smaller the value, the more similar the two signals. Then, the optimal matching path is found, starting from the top left corner of the distance matrix. The optimal matching path is the one with the smallest cumulative distance, starting from the bottom right corner and ending at the bottom right corner. The path movement rules are limited to three types: right, down, and diagonal. Specifically, a cumulative distance matrix with the same dimensions as the distance matrix is ​​created, starting from the top left corner and allowing only right and down movement. Starting from the second row and second column, movement is restricted to right, down, and diagonal. The minimum cumulative distance at the current position is calculated, which is equal to the current distance plus the cumulative distance of the previous optimal path. Finally, the cumulative distance is summed across all matrix elements on the optimal matching path, and then divided by the sequence length to obtain the total cumulative distance. The DTW distance of the signal; during the process, the constraint window is set to 10% of the sequence length, that is, the optimal matching path can only move within the range of 10% of the sequence length on both sides of the main diagonal. The radar wave signals monitored twice are the acquisition results of the same location but different times. The time dimension of the signal is synchronous. The significance of 10% is to allow a small time offset to avoid invalid matching results. Table 2 shows that the number of standard templates corresponding to the rock mass grade of the 24 previous cycled sections is less than the sum of data obtained based on the characteristics of geological radar waves and short-range low-frequency sound waves, so as to make a comprehensive judgment on whether the top temporary support grade needs to be optimized in the future.

[0080] Table 2: Correlation Parameters of Wave Velocity and High-Frequency Signals

[0081]

[0082] Set a first threshold for the proportion of high-frequency signals, a first threshold for the velocity of sound waves, and a first threshold for the distance of ground-penetrating radar waves, respectively.

[0083] For the first change threshold of the proportion of high-frequency signals, it is set to 15% to 20% for rock masses of grades 1 to 2 and 10% to 15% for rock masses of grades 3 to 5. Broken rock masses are more sensitive to fissures and have a lower threshold. When the proportion of high-frequency signals increases relative to the initial value by more than this threshold, it indicates that micro-fissures are expanding rapidly.

[0084] The threshold for the first change in sound wave velocity is uniformly set to 10% to 15%. Engineering experience shows that when the sound wave velocity decreases by 10%, the corresponding elastic modulus decreases by about 8%, which is close to the support bearing limit and requires early warning.

[0085] For the first threshold of distance for ground-penetrating radar waves, the threshold is set to 15% to 25% for rock masses of grades 1 to 2, 20% to 30% for grade 3, and 25% to 35% for grade 4 to 5. Grade 1 to 2 rock masses have good integrity and small signal differences, so the threshold is lower to avoid missed detection. Grade 3 rock masses are moderately stable mineralized rock masses with a small number of fissures, so the threshold should be appropriately increased. Grade 4 to 5 rock masses are between relatively broken and extremely broken, with well-developed fissures and large normal signal differences, so the threshold should be appropriately increased.

[0086] The deformation cross-sectional data of the surrounding rock reflects the risk of macroscopic surface deformation; the degree of change in the proportion of high-frequency signals reflects the risk of internal microcrack propagation; the degree of change in acoustic velocity reflects the risk of a decline in overall mechanical integrity; the distance between two consecutive DTW measurements reflects the risk of short-term signal mutations; the instability of fractured and thick ore bodies may be triggered by any single dimension of risk, requiring timely early warning and optimized support. Therefore, at each monitoring moment, if the monitoring data of the cyclic section meets any of the following conditions, it is comprehensively determined that there is an anomaly in that cyclic section:

[0087] In the relative change rate of the surrounding rock deformation cross-section, any one of the following—roof subsidence, sidewall horizontal displacement, or cross-sectional convergence value—reaches the warning threshold for the corresponding rock mass grade; the degree of change in the proportion of high-frequency signals reaches the first threshold for the proportion of high-frequency signals; the degree of change in the sound wave propagation velocity reaches the first threshold for the sound wave velocity; the DTW distance of two consecutive monitoring ground radar echo signals reaches the first threshold for ground radar distance, such as... Figures 3-4 As shown, only the degree of change in the proportion of high-frequency signals, the degree of change in the propagation speed of sound waves, and the DTW distance analysis of the ground radar echo signals from two consecutive monitoring sessions are considered. When the first threshold for the change in the proportion of high-frequency signals is 15%, the first threshold for the change in the propagation speed of sound waves is 5%, and the first threshold for the distance of ground radar waves is 0.4, it is intuitive to judge whether there is an anomaly in the cycle segment. For example, the cycle segments corresponding to the rock mass grade with fewer than 4, 9, 10, 11, 14, 21, and 22 are abnormal.

[0088] For loop segments that are determined to be without anomalies, the one-dimensional data sequence of the geological radar wave corresponding to the time interval of the loop segment is extracted and stored by matching the corresponding rock mass grade and time interval number label to form a standard template.

[0089] S4: When the number of standard templates corresponding to the rock mass grade of the current cycled section is less than N, perform DTW distance analysis on the time-domain variation data within the monitoring window and the ground radar echo signal between adjacent monitoring times to optimize the level of top temporary support. When the number of standard templates corresponding to the rock mass grade of the current cycled section is not less than N, perform DTW distance analysis on the time-domain variation data within the monitoring window, the ground radar echo signal and the standard template of the same rock mass grade to optimize the level of top temporary support.

[0090] In the initial stage of mining, when the number of standard templates for the rock mass grade corresponding to the currently circulated section is less than N, the number of standard templates for the first mining of this type of rock mass grade is insufficient. A reliable set of judgment criteria needs to be preset to quickly adapt to the initial working conditions and avoid risk loss of control due to waiting for the accumulation of standard templates. At each monitoring moment within the monitoring window, based on the set first change threshold of high-frequency signal proportion, first change threshold of acoustic velocity, and first threshold of ground radar wave distance, if the data monitored in the circulated section meets any of the following conditions, the current top temporary support level is upgraded by one level. When the current level is level 5, it is the preset highest support level, and there is no higher level to upgrade to; an alarm is issued directly. The conditions are:

[0091] When the change in the proportion of high-frequency signals reaches the first threshold for change in the proportion of high-frequency signals; when the change in the speed of sound propagation reaches the first threshold for change in the speed of sound; when the distance between the ground-penetrating radar echo signals from two consecutive monitoring sessions reaches the first threshold for distance between ground-penetrating radar waves.

[0092] When the number of standard templates corresponding to the rock mass grade in the current cyclic section is not less than N, enough data of the same rock mass grade and without abnormal conditions has been accumulated, triggering a threshold update. This allows actual data to replace empirical presets. The normal fluctuation range of indicators such as the proportion of high-frequency signals and acoustic velocity varies at different monitoring times. The rock mass tends to stabilize in about 24 hours. Therefore, statistics are performed in groups according to the monitoring time, so that each set threshold is adapted to the rock mass condition at different tunneling stages. The specific steps are as follows:

[0093] Based on the monitoring time, all standard templates under the same rock mass grade are grouped according to the monitoring time, that is, each group corresponds to one monitoring time;

[0094] For all standard templates in each group, the DTW distance of the ground radar echo signal between any two standard templates is calculated separately. Table 3 shows the DTW distance of the ground radar echo signal between any two standard templates among the 10 standard templates. The smaller the distance, the closer the radar wave reflection characteristics of the two groups of standard templates are, and the more similar the geological conditions are. This is one of the criteria for judging whether to optimize the level of the top temporary support.

[0095] Table 3: Standard Template DTW Distance Data Table

[0096]

[0097] The core purpose of support is to suppress damage accumulation and prevent the condition from deteriorating. The degree of change based on the initial value can intuitively reflect whether the current damage exceeds the normal range. Extract the degree of change of high frequency signal proportion, the degree of change of sound wave propagation speed, and the DTW distance of ground radar echo signal in any two standard templates at each corresponding monitoring time. And respectively calculate the mean and standard deviation of the degree of change of high frequency signal proportion, the degree of change of sound wave propagation speed, and the DTW distance of ground radar echo signal.

[0098] All three indicators are based on the statistical mean within their respective groups, with the range expanded to both sides by 2-3 standard deviations. This is a high-confidence interval designed by the Institute of Statistics, ensuring that the range is neither too narrow, leading to frequent misjudgments, nor too wide, leading to missed judgments. New thresholds are obtained for the proportion of high-frequency signals, the speed of sound propagation, and the distance of ground-penetrating radar waves. Each time a new standard template of the same rock mass grade and without anomalies is added, an iterative update is automatically triggered. This involves assigning the new template to the corresponding group according to time intervals, recalculating the mean and standard deviation of the three indicators within each group, and expanding the range to both sides by 2-3 standard deviations based on the statistical mean, replacing the original thresholds, gradually bringing the values ​​closer to the true normal state of the current rock mass. Figure 5 As shown, based on the statistical mean of each set of indicators, intervals are constructed by expanding to both sides by 2 standard deviations to obtain new thresholds for ground radar wave distance, sound wave velocity, and high-frequency signal proportion. This intuitively presents the normal fluctuation range of each indicator. As the new standard template is iteratively updated, these intervals will continue to converge to the true state of the rock mass.

[0099] If the data from the currently monitored section meets any of the following conditions, the current temporary support level at the top will be upgraded by one level; if the current level is already level 5, an alarm will be triggered directly. The conditions are:

[0100] Based on the established new thresholds for high-frequency signal proportion, sound wave velocity, and ground-penetrating radar (GPR) distance, the following conditions are met: when the change in high-frequency signal proportion reaches the new threshold; the change in sound wave propagation velocity reaches the new threshold; and the DTW distance between the currently monitored GPR echo signal and the GPR echo signal of any standard template within the corresponding group exceeds the new threshold for the corresponding group's GPR distance; the reason for considering that the top temporary support level needs to be optimized when the DTW distance between the current signal and any standard template exceeds the threshold is that different abnormal cycle sections... Due to subtle differences in the local rock mass, the geological radar wave signal exhibits diverse morphologies. The DTW distance is calculated based on a standard template under normal conditions to make the judgment results more reliable. After the temporary support is stabilized, the ore is extracted in a corresponding manner according to the loose characteristics of the broken and thick ore body, such as mechanical shoveling. The ore is then transported out of the roadway. Afterward, the corresponding mined-out area is cemented and filled to constrain further deformation of the surrounding rock. The process is repeated along the continuous tunneling route to the next section, and all the above processes are repeated until the ore body area covered by the entire tunneling route is mined.

[0101] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0102] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0103] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0104] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for continuous tunneling and backfilling mining of fractured, thick ore bodies, characterized in that, The specific steps include: The rock mass grade is determined based on the basic quality indicators of the sidewall rock mass in the tunnel. The temporary support grade of the tunnel top is determined based on the rock mass grade. An equal-length monitoring window is set for each circulation section in the tunnel. The surrounding rock deformation cross-sectional data of the corresponding circulation section is obtained in each monitoring window. Within the monitoring window, several monitoring times are set at equal time intervals. At each monitoring time, ground-penetrating radar waves and short-range low-frequency sound waves are emitted from the top plate of the corresponding loop segment and the echo signals are received. For each monitoring time, the ground-penetrating radar wave echo signal is subjected to Fourier transform to obtain the high-frequency signal ratio. The sound wave propagation speed is calculated based on the propagation time corresponding to the maximum amplitude energy peak of the short-range low-frequency sound wave. The high-frequency signal ratio and sound wave propagation speed at each monitoring time are used as the waveform detection data for that monitoring time. The waveform detection data in each monitoring window is analyzed to obtain the time-domain variation data in that monitoring window. The time-domain variation data includes the proportion of high-frequency signals and the degree of change in sound wave propagation speed. Based on the time-domain variation data, the surrounding rock deformation section data, and the DTW distance of the ground radar echo signal between adjacent monitoring times, it is determined whether the cycle segment is abnormal. For cycle segments that are determined to be normal, they are classified according to rock mass grade, and their ground radar echo signals are stored as standard templates. When the number of standard templates corresponding to the rock mass grade of the currently cyclic section is less than N, the DTW distance analysis of the time-domain variation data within the monitoring window and the ground radar echo signal between adjacent monitoring times is used to optimize the level of the top temporary support. When the number of standard templates corresponding to the rock mass grade of the currently cyclic section is not less than N, the DTW distance analysis of the time-domain variation data within the monitoring window, the ground radar echo signal and the standard template of the same rock mass grade is used to optimize the level of the top temporary support.

2. The continuous tunneling and backfilling mining method for fractured and thick ore bodies according to claim 1, characterized in that: The method for determining the level of temporary support for the top of the tunnel based on the rock mass grade is as follows: Obtain the uniaxial compressive strength and rock integrity coefficient of the rock mass to be determined. Construct a calculation formula for the basic quality index of the rock mass based on the uniaxial compressive strength and rock integrity coefficient. Based on the calculation results, classify the rock mass into grades 1-5 according to the basic quality classification table of the rock mass, and then assign the corresponding grade 1-5 top temporary support.

3. The continuous tunneling and backfilling mining method for fractured and thick ore bodies according to claim 1, characterized in that: During each monitoring moment, ground-penetrating radar waves and short-range low-frequency acoustic waves are emitted from the roof of the corresponding cycle segment, and echo signals are received. The ground-penetrating radar waves have a center frequency in the range of 100–250MHz, a bandwidth of 100–250MHz, and a single pulse duration of 0.3–1.5μs. The short-range low-frequency acoustic waves have a main frequency band in the range of 1–8kHz and a wave packet length of 2–10ms.

4. The continuous tunneling and backfilling mining method for fractured thick ore bodies according to claim 3, characterized in that: The method for obtaining the proportion of high-frequency signals by performing Fourier transform on the ground-penetrating radar echo signal is as follows: A 50Hz low-pass filter was used to filter the ground-penetrating radar echo signal. Preprocessing was performed using the moving average method. Then, a fast Fourier transform was used to convert the time-domain signal into a frequency-domain spectrum to obtain the frequency distribution and corresponding amplitude information of the signal. Using the center frequency of the selected ground-penetrating radar wave as a reference, the high-frequency band was defined as the interval of 1.2–2.0 times the center frequency. The total energy of the high-frequency band and the total energy of the entire frequency band were calculated. The total energy of the high-frequency band was obtained by integrating the square of the amplitude corresponding to each frequency point in the high-frequency band, and the total energy of the entire frequency band was obtained by integrating the square of the amplitude corresponding to each frequency point in the entire frequency band. Finally, the ratio of the total energy of the high-frequency band to the total energy of the entire frequency band was taken as the proportion of the high-frequency signal.

5. The continuous tunneling and backfilling mining method for fractured thick ore bodies according to claim 3, characterized in that: The method for calculating the speed of sound propagation based on the propagation time corresponding to the maximum amplitude energy peak of short-range low-frequency sound waves is as follows: The excitation source is fixed at the center of the roof, and two receiving sensors are linearly arranged along the upper part of both sides of the tunnel to obtain the distance from the excitation source to the two receiving sensors. After the sound wave is emitted, a 1kHz high-pass filter is used to filter the collected short-range low-frequency sound wave. In the pre-processed signal time-domain waveform, the maximum amplitude energy peak corresponding to the reflected wave is located, that is, the signal peak point with the largest absolute amplitude is locked. Taking the excitation source triggering time as the time starting point, the time coordinate corresponding to the signal peak point is the propagation time of the sound wave from the excitation source to the corresponding receiving sensor. Based on the corresponding arrival time, the propagation time is determined. The ratio of the distance from the excitation source to the receiving sensor to the corresponding arrival time is taken as the propagation speed of a single sound wave. The arithmetic mean of the propagation speeds of two single sound waves is taken as the propagation speed of the sound wave.

6. The continuous tunneling and backfilling mining method for fractured and thick ore bodies according to claim 5, characterized in that: The method for determining whether a cycle segment is abnormal based on time-domain variation data, surrounding rock deformation cross-sectional data, and the DTW distance of the ground radar echo signal between adjacent monitoring times is as follows: exist At monitoring times at equal time intervals, the data on surrounding rock deformation cross-sections, the degree of change in the proportion of high-frequency signals, the degree of change in acoustic wave propagation velocity, and the DTW distance of the ground-penetrating radar echo signals between two consecutive monitoring sessions were analyzed. For positive integers greater than 3, the specific process is as follows: The analysis of surrounding rock deformation cross-sectional data shows that the difference between the currently monitored surrounding rock deformation cross-sectional data and the data from the first monitoring of surrounding rock deformation cross-sectional data is used as the ratio of the difference to the data from the first monitoring of surrounding rock deformation cross-sectional data as the relative change rate of the surrounding rock deformation cross-section. The analysis of the proportion of high-frequency signals and the speed of sound propagation is based on the initial proportion of high-frequency signals and the initial speed of sound propagation. The ratio of the difference between the current proportion of high-frequency signals and the initial proportion of high-frequency signals to the initial proportion of high-frequency signals is used as the degree of change of the proportion of high-frequency signals, and the ratio of the difference between the current speed of sound propagation and the initial speed of sound propagation to the initial speed of sound propagation is used as the degree of change of the speed of sound propagation. For DTW distance analysis of preprocessed ground-penetrating radar echo signals from two consecutive monitoring sessions, the Min-Max normalization method was used to process the two signals, converting them into one-dimensional data sequences. A distance matrix was constructed based on the one-dimensional data sequences. The value at each position in the matrix represents the Euclidean distance between the corresponding data point in the one-dimensional data sequence of the first signal and all data points in the one-dimensional data sequence of the second signal after normalization, i.e., the square root of the square of the difference between the two data points. Then, the optimal matching path was found, starting from the upper left corner of the distance matrix and ending at the lower right corner. The path with the smallest cumulative distance was the optimal matching path. The path movement rules were limited to three types: rightward, downward, and diagonal. Finally, the cumulative distance was obtained by summing all matrix elements on the optimal matching path and dividing it by the sequence length to obtain the DTW distance between the two signals. During the process, the constraint window was set to 10% of the sequence length, which means that the optimal matching path could only move within a range of 10% of the sequence length on both sides of the main diagonal. First thresholds for the proportion of high-frequency signals, the velocity of sound waves, and the distance of ground-penetrating radar waves were set. Specifically, for the first threshold for the proportion of high-frequency signals, the threshold was set at 15% to 20% for rock masses of grades 1 to 2, and at 10% to 15% for rock masses of grades 3 to 5. For the first threshold for the velocity of sound waves, the threshold was uniformly set at 10% to 15%. For the first threshold for the distance of ground-penetrating radar waves, the threshold was set at 15% to 25% for rock masses of grades 1 to 2, at 20% to 30% for grade 3, and at 25% to 35% for rock masses of grades 4 to 5. At each monitoring time, if the monitoring data of the looped segment meets any of the following conditions, the looped segment is deemed to have an anomaly: Among the relative change rates of the deformation cross section of the surrounding rock, any one of the following reaches the warning threshold for the corresponding rock mass grade: roof subsidence, horizontal displacement of the two sides, and cross section convergence value; the degree of change in the proportion of high-frequency signals reaches the first change threshold for the proportion of high-frequency signals; the degree of change in the propagation speed of sound waves reaches the first change threshold for the speed of sound waves; and the DTW distance of the ground radar echo signals from two consecutive monitoring sessions reaches the first threshold for the distance of ground radar waves.

7. The continuous tunneling and backfilling mining method for fractured and thick ore bodies according to claim 6, characterized in that: The method for optimizing the level of temporary top support is based on the DTW distance analysis of the time-domain variation data within the monitoring window and the ground radar echo signals between adjacent monitoring times: Based on the set first threshold for the proportion of high-frequency signals, the first threshold for the change of sound wave velocity, and the first threshold for the distance of ground-penetrating radar waves, if the data monitored in the cyclic section meets any one of the following conditions, the current temporary support level at the top will be upgraded by one level; if the current level is already level 5, an alarm will be triggered directly. The conditions are: When the change in the proportion of high-frequency signals reaches the first threshold for change in the proportion of high-frequency signals; when the change in the speed of sound propagation reaches the first threshold for change in the speed of sound; when the distance between the ground-penetrating radar echo signals from two consecutive monitoring sessions reaches the first threshold for distance between ground-penetrating radar waves.

8. A continuous tunneling and backfilling mining method for fractured, thick ore bodies according to claim 6, characterized in that: Based on the temporal variation data within the monitoring window, the DTW distance analysis of the ground-penetrating radar echo signal and the standard template of the same rock mass grade, the method for optimizing the grade of the top temporary support is as follows: When the number of standard templates corresponding to the rock mass grade of the currently cyclic segment is not less than N, the threshold update is triggered, and statistics are performed in groups according to the monitoring time. The specific steps are as follows: Based on the monitoring time, all standard templates under the same rock mass grade are grouped according to the monitoring time, that is, each group corresponds to one monitoring time; For all standard templates within each group, calculate the DTW distance between any two standard templates using ground-penetrating radar echo signals individually. Extract the degree of change in the proportion of high-frequency signals, the degree of change in the propagation speed of sound waves, and the DTW distance of the ground radar echo signals in any two standard templates for each group at the corresponding monitoring time. Then, calculate the mean and standard deviation of the degree of change in the proportion of high-frequency signals, the degree of change in the propagation speed of sound waves, and the DTW distance of the ground radar echo signals. All three indicators are based on the statistical mean within the corresponding group, and are expanded to both sides by 2-3 times the standard deviation to obtain new thresholds for the proportion of high-frequency signals, the speed of sound propagation, and the distance of ground-penetrating radar waves, and are continuously iterated and updated. If the data from the currently monitored section meets any of the following conditions, the current temporary support level at the top will be upgraded by one level; if the current level is already level 5, an alarm will be triggered directly. The conditions are: Based on the set new thresholds for the proportion of high-frequency signals, the speed of sound, and the distance of ground-penetrating radar waves, the following conditions are met: when the change in the proportion of high-frequency signals reaches the new threshold for the proportion of high-frequency signals; when the change in the speed of sound propagation reaches the new threshold for the speed of sound; and when the DTW distance between the currently monitored ground-penetrating radar wave echo signal and the ground-penetrating radar wave echo signal of any standard template in the corresponding group exceeds the new threshold for the distance of ground-penetrating radar waves in the corresponding group.

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