Mine blasting vibration and noise coordinated control blasting method

Abstract

This invention provides a method for coordinated control of vibration and noise in mine blasting, relating to the field of blasting control technology. The method includes: acquiring historical blasting data to train a vibration and noise response prediction model; using geological parameters of the area to be blasted as fixed inputs and blasting parameters as optimization variables, inputting the blasting parameters into the model to generate an energy field distribution, determining overlapping high-risk areas with a safety threshold as the boundary, and iteratively optimizing to generate the optimal blasting parameter set with minimizing its area; inputting this into a coupled response model, decomposing vibration and noise energy components through wave field separation and generating time history curves; extracting the dominant frequencies of vibration and noise to calculate a frequency domain matching index, calculating a time domain peak shifting index based on the peak time difference; if both indices satisfy the constraints, executing the blasting operation; otherwise, adjusting and iterating again, thereby achieving coordinated control of vibration and noise.

Description

Technical Field

[0001] This invention relates to the field of blasting control technology, specifically a method for coordinated control of vibration and noise in mine blasting. Background Technology

[0002] As a primary means of mining, blasting generates two main harmful effects: blasting vibration and blasting noise. Blasting vibration propagates in the rock mass as elastic waves, easily leading to cracking of surrounding buildings and slope instability. Blasting noise propagates as air shock waves, causing noise pollution and triggering complaints and even disputes among residents. Traditional blasting control methods typically treat vibration control and noise control as two separate issues: millisecond delay blasting is used to reduce vibration by controlling the maximum charge per segment to reduce vibration amplitude; noise is reduced by strengthening borehole filling and optimizing the detonation network to minimize energy leakage into the air. However, this fragmented control approach often results in one aspect being neglected while the other is addressed. For example, improper setting of delay parameters during vibration reduction can lead to the noise generated by each borehole segment being superimposed and amplified in the air, resulting in the contradiction of "reducing vibration but increasing noise." Therefore, how to achieve coordinated control of vibration and noise while ensuring the blasting fracturing effect is a technical problem that urgently needs to be solved in this field.

[0003] In the prior art, a dual-index control blasting method for vibration velocity and damage in tunnel construction, disclosed in CN116663120A, establishes a comprehensive damage variable calculation model for surrounding rock blasting and a three-dimensional calculation model for tunnel blasting. It uses orthogonal design for numerical simulation to obtain simulation results of surface vibration velocity and surrounding rock damage, and then uses a Gaussian process regression algorithm to establish a prediction model. Finally, it outputs optimized blasting parameters with set surface vibration velocity control values ​​and surrounding rock damage control values ​​as input. This method achieves dual-index control of blasting vibration velocity and surrounding rock damage, but its control objects are limited to vibration effects (surface vibration velocity) and surrounding rock damage, without addressing the control of blasting noise. Furthermore, this method uses a static prediction model trained based on numerical simulation data, which can only output a set of blasting parameters according to preset control values. It lacks real-time analysis of the dynamic coupling relationship between vibration and noise during blasting, and cannot perform iterative optimization based on the time-frequency characteristics of vibration and noise, making it difficult to achieve synergistic suppression of vibration and noise.

[0004] 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

[0005] The purpose of this invention is to provide a method for coordinated control of vibration and noise in mine blasting, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A method for coordinated control of vibration and noise in mine blasting, comprising the following steps: S1: Obtain historical blasting data, including geological parameters, blasting parameters, and corresponding blasting response parameters of the blasting area during each round of historical blasting; use the geological parameters and blasting parameters in the historical blasting data as input and the corresponding blasting response parameters as output to train the vibration and noise response prediction model; S2: Using blasting parameters as optimization variables, the blasting parameters and geological parameters of the area to be blasted are input into the vibration and noise response prediction model. Based on the output blasting response parameters, the vibration energy field distribution and noise energy field distribution are generated. The vibration safety threshold and noise safety threshold of the area to be blasted are used as constraint boundaries to determine the overlapping high-risk area. With the goal of minimizing the area of ​​the overlapping high-risk area, the optimization variables are iteratively updated to generate the optimal blasting parameter set. S3: Input the optimal blasting parameter set into the coupled response model of vibration and noise. The coupled response model decomposes the total blasting energy corresponding to the optimal blasting parameter set into vibration energy components and noise energy components through the wave field separation algorithm, and generates vibration energy time history curves and noise energy time history curves. S4: Perform frequency domain transformation on the two time history curves, extract the vibration dominant frequency characteristic value and the noise dominant frequency characteristic value to calculate the frequency domain matching index, and calculate the time domain peak shifting index based on the peak time difference. Determine whether the two indices meet the corresponding constraints. If both are met, the optimal blasting parameter set is used as the target blasting parameter set, and the blasting operation is performed accordingly. Otherwise, the optimal blasting parameter set is adjusted based on the index type that does not meet the constraints, and the process returns to the previous step.

[0007] Furthermore, the historical blasting data includes the geological parameters, blasting parameters, and corresponding blasting response parameters of the blasting area for each round of historical blasting; The geological parameters specifically include rock mass density, compressive strength, three-dimensional distribution and burial depth of joint surfaces, and groundwater occurrence status. The blasting parameters specifically include the charge per borehole, the inter-bore delay, the inter-row delay, and the plugging length for each borehole. The blast response parameters specifically include peak vibration and noise decibel time-history decay data.

[0008] Furthermore, using the geological parameters and blasting parameters of each round of historical blasting as input and the blasting response parameters as output, a vibration and noise response prediction model is trained and constructed using a machine learning algorithm; the vibration and noise response prediction model can output the corresponding blasting response parameters based on the input geological parameters and blasting parameters. Geological parameters of the area to be blasted are obtained and used as fixed inputs to the vibration and noise response prediction model. Blasting parameters of the area to be blasted are used as optimization variables. The blasting parameters include the charge per hole, inter-hole delay, inter-row delay, and filling length of each blast hole. The geological parameters and blasting parameters of the area to be blasted are input into the vibration and noise response prediction model, and the model outputs the corresponding blasting response parameters.

[0009] Furthermore, the area to be blasted is evenly divided into several grids according to a preset grid density, and the geometric center of each grid is used as a monitoring point; A three-dimensional geological model of the area to be blasted is constructed based on geological parameters. By combining the correspondence between blasting parameters and blasting response parameters, the vibration energy density and noise energy density of each monitoring point are fitted using the finite element numerical simulation method, thereby establishing the vibration energy field distribution and noise energy field distribution covering the area to be blasted.

[0010] The vibration safety threshold is used as the constraint boundary for the vibration energy field distribution, and the noise safety threshold is used as the constraint boundary for the noise energy field distribution, specifically as follows: In the vibration energy field distribution, the contour lines corresponding to the vibration safety threshold are defined as vibration control boundaries. The area within the vibration control boundaries is the vibration exceedance risk zone, and the area outside the boundaries is the vibration safety zone. In the noise energy field distribution, the contour lines corresponding to the noise safety threshold are defined as noise control boundaries. The area within the noise control boundaries is the noise exceedance risk zone, and the area outside the boundaries is the noise safety zone. The spatial intersection area between the vibration exceeding the standard risk area and the noise exceeding the standard risk area is marked as the overlapping high-risk area, thereby determining the overlapping high-risk area of ​​the area to be blasted. With minimizing the area of ​​overlapping high-risk areas as the optimization objective, an optimization algorithm is used to iteratively solve the blasting parameters. During the iteration process, each iteration generates a corresponding overlapping high-risk area based on the geological parameters of the area to be blasted and the current blasting parameters. The above iteration process is repeated until the area of ​​overlapping high-risk areas no longer decreases for three consecutive times, at which point the iteration stops, and the blasting parameters obtained at this time are taken as the optimal blasting parameter set.

[0011] Furthermore, the optimal blasting parameter set is input into a pre-constructed coupled response model. The coupled response model is based on the blasting energy propagation and conversion mechanism and is used to characterize the mapping relationship between blasting parameters and the vibration energy and noise energy generated by blasting. The coupled response model takes the single-hole charge, inter-hole delay, inter-row delay and filling length of each borehole in the optimal blasting parameter set as input, and decomposes the total blasting energy into vibration energy components propagating in the rock medium and noise energy components propagating in the air medium through a wave field separation algorithm. The wave field separation algorithm is based on the principle of energy conservation and the propagation characteristics of the medium: First, the total charge and explosive performance parameters are obtained according to the optimal blasting parameter set to calculate the total blasting energy released at the moment of blasting; an energy distribution coefficient is introduced, which is determined by the filling length and the wave impedance of the rock mass medium. The vibration energy component and the noise energy component are determined according to the energy distribution coefficient and the total blasting energy, specifically: the vibration energy component is equal to the total blasting energy multiplied by the energy distribution coefficient, and the noise energy component is equal to the total blasting energy multiplied by one minus the energy distribution coefficient; The energy distribution coefficient is a function of the filling length and the wave impedance of the rock mass medium. The wave impedance is equal to the rock mass density multiplied by the longitudinal wave velocity. The longer the filling length, the larger the energy distribution coefficient, meaning more energy is converted into vibration energy. The shorter the filling length, the smaller the energy distribution coefficient, meaning more energy is converted into noise energy.

[0012] Furthermore, the vibration energy component is distributed to each borehole according to the single-hole charge ratio to obtain the vibration energy of each borehole, and then the vibration energy amplitude is obtained through energy-amplitude conversion; similarly, the noise energy component is distributed to each borehole according to the single-hole charge ratio to obtain the noise energy of each borehole, and then the noise energy amplitude is obtained through energy-amplitude conversion; thus, vibration energy time history curves and noise energy time history curves are generated respectively. The vibration energy time history curve and the noise energy time history curve are respectively subjected to frequency domain transformation, and the time domain signal is converted into a frequency domain signal using fast Fourier transform to obtain the vibration energy spectrum and the noise energy spectrum. Extract the dominant vibration frequency characteristic value from the vibration energy spectrum, i.e., the frequency corresponding to the maximum amplitude of the spectrum; extract the dominant noise frequency characteristic value from the noise energy spectrum, i.e., the frequency corresponding to the maximum amplitude of the spectrum; calculate the frequency domain matching index based on the dominant vibration frequency characteristic value and the dominant noise frequency characteristic value, specifically: the frequency domain matching index is equal to the minimum value of the dominant vibration frequency characteristic value and the dominant noise frequency characteristic value divided by the maximum value; The frequency domain matching index ranges from zero to one. The closer the frequency domain matching index is to one, the closer the vibration dominant frequency characteristic value is to the noise dominant frequency characteristic value, the higher the degree of frequency domain overlap, and the greater the risk of mutual reinforcement. The closer the frequency domain matching index is to zero, the higher the degree of frequency separation between the two, and the smaller the mutual interference. If the vibration dominant frequency characteristic value is the same as the noise dominant frequency characteristic value, the minimum value is equal to the maximum value, and the frequency domain matching index is 1.

[0013] Furthermore, the time-domain peak shaving index is calculated based on the vibration energy time history curve and the noise energy time history curve, which is the absolute time difference between the peak times of the two curves. Specifically, the time-domain peak shaving index is the absolute time difference between the peak times of the vibration energy time history curve and the noise energy time history curve. Among them, the peak moment of the vibration energy time history curve is the time point corresponding to the maximum amplitude of the vibration energy time history curve, and the peak moment of the noise energy time history curve is the time point corresponding to the maximum amplitude of the noise energy time history curve; the larger the time domain staggered peak index, the higher the degree of time stagger between the peak vibration energy and the peak noise energy, and the smaller the risk of the two superimposed and enhanced.

[0014] Furthermore, Frequency domain matching index The constraints are: the frequency domain matching index is less than or equal to the preset frequency domain matching index threshold; the constraints are: the time domain peak shaving index is greater than or equal to the preset time domain peak shaving index threshold. If the frequency domain matching index is less than or equal to If the time-domain peak-shaving index is greater than or equal to the time-domain peak-shaving index threshold, then the current optimal blasting parameter set is determined to meet the collaborative control requirements, and the optimal blasting parameter set is determined as the target blasting parameter set. If the frequency domain matching index is greater than If the frequency domain matching index does not meet the requirements, the specific adjustment strategy for adjusting the optimal blasting parameter set is as follows: by changing the ratio of the inter-hole delay to the inter-row delay, the vibration main frequency and the noise main frequency will be relatively offset, increasing the frequency difference between the two, thereby reducing the frequency domain matching index until it meets the corresponding constraint conditions. If the time-domain peak shaving index is less than the time-domain peak shaving index threshold, it is determined that the time-domain peak shaving index does not meet the requirements. At this time, the specific adjustment strategy for adjusting the optimal blasting parameter set is: by changing the absolute values ​​of the inter-hole delay and the inter-row delay, the peak vibration energy and the peak noise energy are relatively offset in time, increasing the peak time difference between the two, thereby improving the time-domain peak shaving index to meet the threshold requirements. If neither the frequency domain matching index nor the time domain peak shifting index meets the threshold requirements, then both adjustment strategies mentioned above are executed simultaneously. Priority is given to ensuring that the frequency domain matching index meets the requirements before iteratively adjusting the time domain peak shifting index. After the adjustment is completed, the optimal blasting parameter set is updated and the process returns to the previous step until both the frequency domain matching index and the time domain peak shifting index meet the threshold requirements. The optimal blasting parameter set that meets the threshold requirement is taken as the target blasting parameter set, and on-site blasting operations are performed based on the target blasting parameter set.

[0015] Compared with the prior art, the beneficial effects of the present invention are: First, by constructing the distribution of vibration energy field and noise energy field, and using the vibration safety threshold and noise safety threshold as constraint boundaries respectively, this invention identifies the overlapping high-risk area of ​​the vibration exceeding risk area and the noise exceeding risk area, and uses this area as the key area for collaborative control, thereby realizing the unified planning and synchronous suppression of the two harmful effects of vibration and noise, and overcoming the technical contradiction of "reducing vibration but increasing noise" or "reducing noise but increasing vibration" in traditional methods. Secondly, by constructing a frequency domain matching index and a time domain peak shifting index, this invention quantifies the degree of matching between the vibration main frequency and the noise main frequency, as well as the relative temporal relationship between the vibration energy peak and the noise energy peak. By comparing the two indices with preset thresholds and adopting frequency domain frequency shifting or time domain peak shifting adjustment strategies according to the type of index that is not satisfied, the invention achieves accurate quantification and directional optimization of the vibration and noise coordinated state. Furthermore, this invention decomposes the total blasting energy into vibration energy components and noise energy components through a wave field separation algorithm, establishes a quantitative relationship between filling length, wave impedance, and energy distribution coefficient, and achieves dual control over the distribution ratio of blasting energy in rock mass and air and the waveform superposition effect through the generation and iterative optimization of vibration energy time history curves and noise energy time history curves. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2 Spline curve images of the characteristic values ​​of the dominant vibration frequency and the characteristic values ​​of the dominant noise frequency; Figure 3 This is a dual Y-axis image showing the peak times of noise and vibration. Detailed Implementation

[0017] 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.

[0018] 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.

[0019] Example: Please see Figure 1-3 The present invention provides a technical solution: A method for coordinated control of vibration and noise in mine blasting, comprising the following steps: S1: Obtain historical blasting data, including geological parameters, blasting parameters, and corresponding blasting response parameters of the blasting area during each round of historical blasting; use the geological parameters and blasting parameters in the historical blasting data as input and the corresponding blasting response parameters as output to train the vibration and noise response prediction model; In this embodiment, the historical blasting data includes the geological parameters, blasting parameters, and corresponding blasting response parameters of the blasting area during each round of historical blasting; The geological parameters specifically include rock mass density, compressive strength, three-dimensional distribution and burial depth of joint surfaces, and groundwater occurrence status. The blasting parameters specifically include the charge per borehole, the inter-bore delay, the inter-row delay, and the plugging length for each borehole. The blast response parameters specifically include peak vibration and noise decibel time-history decay data.

[0020] Using the geological parameters and blasting parameters of each historical blasting round as input and the blasting response parameters as output, a vibration and noise response prediction model is trained and constructed using a machine learning algorithm; the vibration and noise response prediction model can output the corresponding blasting response parameters based on the input geological parameters and blasting parameters. Geological parameters of the area to be blasted are obtained and used as fixed inputs to the vibration and noise response prediction model. Blasting parameters of the area to be blasted are used as optimization variables. The blasting parameters include the charge per hole, inter-hole delay, inter-row delay, and filling length of each blast hole. The geological parameters and blasting parameters of the area to be blasted are input into the vibration and noise response prediction model, and the model outputs the corresponding blasting response parameters.

[0021] The vibration and noise response prediction model uses a random forest algorithm as the machine learning model. Furthermore, in this embodiment, 30 sets of historical blasting data were collected and randomly divided into training and testing sets at an 8:2 ratio. The random forest model parameters were set as follows: 100 decision trees, maximum depth 10, and minimum number of leaf node samples 2. Bagging ensemble learning was used for training. During training, the model constructed multiple decision trees, and each tree randomly selected a subset of input features for node splitting, using mean squared error as the splitting criterion. Finally, the average prediction results of all decision trees were taken as the model output. The test set verified that the model's average relative error in predicting peak vibration velocity was 8.6%, and the average absolute error in predicting noise decibels was 2.3 dB, meeting the requirements for engineering applications. After training, the model can quickly output the corresponding blasting response parameters based on any input geological and blasting parameters, avoiding the tedious process of repeated solutions in traditional finite element numerical simulations.

[0022] Step S1 establishes a high-precision nonlinear mapping relationship from geological parameters and blasting parameters to blasting response parameters by acquiring historical blasting data and training a vibration and noise response prediction model. This provides a fast and reliable response prediction tool for subsequent blasting parameter optimization. This step fully utilizes the actual monitoring information of historical blasting data, enabling the model to learn and solidify the inherent laws between blasting parameters and vibration and noise responses. This avoids the tedious process of repeated solutions in traditional numerical simulations, significantly improving the computational efficiency of parameter optimization. At the same time, it provides an accurate response prediction basis for generating energy field distribution, identifying overlapping high-risk areas, and iteratively optimizing blasting parameters in step S2.

[0023] S2: Using blasting parameters as optimization variables, the blasting parameters and geological parameters of the area to be blasted are input into the vibration and noise response prediction model. Based on the output blasting response parameters, the vibration energy field distribution and noise energy field distribution are generated. The vibration safety threshold and noise safety threshold of the area to be blasted are used as constraint boundaries to determine the overlapping high-risk area. With the goal of minimizing the area of ​​the overlapping high-risk area, the optimization variables are iteratively updated to generate the optimal blasting parameter set. In this embodiment, the geological parameters of the area to be blasted are obtained and used as the fixed input of the vibration and noise response prediction model. The blasting parameters of the area to be blasted are used as optimization variables. The blasting parameters include the single-hole charge, inter-hole delay, inter-row delay and filling length of each blast hole. The geological parameters of the area to be blasted are used as fixed inputs, while the blasting parameters are used as optimization variables. This is because the geological parameters are determined by the site conditions and cannot be changed through blasting design, while the blasting parameters are control variables that can be actively adjusted before construction. By using the latter as optimization variables, the release intensity, distribution ratio, and waveform superposition effect of blasting energy can be actively controlled without changing the geological environment. This minimizes the area of ​​overlapping high-risk areas while meeting vibration and noise safety threshold constraints, thus achieving synergistic optimization of blasting effect and harmful effect control.

[0024] The geological parameters and blasting parameters of the area to be blasted are input into the vibration and noise response prediction model, and the model outputs the corresponding blasting response parameters. The area to be blasted is divided into The grid density is uniformly divided into several grids, and the geometric center of each grid is used as the monitoring point; A three-dimensional geological model of the area to be blasted is constructed based on geological parameters. By combining the correspondence between blasting parameters and blasting response parameters, the vibration energy density and noise energy density of each monitoring point are fitted using the finite element numerical simulation method, thereby establishing the vibration energy field distribution and noise energy field distribution covering the area to be blasted.

[0025] The overall logic behind the above process is as follows: obtain the geological parameters, blasting parameters, and corresponding blasting response parameters of the area to be blasted; divide the blasting area into uniform grids with a preset grid density of 0.5m × 0.5m; use the geometric center of each grid as a monitoring point; construct a three-dimensional geological model of the area to be blasted based on the geological parameters; use the finite element numerical simulation method, taking the blasting parameters as the input load; use the peak vibration velocity and noise decibel time history attenuation data at the monitoring points as the fitting targets; and iteratively adjust the material damping, boundary conditions, and energy attenuation coefficient in the model to fit the vibration energy density and noise energy density of each monitoring point point by point, and then interpolate to generate a continuous vibration energy field distribution and noise energy field distribution covering the entire area to be blasted. The vibration safety threshold is used as the constraint boundary for the vibration energy field distribution, and the noise safety threshold is used as the constraint boundary for the noise energy field distribution, specifically as follows: In the vibration energy field distribution, the contour lines corresponding to the vibration safety threshold are defined as vibration control boundaries. The area within the vibration control boundaries is the vibration exceedance risk zone, and the area outside the boundaries is the vibration safety zone. In the noise energy field distribution, the contour lines corresponding to the noise safety threshold are defined as noise control boundaries. The area within the noise control boundaries is the noise exceedance risk zone, and the area outside the boundaries is the noise safety zone. The vibration safety threshold is determined comprehensively based on the structural type of the protective buildings surrounding the blasting area, the permissible vibration velocity standard, and the on-site geological conditions. The noise safety threshold is determined comprehensively based on the environmental functional zoning of the surrounding area and the national sound environment quality standards. The vibration safety threshold is used as the constraint boundary for the vibration energy field distribution. The contour lines corresponding to the threshold are extracted from the vibration energy field distribution as vibration control boundaries. The area within the boundary is determined as the vibration exceeding risk zone, and the area outside the boundary is the vibration safe zone. Similarly, the noise safety threshold is used as the constraint boundary for the noise energy field distribution. Its contour lines are extracted as noise control boundaries. The area within the boundary is the noise exceeding risk zone, and the area outside the boundary is the noise safe zone. Finally, through spatial superposition analysis, the spatial intersection area of ​​the vibration exceeding risk zone and the noise exceeding risk zone is marked as the overlapping high-risk area. This area is the target area where the combined harmful effects of vibration and noise are most severe.

[0026] With minimizing the area of ​​overlapping high-risk areas as the optimization objective, an optimization algorithm is used to iteratively solve the blasting parameters. During the iteration process, each iteration generates a corresponding overlapping high-risk area based on the geological parameters of the area to be blasted and the current blasting parameters. The above iteration process is repeated until the area of ​​overlapping high-risk areas no longer decreases for three consecutive times, at which point the iteration stops, and the blasting parameters obtained at this time are taken as the optimal blasting parameter set.

[0027] Step S2 uses the geological parameters of the area to be blasted as fixed inputs and the blasting parameters as optimization variables. It utilizes a vibration and noise response prediction model to quickly generate the vibration and noise energy field distribution. It accurately identifies overlapping high-risk areas with vibration and noise safety thresholds as boundaries, and iteratively solves the problem by minimizing the area of ​​these areas as the optimization objective. This achieves an efficient transformation from global multi-objective constraints to local single-objective optimization. This step separates the unchangeable geological conditions from the actively controllable blasting parameters. Under the premise of ensuring the blasting fragmentation effect, iterative optimization actively adjusts key parameters such as single-hole charge, inter-hole delay, inter-row delay, and filling length to minimize the area where both vibration and noise exceed the standard. This provides the basis for optimal blasting parameters that balance safety and efficiency for subsequent coupled response analysis.

[0028] S3: Input the optimal blasting parameter set into the coupled response model of vibration and noise. The coupled response model decomposes the total blasting energy corresponding to the optimal blasting parameter set into vibration energy components and noise energy components through the wave field separation algorithm, and generates vibration energy time history curves and noise energy time history curves. In this embodiment, the optimal blasting parameter set is input into a pre-constructed coupled response model. The coupled response model is based on the blasting energy propagation and conversion mechanism and is used to characterize the mapping relationship between blasting parameters and the vibration energy and noise energy generated by blasting. The coupled response model takes the single-hole charge, inter-hole delay, inter-row delay and filling length of each borehole in the optimal blasting parameter set as input, and decomposes the total blasting energy into vibration energy components propagating in the rock medium and noise energy components propagating in the air medium through a wave field separation algorithm. The wave field separation algorithm is based on the principle of energy conservation and the propagation characteristics of the medium: First, the total amount of explosive and the performance parameters of the explosive are obtained according to the optimal blasting parameter set. The heat of explosion per unit mass of explosive is determined by the measured value of the explosive heat bomb or by thermochemical calculation method (such as Hess's law). Then, the total blasting energy released at the moment of blasting is calculated. Let the total energy of the explosion be Then the vibrational energy component and noise energy components satisfy The ratio of vibration energy component to noise energy component is determined by the filling length and the wave impedance of the rock mass medium, specifically: in, The energy distribution coefficient. , For the filling length, The wave impedance of the rock mass medium. , For rock mass density, The longitudinal wave velocity; the longer the clogging length, the higher the energy distribution coefficient. The larger the length, the more energy is converted into vibrational energy; the shorter the length of the filling, the more energy is converted into vibrational energy. The smaller the value, the more energy is converted into noise energy; The logic behind this formula is based on the distribution mechanism of blasting energy in the two media, rock and air: total blasting energy Released instantaneously by the explosion of explosives, a portion of the energy propagates through the rock mass in the form of elastic waves, forming vibrational energy. Another part propagates through the air in the form of shock waves, forming noise energy. Both satisfy the law of conservation of energy. Energy distribution coefficient As a key parameter characterizing the ratio of vibration to noise energy distribution, its value is affected by the packing length. and rock mass impedance The combined control of these factors means that the longer the packing length, the longer the explosive gas remains within the borehole, and more energy is confined within the rock mass and converted into vibrational waves. The larger the diameter, the shorter the packing length, the easier it is for high-pressure gas to escape from the orifice, resulting in more energy leakage into the air and creating noise. The smaller the value; at the same time, the rock mass wave impedance This reflects the rock mass's ability to impede the propagation of vibration waves; the higher the wave impedance, the higher the efficiency of vibration energy transfer to the rock mass. The corresponding increase.

[0029] Furthermore, in this embodiment, the following is set: ,in, , , , These are empirical coefficients obtained by fitting historical blasting data; by establishing... Based on the functional relationship, this wave field separation algorithm achieves a quantitative description of the distribution ratio of total blast energy between vibration and noise, providing a physical basis for the subsequent generation of vibration energy time history curves and noise energy time history curves.

[0030] Based on determining the vibration energy components and noise energy components, The propellant charge was distributed to each borehole according to the proportion of propellant charge per borehole, and the vibration energy of each borehole was obtained. The vibration energy amplitude is then obtained through energy-amplitude conversion. Similarly, The charge amount was allocated to each borehole according to the single-hole charge ratio, and the noise energy of each borehole was obtained. The noise energy amplitude is then obtained through energy-to-amplitude conversion. ; and then respectively generate vibration energy time history curves. Time history curve of noise energy Its time-domain expression is as follows: in, and The first The amplitude of vibration energy and noise energy generated by each borehole; and These are the attenuation coefficients of vibration energy and noise energy in the medium, respectively. The range of values ​​is , The range of values ​​is ; and The first The dominant vibration frequency and noise frequency generated by each borehole; and This is the initial phase; Indicates the moment of detonation; For the first The detonation time of each borehole is determined by the inter-bore delay and the inter-row delay; Let be the Dirac function, representing the th A gun hole in Detonation at any moment; It is a natural constant; in, The range of values ​​is The value is determined based on the integrity of the rock mass, the degree of joint and fissure development, and the lithology. A lower value is taken for intact and dense rock masses, and a higher value is taken for broken and weak rock masses. The range of values ​​is Based on geometric diffusion, atmospheric absorption, and obstacle shielding effects in the air medium, it covers the typical attenuation range of common rock mass types and environmental conditions in mine blasting; initial phase and This indicates the vibration or noise wave generated when the i-th borehole is detonated. The initial phase angle at time is affected by factors such as the type of explosive, the charge structure, and the borehole conditions; its acquisition methods include: taking... , As a conservative estimate (maximum superposition effect), it is extracted through waveform fitting from a single-hole blasting test or Hilbert transform, or by adopting the random phase assumption. The intervals follow a uniform distribution. In this embodiment, to simplify calculations and ensure safety, the initial phase of all boreholes is set to 0.

[0031] The specific logic of this step lies in obtaining the vibrational energy component from the total blast energy through a wave field separation algorithm. and noise energy components Next, these two global energy values ​​need to be decomposed onto each borehole to generate waveform curves with time histories. Since the amount of propellant in each borehole directly affects the amount of energy released, the energy is determined according to the proportion of the amount of propellant in each borehole to the total amount of propellant in all boreholes. and The energy is distributed to each borehole to obtain the vibration energy of each borehole. and noise energy Then, through energy-amplitude conversion, the energy allocated to each borehole is converted into vibration energy amplitude and noise energy amplitude. Based on this, each borehole is regarded as an independent waveform source, and the vibration signal and noise signal it generates are described by a sinusoidal function with exponential decay, where the decay coefficient is... and This reflects the characteristic that the energy of vibration waves decreases with increasing distance in rock masses and noise waves in air; the dominant vibration frequency... and noise main frequency Determined by blasting parameters, the initial phase and the random or deterministic phase difference reflecting the detonation time are used. The detonation time is jointly determined by the inter-hole delay and the inter-row delay, and the Dirac function is used. This accurately indicates the location of the blast hole. The physical process of instantaneous detonation; by linearly superimposing the waveforms generated by all boreholes in the time domain, the overall vibration energy time history curve is obtained. and noise energy time history curve This enables complete time-domain modeling from global energy allocation to individual borehole waveform generation and then to overall waveform synthesis, providing a foundation for subsequent frequency-domain transformation and collaborative control evaluation.

[0032] Step S3 inputs the optimal blasting parameter set into the coupled response model and uses a wave field separation algorithm to quantitatively decompose the total blasting energy into vibration energy components and noise energy components, generating time history curves for vibration and noise. This achieves a physical mapping from discrete blasting parameters to continuous time-domain waveforms, providing a complete waveform data foundation for subsequent frequency and time-domain analysis. Simultaneously, this step establishes a quantitative relationship between the filling length and rock mass wave impedance on the vibration-noise energy distribution ratio through the energy distribution coefficient λ. This allows for a clear quantification of the propagation path and conversion mechanism of blasting energy, overcoming the deficiency of traditional methods in distinguishing the sources of vibration and noise energy. This provides a physically interpretable decomposition basis for the coordinated control of vibration and noise.

[0033] S4: Perform frequency domain transformation on the two time history curves, extract the vibration dominant frequency characteristic value and the noise dominant frequency characteristic value to calculate the frequency domain matching index, and calculate the time domain peak shifting index based on the peak time difference. Determine whether the two indices meet the corresponding constraints. If both are met, the optimal blasting parameter set is used as the target blasting parameter set, and the blasting operation is performed accordingly. Otherwise, the optimal blasting parameter set is adjusted based on the index type that does not meet the constraints, and the process returns to the previous step. In this embodiment, the vibration energy time history curve Time history curve of noise energy Frequency domain transformations were performed separately, and the time-domain signal was converted into a frequency-domain signal using a fast Fourier transform to obtain the vibration energy spectrum. With noise energy spectrum : From the vibration energy spectrum Extracting vibration dominant frequency eigenvalues That is, the frequency corresponding to the maximum amplitude of the spectrum; from the noise energy spectrum Extracting the dominant frequency feature value of noise That is, the frequency corresponding to the maximum amplitude of the spectrum; the frequency domain matching index is calculated based on the characteristic values ​​of the vibration dominant frequency and the noise dominant frequency. The formula it is based on is as follows: in, The range of values ​​is , The closer the value is to 1, the closer the vibration dominant frequency characteristic value is to the noise dominant frequency characteristic value, the higher the degree of frequency domain overlap, and the greater the risk of the two reinforcing each other. The closer to 0, the higher the degree of frequency separation between the two and the less mutual interference; if the characteristic value of the vibration dominant frequency is the same as that of the noise dominant frequency, then the minimum value is equal to the maximum value, and the frequency domain matching index is 1. For this formula, It is used to quantify the degree of overlap between the dominant frequency of blasting vibration and the dominant frequency of noise in the frequency domain, and directly characterizes the risk of mutual interference between vibration energy and noise energy in the frequency distribution. The closer a value is to 1, the closer the dominant vibration frequency and the dominant noise frequency are, and the larger the overlap in the frequency domain. This makes them more prone to resonance or energy superposition and enhancement, leading to mutual aggravation of vibration and noise, and causing more serious combined damage to the surrounding environment and buildings. Conversely, a value closer to 1 indicates a greater likelihood of resonance or energy superposition and enhancement, leading to mutual aggravation of vibration and noise, and causing more serious combined damage to the surrounding environment and buildings. The closer the value is to 0, the higher the degree of separation between the vibration frequency and the noise frequency. The two are staggered in the frequency domain, which significantly reduces the risk of energy superposition and enhancement, and is conducive to achieving coordinated control of vibration and noise.

[0034] The dominant frequency characteristic value of vibration and the dominant frequency characteristic value of noise are two independent frequency parameters. The magnitude of their absolute difference directly determines the degree of frequency overlap. However, the absolute difference is greatly affected by the order of frequency. For example, the difference between 10Hz and 20Hz is 10Hz, while the difference between 100Hz and 110Hz is also 10Hz. However, the frequency ratio of the former is 0.5, while that of the latter is 0.91, showing a significant difference in the degree of overlap. The ratio form essentially calculates the relative closeness of two frequencies rather than their absolute difference, which can eliminate the influence of frequency magnitude and make the frequency matching degree of different frequency bands comparable. Physically speaking, when two frequencies are equal, the ratio is 1, which means complete overlap and the greatest risk of resonance. When one frequency is much smaller than the other, the ratio approaches 0, which means that the spectrum is completely separated and does not interfere with each other.

[0035] The logic behind this formula stems from the superposition principle of vibration and sound waves propagating in a medium: when two wave signals with different frequencies are superimposed, if the frequencies are the same or similar, a beat frequency phenomenon or resonance effect will occur, leading to a significant increase in the amplitude of the synthesized wave; if the frequency difference is large, the energy is dispersed and the superposition enhancement effect is weak; therefore, the key to controlling the synergy between vibration and noise lies in making the dominant frequencies of the two as separate as possible in the frequency domain; the formula... The proximity of two frequencies is normalized to the (0,1] interval in the form of a ratio. hour The maximum value of 1 represents the most unfavorable state; as the difference between the two increases, the ratio decreases monotonically until it approaches 0, indicating that the control effect is improving.

[0036] According to the vibration energy time history curve Time history curve of noise energy Calculate the time-domain peak shaving index That is, the absolute time difference between the peak times of the two curves: In the formula, This represents the peak moment of the vibration energy time history curve. This represents the peak moment of the noise energy time history curve; The larger the value, the greater the time difference between the peak vibration energy and the peak noise energy, and the lower the risk of their superposition and enhancement.

[0037] Time-domain peak shift index This method is used to quantify the time-separation between the peak energy of blasting vibration and the peak energy of noise, directly characterizing the magnitude of the risk of the two harmful effects being superimposed and enhanced in the time domain. The larger the value, the greater the time difference between the vibration peak and the noise peak, the greater the temporal separation between the two, and the lower the probability of the energy peaks overlapping. Therefore, the risk of vibration and noise mutually reinforcing each other is smaller; conversely, The smaller the value, the more likely the two peaks arrive at almost the same time or nearly at the same time, which can easily lead to in-phase superposition in the time domain, resulting in a significant amplification of the combined effect of vibration and noise, causing greater combined damage to the surrounding environment and buildings.

[0038] Vibration waves propagate in rock masses as elastic waves, with a wave speed typically between 2000 and 6000 m / s, while noise waves propagate in air as sound waves, with a wave speed of approximately 340 m / s. The difference in their propagation speeds is an order of magnitude. Therefore, even if vibration waves and noise waves are generated simultaneously from the same blast source, their arrival times at the same monitoring point will differ due to the difference in propagation medium and wave speed. It is by utilizing this physical property that the time difference between the arrival of the peaks of the two waveforms can be directly measured. From the perspective of the superposition principle, when the peaks of the two waveforms are perfectly aligned in time, the combined amplitude is the sum of the amplitudes of the two waveforms, which is the most harmful. As the time difference increases, the peaks are staggered, the combined amplitude is less than the sum of the amplitudes, and the harm is reduced. Therefore, using the absolute time difference at the peak moment can intuitively and accurately reflect the strength of the time-domain superposition effect.

[0039] The logic behind this formula stems from the fundamental principle of wave superposition: when two waveforms are superimposed in the time domain, the amplitude of the synthesized waveform depends on the instantaneous values ​​of each waveform at the same moment. If the vibration peak and the noise peak arrive simultaneously, the synthesized amplitude reaches its maximum, posing the greatest threat; if there is a difference in their arrival times, the synthesized amplitude is less than the sum of their amplitudes. The formula... The degree of peak shifting can be directly quantified in the form of absolute time difference, which has a clear physical meaning and is easy to calculate.

[0040] Statistical table of blasting vibration-noise coordinated control data Based on the data of the above 15 blasting schemes and Figure 2 , Figure 3 It can be seen that, Figure 2 The red diagonal line represents the complete equality of the vibration and noise frequencies, indicating a perfect frequency domain match. Through parameter iteration optimization, it can be seen that most scattered points deviate from the diagonal line. The closer the curve is to the diagonal line, the closer the vibration and noise frequencies are, the higher the degree of frequency domain overlap, and the greater the risk of superposition enhancement. The further the curve deviates from the diagonal line, the greater the frequency difference between the two, the better the frequency domain misalignment effect, and the more effectively the vibration-noise coupling hazard can be reduced. Figure 3 The peak moment curve shows that the vibration peak moment increases steadily with the scheme number, which is consistent with the blasting row-by-row initiation and rock vibration propagation law. The noise peak moment fluctuates, which is due to the active adjustment of the time-domain peak staggering between holes and rows. The time-domain peak staggering index is reasonably distributed. The data truly reflects the time-domain coupling and decoupling characteristics of vibration and noise in mine blasting. Overall, it verifies the effectiveness and engineering rationality of the vibration and noise collaborative control method in terms of frequency domain staggering and time domain peak staggering.

[0041] frequency domain matching index and time-domain peak-shifting index Each is matched with a preset frequency domain matching index threshold. Time-domain peak misalignment index threshold Perform a comparison, if and If the current optimal blasting parameter set meets the requirements of coordinated control, then the optimal blasting parameter set is determined as the target blasting parameter set. Among them, the frequency domain matching index threshold The specific determination method is as follows: based on the inherent structural frequencies of protective structures surrounding the mine blasting area and their sensitivity to environmental noise, combined with the statistical distribution patterns of historical blasting vibration and noise frequencies, a safety threshold principle is adopted. Specifically, when the ratio of the vibration frequency to the noise frequency is higher than 0.85, the overlap between the two in the frequency domain is high, significantly increasing the risk of resonance, requiring frequency domain misalignment adjustment; when the ratio is lower than 0.7, the two are sufficiently separated, and the superposition enhancement effect is controllable. Considering both safety margin and control costs, this embodiment sets... This threshold can be dynamically calibrated based on actual monitoring data from different mines.

[0042] Time-domain peak shaving index threshold The specific method for determining this is as follows: Based on the difference between the propagation speed of vibration waves in rock mass (approximately 2000–6000 m / s) and the propagation speed of noise waves in air (approximately 340 m / s), and combined with the distance from the monitoring point in the blasting area to the blast source, the inherent propagation time difference between vibration waves and noise waves is calculated. ,in The distance from the explosion source to the monitoring point. For longitudinal wave velocity, Let the velocity of the sound wave be denoted by 1 / 2 of this inherent time difference, which is taken as the minimum effective peak shifting time. In this embodiment, the average distance from the monitoring point to the explosion source is taken. =300m, P-wave velocity = 4000m / s, speed of sound = 340m / s, calculated ,Pick That is, when It is assumed that the peak values ​​of vibration and noise are effectively staggered in the time domain, and the risk of their superposition is controllable. This threshold can also be dynamically adjusted based on on-site measured waveform data and safety control requirements.

[0043] like If the frequency domain matching index does not meet the requirements, the optimal blasting parameter set needs to be adjusted to achieve frequency domain misalignment. The specific adjustment strategy is to change the ratio between the inter-hole delay and the inter-row delay to make the vibration main frequency and the noise main frequency shift relative to each other, increase the frequency difference between the two, and thus reduce the frequency domain matching index until it meets the corresponding constraint conditions. like If the time-domain peak shaving index does not meet the requirements, the optimal blasting parameter set needs to be adjusted to achieve time-domain peak shaving. The specific adjustment strategy is to change the absolute values ​​of the inter-hole delay and inter-row delay to make the peak vibration energy and peak noise energy shift relative in time, increase the peak time difference between the two, and thus improve the time-domain peak shaving index until it meets the corresponding constraint conditions. If neither the frequency domain matching index nor the time domain peak shifting index meets the threshold requirements, then both adjustment strategies are executed simultaneously. Priority is given to ensuring that the frequency domain matching index meets the requirements before iteratively adjusting the time domain peak shifting index. After the adjustment is completed, the optimal blasting parameter set is updated and returned to S3, until the frequency domain matching index meets the threshold. and time-domain peak-shifting index All meet the threshold requirements; Step S4 involves performing frequency domain transformation and time domain analysis on the vibration energy time history curve and the noise energy time history curve, respectively, to extract the dominant vibration frequency and the dominant noise frequency and calculate the frequency domain matching index. Simultaneously, the time domain peak-shaving index at the peak times of the two curves is calculated. The two indices are compared with preset thresholds, achieving a precise quantitative assessment of the coordinated state of vibration and noise in both the frequency and time domains. This step determines whether the dominant vibration frequency and the dominant noise frequency are sufficiently separated based on the frequency domain matching index to avoid resonance enhancement, and whether the peak vibration value and the peak noise value are effectively staggered based on the time domain peak-shaving index to avoid time-domain superposition and amplification. Depending on the type of index that is not satisfied, directional adjustment strategies of frequency domain frequency misalignment or time domain peak misalignment are adopted, providing a clear dual-domain feedback basis for the iterative optimization of blasting parameters. This ensures that the final determined target blasting parameter set can simultaneously achieve coordinated suppression of vibration and noise in both the frequency and time domains.

[0044] The blasting parameter set that satisfies both the frequency domain matching index threshold and the time domain peak offset index threshold is determined as the target blasting parameter set, and on-site blasting operations are carried out accordingly. This achieves a seamless connection from theoretical optimization to engineering application, ensuring the feasibility and effectiveness of the vibration and noise synergistic control method in actual mine blasting. This step directly transforms the frequency domain frequency offset and time domain peak offset results obtained from previous multi-round iterative optimization into an implementable blasting scheme, which fully separates the dominant vibration frequency and the dominant noise frequency, and effectively offsets the vibration peak and the noise peak, fundamentally avoiding the mutual reinforcement effect of vibration and noise. Ultimately, it achieves the synergistic control objective of simultaneously meeting the vibration safety threshold and the noise safety threshold while ensuring the blasting fragmentation effect, significantly improving the safety and environmental friendliness of mine blasting operations.

[0045] 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.

[0046] 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.

[0047] 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.

[0048] 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 coordinated control of vibration and noise in mine blasting, characterized in that, include: Acquire historical blasting data, including the geological parameters, blasting parameters, and corresponding blasting response parameters of the blasting area for each round of historical blasting; The vibration and noise response prediction model is trained by using geological parameters and blasting parameters from historical blasting data as inputs and corresponding blasting response parameters as outputs. Using blasting parameters as optimization variables, the blasting parameters and geological parameters of the area to be blasted are input into the vibration and noise response prediction model. Based on the output blasting response parameters, the vibration energy field distribution and noise energy field distribution are generated. The vibration safety threshold and noise safety threshold of the area to be blasted are used as constraint boundaries to determine the overlapping high-risk area. With the goal of minimizing the area of ​​the overlapping high-risk area, the optimization variables are iteratively updated to generate the optimal blasting parameter set. The optimal blasting parameter set is input into the coupled response model of vibration and noise. The coupled response model decomposes the total blasting energy corresponding to the optimal blasting parameter set into vibration energy components and noise energy components through the wave field separation algorithm, and generates vibration energy time history curves and noise energy time history curves. The frequency domain transformation is performed on the two time history curves to extract the characteristic values ​​of the vibration dominant frequency and the characteristic values ​​of the noise dominant frequency to calculate the frequency domain matching index. The time domain peak shifting index is calculated based on the peak time difference. It is determined whether the two indices meet the corresponding constraints. If both are met, the optimal blasting parameter set is used as the target blasting parameter set, and the blasting operation is performed accordingly. Otherwise, the optimal blasting parameter set is adjusted based on the index type that does not meet the constraints, and the process returns to the previous step.

2. The method for coordinated control of vibration and noise in mine blasting according to claim 1, characterized in that: The historical blasting data includes the geological parameters, blasting parameters, and corresponding blasting response parameters of the blasting area during each round of historical blasting. The geological parameters specifically include rock mass density, compressive strength, three-dimensional distribution and burial depth of joint surfaces, and groundwater occurrence status. The blasting parameters specifically include the charge per borehole, the inter-bore delay, the inter-row delay, and the plugging length for each borehole. The blast response parameters specifically include peak vibration and noise decibel time-history decay data.

3. The method for coordinated control of vibration and noise in mine blasting according to claim 2, characterized in that: Using the geological parameters and blasting parameters of each historical blasting round as input and the blasting response parameters as output, a vibration and noise response prediction model is trained and constructed using a machine learning algorithm; the vibration and noise response prediction model can output the corresponding blasting response parameters based on the input geological parameters and blasting parameters. Geological parameters of the area to be blasted are obtained and used as fixed inputs to the vibration and noise response prediction model. Blasting parameters of the area to be blasted are used as optimization variables. The blasting parameters include the charge per hole, inter-hole delay, inter-row delay, and filling length of each blast hole. The geological parameters and blasting parameters of the area to be blasted are input into the vibration and noise response prediction model, and the model outputs the corresponding blasting response parameters.

4. The method for coordinated control of vibration and noise in mine blasting according to claim 3, characterized in that: The area to be blasted is evenly divided into several grids according to a preset grid density, and the geometric center of each grid is used as a monitoring point. A three-dimensional geological model of the area to be blasted is constructed based on geological parameters. Combining the correspondence between blasting parameters and blasting response parameters, the finite element numerical simulation method is used to fit the vibration energy density and noise energy density of each monitoring point, thereby establishing the vibration energy field distribution and noise energy field distribution covering the area to be blasted. The vibration safety threshold is used as the constraint boundary for the vibration energy field distribution, and the noise safety threshold is used as the constraint boundary for the noise energy field distribution, specifically as follows: In the vibration energy field distribution, the contour lines corresponding to the vibration safety threshold are defined as vibration control boundaries. The area within the vibration control boundaries is the vibration exceedance risk zone, and the area outside the boundaries is the vibration safety zone. In the noise energy field distribution, the contour lines corresponding to the noise safety threshold are defined as noise control boundaries. The area within the noise control boundaries is the noise exceedance risk zone, and the area outside the boundaries is the noise safety zone. The spatial intersection area between the vibration exceeding the standard risk area and the noise exceeding the standard risk area is marked as the overlapping high-risk area, thereby determining the overlapping high-risk area of ​​the area to be blasted. With minimizing the area of ​​overlapping high-risk zones as the optimization objective, the blasting parameters are iteratively solved using an optimization algorithm. During the iteration process, each iteration generates a corresponding overlapping high-risk area based on the geological parameters of the area to be blasted and the current blasting parameters; Repeat the above iterative process until the area of ​​the overlapping high-risk area no longer decreases for three consecutive times, then stop the iteration and take the blasting parameters obtained at this time as the optimal blasting parameter set.

5. The method for coordinated control of vibration and noise in mine blasting according to claim 4, characterized in that: The optimal blasting parameter set is input into a pre-constructed coupled response model, which is based on the blasting energy propagation and conversion mechanism and is used to characterize the mapping relationship between blasting parameters and vibration energy and noise energy generated by blasting. The coupled response model takes the single-hole charge, inter-hole delay, inter-row delay and filling length of each borehole in the optimal blasting parameter set as input, and decomposes the total blasting energy into vibration energy components propagating in the rock medium and noise energy components propagating in the air medium through the wave field separation algorithm. The wave field separation algorithm is based on the principle of energy conservation and the propagation characteristics of the medium: First, the total charge and explosive performance parameters are obtained according to the optimal blasting parameter set to calculate the total blasting energy released at the moment of blasting; an energy distribution coefficient is introduced, which is determined by the filling length and the wave impedance of the rock mass medium. The vibration energy component and the noise energy component are determined according to the energy distribution coefficient and the total blasting energy, specifically: the vibration energy component is equal to the total blasting energy multiplied by the energy distribution coefficient, and the noise energy component is equal to the total blasting energy multiplied by one minus the energy distribution coefficient; The energy distribution coefficient is a function of the filling length and the wave impedance of the rock mass medium. The wave impedance is equal to the rock mass density multiplied by the longitudinal wave velocity. The longer the filling length, the larger the energy distribution coefficient, meaning more energy is converted into vibration energy. The shorter the filling length, the smaller the energy distribution coefficient, meaning more energy is converted into noise energy.

6. The method for coordinated control of vibration and noise in mine blasting according to claim 5, characterized in that: The vibration energy component is distributed to each borehole according to the single-hole charge ratio to obtain the vibration energy of each borehole, and then the vibration energy amplitude is obtained by energy-amplitude conversion. Similarly, the noise energy component is distributed to each borehole according to the single-hole charge ratio to obtain the noise energy of each borehole, and then the noise energy amplitude is obtained through energy-amplitude conversion; then vibration energy time history curve and noise energy time history curve are generated respectively. The vibration energy time history curve and the noise energy time history curve are respectively subjected to frequency domain transformation, and the time domain signal is converted into a frequency domain signal using fast Fourier transform to obtain the vibration energy spectrum and the noise energy spectrum. Extract the dominant vibration frequency characteristic value from the vibration energy spectrum, i.e., the frequency corresponding to the maximum amplitude of the spectrum; extract the dominant noise frequency characteristic value from the noise energy spectrum, i.e., the frequency corresponding to the maximum amplitude of the spectrum; calculate the frequency domain matching index based on the dominant vibration frequency characteristic value and the dominant noise frequency characteristic value, specifically: the frequency domain matching index is equal to the minimum value of the dominant vibration frequency characteristic value and the dominant noise frequency characteristic value divided by the maximum value; The frequency domain matching index ranges from zero to one. The closer the frequency domain matching index is to one, the closer the vibration dominant frequency characteristic value is to the noise dominant frequency characteristic value, the higher the degree of frequency domain overlap, and the greater the risk of mutual reinforcement. The closer the frequency domain matching index is to zero, the higher the degree of frequency separation between the two, and the smaller the mutual interference. If the vibration dominant frequency characteristic value is the same as the noise dominant frequency characteristic value, the minimum value is equal to the maximum value, and the frequency domain matching index is 1.

7. The method for coordinated control of vibration and noise in mine blasting according to claim 6, characterized in that: The time-domain peak shifting index is calculated based on the vibration energy time history curve and the noise energy time history curve. Specifically, the time-domain peak shifting index is the absolute time difference between the peak times of the two curves. Among them, the peak moment of the vibration energy time history curve is the time point corresponding to the maximum amplitude of the vibration energy time history curve, and the peak moment of the noise energy time history curve is the time point corresponding to the maximum amplitude of the noise energy time history curve; the larger the time domain staggered peak index, the higher the degree of time stagger between the peak vibration energy and the peak noise energy, and the smaller the risk of the two superimposed and enhanced.

8. The method for coordinated control of vibration and noise in mine blasting according to claim 7, characterized in that: Frequency domain matching index The constraints are: the frequency domain matching index is less than or equal to the preset frequency domain matching index threshold; the constraints are: the time domain peak shaving index is greater than or equal to the preset time domain peak shaving index threshold. If the frequency domain matching index is less than or equal to If the time-domain peak-shaving index is greater than or equal to the time-domain peak-shaving index threshold, then the current optimal blasting parameter set is determined to meet the collaborative control requirements, and the optimal blasting parameter set is determined as the target blasting parameter set. If the frequency domain matching index is greater than If the frequency domain matching index does not meet the requirements, the specific adjustment strategy for adjusting the optimal blasting parameter set is as follows: by changing the ratio of the inter-hole delay to the inter-row delay, the vibration main frequency and the noise main frequency will be relatively offset, increasing the frequency difference between the two, thereby reducing the frequency domain matching index until it meets the corresponding constraint conditions. If the time-domain peak shaving index is less than the time-domain peak shaving index threshold, it is determined that the time-domain peak shaving index does not meet the requirements. At this time, the specific adjustment strategy for adjusting the optimal blasting parameter set is: by changing the absolute values ​​of the inter-hole delay and the inter-row delay, the peak vibration energy and the peak noise energy are relatively offset in time, increasing the peak time difference between the two, thereby improving the time-domain peak shaving index to meet the threshold requirements. If neither the frequency domain matching index nor the time domain peak shifting index meets the threshold requirements, then both adjustment strategies mentioned above are executed simultaneously. Priority is given to ensuring that the frequency domain matching index meets the requirements before iteratively adjusting the time domain peak shifting index. After the adjustment is completed, the optimal blasting parameter set is updated and the process returns to the previous step until both the frequency domain matching index and the time domain peak shifting index meet the threshold requirements. The optimal blasting parameter set that meets the threshold requirement is taken as the target blasting parameter set, and on-site blasting operations are performed based on the target blasting parameter set.

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