Tunnel cable external force disturbance monitoring method and device

Abstract

The application discloses a tunnel cable external force disturbance monitoring method and device, and belongs to the technical field of power system monitoring. The method comprises the following steps: collecting cable posture data of a tunnel cable in real time by using a capacitive sensor; extracting a plurality of discrete signal segments on a vibration acceleration signal by using an equal-frequency interval sampling method, and performing discrete Fourier transform on each discrete signal segment to obtain a discrete signal characteristic distribution; calculating a vibration cumulative energy mean value and a periodic characteristic intensity parameter based on the discrete signal characteristic distribution; determining a disturbance element of the tunnel cable according to the vibration cumulative energy mean value; determining a disturbance cycle type of the tunnel cable according to the periodic characteristic intensity parameter and the disturbance element; determining a disturbance type of the tunnel cable based on the disturbance element and the disturbance cycle type, and determining an adjustment measure of the tunnel cable according to the disturbance type, displacement and inclination. Therefore, by implementing the application, the problem of low tunnel cable disturbance identification accuracy in the prior art can be solved.

Description

Technical Field

[0001] This invention relates to the field of power system monitoring technology, and in particular to a method and device for monitoring external force disturbances in tunnel cables. Background Technology

[0002] As urban power grids develop towards intelligence and high load capacity, power cables, as a crucial component of power transmission, have a significant impact on the overall grid operation due to their safe and stable operation. During operation, cables are prone to loosening and falling due to background noise, excavation equipment, and manual digging. Currently, traditional cable inspection methods mostly rely on manual or periodic checks, which suffer from poor real-time performance, high missed detection rates, and slow response times, making it difficult to meet the demands of modern smart grids for online cable condition monitoring and early warning.

[0003] Currently, various methods have been developed for monitoring underground cables, including fiber optic sensing, acoustic sensing, and image monitoring. However, fiber optic sensing technology relies on long-distance, close-fitting installation with the cable, placing high demands on construction accuracy and adaptability to the site environment. In complex underground engineering environments, due to space constraints and unstable construction conditions, the deployment of fiber optic sensors is difficult, easily leading to poor contact and affecting the stability of monitoring results. Acoustic sensing technology monitors the condition by capturing sound signals generated during cable operation, theoretically possessing certain application potential. However, due to numerous noise sources in the underground environment, such as traffic vibrations and construction machinery, these can easily interfere with the normal recognition of acoustic sensors, resulting in decreased signal discrimination accuracy. Image monitoring solutions typically deploy cameras at predetermined intervals and combine them with image recognition algorithms to analyze potential hazards or environmental anomalies around the cable. However, limitations such as changing lighting conditions, blind spots, and complex installation environments pose practical challenges to their widespread adoption in large-scale, all-weather monitoring. Furthermore, current underground cable monitoring technologies often identify disturbances based on time-domain characteristics. However, in the strong electromagnetic and noisy environments where underground cables are located, time-domain signals can be overwhelmed by power frequency interference (50Hz), environmental vibration noise, etc., leading to a decrease in the accuracy of disturbance identification. Summary of the Invention

[0004] This invention provides a method and device for monitoring external force disturbances in tunnel cables, which can solve the problem of low accuracy in identifying disturbances in tunnel cables in the prior art.

[0005] To address the aforementioned technical problems, this invention provides a method for monitoring external force disturbances in tunnel cables, comprising: The cable attitude data of the tunnel cable is acquired in real time using capacitive sensors; wherein, the cable attitude data includes vibration acceleration signals, displacement and tilt angle; Using the equal frequency interval sampling method, several discrete signal segments are extracted from the vibration acceleration signal, and discrete Fourier transform is performed on each discrete signal segment to obtain the discrete signal characteristic distribution. The mean value of cumulative vibration energy and the periodic characteristic intensity parameter are calculated based on the discrete signal characteristic distribution. The disturbance element of the tunnel cable is determined based on the average cumulative vibration energy. The disturbance period type of the tunnel cable is determined based on the periodic characteristic intensity parameter and the disturbance element; The disturbance type of the tunnel cable is determined based on the disturbance element and the disturbance period type, and the adjustment measures for the tunnel cable are determined based on the disturbance type, the displacement, and the tilt angle.

[0006] As a preferred embodiment, the method of using equal-frequency interval sampling to extract several discrete signal segments from the vibration acceleration signal, and performing discrete Fourier transform on each discrete signal segment to obtain the discrete signal characteristic distribution, includes: The vibration acceleration signal is briefly extracted using a window function to form several short-time signal segments; The blocks based on each short-time signal segment are superimposed to obtain several periodically extended short-time signal blocks, and each periodically extended short-time signal block is determined as a discrete signal segment. Perform an N-point discrete Fourier transform on the discrete signal segment to obtain the discrete signal characteristic distribution.

[0007] As a preferred embodiment, the step of performing block superposition processing based on each short-time signal segment to obtain several periodically extended short-time signal blocks is as follows: In the formula, For a periodically extended short-time signal block with discrete index k and discrete time index n; It is a short-time signal segment; For window functions; This represents the number of discrete sampling points for a short-time signal segment. Offset the sliding window; For discrete indices of short-time signal segments; This is a discrete-time index.

[0008] As a preferred embodiment, performing an N-point discrete Fourier transform on the discrete signal segment to obtain the discrete signal characteristic distribution specifically involves: In the formula, The characteristic distribution of discrete signals; For a periodically extended short-time signal block with discrete index k and discrete time index n; For discrete indices of short-time signal segments; For discrete-time indexing; For discrete frequency indexing; This represents the number of discrete sampling points for a short-time signal segment.

[0009] As a preferred method, the average cumulative vibration energy is calculated using the following formula: In the formula, The average cumulative energy of vibration; The characteristic distribution of discrete signals; This is the discrete time index corresponding to the time point when the discrete signal segment first exceeds the set threshold. This is the discrete-time index corresponding to the termination time of the discrete signal segment; This refers to the discrete frequency index corresponding to the upper limit of the analog frequency response of the acceleration signal acquisition device. For discrete-time indexing; For discrete frequency indexes.

[0010] As a preferred option, the periodic characteristic strength parameters are calculated using the following formula: In the formula, For periodic characteristic strength parameters; This is the inverse operation form of the characteristic distribution of discrete signals; It is a 3dB bandwidth.

[0011] As a preferred embodiment, determining the disturbance period type of the tunnel cable based on the periodic characteristic intensity parameter and the disturbance element includes: The periodic intensity range is determined based on the perturbation element; When the periodic characteristic strength parameter is within the periodic strength range, the disturbance period type of the tunnel cable is determined to be periodic disturbance. When the periodic characteristic strength parameter is not within the periodic strength range, the disturbance period type of the tunnel cable is determined to be a non-periodic disturbance.

[0012] As a preferred embodiment, determining the adjustment measures for the tunnel cable based on the disturbance type, the displacement, and the tilt angle includes: The displacement is compared with a preset displacement threshold to obtain a first comparison result; The tilt angle is compared with a preset tilt angle threshold to obtain a second comparison result; The fault level of the tunnel cable is determined based on the first comparison result and the second comparison result; Based on the disturbance type and the fault level, adjustment measures for the tunnel cable are determined.

[0013] As a preferred embodiment, before extracting several discrete signal segments from the vibration acceleration signal using the equal-frequency interval sampling method and performing a discrete Fourier transform on each discrete signal segment to obtain the discrete signal characteristic distribution, the vibration acceleration signal is processed as follows: The vibration acceleration signal is decomposed into several vibration sub-signals; Each of the aforementioned resonant sub-signals is denoised to form several denoised resonant sub-signals; The noise-reduced oscillator signals are combined to form a noise-reduced vibration acceleration signal.

[0014] Accordingly, the present invention provides a monitoring device for external force disturbance of tunnel cables, comprising: a data acquisition module, a frequency domain analysis module, a feature calculation module, a disturbance element determination module, a disturbance period type determination module, and an adjustment module; The data acquisition module is used to acquire cable attitude data of the tunnel cable in real time using a capacitive sensor; wherein, the cable attitude data includes vibration acceleration signal, displacement and tilt angle; The frequency domain analysis module is used to extract several discrete signal segments from the vibration acceleration signal using the equal frequency interval sampling method, and to perform discrete Fourier transform on each discrete signal segment to obtain the discrete signal feature distribution. The feature calculation module is used to calculate the mean value of vibration cumulative energy and the periodic characteristic intensity parameter based on the feature distribution of the discrete signal, respectively. The disturbance element determination module is used to determine the disturbance element of the tunnel cable based on the average cumulative vibration energy. The disturbance cycle type determination module is used to determine the disturbance cycle type of the tunnel cable based on the cycle characteristic intensity parameter and the disturbance element; The adjustment module is used to determine the disturbance type of the tunnel cable based on the disturbance element and the disturbance period type, and to determine the adjustment measures for the tunnel cable according to the disturbance type, the displacement and the tilt angle.

[0015] Compared with the prior art, the embodiments of the present invention have the following beneficial effects: This invention provides a method for monitoring external force disturbances in tunnel cables. It utilizes a capacitive sensor to collect cable attitude data in real time. Using an equal-frequency interval sampling method, several discrete signal segments are extracted from the vibration acceleration signal, and a discrete Fourier transform is performed on each segment to obtain the discrete signal characteristic distribution. Based on the discrete signal characteristic distribution, the mean cumulative vibration energy and periodic characteristic intensity parameters are calculated. The disturbance element of the tunnel cable is determined based on the mean cumulative vibration energy. The disturbance period type of the tunnel cable is determined based on the periodic characteristic intensity parameters and the disturbance element. The disturbance type of the tunnel cable is determined based on the disturbance element and the disturbance period type, and adjustment measures for the tunnel cable are determined based on the disturbance type, displacement, and tilt angle. This invention uses a capacitive sensor to collect data from the tunnel cable. Due to its small size and ease of installation, it improves the convenience of data acquisition and can directly convert the collected electrical signals into digital signals, improving data processing efficiency. Then, by performing frequency domain analysis on the vibration acceleration signal, multi-dimensional features can be extracted, thereby accurately identifying the disturbance type, avoiding the influence of environmental factors on time-domain features, and effectively improving the accuracy of disturbance identification. Attached Figure Description

[0016] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments 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 from these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating an embodiment of the tunnel cable external force disturbance monitoring method provided by the present invention; Figure 2 This is a schematic diagram of one embodiment of the tunnel cable external force disturbance monitoring device provided by the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] 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 pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0020] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0021] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0022] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0023] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0024] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0025] See Figure 1To address the problem of low accuracy in identifying disturbances in tunnel cables in existing technologies, an embodiment of the present invention provides a method for monitoring external force disturbances in tunnel cables. This method includes steps 101 to 106, each step of which is detailed below: Step 101: Use a capacitive sensor to collect cable attitude data of the tunnel cable in real time; wherein, the cable attitude data includes vibration acceleration signal, displacement and tilt angle.

[0026] In this embodiment of the invention, the capacitive sensor features high bandwidth, high sensitivity, flexible deployment, and low cost, and its small size facilitates installation. The electrical signal output by the capacitive sensor can be directly converted into a digital signal by a data acquisition device, eliminating the need for dedicated demodulation equipment and effectively improving the convenience of data acquisition.

[0027] In this embodiment of the invention, when identifying external disturbances in tunnel cables, it is necessary to collect cable attitude data such as vibration acceleration signals, displacement, and tilt angle. The vibration acceleration signals are used to determine the type of external disturbance, while the displacement and tilt angle are used to determine whether the tunnel cable is experiencing any abnormalities.

[0028] In this embodiment of the invention, to improve detection sensitivity, the monitoring frequency of the capacitive sensor can be adaptively adjusted according to the real-time temperature and humidity environment inside the tunnel (applicable temperature range -30℃ to 135℃) to achieve dynamic optimization of the sensing strategy and energy efficiency control. Specifically, the basic monitoring frequency can be set to a default of once per second (1Hz), suitable for the normal temperature and humidity range (temperature: -30℃~50℃, humidity: 30%~70%). When the tunnel cable is in a high-temperature and high-humidity environment (temperature > 50℃ or humidity > 70%), the monitoring frequency is increased to twice per second (2Hz) to enhance real-time monitoring of the cable status. When the tunnel cable is in a low-temperature and low-humidity environment (temperature < -30℃ or humidity < 30%), the monitoring frequency is reduced to once every 2 seconds (0.5Hz) to reduce power consumption while ensuring the acquisition of critical data. When the tunnel cable is under extreme conditions (temperature > 100℃ or humidity > 90%), the monitoring frequency is further increased to five times per second (5Hz), triggering a system self-check to ensure equipment stability.

[0029] In this embodiment of the invention, for capacitive sensors, a dual-frequency calibration mechanism (360Hz and 2MHz) is automatically executed to maintain signal processing accuracy and ensure that the parameter drift of the device is controlled within ±0.5% FS. The dwell time of each frequency band is 0.1 seconds to 1 second and can be adaptively adjusted to ensure the stability and responsiveness of the system under various operating conditions. The formula corresponding to the dual-frequency calibration mechanism is as follows: In the formula, The change in electric field strength; The amplitude corresponding to frequency f; The phase component of the vibration signal acquired by the capacitive sensor in time-frequency analysis; For frequency; For time; This is the start time of the frequency band excitation; This is the termination time of the frequency band excitation.

[0030] In this embodiment of the invention, when a cable is damaged by external forces, common types of external disturbances include typical interferences such as pneumatic drilling, mechanical excavation, and pile driving. These external force signals typically manifest as low-frequency vibration signals distributed in the range of hundreds of hertz to kilohertz. The MEMS accelerometer (ADXL1002) has a wide linear frequency response range (DC to 11 kHz, @4 dB), a large measurement capability (±40 g), low temperature drift (4%, suitable for -35°C to +120°C), low typical power consumption (approximately 1 mA), and excellent thermal noise performance (28 µg / √Hz), and can be directly integrated into embedded systems or IoT devices. Therefore, the MEMS accelerometer ADXL1002 can be used to collect the vibration acceleration signal of the tunnel cable.

[0031] Step 102: Using the equal frequency interval sampling method, extract several discrete signal segments from the vibration acceleration signal, and perform discrete Fourier transform on each discrete signal segment to obtain the discrete signal feature distribution.

[0032] As a preferred embodiment, the vibration acceleration signal is processed as follows before the discrete signal is extracted from the vibration acceleration signal by using the equal frequency interval sampling method and performing discrete Fourier transform on each discrete signal segment to obtain the discrete signal characteristic distribution: The vibration acceleration signal is decomposed into several vibration sub-signals; Each of the aforementioned resonant sub-signals is denoised to form several denoised resonant sub-signals; The noise-reduced oscillator signals are combined to form a noise-reduced vibration acceleration signal.

[0033] In this embodiment of the invention, to improve the accuracy of the data, the collected vibration acceleration signal needs to be denoised before frequency domain analysis. Specifically, wavelet packet decomposition is used to suppress noise in the vibration acceleration signal. First, the vibration acceleration signal is decomposed into multiple vibration sub-signals, each corresponding to a specific scale level; then, each vibration sub-signal is denoised to obtain a denoised vibration sub-signal; finally, the denoised vibration sub-signals are summarized to form a denoised vibration acceleration signal, which is then used for subsequent analysis. This denoising process can be implemented through a transformation operation, as shown below: in, This represents the vibration acceleration signal after noise reduction; The symbol represents the filter corresponding to the i-th wavelet packet decomposition. This represents the convolution operation. The set wavelet decomposition levels.

[0034] The noise reduction method of this invention can uniformly segment the vibration acceleration signal from low frequency to high frequency. In particular, the fine segmentation of the high-frequency band can match the frequency band difference between high-frequency disturbance components (such as high-frequency vibration transmitted by the rigid support) and high-frequency noise (such as sensor thermal noise) in the acceleration signal. If the acceleration signal is directly subjected to a one-size-fits-all noise reduction process, key features such as the instantaneous disturbance peak in the smooth time domain (the 103.4ms energy release process of a single impact) will be easily lost, resulting in a decrease in feature recognition. Therefore, the noise reduction method of this invention can retain more key features while suppressing power frequency interference and external environmental noise.

[0035] In this embodiment of the invention, since the external force disturbance of tunnel cables usually has a low correlation with the power frequency current carried by the cable, it is difficult to effectively distinguish them using conventional filtering methods. Therefore, after acquiring the vibration acceleration signal, it is necessary to extract features from the edge side, that is, to perform local identification near the sensor side, in order to improve the system's response capability and detection accuracy to sudden disturbance events. Therefore, a quadratic short-time Fourier transform can be used as the kernel function for analysis to perform time-frequency joint analysis on the acquired vibration acceleration signal, thereby providing a detailed characterization of the local energy distribution and frequency variation trend of the vibration signal.

[0036] In this embodiment of the invention, the quadratic short-time Fourier transform of a continuous signal can describe the joint characteristic distribution over time t and frequency f, expressed as: In the formula, The short-time Fourier transform energy spectrum of a continuous signal x(t) is represented by the short-time Fourier transform. The square of the modulus; Represents the short-time Fourier transform of a continuous signal x(t); The signal to be analyzed; For window functions; The time independent variable of the signal; For window functions Time center; The frequency is the independent variable. This is due to the introduction of a window function. This transformation possesses excellent local analysis capabilities, simultaneously preserving the time and frequency information of the signal, thereby enabling accurate characterization of non-stationary signals.

[0037] When time t is fixed... Considering the instantaneous spectrum at that moment provides a deeper understanding of the signal's local frequency structure. Therefore, to analyze the signal's local frequencies in depth, the equal-frequency-interval sampling method can be used to select sampling points in the frequency domain at equal intervals, thereby obtaining the discrete expression form corresponding to the continuous quadratic short-time Fourier transform (STFT).

[0038] In this embodiment of the invention, if the continuous quadratic short-time Fourier transform (STFT) is directly converted, its corresponding discrete expression can be obtained: In the formula, discrete signal The short-time Fourier transform energy spectrum; The discrete signal to be analyzed; For window functions; For window functions Time index; For window functions Time center; For frequency variables.

[0039] By using the equal-frequency interval sampling method to discretize the quadratic short-time Fourier transform (STFT), the characteristic distribution of the discrete signal can be obtained. .

[0040] As a preferred embodiment, the equal-frequency interval sampling method is used to extract several discrete signal segments from the vibration acceleration signal, and a discrete Fourier transform is performed on each discrete signal segment to obtain the discrete signal feature distribution, including: The vibration acceleration signal is briefly extracted using a window function to form several short-time signal segments; The blocks based on each short-time signal segment are superimposed to obtain several periodically extended short-time signal blocks, and each periodically extended short-time signal block is determined as a discrete signal segment. Perform an N-point discrete Fourier transform on the discrete signal segment to obtain the discrete signal characteristic distribution.

[0041] As a preferred embodiment, the block superposition process based on each short-time signal segment is performed to obtain several periodically extended short-time signal blocks, specifically: In the formula, For a periodically extended short-time signal block with discrete index k and discrete time index n; It is a short-time signal segment; For window functions; This represents the number of discrete sampling points for a short-time signal segment. Offset the sliding window; For discrete indices of short-time signal segments; This is a discrete-time index.

[0042] In this embodiment of the invention, a more in-depth frequency domain analysis of the vibration acceleration signal is performed. First, a window function is used to extract the vibration acceleration signal in a short time, forming multiple short-time signal segments. By performing block superposition processing on the short-time signal segments, a periodically extended short-time signal block adapted to the N-point discrete Fourier transform is obtained. The periodically extended short-time signal block is used as a discrete signal segment. This means taking the signal at the k-th position within the block as a reference time point n, and achieving periodic extension through sN.

[0043] In this embodiment of the invention, for each fixed n, the discrete signal segments can be processed. The N-point Discrete Fourier Transform is performed to obtain the discrete signal characteristic distribution, which is specifically represented as follows: In the formula, The characteristic distribution of discrete signals; For a periodically extended short-time signal block with discrete index k and discrete time index n; For discrete indices of short-time signal segments; For discrete-time indexing; For discrete frequency indexing; This represents the number of discrete sampling points for a short-time signal segment.

[0044] Step 103: Calculate the mean value of vibration cumulative energy and the periodic characteristic intensity parameter based on the discrete signal characteristic distribution.

[0045] In this embodiment of the invention, after obtaining the discrete signal characteristic distribution by performing frequency domain analysis on the vibration acceleration signal, the characteristics of the vibration acceleration signal, including the mean value of vibration cumulative energy and periodic characteristic intensity parameters, can be calculated based on the discrete signal characteristic distribution.

[0046] In a preferred embodiment, the average value of the cumulative vibration energy is the average value of the cumulative vibration energy, which can be calculated using the following formula: In the formula, The average cumulative energy of vibration; The characteristic distribution of discrete signals; This is the discrete time index corresponding to the time point when the discrete signal segment first exceeds the set threshold. This is the discrete-time index corresponding to the termination time of the discrete signal segment; This refers to the discrete frequency index corresponding to the upper limit of the analog frequency response of the acceleration signal acquisition device. For discrete-time indexing; For discrete frequency indexes.

[0047] In a preferred embodiment, the periodic characteristic intensity parameter is the amplitude characteristic that reflects the periodic regularity of the signal, and can be calculated using the following formula: In the formula, For periodic characteristic strength parameters; This is the inverse operation form of the characteristic distribution of discrete signals; The 3dB bandwidth, i.e., the center frequency bandwidth under 3dB conditions, is equivalent to the width between two frequency points when the amplitude of the vibration signal in the frequency domain drops to 0.707 times the peak value. It can be obtained directly after the signal is converted from the time domain to the frequency domain.

[0048] Step 104: Determine the disturbance element of the tunnel cable based on the average value of the accumulated vibration energy.

[0049] In this embodiment of the invention, the average cumulative vibration energy ranges for different external force disturbances. For example, the average cumulative vibration energy ranges from 9.8 to 15.3 for an impact drill; from 8.6 to 9.7 for an electric saw; from 6.2 to 8.3 for a single impact; and from 3.3 to 5.6 for a rammer. Since the average cumulative vibration energy ranges for different external force disturbances do not overlap, the calculated average cumulative vibration energy can be compared with the average cumulative vibration energy ranges for various external force disturbances to determine the disturbance element of the current tunnel cable.

[0050] Step 105: Determine the disturbance period type of the tunnel cable based on the periodic characteristic strength parameter and the disturbance element.

[0051] As a preferred embodiment, determining the disturbance period type of the tunnel cable based on the periodic characteristic intensity parameter and the disturbance element includes: The periodic intensity range is determined based on the perturbation element; When the periodic characteristic strength parameter is within the periodic strength range, the disturbance period type of the tunnel cable is determined to be periodic disturbance. When the periodic characteristic strength parameter is not within the periodic strength range, the disturbance period type of the tunnel cable is determined to be a non-periodic disturbance.

[0052] In this embodiment of the invention, the types of external force disturbances include periodic disturbances and aperiodic disturbances. The periodicity of the external force disturbance can be determined based on the calculated periodic characteristic strength parameter. Different external force disturbances correspond to different periodic strength ranges. When the calculated periodic characteristic strength parameter is within the periodic strength range, the current external force disturbance can be considered a periodic disturbance. Therefore, after determining the disturbance element of the current tunnel cable through the average accumulated vibration energy, the corresponding periodic strength range is determined based on the disturbance element. Then, the calculated periodic characteristic strength parameter is compared with the periodic strength range of the disturbance element. When the periodic characteristic strength parameter is within the periodic strength range, the disturbance period type of the tunnel cable is determined to be a periodic disturbance; otherwise, it is an aperiodic disturbance. For example, the periodic intensity range for an impact drill is (0.07~0.12); for an electric saw, it is (0.07~0.09); for a single impact, it is (0.63~0.82); and for a rammer, it is (0.21~0.35).

[0053] Step 106: Determine the disturbance type of the tunnel cable based on the disturbance element and the disturbance period type, and determine the adjustment measures for the tunnel cable according to the disturbance type, the displacement and the tilt angle.

[0054] In this embodiment of the invention, the disturbance type of the tunnel cable can be identified by analyzing the real-time acquired vibration acceleration signals. The real-time acquired displacement and tilt angles can reflect whether the current position and angle of the tunnel cable are abnormal. When an abnormal position or angle of the tunnel cable is detected, corresponding adjustment measures can be determined based on its disturbance type. Specifically, the disturbance type of the tunnel cable is determined based on the disturbance element and disturbance period type obtained from analyzing the vibration acceleration signals. For example, when the disturbance element is identified as an impact drill and the disturbance period type is periodic, the disturbance type of the tunnel cable is determined to be a periodic impact drill.

[0055] As a preferred embodiment, the adjustment measures for the tunnel cable are determined based on the disturbance type, the displacement, and the tilt angle, including: The displacement is compared with a preset displacement threshold to obtain a first comparison result; The tilt angle is compared with a preset tilt angle threshold to obtain a second comparison result; The fault level of the tunnel cable is determined based on the first comparison result and the second comparison result; Based on the disturbance type and the fault level, adjustment measures for the tunnel cable are determined.

[0056] In this embodiment of the invention, a displacement threshold and an inclination angle threshold are preset for the tunnel cable. When the real-time collected displacement and inclination angle do not exceed the displacement threshold and inclination angle threshold respectively, the current tunnel cable is considered to be normal and no adjustment is required. However, when the displacement exceeds the displacement threshold or the inclination angle exceeds the inclination angle threshold, the current tunnel cable is considered to have experienced abnormal displacement and adjustment is required according to the determined disturbance type. Specifically, by calculating the relative displacement difference between the displacement and the preset displacement threshold, and the relative inclination angle difference between the inclination angle and the inclination angle threshold, the fault level of the current tunnel cable can be determined based on the relative displacement difference and the relative inclination angle difference, and then different levels of adjustment measures can be adopted. For example, for tunnel cables without abnormalities, the adjustment measure adopted is to continue routine inspections; for low fault levels, the adjustment measure adopted is to focus on the cable status in that area during routine inspections; for medium fault levels, the adjustment measure adopted is to send a specialist to check if the fault level has not changed within 30 minutes and record the disturbance characteristic data so that maintenance personnel can make corresponding adjustments based on the disturbance characteristic data and disturbance type; for high fault levels, the adjustment measure adopted is to continuously monitor signal changes, immediately notify maintenance personnel to rush to the site, and suspend surrounding construction so that maintenance personnel can make corresponding adjustments based on the identified disturbance type.

[0057] In this embodiment of the invention, after determining the fault level of the tunnel cable, an alarm is triggered based on the fault level, and the alarm volume is dynamically adjusted according to the current ambient noise level. The adaptive adjustment mechanism of the alarm volume can be expressed by the following formula: In the formula, The alarm volume is adjusted adaptively; The reference volume set under standard noise conditions; This represents the currently detected ambient noise level. This is a reference noise value; Within an acceptable range of noise fluctuations; This is the adjustment coefficient, used to control the system's response sensitivity to changes in noise.

[0058] Implementing the above embodiments has the following effects: This invention provides a method for monitoring external force disturbances in tunnel cables. It utilizes a capacitive sensor to collect cable attitude data in real time. Using an equal-frequency interval sampling method, several discrete signal segments are extracted from the vibration acceleration signal, and a discrete Fourier transform is performed on each segment to obtain the discrete signal characteristic distribution. Based on the discrete signal characteristic distribution, the mean cumulative vibration energy and periodic characteristic intensity parameters are calculated. The disturbance element of the tunnel cable is determined based on the mean cumulative vibration energy. The disturbance period type of the tunnel cable is determined based on the periodic characteristic intensity parameters and the disturbance element. The disturbance type of the tunnel cable is determined based on the disturbance element and the disturbance period type, and adjustment measures for the tunnel cable are determined based on the disturbance type, displacement, and tilt angle. This invention uses a capacitive sensor to collect data from the tunnel cable. Due to its small size and ease of installation, it improves the convenience of data acquisition and can directly convert the collected electrical signals into digital signals, improving data processing efficiency. Then, by performing frequency domain analysis on the vibration acceleration signal, multi-dimensional features can be extracted, thereby accurately identifying the disturbance type, avoiding the influence of environmental factors on time-domain features, and effectively improving the accuracy of disturbance identification.

[0059] like Figure 2 As shown, based on the above method embodiments, corresponding apparatus embodiments are provided; One embodiment of the present invention provides a monitoring device for external force disturbance of tunnel cables, comprising: a data acquisition module, a frequency domain analysis module, a feature calculation module, a disturbance element determination module, a disturbance period type determination module, and an adjustment module; The data acquisition module is used to acquire cable attitude data of the tunnel cable in real time using a capacitive sensor; wherein, the cable attitude data includes vibration acceleration signal, displacement and tilt angle; The frequency domain analysis module is used to extract several discrete signal segments from the vibration acceleration signal using the equal frequency interval sampling method, and to perform discrete Fourier transform on each discrete signal segment to obtain the discrete signal feature distribution. The feature calculation module is used to calculate the mean value of vibration cumulative energy and the periodic characteristic intensity parameter based on the feature distribution of the discrete signal, respectively. The disturbance element determination module is used to determine the disturbance element of the tunnel cable based on the average cumulative vibration energy. The disturbance cycle type determination module is used to determine the disturbance cycle type of the tunnel cable based on the cycle characteristic intensity parameter and the disturbance element; The adjustment module is used to determine the disturbance type of the tunnel cable based on the disturbance element and the disturbance period type, and to determine the adjustment measures for the tunnel cable according to the disturbance type, the displacement and the tilt angle.

[0060] As a preferred embodiment, the equal-frequency interval sampling method is used to extract several discrete signal segments from the vibration acceleration signal, and a discrete Fourier transform is performed on each discrete signal segment to obtain the discrete signal feature distribution, including: The vibration acceleration signal is briefly extracted using a window function to form several short-time signal segments; The blocks based on each short-time signal segment are superimposed to obtain several periodically extended short-time signal blocks, and each periodically extended short-time signal block is determined as a discrete signal segment. Perform an N-point discrete Fourier transform on the discrete signal segment to obtain the discrete signal characteristic distribution.

[0061] As a preferred embodiment, the block superposition process based on each short-time signal segment is performed to obtain several periodically extended short-time signal blocks, specifically: In the formula, For a periodically extended short-time signal block with discrete index k and discrete time index n; It is a short-time signal segment; For window functions; This represents the number of discrete sampling points for a short-time signal segment. Offset the sliding window; For discrete indices of short-time signal segments; This is a discrete-time index.

[0062] As a preferred embodiment, an N-point discrete Fourier transform is performed on the discrete signal segment to obtain the discrete signal feature distribution, specifically as follows: In the formula, The characteristic distribution of discrete signals; For a periodically extended short-time signal block with discrete index k and discrete time index n; For discrete indices of short-time signal segments; For discrete-time indexing; For discrete frequency indexing; This represents the number of discrete sampling points for a short-time signal segment.

[0063] As a preferred embodiment, the average cumulative vibration energy is calculated using the following formula: In the formula, The average cumulative energy of vibration; The characteristic distribution of discrete signals; This is the discrete time index corresponding to the time point when the discrete signal segment first exceeds the set threshold. This is the discrete-time index corresponding to the termination time of the discrete signal segment; This refers to the discrete frequency index corresponding to the upper limit of the analog frequency response of the acceleration signal acquisition device. For discrete-time indexing; For discrete frequency indexes.

[0064] As a preferred embodiment, the periodic characteristic strength parameter is calculated using the following formula: In the formula, For periodic characteristic strength parameters; This is the inverse operation form of the characteristic distribution of discrete signals; It is a 3dB bandwidth.

[0065] As a preferred embodiment, determining the disturbance period type of the tunnel cable based on the periodic characteristic intensity parameter and the disturbance element includes: The periodic intensity range is determined based on the perturbation element; When the periodic characteristic strength parameter is within the periodic strength range, the disturbance period type of the tunnel cable is determined to be periodic disturbance. When the periodic characteristic strength parameter is not within the periodic strength range, the disturbance period type of the tunnel cable is determined to be a non-periodic disturbance.

[0066] As a preferred embodiment, the adjustment measures for the tunnel cable are determined based on the disturbance type, the displacement, and the tilt angle, including: The displacement is compared with a preset displacement threshold to obtain a first comparison result; The tilt angle is compared with a preset tilt angle threshold to obtain a second comparison result; The fault level of the tunnel cable is determined based on the first comparison result and the second comparison result; Based on the disturbance type and the fault level, adjustment measures for the tunnel cable are determined.

[0067] As a preferred embodiment, the vibration acceleration signal is processed as follows before the discrete signal is extracted from the vibration acceleration signal by using the equal frequency interval sampling method and performing discrete Fourier transform on each discrete signal segment to obtain the discrete signal characteristic distribution: The vibration acceleration signal is decomposed into several vibration sub-signals; Each of the aforementioned resonant sub-signals is denoised to form several denoised resonant sub-signals; The noise-reduced oscillator signals are combined to form a noise-reduced vibration acceleration signal.

[0068] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can realize the method for monitoring external force disturbances in tunnel cables provided by any of the above-described method embodiments of the present invention.

[0069] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0070] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for monitoring external force disturbances in tunnel cables, characterized in that, include: The cable attitude data of the tunnel cable is acquired in real time using capacitive sensors; wherein, the cable attitude data includes vibration acceleration signals, displacement and tilt angle; Using the equal frequency interval sampling method, several discrete signal segments are extracted from the vibration acceleration signal, and discrete Fourier transform is performed on each discrete signal segment to obtain the discrete signal characteristic distribution. The mean value of cumulative vibration energy and the periodic characteristic intensity parameter are calculated based on the discrete signal characteristic distribution. The disturbance element of the tunnel cable is determined based on the average cumulative vibration energy. The disturbance period type of the tunnel cable is determined based on the periodic characteristic intensity parameter and the disturbance element; The disturbance type of the tunnel cable is determined based on the disturbance element and the disturbance period type, and the adjustment measures for the tunnel cable are determined according to the disturbance type, the displacement and the tilt angle.

2. The method for monitoring external force disturbances in tunnel cables according to claim 1, characterized in that, The method of using equal-frequency interval sampling extracts several discrete signal segments from the vibration acceleration signal, and performs discrete Fourier transform on each discrete signal segment to obtain the discrete signal characteristic distribution, including: The vibration acceleration signal is briefly extracted using a window function to form several short-time signal segments; The blocks based on each short-time signal segment are superimposed to obtain several periodically extended short-time signal blocks, and each periodically extended short-time signal block is determined as a discrete signal segment. Perform an N-point discrete Fourier transform on the discrete signal segment to obtain the discrete signal characteristic distribution.

3. The method for monitoring external force disturbances in tunnel cables according to claim 2, characterized in that, The step of performing block superposition processing on each short-time signal segment to obtain several periodically extended short-time signal blocks is as follows: In the formula, For a periodically extended short-time signal block with discrete index k and discrete time index n; It is a short-time signal segment; For window functions; This represents the number of discrete sampling points for a short-time signal segment. Offset the sliding window; For discrete indices of short-time signal segments; This is a discrete-time index.

4. The method for monitoring external force disturbances in tunnel cables according to claim 3, characterized in that, The step of performing an N-point discrete Fourier transform on the discrete signal segment to obtain the discrete signal characteristic distribution is as follows: In the formula, The characteristic distribution of discrete signals; For a periodically extended short-time signal block with discrete index k and discrete time index n; For discrete indices of short-time signal segments; For discrete-time indexing; For discrete frequency indexing; This represents the number of discrete sampling points for a short-time signal segment.

5. The method for monitoring external force disturbances in tunnel cables according to claim 4, characterized in that, The mean cumulative energy of vibration is calculated using the following formula: In the formula, The average cumulative energy of vibration; The characteristic distribution of discrete signals; This is the discrete time index corresponding to the time point when the discrete signal segment first exceeds the set threshold. This is the discrete-time index corresponding to the termination time of the discrete signal segment; This refers to the discrete frequency index corresponding to the upper limit of the analog frequency response of the acceleration signal acquisition device. For discrete-time indexing; For discrete frequency indexes.

6. The method for monitoring external force disturbances in tunnel cables according to claim 5, characterized in that, The periodic characteristic strength parameters are calculated using the following formula: In the formula, For periodic characteristic strength parameters; This is the inverse operation form of the characteristic distribution of discrete signals; It is a 3dB bandwidth.

7. The method for monitoring external force disturbances in tunnel cables according to claim 6, characterized in that, Determining the disturbance period type of the tunnel cable based on the periodic characteristic intensity parameter and the disturbance element includes: The periodic intensity range is determined based on the perturbation element; When the periodic characteristic strength parameter is within the periodic strength range, the disturbance period type of the tunnel cable is determined to be periodic disturbance. When the periodic characteristic strength parameter is not within the periodic strength range, the disturbance period type of the tunnel cable is determined to be a non-periodic disturbance.

8. The method for monitoring external force disturbances in tunnel cables according to claim 7, characterized in that, The step of determining the adjustment measures for the tunnel cable based on the disturbance type, the displacement, and the tilt angle includes: The displacement is compared with a preset displacement threshold to obtain a first comparison result; The tilt angle is compared with a preset tilt angle threshold to obtain a second comparison result; The fault level of the tunnel cable is determined based on the first comparison result and the second comparison result; Based on the disturbance type and the fault level, adjustment measures for the tunnel cable are determined.

9. The method for monitoring external force disturbances in tunnel cables according to claim 8, characterized in that, Before extracting several discrete signal segments from the vibration acceleration signal using the equal-frequency interval sampling method and performing a discrete Fourier transform on each discrete signal segment to obtain the discrete signal characteristic distribution, the vibration acceleration signal is processed as follows: The vibration acceleration signal is decomposed into several vibration sub-signals; Each of the aforementioned resonant sub-signals is denoised to form several denoised resonant sub-signals; The noise-reduced oscillator signals are combined to form a noise-reduced vibration acceleration signal.

10. A device for monitoring external force disturbance in tunnel cables, characterized in that, include: The system includes a data acquisition module, a frequency domain analysis module, a feature calculation module, a perturbation element determination module, a perturbation period type determination module, and an adjustment module. The data acquisition module is used to acquire cable attitude data of the tunnel cable in real time using a capacitive sensor; wherein, the cable attitude data includes vibration acceleration signal, displacement and tilt angle; The frequency domain analysis module is used to extract several discrete signal segments from the vibration acceleration signal using the equal frequency interval sampling method, and to perform discrete Fourier transform on each discrete signal segment to obtain the discrete signal feature distribution. The feature calculation module is used to calculate the mean value of vibration cumulative energy and the periodic characteristic intensity parameter based on the feature distribution of the discrete signal, respectively. The disturbance element determination module is used to determine the disturbance element of the tunnel cable based on the average cumulative vibration energy. The disturbance cycle type determination module is used to determine the disturbance cycle type of the tunnel cable based on the cycle characteristic intensity parameter and the disturbance element; The adjustment module is used to determine the disturbance type of the tunnel cable based on the disturbance element and the disturbance period type, and to determine the adjustment measures for the tunnel cable according to the disturbance type, the displacement and the tilt angle.

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