A water conservancy monitoring and early warning method and system based on edge computing

Abstract

The application is suitable for the technical field of water conservancy monitoring, and particularly relates to a water conservancy monitoring and early warning method and system based on edge computing. The method comprises the following steps: performing sound wave detection, collecting a response signal, extracting a corresponding defect signal from the response signal, and generating baseline data; transmitting a sound wave detection signal, receiving a sound wave signal, and extracting the arrival time of a reflected signal peak; constructing a time sequence of the arrival time of the reflected signal peak corresponding to the same preset defect, calculating the continuous change trend of a strain value with time and a strain rate; and issuing an early warning signal according to the comparison result of the strain rate and the strain cumulative value with a preset safety threshold. The application can realize deformation monitoring of each position of a dam surface layer by laying a two-dimensional grid sliding extra-sensing network on the dam surface, overcomes the limitation that a single-point sensor can only measure local information, improves the accuracy and precision of deformation monitoring, and has low laying cost and is convenient for later maintenance.

Description

Technical Field

[0001] This invention belongs to the field of water conservancy monitoring technology, and in particular relates to a water conservancy monitoring and early warning method and system based on edge computing. Background Technology

[0002] Dam safety monitoring is a core component of ensuring the long-term stable operation of water conservancy projects, with timely detection and early warning of dam surface deformation and cracks being particularly crucial. Existing monitoring methods mainly include point sensors and visual measurement methods. Point sensors can only acquire local information from discrete measuring points, making it difficult to achieve continuous coverage of the entire dam surface; while visual measurement methods can achieve area measurement, they are easily affected by environmental factors such as lighting, rain, and fog, and are difficult to achieve continuous monitoring around the clock.

[0003] Existing methods are mostly passive detection methods after damage occurs, lacking the ability to continuously perceive the deformation accumulation process and provide trend warnings. Summary of the Invention

[0004] The purpose of this invention is to provide an edge computing-based water conservancy monitoring and early warning method, which aims to solve the problem that existing methods are mostly passive detection after damage occurs, lacking the ability to continuously perceive the deformation accumulation process and provide trend early warning.

[0005] This invention is implemented as follows: an edge computing-based water conservancy monitoring and early warning method, the method comprising: Acoustic wave detection is performed based on a two-dimensional sensing network deployed on the surface of the dam. Response signals are collected, and corresponding defect signals are extracted from them to generate baseline data. The two-dimensional sensing network is composed of multiple meridian waveguide cables and multiple parallel waveguide cables intersecting each other. Pre-set defects are etched on both the meridian and parallel waveguide cables. According to a preset cycle, acoustic wave detection signals are transmitted to the two-dimensional sensing network, acoustic wave signals are received, and the arrival time of the reflection signal peaks corresponding to each preset defect is extracted based on the acoustic wave signals. The arrival times of the reflected signal peaks corresponding to the same preset defect are used to form a time series, and the continuous change trend and strain rate of the strain value of the waveguide cable segment between adjacent preset defects over time are calculated. Based on the comparison between the strain rate and the cumulative strain value and the preset safety threshold, an early warning signal is issued. The early warning signal is divided into multiple levels, and the processing strategies corresponding to different levels of early warning signals are different.

[0006] Preferably, the steps of transmitting acoustic wave detection signals to the two-dimensional sensing network according to a preset period, receiving acoustic wave signals, and extracting the arrival time of the reflection signal peaks corresponding to each preset defect based on the acoustic wave signals include: The emitted sound wave is controlled based on a preset waveform control function and then input into a two-dimensional sensing network. By continuously monitoring the receiver in the two-dimensional sensing network, the sound wave signal is obtained, and the sound wave signal under different emitted sound waves is obtained accordingly. The reflected signal peaks contained in the acoustic signal are extracted from the baseline data, and the arrival time of each reflected signal peak is recorded.

[0007] Preferably, the step of constructing a time series from the arrival times of the reflected signal peaks corresponding to the same preset defect, and calculating the continuous change trend and strain rate of the strain value of the waveguide cable segment between adjacent preset defects over time, includes: For each cable, the arrival times of the reflected signal peaks corresponding to the same preset defect in multiple periodic scans are arranged in the order of acquisition time to construct the arrival time sequence of the preset defect. Based on the arrival time sequence of two adjacent preset defects, the change in acoustic wave propagation time of the waveguide cable segment between the two adjacent preset defects is calculated. Combined with the acoustic velocity reference value of the waveguide cable, the strain value of the cable segment and its strain rate over time are calculated. When at least one cable segment of both the meridian waveguide and the parallel waveguide is found to have an abnormal strain rate, and the abnormal meridian segment intersects with the abnormal parallel segment, the intersecting area is determined to be a deformation risk area.

[0008] Preferably, the step of issuing a warning signal based on the comparison result of the strain rate and the cumulative strain value with a preset safety threshold, wherein the warning signal is divided into multiple levels and the processing strategy corresponding to different levels of warning signals is different, specifically includes: The strain rate and cumulative strain value of each waveguide cable segment are compared with a preset multi-level safety threshold, which includes at least a first-level threshold and a second-level threshold, wherein the second-level threshold is higher than the first-level threshold. When the strain rate or strain accumulation exceeds the first-level threshold but does not reach the second-level threshold, a first warning signal is issued, indicating that the deformation of the waveguide cable segment is abnormally active; when the strain rate or strain accumulation reaches the second-level threshold, a second warning signal is issued, indicating that the deformation of the waveguide cable segment is intensified. When the reflected signal peak corresponding to any geometric defect is missing, or the arrival time offset of the reflected signal peak exceeds the preset damage judgment threshold, it is determined that structural damage has occurred at the location of the preset defect, and a third warning signal is issued.

[0009] Preferably, the preset defects are evenly distributed with fixed intervals.

[0010] Another object of the present invention is to provide an edge computing-based water conservancy monitoring and early warning system, the system comprising: The baseline data acquisition module is used to perform acoustic wave detection based on a two-dimensional sensing network deployed on the surface of the dam, collect response signals, extract corresponding defect signals from them, and generate baseline data. The two-dimensional sensing network is composed of multiple meridian waveguide cables and multiple parallel waveguide cables intersecting each other. Pre-set defects are etched on both the meridian waveguide cables and the parallel waveguide cables. The continuous detection module is used to transmit acoustic detection signals to the two-dimensional sensing network according to a preset period, receive acoustic signals, and extract the arrival time of the reflection signal peaks corresponding to each preset defect based on the acoustic signals. The strain detection module is used to construct a time series of the arrival times of the reflected signal peaks corresponding to the same preset defect, and to calculate the continuous change trend and strain rate of the strain value of the waveguide cable segment between adjacent preset defects over time. The early warning classification module is used to issue early warning signals based on the comparison results of strain rate and strain accumulation value with preset safety thresholds. The early warning signals are divided into multiple levels, and the processing strategies corresponding to different levels of early warning signals are different.

[0011] Preferably, the continuous detection module includes: The sound wave emitting unit is used to control the emitted sound wave based on a preset waveform control function and input the emitted sound wave into the two-dimensional sensing network; The sound wave receiving unit is used to continuously monitor through the receiving end in the two-dimensional sensing network to obtain sound wave signals, and thereby obtain sound wave signals under different emitted sound waves. The signal detection unit is used to extract the reflected signal peaks contained in the acoustic signal based on the baseline data and record the arrival time of each reflected signal peak.

[0012] Preferably, the strain detection module includes: The time recording unit is used to arrange the arrival times of the reflected signal peaks corresponding to the same preset defect in multiple periodic scans of each cable according to the acquisition time order to construct the arrival time sequence of the preset defect. The strain calculation unit is used to calculate the change in acoustic wave propagation time of the waveguide cable segment between two adjacent preset defects based on the arrival time sequence of two adjacent preset defects, and to calculate the strain value of the cable segment and its strain rate over time by combining the acoustic velocity reference value of the waveguide cable. The risk area determination unit is used to determine the intersection area as a deformation risk area when at least one cable segment of both the meridian waveguide cable and the parallel waveguide cable has an abnormal strain rate detected, and the abnormal meridian segment and the abnormal parallel segment have an intersection area.

[0013] Preferably, the early warning classification module includes: The strain identification unit is used to compare the strain rate and cumulative strain value of each waveguide cable segment with a preset multi-level safety threshold. The multi-level safety threshold includes at least a first-level threshold and a second-level threshold, wherein the second-level threshold is higher than the first-level threshold. The basic early warning unit is used to issue a first early warning signal when the strain rate or strain accumulation value exceeds the first threshold but does not reach the second threshold, indicating that the deformation of the waveguide cable segment is abnormally active; and to issue a second early warning signal when the strain rate or strain accumulation value reaches the second threshold, indicating that the deformation of the waveguide cable segment is intensified. The enhanced early warning unit is used to determine that structural damage has occurred at the location of any preset defect when the reflection signal peak corresponding to any geometric defect is missing or the arrival time offset of the reflection signal peak exceeds the preset damage judgment threshold, and to issue a third early warning signal.

[0014] Preferably, the preset defects are evenly distributed with fixed intervals.

[0015] The edge computing-based water conservancy monitoring and early warning method provided by this invention can realize deformation monitoring at various locations on the dam surface by laying a two-dimensional grid sliding sensing network on the dam surface. This overcomes the limitation of single-point sensors that can only measure local information, improves the accuracy and precision of deformation monitoring, and has low installation cost and is easy to maintain later. Attached Figure Description

[0016] Figure 1 A flowchart illustrating the edge computing-based water conservancy monitoring and early warning method provided in this embodiment of the invention; Figure 2 This is an architecture diagram of a water conservancy monitoring and early warning system based on edge computing, provided in an embodiment of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0018] like Figure 1 The diagram shows a flowchart of a water conservancy monitoring and early warning method based on edge computing provided in an embodiment of the present invention. The method includes: S100 uses a two-dimensional sensing network deployed on the surface of the dam to detect acoustic waves, collect response signals, extract corresponding defect signals, and generate baseline data. The two-dimensional sensing network is composed of multiple meridian waveguide cables and multiple parallel waveguide cables. Pre-set defects are etched on both the meridian and parallel waveguide cables.

[0019] In this step, acoustic wave detection is performed based on a two-dimensional sensing network deployed on the surface of the dam. The two-dimensional sensing network consists of interwoven cables, acoustic wave transmitting devices, and acoustic wave receiving devices, namely, longitudinal waveguide cables and latitude waveguide cables. The cables are used to transmit acoustic waves. The acoustic wave transmitting devices are used to control the transmission parameters of the acoustic waves, such as the frequency and amplitude of the acoustic waves. The acoustic wave receiving devices are used to receive the acoustic wave signals transmitted by the cables. The acoustic wave signals include main signals and reflected signals. Each cable has a set of acoustic wave transmitting devices and a set of acoustic wave receiving devices at both ends. The cables are made of stainless steel, such as 316L stainless steel. Fixed defects are etched on the cables. These defects are generated by laser etching. The shape of the defects is a ring-shaped V-groove with a depth of 0.1 mm and a width of 0.2 mm. The diameter of the cable is 2 mm. The spacing between adjacent defects on the cable is 1 m. The surface of the cable is covered with a protective layer, and the intersections of the longitudinal and latitude lines are fixedly connected to form a sensing grid. After the two-dimensional sensing network is constructed, the sound wave transmitting device generates a sound wave signal according to a preset signal control function. The frequency range of this signal is 50kHz-200kHz. Simultaneously, the sound wave receiving device at the end of the cable monitors the signal and records the received sound wave data. During the transmission of the sound wave, when the main signal passes through a defect, a set of reflected signals will be generated. Since the spacing between the defects is fixed, under normal circumstances, the sound wave receiving device first receives the main signal, followed by multiple reflected wave signals with uniform spacing and identical parameters. The received sound wave signal is processed and features are extracted to identify the main signal and the reflected signals (i.e., reflected signal peaks). The position of the reflected signal peaks is recorded, as are the parameter characteristics of the reflected signal peaks, such as the spacing between adjacent peaks, the duration of a single peak, and the peak height. The arrival times of the reflection signal peaks corresponding to each defect extracted from the acoustic signal are shown in the table below:

[0020] S200 transmits acoustic wave detection signals to the two-dimensional sensing network according to a preset cycle, receives acoustic wave signals, and extracts the arrival time of the reflection signal peaks corresponding to each preset defect based on the acoustic wave signals.

[0021] In this step, acoustic wave detection signals are transmitted to the two-dimensional sensing network according to a preset cycle. After obtaining baseline data, it is used as a reference for detection according to a preset cycle, such as once a day. If there is special weather, the detection frequency can be actively increased. During detection, the corresponding acoustic wave signal is output according to the same acoustic wave control function. The acoustic wave signal is transmitted through a cable and received by an acoustic wave receiving device to obtain the acoustic wave signal. Based on the same extraction method, the reflection signal peaks contained in the acoustic wave signal are identified according to the parameter characteristics of the reflection signal peaks determined in the baseline data, and the arrival time of each reflection signal peak is recorded. Based on its arrival time, the defect corresponding to the reflection signal peak can be calculated.

[0022] S300 constructs a time series of arrival times of the reflected signal peaks corresponding to the same preset defect, and calculates the continuous change trend and strain rate of the strain value of the waveguide cable segment between adjacent preset defects over time.

[0023] In this step, the arrival times of the reflected signal peaks corresponding to the same preset defect are compiled into a time series. When sound waves are generated, they are emitted with different parameters, that is, the sound wave emission is controlled by different parameters such as frequency and amplitude. Therefore, the parameter characteristics of the reflected signal peaks are different under different excitation signals. Thus, the baseline data records the parameter characteristics of the reflected signal peaks under different excitation signals to facilitate the subsequent identification of reflected signal peaks. The arrival times of the reflected signal peaks of the same defect under different detection cycles are identified and a time series is generated. For example, if 100 consecutive detections are performed within a month, the arrival time of the reflected signal peak corresponding to defect No. 1 is recorded according to the detection time to obtain a time series. The strain value of the cable segment is calculated based on the time interval of the reflected signal peaks corresponding to adjacent defects, and the continuous change trend of the strain value over time and the strain rate are further calculated.

[0024] S400 issues an early warning signal based on the comparison between the strain rate and the cumulative strain value and the preset safety threshold. The early warning signal is divided into multiple levels, and the processing strategy corresponding to different levels of early warning signals is different.

[0025] In this step, based on the preset safety threshold, the strain rate and cumulative strain value corresponding to each cable segment are compared with it. Based on the comparison results of each cable segment and the preset classification, each cable segment is classified into different levels. Based on different warning signal levels, different processing strategies are output.

[0026] In a preferred embodiment of the present invention, the steps of transmitting acoustic detection signals to the two-dimensional sensing network at a preset period, receiving acoustic signals, and extracting the arrival time of the reflection signal peaks corresponding to each preset defect based on the acoustic signals include: S201 controls the emitted sound wave based on a preset waveform control function and inputs the emitted sound wave into the two-dimensional sensing network.

[0027] In this step, a preset waveform control function is retrieved. The waveform control function uses a linear chirp function to control the frequency of the emitted sound wave to continuously and smoothly scan from the starting frequency to the ending frequency within a preset time window. The generated sound wave detection signal is amplified and then input into the cable.

[0028] S202 continuously monitors the sound wave signal through the receiver in the two-dimensional sensing network, and obtains the sound wave signal under different emitted sound waves.

[0029] In this step, the acoustic wave signal from inside the cable is continuously monitored, and the mechanical vibration is converted into an electrical signal. When the emitted acoustic wave propagates along the waveguide cable, it will generate a partial reflection echo when it encounters a preset geometric defect. The remaining energy continues to propagate forward and eventually reaches the acoustic wave receiving device at the end along with the reflection echo generated by the defect. The acoustic wave receiving device converts the complete acoustic wave response signal, including the direct wave and the reflection echoes from each defect, into an electrical signal in real time.

[0030] S203, extract the reflected signal peaks contained in the acoustic signal based on the baseline data, and record the arrival time of each reflected signal peak.

[0031] In this step, a matched filtering algorithm is used to perform pulse compression processing on the received signal, compressing the frequency-sweeping transmitted waveform into a high-time-resolution pulse response signal, so that the reflected signal peaks corresponding to each preset defect appear clearly and independently. Baseline data is retrieved, and based on the theoretical occurrence time window and amplitude characteristics of each defect's reflected signal peak in the baseline data, each reflected signal peak is searched and identified within the corresponding time window in the current pulse response signal. For each successfully identified reflected signal peak, the time interval from the start of the transmitted sound wave to the arrival time of the signal peak at the receiver is measured as the arrival time of the reflected signal peak, and it is associated and stored with the waveguide cable's identifier, defect number, and acquisition timestamp.

[0032] In a preferred embodiment of the present invention, the step of constructing a time series from the arrival times of the reflected signal peaks corresponding to the same preset defect, and calculating the continuous change trend and strain rate of the strain value of the waveguide cable segment between adjacent preset defects over time includes: S301, for each cable, the arrival time of the reflected signal peak corresponding to the same preset defect in multiple periodic scans is arranged in the order of acquisition time to construct the arrival time sequence of the preset defect.

[0033] In this step, for each waveguide cable in the two-dimensional sensing network, the arrival time of the reflected signal peak corresponding to the same preset defect on the waveguide cable in each scan is extracted from the stored periodic scan data. Each periodic scan records the arrival time of the reflected signal peak of each preset defect on the waveguide cable according to the method described in step S2, forming a timestamp data group for that scan. Multiple arrival time values ​​of the same preset defect obtained at different acquisition times are arranged in the order of acquisition time to construct the arrival time sequence of the preset defect. The arrival time sequence is used to reflect the continuous evolution of the sound wave propagation time at the location of the preset defect with the dam operation time.

[0034] S302, based on the arrival time sequence of two adjacent preset defects, calculate the change in sound wave propagation time of the waveguide cable segment between the two adjacent preset defects, and combine the sound velocity reference value of the waveguide cable to calculate the strain value of the cable segment and its strain rate over time.

[0035] In this step, for two adjacent preset defects on each waveguide cable, piecewise strain calculation is performed using arrival time series to calculate the difference in arrival time between the two adjacent preset defects in the current scan. The difference between the arrival time of the adjacent defect pair in the healthy state and the time recorded in the baseline data. By comparison, the change in acoustic wave propagation time of the waveguide cable segment between adjacent defects is obtained. When the cable segment is stretched due to dam deformation, As the sound wave travels further within this segment, its propagation time increases accordingly. Based on the principle of acoustic elasticity, this change in propagation time is converted into a change in the length of the cable segment. The strain value of the cable segment was calculated: ; in, Let be the strain value of the i-th cable segment. This refers to the physical length of the cable segment in a healthy state. The equivalent velocity of sound for the waveguide cable; By performing linear regression on the strain values ​​calculated from multiple consecutive cycles of scanning, the rate of change of strain over time in the cable segment, i.e., the strain rate, is obtained.

[0036] S303, when at least one cable segment of both the meridian waveguide cable and the parallel waveguide cable is found to have an abnormal strain rate, and the abnormal meridian segment intersects with the abnormal parallel segment, the intersecting area is determined to be a deformation risk area.

[0037] In this step, after all cable strain rates have been updated, a cross-analysis of the strain rate distribution across the entire network is performed. All meridian waveguides and all parallel waveguides are traversed to identify abnormal cable segments whose strain rates exceed a preset abnormal threshold. When there is at least one abnormal cable segment in a meridian waveguide and at least one abnormal cable segment in a parallel waveguide, the physical positional relationship between the abnormal meridian segment and the abnormal parallel segment in the two-dimensional grid space is determined. If the longitudinal coverage area of ​​the abnormal meridian segment in the dam surface coordinate system overlaps or intersects with the transverse coverage area of ​​the abnormal parallel segment in the dam surface coordinate system, the grid cell corresponding to the overlapping or intersecting area is determined to be a deformation risk area.

[0038] In a preferred embodiment of the present invention, the step of issuing a warning signal based on the comparison result of the strain rate and the cumulative strain value with a preset safety threshold, wherein the warning signal is divided into multiple levels and the processing strategy corresponding to different levels of warning signals is different, specifically includes: S401, compare the strain rate and cumulative strain value of each waveguide cable segment with a preset multi-level safety threshold, wherein the multi-level safety threshold includes at least a first-level threshold and a second-level threshold, and the second-level threshold is higher than the first-level threshold.

[0039] In this step, the strain rate and cumulative strain value of each cable segment are compared with the pre-set multi-level safety thresholds. By setting the multi-level thresholds in a step-by-step manner, the risk of dam surface deformation is managed in a graded manner.

[0040] S402: When the strain rate or strain accumulation value exceeds the first-level threshold but does not reach the second-level threshold, a first warning signal is issued, indicating that the deformation of the waveguide cable segment is abnormally active; when the strain rate or strain accumulation value reaches the second-level threshold, a second warning signal is issued, indicating that the deformation of the waveguide cable segment is aggravated.

[0041] In this step, warning signals of corresponding levels are issued according to the preset graded response rules. When the strain rate or strain accumulation value of the deformation risk area exceeds the first-level threshold but does not reach the second-level threshold, it is determined that the deformation of the waveguide cable segment has entered an abnormally active stage, and a first warning signal, a yellow warning, is issued, prompting the monitoring and management personnel to pay closer attention to the waveguide cable segment. When the strain rate or strain accumulation value of a certain deformation risk area reaches or exceeds the second-level threshold, it is determined that the deformation of the waveguide cable segment has been significantly aggravated, and a second warning signal, an orange warning, is issued, indicating that the waveguide cable segment is at risk of cracking or instability.

[0042] S403, when the reflection signal peak corresponding to any geometric defect is missing, or the arrival time offset of the reflection signal peak exceeds the preset damage judgment threshold, it is determined that structural damage has occurred at the location of the preset defect, and a third warning signal is issued.

[0043] In this step, during the periodic scanning of each waveguide cable, the state integrity of the reflection signal peaks corresponding to each preset defect is continuously monitored. When the reflection signal peak corresponding to any preset defect occurs under one of the following two abnormal conditions, it is determined that irreversible structural damage has occurred at the location of the preset defect, and a third warning signal is issued, which is a red alarm. Permanent absence of reflected signal peak: When the reflected signal peak corresponding to the preset defect cannot be detected in multiple consecutive scans, it is determined that the waveguide cable at the location of the defect has broken, causing the sound wave to be unable to continue to propagate forward; The arrival time of the reflected signal peak is irreversibly shifted and exceeds the preset damage judgment threshold: When the arrival time of the reflected signal peak corresponding to a certain preset defect is continuously shifted relative to the baseline data, and the shift exceeds the preset damage judgment threshold, and the shift does not show any signs of rebound recovery in subsequent scans, it is determined that the waveguide cable at that location has undergone permanent plastic deformation and the dam structure has suffered substantial damage. The third early warning signal includes information such as the waveguide cable number, defect number, spatial coordinates, and anomaly type at the location of the damage.

[0044] like Figure 2 As shown, in a preferred embodiment of the present invention, a water conservancy monitoring and early warning system based on edge computing, the system includes: The baseline data acquisition module 100 is used to perform acoustic wave detection based on a two-dimensional sensing network deployed on the surface of the dam, collect response signals, extract corresponding defect signals from them, and generate baseline data. The two-dimensional sensing network is composed of multiple meridian waveguide cables and multiple parallel waveguide cables intersecting each other. Pre-set defects are etched on both the meridian waveguide cables and the parallel waveguide cables.

[0045] The continuous detection module 200 is used to transmit acoustic wave detection signals to the two-dimensional sensing network according to a preset period, receive acoustic wave signals, and extract the arrival time of the reflection signal peaks corresponding to each preset defect based on the acoustic wave signals.

[0046] In this system, the continuous detection module 200 includes: The sound wave emitting unit is used to control the emitted sound wave based on a preset waveform control function and input the emitted sound wave into the two-dimensional sensing network; The sound wave receiving unit is used to continuously monitor through the receiving end in the two-dimensional sensing network to obtain sound wave signals, and thereby obtain sound wave signals under different emitted sound waves. The signal detection unit is used to extract the reflected signal peaks contained in the acoustic signal based on the baseline data and record the arrival time of each reflected signal peak.

[0047] The strain detection module 300 is used to construct a time series from the arrival times of the reflected signal peaks corresponding to the same preset defect, and to calculate the continuous change trend and strain rate of the strain value of the waveguide cable segment between adjacent preset defects over time.

[0048] In this system, the strain detection module 300 includes: The time recording unit is used to arrange the arrival times of the reflected signal peaks corresponding to the same preset defect in multiple periodic scans of each cable according to the acquisition time order to construct the arrival time sequence of the preset defect. The strain calculation unit is used to calculate the change in acoustic wave propagation time of the waveguide cable segment between two adjacent preset defects based on the arrival time sequence of two adjacent preset defects, and to calculate the strain value of the cable segment and its strain rate over time by combining the acoustic velocity reference value of the waveguide cable. The risk area determination unit is used to determine the intersection area as a deformation risk area when at least one cable segment of both the meridian waveguide cable and the parallel waveguide cable has an abnormal strain rate detected, and the abnormal meridian segment and the abnormal parallel segment have an intersection area.

[0049] The early warning classification module 400 is used to issue early warning signals based on the comparison results of strain rate and strain accumulation value with preset safety threshold. The early warning signals are divided into multiple levels, and the processing strategies corresponding to different levels of early warning signals are different.

[0050] In this system, the early warning classification module 400 includes: The strain identification unit is used to compare the strain rate and cumulative strain value of each waveguide cable segment with a preset multi-level safety threshold. The multi-level safety threshold includes at least a first-level threshold and a second-level threshold, wherein the second-level threshold is higher than the first-level threshold. The basic early warning unit is used to issue a first early warning signal when the strain rate or strain accumulation value exceeds the first threshold but does not reach the second threshold, indicating that the deformation of the waveguide cable segment is abnormally active; and to issue a second early warning signal when the strain rate or strain accumulation value reaches the second threshold, indicating that the deformation of the waveguide cable segment is intensified. The enhanced early warning unit is used to determine that structural damage has occurred at the location of any preset defect when the reflection signal peak corresponding to any geometric defect is missing or the arrival time offset of the reflection signal peak exceeds the preset damage judgment threshold, and to issue a third early warning signal.

[0051] The above description is only 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 water conservancy monitoring and early warning method based on edge computing, characterized in that, The method includes: Acoustic wave detection is performed based on a two-dimensional sensing network deployed on the surface of the dam. Response signals are collected, and corresponding defect signals are extracted from them to generate baseline data. The two-dimensional sensing network is composed of multiple meridian waveguide cables and multiple parallel waveguide cables. Pre-set defects are etched on both the meridian and parallel waveguide cables. The pre-set defects are evenly distributed and spaced on the cables, and the interval between two adjacent sets of pre-set defects is a fixed value. According to a preset cycle, acoustic wave detection signals are transmitted to the two-dimensional sensing network, acoustic wave signals are received, and the arrival time of the reflection signal peaks corresponding to each preset defect is extracted based on the acoustic wave signals. The arrival times of the reflected signal peaks corresponding to the same preset defect are used to form a time series, and the continuous change trend and strain rate of the strain value of the waveguide cable segment between adjacent preset defects over time are calculated. Based on the comparison between the strain rate and the cumulative strain value and the preset safety threshold, an early warning signal is issued. The early warning signal is divided into multiple levels, and the processing strategies corresponding to different levels of early warning signals are different.

2. The edge computing-based water conservancy monitoring and early warning method according to claim 1, characterized in that, The steps of transmitting acoustic wave detection signals to the two-dimensional sensing network according to a preset period, receiving acoustic wave signals, and extracting the arrival time of the reflection signal peaks corresponding to each preset defect based on the acoustic wave signals include: The emitted sound wave is controlled based on a preset waveform control function and then input into a two-dimensional sensing network. By continuously monitoring the receiver in the two-dimensional sensing network, the sound wave signal is obtained, and the sound wave signal under different emitted sound waves is obtained accordingly. The reflected signal peaks contained in the acoustic signal are extracted from the baseline data, and the arrival time of each reflected signal peak is recorded.

3. The edge computing-based water conservancy monitoring and early warning method according to claim 1, characterized in that, The step of constructing a time series from the arrival times of the reflected signal peaks corresponding to the same preset defect, and calculating the continuous variation trend and strain rate of the strain value of the waveguide cable segment between adjacent preset defects over time includes: For each cable, the arrival times of the reflected signal peaks corresponding to the same preset defect in multiple periodic scans are arranged in the order of acquisition time to construct the arrival time sequence of the preset defect. Based on the arrival time sequence of two adjacent preset defects, the change in acoustic wave propagation time of the waveguide cable segment between the two adjacent preset defects is calculated. Combined with the acoustic velocity reference value of the waveguide cable, the strain value of the cable segment and its strain rate over time are calculated. When at least one cable segment of both the meridian waveguide and the parallel waveguide is found to have an abnormal strain rate, and the abnormal meridian segment intersects with the abnormal parallel segment, the intersecting area is determined to be a deformation risk area.

4. The edge computing-based water conservancy monitoring and early warning method according to claim 1, characterized in that, The step involves issuing an early warning signal based on the comparison between the strain rate and the cumulative strain value and a preset safety threshold. The early warning signals are categorized into multiple levels, each with different processing strategies. Specifically, the steps include: The strain rate and cumulative strain value of each waveguide cable segment are compared with a preset multi-level safety threshold, which includes at least a first-level threshold and a second-level threshold, wherein the second-level threshold is higher than the first-level threshold. When the strain rate or strain accumulation exceeds the first-level threshold but does not reach the second-level threshold, a first warning signal is issued, indicating that the deformation of the waveguide cable segment is abnormally active; when the strain rate or strain accumulation reaches the second-level threshold, a second warning signal is issued, indicating that the deformation of the waveguide cable segment is intensified. When the reflected signal peak corresponding to any geometric defect is missing, or the arrival time offset of the reflected signal peak exceeds the preset damage judgment threshold, it is determined that structural damage has occurred at the location of the preset defect, and a third warning signal is issued.

5. A water conservancy monitoring and early warning system based on edge computing, characterized in that, The system includes: The baseline data acquisition module is used to perform acoustic wave detection based on a two-dimensional sensing network deployed on the surface of the dam, collect response signals, extract corresponding defect signals, and generate baseline data. The two-dimensional sensing network is composed of multiple meridian waveguide cables and multiple parallel waveguide cables. Preset defects are etched on both the meridian and parallel waveguide cables. The preset defects are evenly distributed and spaced on the cables, and the interval between two adjacent sets of preset defects is a fixed value. The continuous detection module is used to transmit acoustic detection signals to the two-dimensional sensing network according to a preset period, receive acoustic signals, and extract the arrival time of the reflection signal peaks corresponding to each preset defect based on the acoustic signals. The strain detection module is used to construct a time series of the arrival times of the reflected signal peaks corresponding to the same preset defect, and to calculate the continuous change trend and strain rate of the strain value of the waveguide cable segment between adjacent preset defects over time. The early warning classification module is used to issue early warning signals based on the comparison results of strain rate and strain accumulation value with preset safety thresholds. The early warning signals are divided into multiple levels, and the processing strategies corresponding to different levels of early warning signals are different.

6. The edge computing-based water conservancy monitoring and early warning system according to claim 5, characterized in that, The continuous detection module includes: The sound wave emitting unit is used to control the emitted sound wave based on a preset waveform control function and input the emitted sound wave into the two-dimensional sensing network; The sound wave receiving unit is used to continuously monitor through the receiving end in the two-dimensional sensing network to obtain sound wave signals, and thereby obtain sound wave signals under different emitted sound waves. The signal detection unit is used to extract the reflected signal peaks contained in the acoustic signal based on the baseline data and record the arrival time of each reflected signal peak.

7. The edge computing-based water conservancy monitoring and early warning system according to claim 6, characterized in that, The strain detection module includes: The time recording unit is used to arrange the arrival times of the reflected signal peaks corresponding to the same preset defect in multiple periodic scans of each cable according to the acquisition time order to construct the arrival time sequence of the preset defect. The strain calculation unit is used to calculate the change in acoustic wave propagation time of the waveguide cable segment between two adjacent preset defects based on the arrival time sequence of two adjacent preset defects, and to calculate the strain value of the cable segment and its strain rate over time by combining the acoustic velocity reference value of the waveguide cable. The risk area determination unit is used to determine the intersection area as a deformation risk area when at least one cable segment of both the meridian waveguide cable and the parallel waveguide cable has an abnormal strain rate detected, and the abnormal meridian segment and the abnormal parallel segment have an intersection area.

8. The edge computing-based water conservancy monitoring and early warning system according to claim 5, characterized in that, The early warning classification module includes: The strain identification unit is used to compare the strain rate and cumulative strain value of each waveguide cable segment with a preset multi-level safety threshold. The multi-level safety threshold includes at least a first-level threshold and a second-level threshold, wherein the second-level threshold is higher than the first-level threshold. The basic early warning unit is used to issue a first early warning signal when the strain rate or strain accumulation value exceeds the first threshold but does not reach the second threshold, indicating that the deformation of the waveguide cable segment is abnormally active; and to issue a second early warning signal when the strain rate or strain accumulation value reaches the second threshold, indicating that the deformation of the waveguide cable segment is intensified. The enhanced early warning unit is used to determine that structural damage has occurred at the location of any preset defect when the reflection signal peak corresponding to any geometric defect is missing or the arrival time offset of the reflection signal peak exceeds the preset damage judgment threshold, and to issue a third early warning signal.

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