Multi-touch point positioning method and system integrating distributed acoustic wave and wireless co-judgment

Abstract

This invention relates to the field of optical cable safety monitoring and fault location technology, specifically disclosing a multi-touch point location method and system that integrates distributed acoustic sensing and wireless co-judgment. The method includes real-time demodulation of phase change signals, denoising the signals, performing variational mode decomposition and feature reconstruction on the denoised signals to generate enhanced signals, calculating the local energy of the enhanced signals, and determining potential touch points based on energy thresholds; performing cross-correlation analysis on potential touch points at multiple adjacent locations, identifying multiple peaks in the cross-correlation function, and calculating the spatial locations of multiple touch points; and spatiotemporally correlating the signals collected by wireless acoustic sensing nodes with distributed acoustic events to determine the target optical cable. By integrating distributed acoustic sensing and co-judgment mechanisms, multiple concurrent touch signals that overlap in time and space can be effectively separated and identified, the number of touch points can be accurately determined, and the intensity of each touch event can be linearly quantified.

Description

Technical Field

[0001] This invention relates to the field of optical cable safety monitoring and fault location technology, specifically to a multi-touch point location method and system that integrates distributed acoustic wave and wireless co-judgment. Background Technology

[0002] Distributed acoustic sensing technology, a rapidly developing fiber optic sensing technology in recent years, enables continuous monitoring of vibration and acoustic events distributed along optical fibers by detecting Rayleigh scattering signals generated when light propagates through the fiber. Due to its advantages such as long monitoring distance, high sensitivity, and resistance to electromagnetic interference, this technology has been gradually applied in fields such as optical cable security protection, pipeline intrusion detection, and power line galloping monitoring. Under ideal conditions, traditional distributed acoustic sensing systems can effectively detect and roughly locate single, high-intensity touch or intrusion events. However, with the increasing complexity of application scenarios, existing technologies have revealed significant limitations. When multiple touch points occur simultaneously within the monitoring area, the acoustic signals received by the system overlap, making it difficult for traditional methods to effectively distinguish and separate these concurrent events. This leads to the system's inability to accurately determine the true number of touch points, their individual locations, and the intensity of the touch, easily resulting in missed detections or misclassification of multiple events as a single event, severely restricting its application in scenarios requiring precise sensing.

[0003] Further investigation into the underlying technology reveals two main shortcomings of existing solutions: First, the perception mechanism is singular, relying solely on a single distributed acoustic wave sensing data stream without cross-validation and supplementation from data from other dimensions. This results in insufficient reliability and accuracy in decision-making when faced with complex background noise or concurrent events. Second, there is a bottleneck in signal processing capabilities. Acoustic signals attenuate and experience delays during propagation in long-distance optical fibers, and existing data processing algorithms are inadequate in addressing these physical limitations. They struggle to perform high-precision synchronous analysis and reconstruction of the spatiotemporal relationships between multiple touch points, leading to decreased positioning accuracy and slow system response.

[0004] Therefore, there is an urgent need for an innovative technical solution that can effectively overcome the effects of acoustic signal attenuation and time delay, and achieve real-time, accurate sensing and positioning of multiple touch points. This solution would address the inherent shortcomings of existing distributed acoustic sensing systems in terms of multi-event concurrency, accurate positioning, and adaptability to complex environments, and meet the ever-increasing demands for intelligent operation and maintenance and security protection of optical cables. Summary of the Invention

[0005] The purpose of this invention is to provide a multi-touch point positioning method and system that integrates distributed acoustic waves and wireless co-judgment to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A multi-touchpoint localization method integrating distributed acoustic wave and wireless co-judgment, the method comprising:

[0008] During the silent period, environmental background noise signals are collected, background energy baselines at each location are calculated, and energy thresholds for touch event detection are set.

[0009] The phase-change signal is demodulated in real time, the signal is denoised, the denoised signal is subjected to variational mode decomposition and feature reconstruction to generate an enhanced signal, the local energy of the enhanced signal is calculated, and potential touch points are determined based on the energy threshold.

[0010] Cross-correlation analysis is performed on potential touch points in multiple adjacent locations to identify multiple peaks in the cross-correlation function. Based on the time delay and sound wave propagation speed corresponding to the peaks, the spatial positions of multiple touch points are calculated.

[0011] By spatiotemporally correlating the signals collected by the wireless acoustic sensor node with distributed acoustic events, the target optical cable can be identified.

[0012] As a further embodiment of the present invention, the step of denoising the signal and performing variational mode decomposition and feature reconstruction on the denoised signal to generate an enhanced signal specifically includes:

[0013] Perform time-domain bandpass filtering on the signal to filter out noise outside the preset frequency band;

[0014] Wavelet threshold denoising is performed on the filtered signal to suppress background noise that overlaps with the touch frequency band;

[0015] Variational mode decomposition is performed on the denoised signal. The target mode component is selected based on the envelope spectral entropy of each mode component. The enhanced signal is then reconstructed based on the target mode component.

[0016] As a further embodiment of the present invention, the energy threshold is dynamically set based on the background energy baseline and its standard deviation.

[0017] As a further aspect of the present invention, high-precision synchronous calculation of the spatial positions of the multiple touch points is achieved by establishing and solving an overdetermined system of equations based on multiple cross-correlation time delays.

[0018] As a further embodiment of the present invention, the step of spatiotemporally correlating the signals collected by the wireless acoustic sensing node with distributed acoustic events to determine the target optical cable specifically includes:

[0019] When the confidence level is insufficient, the micro-perturbation generation device is triggered to apply a characteristic perturbation, calculate the correlation coefficient between the response signal and the preset template, and determine the target optical cable.

[0020] The present invention also provides a multi-touch point positioning system that integrates distributed acoustic wave and wireless co-judgment, the system comprising:

[0021] The threshold determination module is used to collect environmental background noise signals during the silent period, calculate the background energy baseline at each location, and set the energy threshold for touch event detection.

[0022] The first determination module is used to demodulate the phase change signal in real time, perform noise reduction on the signal, perform variational mode decomposition and feature reconstruction on the denoised signal to generate an enhanced signal, calculate the local energy of the enhanced signal, and determine the potential touch point based on the energy threshold.

[0023] The cross-correlation analysis module is used to perform cross-correlation analysis on potential touch points in multiple adjacent locations, identify multiple peaks in the cross-correlation function, and calculate the spatial location of multiple touch points based on the time delay and sound wave propagation speed corresponding to the peaks.

[0024] The correlation module is used to perform spatiotemporal correlation between the signals collected by the wireless acoustic sensor node and the distributed acoustic events to determine the target optical cable.

[0025] A distributed acoustic wave sensor host is used to acquire phase change signals from optical cables.

[0026] Wireless acoustic wave sensing nodes are used to collect spatial sound field signals.

[0027] As a further embodiment of the present invention, the wireless acoustic wave sensing node has a built-in high-precision clock module for time synchronization with the distributed acoustic wave sensing host.

[0028] Compared with existing technologies, the beneficial effects of this invention are as follows: By integrating distributed acoustic wave sensing and a co-judgment mechanism, this invention can effectively separate and identify multiple concurrent touch signals that are superimposed in time and space. It can not only accurately determine the number of touch points, but also linearly quantify the intensity of each touch event, fundamentally solving the problems of missed and false alarms caused by signal confusion in traditional single-sensor systems, and significantly improving the perception reliability in complex event scenarios. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention.

[0030] Figure 1 This is a flowchart illustrating the multi-touch point positioning method that integrates distributed acoustic wave and wireless co-judgment provided in an embodiment of the present invention. Detailed Implementation

[0031] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.

[0032] Figure 1 A flowchart illustrating a multi-touch point localization method that integrates distributed acoustic wave and wireless co-judgment is shown below. Figure 1 As shown in the embodiment of the present invention, the multi-touch point positioning method integrating distributed acoustic waves and wireless co-judgment includes:

[0033] During the silent period, environmental background noise signals are collected, background energy baselines at each location are calculated, and energy thresholds for touch event detection are set.

[0034] The phase-change signal is demodulated in real time, the signal is denoised, the denoised signal is subjected to variational mode decomposition and feature reconstruction to generate an enhanced signal, the local energy of the enhanced signal is calculated, and potential touch points are determined based on the energy threshold.

[0035] Cross-correlation analysis is performed on potential touch points in multiple adjacent locations to identify multiple peaks in the cross-correlation function. Based on the time delay and sound wave propagation speed corresponding to the peaks, the spatial positions of multiple touch points are calculated.

[0036] By spatiotemporally correlating the signals collected by the wireless acoustic sensor node with distributed acoustic events, the target optical cable can be identified.

[0037] In this embodiment, the optical cable safety inspection of a 10kV distribution network line is taken as an example:

[0038] The prototype system described in this invention is deployed on 10kV distribution network optical cable lines requiring safety monitoring. Specifically, this includes: connecting a single-mode communication optical cable to a distributed acoustic sensing (DAS) host; installing wireless acoustic sensing nodes on poles or key pipeline nodes, each with a built-in high-precision clock module to ensure time synchronization with the DAS host; and fixing a micro-disturbance generating device near the junction box of the optical cable to be identified. After completing the hardware connection, the online monitoring software for optical cable identification and positioning is started. The software reads the optical cable GIS map and completes system coordinate calibration and initialization.

[0039] After system startup, the DAS host continuously emits probe light towards the optical cable and collects backscattered Rayleigh signals. During the silent period without any touch events, the system continuously collects ambient background noise signals for a period of time (e.g., 5 minutes). Based on this signal, the background energy baseline at each location point is calculated. An energy threshold for touch event detection is set, which is dynamically set based on the background energy baseline and its standard deviation. The energy threshold is calculated as follows:

[0040] ,in The standard deviation of the background energy is used to establish a judgment benchmark for subsequent real-time monitoring.

[0041] In a preferred embodiment of the present invention, the step of denoising the signal and performing variational mode decomposition and feature reconstruction on the denoised signal to generate an enhanced signal specifically includes:

[0042] Perform time-domain bandpass filtering on the signal to filter out noise outside the preset frequency band;

[0043] Wavelet threshold denoising is performed on the filtered signal to suppress background noise that overlaps with the touch frequency band;

[0044] Variational mode decomposition is performed on the denoised signal. The target mode component is selected based on the envelope spectral entropy of each mode component. The enhanced signal is then reconstructed based on the target mode component.

[0045] In this embodiment, the system emits coherent probe light towards the optical cable via a distributed acoustic wave sensing device and detects the resulting backscattered Rayleigh light. When the optical cable is touched along its length, it causes localized strain in the fiber, thereby modulating the phase of the scattered light. This phase change... Changes in fiber optic length caused by touch They are directly proportional, and their relationship is described by the following formula:

[0046] ;

[0047] Where z is the sensing distance, t is time, and n is n. eff Let λ be the effective refractive index of the optical fiber and λ be the incident light wavelength. By demodulating this phase information, the system can acquire the amplitude and frequency information of a touch event in a linear and quantitative manner, achieving non-destructive acquisition. The system enters real-time monitoring mode. The DAS host continuously demodulates the phase signal at a sampling rate of 1000Hz. .

[0048] To effectively extract weak touch features from noise, the system executes a multi-level advanced preprocessing workflow. Its core lies in progressively filtering out noise and enhancing event features in the signal. The specific steps are as follows:

[0049] Primary noise reduction (time-domain filtering): First, the system uses a digital bandpass filter to filter out low-frequency drift and high-frequency thermal noise outside the typical touch event (e.g., 1Hz-500Hz) based on the frequency band characteristics of the event. This is a basic preprocessing step with low computational cost.

[0050] Intermediate denoising (time-frequency domain denoising): To further suppress background noise (such as wind noise and vehicle vibration) that overlaps with the event frequency band, the system employs wavelet threshold denoising. This method can simultaneously perform localized analysis of the signal in both the time and frequency domains.

[0051] The specific process is as follows: Select a wavelet basis (such as the Db4 wavelet) that resembles the shape of the touch signal, and perform multi-scale wavelet decomposition on the signal. Then, apply a soft or hard thresholding function to the decomposed wavelet coefficients, setting or shrinking coefficients with smaller amplitudes (usually corresponding to noise) to zero, while retaining coefficients with larger amplitudes (usually corresponding to the actual touch signal). Finally, reconstruct the signal using the processed wavelet coefficients to obtain a cleaner phase-change signal.

[0052] Advanced Feature Enhancement (Based on Signal Decomposition and Reconstruction): After wavelet denoising, the signal may still contain aliased signals generated by multiple vibration sources. To separate the independent touch event components, the system employs a variational mode decomposition algorithm.

[0053] First, a 1-500Hz digital bandpass filter is used for initial noise reduction. Then, a 5-level decomposition using Db4 wavelets is performed, followed by wavelet denoising using a soft thresholding function. Finally, the denoised signal undergoes variational mode decomposition (preset mode number K=5), and the envelope spectral entropy of each mode is calculated. The two mode components with the lowest entropy values ​​are selected to reconstruct the enhanced signal s. enhanced (z,t). Software calculates s in real time. enhanced The energy at position (z,t) is E(z0,t). When the energy at position z0 satisfies E(z0,t) > E... th When (z0), a potential touch event is determined to have occurred at that location, and the timestamp t0 and location z0 of the event are recorded.

[0054] Algorithm principle: VMD is a completely non-recursive signal decomposition method, the purpose of which is to decompose the original signal... Adaptively decomposed into K eigenmode functions with specific sparsity Each mode revolves around a center frequency. It is achieved by constructing and solving the following constrained variational problem:

[0055] ;

[0056] in, For the k-th modal component, Here, is the center frequency of the k-th mode, and j is the imaginary unit; This is a convolution operation; The original signal is represented by K, which represents the total number of preset modes. This is the Dirac function.

[0057] Application: The wavelet-denoised signal is input into the VMD algorithm, which automatically decomposes the signal into a series of modal components from high frequency to low frequency. The system identifies which modes are mainly dominated by regular touch events and which are residual unstructured noise by calculating the envelope spectral entropy (a measure of signal complexity / regularity) of each modal component. Subsequently, the system selects the modal components with lower envelope spectral entropy values ​​for linear superposition to reconstruct the enhanced touch signal. The characteristics of the event in the signal are significantly amplified.

[0058] Energy quantization: for the reconstructed enhanced signal Calculate its local energy E(z) to quantify the contact intensity:

[0059] ;

[0060] Where N is the number of sampling points within the analysis time window. The value of E(z) directly reflects the intensity of the touch event at that location.

[0061] Suppose that near time t0, the system detects energy exceedances at multiple adjacent but discontinuous locations z1, z2, and z3. To determine whether this is a wide-area event or multiple independent touch points, the system performs cross-correlation analysis. The signals from the same touch event at spatial locations z1 and z2 are extracted as s1(t) and s2(t), respectively, and their cross-correlation functions are calculated. :

[0062] ;

[0063] in, To represent any two positions z i and z j The cross-correlation function of the signal, s i (t) and s j (t) represents the enhanced acoustic signal (i.e., the signal after denoising and VMD reconstruction) acquired at the i-th and j-th positions, respectively, and is a function of time t; τ is the time delay in seconds (s), representing the time delay of signal s. j The amount of time shifted on the time axis.

[0064] By searching peak position It can accurately estimate the time difference of a signal arriving at two locations. By combining the speed of sound propagation *v* in the optical cable, the relative distance difference between the touch point and the two sensing positions can be calculated. :

[0065] ;

[0066] like The presence of multiple distinct peaks indicates the existence of multiple independent vibration sources. This can be determined by locating the time delay corresponding to each peak. And according to the formula (Here, v is taken as the longitudinal wave velocity of the sound wave in the optical cable, which is 1500m / s.) The distance difference is calculated, and combined with the geometric relationship of multiple sensing units, the precise coordinates of the two touch points P1(x1,y1) and P2(x2,y2) are calculated in the software.

[0067] By performing pairwise cross-correlation analysis on signals from multiple sensing locations and solving the overdetermined equations, the system can achieve high-precision synchronous positioning of the spatial locations of multiple touch points, effectively overcoming the errors caused by signal propagation delay.

[0068] In a preferred embodiment of the present invention, the step of determining the target optical cable by spatiotemporally correlating the signals collected by the wireless acoustic sensing node with distributed acoustic events specifically includes:

[0069] When the confidence level is insufficient, the micro-perturbation generation device is triggered to apply a characteristic perturbation, calculate the correlation coefficient between the response signal and the preset template, and determine the target optical cable.

[0070] In this embodiment, to improve recognition reliability, the system introduces wireless acoustic wave sensing nodes for collaborative judgment. First, high-precision clock synchronization technology is used to ensure that the timestamps of the distributed acoustic wave data and the wireless acoustic wave data are aligned.

[0071] Wireless acoustic nodes deployed on the poles synchronously collect a segment of acoustic signal. The software correlates the wireless signal with DAS events in time and space. If a wireless node also reports the presence of an abnormal acoustic wave during the same time period, the overall confidence level is increased, and the software directly marks P1 and P2 as high-confidence touch points on the map.

[0072] If the DAS detects an event but the wireless node is unaware of it, or if the event confidence level is in an ambiguous range (e.g., the cross-correlation peak is not sharp enough), the software automatically triggers a micro-perturbation generator. The micro-perturbation generator applies a micro-perturbation m(t) of a specific frequency (e.g., 50 Hz) for 1 second on the nearest fiber optic cable to be identified. The micro-perturbation signal m(t) will generate a response r with specific characteristics in the distributed acoustic sensing data. m (z,t). By calculating the response signal and the preset template m... template The correlation coefficient of (t) To verify identity: ;

[0073] in, The correlation coefficient is calculated at position z, and its value range is... ;r m(z,t) is the response signal generated by the micro-perturbation generator and collected in the distributed acoustic wave sensing system at position z and time t. In response to signal r m (z,t) is the average value within the time window; m template (t) is a preset template signal, that is, a standard signal form known to the system and emitted by the micro-perturbation generating device; template signal m template The average value of (t).

[0074] like The software identifies when the threshold is exceeded. The optical cable containing the maximum value is the target optical cable. This confirms the link identity of the optical cable and uniquely binds the touch event to that optical cable, thus confirming that the touch event occurred on that specific optical cable. This effectively solves the problems of crosstalk and misjudgment in multi-cable environments.

[0075] This invention, by integrating distributed acoustic sensing with a co-judgment mechanism, can effectively separate and identify multiple concurrent touch signals that overlap in time and space. It can not only accurately determine the number of touch points but also linearly quantify the intensity of each touch event, fundamentally solving the problems of missed and false alarms caused by signal confusion in traditional single-sensor systems, and significantly improving the perception reliability in complex event scenarios.

[0076] By introducing high-precision synchronous data processing technology, this invention can effectively compensate and calibrate the attenuation and time delay of acoustic signals during long-distance transmission, significantly improving the spatial resolution and absolute positioning accuracy of the positioning system. It can accurately determine the relative positional relationship between multiple touch points, effectively overcoming the adverse effects of complex geographical and environmental factors on positioning performance, and making centimeter-level or meter-level high-precision positioning possible in long-distance and complex scenarios.

[0077] Based on the Rayleigh scattering phase detection principle, a lossless coupling acquisition of a very small portion of the fiber optic transmission signal is achieved. The entire sensing and positioning process does not affect the normal communication services of the optical cable itself, realizing true "online" monitoring and avoiding service interruptions caused by maintenance and testing. This provides strong technical support for the continuous and safe operation of the optical cable.

[0078] Through the micro-disturbance generation device and the processing strategy for multiple contact points, it can effectively cope with the complex electromagnetic environment and multi-cable interference on site. The system has strong anti-interference ability and stable and reliable positioning results. It is very suitable for deployment and application in complex outdoor scenarios such as real power lines and communication trunk lines, and has extremely high engineering practical value and promotion prospects.

[0079] This invention also provides a multi-touch point positioning system that integrates distributed acoustic waves and wireless co-judgment, the system comprising:

[0080] The threshold determination module is used to collect environmental background noise signals during the silent period, calculate the background energy baseline at each location, and set the energy threshold for touch event detection.

[0081] The first determination module is used to demodulate the phase change signal in real time, perform noise reduction on the signal, perform variational mode decomposition and feature reconstruction on the denoised signal to generate an enhanced signal, calculate the local energy of the enhanced signal, and determine the potential touch point based on the energy threshold.

[0082] The cross-correlation analysis module is used to perform cross-correlation analysis on potential touch points in multiple adjacent locations, identify multiple peaks in the cross-correlation function, and calculate the spatial location of multiple touch points based on the time delay and sound wave propagation speed corresponding to the peaks.

[0083] The correlation module is used to perform spatiotemporal correlation between the signals collected by the wireless acoustic sensor node and the distributed acoustic events to determine the target optical cable.

[0084] A distributed acoustic wave sensor host is used to acquire phase change signals from optical cables.

[0085] Wireless acoustic wave sensing nodes are used to collect spatial sound field signals.

[0086] In this embodiment, online monitoring software is also included. This software serves as the final human-computer interface, displaying all processing results in real time. On the fiber optic cable route diagram on the main software interface, touch points P1 and P2 are precisely marked with flashing icons, and their touch intensity I(z) is displayed using color depth or numerical labels. Simultaneously, an alarm window pops up, displaying "At [time t0], multiple touches were detected at [locations P1, P2], risk level: 'Medium'." The time, location, intensity, processing logs, and alarm information of all touch events are recorded in the database for user query, statistics, and analysis, thereby achieving real-time monitoring and management of the fiber optic cable status.

[0087] It also includes a micro-disturbance generation device. The online monitoring software displays the optical cable topology, contact point location (displayed by overlaying geographical coordinates), contact intensity (presented in the form of heat map or energy bar) and system alarm logs in real time through a graphical interface, ultimately realizing real-time monitoring and management of the entire optical cable network.

[0088] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A multi-touch point positioning method integrating distributed acoustic waves and wireless co-judgment, characterized in that, The method includes: During the silent period, environmental background noise signals are collected, background energy baselines at each location are calculated, and energy thresholds for touch event detection are set. The phase-change signal is demodulated in real time, the signal is denoised, the denoised signal is subjected to variational mode decomposition and feature reconstruction to generate an enhanced signal, the local energy of the enhanced signal is calculated, and potential touch points are determined based on the energy threshold. Cross-correlation analysis is performed on potential touch points in multiple adjacent locations to identify multiple peaks in the cross-correlation function. Based on the time delay and sound wave propagation speed corresponding to the peaks, the spatial positions of multiple touch points are calculated. The signals collected by the wireless acoustic wave sensor node are spatiotemporally correlated with distributed acoustic wave events to determine the target optical cable. It also includes a multi-touch point positioning system that integrates distributed acoustic waves and wireless co-judgment, the system comprising: The threshold determination module is used to collect environmental background noise signals during the silent period, calculate the background energy baseline at each location, and set the energy threshold for touch event detection. The first determination module is used to demodulate the phase change signal in real time, perform noise reduction on the signal, perform variational mode decomposition and feature reconstruction on the denoised signal to generate an enhanced signal, calculate the local energy of the enhanced signal, and determine the potential touch point based on the energy threshold. The cross-correlation analysis module is used to perform cross-correlation analysis on potential touch points in multiple adjacent locations, identify multiple peaks in the cross-correlation function, and calculate the spatial location of multiple touch points based on the time delay and sound wave propagation speed corresponding to the peaks. The correlation module is used to perform spatiotemporal correlation between the signals collected by the wireless acoustic sensor node and the distributed acoustic events to determine the target optical cable. A distributed acoustic wave sensor host is used to acquire phase change signals from optical cables. Wireless acoustic wave sensing nodes are used to collect spatial sound field signals; The wireless acoustic wave sensor node has a built-in high-precision clock module for time synchronization with the distributed acoustic wave sensor host.

2. The multi-touch point positioning method integrating distributed acoustic waves and wireless co-judgment as described in claim 1, characterized in that, The steps of denoising the signal and performing variational mode decomposition and feature reconstruction on the denoised signal to generate an enhanced signal specifically include: Perform time-domain bandpass filtering on the signal to filter out noise outside the preset frequency band; Wavelet threshold denoising is performed on the filtered signal to suppress background noise that overlaps with the touch frequency band; Variational mode decomposition is performed on the denoised signal. The target mode component is selected based on the envelope spectral entropy of each mode component. The enhanced signal is then reconstructed based on the target mode component.

3. The multi-touch point positioning method integrating distributed acoustic waves and wireless co-judgment as described in claim 1, characterized in that, The energy threshold is dynamically set based on the background energy baseline and its standard deviation.

4. The multi-touch point positioning method integrating distributed acoustic waves and wireless co-judgment as described in claim 1, characterized in that, By establishing and solving an overdetermined system of equations based on multiple cross-correlation time delays, high-precision synchronous calculation of the spatial positions of the multiple touch points is achieved.

5. The multi-touch point positioning method integrating distributed acoustic waves and wireless co-judgment as described in claim 1, characterized in that, The step of spatiotemporally correlating the signals collected by the wireless acoustic sensing node with distributed acoustic events to determine the target optical cable specifically includes: When the confidence level is insufficient, the micro-perturbation generation device is triggered to apply a characteristic perturbation, calculate the correlation coefficient between the response signal and the preset template, and determine the target optical cable.

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