Security and protection system based on PE-VMD-WT signal denoising

Abstract

The invention discloses a security and protection system based on PE-VMD-WT signal denoising. The security and protection system comprises a plurality of sensor modules; the PE-VMD-WT de-noising processing module is used for carrying out PE-VMD-WT combined de-noising processing on the signals acquired by the plurality of sensor modules; the data fusion module is used for fusing the denoised various sensor data by using a deep learning or traditional machine learning algorithm; the time synchronization processing module is used for processing the time synchronization problem among different sensor data; the signal analysis module is used for analyzing the fused signals and identifying abnormal or potential security threats; and the alarm module is used for triggering an alarm signal when the abnormal or potential security threat is identified. The problem that the signal recognition rate is low due to the fact that single-domain features are not sufficiently extracted through a traditional feature extraction method is solved, and therefore the effective recognition rate of different intrusion times is increased.

Description

Technical Field

[0001] The present invention belongs to the technical field of security systems, and in particular relates to a security system based on PE-VMD-WT signal denoising. Background Art

[0002] With the continuous advancement of modern science and technology and the continuous development of social economy, people's living standards are also improving, but many problems are also highlighted. Personal and property safety are threatened, and social security problems are becoming more and more serious. Therefore, security prevention work should be given enough attention. The perimeter security system is a closed and comprehensive system. By adopting special security measures, it plays a certain protective role for areas and facilities. However, various traditional perimeter security technologies have the following defects in front-end detection equipment:

[0003] First: Traditional perimeter defense equipment includes pulse electronic guardrails, infrared beams, video perimeters, radar detection technology, etc. Pulse electronic guardrails are expensive, consume a lot of power, and are prone to sparks, so they cannot be used in flammable and explosive places; infrared beam equipment is easily affected by heat sources, can only be used in open places, and is greatly affected by terrain; video surveillance requires power supply all day, has poor flexibility, and has blind spots. Radar detection technology requires the installation of sensors, has a limited monitoring area, and is expensive. In addition, the above security technologies are easily affected by electromagnetic interference, poor environmental adaptability, etc., and are easily restricted in certain places.

[0004] The fiber optic perimeter security technology currently used in the market is still in a rapid development stage. Its accuracy, monitoring distance, and stability are constantly improving. However, there are still many problems that need to be solved. For example, in the measurement of vibration signals, there is a lot of noise interference. How to distinguish useful signals from useless signals is critical to subsequent signal processing. Currently, the market mostly uses EMD's modal aliasing technology and VMD's decomposition layer technology, but these two technologies have the problem of being unable to adapt to each other, which greatly affects the denoising results. Summary of the invention

[0005] The purpose of the present invention is to propose a security system based on PE-VMD-WT signal denoising in order to solve the problems of high laying cost, low safety, poor anti-electromagnetic interference ability, etc. that the equipment of the current traditional perimeter system may cause, and the shortcomings of the feature extraction technology of the existing optical cable that cannot well meet the signal recognition and processing requirements.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a security system based on PE-VMD-WT signal denoising, comprising:

[0007] A variety of sensor modules are used to collect different types of signals simultaneously in the security monitoring area;

[0008] A PE-VMD-WT denoising processing module, used for performing PE-VMD-WT joint denoising processing on the signals collected by the multiple sensor modules;

[0009] Data fusion module, which uses deep learning or traditional machine learning algorithms to fuse multiple sensor data after denoising to improve the overall signal quality;

[0010] The time synchronization processing module is used to handle the time synchronization problem between different sensor data to ensure the effectiveness and accuracy of data fusion;

[0011] The signal analysis module is used to analyze the fused signals and identify anomalies or potential security threats;

[0012] and an alarm module, which is used to trigger an alarm signal when an abnormality or potential security threat is identified.

[0013] As a further description of the above technical solution:

[0014] The various sensor modules include but are not limited to video signals collected by a video camera, audio signals collected by an audio sensor, and infrared signals collected by an infrared sensor.

[0015] As a further description of the above technical solution:

[0016] The PE-VMD-WT denoising processing module includes a permutation entropy (PE) module, a variational mode decomposition (VMD) module, a wavelet transform (WT) module and a reconstruction module, wherein the variational mode decomposition (VMD) module is used to decompose the signal collected in the security system into a number of intrinsic mode functions (IMFs), the permutation entropy (PE) module analyzes the IMF decomposed by the variational mode decomposition (VMD) module to distinguish between noise IMFs and useful signal IMFs; the wavelet transform (WT) module denoises the noise IMF, and the reconstruction module reconstructs the denoised IMF components to obtain the final denoised signal.

[0017] As a further description of the above technical solution:

[0018] It also includes a real-time denoising module, which processes the video stream captured by the security camera in real time, and removes noise in the video stream through the PE-VMD-WT denoising processing module to ensure low latency of the denoising processing.

[0019] As a further description of the above technical solution:

[0020] It also includes an abnormal real-time detection module, which uses a machine learning model for behavioral analysis to detect abnormal behavior in the video in real time.

[0021] As a further description of the above technical solution:

[0022] A cloud denoising service station may also be provided to receive signals collected by the security system, the PE-VMD-WT denoising processing module may be provided in the cloud denoising service station, denoising may be performed using the PE-VMD-WT denoising processing module, and the processed data may be returned to the security system.

[0023] As a further description of the above technical solution:

[0024] The cloud denoising service station is provided with an encryption module for protecting transmitted data.

[0025] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0026] 1. In the present invention, video signals collected by video cameras, audio signals collected by audio sensors, and infrared signals collected by infrared sensors are collected by multiple sensor modules. A PE-VMD-WT denoising processing module is used to perform PE-VMD-WT joint denoising processing on the signals collected by the multiple sensor modules. Deep learning or traditional machine learning algorithms are used to fuse the denoised multiple sensor data to improve the overall signal quality. The time synchronization processing module is used to handle the time synchronization problem between different sensor data to ensure the effectiveness and accuracy of data fusion. A signal analysis module is used to analyze the fused signal to identify abnormalities or potential security threats. When the alarm module identifies abnormalities or potential security threats, an alarm signal is triggered. This security system solves the problem of low signal recognition rate caused by insufficient extraction of single-domain features by traditional feature extraction methods, thereby improving the effective recognition rate of different intrusion times.

[0027] 2. In the present invention, the video signal collected by the video camera, the audio signal collected by the audio sensor, and the infrared signal collected by the infrared sensor can also be transmitted to the cloud denoising service station, and the PE-VMD-WT denoising processing module can be set in the cloud denoising service station. The PE-VMD-WT denoising processing module is used for denoising, and the processed data is returned to the security system. This system can improve the availability and scalability, ensure the security and privacy of data transmission, and optimize the algorithm to adapt to different network conditions and delay requirements.

[0028] 3. In the present invention, the PE-VMD-WT denoising processing module includes a permutation entropy (PE) module, a variational mode decomposition (VMD) module, a wavelet transform (WT) module and a reconstruction module, wherein the variational mode decomposition (VMD) module is used to decompose the signal collected in the security system into a number of intrinsic mode functions (IMFs), the permutation entropy (PE) module analyzes the IMF decomposed by the variational mode decomposition (VMD) module to distinguish between noise IMFs and useful signal IMFs; the wavelet transform (WT) module denoises the noise IMF, and the reconstruction module reconstructs the denoised IMF components to obtain the final denoised signal, ensuring that the signal in the security system can still maintain its original characteristics and information after the noise is removed, so as to facilitate subsequent signal processing and analysis, and improve adaptability and denoising effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 It is a framework diagram of embodiment 1 in a security system based on PE-VMD-WT signal denoising.

[0031] Figure 2 It is a framework diagram of Example 2 in a security system based on PE-VMD-WT signal denoising. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0034] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0036] In the description of the embodiments of the present invention, it should be noted that the terms "upper", "inner", etc. indicate directions or positional relationships based on the directions or positional relationships shown in the accompanying drawings, or are directions or positional relationships in which the inventive product is usually placed when in use. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore should not be understood as a limitation on the present invention.

[0037] In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0038] Embodiment 1

[0039] See also Figure 1 The present invention provides a technical solution: a security system based on PE-VMD-WT signal denoising, comprising:

[0040] A variety of sensor modules are used to collect different types of signals simultaneously in the security monitoring area;

[0041] A PE-VMD-WT denoising processing module, used for performing PE-VMD-WT joint denoising processing on the signals collected by the multiple sensor modules;

[0042] Data fusion module, which uses deep learning or traditional machine learning algorithms to fuse multiple sensor data after denoising to improve the overall signal quality;

[0043] The time synchronization processing module is used to handle the time synchronization problem between different sensor data to ensure the effectiveness and accuracy of data fusion;

[0044] The signal analysis module is used to analyze the fused signals and identify anomalies or potential security threats;

[0045] and an alarm module, which is used to trigger an alarm signal when an abnormality or potential security threat is identified.

[0046] The various sensor modules include but are not limited to video signals collected by a video camera, audio signals collected by an audio sensor, and infrared signals collected by an infrared sensor.

[0047] The PE-VMD-WT denoising processing module includes a permutation entropy (PE) module, a variational mode decomposition (VMD) module, a wavelet transform (WT) module and a reconstruction module, wherein the variational mode decomposition (VMD) module is used to decompose the signal collected in the security system into a number of intrinsic mode functions (IMFs), the permutation entropy (PE) module analyzes the IMF decomposed by the variational mode decomposition (VMD) module to distinguish between noise IMFs and useful signal IMFs; the wavelet transform (WT) module denoises the noise IMF, and the reconstruction module reconstructs the denoised IMF components to obtain the final denoised signal.

[0048] It also includes a real-time denoising module, which processes the video stream captured by the security camera in real time, and removes noise in the video stream through the PE-VMD-WT denoising processing module to ensure low latency of the denoising processing.

[0049] It also includes an abnormal real-time detection module, which uses a machine learning model for behavioral analysis to detect abnormal behavior in the video in real time.

[0050] Embodiment 2

[0051] See also Figure 2 The present invention also provides another technical solution: a security system based on PE-VMD-WT signal denoising, comprising:

[0052] A variety of sensor modules are used to collect different types of signals simultaneously in the security monitoring area;

[0053] Data fusion module, which uses deep learning or traditional machine learning algorithms to fuse multiple sensor data after denoising to improve the overall signal quality;

[0054] The time synchronization processing module is used to handle the time synchronization problem between different sensor data to ensure the effectiveness and accuracy of data fusion;

[0055] The signal analysis module is used to analyze the fused signals and identify anomalies or potential security threats;

[0056] and an alarm module, which is used to trigger an alarm signal when an abnormality or potential security threat is identified.

[0057] The various sensor modules include but are not limited to video signals collected by a video camera, audio signals collected by an audio sensor, and infrared signals collected by an infrared sensor.

[0058] It also includes a real-time denoising module, which processes the video stream captured by the security camera in real time, and removes noise in the video stream through the PE-VMD-WT denoising processing module to ensure low latency of the denoising processing.

[0059] It also includes an abnormal real-time detection module, which uses a machine learning model for behavioral analysis to detect abnormal behavior in the video in real time.

[0060] A cloud denoising service station may also be provided to receive signals collected by the security system, the PE-VMD-WT denoising processing module may be provided in the cloud denoising service station, denoising may be performed using the PE-VMD-WT denoising processing module, and the processed data may be returned to the security system to improve availability and scalability.

[0061] The PE-VMD-WT denoising processing module includes a permutation entropy (PE) module, a variational mode decomposition (VMD) module, a wavelet transform (WT) module and a reconstruction module, wherein the variational mode decomposition (VMD) module is used to decompose the signal collected in the security system into a number of intrinsic mode functions (IMFs), the permutation entropy (PE) module analyzes the IMF decomposed by the variational mode decomposition (VMD) module to distinguish between noise IMFs and useful signal IMFs; the wavelet transform (WT) module denoises the noise IMF, and the reconstruction module reconstructs the denoised IMF components to obtain the final denoised signal. This ensures that the signal in the security system can still maintain its original characteristics and information after the noise is removed, so as to facilitate subsequent signal processing and analysis.

[0062] The cloud denoising service station is provided with an encryption module for protecting transmitted data.

[0063] Working principle: Video signals collected by video cameras, audio signals collected by audio sensors, and infrared signals collected by infrared sensors are collected through various sensor modules. The PE-VMD-WT denoising processing module is used to perform PE-VMD-WT joint denoising processing on the signals collected by various sensor modules. The denoised multiple sensor data are fused using deep learning or traditional machine learning algorithms to improve the overall signal quality. The time synchronization processing module is used to handle the time synchronization problem between different sensor data to ensure the effectiveness and accuracy of data fusion. The signal analysis module is used to analyze the fused signal to identify anomalies or potential security threats. When the alarm module identifies anomalies or potential security threats, an alarm signal is triggered. This security system solves the problem of low signal recognition rate caused by insufficient extraction of single-domain features by traditional feature extraction methods, thereby improving the effective recognition rate of different intrusion times.

[0064] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A security system based on PE-VMD-WT signal denoising, characterized in that: include: A variety of sensor modules are used to collect different types of signals simultaneously in the security monitoring area; A PE-VMD-WT denoising processing module, used for performing PE-VMD-WT joint denoising processing on the signals collected by the multiple sensor modules; Data fusion module, which uses deep learning or traditional machine learning algorithms to fuse multiple sensor data after denoising to improve the overall signal quality; The time synchronization processing module is used to handle the time synchronization problem between different sensor data to ensure the effectiveness and accuracy of data fusion; The signal analysis module is used to analyze the fused signals and identify anomalies or potential security threats; and an alarm module, which is used to trigger an alarm signal when an abnormality or potential security threat is identified.

2. A security system based on PE-VMD-WT signal denoising according to claim 1, characterized in that: The various sensor modules include but are not limited to video signals collected by a video camera, audio signals collected by an audio sensor, and infrared signals collected by an infrared sensor.

3. A security system based on PE-VMD-WT signal denoising according to claim 2, characterized in that: The PE-VMD-WT denoising processing module includes a permutation entropy (PE) module, a variational mode decomposition (VMD) module, a wavelet transform (WT) module and a reconstruction module, wherein the variational mode decomposition (VMD) module is used to decompose the signal collected in the security system into a number of intrinsic mode functions (IMFs), the permutation entropy (PE) module analyzes the IMF decomposed by the variational mode decomposition (VMD) module to distinguish between noise IMFs and useful signal IMFs; the wavelet transform (WT) module denoises the noise IMF, and the reconstruction module reconstructs the denoised IMF components to obtain the final denoised signal.

4. A security system based on PE-VMD-WT signal denoising according to claim 1, characterized in that: It also includes a real-time denoising module, which processes the video stream captured by the security camera in real time, and removes noise in the video stream through the PE-VMD-WT denoising processing module to ensure low latency of the denoising processing.

5. A security system based on PE-VMD-WT signal denoising according to claim 1, characterized in that: It also includes an abnormal real-time detection module, which uses a machine learning model for behavioral analysis to detect abnormal behavior in the video in real time.

6. A security system based on PE-VMD-WT signal denoising according to claim 1, characterized in that: A cloud denoising service station may also be provided to receive signals collected by the security system, the PE-VMD-WT denoising processing module may be provided in the cloud denoising service station, denoising may be performed using the PE-VMD-WT denoising processing module, and the processed data may be returned to the security system.

7. A security system based on PE-VMD-WT signal denoising according to claim 6, characterized in that: The cloud denoising service station is provided with an encryption module for protecting transmitted data.

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