Earthquake early warning system based on ubiquitous vibration sensing application

Abstract

The invention provides an earthquake early warning system based on ubiquitous vibration sensing application. The earthquake early warning system comprises the following steps: acquiring a sound wave signal of a target area through a sensor array; performing attenuation compensation and amplitude normalization processing on the sound wave signal according to a sound wave propagation attenuation model; carrying out noise reduction processing on the normalized sound wave signal by adopting a self-adaptive filtering algorithm; performing time-frequency domain analysis and feature extraction on the denoised sound wave signal through a wavelet transform algorithm; performing matching degree calculation and similarity judgment on the extracted features and a pre-established sound wave signal feature template library, and identifying suspected target signals; verifying the authenticity of the suspected target signal by adopting a time-frequency domain conjoint analysis method; and according to a signal identification and verification result, carrying out positioning and parameter estimation on the confirmed target signal.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and in particular to an earthquake early warning system based on ubiquitous vibration sensing application. Background Art

[0002] In a system that realizes multi-channel data acquisition of seismic waves and acoustic waves based on network remote control, the ability to monitor weak acoustic wave signals is a key technical challenge. In terms of business, how to effectively identify and extract extremely weak earthquake precursor acoustic waves or specific environmental acoustic wave signals in complex background noise requires the system to have extremely high sensitivity and signal-to-noise ratio. In terms of technical implementation, it is necessary to develop highly sensitive acoustic wave sensors and combine them with advanced signal processing algorithms, such as wavelet transform and adaptive filtering, to accurately capture and amplify weak signals, while suppressing noise interference to ensure the accuracy and reliability of data acquisition. Summary of the invention

[0003] The earthquake early warning system based on ubiquitous vibration sensing application provided by the present invention mainly includes: The acoustic wave signals in the target area are collected through a sensor array; the acoustic wave signals are subjected to attenuation compensation and amplitude normalization processing according to the acoustic wave propagation attenuation model; the normalized acoustic wave signals are subjected to noise reduction processing by an adaptive filtering algorithm; the acoustic wave signals after noise reduction are subjected to time-frequency domain analysis and feature extraction by a wavelet transform algorithm; the extracted features are matched and similarity judged with a pre-established acoustic wave signal feature template library to identify suspected target signals; the authenticity of the suspected target signals is verified by a time-frequency domain joint analysis method; and the confirmed target signals are located and parameter estimation is performed based on the results of signal identification and verification.

[0004] Furthermore, the acquisition of the target area sound wave signal by the sensor array includes: deploying a high-sensitivity sound wave sensor array to acquire the sound wave signal of the target area in all directions and at multiple angles; optimizing the position and number of sensors in the sensor array according to the terrain features and the distribution of noise sources; and acquiring the sound wave signal of the target area to obtain the original sound wave signal.

[0005] Furthermore, the attenuation compensation and amplitude normalization processing of the sound wave signal according to the sound wave propagation attenuation model includes: establishing a sound wave signal propagation attenuation model based on the physical characteristics of sound wave propagation; performing attenuation compensation on the original sound wave signal according to the attenuation model; and performing amplitude normalization processing on the sound wave signal after attenuation compensation to obtain a normalized sound wave signal.

[0006] Furthermore, the use of an adaptive filtering algorithm to perform noise reduction processing on the normalized sound wave signal includes: obtaining the normalized sound wave signal; automatically adjusting filter parameters according to the statistical characteristics of the normalized sound wave signal using an adaptive filtering algorithm; and filtering the normalized sound wave signal according to the adjusted filter parameters to obtain a noise-reduced sound wave signal.

[0007] Furthermore, the time-frequency domain analysis and feature extraction of the denoised sound wave signal by wavelet transform algorithm includes: performing wavelet transform on the denoised sound wave signal to obtain decomposition results of the sound wave signal at different scales and resolutions; analyzing the decomposition results to extract feature information of the sound wave signal in the time domain and frequency domain.

[0008] Furthermore, the extracted features are matched and similarity judged with a pre-established acoustic signal feature template library to identify suspected target signals, including: establishing an acoustic signal feature template library, wherein the feature template library contains feature information of earthquake precursor acoustic waves and specific environmental acoustic waves; matching the extracted features with templates in the feature template library is calculated; if the matching degree is greater than a preset threshold, the acoustic signal is judged to be a suspected target signal.

[0009] Furthermore, the use of a joint analysis method in the time and frequency domains to verify the authenticity of the suspected target signal includes: obtaining the suspected target signal; analyzing the energy distribution characteristics of the suspected target signal in the time domain; analyzing the energy distribution characteristics of the suspected target signal in the frequency domain; if the energy distribution characteristics of the suspected target signal in the time domain and the frequency domain meet preset rules, then judging that the suspected target signal is a true target signal.

[0010] Furthermore, based on the results of signal identification and verification, the confirmed target signal is positioned and parameter estimated, including: acquiring the confirmed target signal; determining the occurrence location of the target signal based on the arrival time and arrival direction of the target signal; estimating the strength of the target signal based on the amplitude and frequency of the target signal; and correlating and analyzing the occurrence time, occurrence location and strength information of the target signal with geological, topographical and environmental background information.

[0011] Furthermore, the occurrence time, location and intensity information of the target signal are correlated and analyzed with the geological, topographical and environmental background information, including: obtaining the occurrence time, location and intensity information of the target signal; obtaining the geological information, topographical information and environmental information of the target area; if the occurrence time, location and intensity information of the target signal are correlated with the geological information, topographical information and environmental information, then generating early warning information.

[0012] The technical solution provided by the embodiment of the present invention may have the following beneficial effects: The earthquake early warning system based on ubiquitous vibration sensing provided by the present invention adopts a high-sensitivity sensor array for all-round acquisition to solve the problem that earthquake precursors and specific environmental sound wave signals are weak and easily interfered by noise. The present invention effectively enhances weak signals through technical means such as signal attenuation compensation, adaptive filtering noise reduction and wavelet transform feature extraction. Combined with the feature template library established with prior knowledge, the present invention realizes the recognition and verification of suspected target signals. Through the joint analysis of time and frequency domains, the authenticity of the signal is further judged and false alarms are eliminated. Finally, the confirmation signal is located and parameter estimated to obtain key information. The present invention also associates the recognition results with background information such as geological environment to improve the reliability of early warning. The method can effectively overcome the technical difficulties of weak sound wave signals being difficult to capture and identify in complex noise environments, significantly improve the detection sensitivity and recognition accuracy of earthquake precursors and specific environmental sound wave signals, and provide reliable technical support for early warning decision-making and emergency response in related fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 The flowchart of the earthquake early warning system based on ubiquitous vibration sensing application of the present invention.

[0014] Figure 2 It is a schematic diagram of the flow of the earthquake early warning system based on ubiquitous vibration sensing application of the present invention.

[0015] Figure 3 It is another schematic diagram of the earthquake early warning system based on ubiquitous vibration sensing application of the present invention.

[0016] Figure 4 It is another schematic diagram of the earthquake early warning system based on ubiquitous vibration sensing application of the present invention.

[0017] Figure 5 It is another schematic diagram of the earthquake early warning system based on ubiquitous vibration sensing application of the present invention.

[0018] Figure 6 It is another schematic diagram of the earthquake early warning system based on ubiquitous vibration sensing application of the present invention.

[0019] Figure 7 It is another schematic diagram of the earthquake early warning system based on ubiquitous vibration sensing application of the present invention. DETAILED DESCRIPTION

[0020] In order to further understand the content of the present invention, the present invention is described in detail in conjunction with the accompanying drawings and embodiments. The present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are only used to explain the relevant inventions, rather than to limit the invention. It is also necessary to explain that, for ease of description, only the parts related to the invention are shown in the accompanying drawings.

[0021] like Figure 1-7 The earthquake early warning system based on ubiquitous vibration sensing application in this embodiment may specifically include: Step S101, using a high-sensitivity acoustic wave sensor array to collect acoustic wave signals from all directions and angles in the target area to improve the probability and accuracy of capturing weak signals. The layout of the sensor array should fully consider the terrain characteristics and noise source distribution, optimize the location and number of sensors, and maximize the signal-to-noise ratio of signal collection.

[0022] Step S102, based on the physical characteristics of sound wave propagation, establish an acoustic wave signal propagation attenuation model, perform attenuation compensation and amplitude normalization processing on the collected original acoustic wave signal, reduce the dynamic range of the signal amplitude, and lay the foundation for subsequent signal enhancement processing.

[0023] Step S103, in view of the characteristics of complex background noise, an adaptive filtering algorithm is used to perform noise reduction processing on the normalized sound wave signal. The adaptive filtering algorithm automatically adjusts the filter parameters and dynamically adapts to the statistical characteristics of the noise, thereby effectively suppressing the background noise and extracting the weak target signal.

[0024] Step S104, based on the adaptive filtering and noise reduction, the wavelet transform algorithm is further used to perform time-frequency domain analysis and feature extraction on the weak signal. The wavelet transform can effectively highlight the local features of the weak signal by performing multi-scale and multi-resolution decomposition on the signal, and provide reliable feature information for subsequent signal recognition and judgment.

[0025] Step S105: Based on the prior knowledge of earthquake precursor sound waves and specific environmental sound waves, a feature template library of sound wave signals is established. The signal features extracted by wavelet transform are matched with the features in the template library and similarity is judged to identify suspected target signals.

[0026] Step S106: For the identified suspected target signal, the authenticity of the signal is further verified by using a time-frequency domain joint analysis method. By analyzing the energy distribution characteristics of the signal in the time domain and frequency domain, it is determined whether the signal has the typical characteristics of earthquake precursor sound waves or specific environmental sound waves, and false alarm signals are eliminated.

[0027] Step S107, based on the results of signal identification and verification, locate and estimate the parameters of the confirmed earthquake precursor sound wave or specific environmental sound wave signal, obtain key parameter information such as the signal's occurrence time, location, and signal strength, and provide data support for subsequent early warning decisions and emergency responses. At the same time, the identification and positioning results are correlated with background information such as geology, topography, and environment to improve the reliability and accuracy of the early warning.

[0028] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An earthquake early warning system based on ubiquitous vibration sensing application, characterized in that: include: Setting a sensor array to collect acoustic wave signals in the target area; performing attenuation compensation and amplitude normalization processing on the acoustic wave signal according to an acoustic wave propagation attenuation model; Adopting an adaptive filtering algorithm to perform noise reduction processing on the normalized sound wave signal; Performing time-frequency domain analysis and feature extraction on the noise-reduced sound wave signal by using a wavelet transform algorithm; The extracted features are matched with a pre-established acoustic signal feature template library and similarity is determined to identify suspected target signals; Using a time-frequency domain joint analysis method to verify the authenticity of the suspected target signal; According to the results of signal identification and verification, the confirmed target signal is located and its parameters are estimated.

2. The earthquake early warning system based on ubiquitous vibration sensing application according to claim 1 is characterized in that: The sensor array collects the target area sound wave signal, including: Deploy a high-sensitivity acoustic wave sensor array to collect acoustic wave signals from all directions and angles in the target area; Optimizing the position and number of sensors in the sensor array according to the topographic features and the distribution of noise sources; The sound wave signal of the target area is collected to obtain the original sound wave signal.

3. The earthquake early warning system based on ubiquitous vibration sensing application according to claim 1, characterized in that: The acoustic wave signal is subjected to attenuation compensation and amplitude normalization processing according to an acoustic wave propagation attenuation model, including: Based on the physical characteristics of sound wave propagation, an acoustic wave signal propagation attenuation model is established; According to the attenuation model, performing attenuation compensation on the original sound wave signal; The attenuation-compensated acoustic wave signal is subjected to amplitude normalization processing to obtain a normalized acoustic wave signal.

4. The earthquake early warning system based on ubiquitous vibration sensing application according to claim 1, characterized in that: The normalized sound wave signal is subjected to noise reduction processing using an adaptive filtering algorithm, including: Acquiring the normalized sound wave signal; According to the statistical characteristics of the normalized sound wave signal, an adaptive filtering algorithm is used to automatically adjust the filter parameters; The normalized sound wave signal is filtered according to the adjusted filter parameters to obtain a noise-reduced sound wave signal.

5. The earthquake early warning system based on ubiquitous vibration sensing application according to claim 1, characterized in that: The time-frequency domain analysis and feature extraction of the noise-reduced sound wave signal are performed by wavelet transform algorithm, including: Performing wavelet transform on the de-noised sound wave signal to obtain decomposition results of the sound wave signal at different scales and resolutions; The decomposition result is analyzed to extract characteristic information of the acoustic wave signal in the time domain and the frequency domain.

6. The earthquake early warning system based on ubiquitous vibration sensing application according to claim 1, characterized in that: The extracted features are matched with the pre-established acoustic signal feature template library and similarity is judged to identify the suspected target signal, including: Establishing an acoustic signal feature template library, wherein the feature template library contains feature information of earthquake precursor acoustic waves and specific environmental acoustic waves; Calculate the matching degree between the extracted features and the templates in the feature template library; If the matching degree is greater than a preset threshold, the sound wave signal is determined to be a suspected target signal.

7. The earthquake early warning system based on ubiquitous vibration sensing application according to claim 1, characterized in that: The authenticity of the suspected target signal is verified by using a time-frequency domain joint analysis method, including: Acquiring the suspected target signal; Analyzing energy distribution characteristics of the suspected target signal in the time domain; Analyzing energy distribution characteristics of the suspected target signal in the frequency domain; If the energy distribution characteristics of the suspected target signal in the time domain and the frequency domain meet the preset rules, the suspected target signal is determined to be a real target signal.

8. The earthquake early warning system based on ubiquitous vibration sensing application according to claim 1, characterized in that: According to the results of signal identification and verification, the confirmed target signal is located and its parameters are estimated, including: acquiring the confirmed target signal; Determining the occurrence position of the target signal according to the arrival time and arrival direction of the target signal; estimating the strength of the target signal according to the amplitude and frequency of the target signal; The occurrence time, location and intensity information of the target signal are correlated and analyzed with the geological, topographical and environmental background information.

9. The earthquake early warning system based on ubiquitous vibration sensing application according to claim 8, characterized in that: Correlate and analyze the occurrence time, location and intensity information of the target signal with the geological, topographical and environmental background information, including: Obtaining the occurrence time, occurrence location and intensity information of the target signal; Acquiring geological information, topographic information and environmental information of the target area; If the occurrence time, occurrence location and intensity information of the target signal are associated with the geological information, topographic information and environmental information, then early warning information is generated.

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