A method and system for identifying debris flow infrasound signals

Abstract

The present invention relates to the technical field of signal recognition, and particularly to a method and system for recognizing debris flow infrasound signals, including: collecting infrasound signal data and muddy water data; determining a first temporary grid; determining a second temporary grid; determining abnormal debris flow grids; adjusting the frequency threshold; correcting the synchronization threshold and giving an alarm. By comprehensively utilizing multiple parameters such as real-time signal frequency, amplitude, muddy water flow velocity, and transparency, and adopting a dynamic threshold adjustment and correction strategy, the present invention realizes the efficient recognition of abnormal debris flow grids. It can not only flexibly adjust the frequency and synchronization thresholds according to the actual situation of the monitoring area, ensuring the adaptability and accuracy of the system in different environments, but also effectively reduce false alarms and missed alarms by correcting the synchronization threshold in real time, improving the reliability of debris flow secondary signal recognition, and effectively solving the problem of the decrease in recognition accuracy due to the difficulty of sample collection and the non-obvious frequency difference.

Description

Technical Field

[0001] The present invention relates to the technical field of signal recognition, and particularly to a method and system for recognizing debris flow infrasound signals. Background Art

[0002] With the frequent occurrence of global climate change and natural disasters, debris flow, as a serious natural disaster, poses a huge threat to the safety of human life and property. The occurrence of debris flow is often accompanied by strong infrasound signals, which can provide early warning information before the disaster occurs. Therefore, how to accurately and effectively recognize debris flow infrasound signals has become the focus of research and technology development.

[0003] The patent document with the publication number CN118376314A discloses a method, device, electronic device and storage medium for recognizing debris flow infrasound. The method includes: inputting the time-frequency analysis result of the target infrasound signal into the trained debris flow infrasound recognition model to obtain the recognition result of the debris flow infrasound recognition model, and the recognition result includes whether it is a debris flow infrasound or not; wherein, the training process of the debris flow infrasound recognition model includes: obtaining a debris flow infrasound signal sample set and an environmental infrasound signal sample set; respectively performing time-frequency analysis on the debris flow infrasound signal sample set and the environmental infrasound signal sample set to obtain the time-frequency characteristic indexes of the debris flow infrasound and the amplitudes corresponding to each frequency in 1-20 Hz, as well as the time-frequency characteristic indexes of the environmental infrasound and the amplitudes corresponding to each frequency in 1-20 Hz; based on the amplitudes of each frequency in 1-20 Hz of the debris flow infrasound and the amplitudes of each frequency in 1-20 Hz of the environmental infrasound, determining the frequencies at which there are significant differences between the amplitudes of the debris flow infrasound and the environmental infrasound; based on the amplitudes corresponding to the frequencies at which there are significant differences between the amplitudes of the debris flow infrasound and the environmental infrasound, using an elastic net regression model to obtain the regression coefficients corresponding to each frequency, and based on the regression coefficients corresponding to each frequency, performing importance ranking on the frequencies with non-zero regression coefficients; taking the time-frequency characteristic indexes of the debris flow infrasound, the time-frequency characteristic indexes of the environmental infrasound, the amplitudes corresponding to the frequencies with non-zero regression coefficients in the debris flow infrasound and the amplitudes corresponding to the frequencies with non-zero regression coefficients in the environmental infrasound as a data set, the data set includes a training set and a test set, and then repeating the first process until there is no amplitude data in the data set; taking the debris flow infrasound recognition model with the highest performance evaluation value as the trained debris flow infrasound recognition model; the first process includes: training the debris flow infrasound recognition model based on the training set; performing performance evaluation on the trained debris flow infrasound recognition model based on the test set to obtain a performance evaluation value; in the currently existing amplitude data in the data set, deleting the amplitude corresponding to the frequency with the lowest importance ranking.

[0004] It can be seen that the following problems exist in the debris flow infrasound recognition method: This method relies on a large number of debris flow infrasound signal samples and environmental infrasound signal samples for training, and the sample collection is difficult; the training process of the elastic net regression model takes a long time, especially with low efficiency in the case of large-scale data sets; if the frequency difference between the environmental infrasound signal and the debris flow infrasound signal is not obvious, it will lead to a decrease in the recognition accuracy of the model. Summary of the Invention

[0005] For this reason, the present invention provides a debris flow infrasound signal recognition method and system, which are used to overcome the problem of decreased recognition accuracy in the prior art due to difficult sample collection and non-obvious frequency differences by combining grid division and real-time signal analysis with dynamic threshold adjustment.

[0006] To achieve the above object, on the one hand, the present invention provides a debris flow infrasound signal recognition method, including:

[0007] Collect the real-time signal frequency, real-time signal amplitude of the infrasound signal in each monitoring grid of the debris flow monitoring area divided by the grid, as well as the real-time flow velocity and real-time transparency of the muddy water.

[0008] Determine a number of first temporary grids according to the real-time signal frequency and a preset frequency threshold.

[0009] Determine a number of second temporary grids according to the real-time signal amplitude and the real-time flow velocity of each of the first temporary grids.

[0010] Determine a number of abnormal debris flow grids according to the real-time transparency and a preset synchronization threshold between any two adjacent second temporary grids.

[0011] Adjust the preset frequency threshold according to the positions and quantities of all the abnormal debris flow grids to form an adjusted frequency threshold.

[0012] Correct the preset synchronization threshold according to the number of abnormal debris flow grids determined based on the adjusted frequency threshold within a preset correction duration to form a corrected synchronization threshold.

[0013] Send an alarm for all the abnormal debris flow grids determined based on the corrected synchronization threshold.

[0014] Further, determining a number of first temporary grids according to the real-time signal frequency and a preset frequency threshold includes:

[0015] When the real-time signal frequency is less than the preset frequency threshold, determine that the monitoring grid is the first temporary grid to form a number of first temporary grids.

[0016] Further, determining a number of second temporary grids according to the real-time signal amplitude and the real-time flow velocity of each of the first temporary grids includes:

[0017] Calculating the standard deviation of the real-time signal amplitude within a preset determination duration to form an amplitude fluctuation value;

[0018] Calculating the standard deviation of the real-time flow velocity within the preset determination duration to form a flow velocity fluctuation value;

[0019] Determining a number of second temporary grids according to the amplitude fluctuation value and the flow velocity fluctuation value.

[0020] Further, determining a number of second temporary grids according to the amplitude fluctuation value and the flow velocity fluctuation value includes:

[0021] Calculating the relative deviation between the amplitude fluctuation value and the flow velocity fluctuation value to form a fluctuation deviation;

[0022] When the fluctuation deviation is greater than a preset fluctuation deviation threshold, determining the first temporary grid as the second temporary grid.

[0023] Further, determining a number of abnormal debris flow grids according to the real-time transparency and a preset synchronization threshold within any two adjacent second temporary grids includes:

[0024] Calculating the standard deviation of the real-time transparency of a single second temporary grid within a preset determination duration to form a first transparency fluctuation value;

[0025] Calculating the standard deviation of the real-time transparency of adjacent second temporary grids within the preset determination duration to form a second transparency fluctuation value;

[0026] Determining the second temporary grid as the abnormal debris flow grid according to the first transparency fluctuation value, the second transparency fluctuation value, and the preset synchronization threshold to form a number of abnormal debris flow grids.

[0027] Further, determining the second temporary grid as the abnormal debris flow grid according to the first transparency fluctuation value, the second transparency fluctuation value, and the preset synchronization threshold to form a number of abnormal debris flow grids includes:

[0028] Drawing a change curve of the first transparency fluctuation value to form a first transparency curve;

[0029] Drawing a change curve of the second transparency fluctuation value to form a second transparency curve;

[0030] Calculating the cosine similarity of the first transparency curve and the second transparency curve to form a synchronization degree;

[0031] When the synchronization degree is greater than the preset synchronization degree threshold, it is determined that the corresponding two second temporary grids are both abnormal debris flow grids, and a number of abnormal debris flow grids are formed.

[0032] Furthermore, adjusting the preset frequency threshold according to the positions and quantities of all the abnormal debris flow grids to form an adjusted frequency threshold includes:

[0033] Calculating the ratio of the quantity of the abnormal debris flow grids to the quantity of all the monitoring grids to form an abnormal proportion;

[0034] When the abnormal proportion is greater than the preset proportion threshold, adjusting the preset frequency threshold according to the positions of the abnormal debris flow grids to form an adjusted frequency threshold.

[0035] Furthermore, adjusting the preset frequency threshold according to the positions of the abnormal debris flow grids to form an adjusted frequency threshold includes:

[0036] Obtaining the distances from the positions of the abnormal debris flow grids to the position of a preset central point to form a number of distribution distances;

[0037] Calculating the standard deviation of all the distribution distances to form a distribution concentration degree;

[0038] When the distribution concentration degree is less than the preset distribution concentration degree threshold, reducing the preset frequency threshold according to the relative deviation between the preset distribution concentration degree threshold and the distribution concentration degree and a preset adjustment coefficient to form an adjusted frequency threshold.

[0039] Furthermore, correcting the preset synchronization degree threshold according to the quantity of the abnormal debris flow grids determined based on the adjusted frequency threshold within a preset correction duration to form a corrected synchronization degree threshold includes:

[0040] Calculating the standard deviation of the quantity of the abnormal debris flow grids to form a corrected quantity fluctuation value;

[0041] When the corrected quantity fluctuation value is greater than the preset quantity fluctuation threshold, reducing the preset synchronization degree threshold according to the relative deviation between the corrected quantity fluctuation value and the preset quantity fluctuation threshold and a preset correction coefficient to form a corrected synchronization degree threshold.

[0042] On the other hand, the present invention also provides a debris flow infrasound signal recognition system, including:

[0043] A data acquisition module for acquiring the real-time signal frequency, real-time signal amplitude of the infrasound signals in each monitoring grid in a debris flow monitoring area divided by grids, as well as the real-time flow velocity and real-time transparency of the muddy water;

[0044] A first determination module, which is connected to the data acquisition module and is used to determine a number of first temporary grids according to the real-time signal frequency and the preset frequency threshold;

[0045] A second determination module, which is respectively connected to the data acquisition module and the first determination module and is used to determine a number of second temporary grids according to the real-time signal amplitude and the real-time flow velocity of each of the first temporary grids;

[0046] An abnormality determination module, which is respectively connected to the data acquisition module and the second determination module and is used to determine a number of abnormal debris flow grids according to the real-time transparency and the preset synchronization threshold within any two adjacent second temporary grids;

[0047] An adjustment module, which is respectively connected to the data acquisition module and the abnormality determination module and is used to adjust the preset frequency threshold according to the positions and quantities of all the abnormal debris flow grids to form an adjusted frequency threshold;

[0048] A correction module, which is respectively connected to the adjustment module and the abnormality determination module and is used to correct the preset synchronization threshold according to the quantity of the abnormal debris flow grids determined based on the adjusted frequency threshold within a preset correction duration to form a corrected synchronization threshold;

[0049] An alarm module, which is respectively connected to the correction module and the abnormality determination module and is used to issue an alarm for all the abnormal debris flow grids determined based on the corrected synchronization threshold.

[0050] Compared with the prior art, the beneficial effects of the present invention are as follows: By comprehensively utilizing multiple parameters such as real-time signal frequency, amplitude, mud flow velocity, and transparency, and adopting a dynamic threshold adjustment and correction strategy, the efficient identification of abnormal debris flow grids is realized. This method can not only flexibly adjust the frequency and synchronization thresholds according to the actual situation of the monitoring area, ensuring the adaptability and accuracy of the system in different environments, but also effectively reduce false alarms and missed alarms by correcting the synchronization threshold in real time, improving the reliability of the identification of secondary debris flow signals. Through this intelligent identification and early warning mechanism, the timeliness of disaster early warning can be significantly improved, potential debris flow risks can be predicted in advance, helping relevant departments to make a quick response, and effectively solving the problem of the decline in the identification accuracy rate due to the difficulty of sample collection and the insignificant frequency difference.

[0051] Furthermore, by comparing the real-time signal frequency with the preset frequency threshold to screen out the first temporary grids, the grids that may have debris flow signs can be effectively identified in advance. Through this screening mechanism, it is possible to quickly lock the possible debris flow activity areas, reduce the computational burden of subsequent analysis, and improve the response speed and accuracy of the identification system, thus providing a reliable basis for timely early warning.

[0052] Furthermore, by calculating the amplitude fluctuation value and the flow velocity fluctuation value, it is possible to effectively identify those grids that exhibit large fluctuations on the time scale. This fluctuation analysis helps to screen out areas more likely to experience debris flows, provides a more detailed spatial division, enhances the sensitivity of the system to the direction and change trend of debris flows, and can more accurately locate potential danger areas, thus providing more reliable data support for subsequent anomaly detection and early warning.

[0053] Furthermore, by judging the relative deviation of the amplitude fluctuation value and the flow velocity fluctuation value, false judgments caused by external noise or insignificant fluctuations can be effectively excluded, ensuring that only when the abnormal fluctuation is large is it determined as the second temporary grid, thereby improving the recognition accuracy of debris flow infrasound signals and reducing the probability of false alarms.

[0054] Furthermore, by calculating the transparency fluctuation value, the changes caused by debris flows can be accurately captured. The comparison of synchrony with adjacent grids further improves the judgment accuracy, can reduce environmental interference, optimize the debris flow monitoring and early warning system, and improve the reliability of the system and the timeliness of early warning.

[0055] Furthermore, by judging the synchrony of transparency fluctuations to identify abnormal changes in debris flows, the accuracy and timeliness of anomaly recognition can be improved, false judgments can be reduced, and the monitoring ability and response speed of the system can be enhanced. Especially in complex terrains or harsh environments, the true situation of debris flow activities can be captured more reliably.

[0056] Furthermore, by dynamically adjusting the threshold according to the actual abnormal distribution of debris flows, false judgments or missed judgments caused by fixed thresholds can be avoided, the sensitivity and recognition accuracy of debris flow abnormal signals are improved, and the system has higher adaptability and reliability under different environments and complex conditions.

[0057] Furthermore, by adjusting the frequency threshold according to the distribution of abnormal debris flow grids, the spatial distribution characteristics of debris flows can be more accurately reflected, and over-response or omission of abnormal situations can be avoided. This method can improve the sensitivity and accuracy of debris flow monitoring, especially in areas where the distribution of abnormal debris flow grids is relatively concentrated, and improve the system's prediction and early warning capabilities for potential disasters.

[0058] Furthermore, through the dynamic monitoring and analysis of the fluctuation of the number of abnormal debris flow grids, the synchrony threshold is effectively adjusted, enabling the system to respond more sensitively to the real-time changes of debris flows, preventing false alarms or missed reports caused by too high a threshold, optimizing the alarm accuracy and response speed, and thus improving the accuracy and reliability of debris flow disaster early warning.

[0059] Furthermore, through a multi-level and multi-parameter judgment mechanism, the recognition accuracy and response speed of debris flow infrasound signals are effectively improved. By dynamically adjusting the frequency threshold and synchronization threshold, the system can adapt to different monitoring environments and conditions, monitor in real time and accurately identify abnormal debris flow grids, avoid false alarms, and ensure the efficiency and accuracy of debris flow monitoring. In addition, the intelligent correction mechanism of the system improves the adaptability in complex environments, making the recognition process more sensitive and stable. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 is a flowchart of the debris flow infrasound signal recognition method of this embodiment;

[0061] Figure 2 is a judgment logic diagram for determining the first temporary grid of this embodiment;

[0062] Figure 3 is a judgment logic diagram for determining the second temporary grid of this embodiment;

[0063] Figure 4 is a schematic diagram of the debris flow infrasound signal recognition system of this embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0064] In order to make the objectives and advantages of the present invention clearer, the present invention will be further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0065] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention and do not limit the protection scope of the present invention.

[0066] Please refer to Figure 1 shown, which is a flowchart of the debris flow infrasound signal recognition method of this embodiment;

[0067] On the one hand, this embodiment provides a debris flow infrasound signal recognition method, including:

[0068] Collect the real-time signal frequency, real-time signal amplitude of infrasound signals in each monitoring grid in the debris flow monitoring area divided by grids, as well as the real-time flow velocity and real-time transparency of the muddy water.

[0069] Determine a number of first temporary grids according to the real-time signal frequency and a preset frequency threshold;

[0070] Determine a number of second temporary grids according to the real-time signal amplitude and the real-time flow velocity of each of the first temporary grids;

[0071] Determine a number of abnormal debris flow grids based on the real-time transparency and the preset synchronization threshold within any two adjacent second temporary grids;

[0072] Adjust the preset frequency threshold according to the positions and quantities of all the abnormal debris flow grids to form an adjusted frequency threshold;

[0073] Correct the preset synchronization threshold according to the quantity of abnormal debris flow grids determined based on the adjusted frequency threshold within a preset correction duration to form a corrected synchronization threshold;

[0074] Send an alarm for all the abnormal debris flow grids determined based on the corrected synchronization threshold.

[0075] During the acquisition process, multiple monitoring grids are arranged in the debris flow monitoring area, and grid division is carried out through Geographic Information System (GIS) technology. Specifically, from an overhead perspective, the monitoring area is divided into regular rectangular or square grids, and sensors or monitoring devices are installed in each grid to collect the frequency and amplitude of infrasound signals, the mud flow velocity, and transparency data in real time. These devices include infrasound sensors, flow velocity sensors, and transparency sensors, which can accurately capture and record data at different positions and time points. All sensors transmit the collected data within each grid in real time through wireless or wired networks, and the data is stored and processed through a data acquisition module. This high-density sensor arrangement ensures comprehensive coverage of each grid in the monitoring area, provides accurate real-time data, and supports subsequent analysis and judgment.

[0076] Real-time transparency refers to the degree of light transmission of suspended substances in the mud water within the debris flow monitoring area, and is usually used to reflect the turbidity of the water body. In debris flow monitoring, real-time transparency is an important indicator for measuring the mud water flow condition and debris flow intensity. Through real-time transparency, the fluidity of the mud water and the presence of a large degree of sediment flow can be judged.

[0077] The preset frequency threshold is the standard boundary for judging the frequency of infrasound signals, depending on the characteristics of debris flows and the frequency range of infrasound signals. It is usually set between 1 Hz and 100 Hz. In this embodiment, it is set to 30 Hz to ensure that the frequency differences between the normal environment and debris flow activities can be accurately distinguished and the recognition accuracy can be improved.

[0078] The preset synchronization threshold is the standard for judging whether the transparency changes of adjacent grids are synchronous, depending on the dynamic characteristics of mud water flow in debris flows. It is usually set between 0.7 and 0.9. In this embodiment, it is set to 0.8, which helps to ensure that the transparency changes of adjacent grids are consistent during the formation or development stage of debris flows and reduce misjudgment.

[0079] The preset correction duration is a time window used to correct the synchronization threshold, which depends on the development speed of the debris flow and the signal change frequency. It is usually set between 10 minutes and 30 minutes. In this embodiment, it is set to 20 minutes, which can effectively capture the rapid changes of the debris flow and adjust the synchronization threshold within a reasonable duration, enhancing the sensitivity and accuracy of the system.

[0080] By dividing the debris flow monitoring area into grids, the infrasound signal frequency, amplitude, mud flow velocity, and transparency data within each grid are collected. First, according to the signal frequency and the preset frequency threshold, the first temporary grids are determined, and then the second temporary grids are further screened based on the signal amplitude and flow velocity. By analyzing the transparency fluctuations of adjacent second temporary grids and the preset synchronization threshold, the abnormal debris flow grids are determined. Then, the frequency threshold is adjusted according to the number and location of the abnormal grids, and the synchronization threshold is corrected. Finally, an alarm is issued for the identified abnormal grids to indicate the risk of debris flow occurrence.

[0081] By comprehensively using multiple parameters such as real-time signal frequency, amplitude, mud flow velocity, and transparency, and adopting a dynamic threshold adjustment and correction strategy, the efficient identification of abnormal debris flow grids is achieved. This method can not only flexibly adjust the frequency and synchronization thresholds according to the actual situation of the monitoring area, ensuring the adaptability and accuracy of the system in different environments, but also effectively reduce false alarms and missed alarms by real-time correcting the synchronization threshold, improving the reliability of debris flow secondary signal identification. Through this intelligent identification and early warning mechanism, the timeliness of disaster early warning can be significantly improved, potential debris flow risks can be predicted in advance, helping relevant departments to make rapid responses, and effectively solving the problem of the decline in identification accuracy due to the difficult sample collection and the unobvious frequency difference.

[0082] Please continue to refer to Figure 2 as shown, which is the decision logic diagram for determining the first temporary grids in this embodiment;

[0083] Determining a number of first temporary grids according to the real-time signal frequency and the preset frequency threshold includes:

[0084] When the real-time signal frequency is less than the preset frequency threshold, it is determined that the monitoring grid is the first temporary grid, forming a number of first temporary grids.

[0085] Within the debris flow monitoring area, the system compares the real-time signal frequency in each monitoring grid with the preset frequency threshold. If the real-time signal frequency of a certain monitoring grid is less than the preset frequency threshold, then this monitoring grid is determined as the first temporary grid, and a number of first temporary grids are formed. This step is a preliminary screening of the signal frequency. By screening out the grids with frequencies lower than the preset frequency threshold, it provides a data basis for subsequent further analysis.

[0086] By comparing the real-time signal frequency with the preset frequency threshold, the first temporary grids can be screened out, which can effectively identify in advance those grids that may show signs of debris flow. Through this screening mechanism, it is possible to quickly lock in the possible debris flow activity areas, reduce the computational burden of subsequent analysis, and improve the response speed and accuracy of the recognition system, thus providing a reliable basis for timely early warning.

[0087] Specifically, determining a number of second temporary grids according to the real-time signal amplitude and the real-time flow velocity of each of the first temporary grids includes:

[0088] Calculating the standard deviation of the real-time signal amplitude within a preset determination duration to form an amplitude fluctuation value;

[0089] Calculating the standard deviation of the real-time flow velocity within the preset determination duration to form a flow velocity fluctuation value;

[0090] Determining a number of second temporary grids according to the amplitude fluctuation value and the flow velocity fluctuation value.

[0091] The preset determination duration refers to the time window used to calculate the signal amplitude fluctuation value and the flow velocity fluctuation value, which depends on the real-time requirements of debris flow monitoring and the dynamic change characteristics of debris flow. It is usually set between several minutes and dozens of minutes. In this embodiment, the preset determination duration is set to 30 minutes, which can effectively balance the real-time nature of the data and the stability of the fluctuation characteristics, avoid the noise interference of short-term fluctuations, and at the same time be able to capture the significant changes during the debris flow process to ensure accurate identification of abnormal signals.

[0092] Based on the first temporary grids, the system further analyzes the changes in the real-time signal amplitude and the real-time flow velocity within each grid. First, by calculating the standard deviation of the real-time signal amplitude within each grid within the preset determination duration, the amplitude fluctuation value is obtained; then, the standard deviation of the real-time flow velocity of each grid within the same duration is calculated to obtain the flow velocity fluctuation value. Then, according to the magnitudes of these two fluctuation values, it is judged which grids show larger change fluctuations and they are classified as second temporary grids to provide a more accurate reference for subsequent anomaly detection.

[0093] Through the calculation of the amplitude fluctuation value and the flow velocity fluctuation value, it is possible to effectively identify those grids that show large fluctuations on the time scale. This fluctuation analysis helps to screen out areas more likely to have debris flow, provides a more detailed spatial division, enhances the sensitivity of the system to the direction and change trend of debris flow, and can more accurately locate potential dangerous areas, thus providing more reliable data support for subsequent anomaly detection and early warning.

[0094] Please continue to refer to Figure 3 as shown, which is the determination logic diagram for determining the second temporary grids in this embodiment;

[0095] Determining a number of second temporary grids based on the amplitude fluctuation value and the flow velocity fluctuation value includes:

[0096] Calculating the relative deviation between the amplitude fluctuation value and the flow velocity fluctuation value to form a fluctuation deviation;

[0097] When the fluctuation deviation is greater than a preset fluctuation deviation threshold, determining that the first temporary grid is the second temporary grid.

[0098] The preset fluctuation deviation threshold is a critical value for judging the relative deviation between the amplitude fluctuation value and the flow velocity fluctuation value, which depends on the characteristic fluctuation range of debris flow, the environmental noise level, and the signal acquisition accuracy. It is usually set between 0.1 and 1. In this embodiment, it is set to 0.5, which can effectively distinguish obvious signal fluctuations, and at the same time avoid misjudgment due to environmental noise or other minor fluctuations, ensuring the accuracy and sensitivity of debris flow identification.

[0099] First, calculate the relative deviation between the amplitude fluctuation value and the flow velocity fluctuation value to form a fluctuation deviation. Then, by comparing the fluctuation deviation with the preset fluctuation deviation threshold, if the fluctuation deviation is greater than the threshold, determine that the first temporary grid is the second temporary grid, further screening out the areas with larger signal fluctuations to accurately identify potential debris flow anomalies.

[0100] By judging the relative deviation between the amplitude fluctuation value and the flow velocity fluctuation value, misjudgment caused by external noise or unobvious fluctuations can be effectively excluded, ensuring that it is only determined as the second temporary grid when the abnormal fluctuation is large, thereby improving the identification accuracy of debris flow infrasound signals and reducing the probability of false alarms.

[0101] Specifically, determining a number of abnormal debris flow grids based on the real-time transparency and the preset synchronization threshold within any two adjacent second temporary grids includes:

[0102] Calculating the standard deviation of the real-time transparency of a single second temporary grid within a preset determination duration to form a first transparency fluctuation value;

[0103] Calculating the standard deviation of the real-time transparency of adjacent second temporary grids within the preset determination duration to form a second transparency fluctuation value;

[0104] Determining the second temporary grid as the abnormal debris flow grid according to the first transparency fluctuation value, the second transparency fluctuation value, and the preset synchronization threshold to form a number of abnormal debris flow grids.

[0105] The preset determination duration refers to the time window used in the process of determining the real-time transparency fluctuation, which depends on the change speed of debris flow and the response speed of the monitoring system. It is usually set between several minutes and dozens of minutes. In this embodiment, it is set to 10 minutes, which can effectively filter out misjudgments caused by instantaneous fluctuations, and at the same time can quickly respond to the real changes of debris flow, improving the accuracy and timeliness of early warning.

[0106] By calculating the standard deviation of the real-time transparency of a single second temporary grid and adjacent second temporary grids within the preset determination duration, a transparency fluctuation value is formed. Then, by comparing the transparency fluctuation value with the preset synchronization threshold, it is determined whether it is an abnormal debris flow grid. If the transparency fluctuation value exceeds the set threshold and is synchronized with the transparency change of the adjacent grid, then the grid is determined to be an abnormal debris flow grid, and multiple abnormal grids are further identified.

[0107] Through the calculation of the transparency fluctuation value, the changes caused by debris flow can be accurately captured. The comparison of synchronization with adjacent grids further improves the accuracy of judgment, can reduce environmental interference, optimize the debris flow monitoring and early warning system, and improve the reliability of the system and the timeliness of early warning.

[0108] Specifically, according to the first transparency fluctuation value, the second transparency fluctuation value, and the preset synchronization threshold, it is determined that the second temporary grid is the abnormal debris flow grid. The formation of several abnormal debris flow grids includes:

[0109] Draw the change curve of the first transparency fluctuation value to form the first transparency curve;

[0110] Draw the change curve of the second transparency fluctuation value to form the second transparency curve;

[0111] Calculate the cosine similarity of the first transparency curve and the second transparency curve to form the synchronization degree;

[0112] When the synchronization degree is greater than the preset synchronization threshold, it is determined that the corresponding two second temporary grids are both the abnormal debris flow grids, forming several abnormal debris flow grids.

[0113] According to the change curves of the first transparency fluctuation value and the second transparency fluctuation value, calculate the cosine similarity between the two to form the synchronization degree. By comparing the synchronization degree with the preset synchronization threshold, when the synchronization degree is greater than the threshold, it is determined that the corresponding second temporary grid is an abnormal debris flow grid, thereby identifying multiple abnormal debris flow grids.

[0114] Judging the abnormal changes of debris flow through the synchrony of transparency fluctuations, thereby improving the accuracy and timeliness of abnormal recognition, reducing misjudgment, enhancing the monitoring ability and response speed of the system. Especially in complex terrain or harsh environments, it can more reliably capture the real situation of debris flow activities.

[0115] Specifically, adjusting the preset frequency threshold according to the positions and quantities of all the abnormal debris flow grids, and forming an adjusted frequency threshold includes:

[0116] Calculating the ratio of the quantity of the abnormal debris flow grids to the quantity of all the monitoring grids to form an abnormal proportion;

[0117] When the abnormal proportion is greater than a preset proportion threshold, adjusting the preset frequency threshold according to the positions of the abnormal debris flow grids to form an adjusted frequency threshold.

[0118] The preset proportion threshold is the ratio of the quantity of abnormal debris flow grids to the total quantity of monitoring grids, serving as the basis for adjusting the frequency threshold. It depends on the scale of the monitoring area, the frequency of debris flow occurrence, and the sensitivity required by the system. Usually, it is set between 5% - 20%. In this embodiment, it is set to 10%, which can effectively avoid excessive threshold adjustment, ensure that the system's judgment of debris flow abnormalities is neither insensitive nor overly responsive to occasional situations, and ensure a relatively stable and reasonable recognition effect.

[0119] By calculating the ratio of the quantity of abnormal debris flow grids to the quantity of all monitoring grids, the abnormal proportion is obtained. If the abnormal proportion is greater than the preset proportion threshold, the preset frequency threshold is adjusted according to the positions of the abnormal debris flow grids to form an adjusted frequency threshold, thereby improving the accuracy and flexibility of frequency determination.

[0120] By dynamically adjusting the threshold according to the actual abnormal distribution of debris flow, it avoids misjudgment or missed judgment caused by a fixed threshold, improves the sensitivity and recognition accuracy of debris flow abnormal signals, and enables the system to have higher adaptability and reliability in different environments and complex conditions.

[0121] Specifically, adjusting the preset frequency threshold according to the positions of the abnormal debris flow grids, and forming an adjusted frequency threshold includes:

[0122] Obtaining the distances from the positions of each abnormal debris flow grid to the position of a preset center point to form a number of distribution distances;

[0123] Calculating the standard deviation of all the distribution distances to form a distribution concentration;

[0124] When the distribution concentration is less than a preset distribution concentration threshold, reduce the preset frequency threshold according to the relative deviation between the preset distribution concentration threshold and the distribution concentration and a preset adjustment coefficient to form an adjusted frequency threshold, where the preset distribution concentration threshold, the relative deviation of the distribution concentration, and the adjusted frequency threshold are positively correlated.

[0125] The preset center point is a fixed reference position, usually set at the geometric center of the debris flow monitoring area or a specific position selected according to actual needs, depending on the geographical distribution of the monitoring area and the specific objectives to be analyzed. It is usually set at the center of the area to facilitate the balanced monitoring of the surrounding grids. The specific value depends on the specific coordinate range and target setting of the monitoring area. In this embodiment, it is set as the geometric center point (latitude and longitude of the geographical coordinates) of the monitoring area, which can make the distance comparison between all grids in the monitoring area and the center point more balanced, contribute to accurately analyzing the abnormal situation of the debris flow, and optimize the effect of frequency threshold adjustment.

[0126] For each abnormal debris flow grid, obtain its corresponding coordinate information through sensors or monitoring devices. Usually, GPS positioning or a geographical coordinate system is used to calibrate the grid position. Use the Euclidean distance formula to calculate the distance from each abnormal debris flow grid to the preset center point to form a number of distribution distances.

[0127] The preset adjustment coefficient is a parameter used to adjust the change of the frequency threshold, depending on the characteristics of the monitoring area and the occurrence frequency of the debris flow. It is usually between 0.1 and 1.0. In this embodiment, it is set as 0.3, which can adapt to the dynamic changes of the debris flow while maintaining the sensitivity of frequency threshold adjustment and the stability of the system.

[0128] According to the positions of the abnormal debris flow grids, first obtain the distance from the grid center point of each abnormal debris flow grid to the preset center point to form a number of distribution distances. Then, calculate the standard deviation of all distribution distances to obtain the distribution concentration. Next, when the distribution concentration is less than the preset distribution concentration threshold, adjust the preset frequency threshold by calculating the relative deviation and the preset adjustment coefficient to reduce the frequency threshold and form the adjusted frequency threshold.

[0129] By adjusting the frequency threshold according to the distribution of abnormal debris flow grids, the spatial distribution characteristics of the debris flow can be more accurately reflected, avoiding over-response or omission of abnormal situations. This method can improve the sensitivity and accuracy of debris flow monitoring, especially in areas where the distribution of abnormal debris flow grids is relatively concentrated, and enhance the system's ability to predict and warn of potential disasters.

[0130] Specifically, correcting the preset synchronization threshold according to the number of abnormal debris flow grids determined based on the adjusted frequency threshold within a preset correction duration to form a corrected synchronization threshold includes:

[0131] Calculate the standard deviation of the number of the abnormal debris flow grids to form a corrected quantity fluctuation value;

[0132] When the corrected quantity fluctuation value is greater than a preset quantity fluctuation threshold, reduce the preset synchronization threshold according to the relative deviation between the corrected quantity fluctuation value and the preset quantity fluctuation threshold and a preset correction coefficient to form a corrected synchronization threshold, wherein the relative deviation between the corrected quantity fluctuation value and the preset quantity fluctuation threshold is positively correlated with the corrected synchronization threshold.

[0133] The preset quantity fluctuation threshold is a threshold for determining whether the corrected quantity fluctuation value is significant, which depends on the fault tolerance of the system and the characteristics of the monitored area, and is usually set between 10% and 30%. In this embodiment, it is set to 20%, which can balance the sensitivity of abnormal fluctuations and the stability of the system, and avoid frequent misadjustments caused by overly strict threshold settings.

[0134] The preset correction coefficient is a constant used to adjust the synchronization threshold, which depends on the response speed and adjustment strategy of the debris flow monitoring system, and is usually set between 0.1 and 1.0. In this embodiment, it is set to 0.5, which can make the adjustment of the synchronization threshold smoother and avoid overly sensitive alarm responses caused by excessive adjustments.

[0135] Within a preset correction duration, calculate the standard deviation of the number of abnormal debris flow grids determined based on the adjusted frequency threshold to obtain a corrected quantity fluctuation value. If the corrected quantity fluctuation value is greater than the preset quantity fluctuation threshold, reduce the preset synchronization threshold according to the relative deviation between the corrected quantity fluctuation value and the preset quantity fluctuation threshold, in combination with the preset correction coefficient, so as to form a corrected synchronization threshold.

[0136] Through the dynamic monitoring and analysis of the number fluctuation of abnormal debris flow grids, the synchronization threshold is effectively adjusted, enabling the system to more sensitively respond to the real-time changes of debris flows, preventing false alarms or missed alarms caused by too high a threshold, optimizing the alarm accuracy and response speed, and thus improving the accuracy and reliability of debris flow disaster warnings.

[0137] Please continue to refer to Figure 4 as shown, which is a schematic diagram of the debris flow infrasound signal recognition system of this embodiment;

[0138] On the other hand, this embodiment also provides a debris flow infrasound signal recognition system, including:

[0139] A data acquisition module for acquiring the real-time signal frequency, real-time signal amplitude of the infrasound signals in each monitoring grid of the debris flow monitoring area divided by grids, as well as the real-time flow velocity and real-time transparency of the muddy water;

[0140] A first determination module, which is connected to the data acquisition module and is used to determine a number of first temporary grids according to the real-time signal frequency and a preset frequency threshold;

[0141] A second determination module, which is respectively connected to the data acquisition module and the first determination module and is used to determine a number of second temporary grids according to the real-time signal amplitude and the real-time flow velocity of each of the first temporary grids;

[0142] An anomaly determination module, which is respectively connected to the data acquisition module and the second determination module and is used to determine a number of abnormal debris flow grids according to the real-time transparency and a preset synchronization threshold within any two adjacent second temporary grids;

[0143] An adjustment module, which is respectively connected to the data acquisition module and the anomaly determination module and is used to adjust the preset frequency threshold according to the positions and quantities of all the abnormal debris flow grids to form an adjusted frequency threshold;

[0144] A correction module, which is respectively connected to the adjustment module and the anomaly determination module and is used to correct the preset synchronization threshold according to the quantity of abnormal debris flow grids determined based on the adjusted frequency threshold within a preset correction duration to form a corrected synchronization threshold;

[0145] An alarm module, which is respectively connected to the correction module and the anomaly determination module and is used to issue an alarm for all the abnormal debris flow grids determined based on the corrected synchronization threshold.

[0146] Through the collaborative work of multiple modules, first, the data acquisition module collects in real time data such as infrasound signal frequency, signal amplitude, flow velocity, and transparency in the debris flow monitoring area. Then, the first determination module determines preliminary grids according to the real-time signal frequency and the preset threshold, and the second determination module further screens the grids according to the signal amplitude and the flow velocity. The anomaly determination module identifies abnormal debris flow grids by analyzing the transparency change of adjacent grids and combining the synchronization threshold. The adjustment module adjusts the frequency threshold according to the positions and quantities of the abnormal grids, the correction module corrects the synchronization threshold according to the fluctuation of the quantity of abnormal grids, and finally, the alarm module issues an alarm based on the corrected synchronization threshold.

[0147] Through a multi-level and multi-parameter judgment mechanism, the recognition accuracy and response speed of debris flow infrasound signals are effectively improved. By dynamically adjusting the frequency threshold and the synchronization threshold, the system can adapt to different monitoring environments and conditions, monitor in real time and accurately identify abnormal debris flow grids, avoid false alarms, and ensure the efficiency and accuracy of debris flow monitoring. In addition, the intelligent correction mechanism of the system improves the adaptability in complex environments, making the recognition process more sensitive and stable.

[0148] So far, the technical solution of the present invention has been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A method for identifying debris flow infrasound signals, characterized in that, Including: Collecting the real-time signal frequency, real-time signal amplitude of infrasound signals in each monitoring grid of a debris flow monitoring area divided by a grid, as well as the real-time flow velocity and real-time transparency of muddy water; Determining a number of first temporary grids according to the real-time signal frequency and a preset frequency threshold; Determining a number of second temporary grids according to the real-time signal amplitude and the real-time flow velocity of each of the first temporary grids; Determining a number of abnormal debris flow grids according to the real-time transparency and a preset synchronization threshold in any two adjacent second temporary grids; Adjusting the preset frequency threshold according to the positions and quantities of all the abnormal debris flow grids to form an adjusted frequency threshold; Correcting the preset synchronization threshold according to the quantity of abnormal debris flow grids determined based on the adjusted frequency threshold within a preset correction duration to form a corrected synchronization threshold; Issuing an alarm for all the abnormal debris flow grids determined based on the corrected synchronization threshold; Determining a number of first temporary grids according to the real-time signal frequency and a preset frequency threshold includes: When the real-time signal frequency is less than the preset frequency threshold, determining the monitoring grid as the first temporary grid to form a number of first temporary grids; Determining a number of second temporary grids according to the real-time signal amplitude and the real-time flow velocity of each of the first temporary grids includes: Calculating the standard deviation of the real-time signal amplitude within a preset determination duration to form an amplitude fluctuation value; Calculating the standard deviation of the real-time flow velocity within the preset determination duration to form a flow velocity fluctuation value; Determining a number of second temporary grids according to the amplitude fluctuation value and the flow velocity fluctuation value; Determining a number of second temporary grids according to the amplitude fluctuation value and the flow velocity fluctuation value includes: Calculating the relative deviation between the amplitude fluctuation value and the flow velocity fluctuation value to form a fluctuation deviation; When the fluctuation deviation is greater than a preset fluctuation deviation threshold, determining the first temporary grid as the second temporary grid; Determining a number of abnormal debris flow grids according to the real-time transparency and a preset synchronization threshold in any two adjacent second temporary grids includes: Calculating the standard deviation of the real-time transparency of a single second temporary grid within a preset determination duration to form a first transparency fluctuation value; Calculating the standard deviation of the real-time transparency of adjacent second temporary grids within the preset determination duration to form a second transparency fluctuation value; Determining the second temporary grid as the abnormal debris flow grid according to the first transparency fluctuation value, the second transparency fluctuation value, and the preset synchronization threshold to form a number of abnormal debris flow grids; Determining the second temporary grid as the abnormal debris flow grid according to the first transparency fluctuation value, the second transparency fluctuation value, and the preset synchronization threshold to form a number of abnormal debris flow grids includes: Drawing a change curve of the first transparency fluctuation value to form a first transparency curve; Drawing a change curve of the second transparency fluctuation value to form a second transparency curve; Calculating the cosine similarity between the first transparency curve and the second transparency curve to form a synchronization degree; When the synchronization degree is greater than the preset synchronization degree threshold, it is determined that the corresponding two second temporary grids are both abnormal debris flow grids, and a number of abnormal debris flow grids are formed.

2. The debris flow infrasound signal recognition method according to claim 1, characterized in that Adjusting the preset frequency threshold according to the positions and quantities of all the abnormal debris flow grids, the formation of the adjusted frequency threshold includes: Calculating the ratio of the quantity of the abnormal debris flow grids to the quantity of all the monitoring grids to form an abnormal proportion; When the abnormal proportion is greater than the preset proportion threshold, adjusting the preset frequency threshold according to the positions of the abnormal debris flow grids to form the adjusted frequency threshold.

3. The debris flow infrasound signal recognition method according to claim 2, characterized in that Adjusting the preset frequency threshold according to the positions of the abnormal debris flow grids, the formation of the adjusted frequency threshold includes: Obtaining the distances from the positions of the abnormal debris flow grids to the position of a preset center point to form a number of distribution distances; Calculating the standard deviation of all the distribution distances to form a distribution concentration degree; When the distribution concentration degree is less than the preset distribution concentration degree threshold, reducing the preset frequency threshold according to the relative deviation between the preset distribution concentration degree threshold and the distribution concentration degree and a preset adjustment coefficient to form the adjusted frequency threshold.

4. The debris flow infrasound signal recognition method according to claim 3, characterized in that Correcting the preset synchronization degree threshold according to the quantity of the abnormal debris flow grids determined based on the adjusted frequency threshold within a preset correction time period, the formation of the corrected synchronization degree threshold includes: Calculating the standard deviation of the quantity of the abnormal debris flow grids to form a corrected quantity fluctuation value; When the corrected quantity fluctuation value is greater than the preset quantity fluctuation threshold, reducing the preset synchronization degree threshold according to the relative deviation between the corrected quantity fluctuation value and the preset quantity fluctuation threshold and a preset correction coefficient to form the corrected synchronization degree threshold.

5. A debris flow infrasound signal recognition system, based on the debris flow infrasound signal recognition method according to any one of claims 1-4, includes: A data acquisition module for acquiring the real-time signal frequency, real-time signal amplitude, real-time flow velocity and real-time transparency of muddy water in each monitoring grid of a debris flow monitoring area divided by grids; A first determination module, connected to the data acquisition module, for determining a number of first temporary grids according to the real-time signal frequency and the preset frequency threshold; A second determination module, respectively connected to the data acquisition module and the first determination module, for determining a number of second temporary grids according to the real-time signal amplitude and the real-time flow velocity of each of the first temporary grids; An abnormality determination module, respectively connected to the data acquisition module and the second determination module, for determining a number of abnormal debris flow grids according to the real-time transparency and the preset synchronization degree threshold in any two adjacent second temporary grids; An adjustment module, respectively connected to the data acquisition module and the abnormality determination module, for adjusting the preset frequency threshold according to the positions and quantities of all the abnormal debris flow grids to form the adjusted frequency threshold; A correction module, respectively connected to the adjustment module and the abnormality determination module, for correcting the preset synchronization degree threshold according to the quantity of the abnormal debris flow grids determined based on the adjusted frequency threshold within a preset correction time period to form the corrected synchronization degree threshold; An alarm module, which is respectively connected to the correction module and the anomaly determination module, and is used to issue an alarm for all the abnormal debris flow grids determined based on the correction synchronization threshold.

Images