Background noise high-precision adaptive filtering method based on broadband signal

Abstract

The invention discloses a background noise high-precision self-adaptive filtering method based on a broadband signal. The method comprises the following steps: acquiring a sampling data sequence; obtaining an amplitude-frequency value and a spectral line corresponding to the amplitude-frequency value on an amplitude-frequency graph; setting an amplitude-frequency peak value as a reference, and transforming other amplitude-frequency values according to a reference proportion; carrying out advanced row length interval low-precision screening, and carrying out iteration to obtain a background noise frequency domain rough boundary; carrying out short-interval high-precision screening, and carrying out iteration to obtain a background noise frequency domain precise boundary; searching amplitude-frequency spectrum lines with amplitude-frequency values greater than the precise boundary of the background noise frequency domain; and solving a corresponding frequency which is regarded as a signal frequency of which background noise is filtered out. According to the method, long-interval low-precision screening and short-interval high-precision screening can be matched, the precise boundary of the background noise frequency domain is detected in a self-adaptive mode, and the frequencies of fundamental waves, harmonic waves and inter-harmonic waves in the signals are determined.

Description

Technical Field

[0001] The present invention relates to a method for high-precision adaptive filtering of background noise based on broadband signals. Background Art

[0002] In a "dual-high" power system with a high proportion of renewable energy and a high proportion of power electronic devices, the electromagnetic oscillation problem generated by power electronic devices cannot be ignored. Its oscillation frequency range is wider than that of traditional oscillations, ranging from several Hz to several kHz. At present, it is urgent to study and explore broadband signal measurement technologies for the "dual-high" power system based on broadband signal data. This measurement technology can provide accurate frequency band analysis data for each new energy station in real time and can be used as input data for subsequent oscillation monitoring, path tracing, fault analysis, etc.

[0003] In the actually obtained broadband signals, the measurement data often contains a large amount of background noise, and it is impossible to avoid the intrusion of background noise well during the measurement stage. Background noise is universal, with a high incidence rate but a lower amplitude than that of fundamental waves, harmonics, and interharmonics. Power system tripping, electromagnetic coupling, electrostatic coupling, common impedance coupling, DC and plant (substation) power system operations, and the operation of large-scale integrated circuits will introduce background noise into normal signals, causing background noise interference. Therefore, it is necessary to filter the broadband signal measurement data before analyzing it to eliminate background noise.

[0004] The power system often adopts hardware technologies such as shielding technology and grounding technology, supplemented by corresponding isolation measures to reduce the interference of background noise. In this way, most of the background noise can be physically isolated. However, the measurement of broadband signals requires a wide frequency band and high precision. Hardware technologies cannot ensure the filtering of background noise at each frequency band in the broadband domain, and there are certain limitations. In addition, the high-precision requirement for broadband signal measurement requires that background noise be filtered more thoroughly to obtain accurate data for subsequent research on broadband oscillations. Therefore, there is an urgent need to propose a high-precision filtering algorithm for background noise from the software aspect.

[0005] Therefore, it is very necessary to design a method for high-precision adaptive filtering of background noise based on broadband signals. Summary of the Invention

[0006] In order to solve the above problems, the present invention proposes a method for high-precision adaptive filtering of background noise based on broadband signals. The present invention can use the cooperation of long-interval low-precision screening and short-interval high-precision screening to adaptively detect the precise boundary line of the background noise frequency domain and determine the frequencies of fundamental waves, harmonics, and interharmonics in the signal.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] A high-precision adaptive filtering method for background noise based on broadband signals, comprising: Performing sampling to obtain a sampling data sequence; According to the sampling data sequence, obtaining the amplitude-frequency value and the corresponding spectral line on the amplitude-frequency diagram; Comparing to obtain the amplitude-frequency peak value, setting it as the reference, and transforming the remaining amplitude-frequency values according to the reference ratio; After determining the reference, first performing low-precision screening in a long interval on the amplitude-frequency diagram and iteratively obtaining a rough boundary line of the background noise frequency domain; Then performing high-precision screening in a short interval on the amplitude-frequency diagram and iteratively obtaining an accurate boundary line of the background noise frequency domain; Searching for the amplitude-frequency spectral lines whose amplitude-frequency values are greater than the accurate boundary line of the background noise frequency domain; obtaining the corresponding frequencies, which are regarded as the signal frequencies for filtering out the background noise.

[0009] Further, performing sampling to obtain a sampling data sequence, including: Sampling at the sampling frequency f s Performing sampling to obtain an n-point sampling data sequence X.

[0010] Further, according to the sampling data sequence, obtaining the amplitude-frequency value and the corresponding spectral line on the amplitude-frequency diagram, including: Performing n-point FFT transformation on the sampling data sequence with a Hanning window, and n discrete frequency spectrum values can be obtained. Respecting the amplitudes respectively, n amplitude-frequency values can be obtained, corresponding to n spectral lines on the amplitude-frequency diagram.

[0011] Further, the frequencies corresponding to the n discrete frequency spectrum values are respectively

[0012] Further, performing low-precision screening in a long interval on the amplitude-frequency diagram and iteratively obtaining a rough boundary line of the background noise frequency domain, including: Iteratively searching for the number of amplitude-frequency spectral lines in the i-th interval 5i~5(i + 1), i = 0, 1, 2…19. If the number of amplitude-frequency spectral lines in the interval is greater than 5, continue to iterate until the number of amplitude-frequency spectral lines in the interval does not exceed 5. Record the value of i at this time as R limit , and taking 5R limit as the rough boundary line of the background noise.

[0013] Further, performing high-precision screening in a short interval and iteratively obtaining an accurate boundary line of the background noise frequency domain, including: Dividing the interval 5(R limit -1)~5R limit into 10 small intervals 5(R limit -1)+0.5j~5(R limit-1) + 0.5(j + 1), where j = 0, 1, 2…9. Iteratively search for the number of amplitude spectrum lines within 10 small intervals. If the number of amplitude spectrum lines within the interval is greater than 3, continue the iteration until the number of amplitude spectrum lines within the interval does not exceed 3. Record the value of j at this time as j limit , and take 5(R limit -1) + 0.5j limit as the accurate demarcation line of background noise.

[0014] Furthermore, the amplitude-frequency peak is A base , the reference is 100, and the reference ratio is k A , and the expression is as follows: Let the amplitude-frequency value be A k , k = 0, 1, 2,…, (n - 1). Transform according to the reference ratio, and the expression is as follows: A k.tr = k A ×A k (1 - 2).

[0015] A high-precision adaptive background noise filtering device based on broadband signals, comprising: A sampling module for acquiring a data sequence; A transformation module for obtaining the amplitude-frequency value and the corresponding spectral line on the amplitude-frequency diagram; A reference module for setting the amplitude-frequency peak as the reference and transforming the remaining amplitude-frequency values according to the reference ratio; A low-precision screening module for iteratively obtaining a rough demarcation line of the background noise frequency domain; A high-precision screening module for iteratively obtaining an accurate demarcation line of the background noise frequency domain; A search module for searching for the amplitude spectrum line whose amplitude-frequency value is greater than the accurate demarcation line of the background noise frequency domain; A frequency confirmation module for calculating the corresponding frequency and regarding it as the signal frequency for filtering background noise.

[0016] Furthermore, the frequency confirmation module searches for the amplitude spectrum line whose amplitude-frequency value is greater than 5(R limit -1) + 0.5j limit .

[0017] A computer device, comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor. When the processor executes the computer program, it implements the steps of a high-precision adaptive background noise filtering method based on broadband signals.

[0018] Compared with the prior art, the beneficial effects of the present invention are:

[0019] The present invention utilizes measured broadband signal data. First, a rough frequency-domain demarcation line of background noise is adaptively obtained through low-precision screening in a long interval, and then an accurate frequency-domain demarcation line of background noise is obtained through high-precision screening in a short interval. The combination of low-precision screening in a long interval and high-precision screening in a short interval maximally saves the amount of computation while ensuring the accuracy of the accurate frequency-domain demarcation line of the background noise to be obtained to the greatest extent, enhancing the filtering ability of the background noise, enabling it to effectively filter the background noise even when the signal-to-noise ratio of the data fluctuates greatly, and improving the reliability and low interference of the input data of subsequent devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings forming a part of this application are used to provide a further understanding of this application. The schematic embodiments of this application and their descriptions are used to explain this application and do not constitute an improper limitation to this application.

[0021] Figure 1 is a flowchart of a method for high-precision adaptive filtering of background noise based on broadband signals according to the present invention;

[0022] Figure 2 is the simulation experiment result of a method for high-precision adaptive filtering of background noise based on broadband signals according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] The present invention will be further described below in conjunction with the drawings and embodiments.

[0024] It should be noted that the following detailed description is illustrative and is intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs.

[0025] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to this application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0026] In the present invention, terms such as "upper", "lower", "left", "right", "front", "rear", "vertical", "horizontal", "side", "bottom", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings. They are only relationship terms determined for facilitating the description of the structural relationship of each component or element of the present invention and do not specifically refer to any component or element of the present invention and should not be construed as a limitation to the present invention.

[0027] In the present invention, terms such as "fixed connection", "connected", "connected to" should be understood in a broad sense, which may mean a fixed connection, an integral connection or a detachable connection; it may be directly connected or indirectly connected through an intermediate medium. For relevant scientific research or technical personnel in this field, the specific meanings of the above terms in the present invention can be determined according to specific circumstances, and it should not be construed as a limitation to the present invention.

[0028] Example 1

[0029] As Figure 1 shown, the specific process is as follows:

[0030] Step 1) Sample at a sampling frequency f s to obtain an n-point sampling data sequence X = {x k , k = 1, …, n}, and enter Step 2);

[0031] Step 2) Apply a Hanning window to the sampling data sequence and perform an n-point FFT transform to obtain n discrete spectral values. Calculate their amplitudes respectively to obtain n amplitude-frequency values A = {A k , k = 1, …, n}, which correspond to n spectral lines on the amplitude-frequency diagram, and enter Step 3);

[0032] Step 3) Compare to obtain the amplitude-frequency peak value A base , set it as the reference 100, and calculate the reference ratio The remaining amplitude-frequency values are transformed according to the reference ratio k A to obtain A k.tr = k A × A k , and enter Step 4);

[0033] Step 4) First perform a long-interval low-precision screening, that is, iteratively search for the number of amplitude-frequency spectrum lines in the i-th interval 5i ~ 5(i + 1), i = 0, 1, 2 … 19. If the number of amplitude-frequency spectrum lines in the interval is greater than 5, continue to iterate until the number of amplitude-frequency spectrum lines in the interval does not exceed 5. Record the value of i at this time as R limit , and enter Step 5);

[0034] Step 5) Then perform a short-interval high-precision screening, that is, divide the interval 5(R limit -1) ~ 5R limit into 10 small intervals 5(R limit -1) + 0.5j ~ 5(R limit -1) + 0.5(j + 1), j = 0, 1, 2 … 9. Iteratively search for the number of amplitude-frequency spectrum lines in the 10 small intervals. If the number of amplitude-frequency spectrum lines in the interval is greater than 3, continue to iterate until the number of amplitude-frequency spectrum lines in the interval does not exceed 3. Record the value of j at this time as j limit , and enter Step 6);

[0035] Step 6) Search for the amplitude-frequency spectrum lines with amplitude-frequency values greater than 5(R limit -1)+0.5j limit , find the corresponding frequency, and regard it as the signal frequency.

[0036] Embodiment 2

[0037] When performing long-interval low-precision screening, iteratively search for the number of amplitude-frequency spectrum lines in the i-th interval 5i~5(i + 1), i = 0, 1, 2…19. If the number of amplitude-frequency spectrum lines in the interval is greater than 5, then regard all the amplitude-frequency spectrum lines involved in this interval as background noise spectrum lines, and the corresponding frequency as the background noise frequency.

[0038] Embodiment 3

[0039] When performing long-interval low-precision screening, iteratively search until the number of amplitude-frequency spectrum lines in the interval does not exceed 5, then temporarily regard all the amplitude-frequency spectrum lines involved in this interval as signals.

[0040] Embodiment 4

[0041] When performing long-interval low-precision screening, iteratively search until the number of amplitude-frequency spectrum lines in the interval does not exceed 5, record the value of i at this time as R limit , and take 5R limit as the rough background noise demarcation line.

[0042] Embodiment 5

[0043] When performing short-interval high-precision screening, iteratively search for the number of amplitude-frequency spectrum lines in 10 small intervals. If the number of amplitude-frequency spectrum lines in the interval is greater than 3, then regard all the amplitude-frequency spectrum lines involved in this interval as background noise spectrum lines.

[0044] Embodiment 6

[0045] When performing short-interval high-precision screening, iteratively search until the number of amplitude-frequency spectrum lines in the interval does not exceed 3, then regard all the amplitude-frequency spectrum lines involved in this small interval as signals.

[0046] Embodiment 7

[0047] When performing short-interval high-precision screening, iteratively search until the number of amplitude-frequency spectrum lines in the interval does not exceed 3, record the value of j at this time as j limit , and take 5(R limit -1)+0.5j limit as the precise background noise demarcation line.

[0048] Embodiment 8

[0049] As Figure 2As shown below, the simulation experiment results of the high-precision adaptive filtering method for background noise based on broadband signals are given. The input signal is:

[0050]

[0051] where n(t) is the background noise with a signal-to-noise ratio of -10 dB, the sampling frequency is f s = 6400 Hz, and the number of sampling points N = 6400. It can be seen that the rough frequency-domain demarcation line of the background noise obtained after long-interval low-precision screening is 25, and the precise frequency-domain demarcation line of the background noise obtained after short-interval high-precision screening is 23.5. Search for the amplitude-frequency spectrum lines with an amplitude-frequency value greater than 23.5, and calculate the corresponding frequencies as 50 Hz, 150 Hz, 250 Hz, and 350 Hz, which are the signal frequencies. Obviously, the high-precision adaptive filtering method for background noise based on broadband signals invented by the present invention enhances the filtering ability of background noise, enabling it to effectively filter background noise even when the signal-to-noise ratio of the data fluctuates greatly.

[0052] Example 9

[0053] Based on the same inventive concept, an embodiment of the present invention further provides a computer-readable storage medium storing a computer program, which when executed, implements an adaptive random pulse noise position recognition method based on broadband signals as described in Examples 1-8.

[0054] Example 10

[0055] Based on the same inventive concept, an embodiment of the present invention further provides a computer device, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor. When the processor executes the computer program, it implements an adaptive random pulse noise position recognition method based on broadband signals as described in Examples 1-8.

[0056] Example 11

[0057] A computer device, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor. When the processor executes the computer program, it implements the steps of a high-precision adaptive filtering method for background noise based on broadband signals.

[0058] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0059] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks.

[0060] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one or more of the flows Figure 1 or blocks.

[0061] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks.

[0062] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0063] Although the specific implementation manners of the present invention have been described above in conjunction with the accompanying drawings, it is not a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications or deformations that can be made without creative efforts on the basis of the technical solutions of the present invention are still within the protection scope of the present invention.

Claims

1. A high-precision adaptive filtering method for background noise based on broadband signals, characterized in that, Including: Sampling is performed to obtain a sampling data sequence; Based on the sampling data sequence, amplitude-frequency values and the corresponding spectral lines on the amplitude-frequency diagram are obtained; The amplitude-frequency peak value is compared and obtained, which is set as the benchmark, and the remaining amplitude-frequency values are transformed according to the benchmark ratio; After determining the benchmark, first perform a long-interval low-precision screening on the amplitude-frequency diagram, and iterate to obtain a rough boundary line of the background noise frequency domain; Then perform a short-interval high-precision screening on the amplitude-frequency diagram, and iterate to obtain an accurate boundary line of the background noise frequency domain; Search for the amplitude-frequency spectral lines whose amplitude-frequency values are greater than the accurate boundary line of the background noise frequency domain; The corresponding frequency is obtained and regarded as the signal frequency after filtering out the background noise.

2. The high-precision adaptive background noise filtering method based on broadband signals according to claim 1, wherein, The performing sampling to obtain a sampling data sequence includes: Sampling is performed at a sampling frequency f s to obtain an n-point sampling data sequence X.

3. A high-precision adaptive background noise filtering method based on broadband signals according to claim 1, characterized in that The obtaining amplitude-frequency values and the corresponding spectral lines on the amplitude-frequency diagram based on the sampling data sequence includes: Applying a Hanning window to the sampling data sequence and performing an n-point FFT transformation, n discrete spectral values can be obtained. By separately calculating their amplitudes, n amplitude-frequency values can be obtained, corresponding to n spectral lines on the amplitude-frequency diagram.

4. A high-precision adaptive background noise filtering method based on broadband signals according to claim 3, characterized in that, The frequencies corresponding to the n discrete spectral values are respectively 5. A high-precision adaptive background noise filtering method based on broadband signals according to claim 1, characterized in that The performing a long-interval low-precision screening on the amplitude-frequency diagram and iterating to obtain a rough boundary line of the background noise frequency domain includes: Iteratively search for the number of amplitude spectrum lines in the \(i\)-th interval \(5i\sim5(i + 1)\), where \(i = 0,1,2,\cdots,19\). If the number of amplitude spectrum lines in the interval is greater than 5, continue the iteration until the number of amplitude spectrum lines in the interval does not exceed 5. Record the value of \(i\) at this time as \(R\). limit , and take \(5R\) limit as a rough demarcation line for background noise.

6. The high-precision adaptive background noise filtering method based on broadband signals according to claim 1, wherein The performing a short-interval high-precision screening and iterating to obtain an accurate boundary line of the background noise frequency domain includes: Divide the interval 5(R limit -1) to 5R limit into 10 sub - intervals 5(R limit -1)+0.5j to 5(R limit -1)+0.5(j + 1), where j = 0, 1, 2…9. Iteratively search for the number of amplitude - spectrum lines within the 10 sub - intervals. If the number of amplitude - spectrum lines within the interval is greater than 3, continue the iteration until the number of amplitude - spectrum lines within the interval does not exceed 3. Record the value of j at this time as j limit , and take 5(R limit -1)+0.5j limit as the accurate boundary line of background noise.

7. A high-precision adaptive background noise filtering method based on broadband signals according to claim 1, characterized in that The peak amplitude-frequency is A base , the reference is 100, and the reference ratio is k A , and the expression is as follows: Let the amplitude-frequency value be A k , k = 0, 1, 2, …, (n - 1), and perform a transformation according to the reference ratio. The expression is as follows: A k.tr = k A × A k (1 - 2).

8. An apparatus for high-precision adaptive filtering of background noise based on broadband signals, characterized in that, Including: A sampling module for obtaining a data sequence; A transformation module for obtaining amplitude-frequency values and the corresponding spectral lines on the amplitude-frequency diagram; A benchmark module for setting the amplitude-frequency peak value as the benchmark and transforming the remaining amplitude-frequency values according to the benchmark ratio; A low-precision screening module for iterating to obtain a rough boundary line of the background noise frequency domain; A high-precision screening module for iterating to obtain an accurate boundary line of the background noise frequency domain; A search module for searching for the amplitude-frequency spectral lines whose amplitude-frequency values are greater than the accurate boundary line of the background noise frequency domain; A frequency confirmation module for obtaining the corresponding frequency and regarding it as the signal frequency after filtering out the background noise.

9. The high-precision adaptive background noise filtering device based on broadband signals according to claim 8, characterized in that The frequency confirmation module searches for amplitude-frequency spectrum lines with an amplitude-frequency value greater than 5(R limit -1)+0.5j limit .

10. A computer device, characterized in that, Including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor. When the processor executes the computer program, the steps of a method for high-precision adaptive filtering of background noise based on a broadband signal according to any one of claims 1-7 are implemented.

Images