A communication line based theft prevention monitoring method

Abstract

The application provides a communication line-based anti-theft monitoring method, which comprises the following steps: identifying the cable offset angle change corresponding to the soil disturbance propagation path, obtaining the correlation between the soil disturbance propagation path and the cable offset angle, determining the potential risk value of the cable subjected to the soil disturbance according to the correlation; sending a control instruction to an underground intelligent anchoring device, monitoring the offset angle change of the anchoring device after the cable is fixed, and obtaining the cable fixing and fastening state; determining the offset angle recovery degree according to the cable fixing and fastening state, if the offset angle recovery degree is unchanged or becomes lower, triggering the alarm activator to activate the sound and light alarm system, and identifying the soil disturbance frequency after the alarm is triggered; and obtaining the anti-theft monitoring response effect by analyzing the soil disturbance frequency change before and after the alarm is triggered and the cable offset angle.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of information technology, and in particular to a communication line-based anti-theft monitoring method. BACKGROUND

[0002] In the process of modern urbanization, underground communication cables, as the lifeline of information transmission, have become a key issue in the field of communication infrastructure protection that needs to be addressed urgently. Existing anti-theft monitoring methods mostly rely on single physical protection or simple sensor monitoring. However, physical protection is easily damaged by professional tools, and traditional vibration sensors have difficulty in accurately distinguishing the source of soil disturbance, resulting in a high false alarm rate. In particular, in high-noise environments such as construction sites, it is difficult to effectively distinguish between normal construction vibrations and illegal excavation behavior, leading to a significant reduction in monitoring effectiveness. The deeper challenge lies in the fact that illegal excavation behavior causes soil disturbance, which in turn causes cable displacement, and the displaced cable changes the propagation characteristics of the disturbance wave in the soil, forming a dynamic interaction relationship. Soil disturbance is an external manifestation of excavation behavior and usually propagates in the form of waves, but its propagation path is influenced by factors such as soil density and humidity, making it highly complex and uncertain. Cable fixation in soil usually relies on anchoring devices, but when the displacement angle is too large, the fixing device may loosen or even fail due to uneven stress. Existing technologies lack real-time monitoring means for this dynamic interaction, and cannot adjust the fixing force of the anchoring device based on the interaction changes, making it difficult to effectively respond to theft. Therefore, how to real-time monitor the dynamic interaction between soil disturbance waves and cable displacement angles in complex construction environments, and dynamically adjust the cable fixation state based on this interaction characteristic, to accurately identify illegal excavation behavior and trigger an alarm in a timely manner, has become a key problem in the anti-theft monitoring of underground communication cables. SUMMARY

[0003] The present application provides a communication line-based anti-theft monitoring method, mainly comprising:

[0004] Obtaining the soil disturbance state and cable position change in a target time period, obtaining the soil disturbance frequency and cable displacement angle, and determining the soil disturbance propagation path based on the soil disturbance frequency and the cable displacement angle;

[0005] Identifying the cable displacement angle change corresponding to the soil disturbance propagation path, obtaining the correlation between the soil disturbance propagation path and the cable displacement angle, and determining the potential risk value of the cable subjected to soil disturbance based on the correlation;

[0006] Comparing the potential risk value with a preset risk threshold to determine whether there is illegal excavation behavior, analyzing the change trend of the cable displacement angle by continuously obtaining real-time soil disturbance state, and determining the cable displacement angle aggravation risk level based on the change trend.

[0007] According to the cable offset angle aggravation risk level, the anchoring device tightening force requirement is determined, the real-time change rate of the cable offset angle is obtained, the tightening force is dynamically adjusted in combination with the tightening force requirement and the real-time change rate, and an anchoring device control instruction is generated;

[0008] The control instruction is sent to the underground intelligent anchoring device, and the change of the offset angle of the anchoring device after the cable is fixed is monitored to obtain a cable fixing and tightening state;

[0009] According to the cable fixing and tightening state, the offset angle recovery degree is determined, if the offset angle recovery degree is unchanged or reduced, an alarm is triggered to activate an audible and visual alarm system, and a soil disturbance frequency after the alarm is triggered is identified;

[0010] The anti-theft monitoring response effect is obtained by analyzing the change of the soil disturbance frequency before and after the alarm is triggered and the cable offset angle.

[0011] Further, the soil disturbance state and the cable position change in a target time period are obtained to obtain a soil disturbance frequency and a cable offset angle, and a soil disturbance propagation path is determined according to the soil disturbance frequency and the cable offset angle, including:

[0012] The soil vibration signal collected in the target time period is obtained, the main frequency component of the soil vibration signal is extracted through Fourier transform, and the soil disturbance frequency is determined;

[0013] Three-dimensional space inclination data of the cable are obtained, and the cable offset angle is calculated according to the difference between the inclination data and the initial position of the cable;

[0014] According to the numerical distribution of the soil disturbance frequency at each monitoring node, a disturbance intensity spatial distribution map is constructed, a disturbance propagation contour map is generated through the disturbance intensity spatial distribution map, and a disturbance propagation direction vector is fitted in combination with the change gradient of the cable offset angle;

[0015] According to the included angle between the disturbance propagation direction vector and the cable trend and the spatial distribution of the disturbance propagation contour map, the soil disturbance propagation path is determined.

[0016] Further, the cable offset angle change corresponding to the soil disturbance propagation path is identified to obtain the correlation between the soil disturbance propagation path and the cable offset angle, including:

[0017] The time sequence data of each monitoring point on the soil disturbance propagation path is obtained, the disturbance wave arrival time and amplitude value are extracted, and the cable offset angle at the corresponding moment is recorded;

[0018] determine a time delay of the disturbance propagation to the cable response according to the correlation coefficient distribution;

[0019] align the soil disturbance signal and the cable offset angle signal according to the time delay, decompose a frequency band component of the cable offset angle signal, calculate a correlation coefficient of the frequency band component and the soil disturbance signal, and obtain a correlation of the soil disturbance propagation path and the cable offset angle.

[0020] Further, according to the comparison of the potential risk value and the preset risk threshold, it is determined whether there is illegal mining behavior, and the change trend of the cable offset angle is analyzed by continuously acquiring the real-time soil disturbance state, including:

[0021] According to the comparison of the potential risk value and the preset risk threshold, it is determined whether there is illegal mining behavior;

[0022] If there is illegal mining behavior, the vibration intensity of the real-time soil disturbance state and the real-time value of the cable offset angle are acquired, and the change rate of the cable offset angle is calculated;

[0023] According to the change rate, a change curve is fitted, and the change trend of the cable offset angle is determined.

[0024] Further, according to the change trend, a cable offset angle aggravation risk level is determined, including:

[0025] According to the change trend of the cable offset angle, a time change slope of the change rate is calculated;

[0026] According to the time change slope and the duration, the cable offset angle aggravation risk level is determined, wherein the time change slope is positive and the duration exceeds a preset time length, which is a high risk level, the time change slope is positive but the duration is less than the preset time length, which is a medium risk level, and the time change slope is not positive, which is a low risk level;

[0027] An offset acceleration value is calculated through the time change slope, and the cable offset angle aggravation risk level is determined according to the offset acceleration value and the change trend.

[0028] Further, an anchoring device control instruction is generated, including:

[0029] A basic tightening intensity requirement value is determined according to the cable offset angle aggravation risk level;

[0030] The basic tightening intensity requirement value is adjusted according to the real-time change rate of the cable offset angle, and an actual tightening intensity value is obtained;

[0031] Determine execution time and adjustment frequency according to the actual tightening force value, and generate anchoring device control instructions containing the actual tightening force value, execution time and the adjustment frequency.

[0032] Further, send the control instructions to the underground intelligent anchoring device, and monitor the change of the cable offset angle after the anchoring device tightens the cable to obtain the cable fixation and fastening state, including:

[0033] Send the control instructions to the underground intelligent anchoring device, and record the sending time;

[0034] Monitor the change of the cable offset angle during the tightening of the anchoring device, calculate the difference of the cable offset angle before and after tightening, and obtain the angle recovery amount;

[0035] According to the percentage of the angle recovery amount in the initial offset angle, determine the cable fixation and fastening state.

[0036] Further, obtaining the cable fixation and fastening state includes:

[0037] Collect the cable offset angle, tension value and deformation amount during the tightening of the anchoring device;

[0038] Calculate the change rate according to the cable offset angle, calculate the tension gradient according to the tension value, and determine the strain level according to the deformation amount;

[0039] According to the change rate, the tension gradient and the strain level, determine the cable fixation and fastening state as a completely fixed state, a relaxed state or an over-tightening state.

[0040] Further, according to the cable fixation and fastening state, determine the offset angle recovery degree, if the offset angle recovery degree is unchanged or reduced, trigger the alarm to activate the sound and light alarm system, including:

[0041] According to the cable fixation and fastening state, calculate the recovery amount of the cable offset angle to obtain the offset angle recovery percentage;

[0042] If the offset angle recovery percentage is unchanged or reduced compared with the previous period, send the activation instruction to the alarm to drive the sound and light alarm device to send a signal.

[0043] Further, by analyzing the soil disturbance frequency change and the cable offset angle before and after the alarm is triggered, obtain the anti-theft monitoring response effect, including:

[0044] Obtain the soil disturbance frequency sequence before and after the alarm is triggered, calculate the difference between the average values before and after triggering to obtain the frequency drop value;

[0045] According to the ratio of the frequency drop value to the average value of the frequency before triggering, obtain the signal attenuation degree;

[0046] According to the difference of the cable offset angle before and after the alarm triggering, the cable offset angle recovery degree is obtained;

[0047] According to the comparison of the alarm triggering time interval and the preset standard, the alarm triggering timeliness score is obtained, and the anti-theft monitoring response effect including the signal weakening degree, the cable offset angle recovery degree and the alarm triggering timeliness score is formed.

[0048] The technical scheme provided by the embodiment of the present application can include the following beneficial effects:

[0049] The present application discloses an anti-theft monitoring method based on communication lines, which aims at soil disturbance and cable offset caused by illegal excavation. The amplitude, frequency spectrum and propagation vector of the soil disturbance waveform are collected in real time, combined with the change of the cable offset angle, and the potential risk value is calculated to determine the illegal excavation behavior. Based on the risk level, the anchoring device is adjusted dynamically, control instructions are generated and sent to the intelligent anchoring device through the wireless communication module, and the offset angle, tension strength and deformation data during the cable fixing process are monitored to analyze the fixing state. If the offset angle recovery is insufficient, an audible light alarm is triggered and the anti-theft monitoring effect is evaluated. The present application significantly improves the cable anti-theft ability and stability, reduces the risk of illegal excavation, and ensures the safe operation of underground cables through the correlation analysis and dynamic regulation of soil disturbance and cable offset. BRIEF DESCRIPTION OF DRAWINGS

[0050] Fig. 1 The flowchart of the anti-theft monitoring method based on communication lines of the present application.

[0051] Fig. 2 The schematic diagram of the anti-theft monitoring method based on communication lines of the present application. DETAILED DESCRIPTION

[0052] The technical scheme in the embodiments of the present application will be described in detail below with reference to the accompanying drawings. The described embodiments are only a part of the embodiments of the present application.

[0053] As Figs. 1-2 , the anti-theft monitoring method based on communication lines of the present application can specifically include:

[0054] S101, the disturbance state of the soil and the position change of the cable in the target time period are obtained, the soil disturbance frequency and the cable offset angle are obtained, and the soil disturbance propagation path is determined according to the soil disturbance frequency and the cable offset angle.

[0055] The soil vibration signals collected by the distributed vibration sensor in a target time period are obtained, the main frequency component and the harmonic component of the vibration signals are extracted by fast Fourier transform, and the soil disturbance frequency is determined according to the ratio of the main frequency component to the harmonic component. Meanwhile, the inclination data of the cable in three-dimensional space are read from the fiber optic gyroscope, and the cable offset angle is calculated according to the difference between the inclination data and the initial position of the cable. According to the numerical distribution of the soil disturbance frequency at each monitoring node, a disturbance intensity spatial distribution map is constructed, wherein the disturbance intensity of each monitoring node is obtained by multiplying the soil disturbance frequency and the vibration signal amplitude. A disturbance propagation contour map is generated by performing two-dimensional interpolation operation on the disturbance intensity spatial distribution map. In combination with the change gradient of the cable offset angle along the length direction of the cable, the disturbance propagation direction is obtained by least square fitting. If the included angle between the propagation direction and the cable trend is less than a preset included angle threshold, it is determined that the disturbance wave propagates along the cable direction. According to the time difference and the spatial interval of adjacent contours in the disturbance propagation contour map, the disturbance wave propagation speed is calculated. The soil disturbance propagation path is determined by the propagation speed, the propagation direction and the spatial distribution characteristics of the disturbance propagation contour map.

[0056] For example, in an embodiment, the distributed vibration sensor uses an optical fiber Bragg grating sensor array, and a sensor node is arranged every 5 meters along the cable path. When the soil is disturbed, the sensor captures the vibration signal and digitizes the sampling, and the sampling frequency is set to 1000 Hz. The collected time domain signal is converted to the frequency domain for analysis by fast Fourier transform. The main frequency component represents the main vibration characteristics of the disturbance, the harmonic component reflects the complexity of the disturbance, and the ratio of the two can effectively distinguish different types of soil disturbance sources. The calculation process of the disturbance intensity involves the comprehensive evaluation of the frequency and the amplitude. At each monitoring node, the amplitude of the vibration signal reflects the size of the disturbance energy, and the soil disturbance frequency embodies the periodic characteristics of the disturbance. By multiplying the frequency value and the amplitude, the disturbance intensity value that can reflect the disturbance energy and frequency characteristics is obtained. This calculation method can effectively distinguish the surface disturbance with high frequency and low amplitude and the deep excavation behavior with low frequency and high amplitude. The two-dimensional interpolation operation uses a bicubic interpolation algorithm to perform spatial continuous processing on the discrete monitoring point data. In the interpolation process, according to the disturbance intensity values and the spatial position relationship of adjacent monitoring points, the disturbance intensity estimation value of any spatial point is calculated. In the generated contour map, each contour line represents the spatial position connection line of the same disturbance intensity, and the density of the contour line reflects the spatial variation rate of the disturbance intensity.

[0057] In one possible implementation, the cable offset angle is obtained by integrating the three-axis angular velocity of the fiber-optic gyroscope. The pitch angle, roll angle and yaw angle data output by the gyroscope are subjected to coordinate transformation to obtain the spatial offset angle of the cable relative to the initial position. The spatial derivative of the offset angle is calculated along the length direction of the cable to obtain the offset angle change gradient, which reflects the uneven degree of force on the cable. The determination of the disturbance propagation path requires the comprehensive consideration of multiple parameters. The propagation speed is calculated by analyzing the time difference and spatial distance of adjacent contour lines. The propagation direction indicates the main propagation direction of the disturbance wave. The spatial distribution characteristics of the contour map, including the shape, density and extension direction of the contour lines, jointly determine the complete propagation path of the soil disturbance in the underground space.

[0058] S102, identify the change of the cable offset angle corresponding to the soil disturbance propagation path, obtain the correlation between the soil disturbance propagation path and the cable offset angle, and determine the potential risk value of the cable subjected to the soil disturbance according to the correlation.

[0059] The time series data of each monitoring point on the soil disturbance propagation path are acquired, the time stamp and amplitude value of the disturbance wave arriving at each point are extracted, and the instantaneous value and change rate of the cable offset angle at the corresponding moment are recorded. The cross-correlation function of the disturbance amplitude sequence and the offset angle sequence is calculated through a sliding time window to obtain the correlation coefficient distribution under different time delays. The time delay of the disturbance propagation to the cable response is determined according to the peak position of the correlation coefficient. The soil disturbance signal and the cable offset signal are aligned according to the time delay, and the aligned offset angle time series signal is decomposed by wavelet transform to obtain angle change components in different frequency bands. The correlation coefficients of each frequency band are calculated by comparing the spectral characteristics of the soil disturbance signal with the energy distribution of the offset angle components in each frequency band. If the correlation coefficient of the low-frequency component exceeds a preset threshold, it is determined that there is a persistent offset caused by deep excavation, and the frequency domain correlation between the disturbance and the offset is obtained. The peak value of the correlation coefficient distribution is taken as a weight coefficient to construct a time domain transfer function in combination with the time delay, and the transfer function describes the mapping relationship between the disturbance amplitude and the offset angle. The cable offset amplitude at a future time is predicted according to the transfer function and the current disturbance intensity. The offset probability of the cable offset exceeding a safety threshold is calculated in combination with the statistical distribution of the historical offset data. The risk assessment factor is obtained by multiplying the offset probability and the frequency domain correlation. The potential risk value of the cable subjected to the soil disturbance is determined according to the weighted sum of the risk assessment factor, the gain coefficient of the transfer function and the offset probability.

[0060] Exemplarily, in an embodiment, the monitoring points on the soil disturbance propagation path are equipped with composite monitoring units composed of high-precision acceleration sensors and angle sensors, and each unit synchronously records the disturbance vibration and cable offset data at a sampling interval of 10 milliseconds. When excavation activities occur underground, disturbance waves propagate from the source to the surrounding, and the time of arrival at each monitoring point is different. By extracting the arrival time and corresponding amplitude value of the disturbance wave, the spatiotemporal feature sequence of disturbance propagation is constructed.

[0061] It should be noted that the calculation of the cross-correlation function uses a sliding time window method, and the window length is set to 2 seconds, and the sliding step is 0.1 seconds,

[0062]

[0063] , R xy (τ) represents the cross-correlation function of the disturbance amplitude sequence and the offset angle sequence, x(t) represents the disturbance amplitude sequence, y(t+τ) represents the offset angle sequence after time delay τ, T represents the time window length, and τ represents the time delay parameter. In each time window, the cross-correlation value R(τ) of the disturbance amplitude sequence x(t) and the offset angle sequence y(t) is calculated, where τ represents the time delay. The cross-correlation function reflects the similarity of two signals at different time offsets, and when R(τ) reaches a peak value, the corresponding τ value is the time delay of the disturbance propagation to cause the cable response. This time delay includes the propagation time of the disturbance wave in the soil and the mechanical response time of the cable, which is usually in the range of 0.5 to 3 seconds. The size of the peak value reflects the influence degree of the disturbance on the cable offset, and the larger the peak value, the stronger the correlation between the disturbance and the offset.

[0064] Specifically, the implementation process of wavelet transform uses Morlet wavelet basis function to perform multi-scale decomposition on the time sequence signal of the cable offset angle. The low-frequency component obtained by decomposition corresponds to slow offset changes with a period greater than 10 seconds, the medium-frequency component corresponds to periodic oscillation with a period of 1 to 10 seconds, and the high-frequency component corresponds to rapid vibration with a period less than 1 second. The soil disturbance signal is also subjected to frequency spectrum analysis to extract its main frequency components. By comparing the energy distribution of each frequency band, the Pearson correlation coefficient of each frequency band is calculated. When the correlation coefficient of the low-frequency component exceeds the preset threshold value of 0.7, it indicates that there is a persistent deep excavation activity, which will cause the cable to produce a long-term one-way offset. The high correlation of the medium-frequency component indicates intermittent excavation activities, such as the periodic operation of an excavator.

[0065] Preferably, the peak value of the correlation coefficient distribution is taken as the weighting coefficient of the frequency response in the construction process of the time-domain transfer function. The transfer function H(s) describes the dynamic response characteristics from the disturbance input to the offset output, and the gain coefficient thereof reflects the amount of change in the offset angle caused by a unit disturbance intensity. According to the currently monitored disturbance intensity A(t), the cable offset angle θ(t+Δt) at time t+Δt can be predicted by the transfer function, i.e., θ(t+Δt) = H(s) × A(t). In combination with the probability distribution of the offset angle in the historical monitoring data, the conditional probability that the offset angle exceeds the safety threshold is calculated by using the Bayesian inference method.

[0066] In a possible implementation, statistical analysis of the historical offset data shows that, under normal construction conditions, the cable offset angle obeys a normal distribution with a mean of 0 and a standard deviation of 2 degrees. When the predicted offset angle exceeds 3 times the standard deviation, it is considered that there is an abnormal risk. The calculation of the offset probability P takes into account the distance between the predicted offset value and the safety threshold, as well as the uncertainty of the prediction.

[0067] Exemplarily, the risk assessment factor is obtained by the product of the offset probability P and the frequency-domain correlation ρ, and is expressed as F = P × ρ. This factor comprehensively reflects the possibility of offset occurrence and the correlation strength between the disturbance and the offset. The gain coefficient G of the transfer function represents the sensitivity of the cable to the disturbance, and the greater the gain, the more easily the cable is affected by the disturbance. The calculation of the potential risk value adopts a weighted summation method, i.e., R = w1 × F + w2 × G + w3 × P, wherein w1, w2, and w3 are preset normalized weight coefficients, and are respectively set to 0.4, 0.3, and 0.3. The risk assessment factor F occupies the largest weight, because it simultaneously considers the two key factors of probability and correlation. The gain coefficient G reflects the inherent characteristics of the system, and the offset probability P is directly related to the safety state.

[0068] It can be understood that, when the potential risk value R exceeds 0.6, a first-level warning is triggered; and when the potential risk value R exceeds 0.8, a second-level warning is triggered and an emergency response mechanism is started. This multi-factor comprehensive evaluation method can effectively reduce the false positive rate of single-index judgment, and improve the accuracy and reliability of the underground cable theft prevention monitoring. By updating each parameter in real time and dynamically adjusting the preset weight coefficients, adaptive recognition of different excavation modes and soil conditions can be achieved.

[0069] S103, if the potential risk value exceeds the preset risk threshold, it is determined that there is an illegal excavation behavior, the change trend of the cable offset angle is analyzed by continuously acquiring the real-time soil disturbance state, and the cable offset angle aggravation risk level is determined according to the change trend of the cable offset angle.

[0070] If the potential risk value exceeds the preset risk threshold, it is determined that there is illegal mining behavior, and a continuous monitoring mechanism is triggered to obtain the vibration intensity and frequency characteristics of soil disturbance at a preset sampling frequency. At the same time, the real-time value of the cable offset angle is recorded, the ratio of the angle difference between adjacent sampling points to the time interval is calculated, and the offset angle change rate sequence is obtained. According to the offset angle change rate sequence, the least square method is used to fit the change curve of the change rate with time, and the time change slope of the change rate is obtained. If the time change slope is continuously positive, it is determined that the offset angle shows an accelerating growth trend. By taking the derivative of the time change slope, the offset acceleration value is obtained, which represents the degree of aggravation of the offset angle change. According to the size of the offset acceleration value and the duration of the accelerating growth trend, the risk level is determined. When the offset acceleration exceeds the preset high risk threshold and the duration exceeds the preset time length, it is determined as a high risk level; when the offset acceleration is between the high risk threshold and the low risk threshold, it is determined as a medium risk level; when the offset acceleration is lower than the low risk threshold, it is determined as a low risk level, and the cable offset angle aggravation risk level is obtained.

[0071] For example, in an embodiment, the determination of the potential risk value uses a multi-level threshold comparison mechanism. When the potential risk value exceeds the preset risk threshold of 0.65, it is determined that there is illegal mining behavior, and the continuous monitoring mode is activated immediately. In this mode, the monitoring system increases the sampling frequency from the regular 1 per second to 10 per second, and real-time collects the vibration intensity value and the main frequency component of soil disturbance. The vibration intensity is obtained by the three-axis combined value of the acceleration sensor, and the main frequency component is extracted from the frequency spectrum analysis.

[0072] Specifically, in the calculation process of the offset angle change rate, the angle difference between two adjacent sampling points is divided by the time interval of 0.1 seconds to obtain the instantaneous change rate. The change rate values of 100 consecutive sampling points form a change rate sequence. The least square method is used to linearly fit the sequence, and the slope of the fitted straight line is the time change slope. When the slope value remains positive for 30 seconds, it indicates that the cable offset is continuously aggravated, which usually corresponds to the continuous operation of the mechanical digging equipment.

[0073] It should be noted that the offset acceleration value is obtained by taking the derivative of the time change slope, and its physical meaning is the degree of change of the offset speed. A positive acceleration value indicates that the offset speed is increasing, and a larger value indicates that the offset is more severe. In actual monitoring, the acceleration value caused by normal construction vibration is usually below 0.01 degree / s2, while the acceleration value of illegal mining activities often exceeds 0.05 degree / s2.

[0074] Preferably, the risk level determination adopts a two-parameter evaluation method. The high risk threshold is set to 0.08 degree / s2, the low risk threshold is set to 0.03 degree / s2, and the time threshold is set to 60 seconds. When the offset acceleration exceeds 0.08 degree / s2 and the duration exceeds 60 seconds, it is directly determined as a high risk level, triggering the emergency response mechanism. When the acceleration is between 0.03 and 0.08 degree / s2, it is a medium risk level, and the monitoring frequency needs to be increased. When it is lower than 0.03 degree / s2, it is a low risk level, and the normal monitoring state is maintained.

[0075] In one possible implementation, the dynamic adjustment of the risk level takes into account the statistical characteristics of historical data. By analyzing the offset data of the same period in the past 30 days, a baseline range of normal offset patterns is established. When the real-time monitoring value deviates from the baseline range by more than 2 times the standard deviation, the risk level is automatically raised.

[0076] The amplitude, frequency spectrum and propagation vector of the disturbance waveform of the soil disturbance propagation path are collected, and the change of the offset angle of the cable in the target time period is monitored. The amplitude, frequency spectrum and propagation vector of the disturbance waveform and the change of the offset angle are weighted to determine the potential risk value of the cable caused by soil disturbance. If the risk value exceeds the risk threshold corresponding to the historical disturbance data, it is determined that there is illegal excavation behavior, and an early warning signal containing the excavation probability, disturbance source positioning and risk level is output.

[0077] The vibration data of the distributed sensor array on the soil disturbance propagation path is collected, the instantaneous amplitude values of the disturbance waveform at each monitoring point are extracted, and the main frequency component and harmonic distribution of the frequency spectrum are obtained through Fourier transform. According to the waveform phase difference and spatial coordinates of adjacent monitoring points, the propagation direction and speed of the disturbance wave are calculated, and a three-dimensional propagation vector is constructed. At the same time, the continuous sampling values of the cable deflection angle in the target time period are obtained from the fiber gyroscope, and the amplitude range of the angle change is calculated. The amplitude weight factor is obtained by normalizing the amplitude value, the frequency domain weight factor is obtained by integrating the energy density of the frequency spectrum, and the absolute value of the cosine of the angle between the propagation vector and the cable trend is calculated to obtain the direction weight factor. According to the ratio of the angle change amplitude to the preset reference value, the angle sensitivity coefficient is determined. The amplitude weight factor, frequency domain weight factor and direction weight factor are multiplied by the corresponding preset weight coefficients respectively, and then multiplied by the angle sensitivity coefficient to obtain a comprehensive risk value. The risk value samples of normal construction and illegal excavation events in the past preset time period are extracted from the historical monitoring records, and the mean and standard deviation of the two types of samples are calculated. According to the statistical parameters of the two types of samples, the risk discrimination threshold is determined by maximum likelihood estimation. If the comprehensive risk value exceeds the risk discrimination threshold, it is determined that there is illegal excavation behavior. The excavation probability percentage is calculated according to the ratio of the comprehensive risk value to the risk discrimination threshold. The spatial coordinates of the disturbance source are determined by the intersection of the propagation vectors of multiple monitoring points. According to the excavation probability percentage, the risk level is divided into high, medium and low, and the early warning signal containing the excavation probability percentage, the coordinates of the disturbance source and the risk level is output.

[0078] For example, in an embodiment, a distributed sensor array is deployed every 10 meters along the underground cable path, each node containing a three-axis acceleration sensor, a piezoelectric vibration sensor and a signal conditioning circuit. When the soil is disturbed, the vibration wave propagates outward in the form of a spherical wave, and each monitoring point captures the vibration signal in turn. The instantaneous amplitude value is obtained by calculating the vector sum of the three-axis acceleration, reflecting the disturbance intensity at that point. Fourier transform converts the time domain vibration signal to the frequency domain, and the main frequency component represents the main vibration characteristics of the disturbance source, usually with a main frequency of 10-50 Hz, while the harmonic distribution reflects the complexity of the disturbance.

[0079] It should be noted that the construction of the propagation vector is based on the principle of wave front arrival time difference. The adjacent monitoring points record the arrival time of the same disturbance wave front, and the time difference multiplied by the wave speed in the soil is the propagation distance of the wave front. Combined with the three-dimensional spatial coordinates of the monitoring points, the propagation direction is determined by vector operation. The propagation speed varies depending on the soil type, about 200-400 meters per second in sand and about 100-200 meters per second in clay. The three-dimensional propagation vector contains information on the propagation direction, speed and attenuation characteristics of the disturbance wave. The fiber optic gyroscope continuously records the spatial attitude of the cable at a sampling rate of 1000 Hz, and the offset angle is obtained by integrating the angular velocity. The range of angle change amplitude reflects the difference between the maximum and minimum offsets of the cable during the monitoring period.

[0080] Specifically, the calculation process of the weight factor involves the standardization of multiple physical quantities. The amplitude normalization adopts the maximum value normalization method, which divides the amplitude values of all monitoring points by the maximum amplitude to obtain an amplitude weight factor between 0 and 1. This factor reflects the vibration intensity proportion of each monitoring point relative to the strongest disturbance point. The frequency domain weight factor is obtained by integrating the energy density of the frequency spectrum in the range of 0 to 100 Hz. The larger the integral value, the more concentrated the disturbance energy, and the frequency spectrum energy of illegal excavation is usually concentrated in a specific frequency band. The direction weight factor is obtained by calculating the absolute value of the cosine of the angle between the propagation vector and the cable orientation. When the disturbance propagation direction is parallel to the cable, the factor is close to 1, indicating that the disturbance has the greatest impact on the cable; when it is perpendicular, it is close to 0, indicating the minimum impact. The angle sensitivity coefficient is defined as the ratio of the measured angle change amplitude to the reference value of the angle change under normal working conditions. The reference value is obtained by statistical analysis of the angle change during the disturbance-free period, which is usually within 0.5 degrees.

[0081] Preferably, the calculation of the comprehensive risk value uses the weighted summation method. The amplitude weight factor, frequency domain weight factor and direction weight factor are assigned weight coefficients of 0.3, 0.3 and 0.4 respectively. These coefficients are determined by regression analysis of a large amount of historical data. Each weight factor is multiplied by the corresponding coefficient, then multiplied by the angle sensitivity coefficient, and finally summed to obtain the comprehensive risk value. The physical meaning of this value is a comprehensive evaluation index of the threat of disturbance to the cable, with a numerical range usually between 0 and 10.

[0082] Illustratively, the statistical analysis process of historical monitoring records includes two stages of data classification and parameter estimation. The monitoring records of the past 6 months are extracted from the database, and the records are classified into normal construction and illegal excavation according to the event log. The normal construction category includes legal operations such as road maintenance and pipeline laying, and the risk value is usually below 2; the illegal excavation category includes theft and destructive construction, and the risk value is usually above 4. The mean and standard deviation of the two types of samples are calculated respectively. The risk value mean of normal construction is about 1.2, and the standard deviation is 0.5; the risk value mean of illegal excavation is about 5.8, and the standard deviation is 1.2.

[0083] In one possible implementation, maximum likelihood estimation is used to determine the optimal discriminant threshold. Assuming that both classes of risk values follow normal distribution, the discriminant threshold is solved by maximizing the likelihood function of the classification accuracy. The threshold is usually located near the intersection of the two distributions, about 3.2. When the integrated risk value calculated in real time exceeds 3.2, the probability of determining the existence of illegal mining behavior is greater than 95%. Further, the quantitative calculation of the mining probability is based on the Bayesian posterior probability theory. The ratio of the integrated risk value to the discriminant threshold is used as the likelihood ratio, and the posterior probability is calculated in combination with the prior probability. When the ratio is 1.5, the mining probability is about 75%; when the ratio is 2, the probability is more than 90%. The multi-point intersection method is used for disturbance source positioning, and at least three propagation vectors of monitoring points are needed. The reverse elongation line of each propagation vector represents the possible direction of the disturbance source, and the spatial intersection area of multiple elongation lines is the position of the disturbance source, and the positioning accuracy can reach within 5 meters.

[0084] It can be understood that the risk level division adopts a three-level system. The mining probability below 60% is low risk, and a blue warning is issued; the mining probability of 60%-85% is medium risk, a yellow warning is issued and the inspection personnel are notified; and the mining probability above 85% is high risk, a red warning is issued and an automatic alarm is triggered. The warning signal is output in a structured data format, including time stamp, mining probability percentage, longitude and latitude coordinates of the disturbance source, risk level identification, recommended response measures and other information, and is transmitted to the monitoring center in real time through a wireless network.

[0085] S104, according to the cable offset angle aggravating risk level to determine the anchoring device tightening strength requirement, and obtain the real-time change rate of the current cable offset angle, combine the anchoring device tightening strength requirement and the real-time change rate of the offset angle to dynamically adjust the tightening strength, generate anchoring device control instruction, the instruction includes tightening strength value, execution time and adjustment frequency.

[0086] According to the cable offset angle aggravation risk level and the preset force reference value corresponding relationship, the basic tightening force demand value is determined, wherein the high risk level corresponds to the high force reference value, the medium risk level corresponds to the medium force reference value, and the low risk level corresponds to the low force reference value. At the same time, the real-time sampling data of the current cable offset angle is obtained from the angle sensor, the ratio of the angle difference value of adjacent sampling points to the time interval is calculated, and the real-time change rate of the offset angle is obtained. According to the positive and negative of the real-time change rate, the offset trend is judged, if the change rate is positive and the value continues to increase, a dynamic compensation amount proportional to the change rate is added to the basic tightening force demand value; if the change rate is negative or tends to be stable, the basic tightening force demand value is maintained. The actual tightening force value is determined by adding the basic tightening force demand value and the dynamic compensation amount. According to the comparison result of the actual tightening force value and the preset force threshold value, the execution time is determined, which is immediately executed when exceeding the high threshold value, delayed executed when between the high threshold value and the low threshold value, and periodically executed when below the low threshold value. According to the offset angle aggravation risk level, the adjustment frequency is determined, wherein the high risk level corresponds to the high frequency adjustment, the medium risk level corresponds to the medium frequency adjustment, and the low risk level corresponds to the low frequency adjustment. The control instruction data packet is constructed by encoding the actual tightening force value, the execution time and the adjustment frequency. The check code and the time stamp are added in the data packet to generate the anchoring device control instruction containing the tightening force value, the execution time and the adjustment frequency.

[0087] For example, in an embodiment, the corresponding relationship between the cable offset angle aggravation risk level and the force reference value is established by historical data statistics. The actual tightening records of the anchoring device under different risk levels in the past year are collected, and the average tightening force required for each risk level is counted. The force reference value corresponding to the high risk level is set to 800-1200 Newton, which can provide sufficient constraint force when the cable offset is aggravated; the medium risk level corresponds to 400-800 Newton, which maintains the basic stability of the cable; and the low risk level corresponds to 200-400 Newton, which is for preventive fixation.

[0088] It should be noted that the real-time change rate of the offset angle is obtained by high-frequency sampling. The angle sensor collects the cable spatial posture data at a frequency of 100 Hz, and records three components of the pitch angle, roll angle and yaw angle at each sampling point. The difference in angle vector between adjacent sampling points reflects the angle change amount within 10 milliseconds, and the instantaneous change rate is obtained by dividing the time interval of 0.01 seconds. The positive value of the change rate indicates that the offset angle is increasing, the negative value indicates that the offset angle is decreasing, and the zero value indicates that the angle remains stable. The calculation of the dynamic compensation amount is based on the multiplication relationship between the change rate and the compensation coefficient. When the change rate is positive and continuously increasing, it indicates that there is a continuous external force acting to cause the cable offset to intensify, and at this time the dynamic compensation amount is equal to the change rate multiplied by the preset compensation coefficient. The compensation coefficient is determined according to the soil type and the cable material, and the compensation coefficient is 50 Newton·seconds / degree in a sandy soil environment and 80 Newton·seconds / degree in a clay environment. If the change rate is 2 degrees per second, the dynamic compensation amount in a sandy soil environment is 100 Newton. This proportional relationship ensures that the tightening intensity can be increased accordingly with the increase of the offset speed, realizing adaptive adjustment. When the change rate is negative or tends to be stable, it indicates that the offset is controlled or is recovering, at which time no additional compensation is added and the basic intensity is maintained.

[0089] Preferably, the actual tightening intensity value is obtained by adding the basic value and the dynamic compensation amount, and this value needs to be limited to protect the anchoring device. The upper limit is set to 1500 Newton to prevent excessive tightening from damaging the cable insulation layer; the lower limit is set to 100 Newton to ensure that the minimum fixing force is maintained. The actual tightening intensity value is updated every 100 milliseconds to form a continuous intensity control curve.

[0090] Exemplarily, the determination of the execution time adopts a three-level threshold judgment mechanism. The high threshold is set to 1000 Newton, when the actual tightening intensity value exceeds this threshold, the control instruction is immediately executed, the response time is less than 50 milliseconds, and it is suitable for fast response in emergency situations. The low threshold is set to 500 Newton, and when the intensity value is lower than this threshold, it is executed according to the preset period, and the period is 5 seconds, which is suitable for regular maintenance adjustment. In the case between the two thresholds, the delay is 1 second, which avoids frequent adjustment and maintains the necessary response speed.

[0091] In one possible implementation, the adjustment frequency is dynamically selected according to the risk level. High risk level corresponds to high frequency adjustment of 10 Hz, adjusting the anchoring force 10 times per second, ensuring timely response to rapid changes in the offset angle. The medium risk level uses 5 Hz medium frequency adjustment to balance the adjustment effect and device life. The low risk level uses 1 Hz low frequency adjustment to reduce unnecessary mechanical action and prolong the service life of the anchoring device. The selection of the adjustment frequency also takes into account the fatigue characteristics of the cable material to avoid material fatigue damage caused by high frequency adjustment. Further, the construction of the control instruction data packet follows a specific encoding format. The data packet header contains a 4-byte device identification code for identifying the target anchoring device. The tightening force value occupies 2 bytes, encoded with a minimum resolution of 0.1 Newton. The execution time occupies 2 bytes, recorded in milliseconds. The adjustment frequency occupies 1 byte, with a resolution of 0.1 Hz. The data packet tail adds a 2-byte cyclic redundancy check code and a 4-byte timestamp.

[0092] It can be understood that the check code is calculated using the CRC-16 algorithm to ensure the integrity of data transmission. The timestamp records the exact time when the instruction is generated, which is used to synchronize the coordinated action of multiple anchoring devices. The complete control instruction data packet is 15 bytes long, sent to the underground anchoring device through the wireless communication module in LoRa protocol, with a transmission distance of up to 2 kilometers, and the signal attenuation through the soil is within an acceptable range.

[0093] In one embodiment, when the cable offset angle is monitored to increase rapidly from 2 degrees to 5 degrees, with a change rate of 3 degrees per second, the system determines that it is in a high risk state. The basic tightening force requirement value is 1000 Newton, the dynamic compensation amount is 150 Newton, and the actual tightening force value is 1150 Newton. Since it exceeds the high threshold, the execution time is set to immediate execution, and the adjustment frequency is 10 Hz. The control instruction reaches the anchoring device within 20 milliseconds and starts execution, effectively containing the further aggravation of the cable offset.

[0094] S105, send control instructions to the underground intelligent anchoring device, and monitor the change of the anchoring device's offset angle after the cable is fixed, to obtain the cable fixation tightening state.

[0095] The wireless communication module sends control instructions to the underground intelligent anchoring device using a preset communication protocol, and records the time when the instructions are sent. The anchoring device returns an acknowledgement signal containing the receiving time and execution status identifier after receiving the instructions, and the execution status identifier in the acknowledgement signal is used to determine whether the instructions are successfully received. During the execution of the tightening action of the anchoring device, the real-time value of the cable offset angle is continuously monitored, the initial offset angle before tightening and the angle change sequence during tightening are recorded. The ratio of the difference value of adjacent sampling points in the angle change sequence to the time interval is calculated to obtain the change rate. If the change rate changes from positive to negative, it indicates that the offset is controlled. By comparing the initial offset angle with the stable offset angle after tightening, the difference between the two is calculated to obtain the angle recovery amount. According to the percentage of the angle recovery amount to the initial offset angle, the cable fixing and tightening state is determined: if the percentage exceeds the preset high threshold, it is a normal tightening state, if it is between the high threshold and the low threshold, it is an under-tightening state, and if it is lower than the low threshold, it is an over-tightening state.

[0096] For example, in one embodiment, the wireless communication module uses the LoRa communication protocol to send control instructions to the underground intelligent anchoring device. The LoRa protocol has long-distance transmission and strong penetration capability, and the signal attenuation is small in underground environment. The time when the instructions are sent is recorded with a millisecond timestamp, which is used for subsequent communication quality evaluation. The communication module built-in the anchoring device returns an acknowledgement signal immediately after receiving the instructions, and the signal contains a 16-bit execution status identifier code, of which the first 8 bits represent the receiving state and the last 8 bits represent the execution preparation state.

[0097] It should be noted that the monitoring during the execution of the tightening action of the anchoring device uses a high-frequency continuous sampling method. The angle sensor collects cable offset angle data at a frequency of 50Hz, forming a dense angle change sequence. The initial offset angle is defined as the average value of the angle within 10 seconds before the start of the tightening action, which is used to establish a comparison reference. The change rate is calculated by dividing the angle difference of two adjacent sampling points by the sampling interval of 0.02 seconds, with the unit of degree / second. When the change rate of the last 5 sampling points changes from positive to negative, it is determined that the offset trend is effectively controlled.

[0098] Specifically, the calculation of the angle recovery amount involves the comparison of the angles before and after tightening. The stable offset angle after tightening is defined as the average value of the angle within 30 seconds after the end of the tightening action, ensuring that the cable reaches a new equilibrium state. The difference between the initial offset angle and the stable offset angle is the angle recovery amount, which reflects the actual tightening effect of the anchoring device. The percentage of the angle recovery amount to the initial offset angle is used to evaluate the tightening efficiency, and the higher the percentage, the better the tightening effect.

[0099] Preferably, the determination of the cable fixation tightening state adopts a three-level threshold system. The high threshold is set to 70%, when the angle recovery percentage exceeds this value, it is determined to be a normal tightening state, indicating that the anchoring device effectively restricts the cable deviation. The low threshold is set to 30%, when the percentage is lower than this value, it is a over-tightening state, which may exist anchoring device failure or cable material restrictions. Between 30% and 70% is an under-tightening state, which needs further adjustment of the tightening parameters.

[0100] In one possible implementation, the tightening state information is fed back to the monitoring center in the form of a state code. The normal tightening state is coded as 01, the under-tightening state is coded as 10, and the over-tightening state is coded as 11. The state code is packaged together with the time stamp and device identification into a state report, which is uploaded every 5 seconds to realize continuous monitoring of the cable fixation effect.

[0101] Real-time monitoring of the tightening action of the anchoring device, collecting the deviation angle, tension strength and deformation data of the cable during the fixation process, analyzing the deviation angle change rate, tension distribution and fixation point stability of the cable according to the deviation angle, tension strength and deformation data during the fixation process, and obtaining the corresponding cable fixation tightening state, which includes the completely fixed state, the slack state and the over-tightening state.

[0102] Real-time monitoring of the tightening action execution process of the anchoring device, collecting the deviation angle time series data of the cable during the fixation process, the tension value measured by the tension sensor and the deformation amount recorded by the strain gauge. The difference operation is performed on the deviation angle time series data to obtain the angle increment of adjacent sampling points, which is divided by the sampling time interval to obtain the deviation angle change rate. At the same time, the distribution characteristics of the tension value in the length direction of the cable are extracted, the ratio of the tension difference value and the distance between adjacent measuring points is calculated to obtain the tension gradient. According to the time series of the deviation angle change rate, the sliding window method is used to calculate the mean and standard deviation of the change rate, if the standard deviation is less than the preset stability threshold, it is determined that the angle change enters the stable state. Calculate the variance of the tension gradient at each measuring point as the spatial non-uniformity, and if the non-uniformity exceeds the preset upper limit, it indicates that there is stress concentration. According to the ratio of the deformation amount and the allowable strain of the material, the strain level of the cable is determined. The stable state of the angle change is quantified as a stability index, the stress concentration degree is quantified as a concentration index, and the strain level is taken as the third dimension to construct an evaluation space. In the evaluation space, when the stability is high, the concentration is low, and the strain level is moderate, it is determined to be a completely fixed state; when the stability is low and the tension value is less than the preset lower limit, it is determined to be a slack state; when the strain level exceeds the preset upper limit or the concentration is too high, it is determined to be an over-tightening state. According to the position of the current state point in the evaluation space and the closeness to the typical characteristic values of the three states, the final cable fixation tightening state is determined, and the determination results of the completely fixed state, the slack state or the over-tightening state are output.

[0103] Exemplarily, in one embodiment, the distributed sensor network is composed of angle sensors, tension sensors, and strain gauges, with an integrated monitoring node every 5 meters along the cable. The angle sensor adopts MEMS gyroscope technology, capable of real-time acquisition of spatial posture data of the cable at a frequency of 100 Hz. The tension sensor adopts a resistance strain principle, with a range of 0-2000 Newton and an accuracy of 0.1%. The strain gauge is directly attached to the surface of the cable, and the small deformation is measured through a Wheatstone bridge circuit, with a resolution of 0.001 mm.

[0104] It should be noted that the calculation of the rate of change of the offset angle uses a numerical differentiation method. During the tightening action of the anchoring device, the angle sensor continuously records the offset angle value of the cable, forming a time series data stream. The angle difference between two adjacent sampling points reflects the angle change in 0.01 seconds, and the instantaneous change rate is obtained by dividing the time interval. In order to reduce the influence of measurement noise, a five-point central difference formula is used for smoothing, and the change rate is equal to the angle difference between the last two points divided by 4 times the sampling interval. The calculation of the tension gradient is based on the difference in tension between adjacent measuring points. If the tension of the i-th measuring point is Fi, the tension of the i+1-th measuring point is Fi+1, and the distance between the two measuring points is 5 meters, then the tension gradient is (Fi+1-Fi) / 5, with the unit of Newton / meter. The tension gradient reflects the rate of change of tension in space, and the larger the gradient, the more uneven the stress distribution.

[0105] Specifically, the sliding window method is used to evaluate the stability of the angle change. The window width is set to 2 seconds, containing 200 sampling points. The mean and standard deviation of the change rate are calculated within each window, the mean reflects the overall level of the change rate, and the standard deviation reflects the fluctuation degree of the change rate. When the standard deviation is less than the preset stability threshold of 0.5 degrees / second, it indicates that the angle change rate remains relatively constant within the time window, and is determined as a stable state. The window slides forward with a step size of 0.1 seconds, achieving continuous evaluation of stability. The spatial unevenness is obtained by calculating the variance of the tension gradient of all measuring points. The larger the variance value, the more uneven the tension distribution. When the unevenness exceeds the preset upper limit of 100 (Newton / meter) 2 , it indicates that there is a local stress concentration phenomenon, which may cause local damage to the cable.

[0106] Preferably, the determination of the cable strain level needs to consider the material properties. The insulation layer of the underground communication cable usually adopts polyethylene material, with a permissible strain of 3%. The deformation is directly measured by the strain gauge, and if the measured deformation is ΔL and the original length is L0, then the strain ε = ΔL / L0. The strain level is defined as the ratio of the measured strain to the permissible strain. The ratio is less than 0.3 for low strain area, 0.3-0.7 for moderate strain area, and greater than 0.7 for high strain area. This classification ensures the safety margin of the cable under different strain levels.

[0107] Exemplarily, the construction of the evaluation space involves a quantitative process of three dimensions. The stability index is calculated by the inverse of the standard deviation of the angle change rate, the smaller the standard deviation, the higher the stability, and the value range is normalized to 0-1. The concentration index is equal to the ratio of the spatial non-uniformity to the preset upper limit, also normalized to the range of 0-1. The strain level directly adopts the ratio of the foregoing, and the range is also between 0-1. The three normalized indexes constitute the coordinate system of the three-dimensional evaluation space, and the state at each moment can be represented as a point in the space.

[0108] In a possible implementation, the typical characteristic values of the three fastening states are obtained by a large amount of historical data statistics. The typical characteristics of the fully fixed state are that the stability is greater than 0.8, the concentration is less than 0.3, and the strain level is between 0.3-0.5. In this state, the cable is effectively fixed, and neither too large displacement nor damage due to excessive tightening occurs. The typical characteristics of the slack state are that the stability is less than 0.3, the tension value is less than 200 Newton, and the strain level is less than 0.1. At this time, the anchoring device fails to provide sufficient restraint force, and the cable is in a free swinging state. The typical characteristics of the over-tightening state are that the strain level is greater than 0.7 or the concentration is greater than 0.7, indicating that the cable bears excessive stress and there is a risk of rupture. Further, the determination of the final state is based on the fuzzy membership principle. The Euclidean distance of the current state point to the three typical characteristic values is calculated, the closer the distance, the higher the membership. The membership is calculated by a Gaussian function, and the σ parameter is set to 0.2 to ensure that the membership changes within a reasonable range. The state with the highest membership is selected as the current determination result, and when the highest membership is less than 0.6, the uncertain state is output, prompting manual confirmation.

[0109] S106, according to the cable fixing and fastening state, the recovery degree of the offset angle is determined, if the recovery degree of the offset angle is unchanged or decreased, the alarm is triggered to activate the sound and light alarm system, and the soil disturbance frequency after the alarm is triggered is identified.

[0110] According to the cable fixing and fastening state, the recovery amount of the current offset angle relative to the initial offset angle before tightening is calculated, and the recovery amount is divided by the initial offset angle to obtain the offset angle recovery percentage. By comparing the recovery percentage with the recovery percentage of the previous monitoring period, if it remains unchanged or decreases, it is determined that the offset angle recovery degree is abnormal. When the offset angle recovery degree is abnormal, an activation instruction is sent to the alarm, and the alarm drives the sound and light alarm device to emit sound and light signals. At the same time, the soil vibration signal in a preset time period after the alarm is triggered is collected, the frequency spectrum of the vibration signal is extracted through Fourier transform, and the main frequency component is identified as the soil disturbance frequency.

[0111] For example, in one embodiment, the calculation of the recovery percentage of the offset angle is based on real-time monitoring data. The initial offset angle before tightening is determined by the average value of the angle within 10 seconds before the anchoring device is activated, and the current offset angle is the instantaneous value collected in real time. The recovery amount is equal to the absolute value of the initial offset angle minus the current offset angle, and the recovery percentage is equal to the recovery amount divided by the initial offset angle multiplied by 100%. The monitoring period is set to 5 minutes, and the recovery percentage value is recorded at the end of each period.

[0112] It should be noted that the determination of the abnormality of the recovery degree uses a comparison method. If the recovery percentage of the current period is less than or equal to the value of the previous period, it indicates that the cable offset has not been improved or has worsened, and it is determined to be an abnormal state. This determination method can timely discover the failure of the anchoring device or the occurrence of a new disturbance source.

[0113] Preferably, the audible and visual alarm device includes a high-power buzzer and an LED stroboscopic lamp. After receiving the activation instruction, the alarm outputs a 12V DC voltage to drive the buzzer to emit an alarm sound of 110 decibels, and controls the LED lamp to flash red light at a frequency of 5Hz. Within 30 seconds after the alarm is triggered, the vibration sensor records the soil vibration signal at a sampling rate of 200Hz, and extracts the frequency spectrum in the range of 0-100Hz through 512-point fast Fourier transform. The peak frequency is the main frequency of soil disturbance.

[0114] S107, obtain the response effect of the anti-theft monitoring by analyzing the change of the soil disturbance frequency before and after the alarm is triggered and the cable offset angle.

[0115] Obtain the soil disturbance frequency sequence within a preset time period before the alarm is triggered and the disturbance frequency sequence of the same length after the alarm is triggered, calculate the average values of the two frequency sequences respectively, and obtain the frequency drop value by subtracting the average value after the alarm is triggered from the average value before the alarm is triggered. At the same time, the cable offset angle at the moment when the alarm is triggered is extracted as the initial angle, the offset angle at the end of the preset time period after the alarm is triggered is obtained as the terminal angle, and the angle recovery amount is calculated by subtracting the initial angle from the terminal angle. According to the ratio of the frequency drop value to the average frequency before the alarm is triggered, the signal weakening degree percentage is calculated. The cable offset angle recovery degree percentage is obtained by the ratio of the angle recovery amount to the initial angle. Record the time interval from detecting the abnormality to the alarm emitting the audible and visual signal, compare the interval with the preset response time standard, and obtain the alarm triggering timeliness score. The signal weakening degree, the cable offset angle recovery degree and the alarm triggering timeliness score are used as the three components of the response effect of the anti-theft monitoring, and the response effect of the anti-theft monitoring including the signal weakening degree, the cable offset angle recovery degree and the alarm triggering timeliness is formed.

[0116] For example, in one embodiment, the collection time period of the soil disturbance frequency sequence is set to 30 seconds before and after the alarm trigger. The vibration sensor records the soil vibration signal at a sampling rate of 100 Hz, and the dominant frequency value of each second is extracted by fast Fourier transform to form a sequence containing 30 frequency values. The frequency sequence before the trigger reflects the disturbance characteristics of normal excavation or theft activities, and the frequency sequence after the trigger reflects the disturbance changes under the influence of the alarm. The frequency average value is obtained by arithmetic average calculation, and the frequency drop value is equal to the average value before the trigger minus the average value after the trigger, and the positive value indicates that the disturbance is weakened, and the negative value indicates that the disturbance is enhanced.

[0117] It should be noted that the calculation of the signal weakening degree percentage reflects the deterrent effect of the alarm. When the illegal excavator hears the alarm sound and light signal, he will usually stop or slow down the excavation action, resulting in a decrease in soil disturbance frequency. The signal weakening degree is equal to the frequency drop value divided by the average frequency before the trigger and multiplied by 100%. A weakening degree of more than 60% indicates that the alarm deterrent effect is significant, 30%-60% is moderate, and less than 30% indicates that the intruder may not be effectively deterred. The calculation of the cable offset angle recovery degree is based on the angle recovery amount, which is equal to the absolute value of the difference between the angle after the trigger and the initial angle, and the recovery degree percentage reflects the correction ability of the anchoring device.

[0118] Specifically, the alarm trigger timeliness score uses a piecewise function method. The preset response time standard is 3 seconds, the actual response time is less than 1 second, the score is 100 points, 1-3 seconds linearly decreases to 60 points, more than 3 seconds but not more than 5 seconds, the score is 40 points, and more than 5 seconds, the score is 20 points. This scoring mechanism takes into account the impact of different response speeds on the anti-theft effect, and the faster the response, the more effectively the intruder can be deterred.

[0119] Preferably, the three components together constitute a complete evaluation of the anti-theft monitoring response effect. The signal weakening degree reflects the inhibitory effect of the alarm on the intrusion behavior, the cable offset angle recovery degree reflects the automatic correction ability of the system, and the alarm trigger timeliness evaluates the fast response performance of the system. The three indicators evaluate the comprehensive performance of the anti-theft monitoring system from different dimensions.

[0120] In one possible implementation, the anti-theft monitoring response effect can be further classified. When all three indicators are at a good level, it is determined to be a first-level response effect; two indicators are good for a second-level effect; only one indicator is good or all indicators are poor for a third-level effect.

[0121] The preferred embodiments of the application disclosed above are only to facilitate the elucidation of the application. The preferred embodiments do not describe all the details of the application and limit the application to the specific embodiments. Obviously, many modifications and variations can be made in light of the teachings above. The description is chosen and described in order to provide the best illustration of the application and its practical application to those skilled in the art and to enable those skilled in the art to best utilize the application. The application is limited only by the claims and their full scope and equivalents.

Claims

1. A theft prevention monitoring method based on a communication line, characterized by, The method comprises the following steps: obtaining the soil disturbance state and the cable position change in a target time period, obtaining the soil disturbance frequency and the cable offset angle, determining the soil disturbance propagation path according to the soil disturbance frequency and the cable offset angle, wherein a disturbance intensity spatial distribution map is constructed according to the numerical distribution of the soil disturbance frequency at each monitoring node, a disturbance propagation contour map is generated through the disturbance intensity spatial distribution map, and a disturbance propagation direction vector is fitted by combining the change gradient of the cable offset angle; the angle between the disturbance propagation direction vector and the cable trend, and the spatial distribution of the disturbance propagation contour map are determined to determine the soil disturbance propagation path; identifying the cable offset angle change corresponding to the soil disturbance propagation path to obtain the correlation between the soil disturbance propagation path and the cable offset angle, and determining the potential risk value of the cable subjected to soil disturbance according to the correlation; comparing the potential risk value with a preset risk threshold value to determine whether there is illegal excavation behavior, analyzing the change trend of the cable offset angle by continuously obtaining real-time soil disturbance state, and determining the cable offset angle aggravation risk level according to the change trend; determining the tightening intensity requirement of the anchoring device according to the cable offset angle aggravation risk level, simultaneously obtaining the real-time change rate of the cable offset angle, dynamically adjusting the tightening intensity by combining the tightening intensity requirement and the real-time change rate, and generating an anchoring device control instruction; sending the control instruction to the underground intelligent anchoring device, and monitoring the offset angle change of the anchoring device after the cable is fixed and tightened to obtain the cable fixed and tightened state; determining the offset angle recovery degree according to the cable fixed and tightened state, triggering the alarm to activate the sound and light alarm system if the offset angle recovery degree is unchanged or reduced, and identifying the soil disturbance frequency after the alarm is triggered; obtaining the anti-theft monitoring response effect by analyzing the soil disturbance frequency change and the cable offset angle before and after the alarm is triggered.

2. The communication line based theft monitoring method according to claim 1, wherein, The method comprises the following steps: obtaining the soil disturbance state and the cable position change in a target time period, obtaining the soil disturbance frequency and the cable offset angle, determining the soil disturbance propagation path according to the soil disturbance frequency and the cable offset angle, wherein a disturbance intensity spatial distribution map is constructed according to the numerical distribution of the soil disturbance frequency at each monitoring node, a disturbance propagation contour map is generated through the disturbance intensity spatial distribution map, and a disturbance propagation direction vector is fitted by combining the change gradient of the cable offset angle; the angle between the disturbance propagation direction vector and the cable trend, and the spatial distribution of the disturbance propagation contour map are determined to determine the soil disturbance propagation path; identifying the cable offset angle change corresponding to the soil disturbance propagation path to obtain the correlation between the soil disturbance propagation path and the cable offset angle, and determining the potential risk value of the cable subjected to soil disturbance according to the correlation; 3. The communication line based theft monitoring method according to claim 1, wherein, comparing the potential risk value with a preset risk threshold value to determine whether there is illegal excavation behavior, analyzing the change trend of the cable offset angle by continuously obtaining real-time soil disturbance state, and determining the cable offset angle aggravation risk level according to the change trend; determining the tightening intensity requirement of the anchoring device according to the cable offset angle aggravation risk level, simultaneously obtaining the real-time change rate of the cable offset angle, dynamically adjusting the tightening intensity by combining the tightening intensity requirement and the real-time change rate, and generating an anchoring device control instruction; sending the control instruction to the underground intelligent anchoring device, and monitoring the offset angle change of the anchoring device after the cable is fixed and tightened to obtain the cable fixed and tightened state; determining the offset angle recovery degree according to the cable fixed and tightened state, triggering the alarm to activate the sound and light alarm system if the offset angle recovery degree is unchanged or reduced, and identifying the soil disturbance frequency after the alarm is triggered; obtaining the anti-theft monitoring response effect by analyzing the soil disturbance frequency change and the cable offset angle before and after the alarm is triggered. The method comprises the following steps: obtaining the soil disturbance state and the cable position change in a target time period, obtaining the soil disturbance frequency and the cable offset angle, determining the soil disturbance propagation path according to the soil disturbance frequency and the cable offset angle, wherein a disturbance intensity spatial distribution map is constructed according to the numerical distribution of the soil disturbance frequency at each monitoring node, a disturbance propagation contour map is generated through the disturbance intensity spatial distribution map, and a disturbance propagation direction vector is fitted by combining the change gradient of the cable offset angle; the angle between the disturbance propagation direction vector and the cable trend, and the spatial distribution of the disturbance propagation contour map are determined to determine the soil disturbance propagation path; identifying the cable offset angle change corresponding to the soil disturbance propagation path to obtain the correlation between the soil disturbance propagation path and the cable offset angle, and determining the potential risk value of the cable subjected to soil disturbance according to the correlation; comparing the potential risk value with a preset risk threshold value to determine whether there is illegal excavation behavior, analyzing the change trend of the cable offset angle by continuously obtaining real-time soil disturbance state, and determining the cable offset angle aggravation risk level according to the change trend; determining the tightening intensity requirement of the anchoring device according to the cable offset angle aggravation risk level, simultaneously obtaining the real-time change rate of the cable offset angle, dynamically adjusting the tightening intensity by combining the tightening intensity requirement and the real-time change rate, and generating an anchoring device control instruction; sending the control instruction to the underground intelligent anchoring device, and monitoring the offset angle change of the anchoring device after the cable is fixed and tightened to obtain the cable fixed and tightened state; determining the offset angle recovery degree according to the cable fixed and tightened state, triggering the alarm to activate the sound and light alarm system if the offset angle recovery degree is unchanged or reduced, and identifying the soil disturbance frequency after the alarm is triggered; obtaining the anti-theft monitoring response effect by analyzing the soil disturbance frequency change and the cable offset angle before and after the alarm is triggered. According to the time delay alignment soil disturbance signal and cable offset angle signal, the frequency band components of the cable offset angle signal are decomposed, the correlation coefficient of the frequency band components and the soil disturbance signal is calculated, and the correlation between the soil disturbance propagation path and the cable offset angle is obtained.

4. The communication line based theft monitoring method according to claim 1, wherein, According to the potential risk value and the preset risk threshold, it is determined whether there is illegal excavation behavior, and the change trend of the cable offset angle is analyzed by continuously acquiring the real-time soil disturbance state, including: According to the potential risk value and the preset risk threshold, it is determined whether there is illegal excavation behavior; If there is illegal excavation behavior, the vibration intensity of the real-time soil disturbance state and the real-time value of the cable offset angle are obtained, and the change rate of the cable offset angle is calculated; According to the change rate, the change curve is fitted, and the change trend of the cable offset angle is determined.

5. The communication line based theft monitoring method according to claim 1, wherein, According to the change trend, the cable offset angle aggravation risk level is determined, including: According to the change trend of the cable offset angle, the time change slope of the change rate is calculated; According to the time change slope and the duration, the cable offset angle aggravation risk level is determined, wherein the time change slope is positive and the duration exceeds the preset time length, which is a high risk level, the time change slope is positive but the duration is less than the preset time length, which is a medium risk level, and the time change slope is not positive, which is a low risk level; The time change slope is calculated by the time change slope, and the cable offset angle aggravation risk level is determined according to the offset acceleration value and the change trend.

6. The communication line based theft monitoring method according to claim 1, wherein, The generation of anchor device control instruction, including: According to the cable offset angle aggravation risk level, the basic tightening degree requirement value is determined; According to the real-time change rate of the cable offset angle, the basic tightening degree requirement value is adjusted to obtain the actual tightening degree value; According to the actual tightening degree value, the execution time and the adjustment frequency are determined, and the anchor device control instruction containing the actual tightening degree value, the execution time and the adjustment frequency is generated.

7. The communication line based burglar monitoring method according to claim 1, wherein The control instruction is sent to the underground intelligent anchor device, and the offset angle change of the anchor device after tightening the cable is monitored to obtain the cable fixing and tightening state, including: The control instruction is sent to the underground intelligent anchor device, and the sending time is recorded; The cable offset angle change during the tightening of the anchor device is monitored, the difference value of the cable offset angle before and after tightening is calculated, and the angle recovery amount is obtained; According to the percentage of the angle recovery amount in the initial offset angle, the cable fixing and tightening state is determined.

8. The communication line based burglar monitoring method according to claim 1, wherein The cable fixing and tightening state is obtained, including: The cable offset angle, tension value and deformation amount during the tightening of the anchor device are collected; According to the cable offset angle, the change rate is calculated, according to the tension value, the tension gradient is calculated, and according to The deformation amount determines the strain level; According to the change rate, the tension gradient and the strain level, the cable fixing and tightening state is determined as completely fixed state, loose state or over-tightening state.

9. The communication line based burglar monitoring method according to claim 1, wherein According to the cable fixing and tightening state, the offset angle recovery degree is determined, and if the offset angle recovery degree is unchanged or reduced, the alarm is triggered to activate the sound and light alarm system, including: According to the cable fixed fastening state, the recovery amount of the cable offset angle is calculated to obtain an offset angle recovery percentage; If the offset angle recovery percentage is unchanged or reduced compared with the previous period, an activation instruction is sent to the alarm to drive the audible and visual alarm device to issue a signal.

10. The communication line based burglar monitoring method according to claim 1, wherein The response effect of the anti-theft monitoring includes: A soil disturbance frequency sequence before and after the alarm is triggered is obtained, and a difference between the average values before and after the triggering is calculated to obtain a frequency drop value; According to the ratio of the frequency drop value to the average value of the frequency before the triggering, a signal weakening degree is obtained; According to the difference between the cable offset angles before and after the alarm triggering, a cable offset angle recovery degree is obtained; According to a comparison between the alarm triggering time interval and a preset standard, an alarm triggering timeliness score is obtained to form the response effect of the anti-theft monitoring including the signal weakening degree, the cable offset angle recovery degree, and the alarm triggering timeliness score.

Images