Integrated virtual digital gyroscope simulation system and establishment method

Abstract

The invention discloses an integrated virtual digital gyroscope simulation system and an establishment method, and belongs to the field of gyroscope simulation. Comprising a front-end gyroscope structure simulation model, an MOPSO algorithm optimization model, a rear-end circuit model, a key kinetic parameter calculation model and a visualization model, and the input end of the front-end gyroscope structure simulation model and the input end of the MOPSO algorithm optimization model are connected with gyroscope structure size parameters respectively. The output end of the front-end gyroscope structure simulation model and the output end of the key kinetic parameter calculation model are further connected with the input end of the MOPSO algorithm optimization model, and the output end of the MOPSO algorithm optimization model is further connected with the rear-end circuit model. According to the integrated virtual digital gyroscope simulation system and the establishment method, the performance of the resonant gyroscope is improved, the design flexibility is improved, and the iteration speed is increased. By means of the visual operation interface, parameter input and result observation can be visually carried out, the interactivity and intuition of design are greatly improved, and visual operation of system-level simulation of the virtual digital gyroscope is achieved.

Description

Technical Field

[0001] The invention discloses an integrated virtual digital gyroscope simulation system and an establishment method, belonging to the field of gyroscope simulation. Background Art

[0002] As a key component in inertial navigation and positioning systems, the performance and reliability of gyroscopes are crucial to the entire system. Existing gyroscopes usually rely on complex hardware circuits and detection systems, which not only increase costs but also limit design flexibility and iteration speed. Traditional detection and calibration processes are often time-consuming and costly. In addition, with the diversification of application scenarios, the requirements for gyroscope performance are also increasing, including higher accuracy, faster response time, and better stability.

[0003] With the rapid development of new generation information technology, optimizing structural parameters through algorithms has become an effective means to improve performance parameters. However, the application of algorithm digital optimization to the improvement of resonant gyroscope performance and the system integration of circuit simulation has not yet been realized, and its visualization has not been fully developed. The exploration of this field has great application potential. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide a method for improving the performance of a resonant gyroscope, the flexibility of design, and the iteration speed. Through a visual operation interface, parameter input and result observation can be intuitively performed, which greatly improves the interactivity and intuitiveness of the design, and realizes an integrated virtual digital gyroscope simulation system and an establishment method for visual operation of a virtual digital gyroscope system-level simulation.

[0005] The technical solution adopted by the present invention to solve its technical problem is: the integrated virtual digital gyroscope simulation system is characterized by: comprising: a front-end gyroscope structure simulation model, a MOPSO algorithm optimization model, a back-end circuit model, a key dynamic parameter calculation model and a visualization model, the front-end gyroscope structure simulation model, the MOPSO algorithm optimization model, the back-end circuit model, and the key dynamic parameter calculation model are respectively connected to the visualization model; the input ends of the front-end gyroscope structure simulation model and the MOPSO algorithm optimization model are respectively connected to the gyroscope structure size parameters, the output ends of the front-end gyroscope structure simulation model and the key dynamic parameter calculation model are also respectively connected to the input end of the MOPSO algorithm optimization model, and the output end of the MOPSO algorithm optimization model is also connected to the back-end circuit model.

[0006] Preferably, the visualization model includes a gyroscope simulation visual module, an algorithm optimization structure visualization module and a virtual drive detection circuit visualization module. The output end of the front-end gyroscope structure simulation model is connected to the gyroscope simulation visual module in the visualization model, and the key dynamic parameter calculation model is also connected to the gyroscope simulation visual module. The output end of the MOPSO algorithm optimization model is connected to the algorithm optimization structure visualization module in the visualization model, and the output end of the back-end circuit model is connected to the virtual drive detection circuit visualization module in the visualization model.

[0007] Preferably, in the back-end circuit model, a virtual driving and detection circuit of the gyroscope is built by Simulink.

[0008] Preferably, a system-level connection for parameter synchronization is achieved between the front-end gyroscope structure simulation model and the virtual detection circuit.

[0009] A method for establishing an integrated virtual digital gyroscope simulation system, characterized in that it comprises the following steps:

[0010] Step 1, establishing a front-end gyroscope structure simulation model;

[0011] In the process of building the front-end simulation model of the resonant gyroscope, the key size parameters of the structure to be studied are first extracted, and these parameters are set as input variables of the simulation model and the integrated virtual digital gyroscope simulation system. After that, physical fields such as solid mechanics and thermodynamics are introduced, and the model is meshed to simulate and obtain key parameters such as the frequency, quality factor and shell unit displacement of the working mode;

[0012] Step 2, establishing a key kinetic parameter calculation model;

[0013] A key dynamic parameter calculation model calculates and outputs key dynamic performance parameters by taking the simulated performance parameters of the resonant gyro as input;

[0014] Step 3, establish the MOPSO algorithm optimization model;

[0015] The multi-objective particle swarm optimization algorithm is used to optimize the structure of the resonant gyroscope and generate the Pareto optimal solution set.

[0016] Step 4, establishing a back-end circuit model;

[0017] Through digital virtual technology, Simulink was used to build a virtual gyro drive and detection circuit, and the circuit was digitally constructed, including the design of the overall detection loop, the design of the drive loop, and the specific impact of various errors on the gyroscope;

[0018] Step 5, establish a visual output module;

[0019] The visual user interaction interface is designed through graphical user interface programming, including the input of front-end resonant gyroscope simulation performance parameters and the output of modal drive detection results, forming a gyroscope simulation visualization module, an algorithm optimization structure visualization module and a virtual drive detection circuit visualization module.

[0020] Preferably, step 2 comprises the following steps:

[0021] Step 2-1, establish a digital model of the shape function:

[0022]

[0023] Among them, q1 and q2 are two generalized coordinates of vibration displacement, U is the shell unit displacement, Φ is the shape function, also known as the normal mode vector, which is the displacement vector of the infinitesimal mass unit of the shell, normalized to the maximum amplitude of a single mode, (Φ x1 , Φ y1 , Φ z1 ) and (Φ x2 , Φ y2 , Φ z2 ) are the shape functions of the two working modes;

[0024] Step 2-2, establish effective mass M eff , angular gain A g and angle random walk Ω ARW The kinetic parameters of the model:

[0025]

[0026] Where ρ is the material density, ω is the operating modal frequency, and q drive is the vibration amplitude, K B is the Boltzmann constant and T is the temperature.

[0027] Preferably, step 4 comprises the following steps:

[0028] Step 4-1: Establish a virtual drive circuit model;

[0029] The working modal frequency, quality factor, displacement and angular gain of the shell unit of the front-end input resonant gyroscope are used as key dynamic parameters, and the virtual circuit driving parameters include the electrode gap and DC bias size;

[0030] Step 4-2: Establish a virtual detection circuit model;

[0031] The virtual detection circuit model generates signals through the Simulink model. The key input parameters include input angular rate, signal frequency, signal gain, and interference signal characteristics for two modes, including the amplitude and frequency of high-frequency interference and the signal-to-noise ratio of Gaussian white noise.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] The integrated virtual digital gyroscope simulation system and its establishment method improve the performance of the resonant gyroscope, as well as the flexibility and iteration speed of the design. Through the visual operation interface, parameters can be input and results can be observed intuitively, which greatly improves the interactivity and intuitiveness of the design and realizes the visual operation of the virtual digital gyroscope system-level simulation.

[0034] Through the integrated virtual digital gyroscope simulation system and establishment method, an integrated virtual digital gyroscope simulation system is provided. By establishing a front-end resonant gyroscope simulation model, the model can simulate and calculate the key parameters such as the working modal frequency, quality factor and shell unit displacement of a resonant gyroscope of any size according to the input structural size parameters. And the results are input into the key dynamic parameter calculation module. The key dynamic parameter calculation module receives the output parameters of the simulation model, calculates and outputs key dynamic performance parameters such as effective mass, angular gain and angle random walk. The structural parameters can also be optimized through the multi-objective algorithm optimization module to significantly improve the dynamic performance of the resonant gyroscope. Through digital virtual technology, a gyroscope virtual detection circuit is built with Simulink. The circuit includes the design of the overall detection loop, the design of the drive loop, and the simulation of the specific effects of various errors on the gyroscope. A system connection with parameter synchronization is established between the front-end resonant gyroscope simulation model and the virtual detection circuit, achieving the goal of systematic integration and digital virtualization. The virtual digital gyroscope simulation system has achieved the joint simulation design of structure and circuit for the first time, greatly improving the efficiency of gyroscope design.

[0035] The dynamic performance of the resonant gyroscope can be significantly improved by finely optimizing the structure of the resonant gyroscope using the multi-objective particle swarm optimization (MOPSO) algorithm. This method can not only obtain the optimal dynamic parameters, but also provide an important reference for designers in the structural design stage.

[0036] Through digital virtual technology, a gyro virtual detection circuit was built with Simulink, and the circuit was digitally constructed, including the design of the overall detection loop, the design of the drive loop, and the specific impact of various errors on the gyroscope; the back-end Simulink model was obtained. Among them, a system connection with parameter synchronization was established between the front-end resonant gyro simulation model and the digital virtual circuit.

[0037] The integrated virtual digital gyroscope simulation system can not only provide performance parameters based on specific structural dimensions, but also further meet the customized needs of users. The system captures the mapping relationship between each structural dimension and the corresponding dynamic parameters and integrates it into the optimization algorithm module. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is the principle block diagram of the integrated virtual digital gyroscope simulation system.

[0039] Figure 2 The present invention is a flow chart of the method for establishing an integrated virtual digital gyroscope simulation system. DETAILED DESCRIPTION

[0040] Figures 1-2 The best embodiment of the present invention is shown below in conjunction with the attached Figures 1-2 The present invention is further described.

[0041] like Figure 1 As shown, an integrated virtual digital gyroscope simulation system includes a front-end gyroscope structure simulation model, a MOPSO algorithm optimization model, a back-end circuit model, a key dynamic parameter calculation model and a visualization model. The visualization model includes a gyroscope simulation visual module, an algorithm optimization structure visualization module and a virtual drive detection circuit visualization module.

[0042] The input ends of the front-end gyroscope structure simulation model and the MOPSO algorithm optimization model are respectively connected to the gyroscope structure size parameters, and the output ends of the front-end gyroscope structure simulation model are respectively connected to the key dynamic parameter calculation model and the gyroscope simulation visualization module in the visualization model, and the key dynamic parameter calculation model is simultaneously connected to the gyroscope simulation visualization module. The output ends of the front-end gyroscope structure simulation model and the key dynamic parameter calculation model are also respectively connected to the input end of the MOPSO algorithm optimization model. The output end of the MOPSO algorithm optimization model is respectively connected to the back-end circuit model and the algorithm optimization structure visualization module in the visualization model. The input end of the back-end circuit model is connected to parameters such as electrode gap and angular velocity, and the output end of the back-end circuit model is connected to the virtual drive detection circuit visualization module in the visualization model.

[0043] In the simulation model of the front-end gyroscope structure, physical fields such as solid mechanics and thermodynamics are added to change the shape and size of the resonant gyroscope, and the simulation performance parameters of the desired resonant gyroscope of any size are obtained through simulation calculation. In the key dynamic parameter calculation model, the working modal frequency, quality factor and displacement of the shell unit of the resonant gyroscope are used as input to calculate and output key parameters such as effective mass, angular gain and angular random walk. These parameters are then integrated into the virtual detection circuit and the intuitive visual operation interface to achieve comprehensive evaluation and monitoring of gyroscope performance.

[0044] In the MOPSO algorithm optimization model, the multi-objective particle swarm optimization (MOPSO) algorithm is used to optimize the structure of the resonant gyroscope and generate the Pareto optimal solution set. Users can select appropriate structural size parameters from these solution sets based on specific application scenarios and performance requirements to achieve optimal design.

[0045] In the back-end circuit model, the gyro virtual drive and detection circuit was built with Simulink through digital virtual technology, and the circuit was digitally constructed, including the design of the overall detection loop, the design of the drive loop, and the specific impact of various errors on the gyroscope. The simulation model of the front-end resonant gyro and the virtual detection circuit achieved a system-level connection with parameter synchronization, ensuring that the output parameters of the front-end gyro structure can be directly used as the input of the virtual detection circuit, thus achieving the goal of systematic integration and digital virtualization.

[0046] In the back-end circuit model, a highly flexible platform is provided by simulating the input of high-frequency error and Gaussian white noise error. The back-end circuit model is equipped with a parameterizable FIR low-pass filter, which can generate and optimize the driving signal, detection signal and filtering effect of the virtual circuit mode, providing data support for the subsequent visualization module.

[0047] As can be seen from the above, the visualization model includes a gyroscope simulation visualization module, an algorithm optimization structure visualization module, and a virtual drive detection circuit visualization module. In the gyroscope simulation visualization module, users can input key resonant gyroscope structural size parameters through an intuitive visualization interface. The system then outputs a series of key performance parameters including operating modal frequency, quality factor, shell unit displacement, effective mass, angular gain, and angle random walk. This function enables users to directly obtain the performance indicators of gyroscopes in any size configuration, thereby achieving a comprehensive evaluation and real-time monitoring of its performance.

[0048] In the algorithm optimization structure visualization module, in order to meet the customized needs of users, the required key structural size parameters can be input through the algorithm optimization structure visualization module, and these parameters will be used as the initial input of the optimization algorithm. The system's built-in multi-objective particle swarm optimization (MOPSO) algorithm will perform intelligent optimization based on this and automatically adjust the structure of the resonant gyroscope to achieve optimal performance. Finally, the algorithm optimization structure visualization module will display the Pareto optimal solution set, providing users with an intuitive and efficient structural optimization solution.

[0049] In the virtual drive detection circuit visualization module, the parameters such as electrode gap and DC bias size are used as the input of the virtual drive circuit, the angular rate, signal frequency, signal gain and FIR filter input signal are used as the input of the virtual detection circuit, and the interference signal characteristics of the two modes and the results of modal drive detection are used as the output of the virtual drive detection circuit visualization module. Allowing users to input parameters and observe the output results in real time greatly improves the interactivity and intuitiveness of the design and realizes the visualization operation of the virtual digital gyroscope system-level simulation.

[0050] like Figure 2 As shown, establishing the above-mentioned integrated virtual digital gyroscope simulation system includes the following steps:

[0051] Step 1, establishing a front-end gyroscope structure simulation model;

[0052] In the process of building the front-end simulation model of the resonant gyroscope, the key dimensional parameters of the structure to be studied are first extracted, and these parameters are set as input variables of the simulation model and the integrated virtual digital gyroscope simulation system. After that, physical fields such as solid mechanics and thermodynamics are introduced, and the model is meshed to simulate and obtain key parameters such as the frequency, quality factor and shell unit displacement of the working mode.

[0053] Step 2, establishing a key kinetic parameter calculation model;

[0054] The key dynamic parameter calculation model uses the simulated resonant gyro performance parameters obtained by simulation as input to calculate and output the key dynamic performance parameters. Specifically, it includes the following steps:

[0055] Step 2-1, establish a digital model of the shape function:

[0056]

[0057] Among them, q1 and q2 are two generalized coordinates of vibration displacement, U is the shell unit displacement, Φ is the shape function, also known as the normal mode vector, which is the displacement vector of the infinitesimal mass unit of the shell, normalized to the maximum amplitude of a single mode. (Φ x1 , Φ y1 , Φ z1 ) and (Φ x2 , Φ y2 , Φ z2 ) are the shape functions of the two working modes.

[0058] Step 2-2, establish effective mass M eff , angular gain A g and angle random walk Ω ARW The kinetic parameters of the model:

[0059]

[0060] Where ρ is the material density, ω is the operating modal frequency, and q drive is the vibration amplitude, K B is the Boltzmann constant and T is the temperature.

[0061] Step 3, establish the MOPSO algorithm optimization model;

[0062] The multi-objective particle swarm optimization (MOPSO) algorithm is used to optimize the structure of the resonant gyroscope and generate the Pareto optimal solution set. Users can select appropriate structural size parameters from these solution sets according to specific application scenarios and performance requirements to achieve optimal design.

[0063] Step 4, establishing a back-end circuit model;

[0064] Through digital virtual technology, Simulink was used to build a gyro virtual drive and detection circuit, and the circuit was digitally constructed, including the design of the overall detection loop, the design of the drive loop, and the specific impact of various errors on the gyroscope. The simulation model of the front-end resonant gyro and the virtual detection circuit achieved a system-level connection with parameter synchronization, ensuring that the output parameters of the front-end gyro structure can be directly used as the input of the virtual detection circuit, thereby achieving the goal of systematic integration and digital virtualization, including the following steps:

[0065] Step 4-1: Establish a virtual drive circuit model;

[0066] The front-end inputs the key dynamic parameters of the resonant gyroscope, such as the operating modal frequency, quality factor, and displacement and angular gain of the shell unit. The virtual circuit driving parameters include parameters such as electrode gap and DC bias size. This model mainly realizes the simulation of the virtual driving module to help users select appropriate driving schemes and driving parameters.

[0067] Step 4-2: Establish a virtual detection circuit model;

[0068] The virtual detection circuit model generates signals through the Simulink model, which is built based on mathematical formulas. Users can directly adjust the main wave amplitude and orthogonal amplitude of the generated signal. The key input parameters cover many aspects of signal generation, including input angular rate, signal frequency, signal gain, and interference signal characteristics for two modes, such as the amplitude and frequency of high-frequency interference and the signal-to-noise ratio of Gaussian white noise. In addition, the phase-locked loop module allows users to set the amplitude and frequency of the in-phase and orthogonal signals. The FIR filter module shows the parameters of the filter used in detail, including the order, pass frequency and cutoff frequency settings of the two-mode filter and the subsequent demodulation application.

[0069] Step 5, establish a visual output module;

[0070] The visual user interaction interface is designed through graphical user interface programming, including the input of front-end resonant gyroscope simulation performance parameters and the output of modal drive detection results, forming a gyroscope simulation visualization module, an algorithm optimization structure visualization module and a virtual drive detection circuit visualization module.

[0071] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any technician familiar with the profession may use the above disclosed technical content to change or modify it into an equivalent embodiment with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention still belongs to the protection scope of the technical solution of the present invention.

Claims

1. An integrated virtual digital gyroscope simulation system, characterized in that: include: The front-end gyroscope structure simulation model, the MOPSO algorithm optimization model, the back-end circuit model, the key dynamic parameter calculation model and the visualization model, the front-end gyroscope structure simulation model, the MOPSO algorithm optimization model, the back-end circuit model, the key dynamic parameter calculation model are connected to the visualization model respectively; the input ends of the front-end gyroscope structure simulation model and the MOPSO algorithm optimization model are respectively connected to the gyroscope structure size parameters, the output ends of the front-end gyroscope structure simulation model and the key dynamic parameter calculation model are also respectively connected to the input end of the MOPSO algorithm optimization model, and the output end of the MOPSO algorithm optimization model is also connected to the back-end circuit model.

2. The integrated virtual digital gyroscope simulation system according to claim 1, characterized in that: The visualization model includes a gyroscope simulation visualization module, an algorithm optimization structure visualization module and a virtual drive detection circuit visualization module. The output end of the front-end gyroscope structure simulation model is connected to the gyroscope simulation visualization module in the visualization model, and the key dynamic parameter calculation model is also connected to the gyroscope simulation visualization module. The output end of the MOPSO algorithm optimization model is connected to the algorithm optimization structure visualization module in the visualization model, and the output end of the back-end circuit model is connected to the virtual drive detection circuit visualization module in the visualization model.

3. The integrated virtual digital gyroscope simulation system according to claim 1, characterized in that: In the back-end circuit model, the virtual drive and detection circuits of the gyroscope instrument were built through Simulink.

4. The integrated virtual digital gyroscope simulation system according to claim 3, characterized in that: A system-level connection is provided between the front-end gyroscope structure simulation model and the virtual detection circuit to achieve parameter synchronization.

5. A method for establishing an integrated virtual digital gyroscope simulation system, used to implement the integrated virtual digital gyroscope simulation system according to any one of claims 1 to 4, characterized in that: The steps include: Step 1, establishing a front-end gyroscope structure simulation model; In the process of building the front-end simulation model of the resonant gyroscope, the key size parameters of the structure to be studied are first extracted, and these parameters are set as input variables of the simulation model and the integrated virtual digital gyroscope simulation system. After that, physical fields such as solid mechanics and thermodynamics are introduced, and the model is meshed to simulate and obtain key parameters such as the frequency, quality factor and shell unit displacement of the working mode; Step 2, establishing a key kinetic parameter calculation model; The key dynamic parameter calculation model calculates and outputs the key dynamic performance parameters by taking the simulated performance parameters of the resonant gyro as input; Step 3, establish the MOPSO algorithm optimization model; The multi-objective particle swarm optimization algorithm is used to optimize the structure of the resonant gyroscope and generate the Pareto optimal solution set. Step 4, establishing a back-end circuit model; Through digital virtual technology, Simulink was used to build a virtual gyro drive and detection circuit, and the circuit was digitally constructed, including the design of the overall detection loop, the design of the drive loop, and the specific impact of various errors on the gyroscope; Step 5, establish a visual output module; The visual user interaction interface is designed through graphical user interface programming, including the input of front-end resonant gyroscope simulation performance parameters and the output of modal drive detection results, forming a gyroscope simulation visualization module, an algorithm optimization structure visualization module and a virtual drive detection circuit visualization module.

6. The method for establishing an integrated virtual digital gyroscope simulation system according to claim 5, characterized in that: Step 2 includes the following steps: Step 2-1, establish a digital model of the shape function: Among them, q1 and q2 are two generalized coordinates of vibration displacement, U is the shell unit displacement, Φ is the shape function, also known as the normal mode vector, which is the displacement vector of the infinitesimal mass unit of the shell, normalized to the maximum amplitude of a single mode, (Φ x1 , Φ y1 , Φ z1 ) and (Φ x2 , Φ y2 , Φ z2 ) are the shape functions of the two working modes; Step 2-2, establish effective mass M eff , angular gain A g and angle random walk Ω ARW The kinetic parameters of the model: Where ρ is the material density, ω is the operating modal frequency, and q drive is the vibration amplitude, K B is the Boltzmann constant and T is the temperature.

7. The method for establishing an integrated virtual digital gyroscope simulation system according to claim 5, characterized in that: Step 4 includes the following steps: Step 4-1: Establish a virtual drive circuit model; The front-end input resonant gyroscope's operating modal frequency, quality factor, and the displacement and angular gain of the shell unit are used as key dynamic parameters, and the virtual circuit driving parameters include the electrode gap and DC bias size; Step 4-2: Establish a virtual detection circuit model; The virtual detection circuit model generates signals through the Simulink model. The key input parameters include input angular rate, signal frequency, signal gain, and interference signal characteristics for two modes, including the amplitude and frequency of high-frequency interference and the signal-to-noise ratio of Gaussian white noise.

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