Slope stability monitoring method for surface mine ecological restoration construction

Abstract

The invention relates to the technical field of slope stability monitoring, in particular to a slope stability monitoring method for surface mine ecological restoration construction, which comprises the following steps: detecting each anchor point on a slope along the direction of a fixed pile through an intelligent sensor, setting no less than two scanning points on each anchor point, acquiring a reflection signal of each scanning point on each anchor point; obtaining each echo signal in each reflected signal, and obtaining the noise interference degree of each echo signal; screening each real echo signal; obtaining a defect judgment value of each real echo signal so as to determine each defect echo signal of each scanning point; according to the distribution time difference of the defect echo signals between different scanning points on each anchor point, obtaining a defect metric value of each anchor point; and evaluating the stability of the slope through the position distribution of all the anchor points and the defect metric value. The invention aims to improve the accuracy of slope stability monitoring.

Description

Technical Field

[0001] This application relates to the field of slope stability monitoring technology, specifically to a slope stability monitoring method for ecological restoration construction in open-pit mines. Background Technology

[0002] Because open-pit mines have shallow or exposed ore bodies, mining requires stripping away rock and soil and excavating layer by layer to form a stepped mining area. This method removes the original vegetation and soil layers, leading to a loss of mountain stability and making the mine highly susceptible to geological disasters such as collapses, landslides, and debris flows. Therefore, ecological restoration of open-pit mines is necessary.

[0003] Slopes formed during open-pit mining are relatively steep and have low rock stability, making them prone to landslides and collapses during ecological restoration. To mitigate these risks, slopes are reinforced using anchor bolts or cables. Anchor bolts or cables are key load-bearing components in slope reinforcement; monitoring the internal condition of the anchor bolts or cables allows for analysis of slope stability.

[0004] Currently, smart sensors are commonly used to detect the internal condition of anchor bolts or cables in order to estimate slope stability. However, in real-world scenarios, the reflected signals obtained by the smart sensor receivers are easily affected by the mixing of cement and steel bars inside the anchor bolts or cables, as well as external environmental interference. This can lead to deviations in the analysis of internal defects in the anchor bolts or cables, thereby affecting the accuracy of slope stability monitoring. Summary of the Invention

[0005] In view of the above, it is necessary to provide a slope stability monitoring method for ecological restoration construction in open-pit mines, which improves the accuracy of slope stability monitoring compared with traditional slope stability monitoring methods for ecological restoration construction in open-pit mines.

[0006] The slope stability monitoring method proposed in this application for ecological restoration construction in open-pit mines adopts the following technical solution: One embodiment of this application provides a slope stability monitoring method for ecological restoration construction in open-pit mines, the method comprising the following steps: The intelligent sensor detects each anchor point on the slope along the direction of the fixed pile. At least two scanning points are set on each anchor point to obtain the reflected signal of each scanning point on each anchor point. The system acquires each echo signal from each reflected signal, and obtains the noise interference level of each echo signal by comparing the frequency of the transmitted signal and the dominant frequency of each echo signal. It then filters each true echo signal by analyzing the distribution of noise interference levels of all echo signals in the reflected signals at each scanning point. Finally, it obtains the defect judgment value of each true echo signal by comparing the energy of each true echo signal with that of the transmitted signal in the time domain and fusing this energy with the regularity of each true echo signal, thereby determining the defect echo signals at each scanning point. Finally, it obtains the defect measurement value for each anchor point by analyzing the distribution time difference of defect echo signals between different scanning points at each anchor point. The stability of the slope is assessed by analyzing the location distribution of all anchor points and the defect measurement values.

[0007] In one embodiment, the process of obtaining the noise interference level is as follows: Extract the frequency with the largest amplitude in the frequency domain for each echo signal; calculate the difference between the statistically obtained frequency and the frequency of the transmitted signal. The noise interference level is directly proportional to the difference value.

[0008] In one embodiment, the process of acquiring the real echo signal is as follows: Obtain the noise interference threshold of all echo signals in the reflected signals of each scanning point, wherein the real echo signal is the echo signal with noise interference less than the segmentation threshold.

[0009] In one embodiment, the process of obtaining the defect determination value is as follows: Obtain the fitting curve of all sampling points of each real echo signal in the time domain, and obtain the goodness of fit of the fitting curve; The defect determination value is inversely proportional to the goodness of fit and the time-domain energy characterization value of the transmitted signal, and directly proportional to the time-domain energy characterization value of each real echo signal.

[0010] In one embodiment, the defect determination value is calculated as follows: Calculate the ratio of the time-domain energy characterization value of each real echo signal to the time-domain energy characterization value of the transmitted signal; The defect determination value is the product of the inverse proportional mapping result of the goodness of fit and the ratio.

[0011] In one embodiment, the method for obtaining the defect echo signal is as follows: when the defect determination value of each real echo signal is greater than the defect determination value of the adjacent real echo signal, each real echo signal is taken as the defect echo signal.

[0012] In one embodiment, the process of obtaining the defect metric value is as follows: For each anchor point, a time window is constructed based on the time width of each defect echo signal and the time of the maximum peak value. The defect echo signals of the remaining scan points within the time window are recorded as the corresponding defect echo signals of each scan point. The time difference between the maximum peak value of each defect echo signal at each scanning point and the maximum peak value of all the corresponding defect echo signals is obtained by summing the results. By combining the accumulated result with the time width of each defect echo signal at each scanning point, the defect characterization value of each defect echo signal at each scanning point is obtained. By analyzing the distribution of defect characterization values ​​of all defect echo signals at all scan points of each anchor point, the defect measurement value of each anchor point is obtained.

[0013] In one embodiment, the defect characterization value is the ratio of the time width of the defect echo signal at each scan point to the summation result.

[0014] In one embodiment, the defect metric is the maximum value among the defect characterization values ​​of all defect echo signals at all scan points of each anchor point.

[0015] In one embodiment, the process of assessing slope stability is as follows: Each anchor point whose defect metric value exceeds a preset threshold is marked as a risk point; If the defect measurement value of all anchor points is zero, the slope stability is considered good. If the risk points are not adjacent, it is determined that the internal stress of the slope is uneven; If the number of directly adjacent risk points is greater than the preset value, the slope stability in the area where the directly adjacent risk points are located is determined to be poor.

[0016] This application has at least the following beneficial effects: This application can accurately identify false echo signals caused by external interference by comparing the frequency of the transmitted signal and the main frequency of the echo signal, thereby effectively distinguishing real signals from noise, reducing misjudgments of internal defects of fixed piles caused by noise interference, and helping to improve the accuracy of slope stability monitoring. Furthermore, by combining time-domain energy differences with signal regularity, it is possible to comprehensively assess from multiple dimensions whether the real echo signal is caused by defects, making defect determination more comprehensive and accurate, and providing a more precise basis for subsequent defect treatment and slope stability assessment. Furthermore, by analyzing the time difference of the defect echo signal distribution at different scanning points, the spatial distribution of defects within the fixed pile can be determined, thereby further verifying the authenticity of the defects inside the fixed pile at the anchor point. Furthermore, by comprehensively considering the location distribution and defect measurement values ​​of all anchor points, the stability of the slope can be comprehensively assessed as a whole. This not only focuses on the defect status of individual anchor points, but also considers the interrelationships between anchor points and the overall stress situation of the slope, thereby improving the accuracy of slope stability monitoring. Attached Figure Description

[0017] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating the steps of a slope stability monitoring method for ecological restoration construction in open-pit mines, as provided in this application; Figure 2 A schematic diagram of the process for obtaining defect characterization values; Figure 3 This is a schematic diagram of the process for obtaining defect metrics. Detailed Implementation

[0019] In the description of the embodiments in this application, the words "exemplary," "or," and "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplary," "or," and "for example" is intended to present the relevant concepts in a specific manner.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. It should be understood that, unless otherwise stated, " / " in this application means "or".

[0021] It should also be noted that the terms "first" and "second" in this application are used to distinguish similar objects, rather than to describe a specific order or sequence.

[0022] The following, in conjunction with the accompanying drawings, details a specific scheme for a slope stability monitoring method for ecological restoration construction in open-pit mines, as provided in this application.

[0023] This application provides an embodiment of a slope stability monitoring method for ecological restoration construction in open-pit mines. Specifically, it provides the following slope stability monitoring method for ecological restoration construction in open-pit mines. Please refer to [link to relevant documentation]. Figure 1 The method includes the following steps: Step 1: Use smart sensors to detect each anchor point on the slope along the direction of the fixed pile. Set no less than two scanning points on each anchor point to obtain the reflected signals of each scanning point on each anchor point.

[0024] In the ecological restoration of open-pit mine slopes, it is necessary to reinforce the shallow, loose soil and rock to ensure stable root development for plants. During reinforcement, anchor bolts or cables are used to connect the shallow soil and rock to the deeper, stable layers. Anchor bolts or cables are fixed piles formed by concrete casting; both are stabilizing structures used for connection. Anchor bolts are typically shorter and smaller in diameter, while anchor cables are longer and have greater load-bearing capacity. The choice between anchor bolts and cables depends primarily on the slope conditions. The exposed foundation piles of anchor bolts or cables on the slope are called anchor points. These anchor points are connected by concrete casting to form a grid, within which plants are planted to achieve ecological restoration.

[0025] To monitor the stability of open-pit mine slopes, intelligent sensors are used to probe each anchor point along the direction of the fixed piles. A coupling agent is evenly applied between the intelligent sensor probe and the anchor point to reduce ultrasonic signal loss. At least two scanning points are set at each anchor point, and the reflected signals from each scanning point at each anchor point are acquired through the intelligent sensor receiver. In this embodiment, glycerol is used as the coupling agent. Specifically, the intelligent sensor in this embodiment is an ultrasonic detector.

[0026] Furthermore, for the smart sensor transmitter, the frequency of the emitted ultrasonic pulse signal is between 5MHz and 10MHz. In this embodiment, the frequency of the emitted signal is set to 5MHz. The smart sensor receiver samples the reflected signal at 10 times the emitted frequency. The total detection time exceeds the total time of the signal's round-trip propagation in the fixed pile, i.e., the sampling monitoring time. Where T is the monitoring time at the receiving end, L represents the length of the fixed pile, and v represents the propagation speed of the ultrasonic signal in the fixed pile. This represents the scaling factor. To ensure that all reflected signals are collected, this embodiment sets... The value is 20%, and it satisfies... The value can be set by the implementer within the range (0,1]. This application does not impose any special restrictions on the specific value of .

[0027] Step 2: Obtain each echo signal from each reflected signal, and obtain the noise interference level of each echo signal; filter each real echo signal; determine each defect echo signal at each scanning point.

[0028] In the process of using ultrasonic waves to detect internal defects in materials, the main basis is the propagation characteristics of ultrasonic signals in a medium. When the propagation medium changes, such as in the propagation process of cement-crack-cement, due to the different acoustic impedances of different media, the ultrasonic signal will be reflected and scattered at the interface of the medium change. At this time, additional reflected signals can be detected at the receiving end, thus helping to determine the internal damage. However, in actual detection, it is easily affected by external environmental interference, and the presence of reinforcing steel aggregate in cement can cause changes in the medium between cement and reinforcing steel, resulting in the detection of multiple interference signals at the receiving end, increasing the risk of misjudging the defects within the fixed pile.

[0029] Step 2.1: Obtain each echo signal from each reflected signal. By comparing the frequency of the transmitted signal and the main frequency of each echo signal, obtain the noise interference level of each echo signal.

[0030] During the propagation of ultrasound, when the propagation medium changes, a reflected signal will be generated at the interface of the changed medium, while some signals will continue to propagate in the original direction. For example, in a fixed pile, due to the structure of cement pouring and steel reinforcement, the ultrasound will encounter the interface between the cement and steel reinforcement during propagation. Therefore, multiple echo signals may appear in the reflected ultrasound signal.

[0031] In the reflected signals detected by the intelligent sensor receiver, a single echo signal may represent an echo signal generated by changes in the steel reinforcement material, external environmental interference, or a real gap. Therefore, each echo signal in each reflected signal is obtained through envelope acquisition. Specifically, envelope analysis is performed on each reflected signal to obtain each envelope. If the minimum value of each envelope is less than 10% of the most recent maximum value, each envelope is divided into two envelopes, resulting in multiple envelopes in each reflected signal. The signal segment between the two ends of each envelope in each reflected signal is considered an echo signal.

[0032] For a single echo signal, the echo signal caused by the actual physical changes between the media is the real echo signal, such as the interface change between steel bars and cement, and the echo signal caused by real gaps, etc. The echo signal formed by the abnormal amplitude caused by external environmental interference is the false echo signal, such as the echo signal caused by vibration and equipment acquisition noise. Therefore, it is necessary to first eliminate the false echo signals caused by external environmental interference.

[0033] The true echo signal is generated by the reflection of the transmitted wave at the interface of the medium change. This reflected wave only carries a part of the energy of the transmitted wave. Therefore, there is an energy difference between the true echo signal and the transmitted wave. However, the main frequency of the true echo signal is basically the same as the frequency of the transmitted wave. On the other hand, the false echo signal is caused by external environmental interference and is unrelated to the transmitted wave. Therefore, the false echo signal is significantly different from the transmitted wave.

[0034] Based on the above analysis, the frequency with the largest amplitude in the frequency domain of each echo signal is extracted and denoted as the dominant frequency of each echo signal. By comparing the frequency of the transmitted signal and the dominant frequency of each echo signal, the noise interference level of each echo signal is obtained, specifically: Calculate the difference between the main frequency of each echo signal and the frequency of the transmitted signal; the noise interference of each echo signal is proportional to the difference value.

[0035] In this embodiment, the echo signal is converted to the frequency domain using short-time Fourier transform. Short-time Fourier transform is a well-known technique and will not be described in detail here. As other implementation methods, implementers may use other existing techniques based on the ability to convert the echo signal to the frequency domain. This application does not impose any special restrictions.

[0036] In this embodiment, the difference between the main frequency of each echo signal and the frequency of the transmitted signal is the absolute value of the difference. As another implementation, based on the ability to measure the degree of difference between the main frequency of each echo signal and the frequency of the transmitted signal, the implementer may use other calculation methods, such as the square of the difference, the ratio, etc. This application does not impose any special restrictions.

[0037] In this embodiment, the expression for the noise interference degree of each echo signal is: In the formula, A represents the noise interference level of a single echo signal; The frequency of the transmitted signal is represented, which is 5MHz in this embodiment; f represents the main frequency of a single echo signal. This indicates the absolute value operation.

[0038] In this embodiment, the expression for the noise interference degree of each echo signal is: In the formula, A represents the noise interference level of a single echo signal; The frequency of the transmitted signal is represented, which is 5MHz in this embodiment; f represents the main frequency of a single echo signal.

[0039] It should be noted that the focus of noise interference assessment is on analyzing the difference between the dominant frequency of the echo signal and the frequency of the signal transmitted by the smart sensor. For genuine echo signals, the frequency difference is very small due to energy attenuation and the difference between the transmitted and transmitted waves. However, for spurious echo signals caused by external environmental interference, which are unrelated to the transmitted signal, the frequency difference is large. Therefore, the higher the calculated noise interference level, the more likely the echo signal is a spurious echo signal caused by external environmental interference.

[0040] Furthermore, the noise interference degree of each echo signal in the reflected signal of each scanning point is calculated, and the segmentation threshold of the noise interference degree of all echo signals in the reflected signal of each scanning point is obtained. Each echo signal with a noise interference degree less than the segmentation threshold is taken as a real echo signal, and the remaining echo signals are taken as false echo signals.

[0041] In this embodiment, the Otsu threshold segmentation algorithm is used to obtain the segmentation threshold of noise interference. The Otsu threshold segmentation algorithm is a well-known technology and will not be described in detail here. As other implementation methods, based on the ability to obtain the segmentation threshold of noise interference, implementers may use other existing feasible technologies, such as iterative threshold segmentation, global threshold segmentation, etc. This application does not impose any special restrictions.

[0042] Step 2.2: By analyzing the noise interference distribution of all echo signals in the reflected signals of each scanning point, each real echo signal is filtered out. By comparing the energy of each real echo signal with the transmitted signal in the time domain and fusing it with the regularity of each real echo signal, the defect judgment value of each real echo signal is obtained, so as to determine the defect echo signal of each scanning point.

[0043] However, since true echo signals are usually caused by changes in the interface between steel bars and cement, or by actual gaps, it is necessary to further analyze the causes of true echo signals and distinguish between true echo signals caused by changes in the medium interface and those caused by actual gaps.

[0044] When ultrasound propagates through a medium, the intensity of the echo signal depends primarily on the difference in acoustic impedance at the interface of the medium change. Generally, the greater the difference, the higher the reflection intensity. In practice, the acoustic impedance ratio is often used to measure the difference in acoustic impedance at the interface of the medium change. In this embodiment, the medium changes are mainly concrete-air and concrete-steel, with corresponding acoustic impedance ratios of approximately 1000:1 and 10:1, respectively. Therefore, a strong echo signal will be generated at the defect.

[0045] Since anchor bolts or anchor cables are fixed piles formed by concrete pouring, they are mainly used to resist the shear force of slope sliding. When potential sliding occurs on the slope, the force is first applied to the fixed piles. When the shear force exceeds the upper limit of the fixed pile's bearing capacity, cracks and defects form inside the fixed pile. These cracks and defects are often irregular, and the irregularity of the cracks affects the propagation of ultrasonic pulse signals, causing additional noise in the reflected waves at the defect interface. This noise not only appears in the initial reflected wave but also persists in the subsequent echo signals passing through the defect interface because these echo signals are also affected by the irregular interface.

[0046] Based on the above analysis, by comparing the energy of each real echo signal and the transmitted signal in the time domain, and fusing it with the regularity of each real echo signal, the defect judgment value of each real echo signal is obtained, specifically: Obtain the fitting curves of all sampling points of each real echo signal in the time domain, and obtain the goodness of fit of the fitting curves; calculate the ratio of the time domain energy characterization value of each real echo signal to the time domain energy characterization value of the transmitted signal; and use the product of the inverse proportional mapping result of the goodness of fit and the ratio as the defect judgment value of each real echo signal.

[0047] It should be noted that: inverse proportional mapping refers to the variable and its inverse proportional mapping result changing in opposite directions. The larger the variable, the smaller the inverse proportional mapping result of the variable, and the smaller the variable, the larger the inverse proportional mapping result of the variable. Specifically, it can be achieved by calculating the reciprocal of the data, using the opposite of the data as the exponent of an exponential function with the natural constant as the base, etc. This application does not impose any special restrictions on this.

[0048] In this embodiment, the fitted curve is obtained by the least squares method. The least squares method is a well-known technique and will not be described in detail in this application. As other implementation methods, based on the ability to obtain the fitted curve of the sampling points, the implementer may use other existing techniques, such as local weighted regression, K-nearest neighbor regression, etc. This application does not impose any special restrictions.

[0049] In this embodiment, the goodness of fit is inversely mapped by calculating the reciprocal of the sum of the goodness of fit and 1, and the time-domain energy characterization value is the maximum value of the echo signal.

[0050] In another embodiment, the goodness of fit is inversely mapped by using the negative of the goodness of fit as the exponent of an exponential function with the natural constant as the base, and the time-domain energy characterization value is the effective value of the echo signal.

[0051] In this embodiment, the chi-square test is used to obtain the goodness of fit. The chi-square test is a well-known technique and will not be described in detail here. As other implementation methods, implementers may use other existing feasible techniques to obtain the goodness of fit, and this application does not impose any special restrictions.

[0052] It should be noted that echo signals caused by real defects typically exhibit strong reflection at the defect interface, resulting in significantly higher energy levels compared to other echo signals. Consequently, the ratio of the time-domain energy representation of the echo signal to that of the transmitted signal is relatively large. Furthermore, irregular cracks at the defect cause scattering and refraction of the echo signal, leading to increased noise and consequently lower goodness of fit. Therefore, a higher calculated defect determination value indicates a greater likelihood that the echo signal is caused by a real defect.

[0053] Furthermore, when determining defects for a single scan point, if the defect determination value of each real echo signal of a single scan point is greater than the defect determination value of the adjacent real echo signals, then each real echo signal is taken as the defect echo signal of each scan point.

[0054] It should be noted that if only echo signals are caused by changes at the concrete-steel interface, the energy of the ultrasonic signal gradually attenuates as the propagation path increases. Therefore, the ratio of the time-domain energy characterization value of each real echo signal to the time-domain energy characterization value of the transmitted signal gradually decreases. However, for echo signals caused by real defects, their energy may be greater than that of the echo signal at the interface of the previous medium change. Therefore, defect echo signals can be identified by comparing the defect determination values ​​of each real echo signal with the defect determination values ​​of its adjacent real echo signals.

[0055] Step 3: Obtain the defect measurement value of each anchor point by measuring the distribution time difference of the defect echo signal between different scanning points on each anchor point.

[0056] When the fixed pile at any anchor point forms an internal defect due to resisting shear force, the position of the defect is relatively fixed. Therefore, the depth position of the defect echo signal at different scanning points on any anchor point should be basically the same. If the depth position of the defect echo signal at different scanning points differs greatly, it may be due to misjudgment. Therefore, it is necessary to comprehensively analyze the defect echo signal at different scanning points on any anchor point to further determine the authenticity of the defect.

[0057] Based on the above analysis, the defect measurement value of each anchor point is obtained by using the distribution time difference of the defect echo signal between different scanning points on each anchor point, specifically: The time when the maximum peak value of each defect echo signal is located is recorded as the reference time of each defect echo signal; with the reference time of any defect echo signal at any scanning point as the center and a preset multiple of the time width of the defect echo signal as the length, a time window of the defect echo signal is constructed. For each of the remaining scan points that are at the same anchor point as any of the scan points, the defect echo signals of the remaining scan points within the time window are counted and recorded as the reference defect echo signals of any defect echo signal; the cumulative result of the time difference between any defect echo signal and all its reference defect echo signals is calculated; the ratio of the time width of any defect echo signal to the cumulative result is used as the defect characterization value of any defect echo signal. According to the method for calculating the defect characterization value of any defect echo signal, calculate the defect characterization value of each scan point of each anchor point; the flowchart for obtaining the defect characterization value is shown below. Figure 2 As shown; The maximum value among the defect characterization values ​​of all defect echo signals from all scan points at each anchor point is used as the defect metric for each anchor point. This metric is used to assess the internal defects of the fixed piles at each anchor point. The larger the calculated defect metric, the greater the likelihood of internal defects in the fixed piles at each anchor point. Furthermore, to accurately analyze and compare the echo signals from different scan points, the reflected signals from different scan points need to be time-aligned. Specifically, by using the reflection time of the reflected signal from a single scan point, all reflected signals are adjusted to a unified time reference. A schematic diagram of the defect metric acquisition process is shown below. Figure 3 As shown.

[0058] It should be noted that: if no defect echo signal is found at any of the other scan points within the time window, it indicates that any defect echo signal may be a misjudgment, and the defect characterization value of any defect echo signal is assigned to 0; if some of the other scan points do not have defect echo signals within the time window, missing values ​​are ignored, and the defect characterization value of any defect echo signal continues to be calculated. If any of the other scan points has multiple defect echo signals within the time window, the defect echo signal with the largest amplitude is used for subsequent calculations.

[0059] In this embodiment, the preset multiplier is 5. The preset multiplier is preset by the user and can be set by the implementer according to the actual situation. This application does not impose any special restrictions.

[0060] It should be noted that in real-world scenarios, defects are often elongated surfaces. Therefore, the defect depth at different scanning points for the same anchor point is generally consistent. Consequently, the smaller the time difference between defect echo signals from different scanning points, the more likely a real defect exists within the anchor point's fixed pile. Conversely, if the time difference between defect echo signals from different scanning points within the same time window is large, but the number of scanning points with defect echo signals within the same time window is small, it indicates the presence of discretely distributed fine cracks within the anchor point's fixed pile. Furthermore, a larger calculated defect metric value indicates a greater likelihood of defects existing within the fixed piles of each anchor point.

[0061] Step 4: Assess the stability of the slope by analyzing the location distribution of all anchor points and the defect metric values.

[0062] If a single anchor point has internal defects, it indicates that the overall stress on that anchor point is relatively large, resulting in significant shear force on the slope at that anchor point. However, if multiple connected anchor points have internal defects, it indicates a greater risk of landslides in the corresponding areas of the connected anchor points, leading to lower slope stability.

[0063] If the defect metric value of a single anchor point is greater than the preset threshold, it indicates that the crack in the fixed pile of the single anchor point exists at multiple scanning points and the crack is serious. In this case, the single anchor point will be marked as a risk point.

[0064] Furthermore, based on the risk assessment of the anchor points on the slope, a stability analysis of the slope is conducted, specifically as follows: (1) If the defect measurement value of all anchor points is zero, that is, there are no risk points, the slope stability is judged to be good and there is no risk of lateral slippage; (2) If there are scattered risk points, that is, the risk points are not adjacent, it is determined that the internal stress of the slope is uneven and the shear force is unevenly distributed, and further reinforcement is required; (3) If the number of directly adjacent risk points is greater than 4, it is determined that the slope stability in the area where the directly adjacent risk points are located is poor and there may be a risk of lateral slippage. It is necessary to notify the staff to conduct a risk assessment and deal with it in a timely manner to avoid the risk of landslides or collapses. Here, 4 is just one embodiment of this application. The implementer can set it according to the actual situation. This application does not impose any special restrictions.

[0065] In this embodiment, the preset threshold value is 1, and the preset threshold value is calculated based on experimental data.

[0066] In summary, by comparing the frequency of the transmitted signal and the dominant frequency of the echo signal, this application can accurately identify false echo signals caused by external interference, thereby effectively distinguishing real signals from noise, reducing misjudgments of internal defects in fixed piles due to noise interference, and helping to improve the accuracy of slope stability monitoring. Furthermore, by combining time-domain energy differences with signal regularity, it is possible to comprehensively assess from multiple dimensions whether the real echo signal is caused by defects, making defect determination more comprehensive and accurate, and providing a more precise basis for subsequent defect treatment and slope stability assessment. Furthermore, by analyzing the time difference of the defect echo signal distribution at different scanning points, the spatial distribution of defects within the fixed pile can be determined, thereby further verifying the authenticity of the defects inside the fixed pile at the anchor point. Furthermore, by comprehensively considering the location distribution and defect measurement values ​​of all anchor points, the stability of the slope can be comprehensively assessed as a whole. This not only focuses on the defect status of individual anchor points, but also considers the interrelationships between anchor points and the overall stress situation of the slope, thereby improving the accuracy of slope stability monitoring.

[0067] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0068] It will be apparent to those skilled in the art that this application is not limited to the details of the exemplary embodiments described above, and that this application can be implemented in other specific forms without departing from its essential characteristics. Therefore, the embodiments described above should be considered exemplary and non-limiting in all respects.

Claims

1. A slope stability monitoring method for ecological restoration construction in open-pit mines, characterized in that, The method includes the following steps: Intelligent sensors are used to detect each anchor point on the slope along the direction of the fixed pile. At least two scanning points are set on each anchor point to obtain the reflected signals of each scanning point on each anchor point. The system acquires each echo signal from each reflected signal, and obtains the noise interference level of each echo signal by comparing the frequency of the transmitted signal and the dominant frequency of each echo signal. It then filters each true echo signal by analyzing the distribution of noise interference levels of all echo signals in the reflected signals at each scanning point. Finally, it obtains the defect judgment value of each true echo signal by comparing the energy of each true echo signal with that of the transmitted signal in the time domain and fusing this energy with the regularity of each true echo signal, thereby determining the defect echo signals at each scanning point. Finally, it obtains the defect measurement value for each anchor point by analyzing the distribution time difference of defect echo signals between different scanning points at each anchor point. The stability of the slope is assessed by analyzing the location distribution of all anchor points and the defect measurement values.

2. The slope stability monitoring method for ecological restoration construction in open-pit mines as described in claim 1, characterized in that, The process of obtaining the noise interference level is as follows: Extract the frequency with the largest amplitude in the frequency domain for each echo signal; calculate the difference between the statistically obtained frequency and the frequency of the transmitted signal. The noise interference level is directly proportional to the difference value.

3. The slope stability monitoring method for ecological restoration construction in open-pit mines as described in claim 1, characterized in that, The process of acquiring the actual echo signal is as follows: Obtain the noise interference threshold of all echo signals in the reflected signals of each scanning point, wherein the real echo signal is the echo signal with noise interference less than the segmentation threshold.

4. The slope stability monitoring method for ecological restoration construction in open-pit mines as described in claim 1, characterized in that, The process for obtaining the defect determination value is as follows: Obtain the fitting curve of all sampling points of each real echo signal in the time domain, and obtain the goodness of fit of the fitting curve; The defect determination value is inversely proportional to the goodness of fit and the time-domain energy characterization value of the transmitted signal, and directly proportional to the time-domain energy characterization value of each real echo signal.

5. A slope stability monitoring method for ecological restoration construction in open-pit mines as described in claim 4, characterized in that, The method for calculating the defect determination value is as follows: Calculate the ratio of the time-domain energy characterization value of each real echo signal to the time-domain energy characterization value of the transmitted signal; The defect determination value is the product of the inverse proportional mapping result of the goodness of fit and the ratio.

6. The slope stability monitoring method for ecological restoration construction in open-pit mines as described in claim 1, characterized in that, The method for obtaining the defect echo signal is as follows: when the defect determination value of each real echo signal is greater than the defect determination value of the adjacent real echo signal, each real echo signal is taken as the defect echo signal.

7. The slope stability monitoring method for ecological restoration construction in open-pit mines as described in claim 1, characterized in that, The process for obtaining the defect metric value is as follows: For each anchor point, a time window is constructed based on the time width of each defect echo signal and the time of the maximum peak value. The defect echo signals of the remaining scan points within the time window are recorded as the corresponding defect echo signals of each scan point. The time difference between the maximum peak value of each defect echo signal at each scanning point and the maximum peak value of all the corresponding defect echo signals is obtained by summing the results. By combining the accumulated result with the time width of each defect echo signal at each scanning point, the defect characterization value of each defect echo signal at each scanning point is obtained. By analyzing the distribution of defect characterization values ​​of all defect echo signals at all scan points of each anchor point, the defect measurement value of each anchor point is obtained.

8. A slope stability monitoring method for ecological restoration construction in open-pit mines as described in claim 7, characterized in that, The defect characterization value is the ratio of the time width of the defect echo signal at each scan point to the accumulated result.

9. A slope stability monitoring method for ecological restoration construction in open-pit mines as described in claim 7, characterized in that, The defect metric is the maximum value among the defect characterization values ​​of all defect echo signals at all scan points of each anchor point.

10. A slope stability monitoring method for ecological restoration construction in open-pit mines as described in claim 1, characterized in that, The process for assessing slope stability is as follows: Each anchor point whose defect metric value exceeds a preset threshold is marked as a risk point; If the defect measurement value of all anchor points is zero, the slope stability is considered good. If the risk points are not adjacent, it is determined that the internal stress of the slope is uneven; If the number of directly adjacent risk points is greater than the preset value, the slope stability in the area where the directly adjacent risk points are located is determined to be poor.

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