CN112651104A - Design method of comprehensive signal detection processing simulation analysis platform - Google Patents
Design method of comprehensive signal detection processing simulation analysis platform Download PDFInfo
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Abstract
The invention belongs to the technical field of signal processing simulation analysis, and particularly relates to a design method of a comprehensive signal detection processing simulation analysis platform, which comprises the following steps: step 1, designing a joint call of a VB front window interface and MATLAB; step 2, receiving a data source signal through a PC end by a VB front window interface, and importing a signal data file to be processed into an MATLAB running environment; step 3, the MATLAB utilizes a signal processing algorithm to carry out processing operations of filtering out harmonic waves, reducing noise and analyzing frequency spectrum on the imported signal data; step 4, the VB front window interface stores, saves and converts the processed signal data and data images by utilizing an Access database; and 5, judging whether the monitoring equipment is normal or not. The invention provides a design method of a comprehensive signal detection processing simulation analysis platform, which has the advantages of low cost, high judgment precision of monitoring equipment and good optimization processing performance.
Description
Technical Field
The invention belongs to the technical field of signal processing simulation analysis, and particularly relates to a design method of a comprehensive signal detection processing simulation analysis platform.
Background
At present, a comprehensive signal detection processing system mainly sends signals to a computer or a corresponding signal processing system through a data acquisition system, and corresponding calculation and processing are carried out according to different requirements. After analog quantity is collected and converted into digital quantity, the digital quantity is processed by a computer to obtain required data. And simultaneously, the obtained data can be stored, displayed and printed by a computer to realize the monitoring of certain physical quantities, wherein a part of the data can also be used as a feedback control quantity in the generation process. In the prior art, the cost is high due to the fact that a large number of hardware devices are utilized, a computer usually carries out simple algorithm processing, the optimization processing performance is not good, and the judgment precision of monitoring equipment is influenced, so that a comprehensive signal detection processing simulation analysis platform is urgently needed in the prior art, and the design of a comprehensive signal detection processing system can be subjected to simulation analysis verification feasibility.
Disclosure of Invention
The invention mainly aims to solve the problems in the prior art and provides a design method of a comprehensive signal detection processing simulation analysis platform, which has the advantages of low cost, high judgment precision of monitoring equipment and good optimization processing performance.
The technical problem solved by the invention is realized by adopting the following technical scheme: a design method of a comprehensive signal detection processing simulation analysis platform comprises the following steps:
step 1: a VB front window interface is designed, and the VB front window interface and the MATLAB are mutually connected and called through an ActiveX technology, so that an input signal data file can be transmitted back between the VB front window interface and the MATLAB running environment;
step 2, receiving a data source signal through a PC end by a VB front window interface, and importing a signal data file to be processed into an MATLAB running environment;
step 3, the MATLAB utilizes a signal processing algorithm to carry out processing operations of filtering out harmonic waves, reducing noise and analyzing frequency spectrum on the imported signal data;
step 4, the VB front window interface stores, saves and converts the processed signal data and data images by utilizing an Access database;
and step 5, the VB front window interface judges whether the data stored in the Access database is normal or not according to the signal data and the image information after the processing operation, so that whether the monitoring equipment is normal or not is judged.
Further, the MATLAB in step 3 may also perform processing operations of digital conversion and display on the imported signal data by using a signal processing algorithm.
Further, the data source signal may be an electrical signal generated by a monitoring device or experiment.
Furthermore, the Access database can be in data transmission with Word and Excel office software.
Further, step 3, the MATLAB utilizes the signal processing algorithm to carry out processing operations of filtering harmonic waves, reducing noise and analyzing frequency spectrum on the imported signal data, and further comprises,
and the MATLAB carries out noise reduction processing on the input noise-containing signals through three steps of signal decomposition, signal processing and signal reconstruction by using a wavelet threshold denoising algorithm.
Further, step 3, the MATLAB utilizes the signal processing algorithm to carry out processing operations of filtering harmonic waves, reducing noise and analyzing frequency spectrum on the imported signal data, and further comprises,
MATLAB utilizes a frequency sampling design method to design an FIR filter, and the FIR filter carries out filtering operation on the input harmonic-containing signal.
Further, step 3, the MATLAB utilizes the signal processing algorithm to carry out processing operations of filtering harmonic waves, reducing noise and analyzing frequency spectrum on the imported signal data, and further comprises,
and carrying out spectrum analysis processing operation on the imported signal data by using a discrete Fourier transform algorithm by MATLAB.
Further, the VB front window interface comprises a signal processing module, a database management module and a serial port configuration module.
The invention has the beneficial effects that:
the invention realizes VB and MATLAB mixed programming through a computer, transmits user signal data information to the MATLAB through a VB interface, and simultaneously can also transmit a calculation result in the MATLAB back to a VB front window interface, so that the signal detection processing of the invention is realized by software, and the generation cost is lower; the VB front window interface can call an MATLAB built-in signal processing algorithm program, not only can carry out processing operations of filtering out harmonic waves, reducing noise and analyzing frequency spectrum on the imported signal data, but also can carry out processing operations of digital conversion and display on the imported signal data, so that the capability of the platform for processing signals is greatly improved, and the optimized processing performance is better; the simulation analysis platform can perform data simulation on the signal detection processing process, and greatly improves the judgment precision of the monitoring equipment compared with the method of directly processing signals by using a computer algorithm.
Drawings
FIG. 1 is a flow chart of the design method of the integrated signal detection processing simulation analysis platform of the present invention.
FIG. 2 is a block diagram of the overall design of the integrated signal detection processing simulation analysis platform of the present invention.
FIG. 3 is a block diagram of the wavelet threshold denoising algorithm of the present invention.
Fig. 4 is a flow chart of a signal processing algorithm of the present invention.
Fig. 5 is a flow chart of the FIR filter programming of the present invention.
Fig. 6 is a VB front window interface schematic of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
As shown in fig. 1 to 6, the design method of the integrated signal detection processing simulation analysis platform provided by the present invention includes the following steps:
step 1: a VB front window interface is designed, and the VB front window interface and the MATLAB are mutually connected and called through an ActiveX technology, so that an input signal data file can be transmitted back between the VB front window interface and the MATLAB running environment;
step 2, receiving a data source signal through a PC end by a VB front window interface, and importing a signal data file to be processed into an MATLAB running environment;
step 3, the MATLAB utilizes a signal processing algorithm to carry out processing operations of filtering out harmonic waves, reducing noise and analyzing frequency spectrum on the imported signal data;
step 4, the VB front window interface stores, saves and converts the processed signal data and data images by utilizing an Access database;
and step 5, the VB front window interface judges whether the data stored in the Access database is normal or not according to the signal data and the image information after the processing operation, so that whether the monitoring equipment is normal or not is judged.
In step 3, the MATLAB can also perform digital conversion and display processing operation on the imported signal data by using a signal processing algorithm.
The data source signal may be an electrical signal generated by a monitoring device or experiment.
The Access database can be in data transmission with Word and Excel office software.
Step 3, the MATLAB utilizes the signal processing algorithm to carry out processing operations of filtering harmonic waves, reducing noise and analyzing frequency spectrum on the imported signal data, and further comprises the following steps,
and the MATLAB carries out noise reduction processing on the input noise-containing signals through three steps of signal decomposition, signal processing and signal reconstruction by using a wavelet threshold denoising algorithm.
Step 3, the MATLAB utilizes the signal processing algorithm to carry out processing operations of filtering harmonic waves, reducing noise and analyzing frequency spectrum on the imported signal data, and further comprises the following steps,
MATLAB utilizes a frequency sampling design method to design an FIR filter, and the FIR filter carries out filtering operation on the input harmonic-containing signal.
Step 3, the MATLAB utilizes the signal processing algorithm to carry out processing operations of filtering harmonic waves, reducing noise and analyzing frequency spectrum on the imported signal data, and further comprises the following steps,
and carrying out spectrum analysis processing operation on the imported signal data by using a discrete Fourier transform algorithm by MATLAB.
The VB front window interface comprises a signal processing module, a database management module and a serial port configuration module.
Examples
Step 1, designing a VB front window interface, and realizing the mutual connection and calling of the VB front window interface and an MATLAB through an ActiveX technology, so that an input signal data file can be transmitted back between the VB front window interface and an MATLAB running environment;
step 2, receiving a data source signal through a PC end by a VB front window interface, and importing a signal data file to be processed into an MATLAB running environment;
the data source signal may be an electrical signal generated by a monitoring device or experiment.
Step 3, the MATLAB utilizes a signal processing algorithm to carry out processing operations of filtering out harmonic waves, reducing noise and analyzing frequency spectrum on the imported signal data;
in step 3, the MATLAB can also perform digital conversion and display processing operation on the imported signal data by using a signal processing algorithm.
As shown in fig. 4, a signal processing algorithm flowchart (EMD signal decomposition) can express main information such as the frequency and amplitude of vibration by decomposing a time-series signal in the time domain and converting the time-series signal into the sum of oscillation functions (IMFs).
And 3, carrying out processing operations of harmonic wave filtering, noise reduction and spectrum analysis on the imported signal data by using the MATLAB through a signal processing algorithm, and further carrying out noise reduction processing on the input noise-containing signal through three steps of signal decomposition, signal processing and signal reconstruction by using the MATLAB through a wavelet threshold denoising algorithm.
As shown in fig. 3, the wavelet threshold denoising algorithm decomposes a signal containing noise by using wavelet transform to obtain a low-frequency wavelet coefficient and a high-frequency wavelet coefficient. With the gradual increase of the decomposition layer number, the correlation coefficient of the low-frequency wavelet coefficient and the actual signal is in a trend from low to high to low. The maximum correlation coefficient may be set as a threshold value, and a noise canceling signal can be obtained by performing filtering and inversion processing on the wavelet coefficient containing noise.
And 3, carrying out processing operations of filtering harmonic waves, noise reduction and frequency spectrum analysis on the imported signal data by using a MATLAB signal processing algorithm, further comprising designing an FIR filter by using a frequency sampling design method by using the MATLAB signal processing algorithm, and carrying out filtering operation on the input harmonic-containing signal through the FIR filter.
And the MATLAB calls a built-in FIR filter function to design, and carries out harmonic wave filtering processing operation on the imported signal data.
As shown in fig. 5, the FIR filter programming flow chart selects a suitable ideal frequency selective filter (which is always a non-causal, infinite impulse response) and then truncates (or windows) its impulse response to obtain a linear phase and causal FIR filter.
And 3, carrying out processing operations of filtering out harmonic waves, reducing noise and carrying out spectrum analysis on the imported signal data by using the MATLAB through a signal processing algorithm, and further carrying out spectrum analysis processing operations on the imported signal data by using a discrete Fourier transform algorithm.
And the MATLAB calls a built-in FFT function to design, and carries out spectrum analysis processing operation on the imported signal data.
Step 4, the VB front window interface stores, saves and converts the processed signal data and data images by utilizing an Access database;
the Access database can be in data transmission with Word and Excel office software.
The Access database has strong data processing and statistical analysis capabilities, and various statistics such as summarization, averaging and the like can be conveniently carried out by utilizing the query function of the Access. And the statistical conditions can be flexibly set. For example, Excel cannot compare with tens of thousands of records, hundreds of thousands of records and more, which is fast and convenient to operate in statistical analysis. Access can improve work efficiency and working capacity.
And step 5, the VB front window interface judges whether the data stored in the Access database is normal or not according to the signal data and the image information after the processing operation, so that whether the monitoring equipment is normal or not is judged.
The VB front window interface comprises a signal processing module, a database management module and a serial port configuration module.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. A design method of a comprehensive signal detection processing simulation analysis platform is characterized by comprising the following steps: the method comprises the following steps:
step 1: a VB front window interface is designed, and the VB front window interface and the MATLAB are mutually connected and called through an ActiveX technology, so that an input signal data file can be transmitted back between the VB front window interface and the MATLAB running environment;
step 2, receiving a data source signal through a PC end by a VB front window interface, and importing a signal data file to be processed into an MATLAB running environment;
step 3, the MATLAB utilizes a signal processing algorithm to carry out processing operations of filtering out harmonic waves, reducing noise and analyzing frequency spectrum on the imported signal data;
step 4, the VB front window interface stores, saves and converts the processed signal data and data images by utilizing an Access database;
and step 5, the VB front window interface judges whether the data stored in the Access database is normal or not according to the signal data and the image information after the processing operation, so that whether the monitoring equipment is normal or not is judged.
2. The integrated signal detection processing simulation analysis platform design method according to claim 1, characterized in that: in step 3, the MATLAB can also perform digital conversion and display processing operation on the imported signal data by using a signal processing algorithm.
3. The integrated signal detection processing simulation analysis platform design method according to claim 1, characterized in that: the data source signal may be an electrical signal generated by a monitoring device or experiment.
4. The integrated signal detection processing simulation analysis platform design method according to claim 1, characterized in that: the Access database can be in data transmission with Word and Excel office software.
5. The integrated signal detection processing simulation analysis platform design method according to claim 1, characterized in that: step 3, the MATLAB utilizes the signal processing algorithm to carry out processing operations of filtering harmonic waves, reducing noise and analyzing frequency spectrum on the imported signal data, and further comprises the following steps,
and the MATLAB carries out noise reduction processing on the input noise-containing signals through three steps of signal decomposition, signal processing and signal reconstruction by using a wavelet threshold denoising algorithm.
6. The integrated signal detection processing simulation analysis platform design method according to claim 1, characterized in that: step 3, the MATLAB utilizes the signal processing algorithm to carry out processing operations of filtering harmonic waves, reducing noise and analyzing frequency spectrum on the imported signal data, and further comprises the following steps,
MATLAB utilizes a frequency sampling design method to design an FIR filter, and the FIR filter carries out filtering operation on the input harmonic-containing signal.
7. The integrated signal detection processing simulation analysis platform design method according to claim 1, characterized in that: step 3, the MATLAB utilizes the signal processing algorithm to carry out processing operations of filtering harmonic waves, reducing noise and analyzing frequency spectrum on the imported signal data, and further comprises the following steps,
and carrying out spectrum analysis processing operation on the imported signal data by using a discrete Fourier transform algorithm by MATLAB.
8. The integrated signal detection processing simulation analysis platform design method according to claim 1, characterized in that: the VB front window interface comprises a signal processing module, a database management module and a serial port configuration module.
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