Debris flow infrasound signal identification method and system

Abstract

The invention relates to the technical field of signal identification, in particular to a debris flow infrasound signal identification method and system, and the method comprises the steps: collecting infrasound signal data and muddy water data; determining a first temporary grid; determining a second temporary grid; judging an abnormal debris flow grid; adjusting a frequency threshold; and correcting the synchronization degree threshold value and giving an alarm. According to the method, multiple parameters such as real-time signal frequency, amplitude, muddy water flowing speed and transparency are comprehensively utilized, a dynamic threshold value adjustment and correction strategy is adopted, efficient identification of the debris flow abnormal grid is achieved, the frequency and the synchronization degree threshold value can be flexibly adjusted according to the actual situation of a monitoring area, and the accuracy of the debris flow abnormal grid is improved. According to the method, the adaptability and accuracy of the system in different environments are ensured, false alarm and missing alarm are effectively reduced by correcting the synchronization degree threshold value in real time, the reliability of debris flow secondary signal identification is improved, and the problem that the identification accuracy is reduced due to the fact that the sample collection difficulty is large and the frequency difference is not obvious is effectively solved.

Description

Technical Field

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

[0002] With global climate change and frequent natural disasters, debris flow, as a serious natural disaster, poses a huge threat to human life and property. 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 identify debris flow infrasound signals has become the focus of research and technology development.

[0003] Patent document with publication number CN118376314A discloses a method, device, electronic device and storage medium for identifying debris flow infrasound. The method comprises: inputting the time-frequency analysis result of the target infrasound signal into a trained debris flow infrasound identification model to obtain the identification result of the debris flow infrasound identification model, wherein the identification result includes whether it is debris flow infrasound or not debris flow infrasound; wherein the training process of the debris flow infrasound identification model comprises: obtaining a debris flow infrasound signal sample set and an environmental infrasound signal sample set; Time-frequency analysis was performed on the debris flow infrasound signal sample set and the environmental infrasound signal sample set respectively to obtain the time-frequency characteristic indicators of the debris flow infrasound and the amplitudes corresponding to each frequency in 1-20 Hz, as well as the time-frequency characteristic indicators 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, the frequencies where the amplitudes of the debris flow infrasound and the environmental infrasound were significantly different were determined; based on the amplitudes of the debris flow infrasound and the environmental infrasound, the amplitudes of the debris flow infrasound and the environmental infrasound were significantly different. The amplitudes corresponding to the frequencies with significant differences in amplitude and ambient infrasound amplitude are obtained by using an elastic network regression model, and the frequencies with non-zero regression coefficients are ranked in importance based on the regression coefficients corresponding to the frequencies; the time-frequency characteristic indicators of debris flow infrasound, the time-frequency characteristic indicators of ambient infrasound, the amplitudes corresponding to the frequencies with non-zero regression coefficients in debris flow infrasound, and the amplitudes corresponding to the frequencies with non-zero regression coefficients in ambient infrasound are taken as data sets, the data sets include a training set and a test set, and then the first process is repeated until there is no amplitude data in the data set; the debris flow infrasound recognition model with the highest performance evaluation value is taken 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; and deleting the amplitude corresponding to the frequency with the lowest importance ranking in the amplitude data currently existing in the data set.

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

[0005] To this end, the present invention provides a debris flow infrasound signal recognition method and system, which is used to overcome the problem of reduced recognition accuracy in the prior art due to difficulty in sample collection and unclear frequency difference through grid division and real-time signal analysis combined with dynamic threshold adjustment.

[0006] To achieve the above object, the present invention provides a method for identifying debris flow infrasound signals, comprising: Collect the real-time signal frequency, real-time signal amplitude, and real-time flow speed and real-time transparency of the infrasound signal in each monitoring grid in the debris flow monitoring area divided by grids; Determine a plurality of first temporary grids according to the real-time signal frequency and a preset frequency threshold; Determine a plurality of second temporary grids according to the real-time signal amplitude and the real-time flow speed of each of the first temporary grids; Determine 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 numbers of all the abnormal debris flow grids to form an adjusted frequency threshold; The preset synchronization threshold is corrected according to the number of abnormal debris flow grids determined based on the adjustment frequency threshold within a preset correction time period to form a corrected synchronization threshold; An alarm is issued for all the abnormal debris flow grids determined based on the modified synchronization threshold.

[0007] Further, determining a plurality of first temporary grids according to the real-time signal frequency and a preset frequency threshold comprises: When the real-time signal frequency is less than the preset frequency threshold, the monitoring grid is determined to be the first temporary grid, and a plurality of first temporary grids are formed.

[0008] Further, determining a plurality of second temporary grids according to the real-time signal amplitude and the real-time flow speed of each of the first temporary grids comprises: Calculate the standard deviation of the real-time signal amplitude within a preset determined time period to form an amplitude fluctuation value; Calculating the standard deviation of the real-time flow velocity within the preset determined time period to form a flow velocity fluctuation value; A plurality of second temporary grids are determined according to the amplitude fluctuation value and the flow velocity fluctuation value.

[0009] Further, determining a plurality of second temporary grids according to the amplitude fluctuation value and the flow velocity fluctuation value comprises: Calculating a 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, the first temporary grid is determined to be the second temporary grid.

[0010] Further, 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 a standard deviation of the real-time transparency of a single second temporary grid within a preset determination time period to form a first transparency fluctuation value; Calculating the standard deviation of the real-time transparency of the adjacent second temporary grids within the preset determination time to form a second transparency fluctuation value; The second temporary grid is determined to be the abnormal debris flow grid according to the first transparency fluctuation value, the second transparency fluctuation value and the preset synchronization threshold, so as to form a plurality of abnormal debris flow grids.

[0011] 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, and forming a plurality of abnormal debris flow grids includes: Drawing a variation curve of the first transparency fluctuation value to form a first transparency curve; Drawing a variation curve of the second transparency fluctuation value to form a second transparency curve; calculating the cosine similarity of 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 the abnormal debris flow grids, and a plurality of abnormal debris flow grids are formed.

[0012] Further, the preset frequency threshold is adjusted according to the positions and numbers of all the abnormal debris flow grids, and the adjusted frequency threshold is formed including: Calculate the ratio of the number of abnormal debris flow grids to the number of all monitoring grids to form an abnormal proportion; When the abnormal proportion is greater than a preset proportion threshold, the preset frequency threshold is adjusted according to the position of the abnormal debris flow grid to form an adjusted frequency threshold.

[0013] Further, adjusting the preset frequency threshold according to the position of the abnormal debris flow grid to form the adjusted frequency threshold includes: Obtaining the distance from the position of each abnormal debris flow grid to the position of a preset center point to form a number of distribution distances; Calculate the standard deviation of all distribution distances to form the distribution concentration; When the distribution concentration is less than a preset distribution concentration threshold, the preset frequency threshold is reduced according to the preset distribution concentration threshold and the relative deviation of the distribution concentration and a preset adjustment coefficient to form an adjusted frequency threshold.

[0014] Further, the preset synchronization threshold is corrected according to the number of abnormal debris flow grids determined based on the adjustment frequency threshold within the preset correction time, and the corrected synchronization threshold is formed, including: Calculating the standard deviation of the number of abnormal debris flow grids to form a corrected number fluctuation value; When the corrected quantity fluctuation value is greater than the preset quantity fluctuation threshold, the preset synchronization threshold is reduced 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.

[0015] On the other hand, the present invention also provides a debris flow infrasound signal recognition system, comprising: A data acquisition module is used to collect the real-time signal frequency, real-time signal amplitude, and real-time flow speed and real-time transparency of the infrasound signal in each monitoring grid in the debris flow monitoring area divided by grids; A first determination module, connected to the data acquisition module, for determining a plurality of first temporary grids according to the real-time signal frequency and a preset frequency threshold; a second determination module, connected to the data acquisition module and the first determination module respectively, 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 abnormal determination module, which is connected to the data acquisition module and the second determination module respectively, and is used to determine 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; An adjustment module, which is connected to the data acquisition module and the abnormality determination module respectively, and is used to adjust the preset frequency threshold according to the position and number of all the abnormal debris flow grids to form an adjusted frequency threshold; A correction module, which is connected to the adjustment module and the abnormality determination module respectively, and is used to correct the preset synchronization threshold according to the number of abnormal debris flow grids determined based on the adjustment frequency threshold within a preset correction time to form a corrected synchronization threshold; An alarm module is connected to the correction module and the abnormality determination module respectively, and is used to issue an alarm to all the abnormal debris flow grids determined based on the correction synchronization threshold.

[0016] Compared with the prior art, the beneficial effect of the present invention is that by comprehensively utilizing multiple parameters such as real-time signal frequency, amplitude, mud and water flow speed and transparency, and adopting dynamic threshold adjustment and correction strategies, efficient identification of debris flow abnormal grids is achieved. This method can not only flexibly adjust the frequency and synchronization threshold 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, and improve the reliability of debris flow secondary signal identification. Through this intelligent identification and early warning mechanism, the timeliness of disaster warning can be significantly improved, potential debris flow risks can be predicted in advance, and relevant departments can be helped to respond quickly, effectively solving the problem of reduced identification accuracy due to the difficulty of sample collection and unclear frequency differences.

[0017] Furthermore, by comparing the real-time signal frequency with the preset frequency threshold to screen out the first temporary grid, those grids that may have signs of debris flow can be effectively identified in advance. This screening mechanism can help quickly lock possible debris flow activity areas, reduce the computational burden of subsequent analysis, and improve the response speed and accuracy of the identification system, thereby providing a reliable basis for timely warning.

[0018] Furthermore, by calculating the amplitude fluctuation value and velocity fluctuation value, grids that show large fluctuations on a time scale can be effectively identified. This fluctuation analysis helps to screen out areas where debris flows are more likely to occur, provides a more detailed spatial division, enhances the system's sensitivity to the direction and trend of debris flows, and can more accurately locate potential danger areas, thereby providing more reliable data support for subsequent anomaly detection and early warning.

[0019] Furthermore, by judging the relative deviation of the amplitude fluctuation value and the velocity fluctuation value, the misjudgment caused by external noise or inconspicuous fluctuation can be effectively eliminated, ensuring that only when the abnormal fluctuation is large is it judged as the second temporary grid, thereby improving the recognition accuracy of debris flow infrasound signals and reducing the probability of false alarms.

[0020] Furthermore, by calculating the transparency fluctuation value, the changes caused by debris flow can be accurately captured, and the synchronization comparison with adjacent grids can further improve the accuracy of judgment, which can reduce environmental interference, optimize the debris flow monitoring and early warning system, and improve the reliability of the system and the timeliness of the early warning.

[0021] Furthermore, the abnormal changes of debris flows can be judged through the synchronization of transparency fluctuations, thereby improving the accuracy and timeliness of abnormality identification, reducing misjudgments, and enhancing the monitoring capabilities and response speed of the system, especially in complex terrain or harsh environments, and being able to more reliably capture the true situation of debris flow activities.

[0022] Furthermore, by dynamically adjusting the threshold according to the actual abnormal distribution of debris flow, misjudgment or missed judgment caused by fixed threshold is avoided, the sensitivity and recognition accuracy of abnormal debris flow signals are improved, making the system more adaptable and reliable in different environments and complex conditions.

[0023] Furthermore, by adjusting the frequency threshold according to the distribution of abnormal debris flow grids, the spatial distribution characteristics of debris flow can be more accurately reflected to avoid over-response or omission of abnormal conditions. This method can improve the sensitivity and accuracy of debris flow monitoring, especially in areas where abnormal debris flow grids are concentrated, and improve the system's ability to predict and warn of potential disasters.

[0024] Furthermore, through dynamic monitoring and analysis of fluctuations in the number of abnormal debris flow grids, the synchronization threshold is effectively adjusted, so that the system can respond more sensitively to real-time changes in debris flows, prevent false alarms or missed alarms due to excessively high thresholds, optimize alarm accuracy and response speed, and thus improve the accuracy and reliability of debris flow disaster warnings.

[0025] Furthermore, through a multi-level, 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 and accurately identify abnormal debris flow grids in real time, avoid the generation of false alarms, and ensure the efficiency and accuracy of debris flow monitoring. In addition, the system's intelligent correction mechanism improves its adaptability in complex environments, making the recognition process more sensitive and stable. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a flow chart of the method for identifying debris flow infrasound signals in this embodiment; Figure 2 A decision logic diagram for determining the first temporary grid in this embodiment; Figure 3 A decision logic diagram for determining the second temporary grid in this embodiment; Figure 4 Schematic diagram of the debris flow infrasound signal recognition system of this embodiment. DETAILED DESCRIPTION

[0027] In order to make the objects and advantages of the present invention more clearly understood, the present invention is 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.

[0028] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0029] See also Figure 1 As shown, it is a flow chart of the method for identifying debris flow infrasound signals in this embodiment; On the one hand, this embodiment provides a method for identifying debris flow infrasound signals, including: Collect the real-time signal frequency, real-time signal amplitude, and real-time flow speed and real-time transparency of the infrasound signal in each monitoring grid in the debris flow monitoring area divided by grids; Determine a plurality of first temporary grids according to the real-time signal frequency and a preset frequency threshold; Determine a plurality of second temporary grids according to the real-time signal amplitude and the real-time flow speed of each of the first temporary grids; Determine 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 numbers of all the abnormal debris flow grids to form an adjusted frequency threshold; The preset synchronization threshold is corrected according to the number of abnormal debris flow grids determined based on the adjustment frequency threshold within a preset correction time period to form a corrected synchronization threshold; An alarm is issued for all the abnormal debris flow grids determined based on the modified synchronization threshold.

[0030] The data collection process involves laying out multiple monitoring grids in the debris flow monitoring area and dividing the grids using geographic information system (GIS) technology. Specifically, this method divides the monitoring area into regular rectangular or square grids from a bird's-eye view. Sensors or monitoring equipment are installed in each grid to collect the frequency and amplitude of infrasound signals, mud and water flow speed, 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 locations and time points. All sensors transmit the collected data in each grid in real time through wireless or wired networks, and store and process them through data acquisition modules. 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.

[0031] Real-time transparency refers to the degree of light transmission of suspended matter in muddy water in 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 to measure the flow of muddy water and the intensity of debris flow. Through real-time transparency, the fluidity of muddy water and whether there is a large degree of sediment flow can be judged.

[0032] The preset frequency threshold is a standard limit for judging the frequency of the infrasound signal, which depends on the characteristics of the debris flow and the frequency range of the infrasound signal. It is usually set between 1 Hz and 100 Hz. In this embodiment, it is set to 30 Hz to ensure that the frequency difference between the normal environment and the debris flow activity can be accurately distinguished, thereby improving the accuracy of recognition.

[0033] The preset synchronization threshold is a standard for judging whether the transparency changes of adjacent grids are synchronized. It depends on the dynamic characteristics of mud and water flow in the debris flow and 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 the debris flow and reduce misjudgment.

[0034] The preset correction duration is the time window used to correct the synchronization threshold, which depends on the speed of the debris flow development and the frequency of the signal change. 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 time, thereby enhancing the sensitivity and accuracy of the system.

[0035] By dividing the debris flow monitoring area into grids, the frequency, amplitude, mud and water flow speed and transparency data of the infrasound signal in each grid are collected. First, the first temporary grid is determined according to the signal frequency and the preset frequency threshold, and then the second temporary grid is further screened out according to the signal amplitude and flow speed. By analyzing the transparency fluctuations of the adjacent second temporary grids and the preset synchronization threshold, the abnormal debris flow grid is determined. Then, the frequency threshold is adjusted according to the number and position of the abnormal grids, and the synchronization threshold is corrected. Finally, an alarm is issued for the identified abnormal grid to indicate the risk of debris flow.

[0036] By comprehensively utilizing multiple parameters such as real-time signal frequency, amplitude, mud and water flow speed and transparency, and adopting dynamic threshold adjustment and correction strategies, efficient identification of debris flow abnormal 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 correcting the synchronization threshold in real time, and improve the reliability of debris flow secondary signal identification. Through this intelligent identification and early warning mechanism, the timeliness of disaster warning can be significantly improved, potential debris flow risks can be predicted in advance, and relevant departments can be helped to respond quickly, effectively solving the problem of reduced identification accuracy due to the difficulty of sample collection and unclear frequency differences.

[0037] Please continue reading Figure 2 As shown, it is a decision logic diagram for determining the first temporary grid in this embodiment; Determining a plurality of first temporary grids according to the real-time signal frequency and a preset frequency threshold comprises: When the real-time signal frequency is less than the preset frequency threshold, the monitoring grid is determined to be the first temporary grid, and a plurality of first temporary grids are formed.

[0038] In 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 monitoring grid is less than the preset frequency threshold, the monitoring grid is determined to be the first temporary grid, and several first temporary grids are formed. This step is a preliminary screening of the signal frequency. By screening out grids below the preset frequency threshold, it provides a data basis for subsequent further analysis.

[0039] By comparing the real-time signal frequency with the preset frequency threshold and screening out the first temporary grid, those grids that may have signs of debris flow can be effectively identified in advance. This screening mechanism can help quickly lock possible debris flow activity areas, reduce the computational burden of subsequent analysis, and improve the response speed and accuracy of the identification system, thereby providing a reliable basis for timely warning.

[0040] Specifically, determining a plurality of second temporary grids according to the real-time signal amplitude and the real-time flow speed of each of the first temporary grids includes: Calculate the standard deviation of the real-time signal amplitude within a preset determined time period to form an amplitude fluctuation value; Calculating the standard deviation of the real-time flow velocity within the preset determined time period to form a flow velocity fluctuation value; A plurality of second temporary grids are determined according to the amplitude fluctuation value and the flow velocity fluctuation value.

[0041] The preset determination time 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 the debris flow. It is usually set between several minutes and tens of minutes. In this embodiment, the preset determination time is set to 30 minutes, which can effectively balance the real-time data and the stability of the fluctuation characteristics, avoid noise interference from short-term fluctuations, and at the same time capture significant changes in the debris flow process to ensure accurate identification of abnormal signals.

[0042] Based on the first temporary grid, the system further analyzes the changes in the real-time signal amplitude and real-time flow velocity in each grid. First, the standard deviation of the real-time signal amplitude in each grid within the preset time length is calculated to obtain the amplitude fluctuation value; then the standard deviation of the real-time flow velocity of each grid within the same time length is calculated to obtain the flow velocity fluctuation value. Then, based on the size of these two fluctuation values, it is determined which grids show larger fluctuations and divided into the second temporary grid to provide a more accurate reference for subsequent anomaly detection.

[0043] By calculating the amplitude fluctuation value and velocity fluctuation value, grids that show large fluctuations on a time scale can be effectively identified. This fluctuation analysis helps to screen out areas where debris flows are more likely to occur, provides a more detailed spatial division, enhances the system's sensitivity to the direction and trend of debris flows, and can more accurately locate potential danger areas, thereby providing more reliable data support for subsequent anomaly detection and early warning.

[0044] Please continue reading Figure 3 As shown, it is a decision logic diagram for determining the second temporary grid in this embodiment; Determining a plurality of second temporary grids according to the amplitude fluctuation value and the flow velocity fluctuation value comprises: Calculating a 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, the first temporary grid is determined to be the second temporary grid.

[0045] The preset fluctuation deviation threshold is the critical value for judging the relative deviation of the amplitude fluctuation value and the flow velocity fluctuation value, which depends on the characteristic fluctuation range of the 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 while avoiding misjudgment due to environmental noise or other slight fluctuations, thereby ensuring the accuracy and sensitivity of debris flow identification.

[0046] First, the relative deviation of the amplitude fluctuation value and the velocity fluctuation value is calculated to form the fluctuation deviation. Then, by comparing the fluctuation deviation with the preset fluctuation deviation threshold, if the fluctuation deviation is greater than the threshold, the first temporary grid is determined to be the second temporary grid, and the area with large signal fluctuation is further screened out to accurately identify potential debris flow anomalies.

[0047] By judging the relative deviation of the amplitude fluctuation value and the velocity fluctuation value, the misjudgment caused by external noise or inconspicuous fluctuation can be effectively eliminated, ensuring that only when the abnormal fluctuation is large is it judged as the second temporary grid, thereby improving the recognition accuracy of debris flow infrasound signals and reducing the probability of false alarms.

[0048] Specifically, 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 a standard deviation of the real-time transparency of a single second temporary grid within a preset determination time period to form a first transparency fluctuation value; Calculating the standard deviation of the real-time transparency of the adjacent second temporary grids within the preset determination time to form a second transparency fluctuation value; The second temporary grid is determined to be the abnormal debris flow grid according to the first transparency fluctuation value, the second transparency fluctuation value and the preset synchronization threshold, so as to form a plurality of abnormal debris flow grids.

[0049] The preset judgment time refers to the time window used in judging real-time transparency fluctuations, which depends on the changing speed of the debris flow and the response speed of the monitoring system. It is usually set between several minutes and tens of minutes. In this embodiment, it is set to 10 minutes, which can effectively filter out misjudgments caused by instantaneous fluctuations, while quickly responding to real changes in the debris flow, thereby improving the accuracy and timeliness of the early warning.

[0050] The transparency fluctuation value is formed by calculating the real-time transparency standard deviation of a single second temporary grid and adjacent second temporary grids within the preset determination time. 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, the grid is determined to be an abnormal debris flow grid, and multiple abnormal grids are identified.

[0051] By calculating the transparency fluctuation value, the changes caused by debris flow can be accurately captured, and the synchronization comparison with adjacent grids can further improve the accuracy of judgment, which can reduce environmental interference, optimize the debris flow monitoring and early warning system, and improve the reliability of the system and the timeliness of the early warning.

[0052] Specifically, 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, and forming a plurality of abnormal debris flow grids includes: Drawing a variation curve of the first transparency fluctuation value to form a first transparency curve; Drawing a variation curve of the second transparency fluctuation value to form a second transparency curve; calculating the cosine similarity of 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 the abnormal debris flow grids, and a plurality of abnormal debris flow grids are formed.

[0053] According to the change curve of the first transparency fluctuation value and the second transparency fluctuation value, the cosine similarity between the two is calculated to form a synchronization degree. By comparing the synchronization degree with a preset synchronization degree threshold, when the synchronization degree is greater than the threshold, the corresponding second temporary grid is determined to be an abnormal debris flow grid, thereby identifying multiple abnormal debris flow grids.

[0054] Abnormal changes in debris flows can be judged through the synchronization of transparency fluctuations, thereby improving the accuracy and timeliness of abnormal identification, reducing misjudgments, and enhancing the system's monitoring capabilities and response speed. Especially in complex terrain or harsh environments, the true situation of debris flow activities can be more reliably captured.

[0055] Specifically, adjusting the preset frequency threshold according to the positions and numbers of all the abnormal debris flow grids to form the adjusted frequency threshold includes: Calculate the ratio of the number of abnormal debris flow grids to the number of all monitoring grids to form an abnormal proportion; When the abnormal proportion is greater than a preset proportion threshold, the preset frequency threshold is adjusted according to the position of the abnormal debris flow grid to form an adjusted frequency threshold.

[0056] The preset ratio threshold is the ratio of the number of abnormal debris flow grids to the total number of monitoring grids. It is used 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. It is usually set between 5% and 20%. In this embodiment, it is set to 10%, which can effectively avoid excessive adjustment of the threshold, ensure that the system's judgment of debris flow anomalies does not lose sensitivity, and avoid excessive response to occasional situations, thereby ensuring a relatively stable and reasonable recognition effect.

[0057] The abnormal proportion is obtained by calculating the ratio of the number of abnormal debris flow grids to the number of all monitoring grids. If the abnormal proportion is greater than the preset proportion threshold, the preset frequency threshold is adjusted according to the position of the abnormal debris flow grid to form an adjusted frequency threshold, thereby improving the accuracy and flexibility of frequency determination.

[0058] By dynamically adjusting the threshold according to the actual abnormal distribution of debris flow, misjudgment or missed judgment caused by fixed threshold can be avoided, the sensitivity and recognition accuracy of abnormal debris flow signals are improved, and the system has higher adaptability and reliability in different environments and complex conditions.

[0059] Specifically, adjusting the preset frequency threshold according to the position of the abnormal debris flow grid to form the adjusted frequency threshold includes: Obtaining the distance from the position of each abnormal debris flow grid to the position of a preset center point to form a number of distribution distances; Calculate the standard deviation of all distribution distances to form the distribution concentration; When the distribution concentration is less than a preset distribution concentration threshold, the preset frequency threshold is reduced according to the preset distribution concentration threshold, the relative deviation of the distribution concentration and the preset adjustment coefficient to form an adjusted frequency threshold, wherein the preset distribution concentration threshold, the relative deviation of the distribution concentration and the adjusted frequency threshold are positively correlated.

[0060] The preset center point is a fixed reference position, which is usually set at the geometric center of the debris flow monitoring area or a specific location selected according to actual needs. It depends on the geographical distribution of the monitoring area and the specific targets to be analyzed. It is usually set at the center of the area to facilitate 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 to the geometric center point of the monitoring area (the longitude and latitude of the geographic coordinates), which can make the distance comparison between all grids in the monitoring area and the center point more balanced, which helps to accurately analyze the abnormal situation of debris flow and optimize the effect of frequency threshold adjustment.

[0061] For each abnormal debris flow grid, its corresponding coordinate information is obtained through sensors or monitoring equipment. GPS positioning or geographic coordinate system is usually used to calibrate the grid position. The Euclidean distance formula is used to calculate the distance from each abnormal debris flow grid to the preset center point to form several distribution distances.

[0062] The preset adjustment coefficient is a parameter used to adjust the frequency threshold change. It depends on the characteristics of the monitoring area and the frequency of debris flow. It is usually between 0.1 and 1.0. In this embodiment, it is set to 0.3, which can adapt to the dynamic changes of debris flow while maintaining the sensitivity of frequency threshold adjustment and the stability of the system.

[0063] According to the position of the abnormal debris flow grid, the distance from the grid center point of each abnormal debris flow grid to the preset center point is first obtained to form a number of distribution distances. Then, the standard deviation of all distribution distances is calculated to obtain the distribution concentration. Next, when the distribution concentration is less than the preset distribution concentration threshold, the preset frequency threshold is adjusted by calculating the relative deviation and the preset adjustment coefficient so as to reduce the frequency threshold and form an adjusted frequency threshold.

[0064] By adjusting the frequency threshold according to the distribution of abnormal debris flow grids, the spatial distribution characteristics of debris flow can be more accurately reflected to avoid over-response or missing abnormal situations. This method can improve the sensitivity and accuracy of debris flow monitoring, especially in areas where abnormal debris flow grids are concentrated, and improve the system's ability to predict and warn of potential disasters.

[0065] Specifically, the preset synchronization threshold is corrected according to the number of abnormal debris flow grids determined based on the adjustment frequency threshold within the preset correction time, and the corrected synchronization threshold is formed, including: Calculating the standard deviation of the number of abnormal debris flow grids to form a corrected number fluctuation value; When the corrected quantity fluctuation value is greater than the preset quantity fluctuation threshold, the preset synchronization threshold is reduced according to the relative deviation between the corrected quantity fluctuation value and the preset quantity fluctuation threshold and the 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.

[0066] The preset quantity fluctuation threshold is a threshold used to determine whether the correction quantity fluctuation value is significant. It depends on the fault tolerance of the system and the characteristics of the monitored area. It 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 due to overly strict threshold settings.

[0067] 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. It is usually set between 0.1 and 1.0. In this embodiment, it is set to 0.5, which can make the synchronization threshold adjustment smoother and avoid excessive adjustments that lead to overly sensitive alarm responses.

[0068] Within the preset correction time, the number of abnormal debris flow grids determined based on the adjusted frequency threshold is used to calculate the standard deviation of the number to obtain a corrected number fluctuation value. If the corrected number fluctuation value is greater than the preset number fluctuation threshold, the preset synchronization threshold is reduced according to the relative deviation between the corrected number fluctuation value and the preset number fluctuation threshold, combined with the preset correction coefficient, to form a corrected synchronization threshold.

[0069] By dynamically monitoring and analyzing the fluctuations in the number of abnormal debris flow grids, the synchronization threshold is effectively adjusted, allowing the system to respond more sensitively to real-time changes in debris flows, preventing false alarms or missed alarms due to excessively high thresholds, optimizing alarm accuracy and response speed, and thus improving the accuracy and reliability of debris flow disaster warnings.

[0070] Please continue reading Figure 4 As shown, it is a schematic diagram of the debris flow infrasound signal recognition system of this embodiment; On the other hand, this embodiment also provides a debris flow infrasound signal recognition system, including: A data acquisition module is used to collect the real-time signal frequency, real-time signal amplitude, and real-time flow speed and real-time transparency of the infrasound signal in each monitoring grid in the debris flow monitoring area divided by grids; A first determination module, connected to the data acquisition module, for determining a plurality of first temporary grids according to the real-time signal frequency and a preset frequency threshold; a second determination module, connected to the data acquisition module and the first determination module respectively, 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 abnormal determination module, which is connected to the data acquisition module and the second determination module respectively, and is used to determine 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; An adjustment module, which is connected to the data acquisition module and the abnormality determination module respectively, and is used to adjust the preset frequency threshold according to the position and number of all the abnormal debris flow grids to form an adjusted frequency threshold; A correction module, which is connected to the adjustment module and the abnormality determination module respectively, and is used to correct the preset synchronization threshold according to the number of abnormal debris flow grids determined based on the adjustment frequency threshold within a preset correction time to form a corrected synchronization threshold; An alarm module is connected to the correction module and the abnormality determination module respectively, and is used to issue an alarm to all the abnormal debris flow grids determined based on the correction synchronization threshold.

[0071] Through the collaborative work of multiple modules, the data acquisition module first collects data such as infrasound signal frequency, signal amplitude, flow velocity and transparency in the debris flow monitoring area in real time. Then, the first determination module determines the preliminary grid according to the real-time signal frequency and the preset threshold, and the second determination module further screens the grid according to the signal amplitude and flow velocity. The abnormal determination module identifies abnormal debris flow grids by analyzing the transparency changes of adjacent grids and combining the synchronization threshold. The adjustment module adjusts the frequency threshold according to the location and number of abnormal grids, and the correction module corrects the synchronization threshold according to the fluctuation of the number of abnormal grids. Finally, the alarm module issues an alarm based on the corrected synchronization threshold.

[0072] Through the 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 and accurately identify abnormal debris flow grids in real time, avoid the generation of false alarms, and ensure the efficiency and accuracy of debris flow monitoring. In addition, the system's intelligent correction mechanism improves its adaptability in complex environments, making the recognition process more sensitive and stable.

[0073] So far, the technical solutions of the present invention have 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: include: Collect the real-time signal frequency, real-time signal amplitude, and real-time flow speed and real-time transparency of the infrasound signal in each monitoring grid in the debris flow monitoring area divided by grids; Determine a plurality of first temporary grids according to the real-time signal frequency and a preset frequency threshold; Determine a plurality of second temporary grids according to the real-time signal amplitude and the real-time flow speed of each of the first temporary grids; Determine 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 numbers of all the abnormal debris flow grids to form an adjusted frequency threshold; The preset synchronization threshold is corrected according to the number of abnormal debris flow grids determined based on the adjustment frequency threshold within a preset correction time period to form a corrected synchronization threshold; An alarm is issued for all the abnormal debris flow grids determined based on the modified synchronization threshold.

2. The method for identifying debris flow infrasound signals according to claim 1, characterized in that: Determining a number of first temporary grids according to the real-time signal frequency and a preset frequency threshold comprises: When the real-time signal frequency is less than the preset frequency threshold, the monitoring grid is determined to be the first temporary grid, and a plurality of first temporary grids are formed.

3. The method for identifying debris flow infrasound signals according to claim 2, characterized in that: Determining a plurality of second temporary grids according to the real-time signal amplitude and the real-time flow speed of each of the first temporary grids comprises: Calculate the standard deviation of the real-time signal amplitude within a preset determined time period to form an amplitude fluctuation value; Calculating the standard deviation of the real-time flow velocity within the preset determined time period to form a flow velocity fluctuation value; A plurality of second temporary grids are determined according to the amplitude fluctuation value and the flow velocity fluctuation value.

4. The method for identifying debris flow infrasound signals according to claim 3, characterized in that: Determining a plurality of second temporary grids according to the amplitude fluctuation value and the flow velocity fluctuation value comprises: Calculating a 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, the first temporary grid is determined to be the second temporary grid.

5. The method for identifying debris flow infrasound signals according to claim 4, characterized in that: 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 a standard deviation of the real-time transparency of a single second temporary grid within a preset determination time period to form a first transparency fluctuation value; Calculating the standard deviation of the real-time transparency of the adjacent second temporary grids within the preset determination time to form a second transparency fluctuation value; The second temporary grid is determined to be the abnormal debris flow grid according to the first transparency fluctuation value, the second transparency fluctuation value and the preset synchronization threshold, so as to form a plurality of abnormal debris flow grids.

6. The method for identifying debris flow infrasound signals according to claim 5, characterized in that: 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, and forming a plurality of abnormal debris flow grids comprises: Drawing a variation curve of the first transparency fluctuation value to form a first transparency curve; Drawing a variation curve of the second transparency fluctuation value to form a second transparency curve; calculating the cosine similarity of 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 the abnormal debris flow grids, and a plurality of abnormal debris flow grids are formed.

7. The method for identifying debris flow infrasound signals according to claim 6, characterized in that: Adjusting the preset frequency threshold according to the positions and numbers of all the abnormal debris flow grids to form the adjusted frequency threshold comprises: Calculate the ratio of the number of abnormal debris flow grids to the number of all monitoring grids to form an abnormal proportion; When the abnormal proportion is greater than a preset proportion threshold, the preset frequency threshold is adjusted according to the position of the abnormal debris flow grid to form an adjusted frequency threshold.

8. The method for identifying debris flow infrasound signals according to claim 7, characterized in that: Adjusting the preset frequency threshold according to the position of the abnormal debris flow grid to form the adjusted frequency threshold includes: Obtaining the distance from the position of each abnormal debris flow grid to the position of a preset center point to form a number of distribution distances; Calculate the standard deviation of all distribution distances to form the distribution concentration; When the distribution concentration is less than a preset distribution concentration threshold, the preset frequency threshold is reduced according to the preset distribution concentration threshold and the relative deviation of the distribution concentration and a preset adjustment coefficient to form an adjusted frequency threshold.

9. The method for identifying debris flow infrasound signals according to claim 8, characterized in that: The preset synchronization threshold is corrected according to the number of abnormal debris flow grids determined based on the adjustment frequency threshold within the preset correction time, and the corrected synchronization threshold is formed, comprising: Calculating the standard deviation of the number of abnormal debris flow grids to form a corrected number fluctuation value; When the corrected quantity fluctuation value is greater than the preset quantity fluctuation threshold, the preset synchronization threshold is reduced 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.

10. A debris flow infrasound signal recognition system, based on the debris flow infrasound signal recognition method according to any one of claims 1 to 9, comprising: A data acquisition module is used to collect the real-time signal frequency, real-time signal amplitude, and real-time flow speed and real-time transparency of the infrasound signal in each monitoring grid in the debris flow monitoring area divided by grids; A first determination module, connected to the data acquisition module, for determining a plurality of first temporary grids according to the real-time signal frequency and a preset frequency threshold; a second determination module, connected to the data acquisition module and the first determination module respectively, 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 abnormal determination module, which is connected to the data acquisition module and the second determination module respectively, and is used to determine 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; An adjustment module, which is connected to the data acquisition module and the abnormality determination module respectively, and is used to adjust the preset frequency threshold according to the position and number of all the abnormal debris flow grids to form an adjusted frequency threshold; A correction module, which is connected to the adjustment module and the abnormality determination module respectively, and is used to correct the preset synchronization threshold according to the number of abnormal debris flow grids determined based on the adjustment frequency threshold within a preset correction time to form a corrected synchronization threshold; An alarm module is connected to the correction module and the abnormality determination module respectively, and is used to issue an alarm to all the abnormal debris flow grids determined based on the correction synchronization threshold.

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