Error Identification Method for Resonant Gyroscopes Based on Variable DC Bias Voltage

Abstract

A method for identifying resonant gyroscope errors based on variable DC bias voltage, involving resonant gyroscope detection technology, including setting... n DC bias voltage U D The frequency split Δ was measured. f and spindle azimuth angle; based on DC bias voltage 𝑈 𝐷 The frequency splitting function and principal axis azimuth function are established using the fourth harmonic coefficient of mass, the fourth harmonic azimuth angle of mass, the fourth harmonic coefficient of gap, and the fourth harmonic azimuth angle of gap. A set of error parameters is randomly selected and substituted into the simulation function to obtain the simulation arrays for frequency splitting and principal axis azimuth. The evaluation and optimization function values ​​are then calculated. MF ; Determine and evaluate the optimization function value MF If the error exceeds a preset threshold, the random error parameter set is updated according to a swarm intelligence optimization algorithm; otherwise, the error parameter is output. This method can identify the fourth harmonic error of the harmonic oscillator mass inhomogeneity and the fourth harmonic error of the lip gap inhomogeneity.

Description

Technical Field

[0001] This invention relates to the field of resonant gyroscope detection technology, and in particular to a method for identifying resonant gyroscope errors based on variable DC bias voltage. Background Technology

[0002] A resonant gyroscope is an inertial-level solid-state wave gyroscope. Its working principle is based on the precession effect of the standing wave of the resonator to sense the angle or angular velocity of the external environment. It has unique advantages such as high precision, small size, strong shock resistance, long life and high reliability. It has broad application prospects in military and civilian fields such as precision guidance, aviation, aerospace, navigation, and consumer electronics. It is recognized by the inertial technology community at home and abroad as a disruptive inertial device in the 21st century.

[0003] Currently, Northrop Grumman in the United States and Safran in France have mastered most of the core technologies of resonant gyroscopes and have achieved mass production applications. Safran's resonant gyroscope with a two-piece planar electrode structure significantly reduces assembly difficulty and production costs, achieving an annual output of 25,000 units with an accuracy ranging from 0.1° / h to 0.0001° / h, giving it strong market competitiveness. While China has developed experimental prototypes of resonant gyroscopes, there is still a long way to go before engineering prototypes and commercial applications. Furthermore, the accuracy of domestically reported resonant gyroscopes is still 2-3 orders of magnitude lower than the highest international levels.

[0004] The development of resonant gyroscopes involves multiple processes and procedures, including the fabrication of resonators, chemical etching, coating, leveling and precision assembly, fabrication and etching of flat electrodes, circuit design, manufacturing and testing, and vacuum packaging of the meter head. Among these processes, the development of resonant gyroscopes is usually evaluated by testing indicators such as the quality factor, quality factor non-uniformity, and frequency splitting of the resonators.

[0005] Taking frequency fragmentation as an example, existing research shows that in addition to the fourth harmonic error of the resonator's mass inhomogeneity affecting the frequency fragmentation, the fourth harmonic error of the lip gap inhomogeneity during the assembly of the resonator and the plate electrode also affects the frequency fragmentation of the gyroscope head. Furthermore, the frequency fragmentation introduced by the latter is also related to the DC bias voltage of the head. Specifically, the fourth harmonic error of the resonator's mass inhomogeneity includes the fourth harmonic coefficient of the resonator's mass. And the fourth harmonic azimuth angle The fourth harmonic error of the non-uniformity of the lip gap of the harmonic oscillator mainly includes the fourth harmonic coefficient of the gap. and the fourth harmonic azimuth angle of the gap As can be seen from the above, both the fourth harmonic error due to mass non-uniformity and the fourth harmonic error due to lip gap non-uniformity during assembly will affect the frequency fragmentation of the resonant gyroscope head. Therefore, it is necessary to identify these two types of errors so that they can be eliminated or compensated in the assembly process or control algorithm, thus laying the foundation for improving the assembly accuracy and performance of the resonant gyroscope. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to overcome the shortcomings of the existing technology and provide a resonant gyroscope error identification method based on variable DC bias voltage. This method can simultaneously identify the fourth harmonic error of the resonator mass non-uniformity and the fourth harmonic error of the lip gap non-uniformity.

[0007] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0008] A method for identifying resonant gyroscope errors based on variable DC bias voltage includes the following steps:

[0009] S1: Data measurement, based on the resonant gyroscope component under test, settings n More than one different DC bias voltage U D ,and n The integers are greater than 2, and the frequency splitting Δ is measured under the corresponding DC bias voltage conditions. f and principal axis azimuth A set of DC bias voltage values ​​were obtained. U D1 , U D2 , … , U Dn} and the measured frequency splitting array corresponding to each DC bias voltage value { , ,···, } and the measured array of principal axis azimuth angles { , ,···, };

[0010] S2: Establish the simulation calculation function for resonant gyroscope error identification, based on a set of DC bias voltage values ​​obtained in step S1 { U D1 , U D2 , … , U Dn} and the fourth harmonic coefficient of mass azimuth angle of the fourth harmonic of mass The fourth harmonic coefficient of the gap and the fourth harmonic azimuth angle of the gap Four variables are used to establish the corresponding values ​​of the known DC bias voltage. n Frequency decomposition function { , ,···, }and n The frequency principal axis azimuth angle function { , ,···, };

[0011] S3: Simulation calculation, based on the fourth harmonic coefficient of mass. azimuth angle of the fourth harmonic of mass The fourth harmonic coefficient of the gap and the fourth harmonic azimuth angle of the gap Random values ​​are selected within the range of values ​​to obtain a random error parameter set. This random parameter set is then substituted into the simulation calculation function established in step S2 to calculate the relationship between the DC bias voltage values ​​and the given values. U D1 , U D2 , … , U Dn The corresponding frequency splitting simulation array { , ,···, } and principal axis azimuth simulation array { , ,···, };

[0012] S4: Calculate the evaluation optimization function value MF The evaluation optimization function value is calculated based on equation (1). MF ;

[0013]

[0014] In equation (1), and These are the weighting factors;

[0015] S5: Judgment, evaluate the optimization function value MF Whether it exceeds a preset threshold, if so, evaluate the optimization function value. MF If the error exceeds the preset threshold, step S3 is repeated, and the random error parameter set is updated according to the swarm intelligence optimization algorithm; otherwise, the current error parameter is output as the error parameter of the resonant gyroscope component under test.

[0016] In step S2, the simulation calculation function is shown in equation (2).

[0017]

[0018] In equation (2),

[0019]

[0020]

[0021]

[0022]

[0023]

[0024] in, ε The permittivity of the dielectric between the lip of the harmonic oscillator and the plate electrode is given. The density of the harmonic oscillator, Let be the Young's modulus of the harmonic oscillator. Let be the thickness of the resonator shell. Let be the radius of the mid-surface of the resonator shell. It is the reciprocal of the gap between the lip of the harmonic oscillator and the plate electrode.

[0025] The mass fourth harmonic coefficient azimuth angle of the fourth harmonic of mass The fourth harmonic coefficient of the gap and the fourth harmonic azimuth angle of the gap The range of values ​​for are as follows: The value range is 0 to 0.001. The value range is 0 to 0.1. and The value range is ±180°.

[0026] The random error parameter set contains at least 20 columns of error parameters, each column of error parameters being composed of the fourth harmonic quality coefficient. azimuth angle of the fourth harmonic of mass The fourth harmonic coefficient of the gap and the fourth harmonic azimuth angle of the gap The system consists of four error parameters. In step S3, the error parameters in the random error parameter group are substituted into the simulation calculation function column by column.

[0027] The swarm intelligence optimization algorithm is a particle swarm optimization algorithm, a genetic algorithm, or an ant colony algorithm.

[0028] The preset threshold value ranges from 0 to 1.

[0029] The weighting factor and The values ​​range from 0.01 to 1000.

[0030] Compared with the prior art, the advantages of the present invention are as follows:

[0031] This invention presents a resonant gyroscope error identification method based on variable DC bias voltage. Its main purpose is to address two types of error identification problems in resonant gyroscopes: fourth harmonic error due to resonator mass inhomogeneity and fourth harmonic error due to resonator lip assembly gap inhomogeneity. This provides data support for resonant gyroscope error correction and compensation, and is of significant importance for improving the assembly accuracy and performance of resonant gyroscopes. This invention establishes a simulation calculation function for resonant gyroscope error identification and combines it with a swarm intelligence optimization algorithm to identify the fourth harmonic errors of both resonator mass inhomogeneity and lip gap inhomogeneity. The use of a swarm intelligence optimization algorithm for error parameter identification results in a higher degree of automation and intelligence. After acquiring frequency splitting and principal axis azimuth data under different DC bias voltages, it can quickly achieve automated identification of error parameters, resulting in higher efficiency and greater versatility. Attached Figure Description

[0032] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0033] Picture 1 This is a flowchart illustrating an embodiment of the resonant gyroscope error identification method based on variable DC bias voltage according to the present invention.

[0034] Picture 2 This is a comparison chart of simulation results and measured data for frequency splitting in an embodiment of the resonant gyroscope error identification method based on variable DC bias voltage according to the present invention.

[0035] Picture 3 This is a comparison chart of simulation results and measured data of the principal axis azimuth angle in an embodiment of the resonant gyroscope error identification method based on variable DC bias voltage according to the present invention. Detailed Implementation

[0036] like Picture 1 As shown, an embodiment of the resonant gyroscope error identification method based on variable DC bias voltage according to the present invention includes the following steps:

[0037] S1: Data measurement, based on the resonant gyroscope component under test, settings n More than one different DC bias voltage U D ,and n The integers are greater than 2, and the frequency splitting Δ is measured under the corresponding DC bias voltage conditions. fand principal axis azimuth A set of DC bias voltage values ​​were obtained. U D1 , U D2 , … , U Dn} and the measured frequency splitting array corresponding to each DC bias voltage value { , ,···, } and the measured array of principal axis azimuth angles { , ,···, };

[0038] In this embodiment, n =7, and the actual array data is shown in Table 1;

[0039]

[0040] Table 1: Measured array data based on different DC bias voltages

[0041] S2: Establish the simulation calculation function for resonant gyroscope error identification, based on a set of DC bias voltage values ​​obtained in step S1 { U D1 , U D2 , … , U Dn} and the fourth harmonic coefficient of mass azimuth angle of the fourth harmonic of mass The fourth harmonic coefficient of the gap and the fourth harmonic azimuth angle of the gap Four variables are used to establish the corresponding values ​​of the known DC bias voltage. n Frequency decomposition function { , ,···, }and n The frequency principal axis azimuth angle function { , ,···, };

[0042] S3: Simulation calculation, based on the fourth harmonic coefficient of mass. azimuth angle of the fourth harmonic of mass The fourth harmonic coefficient of the gap and the fourth harmonic azimuth angle of the gap Random values ​​are selected within the range of values ​​to obtain a random error parameter set. This random parameter set is then substituted into the simulation calculation function established in step S2 to calculate a frequency splitting simulation array corresponding to each set of DC bias voltage values. , ,···, } and principal axis azimuth simulation array { , ,···, };

[0043] S4: Calculate the evaluation optimization function value MF The evaluation optimization function value is calculated based on equation (1). MF ;

[0044]

[0045] In equation (1), and These are the weighting factors; weighting factors and The values ​​range from 0.01 to 1000. In this embodiment, =10, =1.

[0046] S5: Judgment, evaluate the optimization function value MF Whether it is greater than a preset threshold, the preset threshold ranges from 0 to 1, and in this embodiment, the preset threshold is 0.183. If the evaluation optimization function value... MF If the error exceeds the preset threshold, step S3 is repeated, and the random error parameter set is updated according to the swarm intelligence optimization algorithm; otherwise, the current error parameter is output as the error parameter of the resonant gyroscope component under test.

[0047] In this embodiment, the error parameters of the output resonant gyroscope component under test are shown in Table 2:

[0048]

[0049] Table 2: Error parameters of the output resonant gyroscope component under test

[0050] Based on the error parameters shown in Table 2 and the measured array data, simulation results versus measured data comparison charts for frequency splitting and principal axis azimuth angle are plotted, as follows: Picture 2 , Picture 3As shown in Table 2, the error parameters have a good match with the measured data. The resonant gyroscope error identification method based on variable DC bias voltage of this invention mainly aims to solve two types of error identification problems: fourth harmonic error due to inhomogeneity of the resonator mass and fourth harmonic error due to inhomogeneity of the resonator lip assembly gap. This provides data for the correction and compensation of resonant gyroscope errors and is of great significance for improving the assembly accuracy and performance of resonant gyroscopes. This invention establishes a simulation calculation function for resonant gyroscope error identification and combines it with a swarm intelligence optimization algorithm to identify the fourth harmonic error due to inhomogeneity of the mass and the fourth harmonic error due to inhomogeneity of the lip gap. This invention uses a swarm intelligence optimization algorithm for error parameter identification, resulting in a higher degree of automation and intelligence. After obtaining data on frequency splitting and principal axis azimuth angle under different high voltages, it can quickly achieve automated identification of error parameters, resulting in higher efficiency and greater versatility.

[0051] In step S2 of this embodiment, the simulation calculation function is shown in equation (2).

[0052]

[0053] In equation (2),

[0054]

[0055]

[0056]

[0057]

[0058]

[0059] in, ε The permittivity of the dielectric between the lip of the harmonic oscillator and the plate electrode is given. The density of the harmonic oscillator, Let be the Young's modulus of the harmonic oscillator. Let be the thickness of the resonator shell. Let be the radius of the mid-surface of the resonator shell. It is the reciprocal of the gap between the lip of the harmonic oscillator and the plate electrode.

[0060] In this embodiment, the fourth harmonic coefficient of mass azimuth angle of the fourth harmonic of mass The fourth harmonic coefficient of the gap and the fourth harmonic azimuth angle of the gap The range of values ​​for are as follows: The value range is 0 to 0.001. The value range is 0 to 0.1. and The value range is ±180°.

[0061] In this embodiment, the random error parameter group contains 100 columns of error parameters, each column of error parameters being composed of the fourth harmonic quality coefficient. azimuth angle of the fourth harmonic of mass The fourth harmonic coefficient of the gap and the fourth harmonic azimuth angle of the gap The system consists of four types of error parameters. In step S3, each error parameter in the random error parameter group is substituted into the simulation calculation function. In other embodiments, the random error parameter group contains at least 20 columns of error parameters.

[0062] In this embodiment, the swarm intelligence optimization algorithm used is the particle swarm optimization algorithm. In other embodiments, genetic algorithms or ant colony algorithms may also be used.

[0063] While the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the invention. Any person skilled in the art can make many possible variations and modifications to the technical solutions of the present invention, or modify them into equivalent embodiments, without departing from the scope of the present invention. Therefore, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention, without departing from the scope of the present invention, should fall within the protection scope of the present invention.

Claims

1. A method for identifying the error of a resonant gyroscope based on a variable DC bias voltage, characterized in that, Includes the following steps: S1: Data measurement, based on the resonant gyroscope component under test, settings n More than one different DC bias voltage U D ,and n The integers are greater than 2, and the frequency splitting Δ is measured under the corresponding DC bias voltage conditions. f and principal axis azimuth A set of DC bias voltage values ​​were obtained. U D1 , U D2 , … , U Dn } and the measured frequency splitting array corresponding to each DC bias voltage value { , ,···, } and the measured array of principal axis azimuth angles { , ,···, }; S2: Establish the simulation calculation function for resonant gyroscope error identification, based on a set of DC bias voltage values ​​obtained in step S1 { U D1 , U D2 , … , U Dn } and the fourth harmonic coefficient of mass azimuth angle of the fourth harmonic of mass The fourth harmonic coefficient of the gap and the fourth harmonic azimuth angle of the gap Four variables are used to establish the corresponding values ​​of the known DC bias voltage. n Frequency decomposition function { , ,···, }and n The frequency principal axis azimuth angle function { , ,···, }; S3: Simulation calculation, based on the fourth harmonic coefficient of mass. azimuth angle of the fourth harmonic of mass The fourth harmonic coefficient of the gap and the fourth harmonic azimuth angle of the gap Random values ​​are selected within the range of values ​​to obtain a random error parameter set. This random error parameter set is then substituted into the simulation calculation function established in step S2 to calculate the relationship between the DC bias voltage values ​​and the given values. U D1 , U D2 , … , U Dn The corresponding frequency splitting simulation array { , ,···, } and principal axis azimuth simulation array { , ,···, }; S4: Calculate the evaluation optimization function value MF The evaluation optimization function value is calculated based on equation (1). MF ; In equation (1), and These are the weighting factors; S5: Judgment, evaluate the optimization function value MF Whether it exceeds a preset threshold, if so, evaluate the optimization function value. MF If the error exceeds the preset threshold, step S3 is repeated, and the random error parameter set is updated according to the swarm intelligence optimization algorithm; otherwise, the current error parameter is output as the error parameter of the resonant gyroscope component under test.

2. The method for identifying resonant gyroscope errors based on variable DC bias voltage according to claim 1, characterized in that, In step S2, the simulation calculation function is shown in equation (2). In equation (2), in, ε The permittivity of the dielectric between the lip of the harmonic oscillator and the plate electrode is given. The density of the harmonic oscillator, Let be the Young's modulus of the harmonic oscillator. Let be the thickness of the resonator shell. Let be the radius of the mid-surface of the resonator shell. It is the reciprocal of the gap between the lip of the resonator and the plate electrode.

3. The method for identifying resonant gyroscope errors based on variable DC bias voltage according to claim 2, characterized in that, The mass fourth harmonic coefficient azimuth angle of the fourth harmonic of mass The fourth harmonic coefficient of the gap and the fourth harmonic azimuth angle of the gap The range of values ​​for are as follows: The value range is 0 to 0.

001. The value range is 0 to 0.

1. and The value range is ±180°.

4. The method for identifying resonant gyroscope errors based on variable DC bias voltage according to any one of claims 1 to 3, characterized in that, The random error parameter set contains at least 20 columns of error parameters, each column of error parameters being composed of the fourth harmonic quality coefficient. azimuth angle of the fourth harmonic of mass The fourth harmonic coefficient of the gap and the fourth harmonic azimuth angle of the gap The system consists of four error parameters. In step S3, the error parameters in the random error parameter group are substituted into the simulation calculation function column by column.

5. The method for identifying resonant gyroscope errors based on variable DC bias voltage according to any one of claims 1 to 3, characterized in that, The swarm intelligence optimization algorithm is a particle swarm optimization algorithm, a genetic algorithm, or an ant colony algorithm.

6. The method for identifying resonant gyroscope errors based on variable DC bias voltage according to any one of claims 1 to 3, characterized in that, The preset threshold value ranges from 0 to 1.

7. The method for identifying resonant gyroscope errors based on variable DC bias voltage according to any one of claims 1 to 3, characterized in that, The weighting factor and The values ​​range from 0.01 to 1000.

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