A method, device and storage device for multi-span decomposition and extraction of characteristic signals
Through the multi-span decomposition method, the fundamental wave and its left and right fundamental waves are constructed, and convolution calculation and energy graph drawing are performed, which solves the problem of low noise sensitivity and automation of feature signal extraction in the prior art, and realizes high-precision feature signal decomposition and extraction.
Patent Information
- Application Number
- CN202211722014.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-12-30
- Publication Date
- 2025-09-05
- Estimated Expiration
- 2042-12-30
AI Technical Summary
The existing feature signal extraction methods are susceptible to noise, have poor noise immunity, are difficult to adapt to multi-scale changes in features, and have low degree of automation in distinguishing and identifying multiple source signals.
The multi-span decomposition method is used to construct the fundamental wave and its left and right fundamental waves. Through multi-span convolution calculation, a multi-span waveform decomposition energy map is drawn, and the extreme points and their coordinates are extracted to determine the target feature position and span.
The signal-to-noise ratio of feature signal extraction is significantly improved, the noise immunity is enhanced, and the decomposition and accurate extraction of overlapping feature signals is realized, which improves the degree of automation and extraction accuracy of operations.
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Figure CN116150602B_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of signal processing, and in particular to a method, device and storage device for multi-span decomposition and extraction of characteristic signals. Background Art
[0002] Extracting the characteristic signals of interest (referred to as target features) from the detection signal is a common and fundamental problem faced in the field of signal processing and extraction. The effectiveness of target feature extraction is easily affected by the noise of the detection signal. Furthermore, the signal to be processed may contain signals caused by multiple characteristic sources, and the characteristic signals from multiple sources often overlap. Therefore, how to accurately identify and extract the target characteristic signals from the detection signal is a key factor in determining the quality of signal processing and feature extraction. Commonly used feature signal extraction methods include the amplitude gradient method, wavelet decomposition, and image processing. Among them, the amplitude gradient method is easily affected by local signals and has weak noise resistance. The wavelet decomposition method has difficulty adapting to the continuous multi-scale changes of features due to its basically fixed decomposition scale. It is also difficult to distinguish and identify different sources for signals containing multiple sources. Image processing methods often require human intervention to distinguish and identify different sources and have a low degree of automation. Summary of the Invention
[0003] Based on the problems existing in the above traditional feature signal extraction methods, this solution proposes a method, device and storage device for multi-span decomposition and feature signal extraction.
[0004] The present invention provides a method for multi-span decomposition and feature signal extraction, which specifically includes the following steps:
[0005] S1: constructing a fundamental wave and its left and right fundamental waves according to target features; the target features specifically refer to shape features of the target waveform;
[0006] S2: incrementally change the spans of the left and right fundamental waves, perform convolution calculation on the signal to be processed using the multi-span fundamental waves, and obtain its multi-span convolution result;
[0007] S3: Draw a multi-span waveform decomposition energy diagram of the signal to be processed according to the multi-span convolution result;
[0008] S4: Extract the extreme points and their coordinates in the multi-span waveform decomposition energy diagram to obtain the position and span of the target feature contained in the signal to be processed.
[0009] A storage device stores instructions and data for implementing a method for multi-span decomposition and feature signal extraction.
[0010] A device for multi-span decomposition and feature signal extraction includes a processor and a storage device; the processor loads and executes instructions and data in the storage device to implement the multi-span decomposition and feature signal extraction method.
[0011] Compared with the existing technology, the beneficial effects of the present invention include: significantly improving the signal-to-noise ratio of feature signal extraction, enhancing its noise resistance, and realizing the decomposition, stripping and precise extraction of overlapping feature signals, thereby improving the degree of automation of operations and the accuracy of feature extraction. BRIEF DESCRIPTION OF THE DRAWINGS
[0012] Figure 1 Schematic diagram of the method of the present invention;
[0013] Figure 2 is a schematic target waveform feature, used to design the fundamental waveform based on its shape;
[0014] Figure 3 is the signal to be processed in embodiment 1;
[0015] Figure 4 This is the present invention for Example 1 ( Figure 3 ) A multi-span waveform decomposition energy diagram obtained after signal processing;
[0016] Figure 5 is the signal to be processed in embodiment 2;
[0017] Figure 6 This case is for Example 2 ( Figure 5 ) A multi-span waveform decomposition energy diagram obtained after signal processing;
[0018] Figure 7 It is a schematic diagram of the working of the hardware device of an embodiment of the present invention. DETAILED DESCRIPTION
[0019] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.
[0020] Please refer to Figure 1 , Figure 1 It is a schematic flow chart of the method of the present invention;
[0021] The present invention provides a method for multi-span decomposition and feature signal extraction, which specifically includes the following steps:
[0022] S1: Construct the fundamental wave and its left and right fundamental waves according to the shape characteristics of the target waveform (referred to as target characteristics);
[0023] S2: incrementally change the spans of the left and right fundamental waves, perform convolution calculation on the signal to be processed using the multi-span fundamental waves, and obtain its multi-span convolution result;
[0024] S3: Draw a multi-span waveform decomposition energy diagram of the signal to be processed according to the multi-span convolution result;
[0025] S4: Extract the extreme points and their coordinates in the multi-span waveform decomposition energy diagram to obtain the position and span of the target feature contained in the signal to be processed.
[0026] It should be noted that the specific steps of constructing the characteristic fundamental wave and its left and right fundamental waves in step S1 are: obtaining a target waveform; constructing a characteristic fundamental wave with a similar shape according to the shape of the target waveform; and symmetrically dividing the characteristic fundamental wave into a left fundamental wave and a right fundamental wave.
[0027] It should be noted that the calculation process of the multi-span convolution in step S2 is specifically as follows: by adjusting the distance between the left fundamental wave and the right fundamental wave, the span of the left and right fundamental waves is changed; the left fundamental wave and the right fundamental wave after the adjusted span are respectively used to perform convolution calculations with the signal to be processed; and the convolution results of the left and right fundamental waves are summed to obtain the convolution result under the corresponding span; the span of the left and right fundamental waves is incrementally changed, and the above S32 process is repeated to obtain the calculation result of the multi-span convolution.
[0028] It should be noted that the specific steps of drawing the multi-span waveform decomposition energy diagram in step S3 are: taking the symmetrical center position of the fundamental wave as the first coordinate axis; taking half the distance between the left and right fundamental waves as the second coordinate axis; and taking the convolution result in S3 as the third coordinate axis to draw the multi-span waveform decomposition energy diagram.
[0029] It should be noted that step S4 specifically includes: extracting the maximum value and its coordinates in the multi-span waveform decomposition energy diagram; wherein the maximum value is the maximum value of the multi-span waveform decomposition energy, and the two coordinates corresponding to the maximum value are the center position of the target feature and its span, respectively.
[0030] As an example, please refer to Figure 2 , Figure 2 is the target characteristic waveform obtained in step S1 of the present invention. Figure 2 The waveform of the waveform is extracted to construct the fundamental waveform; the coordinates of the characteristic points can be the points corresponding to the maximum or minimum values. Figure 2 The antisymmetric features of the characteristic points circled in the elliptical area are used to construct an antisymmetric fundamental waveform (0.3, 1.0, 0, -1.0, -0.3), and then separate it into a left fundamental waveform (0.3, 1.0, 0) and a right fundamental waveform (0, -1.0, -0.3). Of course, this is only for illustrative purposes and is not intended to be limiting.
[0031] Example 1: Using the above fundamental wave, Figure 3 The signal to be processed is subjected to the multi-span decomposition calculation of the present invention. The span increases from 0 to half of the data length, and the multi-span decomposition of the full data domain is performed to obtain its multi-span decomposition energy diagram, as shown in FIG. Figure 4 shown. Figure 3 The signal shown is a long-span wave, the antisymmetric center position of which is 20+(77-20) / 2=48, the distance between the two peaks is 77-20=57, and the span is (77-20) / 2=28. Figure 4 In order to use the above fundamental wave Figure 3 Energy map obtained after multi-span decomposition of the signal. Figure 4 The coordinate value 48 of the maximum energy value is the location of the target feature center, and the coordinate value 28 is the span of the target feature, which is half the distance between the maximum and minimum peaks of the target feature. Figure 3 The symmetrical center positions and distances of the two peaks shown are consistent.
[0032] Example 2: Using the above fundamental wave, Figure 5 The signal to be extracted is subjected to the multi-span decomposition calculation of the present invention. The span increases from 0 to half of the data length, and the multi-span decomposition of the full data domain is performed to obtain its multi-span decomposition energy diagram, as shown in FIG. Figure 6 shown. Figure 5 The signal contains two mutually coupled target features, whose center positions are 81+(116-81) / 2=98 and 98+(105-98) / 2=101, and their spans are (116-81) / 2=17 and (105-98) / 2=3. Figure 6 There are two maximum values in it. The coordinate values 98 and 101 of the two maximum values are the position coordinates of the centers of the two target features, and the coordinate values 17 and 3 are the spans of the two target features. The position and span are Figure 5 The center positions and spans of the two coupled target features are shown.
[0033] See Figure 7 , Figure 7 4 is a schematic diagram of the working of the hardware device of an embodiment of the present invention, wherein the hardware device specifically comprises: a device 401 for multi-span decomposition and extraction of characteristic signals, a processor 402 and a storage device 403.
[0034] A device 401 for decomposing multiple spans and extracting characteristic signals: The device 401 for decomposing multiple spans and extracting characteristic signals implements the method for decomposing multiple spans and extracting characteristic signals.
[0035] Processor 402: The processor 402 loads and executes instructions and data in the storage device 403 to implement the method for multi-span decomposition and feature signal extraction.
[0036] Storage device 403: The storage device 403 stores instructions and data; the storage device 403 is used to implement the method of multi-span decomposition and feature signal extraction.
[0037] A storage device stores instructions and data for implementing a method for multi-span decomposition and feature signal extraction.
[0038] A device for multi-span decomposition and feature signal extraction includes a processor and a storage device; the processor loads and executes instructions and data in the storage device to implement the multi-span decomposition and feature signal extraction method.
[0039] The beneficial effects of the present invention are: it can significantly improve the signal-to-noise ratio of feature signal extraction, enhance its noise resistance, and can realize the decomposition, stripping and precise extraction of overlapping feature signals, thereby improving the degree of automation of calculations and the accuracy of feature extraction.
[0040] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.
[0041] The above specific embodiments of the present invention do not constitute a limitation on the scope of protection of the present invention. Any other corresponding changes and modifications made based on the technical concept of the present invention should be included in the scope of protection of the claims of the present invention.
Claims
1. A method for multi-span decomposition and feature signal extraction, characterized by: The following steps are involved: S1: constructing a fundamental wave and its left and right fundamental waves according to target features; the target features specifically refer to shape features of the target waveform; S2: incrementally change the spans of the left and right fundamental waves, perform convolution calculation on the signal to be processed using the multi-span fundamental waves, and obtain its multi-span convolution result; S3: Draw a multi-span waveform decomposition energy diagram of the signal to be processed according to the multi-span convolution result; S4: extracting the extreme points and their coordinates in the multi-span waveform decomposition energy graph to obtain the position and span of the target feature contained in the signal to be processed; The specific steps of constructing the fundamental wave and its left and right fundamental waves in step S1 are as follows: S21: Obtain target features; S22: construct fundamental wave according to target characteristics; S23: symmetrically dividing the fundamental wave into a left fundamental wave and a right fundamental wave; The calculation process of multi-span convolution in step S2 is specifically as follows: S31: Adjust the distance between the left fundamental wave and the right fundamental wave to change the span of the left and right fundamental waves. Here, the span refers to half of the distance between the left fundamental wave and the right fundamental wave. S32: performing convolution calculations on the left fundamental wave and the right fundamental wave after adjusting the span respectively with the signal to be processed; and summing the convolution results of the left and right fundamental waves to obtain the convolution result of the fundamental wave with the signal to be processed under the corresponding span; S33: incrementally changing the spans of the left and right fundamental waves, repeating the above S32 process, and obtaining the calculation result of multi-span convolution of the fundamental wave with the signal to be processed; The specific steps of drawing the multi-span waveform decomposition energy diagram in step S3 are as follows: S41: The symmetric center position of the fundamental wave is the first coordinate axis; S42: The span of the left and right fundamental waves is used as the second coordinate axis; S43: Using the convolution result in S3 as the third coordinate axis, an energy diagram of the multi-span waveform decomposition of the fundamental wave on the signal to be processed is plotted.
2. The method for multi-span decomposition and feature signal extraction according to claim 1, wherein: Step S4 is specifically: extracting the maximum value and its coordinates in the multi-span waveform decomposition energy diagram; the maximum value is the maximum value of the multi-span waveform decomposition energy, and the two coordinates corresponding to the maximum value are the center position of the target feature and the span of the target feature.
3. A storage device, characterized in that: The storage device stores instructions and data for implementing a method for multi-span decomposition and feature signal extraction as described in any one of claims 1-2.
4. A device for multi-span decomposition and feature signal extraction, characterized by: It includes a processor and a storage device; the processor loads and executes instructions and data in the storage device to implement a method for multi-span decomposition and feature signal extraction as described in any one of claims 1-2.
Citation Information
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