Low-frequency weak signal processing system

Abstract

The invention discloses a low-frequency weak signal processing system, and the system comprises a signal collection and storage module which is used for collecting and storing low-frequency weak signals; the filter module is used for filtering the low-frequency weak signal so as to reduce noise interference; the frequency domain analysis module is used for converting the filtered signal to a frequency domain for analysis; the frequency identification module is used for identifying a specific frequency component in an output signal of the frequency domain analysis module; and the frequency anomaly detection module is used for detecting an abnormal frequency amplitude in an output signal of the frequency identification module. The processing system provided by the invention can effectively extract weak low-frequency signals from a noise background through the steps of signal acquisition and storage, filtering processing, frequency domain analysis, frequency identification, anomaly detection and the like, and improves the signal processing precision and efficiency.

Description

Technical Field

[0001] The invention relates to the technical field of signal processing, and in particular to a low-frequency weak signal processing system. Background Art

[0002] Low-frequency weak signals refer to those electrical signals with low frequency and weak signal strength. Such signals usually appear in various scientific and technological fields, such as biomedical engineering, seismology, environmental monitoring, industrial automation, etc. Due to their low frequency (e.g., in the audio range or lower) and weak strength, they are easily masked by background noise. Due to the low signal-to-noise ratio, the signal may be difficult to detect in a strong noise background, so there are some special challenges in the acquisition, processing and analysis process.

[0003] These signals are easily interfered by noise during the actual processing process, especially in a strong noise background environment. Traditional signal processing systems often find it difficult to accurately extract useful information. In addition, existing signal processing systems generally have problems such as high cost, insufficient accuracy, and limited application scope. Summary of the invention

[0004] 1. Technical Problems Solved

[0005] The technical problem to be solved by the present invention is the various problems mentioned in the above background technology, and a low-frequency weak signal processing system is provided.

[0006] 2. Technical Solution

[0007] In order to solve the above technical problems, the present invention provides a technical solution: a low-frequency weak signal processing system, comprising:

[0008] Signal acquisition and storage module, used to collect and store low-frequency weak signals;

[0009] A filter module, used for filtering the low-frequency weak signal to reduce noise interference;

[0010] A frequency domain analysis module, used for converting the filtered signal into the frequency domain for analysis;

[0011] A frequency identification module, used to identify specific frequency components in the output signal of the frequency domain analysis module;

[0012] A frequency anomaly detection module, used to detect the abnormal frequency amplitude in the output signal of the frequency identification module;

[0013] The filter module includes an infinite impulse response filter (IIR), and the IIR filter has selectable filter types including Butterworth filter, Chebyshev filter, inverse Chebyshev filter, elliptic filter, and Bessel filter;

[0014] The frequency identification module uses Fourier transform algorithm to convert the signal from time domain to frequency domain and generate a spectrum diagram to provide the amplitude spectrum, power spectrum and phase spectrum of the signal;

[0015] The frequency anomaly detection module includes setting the upper and lower frequency thresholds, which are used to determine whether the frequency is abnormal and provide a method for manually correcting the frequency.

[0016] As an improvement, the signal acquisition storage module includes a signal acquisition card and a DAQ assistant in LabVIEW, the signal acquisition card is used to acquire analog input voltage signals in real time, the DAQ assistant in LabVIEW can configure the parameters of the signal acquisition card, and the signal generator module is used to generate simulated sinusoidal signals for experimental research.

[0017] As an improvement, the filter module also includes applying a window function technology to perform time-domain weighted processing on the filtered signal to reduce signal leakage.

[0018] As an improvement, the frequency identification module also includes a peak detection module for detecting the signal amplitude and waveform width in real time, quickly finding the location of the peak, and calculating the frequency of the signal in combination with a MATLAB script.

[0019] As an improvement, it further includes a data storage module and an offline analysis module, wherein the data storage module is used to store the signal data collected by the signal acquisition storage module, and the offline analysis module is used to perform offline analysis on the signal data stored by the data storage module.

[0020] 3. Beneficial Effects

[0021] The advantages of the present invention compared with the prior art are:

[0022] The present invention proposes a low-frequency weak signal processing system, which can effectively extract weak low-frequency signals from the noise background through steps such as signal acquisition and storage, filtering processing, frequency domain analysis, frequency identification and anomaly detection, thereby improving the accuracy and efficiency of signal processing. At the same time, the system uses an infinite impulse response filter (IIR) to filter the signal, which significantly reduces noise interference; and converts the signal to the frequency domain for analysis through a Fourier transform algorithm, thereby accurately identifying specific frequency components and their anomalies. In addition, the system also has functions such as signal simulation, data storage and offline analysis, and is suitable for low-frequency signal processing and analysis in a variety of application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a structural diagram of a low-frequency weak signal processing system of the present invention.

[0024] Figure 2 This is a diagram of the amplification effect of a low-frequency weak signal processing system of the present invention.

[0025] Figure 3 The present invention discloses a noise waveform diagram of a low-frequency weak signal processing system.

[0026] Figure 4 It is a noise filtering waveform diagram of a low-frequency weak signal processing system of the present invention.

[0027] Figure 5 It is a sinusoidal signal waveform diagram of a low-frequency weak signal processing system of the present invention.

[0028] Figure 6 The invention discloses a sine signal amplitude spectrum of a low-frequency weak signal processing system.

[0029] Figure 7 It is a frequency error diagram of a low-frequency weak signal processing system of the present invention. DETAILED DESCRIPTION

[0030] 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 only part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0031] like Figure 1 As shown, a low-frequency weak signal processing system comprises:

[0032] The signal acquisition storage module is used to collect and store low-frequency weak signals. The signal acquisition storage module includes a signal acquisition card and a DAQ assistant in LabVIEW. The signal acquisition card is used to collect analog input voltage signals in real time. The DAQ assistant in LabVIEW can configure the parameters of the signal acquisition card. The signal generator module is used to generate simulated sinusoidal signals for experimental research.

[0033] A filter module, used for filtering the low-frequency weak signal to reduce noise interference, the filter module includes an infinite impulse response filter (IIR), and the IIR filter has selectable filter types, including Butterworth filter, Chebyshev filter, inverse Chebyshev filter, elliptic filter, and Bessel filter;

[0034] A frequency domain analysis module, used for converting the filtered signal into the frequency domain for analysis;

[0035] The frequency identification module is used to identify the specific frequency components in the output signal of the frequency domain analysis module. The frequency identification module uses the Fourier transform algorithm to convert the signal from the time domain to the frequency domain, and generates a spectrum diagram to provide the amplitude spectrum, power spectrum and phase spectrum of the signal. The frequency identification module also includes a peak detection module for real-time detection of the signal amplitude and waveform width, quickly finding the location of the peak, and calculating the frequency of the signal in combination with the MATLAB script.

[0036] The frequency anomaly detection module is used to detect the abnormal frequency amplitude in the output signal of the frequency identification module. The frequency anomaly detection module includes setting the upper and lower limit thresholds of the frequency, which is used to determine whether the frequency is abnormal and provide a method for manually correcting the frequency.

[0037] It also includes a data storage module and an offline analysis module. The data storage module is used to store the signal data collected by the signal acquisition storage module, and the offline analysis module is used to perform offline analysis on the signal data stored by the data storage module.

[0038] The working principle of the present invention is as follows: the signal acquisition storage module is used to collect low-frequency weak signals and store them, wherein the DAQ assistant in LabVIEW is used to configure the signal acquisition card to realize the real-time acquisition of analog input voltage signals. The filter module uses an infinite impulse response filter (IIR), such as a Butterworth filter, a Chebyshev filter, etc., to filter the collected signals to reduce noise interference, and can further reduce signal leakage by applying the window function technology. The frequency domain analysis module uses the Fourier transform algorithm to convert the filtered signal to the frequency domain for analysis, and generates the amplitude spectrum, power spectrum and phase spectrum of the signal. The frequency identification module identifies specific frequency components based on the results of the frequency domain analysis, and calculates the signal frequency in combination with the MATLAB script. The frequency anomaly detection module sets the upper and lower limit thresholds of the frequency, which is used to detect the abnormal frequency amplitude in the output signal of the frequency identification module, and provides a method for manually correcting the frequency. In addition, the system also includes a data storage module for saving the collected signal data, and an offline analysis module for further analyzing the saved data.

[0039] The following is a data analysis of the amplification effect of this system:

[0040] like Figure 2 The system shown here amplifies a 20Hz, 5mv sinusoidal signal. The circuit has an average peak of about 270mv, which can effectively amplify low-frequency weak signals by 54 times.

[0041] The following is a data analysis of the filtering effect of this system:

[0042] A signal generator is used to generate a 10Hz, 5mV amplitude sinusoidal signal, and Gaussian white noise is added to it. After preprocessing through a secondary filter amplifier circuit, it is connected to a computer program to run, such as Figure 3 The waveform of the added noise source is shown as Figure 4 The waveform after being filtered by the Butterworth filter, it can be seen that its actual filtering effect is obvious.

[0043] The following is the frequency measurement and spectrum analysis of this system:

[0044] A signal generator is used to generate a 10Hz, 5mv sinusoidal signal, which is then passed through a preprocessing circuit and a digital bandpass filter. The waveform generated is as follows: Figure 5 As shown. The spectrum analysis and peak detection frequency error experiment of the signal show that the actual spectrum analysis is correct, as shown in Figure 6 The maximum value of the amplitude spectrum of the signal is at 10Hz, indicating that the signal has the largest amplitude at a frequency of 10Hz, that is, this frequency component contributes the most to the signal. In the frequency error experiment, a 20Hz sine signal is used, and the system is continuously running. The frequency value calculated by the frequency calculation and peak detection module each time is compared with the actual set frequency value. It is concluded that the average frequency error is about 0.03%.

[0045] The present invention realizes the effective processing of low-frequency weak signals through the effective integration of the above modules, improves the accuracy and reliability of signal processing, and is suitable for various application scenarios that require accurate analysis of low-frequency signals.

[0046] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0047] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

[0048] The present invention and its embodiments are described above, and such description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if ordinary technicians in the field are inspired by it, without departing from the purpose of the invention, they can design a structure and embodiment similar to the technical solution without creativity, which should belong to the protection scope of the present invention.

Claims

1. A low-frequency weak signal processing system, characterized in that: include: Signal acquisition and storage module, used to collect and store low-frequency weak signals; A filter module, used for filtering the low-frequency weak signal to reduce noise interference; A frequency domain analysis module, used for converting the filtered signal into the frequency domain for analysis; A frequency identification module, used to identify specific frequency components in the output signal of the frequency domain analysis module; A frequency anomaly detection module, used to detect the abnormal frequency amplitude in the output signal of the frequency identification module; The filter module includes an infinite impulse response filter (IIR), and the IIR filter has selectable filter types including Butterworth filter, Chebyshev filter, inverse Chebyshev filter, elliptic filter, and Bessel filter; The frequency identification module uses Fourier transform algorithm to convert the signal from time domain to frequency domain and generate a spectrum diagram to provide the amplitude spectrum, power spectrum and phase spectrum of the signal; The frequency anomaly detection module includes setting upper and lower frequency thresholds, which are used to determine whether the frequency is abnormal and provide a method for manually correcting the frequency.

2. The low-frequency weak signal processing system according to claim 1, characterized in that: The signal acquisition storage module includes a signal acquisition card and a DAQ assistant in LabVIEW, the signal acquisition card is used to acquire analog input voltage signals in real time, the DAQ assistant in LabVIEW can configure the parameters of the signal acquisition card, and the signal generator module is used to generate simulated sinusoidal signals for experimental research.

3. The low-frequency weak signal processing system according to claim 1, characterized in that: The filter module also includes applying a window function technology to perform time domain weighted processing on the filtered signal to reduce signal leakage.

4. The low-frequency weak signal processing system according to claim 1, characterized in that: The frequency identification module also includes a peak detection module for detecting the signal amplitude and waveform width in real time, quickly finding the location of the peak, and calculating the frequency of the signal in combination with a MATLAB script.

5. The low-frequency weak signal processing system according to claim 1, characterized in that: It also includes a data storage module and an offline analysis module. The data storage module is used to store the signal data collected by the signal acquisition storage module, and the offline analysis module is used to perform offline analysis on the signal data stored by the data storage module.

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