CN114398763A - Random signal analysis experiment virtual simulation system and control method - Google Patents
Random signal analysis experiment virtual simulation system and control method Download PDFInfo
- Publication number
- CN114398763A CN114398763A CN202111595262.3A CN202111595262A CN114398763A CN 114398763 A CN114398763 A CN 114398763A CN 202111595262 A CN202111595262 A CN 202111595262A CN 114398763 A CN114398763 A CN 114398763A
- Authority
- CN
- China
- Prior art keywords
- signal
- experiment
- module
- random signal
- virtual simulation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000002474 experimental method Methods 0.000 title claims abstract description 120
- 238000004458 analytical method Methods 0.000 title claims abstract description 72
- 238000000034 method Methods 0.000 title claims abstract description 47
- 238000004891 communication Methods 0.000 claims abstract description 33
- 230000007274 generation of a signal involved in cell-cell signaling Effects 0.000 claims abstract description 11
- 238000011161 development Methods 0.000 claims description 45
- 230000003595 spectral effect Effects 0.000 claims description 25
- 238000005311 autocorrelation function Methods 0.000 claims description 24
- 238000009826 distribution Methods 0.000 claims description 14
- 238000004364 calculation method Methods 0.000 claims description 9
- 230000006870 function Effects 0.000 claims description 5
- 238000013461 design Methods 0.000 claims description 4
- 230000002776 aggregation Effects 0.000 abstract description 2
- 238000004220 aggregation Methods 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 11
- 238000005259 measurement Methods 0.000 description 4
- 238000012360 testing method Methods 0.000 description 4
- 238000012512 characterization method Methods 0.000 description 3
- 238000003491 array Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000008092 positive effect Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000004451 qualitative analysis Methods 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention belongs to the technical field of experimental network teaching of communication engineering, information engineering and the like, and discloses a random signal analysis experiment virtual simulation system and a control method, wherein the random signal analysis experiment virtual simulation system comprises: the communication signal generation hardware circuit module is used for generating communication signals of different modulation modes; a noise generation module for generating a noise signal; the communication system hardware circuit module is used for realizing a linear system or a nonlinear system; and the signal analysis software module is used for realizing characteristic analysis of the communication signal. The invention adopts a virtual simulation experiment platform of random signal analysis experiment combining software and hardware, which can not only solve the problem of overlarge investment of experimental equipment, but also solve the problem of incapability of aggregation; meanwhile, the experiment time and the experiment site of the students are flexible, and the students can perform experiments at any time and any place as long as the students have a network and a notebook computer.
Description
Technical Field
The invention belongs to the technical field of experimental network teaching of communication engineering, information engineering and the like, and particularly relates to a virtual simulation system for a random signal analysis experiment and a control method.
Background
At present, the random signal analysis experiment is an indispensable experiment course for related professions such as communication engineering, information engineering and the like, and the traditional random signal analysis experiment course analyzes and tests the working principle, composition and performance of each subsystem by using a specially developed experiment box and specially designed experiment items through classroom instruction, student manual practice after class and lecture mode of answering questions, so that students can learn the characteristics of random signals in various communication systems. Through experiments, the using method of a conventional measuring instrument in the communication engineering is mastered; by matching with the test key of the main performance index of the learning system of the typical experiment system, the knowledge of students on the qualitative and quantitative analysis of the system is enriched and broadened, so that the students receive engineering training.
However, with the continuous change of social environment and the continuous development of science and technology, the traditional offline experimental mode cannot meet the experimental requirements. The traditional off-line experiment mode needs to prepare one set of experimental equipment for each student doing the experiment at the same time, and because the total number of people is too many, even if batch teaching is carried out, the number of sets of experimental equipment needing to be prepared is not few, and the economic cost is relatively high. In the traditional experiment mode, students must come to the laboratory to complete the experiment within a specified time, while in the current management mode of schools, "one class schedule for a whole life" is implemented, the course and the class time of each student are not completely the same, so that it is difficult to ensure that students in one class can enter the laboratory to complete the experiment at the same time.
Through the above analysis, the problems and defects of the prior art are as follows:
(1) the traditional offline experimental mode has higher economic cost.
(2) Under the traditional experiment mode, it is difficult to ensure that students in one class can simultaneously enter a laboratory to complete the experiment.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a virtual simulation system and a control method for a random signal analysis experiment.
The invention is realized in such a way that a virtual simulation control method for a random signal analysis experiment comprises the following steps:
step one, inputting account information, entering an experiment selection interface, and selecting an experiment equipment number to start an experiment;
secondly, selecting an experimental project; setting experiment parameters;
thirdly, the virtual oscilloscope port drags the connecting line to a signal port to be observed, and the virtual oscilloscope is connected with the signal to be observed;
fourthly, observing the time domain waveform of the signal, and recording the amplitude of the observed signal; observing a signal frequency domain waveform;
fifthly, entering a random signal characteristic analysis module; calculating the mean value of the random signals, reading data displayed in an interface and recording an experimental result; calculating the variance of the random signal, reading data displayed in an interface and recording an experimental result; calculating the autocorrelation function of the random signal, and storing an autocorrelation function oscillogram displayed in an interface; selecting a power spectral density estimation method, estimating the power spectral density of the random signal, and storing a signal power spectral density oscillogram displayed in an interface;
sixthly, analyzing the characteristics of the random signal by MATLAB secondary development experiment: according to the IP address and the equipment number information of the copied remote equipment, filling hardware information when writing an MATLAB code, writing an MATLAB program according to own interest and thought to analyze the characteristics of signals, and storing an experimental result;
seventhly, generating an FPGA secondary development experiment by using the signal, and compiling an FPGA hardware description language program in a Quartus II software system; compiling, simulating and locking an IO port pin in an FPGA compiling environment to generate an rbf target file; selecting the generated rbf target file and loading the rbf target file to a secondary development platform; observing the waveform of the output signal by using a virtual oscilloscope;
and eighthly, uploading an experiment report on line and inquiring experiment results.
Further, the virtual simulation control method for the random signal analysis experiment utilizes a virtual oscilloscope to observe the characteristics of the time domain and the frequency domain of the signal.
Further, the virtual simulation control method for the random signal analysis experiment has the function of secondary development based on the FPGA and the MATLAB, and supports students to design hardware circuits and software systems according to own interests to complete signal generation and analysis experiments.
Further, the experimental parameters include: carrier frequency, symbol rate.
Another object of the present invention is to provide a virtual simulation system for a random signal analysis experiment, which implements the virtual simulation control method for a random signal analysis experiment, the virtual simulation system for a random signal analysis experiment including:
the communication signal generation hardware circuit module is used for generating communication signals of different modulation modes;
a noise generation module for generating a noise signal;
the communication system hardware circuit module is used for realizing a linear system and a nonlinear system;
and the signal analysis software module is used for realizing characteristic analysis of the communication signal.
Further, the communication signal generating hardware circuit module comprises a digital modulation system and an analog modulation system; the digital modulation system comprises an ASK modulation system, an FSK modulation system, a BPSK modulation system, a QPSK modulation system and a 16QAM modulation system; the analog modulation system comprises an AM modulation system, an FM modulation system and a PM modulation system;
the noise generation software module comprises a normal distribution noise generation module, a Poisson distribution noise generation module and a Rayleigh distribution noise generation module.
Further, the communication system circuit module comprises a linear system circuit and a nonlinear system circuit, wherein the linear system comprises a low-pass filter circuit, a high-pass filter circuit and a band-pass filter circuit, and the nonlinear circuit comprises a limiting amplifier circuit, a diode circuit and a mixer circuit;
the signal analysis software module is used for calculating and analyzing various random signal characteristics and comprises a mean value calculation module of a random signal, a variance calculation module of the random signal, an autocorrelation function estimation module of the random signal and a power spectral density estimation module of the random signal, wherein the autocorrelation function estimation has two modes of biased estimation and unbiased estimation, and the power spectral density estimation adopts three methods of an autocorrelation function method, a Fourier transform method and a piecewise average periodogram method.
By combining all the technical schemes, the invention has the advantages and positive effects that: the invention adopts a virtual simulation experiment platform of random signal analysis experiment combining software and hardware, which can not only solve the problem of overlarge investment of experimental equipment, but also solve the problem of incapability of aggregation; meanwhile, the experiment time and the experiment site of the students are flexible, and the students can perform experiments at any time and any place as long as the students have a network and a notebook computer.
The invention can reduce the investment of colleges on expensive experimental equipment, and is not limited by experimental sites and experimental time during the experiment; the system has the secondary development functions of FPGA and Matlab, and the experimental content is expandable and customizable, so that the system has strong flexibility; in the teaching process, students can know analog and digital modulation systems more intuitively and understand a signal characteristic analysis method more deeply through the virtual simulation experiment platform; the student experiment evaluation system can be used for examining and scoring the experiment operation and the obtained data of students, thereby greatly reducing the on-site examination and scoring burden of teachers.
Drawings
Fig. 1 is a flowchart of a virtual simulation control method for a random signal analysis experiment according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of a virtual simulation system for a random signal analysis experiment according to an embodiment of the present invention;
in fig. 2: 1. a communication signal generating hardware circuit module; 2. a noise generation module; 3. a communication system hardware circuit module; 4. a signal analysis software module.
Fig. 3 is a schematic diagram of a virtual simulation system for a random signal analysis experiment according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of selecting a match mode of a virtual oscilloscope according to an embodiment of the present invention.
Fig. 5 is a diagram of a virtual oscilloscope horizontal axis adjustment button provided by an embodiment of the invention.
Fig. 6 is a diagram of a virtual oscilloscope vertical axis adjustment button provided by an embodiment of the present invention.
FIG. 7 is a schematic diagram of a frequency of a measurement signal of a virtual oscilloscope according to an embodiment of the present invention.
Fig. 8 is a functional diagram of random signal analysis "MATLAB secondary development" provided by an embodiment of the present invention.
Fig. 9 is an information prompt box of MATLAB secondary development equipment according to an embodiment of the present invention.
Fig. 10 is a functional schematic diagram of random signal analysis "FPGA secondary development" provided in the embodiment of the present invention.
Fig. 11 is an illustration of the secondary development operation of the FPGA provided in the embodiment of the present invention.
Fig. 12 is a schematic diagram of an FPGA secondary development module according to an embodiment of the present invention.
Fig. 13 is a schematic diagram of measuring signals of the FPGA secondary development provided in the embodiment of the present invention.
Fig. 14 is a student operation interface of the virtual simulation experiment platform provided in the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides a virtual simulation system and a control method for a random signal analysis experiment, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the virtual simulation control method for a random signal analysis experiment provided by the present invention includes the following steps:
s101: inputting account information into an experiment selection interface, and selecting an experiment equipment number to start an experiment;
s102: selecting an experimental project; setting experiment parameters;
s103: the virtual oscilloscope port drags the connecting wire to a signal port to be observed, and the virtual oscilloscope is connected with the signal to be observed;
s104: observing a signal time domain waveform, and recording the amplitude of the observed signal; observing a signal frequency domain waveform;
s105: entering a random signal characteristic analysis module; calculating the mean value of the random signals, reading data displayed in an interface and recording an experimental result; calculating the variance of the random signal, reading data displayed in an interface and recording an experimental result; calculating the autocorrelation function of the random signal, and storing an autocorrelation function oscillogram displayed in an interface; selecting a power spectral density estimation method, estimating the power spectral density of the random signal, and storing a signal power spectral density oscillogram displayed in an interface;
s106: random signal characterization analysis "MATLAB secondary development" experiment: according to the copied information such as the IP address, the equipment number and the like of the remote equipment, hardware information is filled in when an MATLAB code is written, an MATLAB program is written according to the interest and the idea of the MATLAB program to analyze the characteristics of the signal, and the experimental result is stored;
s107: generating an FPGA secondary development experiment by using a signal, and compiling an FPGA hardware description language program in a Quartus II software system; compiling, simulating and locking an IO port pin in an FPGA compiling environment to generate an rbf target file; selecting the generated rbf target file and loading the rbf target file to a secondary development platform; observing the waveform of the output signal by using a virtual oscilloscope;
s108: and uploading an experiment report on line and inquiring experiment results.
Those skilled in the art can also implement the method of controlling virtual simulation of random signal analysis experiment provided by the present invention by using other steps, and the method of controlling virtual simulation of random signal analysis experiment provided by the present invention shown in fig. 1 is only a specific embodiment.
As shown in fig. 2, the virtual simulation system for random signal analysis experiment provided by the present invention includes:
the communication signal generation hardware circuit module 1 is used for generating communication signals with different modulation modes.
And the noise generation module 2 is used for generating a noise signal.
And the communication system hardware circuit module 3 is used for realizing a linear system or a nonlinear system.
And the signal analysis software module 4 is used for realizing characteristic analysis of the communication signal.
The technical solution of the present invention is further described with reference to the following specific examples.
Example 1:
in an embodiment of the invention: the communication signal generation hardware circuit module 1 comprises a digital modulation system and an analog modulation system, wherein the digital modulation system comprises an ASK modulation system, an FSK modulation system, a BPSK modulation system, a QPSK modulation system and a 16QAM modulation system; the analog modulation system comprises an AM modulation system, an FM modulation system and a PM modulation system.
Example 2:
in an embodiment of the invention: the noise generation software module 2 can generate several random noises with different distributions, and specifically includes a normal distribution noise generation module, a poisson distribution noise generation module, and a rayleigh distribution noise generation module.
Example 3:
in an embodiment of the invention: the communication system circuit module 3 includes a linear system circuit and a nonlinear system circuit, wherein the linear system includes a low-pass filter circuit, a high-pass filter circuit, and a band-pass filter circuit, and the nonlinear circuit includes a limiting amplifier circuit, a diode circuit, and a mixer circuit.
Example 4:
in an embodiment of the invention: the signal analysis software module 4 can perform calculation analysis on various random signal characteristics, including a mean value calculation module of a random signal, a variance calculation module of the random signal, an autocorrelation function estimation module of the random signal, and a power spectral density estimation module of the random signal, wherein the autocorrelation function estimation has two modes of biased estimation and unbiased estimation, and the power spectral density estimation can adopt three methods of an autocorrelation function method, a fourier transform method and a piecewise average periodogram method.
Example 5:
in an embodiment of the invention: the virtual simulation system for the random signal analysis experiment provided by the invention can observe the characteristics of the time domain and the frequency domain of the signal by using the virtual oscilloscope.
Example 6:
in an embodiment of the invention: the virtual simulation system for the random signal analysis experiment provided by the invention also has the function of secondary development based on the FPGA and the MATLAB, and supports students to design hardware circuits and software systems according to own interests so as to finish the generation of signals and the analysis experiment.
Example 7:
the virtual simulation control method for the random signal analysis experiment specifically comprises the following steps:
step one, registration: filling in information such as name, school number, specialty, class and the like, registering an account number, and acquiring an experimental authority;
step two, logging in an experiment platform: after entering a virtual simulation platform of random signal analysis experiment, inputting account information into an experiment selection interface, and selecting an experiment equipment number to start an experiment;
thirdly, selecting experimental items: selecting experimental items, such as "ASK signal generation and analysis experiment";
step four, setting parameters: setting experimental parameters such as carrier frequency, code element rate and the like;
fifthly, connecting a virtual instrument: clicking a virtual oscilloscope port, dragging a connecting wire to a signal port to be observed, and connecting the virtual oscilloscope with the signal to be observed;
sixthly, observing a signal time domain waveform: moving the mouse to the position of a virtual oscilloscope, clicking a left key, opening an oscilloscope window, observing the time domain waveform of a signal, and recording the amplitude of the observed signal;
and seventhly, observing a signal frequency domain waveform:
1) clicking a "math" button in the virtual oscilloscope, selecting an "FFT" mode, and selecting a signal channel to be observed, such as "CH 1";
2) moving the mouse to a horizontal axis zooming button in the virtual oscilloscope, clicking a left mouse button, sliding a mouse roller and adjusting a time window to a proper size;
3) moving the mouse to a longitudinal axis zooming button of a channel corresponding to the oscillography, clicking a left button of the mouse, sliding a roller of the mouse, and adjusting the amplitude to be a proper size; observing the frequency domain waveform of the selected channel signal after the transverse and longitudinal axes are adjusted;
4) measurement of signal frequency: moving the mouse to the position of the cursor, clicking the left button of the mouse, dragging the cursor to the peak point of the signal frequency domain waveform, and reading the value at the upper right corner of the oscilloscope (as shown in figure 5), so as to obtain the central frequency of the measured signal;
eighthly, clicking a 'random signal characteristic analysis' button to enter a random signal characteristic analysis module;
1) clicking a 'mean' button to calculate the mean of the random signals, reading data displayed in an interface and recording an experimental result;
2) clicking a variance button to calculate the variance of the random signal, reading data displayed in an interface and recording an experimental result;
3) clicking an autocorrelation function button to calculate the autocorrelation function of the random signal and storing an autocorrelation function oscillogram displayed in an interface;
4) clicking a power spectral density button, selecting a power spectral density estimation method, estimating the power spectral density of the random signal, and storing a signal power spectral density oscillogram displayed in an interface;
ninth, random signal characterization analysis "MATLAB secondary development" experiment:
1) clicking an MATLAB secondary development button to enter an MATLAB secondary development module;
2) after clicking a 'MATLAB secondary development' button, popping up an equipment information prompt box by the platform, indicating the ip address, the port number, the user identification code and other information of the current equipment, clicking a 'one-key copy' button, and copying equipment information;
3) according to the copied information such as the IP address, the equipment number and the like of the remote equipment, hardware information is filled in when an MATLAB code is written, then an MATLAB program is written according to the interest and the idea of the MATLAB program to analyze the characteristics of the signal, and the experimental result is stored;
tenth step, FPGA secondary development experiment of signal generation
1) Clicking an FPGA secondary development button to enter an FPGA secondary development module;
2) after clicking the 'FPGA secondary development' button, the platform pops up an FPGA secondary development operation instruction, and writes an FPGA hardware description language program in a Quartus II software system according to the operation instruction.
3) Compiling, simulating and locking an IO port pin in an FPGA compiling environment to generate an rbf target file;
4) loading an FPGA program file: moving the mouse to a chip icon in the secondary development module, clicking a left button of the mouse, popping up a file loading dialog box, selecting the rbf target file generated in the step 3), and loading the rbf target file to the secondary development platform.
5) Observing the waveform of the output signal by using a virtual oscilloscope: and moving the mouse to the position of a test hole in the virtual oscilloscope, clicking a left mouse button to drag the mouse to an input pin or an output pin end of the secondary development module, loosening the mouse, clicking a screen area of the virtual oscilloscope by the left mouse button, and unfolding the virtual instrument to observe the waveform of the tested signal.
Step ten, submitting an experimental report: after the experiment is completed, the students write the experiment report, and click an upload report button in the virtual simulation experiment platform to upload the experiment report on line.
Step ten, inquiring experimental results: the experiment result can be inquired by clicking the 'inquiry result' button in the experiment platform.
The technical solution of the present invention is further described below with reference to the accompanying drawings.
As shown in fig. 3, the software and hardware combined "random signal analysis experiment" virtual simulation experiment platform provided by the present invention includes a hardware circuit module for generating a communication signal, a noise generation module, a communication system hardware circuit module, and a signal analysis software module.
A hardware circuit module for generating communication signals in a software and hardware random signal analysis experiment virtual simulation experiment platform comprises a digital modulation system and an analog modulation system, wherein the digital modulation system comprises an ASK modulation system, an FSK modulation system, a BPSK modulation system, a QPSK modulation system and a 16QAM modulation system; the analog modulation system comprises an AM modulation system, an FM modulation system and a PM modulation system;
the noise generation software module in the software and hardware random signal analysis experiment virtual simulation experiment platform can generate several random noises with different distributions, and specifically comprises a normal distribution noise generation module, a Poisson distribution noise generation module and a Rayleigh distribution noise generation module;
a communication system circuit module in a software and hardware random signal analysis experiment virtual simulation experiment platform comprises a linear system circuit and a nonlinear system circuit, wherein the linear system comprises a low-pass filter circuit, a high-pass filter circuit and a band-pass filter circuit, and the nonlinear circuit comprises a limiting amplifier circuit, a diode circuit and a mixer circuit;
a software and hardware 'random signal analysis experiment' virtual simulation experiment platform can observe the characteristics of a signal time domain and a signal frequency domain by using a virtual oscilloscope;
a signal analysis software module in a random signal analysis experiment virtual simulation experiment platform of software and hardware can calculate and analyze various random signal characteristics, and comprises a mean value calculation module of random signals, a variance calculation module of the random signals, an autocorrelation function estimation module of the random signals and a power spectral density estimation module of the random signals, wherein the autocorrelation function estimation module has two modes of biased estimation and unbiased estimation, and the power spectral density estimation can adopt three methods of an autocorrelation function method, a Fourier transform method and a piecewise average periodogram method.
The random signal analysis experiment virtual simulation experiment platform of software and hardware also has the function of secondary development based on FPGA and MATLAB, and supports students to design hardware circuits and software systems according to own interests so as to finish the generation and analysis experiments of signals.
The operation method of the virtual simulation experiment platform provided by the invention comprises the following steps:
s1: registering: filling in information of name, school number, specialty, class and the like, registering account numbers and acquiring experimental authority.
S2: logging in an experimental platform: after entering a virtual simulation platform of random signal analysis experiment, inputting account information, entering an experiment selection interface, and selecting an experiment equipment number to start an experiment.
S3: selecting experimental items: selecting experimental items, such as selecting "ASK signal generation and analysis experiment".
S4: setting parameters: experimental parameters such as carrier frequency, symbol rate, etc. are set.
S5: virtual instrument connection: and clicking a virtual oscilloscope port, dragging the connecting wire to a signal port to be observed, and connecting the virtual oscilloscope with the signal to be observed.
S6: observing a signal time domain waveform: and moving the mouse to the position of the virtual oscilloscope, clicking a left key, opening an oscilloscope window, observing the time domain waveform of the signal, and recording the amplitude of the observed signal.
S7: observation signal frequency domain waveform:
s7.1, clicking a 'math' button in the virtual oscilloscope, selecting an 'FFT' mode, and selecting a signal channel to be observed, such as 'CH 1', as shown in FIG. 4;
s7.2: moving the mouse to a horizontal axis zooming button (shown in figure 5) in the virtual oscilloscope, clicking a left button of the mouse, sliding a roller of the mouse, and adjusting the time window to a proper size;
s7.3: moving the mouse to a longitudinal axis zooming button (shown in figure 6) of a channel corresponding to the oscillography, clicking a left button of the mouse, sliding a roller of the mouse, and adjusting the amplitude to a proper size; observing the frequency domain waveform of the selected channel signal after the transverse and longitudinal axes are adjusted;
s7.4: measurement of signal frequency: moving the mouse to the position of the cursor, clicking the left button of the mouse, dragging the cursor to the peak point of the signal frequency domain waveform, and reading the value at the upper right corner of the oscilloscope (as shown in fig. 7), so as to obtain the central frequency of the measured signal.
S8: clicking a 'random signal characteristic analysis' button to enter a random signal characteristic analysis module;
s8.1: clicking a 'mean' button to calculate the mean of the random signals, reading data displayed in an interface and recording an experimental result;
s8.2: clicking a variance button to calculate the variance of the random signal, reading data displayed in an interface and recording an experimental result;
s8.3: clicking an autocorrelation function button to calculate the autocorrelation function of the random signal and storing an autocorrelation function oscillogram displayed in an interface;
s8.4: clicking a power spectral density button, selecting a power spectral density estimation method, estimating the power spectral density of the random signal, and storing a signal power spectral density oscillogram displayed in an interface.
S9: random signal characterization analysis "MATLAB secondary development" experiment:
s9.1: clicking a 'MATLAB secondary development' button, and entering an MATLAB secondary development module as shown in FIG. 8;
s9.2: after clicking the "MATLAB secondary development" button, the platform pops up an equipment information prompt box (as shown in fig. 9), indicates information such as the ip address, the port number, the user identification code and the like of the current equipment, clicks the "one-click copy" button, and copies the information.
S9.3: and according to information about a signal IP address, an equipment number and the like of the remote equipment, which is popped up by the simulation platform, hardware information is filled in when MATLAB codes are written, then an MATLAB program is written according to own interests and ideas to analyze the characteristics of the signals, and the experimental results are saved.
S10: signal generation 'FPGA secondary development' experiment
S10.1: clicking a 'FPGA secondary development' button, and entering an FPGA secondary development module as shown in figure 10;
s10.2: after clicking a button of 'FPGA secondary development', popping up an FPGA secondary development operation instruction (as shown in figure 11) by the platform, and writing an FPGA hardware description language program in a Quartus II software system according to the operation instruction;
s10.3: compiling, simulating and locking an IO port pin in an FPGA compiling environment to generate an rbf target file;
s10.4: loading an FPGA program file: moving the mouse to a chip icon in the secondary development module, clicking a left mouse button as shown in fig. 12, popping up a file loading dialog box, selecting the rbf target file generated in the step S10.3, and loading the rbf target file to the secondary development platform;
s10.5: observing the waveform of the output signal by using a virtual oscilloscope: the mouse is moved to the position of a test hole in the virtual oscilloscope, the left button of the mouse is clicked and dragged to the input pin or the output pin end of the secondary development module, the mouse is released, the left button of the mouse is clicked in the screen area of the virtual oscilloscope, the virtual instrument is unfolded, and then the tested signal waveform can be observed, and the signal measurement schematic diagram is shown in fig. 13.
S11: submitting an experimental report: after the experiment is completed, the students write the experiment report, click the "upload report" button in the virtual simulation experiment platform to upload the experiment report on line, as shown in fig. 14.
S12: and (4) inquiring experimental results: the experiment result can be inquired by clicking the 'inquiry result' button in the experiment platform.
It should be noted that the embodiments of the present invention can be realized by hardware, software, or a combination of software and hardware. The hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the apparatus and methods described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided on a carrier medium such as a disk, CD-or DVD-ROM, programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier, for example. The apparatus and its modules of the present invention may be implemented by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors, or by a combination of hardware circuits and software, e.g., firmware.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (7)
1. A virtual simulation control method for a random signal analysis experiment is characterized by comprising the following steps:
step one, inputting account information, entering an experiment selection interface, and selecting an experiment equipment number to start an experiment;
secondly, selecting an experimental project; setting experiment parameters;
thirdly, the virtual oscilloscope port drags the connecting line to a signal port to be observed, and the virtual oscilloscope is connected with the signal to be observed;
fourthly, observing the time domain waveform of the signal, and recording the amplitude of the observed signal; observing a signal frequency domain waveform;
fifthly, entering a random signal characteristic analysis module; calculating the mean value of the random signals, reading data displayed in an interface and recording an experimental result; calculating the variance of the random signal, reading data displayed in an interface and recording an experimental result; calculating the autocorrelation function of the random signal, and storing an autocorrelation function oscillogram displayed in an interface; selecting a power spectral density estimation method, estimating the power spectral density of the random signal, and storing a signal power spectral density oscillogram displayed in an interface;
sixthly, analyzing the characteristics of the random signal by MATLAB secondary development experiment: according to the IP address and the equipment number information of the copied remote equipment, filling hardware information when writing an MATLAB code, writing an MATLAB program according to own interest and thought to analyze the characteristics of signals, and storing an experimental result;
seventhly, generating an FPGA secondary development experiment by using the signal, and compiling an FPGA hardware description language program in a Quartus II software system; compiling, simulating and locking an IO port pin in an FPGA compiling environment to generate an rbf target file; selecting the generated rbf target file and loading the rbf target file to a secondary development platform; observing the waveform of the output signal by using a virtual oscilloscope;
and eighthly, uploading an experiment report on line and inquiring experiment results.
2. The stochastic signal analysis experiment virtual simulation control method of claim 1, wherein the stochastic signal analysis experiment virtual simulation control method uses a virtual oscilloscope to observe the time domain and frequency domain characteristics of a signal.
3. The virtual simulation control method for the random signal analysis experiment as claimed in claim 1, wherein the virtual simulation control method for the random signal analysis experiment has a function of secondary development based on FPGA and MATLAB, and supports students to design hardware circuits and software systems according to their interests to complete the generation of signals and the analysis experiment.
4. The method for controlling virtual simulation of stochastic signal analysis experiment according to claim 1, wherein the experiment parameters comprise: carrier frequency, symbol rate.
5. A stochastic signal analysis experiment virtual simulation system for implementing the stochastic signal analysis experiment virtual simulation control method according to any one of claims 1 to 4, the stochastic signal analysis experiment virtual simulation system comprising:
the communication signal generation hardware circuit module is used for generating communication signals of different modulation modes;
a noise generation module for generating a noise signal;
the communication system hardware circuit module is used for realizing a linear system or a nonlinear system;
and the signal analysis software module is used for realizing characteristic analysis of the communication signal.
6. The stochastic signal analysis experiment virtual simulation system of claim 5, wherein the communication signal generation hardware circuit module comprises a digital modulation system and an analog modulation system; the digital modulation system comprises an ASK modulation system, an FSK modulation system, a BPSK modulation system, a QPSK modulation system and a 16QAM modulation system; the analog modulation system comprises an AM modulation system, an FM modulation system and a PM modulation system;
the noise generation software module comprises a normal distribution noise generation module, a Poisson distribution noise generation module and a Rayleigh distribution noise generation module.
7. The stochastic signal analysis experiment virtual simulation system of claim 5, wherein the communication system circuit module comprises a linear system circuit and a nonlinear system circuit, wherein the linear system comprises a low pass filter circuit, a high pass filter circuit, a band pass filter circuit, and the nonlinear circuit comprises a limiting amplifier circuit, a diode circuit, a mixer circuit;
the signal analysis software module is used for calculating and analyzing various random signal characteristics and comprises a mean value calculation module of a random signal, a variance calculation module of the random signal, an autocorrelation function estimation module of the random signal and a power spectral density estimation module of the random signal, wherein the autocorrelation function estimation has two modes of biased estimation and unbiased estimation, and the power spectral density estimation adopts three methods of an autocorrelation function method, a Fourier transform method and a piecewise average periodogram method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111595262.3A CN114398763B (en) | 2021-12-23 | 2021-12-23 | Random signal analysis experiment virtual simulation system and control method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111595262.3A CN114398763B (en) | 2021-12-23 | 2021-12-23 | Random signal analysis experiment virtual simulation system and control method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114398763A true CN114398763A (en) | 2022-04-26 |
| CN114398763B CN114398763B (en) | 2024-04-09 |
Family
ID=81226470
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111595262.3A Active CN114398763B (en) | 2021-12-23 | 2021-12-23 | Random signal analysis experiment virtual simulation system and control method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114398763B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102097018A (en) * | 2011-01-06 | 2011-06-15 | 吉林中软吉大信息技术有限公司 | Platform and method of virtual simulation communication system |
| CN104504975A (en) * | 2014-12-29 | 2015-04-08 | 清华大学 | Portable comprehensive electronic experimental platform on basis of field programmable gate arrays |
| US20200320902A1 (en) * | 2019-04-03 | 2020-10-08 | Dalian University Of Technology | Teaching system for remote hydraulic experiments based on combination of virtual and real |
-
2021
- 2021-12-23 CN CN202111595262.3A patent/CN114398763B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102097018A (en) * | 2011-01-06 | 2011-06-15 | 吉林中软吉大信息技术有限公司 | Platform and method of virtual simulation communication system |
| CN104504975A (en) * | 2014-12-29 | 2015-04-08 | 清华大学 | Portable comprehensive electronic experimental platform on basis of field programmable gate arrays |
| US20200320902A1 (en) * | 2019-04-03 | 2020-10-08 | Dalian University Of Technology | Teaching system for remote hydraulic experiments based on combination of virtual and real |
Non-Patent Citations (1)
| Title |
|---|
| 石昊强;蒋占军;: "Matlab和FPGA相结合的软硬件综合实验设计", 实验室研究与探索, no. 01 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114398763B (en) | 2024-04-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Chugani et al. | LabVIEW signal processing | |
| Mosterman et al. | Design and implementation of an electronics laboratory simulator | |
| CN106128178A (en) | Experimental system based on virtual instrument | |
| CN104933923A (en) | A medical electronic apparatus simulation experiment teaching platform based on a virtual instrument | |
| CN114398763A (en) | Random signal analysis experiment virtual simulation system and control method | |
| Lyubomirov et al. | Engineering Education And Examination Of Electronic Circuits Using Multisim | |
| Costa et al. | A reconfigurable and expandable kit to teach electronic circuits based on Operational Amplifiers | |
| Ptak | Application of DasyLab in teaching electrical engineering | |
| Momox et al. | A MATLAB GUI for Engineering Education in the Undergraduate Laboratory | |
| Li et al. | Developing digital measurement and analysis laboratory in circuits and electronics lab at TAMUK | |
| Stonick | Teaching signals and systems using the virtual laboratory environment in ECE at CMU | |
| Liang et al. | Application research of virtual reality technology in electronic technique teaching | |
| Plummer et al. | A circuits II laboratory accessible by Internet | |
| Krneta et al. | Labview-based laboratory environment for learning of filtering concepts | |
| Weissman et al. | Communication courseware for college students | |
| CN117269601A (en) | Radio signal test simulation system | |
| Shehova et al. | RESEARCH AND TEACHING OF DIGITALLY PROGRAMMABLE OSCILLATORS WITH MODELING IN THE TINA-TI ENVIRONMENT AND THE APPLICATION OF OPEN SOURCE PLATFORMS | |
| Aguirre et al. | Platform for testing and measuring based on virtual instrument | |
| Drăguşin et al. | Data Acquisition Systems with Virtual Results in Audio Signals Analysis | |
| Momox et al. | A MATLAB graphical user interface for electronic test instrument control in the electronics engineering undergraduate lab | |
| Yang et al. | Diagnosis of misconception in electronic circuits engineering courses: a case study at UESTC, China | |
| Achumba et al. | Genuine lab experiences for students in resource constrained environments: the RealLab with integrated intelligent assessment | |
| White | Microwave workshop for Windows | |
| Pardo et al. | VISCP: A virtual instrumentation and CAD tool for electronic engineering learning | |
| Ruangsiri et al. | Development of Virtual Experimental Package for Resonance Circuit Education |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |