A method and system for optimizing rock resonance frequency for rock breaking

Abstract

The application provides a rock resonance frequency optimization method and system for rock breaking, relates to the technical field of rock resonance frequency optimization methods, and comprises the following steps: calculating the power spectrum density of each measurement point, obtaining the average power spectrum of target rock at a scanning frequency point, setting the identification condition of the resonance frequency of the target rock by using a peak detection method, and constructing the phonon energy transmission efficiency; the optimal frequency is dynamically updated, the phonon transmission efficiency is recalculated, and adaptive frequency optimization is realized. Through adaptive weight, the efficiency bottleneck or instability risk caused by parameter solidification in the traditional method is avoided; by fusing multi-measurement point data, random noise is effectively suppressed, the dominant resonance peak is highlighted, and the robustness of the system is improved from the data level; at the same time, through the iterative update driven by the efficiency difference value, the efficiency decay problem caused by environmental changes in the traditional open-loop control is overcome; in addition, the power spectrum density is directly related to the phonon excitation strength, the energy utilization rate is quantitatively evaluated, and the universality of the method is significantly improved.

Description

Technical Field

[0001] This invention relates to the technical field of rock resonance frequency optimization methods, specifically to a rock resonance frequency optimization method and system for rock breaking. Background Technology

[0002] In rock breaking engineering, traditional rock breaking methods (such as mechanical impact, cutting, and blasting) mainly rely on forcibly applying static or impact dynamic loads exceeding the rock's strength limit. These methods suffer from inherent drawbacks such as low energy utilization, high energy consumption, significant tool wear, and a tendency to cause excessive damage or unintended breakage in non-target areas. In recent years, resonant rock breaking technology based on the rock's natural frequencies has received widespread attention. Its core idea is to apply an alternating load matching a certain resonant frequency of the rock, causing cumulative fatigue failure or localized stress concentration within the rock, thereby significantly reducing the energy input required for rock breaking. However, rock, as a complex geological body composed of multiple minerals, is heterogeneous, porous, and contains natural bedding and microfractures. Its vibration response exhibits significant nonlinearity, anisotropy, and multi-scale characteristics. Local resonant frequencies at different measurement locations (such as different points on the surface or different depth layers) often differ, and the overall "effective resonant frequency" of the rock can drift with factors such as excitation intensity, frequency scanning direction, and coupling conditions, posing significant challenges to the engineering application of resonant rock breaking.

[0003] In the prior art, patent document CN114280094A discloses a laser melting supercooled liquid jet alternating hot and cold rock breaking method. This method involves performing multiple destructive tests on the test area of ​​a rock sample using a supercooled liquid jet and a laser beam to obtain multiple test temperature information and multiple test image information at multiple points on the surface of the rock sample after multiple destructive tests. However, this method does not transform the rock breaking problem into an optimization problem of maximizing the phonon energy transmission efficiency within the rock, nor does it eliminate the interference of broad and flat pseudo-resonance peaks caused by local heterogeneity or poor coupling in the rock; moreover, it fails to achieve precise resonance control at the target rock layer. Therefore, there is an urgent need to propose an efficient and reliable rock resonance frequency optimization method and system for rock breaking to overcome the shortcomings of the aforementioned prior art.

[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 and system for optimizing rock resonance frequencies for rock breaking, 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 optimizing rock resonance frequencies for rock breaking includes the following steps: S1: Set the frequency interval, obtain the discrete scanning frequency points, evenly arrange the measurement points on the surface of the target rock, measure the vibration signal of each measurement point at the scanning frequency point, and normalize the vibration signal of each measurement point. S2: Perform a fast Fourier transform on the vibration signal of the normalized measurement point to obtain the amplitude spectrum of each measurement point, and calculate the power spectral density of each measurement point based on the amplitude spectrum. Average the power spectral density of all measurement points to obtain the average power spectrum of the target rock at the scanning frequency point to highlight the dominant resonance peaks of each layer of the target rock. The peak region of the power spectrum corresponds to the phonon density region, and the amplitude of the peak corresponds to the excitation intensity of the phonons. S3: The peak detection method is used to set the identification conditions of the resonance frequency of the target rock, and the scanning frequency points that meet the identification conditions are screened. The bandwidth sharpness method is used to construct the quality factor under each scanning frequency point. The obtained quality factor is multiplied with the average power spectrum, and the maximum value of the result is taken to obtain the optimal resonance frequency, thus completing the regulation of the resonance frequency of the target rock layer. S4: Based on the optimal resonance frequency, calculate the optimal average power spectrum of the rock at the optimal resonance frequency, divide the optimal average power spectrum by the maximum average power spectrum of the target rock at each scanning frequency point, and construct the phonon energy transfer efficiency. S5: Calculate the difference between the preset ideal energy transmission efficiency and the phonon energy transmission efficiency. When the difference is greater than 0, construct the weighting ratio coefficient of the average power spectrum, dynamically update the optimal frequency, and recalculate the phonon transmission efficiency until the difference is less than 0, thus achieving rock breaking.

[0007] Furthermore, the specific steps for acquiring the vibration signal at each measurement point are as follows: Set the starting frequency, ending frequency, and frequency step size for scanning. Starting from the starting frequency, increment the step size each time to generate the next frequency point sequentially until the ending frequency is reached. Number each discrete frequency point sequentially to obtain discrete scanning frequency points. Distribute a preset number of measurement points evenly on the surface of the target rock and measure the vibration signal of each measurement point at the scanning frequency point. Normalize the vibration signal of each measurement point.

[0008] Further, the amplitude spectrum of each measurement point is obtained, and the specific steps are as follows: The specific steps for obtaining the amplitude spectrum at each measurement point include: At each scanning frequency point, the normalized vibration signals acquired at each measurement point are used to form a discrete sampling sequence according to the sampling order; A fast Fourier transform is performed on each discrete sampling sequence to convert the time-domain vibration response into a frequency-domain vibration response; Read the amplitude information corresponding to each frequency component after transformation to obtain the amplitude spectrum of each measurement point at the corresponding scanning frequency point.

[0009] Furthermore, the average power spectrum of the target rock at the scanning frequency point is obtained, and the specific steps are as follows: Based on the amplitude spectrum of each measurement point at each scanning frequency point, the power spectral density corresponding to each measurement point is calculated respectively. The power spectral density of each measurement point is organized according to the scanning frequency point; The power spectral density of all measurement points at the same scanning frequency is averaged to obtain the average power spectrum of the target rock at that scanning frequency.

[0010] Further, the scanning frequency points that meet the recognition criteria are selected, and the specific steps are as follows: The specific steps for selecting scanning frequency points that meet the recognition criteria include: The average power spectrum is compared point by point according to the order of the scanning frequency points; When the average power spectrum corresponding to the current scanning frequency point is greater than the average power spectrum corresponding to its left and right adjacent scanning frequency points, and is also greater than the preset average power spectrum threshold, the current scanning frequency point is determined as a candidate resonance frequency point that meets the identification conditions. All candidate resonance frequency points are used to form a candidate resonance frequency set.

[0011] Furthermore, to obtain the optimal resonance frequency, the specific steps are as follows: Taking the resonance peaks corresponding to each candidate resonance frequency point as the analysis object, determine the left and right frequencies corresponding to half of the peak value of the resonance peak; The quality factor of the corresponding candidate resonant frequency point is constructed based on the bandwidth between the right frequency and the left frequency. The smaller the bandwidth, the higher the corresponding quality factor. The quality factor of each candidate resonance frequency point is evaluated in combination with the corresponding average power spectrum. The candidate resonance frequency with the largest combined evaluation result is determined as the optimal resonance frequency.

[0012] Furthermore, the phonon energy transfer efficiency is constructed through the following steps: The optimal resonance frequency is used as the updated scanning frequency point, and the vibration signal acquisition process of claim 2 is executed again. Based on the reacquired vibration signal, the average power spectrum corresponding to the optimal resonance frequency is calculated according to the methods of claims 3 and 4. The phonon energy transfer efficiency is obtained by comparing the average power spectrum corresponding to the optimal resonance frequency with the maximum value of the average power spectrum corresponding to all scanned frequency points.

[0013] Furthermore, the optimal frequency is dynamically updated until it exceeds the ideal energy transfer efficiency. The specific steps are as follows: Calculate the difference between the phonon energy transfer efficiency and the preset ideal energy transfer efficiency; When the phonon energy transmission efficiency is lower than the preset ideal energy transmission efficiency, the weight ratio of the average power spectrum and quality factor in the combined evaluation is dynamically adjusted according to the difference, and the optimal frequency is recalculated based on the adjusted weight ratio. The steps of claims 2 to 7 are re-executed using the updated optimal frequency to re-obtain the phonon energy transfer efficiency. Repeat the above update process until the phonon energy transfer efficiency reaches or exceeds the preset ideal energy transfer efficiency. After the phonon energy transmission efficiency reaches or exceeds the preset ideal energy transmission efficiency, the updated optimal frequency is maintained to apply vibration excitation to the target rock in order to achieve rock breaking.

[0014] The present invention also provides a rock resonance frequency optimization system for rock breaking, the optimization system being used to perform the above-described optimization method, comprising: The data acquisition module is used to set the frequency interval, acquire discrete scanning frequency points, uniformly arrange measurement points on the surface of the target rock, measure the vibration signal of each measurement point at the scanning frequency point, and normalize the vibration signal of each measurement point. The intensity calculation module is used to perform a fast Fourier transform on the vibration signal of the normalized measurement point to obtain the amplitude spectrum of each measurement point. Based on the amplitude spectrum, the power spectral density of each measurement point is calculated. The power spectral density of all measurement points is averaged to obtain the average power spectrum of the target rock at the scanning frequency point, which is used to highlight the dominant resonance peaks of each layer of the target rock. The peak region of the power spectrum corresponds to the phonon density region, and the amplitude of the peak corresponds to the excitation intensity of the phonons. The frequency extraction module is used to set the identification conditions of the resonance frequency of the target rock using the peak detection method, screen the scanning frequency points that meet the identification conditions, construct the quality factor under each scanning frequency point using the bandwidth sharpness method, multiply the obtained quality factor with the average power spectrum, take the maximum value of the result, obtain the optimal resonance frequency, and complete the regulation of the resonance frequency of the target rock layer. The transmission evaluation module is used to calculate the optimal average power spectrum of the rock at the optimal resonance frequency based on the optimal resonance frequency. The optimal average power spectrum is divided by the maximum average power spectrum of the target rock at each scanning frequency point to construct the phonon energy transmission efficiency. The efficiency optimization module is used to calculate the difference between the preset ideal energy transmission efficiency and the phonon energy transmission efficiency. When the difference is greater than 0, the weight ratio coefficient of the average power spectrum is constructed, the optimal frequency is dynamically updated, and the phonon transmission efficiency is recalculated until the difference is less than 0, thus achieving rock breaking.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This scheme introduces the average power spectrum as a comprehensive measure of the overall vibration intensity of the rock and its various layers. The peak region of the power spectrum directly corresponds to the phonon density region, and the peak amplitude corresponds to the phonon excitation intensity. This transforms the rock-breaking problem into an optimization problem of maximizing the phonon energy transmission efficiency within the rock, fundamentally overcoming the limitations of traditional methods that rely solely on the amplitude of a single measurement point to determine the resonance frequency. Furthermore, the scheme employs the bandwidth sharpness method to construct a quality factor, incorporating the sharpness of the resonance peak into the optimal frequency evaluation index. This effectively eliminates interference from broad and flat pseudo-resonance peaks caused by local heterogeneity or poor coupling in the rock. By multiplying the quality factor by the average power spectrum and taking the maximum value, the scheme ensures that the selected optimal resonance frequency possesses both strong overall vibration excitation capability and high energy concentration characteristics, thereby achieving precise resonance control of the target rock layer. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2 A graph showing the relationship between the difference between the phonon energy transfer efficiency and the preset ideal energy transfer efficiency and the weighting coefficient of the average power spectrum. Figure 3 This is a schematic diagram of the overall system of the present invention. 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 Figures 1-2 The present invention provides a technical solution: A method for optimizing rock resonance frequencies for rock breaking includes the following steps: S1: Set the frequency interval, obtain the discrete scanning frequency points, evenly arrange the measurement points on the surface of the target rock, measure the vibration signal of each measurement point at the scanning frequency point, and normalize the vibration signal of each measurement point. The specific steps for acquiring the vibration signal at each measurement point are as follows: Set the starting frequency, ending frequency, and frequency step size for scanning. Starting from the starting frequency, increment the step size each time to generate the next frequency point sequentially until the ending frequency is reached. Number each discrete frequency point sequentially to obtain discrete scanning frequency points. Distribute a preset number of measurement points evenly on the surface of the target rock and measure the vibration signal of each measurement point at the scanning frequency point. Normalize the vibration signal of each measurement point.

[0020] In the above process, the discrete scanning frequency points are generated by increasing the step size from the starting frequency to the ending frequency in a fixed manner. This is to systematically cover the frequency range in which the target rock may resonate, avoiding the omission of sharp resonance peaks due to excessively wide frequency intervals or the increase of unnecessary data acquisition burden due to excessively close intervals. The predetermined number of measurement points are evenly distributed on the surface of the target rock to obtain the overall vibration response information of the rock in spatial distribution, so as to overcome the response differences at different locations caused by the heterogeneity of the rock—a single measurement point cannot represent the overall resonance behavior of the rock. The vibration signal of each measurement point is normalized to eliminate the dimensional and scale effects caused by differences in sensor sensitivity, different coupling conditions, or inconsistent signal amplitude baselines at each measurement point. This ensures that subsequent Fourier transforms, power spectral density calculations, and averaging of vibration energy at different measurement points and frequencies under the same reference are comparable and physically consistent. The preset number of measurement points is mainly determined based on the size and geometry of the target rock, the estimated degree of heterogeneity, and the order of the resonance modes to be identified. For small-sized (e.g., side length less than 0.5 m) and relatively homogeneous rock samples, 5 to 9 measurement points are usually sufficient to effectively capture the main vibration modes. For large-sized (e.g., side length exceeding 1 m) or rocks with obvious bedding, fissures, or anisotropy, the number of measurement points needs to be increased to more than 20, and arranged in a grid pattern (e.g., equally spaced rows and columns) or a circularly divided manner to ensure that every possible vibration midpoint and nodal area is covered by measurement points. The starting frequency is typically set to a value far removed from the lowest rigid body mode of the rock or the lowest effective output frequency of the equipment, such as 5–20 Hz, to avoid interference from environmental vibrations in the low-frequency band or insufficient exciter output. The ending frequency is determined based on the highest mode of interest corresponding to the minimum expected structural size of the rock, generally taking 2–3 times the longitudinal or transverse wave velocity of the rock divided by the minimum characteristic size as the upper limit (for example, for granite on the meter scale, the ending frequency is often set to 500–2000 Hz). The selection of the frequency step size follows the Nyquist sampling theorem and the resonance peak resolution criterion: the step size should be at least 1 / 3 to 1 / 5 of the full width at half maximum (FWHM) of the expected sharpest resonance peak to ensure that the peak point of the resonance peak can be effectively captured without peak omission or amplitude underestimation caused by frequency undersampling.

[0021] S2: Perform a fast Fourier transform on the vibration signal of the normalized measurement point to obtain the amplitude spectrum of each measurement point, and calculate the power spectral density of each measurement point based on the amplitude spectrum. Average the power spectral density of all measurement points to obtain the average power spectrum of the target rock at the scanning frequency point to highlight the dominant resonance peaks of each layer of the target rock. The peak region of the power spectrum corresponds to the phonon density region, and the amplitude of the peak corresponds to the excitation intensity of the phonons. The specific steps for obtaining the amplitude spectrum of each measurement point are as follows: At each scanning frequency point, the normalized vibration signals acquired at each measurement point are used to form a discrete sampling sequence according to the sampling order; A fast Fourier transform is performed on each discrete sampling sequence to convert the time-domain vibration response into a frequency-domain vibration response; Read the amplitude information corresponding to each frequency component after transformation to obtain the amplitude spectrum of each measurement point at the corresponding scanning frequency point.

[0022] The formula upon which the above process is based is: in, Indicates the first Each measurement point at the scanning frequency point The amplitude spectrum below; This indicates the total number of sampling points for the signal; Indicates the index number of time-domain sampling points; Indicates the first Among the measurement points, the th measurement point after performing a fast Fourier transform One sampling point; Indicates the first Each scanning frequency point.

[0023] The reason for this approach is that the normalized vibration signals acquired at each measurement point exhibit complex waveforms that change over time in the time domain, failing to directly reveal the distribution characteristics of vibration energy at different frequency components. Therefore, it is necessary to organize them into a discrete sampling sequence according to the sampling order, and then convert the time-domain vibration response into a frequency-domain vibration response using a Fast Fourier Transform (FFT). The FFT can efficiently decompose the time-domain signal into a series of sinusoidal components of different frequencies, where the amplitude of each frequency component directly reflects its contribution to the original vibration signal. By reading the amplitude information corresponding to each frequency component after the transformation, the amplitude spectrum of each measurement point at the corresponding scanning frequency can be obtained. The core advantage of this conversion is that resonance phenomena, which are difficult to distinguish in the time domain, will appear as obvious peaks in the amplitude spectrum in the frequency domain, thus providing quantitative frequency-domain characteristic parameters for subsequent calculations of power spectral density, identification of dominant resonance peaks, and construction of quality factors.

[0024] The specific steps for obtaining the average power spectrum of the target rock at the scanning frequency point are as follows: Based on the amplitude spectrum of each measurement point at each scanning frequency point, the power spectral density corresponding to each measurement point is calculated respectively. The power spectral density of each measurement point is organized according to the scanning frequency point; The power spectral density of all measurement points at the same scanning frequency is averaged to obtain the average power spectrum of the target rock at that scanning frequency.

[0025] The formula upon which the above process is based is: in, Indicates the first Each measurement point at the scanning frequency point Power spectral density at the following values; In the above process, based on the amplitude spectrum of each measurement point at each scanning frequency, the power spectral density of each measurement point is calculated. This is because the amplitude spectrum only gives the magnitude of the vibration signal at different frequency components, while the amplitude itself cannot directly reflect the intensity of the vibration energy distribution in the frequency domain. The power spectral density is calculated by squaring the amplitude and dividing by the number of sampling points. This method converts the amplitude dimension into the energy dimension, thereby quantitatively characterizing the vibrational energy carried by each frequency component. Physically, this formula is equivalent to "energy normalization" of the signal, allowing for comparison of vibrational energy at different scanning frequencies and measurement points on a unified energy scale. Using power spectral density instead of directly using the amplitude spectrum eliminates potential energy scaling differences introduced by varying the number of sampling points in the Fourier transform, ensuring that the average power spectrum obtained through subsequent averaging has a clear physical meaning—that is, the vibrational energy density received at a specific location on the rock surface within a unit frequency width.

[0026] The formula upon which the above process is based is: in, Indicates the target rock at the scanning frequency point The average power spectrum is given below. The peak region of the average power spectrum corresponds to the phonon density region, and the magnitude of the peak corresponds to the excitation intensity of the phonons.

[0027] In the above process, the power spectral density of each measurement point is sorted according to the scanning frequency point, and the power spectral density of all measurement points at the same scanning frequency point is averaged. This is because the heterogeneity and anisotropy of the rock cause significant differences in the local vibration energy generated by different measurement points at the same scanning frequency point. That is, some measurement points may be located at the resonance antinode and have a strong response, while other measurement points may be located at the nodal point and have a weak response. If the power spectral density of a single measurement point is directly used to represent the resonance characteristics of the entire rock, it is very easy to make misleading judgments due to improper selection of measurement point location. By arithmetically averaging the power spectral density of all measurement points, the influence of local anomalous responses can be effectively suppressed, highlighting the dominant vibration modes common to the overall rock structure and its various layers. Within this framework, the peak region of the average power spectrum corresponds to the frequency range where phonons are most densely distributed spatially within the rock, i.e., the frequency band with a high phonon state density. The amplitude of the peak directly corresponds to the intensity of phonon excitation by external excitation. A higher amplitude indicates that more phonons participate in coherent vibration within the rock at that frequency, and the more easily energy can form global resonance propagation within the rock. Therefore, the average power spectrum is the core basis for subsequent screening of dominant resonance peaks and construction of quality factors.

[0028] S3: The peak detection method is used to set the identification conditions of the resonance frequency of the target rock, and the scanning frequency points that meet the identification conditions are screened. The bandwidth sharpness method is used to construct the quality factor under each scanning frequency point. The obtained quality factor is multiplied with the average power spectrum, and the maximum value of the result is taken to obtain the optimal resonance frequency, thus completing the regulation of the resonance frequency of the target rock layer. The specific steps for selecting scanning frequency points that meet the recognition criteria are as follows: The average power spectrum is compared point by point according to the order of the scanning frequency points; When the average power spectrum corresponding to the current scanning frequency point is greater than the average power spectrum corresponding to its left and right adjacent scanning frequency points, and is also greater than the preset average power spectrum threshold, the current scanning frequency point is determined as a candidate resonance frequency point that meets the identification conditions. All candidate resonance frequency points are used to form a candidate resonance frequency set.

[0029] The formula upon which the above process is based is: in, This represents the set of scan frequency points of rocks that meet the identification criteria; This indicates the preset average power spectrum threshold.

[0030] The reason for this processing in the above process is that the average power spectrum The frequency-dependent curve is not smooth and monotonic, but rather superimposed with various local fluctuations caused by rock heterogeneity, environmental noise, and measurement errors. Directly calculating the quality factor and searching for the optimal frequency for all scanned frequency points would not only be computationally intensive but also prone to misidentifying random fluctuations caused by noise or broad, flat pseudo-resonance peaks as dominant resonance peaks. By comparing the average power spectrum point-by-point according to the order of the scanned frequency points and using a peak detection method to set identification conditions—that is, requiring the average power spectrum of the current scanned frequency point to be simultaneously greater than the average power spectra of its left and right adjacent scanned frequency points—it is ensured that this point is a local maximum and exceeds a preset average power spectrum threshold. This means ensuring that the vibrational energy corresponding to the point is significant enough to limit the candidate resonance frequency points to those physical resonance peaks that truly satisfy the condition of "locally strongest and energy meeting the standard," thereby constructing a set of candidate resonance frequencies. This process is essentially a feature selection strategy based on frequency domain morphology. Its core advantage is that it can efficiently eliminate a large number of non-resonant fluctuations through simple numerical comparisons, while significantly reducing the risk of misselecting noise spurious peaks or coupled parasitic resonances as the optimal resonance frequency. Preset average power spectrum threshold The determination of the frequency spectrum requires a comprehensive consideration of the background vibration and noise level of the rock, the statistical distribution characteristics of the average power spectrum at all scanning frequency points in the frequency sweep test, and the minimum energy injection requirement for rock breaking. The determination method involves conducting a pre-test without excitation or with only extremely low amplitude excitation before the formal frequency sweep, calculating the root mean square value or median of the average power spectrum at each scanning frequency point, and then... The value is set to 3 to 5 times this statistical value to ensure that only energy peaks significantly higher than the background noise are included in the candidate resonant frequency set.

[0031] The specific steps for obtaining the optimal resonance frequency are as follows: Taking the resonance peaks corresponding to each candidate resonance frequency point as the analysis object, determine the left and right frequencies corresponding to half of the peak value of the resonance peak; The quality factor of the corresponding candidate resonant frequency point is constructed based on the bandwidth between the right frequency and the left frequency. The smaller the bandwidth, the higher the corresponding quality factor. The quality factor of each candidate resonance frequency point is evaluated in combination with the corresponding average power spectrum. The candidate resonance frequency with the largest combined evaluation result is determined as the optimal resonance frequency.

[0032] The formula upon which the above process is based is: in, in, Indicates the target rock at the scanning frequency point The quality factor below; Indicates bandwidth; This represents the left-hand frequency corresponding to half of the maximum power spectral density; This represents the right-hand frequency corresponding to half of the maximum power spectral density. In the above process, the resonance peaks corresponding to each candidate resonance frequency point are taken as the analysis object, and the left-hand frequency corresponding to half of the peak value of the resonance peak is determined. and right-side frequency Then, based on the bandwidth between the right and left frequencies... Constructing quality factors This is because the width of the resonance peak directly reflects the energy dissipation characteristics of the rock vibration system. In vibration theory, the quality factor... It is a dimensionless parameter that measures the sharpness of resonance peaks: The smaller the value, the narrower the resonance peak, the higher the concentration of energy near the resonance frequency, the stronger the coherence between phonons inside the rock, the longer the vibrational energy is maintained in the rock, and the slower the rate of dissipation. Conversely, a larger value indicates a narrower resonance peak, a higher degree of energy concentration near the resonance frequency, stronger coherence between phonons inside the rock, a longer duration of vibrational energy retention within the rock, and a slower rate of dissipation. A higher value indicates stronger system damping, meaning energy is easily dissipated through the pores, micro-cracks, or internal friction of the rock, making it impossible to form a sustained, efficient resonance. Calculating the quality factor for each candidate resonance frequency point using the bandwidth sharpness method essentially provides a quantitative evaluation of the "energy retention capability" of each resonance peak.

[0033] The obtained quality factor is multiplied by the average power spectrum, and the maximum value of the result is taken to obtain the optimal resonance frequency, thus completing the regulation of the resonance frequency of the target rock layer: in, This represents the optimal resonant frequency.

[0034] The quality factors obtained in the above process and the corresponding average power spectrum Multiply the results and determine the candidate resonance frequency that yields the largest combined evaluation result as the optimal resonance frequency. This is because the average power spectrum alone has significant limitations as an evaluation metric: a resonance peak may have very high power. (i.e., high phonon excitation intensity), but if its A wide frequency range indicates that the energy in this resonance mode is dispersed over a broad frequency band, and the actual phonon energy density injected into the rock is not high, making it difficult to form long-distance coherent propagation within the rock; conversely, a single resonance peak may have extremely high energy density. Worth it, but A low value indicates that although the energy accumulation characteristics are excellent, the overall excitation intensity is insufficient, making it ineffective for rock breaking. Multiplying the two values ​​essentially employs a product coupling strategy to simultaneously optimize the "excitation intensity" (from...). Characterization) and "energy accumulation persistence" (by (Characteristics) These two indicators will only have a significantly larger product than other candidate frequencies when a candidate frequency simultaneously possesses both high phonon excitation intensity and narrow resonance peak width. The optimal resonance frequency selected in this way... It can ensure that in subsequent rock-breaking stimulation, the input energy can not only strongly excite the dominant resonant modes of each layer of the rock, but also penetrate into the entire volume of the rock in the form of a low-dissipation, high-density phonon flow.

[0035] S4: Based on the optimal resonance frequency, calculate the optimal average power spectrum of the rock at the optimal resonance frequency, divide the optimal average power spectrum by the maximum average power spectrum of the target rock at each scanning frequency point, and construct the phonon energy transfer efficiency. The specific steps for constructing phonon energy transfer efficiency are as follows: The optimal resonance frequency is used as the updated scanning frequency point, and the vibration signal acquisition process of claim 2 is executed again. Based on the reacquired vibration signal, the average power spectrum corresponding to the optimal resonance frequency is calculated according to the methods of claims 3 and 4. The phonon energy transfer efficiency is obtained by comparing the average power spectrum corresponding to the optimal resonance frequency with the maximum value of the average power spectrum corresponding to all scanned frequency points.

[0036] The formula upon which the above process is based is: in, Indicates in The optimal average power spectrum under these conditions; This indicates the phonon energy transfer efficiency.

[0037] In the above process, the optimal resonant frequency will be determined. Using the updated scanning frequency point, the vibration signal acquisition process is re-executed, and the optimal average power spectrum at that frequency point is calculated. Instead of directly using the power spectrum data of that frequency point obtained during the initial frequency sweep, this is because the residence time of the excitation signal at each scan frequency point during the initial frequency sweep is usually short (generally on the order of milliseconds to seconds). The purpose is to complete a coarse scan of the entire frequency band within a limited time to identify the location of candidate resonance peaks. When locked... Subsequently, a long-term, high-precision specialized acquisition of this single frequency point is required: extending the excitation dwell time, increasing the sampling rate, or increasing the number of repeated measurements to obtain a statistically more stable, lower-noise, and more closely approximate average power spectrum of the rock's true steady-state response. Furthermore, the reacquisition process can simultaneously adjust the excitation amplitude to the engineering strength required for actual rock breaking (the initial frequency sweep often uses a low-amplitude excitation to avoid damaging the rock), thus... It can accurately reflect the phonon excitation capability of rocks at this resonance frequency under high energy input conditions, providing high-fidelity molecular data for subsequent calculation of phonon energy transfer efficiency; The optimal average power spectrum Maximum average power spectrum of the target rock at various scanning frequencies The ratio is processed to obtain the phonon energy transfer efficiency. Its physical essence is to normalize the phonon excitation intensity achieved at the actually selected optimal resonance frequency relative to the strongest phonon excitation intensity theoretically achievable across the entire frequency band; where, the denominator This represents the maximum overall vibrational energy response that a rock can produce at a certain frequency point within the initial frequency sweep range—this frequency point usually corresponds to a certain dominant resonance mode of the rock, but due to the resonance peak width of this mode, This could significantly lead to a low quality factor, and may not be the optimal operating frequency for rock breaking. (Molecular) This is after step S3 The actual phonon excitation intensity corresponding to the optimal frequency obtained after screening using the product maximization criterion. Therefore, Essentially, this reflects "the percentage of energy excitation efficiency achievable at the selected optimal frequency relative to the globally optimal excitation efficiency, while also considering the persistence of energy accumulation." The closer this ratio is to 100%, the better. In meeting high While maintaining the value constraint, there is almost no sacrifice in excitation intensity; if the ratio is too low, it means that more excitation intensity has been sacrificed in order to obtain a higher quality factor. In this case, it is necessary to rebalance the two through the dynamic weight adjustment in the subsequent step S5.

[0038] S5: Calculate the difference between the preset ideal energy transmission efficiency and the phonon energy transmission efficiency. When the difference is greater than 0, construct the weighting ratio coefficient of the average power spectrum, dynamically update the optimal frequency, and recalculate the phonon transmission efficiency until the difference is less than 0, thus achieving rock breaking.

[0039] The specific steps for dynamically updating the optimal frequency until it exceeds the ideal energy transfer efficiency are as follows: Calculate the difference between the phonon energy transfer efficiency and the preset ideal energy transfer efficiency; When the phonon energy transmission efficiency is lower than the preset ideal energy transmission efficiency, the weight ratio of the average power spectrum and quality factor in the combined evaluation is dynamically adjusted according to the difference, and the optimal frequency is recalculated based on the adjusted weight ratio. The steps of claims 2 to 7 are re-executed using the updated optimal frequency to re-obtain the phonon energy transfer efficiency. Repeat the above update process until the phonon energy transfer efficiency reaches or exceeds the preset ideal energy transfer efficiency. After the phonon energy transmission efficiency reaches or exceeds the preset ideal energy transmission efficiency, the updated optimal frequency is maintained to apply vibration excitation to the target rock in order to achieve rock breaking.

[0040] The formula upon which the above process is based is: in, This represents the difference between the phonon energy transfer efficiency and the preset ideal energy transfer efficiency. This represents the ideal energy transfer efficiency; The weighting coefficients representing the average power spectrum; In the above process, the dependent variable The weighting coefficients representing the average power spectrum are used to quantitatively allocate the average power spectrum during the dynamic update process in step S5. With quality factor Recalculate the optimal resonance frequency The relative importance of time. The magnitude of the value directly determines the bias strategy of the combined evaluation: when When the value is large (approaching 0.5), the weight of the average power spectrum is significantly increased, and the system focuses more on finding candidate frequencies with high phonon excitation intensity when searching for the optimal frequency; when When the value is small (close to 0), the weight of the quality factor dominates, and the system prioritizes the frequency points with sharp resonance peaks and good energy concentration persistence. Independent variable Indicates phonon energy transfer efficiency Compared with the preset ideal energy transfer efficiency The difference between them, the sign and magnitude of which reflect the currently selected optimal resonant frequency. The degree of deviation between the actual energy transfer capacity and the expected engineering goals. The reason why it can influence The physical reason is that: when far below (Right now When the value is large and positive, it indicates that although the current optimal frequency passed the test in step S3... The product maximization criterion was used for selection, but its actual phonon excitation intensity was relative to the maximum average power spectrum across the entire frequency band. However, excessive sacrifice leads to substandard transmission efficiency. In this case, the system needs to significantly reduce its emphasis on excitation intensity and relatively increase its requirements for sustained energy accumulation. The value should be larger to restore the weight of the average power spectrum; conversely, when... Only slightly lower (Right now When the value is a small positive value, it indicates that the current frequency is close to the ideal state, and only minor adjustments to the quality factor are needed to achieve the target. The value should be small so that the search is dominated by the quality factor. and There is a positive correlation between them: The larger, The larger; When it approaches 0, Approaching 0; The formula uses the hyperbolic tangent function. As a core form of mathematics, its rationality is reflected in the following three aspects: First, The range of the function is After scaling by a factor of 0.5, The theoretical range of values ​​is However, due to the actual application scenarios exist Below The time is a positive number, therefore The actual range of values ​​is limited to This precisely satisfies the physical constraint that the weighting coefficient must be non-negative and not exceed 0.5, because the weight of the quality factor is... First, it must be ensured that it is non-negative. Second, The function has a smooth S-shaped curve characteristic and can achieve... Follow The transition from 0 to a larger value is a continuous one, gradually approaching 0.5. This avoids the problems of weight abrupt changes and discontinuous optimal frequency jumps that may occur when using piecewise functions or step functions, thus ensuring the numerical stability of the iterative update process. Thirdly, the independent variables are introduced... The denominator is then subjected to dimensionless normalization. , making The sensitivity can be adjusted according to the preset ideal energy transfer efficiency. Absolute value autoscaling - when At higher levels, the same absolute difference The corresponding relative ratio is smaller, and the weight adjustment range is also reduced accordingly, reflecting the system's cautious adjustment logic for high expected targets; when When the value is low, the adjustment range is relatively larger, reflecting the need for rapid convergence to low-expectation targets; The energy efficiency can be dynamically set according to the energy efficiency requirements of the rock-breaking task: if the project requires rapid rock breaking but allows for higher energy consumption, the energy efficiency can be adjusted accordingly. Setting it to a lower level of 60%–70% allows the system to converge quickly to a feasible solution; if the engineering goal is to achieve extreme energy efficiency and low tool wear, then... Setting the energy level at a high level of 85% to 95% forces the system to iterate multiple times to approach the optimal energy matching state.

[0041] The updated formula for calculating the optimal frequency is: Based on the updated optimal frequency, recalculate in The optimal average power spectrum under the condition, until Greater than This enables rock breaking.

[0042] Ultimately, when When the conditions are met and maintained, the vibration excitation output by the system can inject phonon energy into the rock with near-theoretical efficiency, enabling the rock to achieve rapid and controllable fatigue fracture with low input power, thereby achieving the overall invention objective of reducing energy consumption, reducing tool wear, and increasing rock breaking rate.

[0043] In the above embodiments, 20 sets of data are provided regarding the difference between the phonon energy transfer efficiency and the preset ideal energy transfer efficiency, and the weighting coefficient of the average power spectrum, to reflect how the weighting coefficient of the average power spectrum changes with the difference, as shown in Table 1: Table 1: Relationship between the difference between phonon energy transfer efficiency and the preset ideal energy transfer efficiency and the weighting coefficient of the average power spectrum. From Table 1 above, a preset ideal energy transfer efficiency is set. It can be seen that the weighting coefficient of the average power spectrum The difference between the phonon energy transfer efficiency and the preset ideal energy transfer efficiency The value increases monotonically with increasing , exhibiting a non-linear positive correlation: when When the concentration is relatively low (e.g., 0.1% to 8%), The growth is slow, gradually increasing from 0.001 to 0.050, reflecting that the system prioritizes the quality factor in searching for the optimal resonant frequency within this range; when When the increase reaches 10%–30%, The acceleration to 0.174 indicates that with the actual phonon energy transfer efficiency... As the deviation from the ideal value widens, the system begins to significantly increase the weight of the average power spectrum to restore focus on the excitation intensity; when When further increased to 40%–80%, It continued to increase to 0.348, but the growth slope gradually slowed down, reflecting the saturation characteristic of the hyperbolic tangent function—even though... As the weighting coefficients increase exponentially, the adjustment range also tends to be gradual, avoiding system instability due to over-adjustment. Overall, the weighting coefficients remain within the range of 0 to 0.5, and as... From 0.1% to 80%, The value monotonically increased from near 0 to approximately 0.348, achieving a smooth transition from "quality factor dominance" to "balance between average power spectrum and quality factor".

[0044] Please see Figure 3 The present invention also provides a rock resonance frequency optimization system for rock breaking, the optimization system being used to perform the above-described optimization method, comprising: The data acquisition module is used to set the frequency interval, acquire discrete scanning frequency points, uniformly arrange measurement points on the surface of the target rock, measure the vibration signal of each measurement point at the scanning frequency point, and normalize the vibration signal of each measurement point. The intensity calculation module is used to perform a fast Fourier transform on the vibration signal of the normalized measurement point to obtain the amplitude spectrum of each measurement point. Based on the amplitude spectrum, the power spectral density of each measurement point is calculated. The power spectral density of all measurement points is averaged to obtain the average power spectrum of the target rock at the scanning frequency point, which is used to highlight the dominant resonance peaks of each layer of the target rock. The peak region of the power spectrum corresponds to the phonon density region, and the amplitude of the peak corresponds to the excitation intensity of the phonons. The frequency extraction module is used to set the identification conditions of the resonance frequency of the target rock using the peak detection method, screen the scanning frequency points that meet the identification conditions, construct the quality factor under each scanning frequency point using the bandwidth sharpness method, multiply the obtained quality factor with the average power spectrum, take the maximum value of the result, obtain the optimal resonance frequency, and complete the regulation of the resonance frequency of the target rock layer. The transmission evaluation module is used to calculate the optimal average power spectrum of the rock at the optimal resonance frequency based on the optimal resonance frequency. The optimal average power spectrum is divided by the maximum average power spectrum of the target rock at each scanning frequency point to construct the phonon energy transmission efficiency. The efficiency optimization module is used to calculate the difference between the preset ideal energy transmission efficiency and the phonon energy transmission efficiency. When the difference is greater than 0, the weight ratio coefficient of the average power spectrum is constructed, the optimal frequency is dynamically updated, and the phonon transmission efficiency is recalculated until the difference is less than 0, thus achieving rock breaking.

[0045] 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.

[0046] 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 according to actual needs.

[0047] 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 optimizing the resonant frequency of rock for rock breaking, characterized by the following steps: include: S1: Set the frequency interval, obtain discrete scanning frequency points, evenly arrange measurement points on the surface of the target rock, measure the vibration signal of each measurement point at the scanning frequency point, and normalize the vibration signal of each measurement point. S2: Perform a fast Fourier transform on the vibration signal of the normalized measurement point to obtain the amplitude spectrum of each measurement point, and calculate the power spectral density of each measurement point based on the amplitude spectrum. Average the power spectral density of all measurement points to obtain the average power spectrum of the target rock at the scanning frequency point to highlight the dominant resonance peaks of each layer of the target rock. The peak region of the power spectrum corresponds to the phonon density region, and the amplitude of the peak corresponds to the excitation intensity of the phonons. S3: The peak detection method is used to set the identification conditions of the resonance frequency of the target rock, and the scanning frequency points that meet the identification conditions are screened. The bandwidth sharpness method is used to construct the quality factor under each scanning frequency point. The obtained quality factor is multiplied with the average power spectrum, and the maximum value of the result is taken to obtain the optimal resonance frequency, thus completing the regulation of the resonance frequency of the target rock layer. S4: Based on the optimal resonance frequency, calculate the optimal average power spectrum of the rock at the optimal resonance frequency, divide the optimal average power spectrum by the maximum average power spectrum of the target rock at each scanning frequency point, and construct the phonon energy transfer efficiency. S5: Calculate the difference between the preset ideal energy transmission efficiency and the phonon energy transmission efficiency. When the difference is greater than 0, construct the weighting ratio coefficient of the average power spectrum, dynamically update the optimal frequency, and recalculate the phonon transmission efficiency until the difference is less than 0, thus achieving rock breaking.

2. The method for optimizing rock resonance frequency for rock breaking according to claim 1, characterized in that, The specific steps for acquiring the vibration signal at each measurement point are as follows: Set the starting frequency, ending frequency, and frequency step size for scanning. Starting from the starting frequency, increment the step size each time to generate the next frequency point sequentially until the ending frequency is reached. Number each discrete frequency point sequentially to obtain discrete scanning frequency points. Distribute a preset number of measurement points evenly on the surface of the target rock and measure the vibration signal of each measurement point at the scanning frequency point. Normalize the vibration signal of each measurement point.

3. The method for optimizing rock resonance frequency for rock breaking according to claim 2, characterized in that, The specific steps for obtaining the amplitude spectrum of each measurement point are as follows: At each scanning frequency point, the normalized vibration signals acquired at each measurement point are used to form a discrete sampling sequence according to the sampling order; A fast Fourier transform is performed on each discrete sampling sequence to convert the time-domain vibration response into a frequency-domain vibration response; Read the amplitude information corresponding to each frequency component after transformation to obtain the amplitude spectrum of each measurement point at the corresponding scanning frequency point.

4. The method for optimizing rock resonance frequency for rock breaking according to claim 1, characterized in that, The specific steps for obtaining the average power spectrum of the target rock at the scanning frequency point are as follows: Based on the amplitude spectrum of each measurement point at each scanning frequency point, the power spectral density corresponding to each measurement point is calculated respectively. The power spectral density of each measurement point is organized according to the scanning frequency point; The power spectral density of all measurement points at the same scanning frequency is averaged to obtain the average power spectrum of the target rock at that scanning frequency.

5. The method for optimizing rock resonance frequency for rock breaking according to claim 1, characterized in that, The specific steps for selecting scanning frequency points that meet the recognition criteria are as follows: The average power spectrum is compared point by point according to the order of the scanning frequency points; When the average power spectrum corresponding to the current scanning frequency point is greater than the average power spectrum corresponding to its left and right adjacent scanning frequency points, and is also greater than the preset average power spectrum threshold, the current scanning frequency point is determined as a candidate resonance frequency point that meets the identification conditions. All candidate resonance frequency points are used to form a candidate resonance frequency set.

6. The method for optimizing rock resonance frequency for rock breaking according to claim 1, characterized in that, The specific steps for obtaining the optimal resonance frequency are as follows: Taking the resonance peaks corresponding to each candidate resonance frequency point as the analysis object, determine the left and right frequencies corresponding to half of the peak value of the resonance peak; The quality factor of the corresponding candidate resonant frequency point is constructed based on the bandwidth between the right frequency and the left frequency. The smaller the bandwidth, the higher the corresponding quality factor. The quality factor of each candidate resonance frequency point is evaluated in combination with the corresponding average power spectrum. The candidate resonance frequency with the largest combined evaluation result is determined as the optimal resonance frequency.

7. The method for optimizing rock resonance frequency for rock breaking according to claim 6, characterized in that, The specific steps for constructing phonon energy transfer efficiency are as follows: The optimal resonance frequency is used as the updated scanning frequency point, and the vibration signal acquisition process of claim 2 is executed again. Based on the reacquired vibration signal, the average power spectrum corresponding to the optimal resonance frequency is calculated according to the methods of claims 3 and 4. The phonon energy transfer efficiency is obtained by comparing the average power spectrum corresponding to the optimal resonance frequency with the maximum value of the average power spectrum corresponding to all scanned frequency points.

8. The method for optimizing rock resonance frequency for rock breaking according to claim 1, characterized in that, The specific steps for dynamically updating the optimal frequency until it exceeds the ideal energy transfer efficiency are as follows: Calculate the difference between the phonon energy transfer efficiency and the preset ideal energy transfer efficiency; When the phonon energy transmission efficiency is lower than the preset ideal energy transmission efficiency, the weight ratio of the average power spectrum and quality factor in the combined evaluation is dynamically adjusted according to the difference, and the optimal frequency is recalculated based on the adjusted weight ratio. The steps of claims 2 to 7 are re-executed using the updated optimal frequency to re-obtain the phonon energy transfer efficiency. Repeat the above update process until the phonon energy transfer efficiency reaches or exceeds the preset ideal energy transfer efficiency. After the phonon energy transmission efficiency reaches or exceeds the preset ideal energy transmission efficiency, the updated optimal frequency is maintained to apply vibration excitation to the target rock in order to achieve rock breaking.

9. A rock resonance frequency optimization system for rock breaking, characterized in that: The optimization system is used to execute the optimization method according to any one of claims 1-8, including: The data acquisition module is used to set the frequency interval, acquire discrete scanning frequency points, uniformly arrange measurement points on the surface of the target rock, measure the vibration signal of each measurement point at the scanning frequency point, and normalize the vibration signal of each measurement point. The intensity calculation module is used to perform a fast Fourier transform on the vibration signal of the normalized measurement point to obtain the amplitude spectrum of each measurement point. Based on the amplitude spectrum, the power spectral density of each measurement point is calculated. The power spectral density of all measurement points is averaged to obtain the average power spectrum of the target rock at the scanning frequency point, which is used to highlight the dominant resonance peaks of each layer of the target rock. The peak region of the power spectrum corresponds to the phonon density region, and the amplitude of the peak corresponds to the excitation intensity of the phonons. The frequency extraction module is used to set the identification conditions of the resonance frequency of the target rock using the peak detection method, screen the scanning frequency points that meet the identification conditions, construct the quality factor under each scanning frequency point using the bandwidth sharpness method, multiply the obtained quality factor with the average power spectrum, take the maximum value of the result, obtain the optimal resonance frequency, and complete the regulation of the resonance frequency of the target rock layer. The transmission evaluation module is used to calculate the optimal average power spectrum of the rock at the optimal resonance frequency based on the optimal resonance frequency. The optimal average power spectrum is divided by the maximum average power spectrum of the target rock at each scanning frequency point to construct the phonon energy transmission efficiency. The efficiency optimization module is used to calculate the difference between the preset ideal energy transmission efficiency and the phonon energy transmission efficiency. When the difference is greater than 0, the weight ratio coefficient of the average power spectrum is constructed, the optimal frequency is dynamically updated, and the phonon transmission efficiency is recalculated until the difference is less than 0, thus achieving rock breaking.

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