Inertial measurement unit modeling simulation method and system based on digital twinning

Abstract

The invention relates to a general control or regulation system, and discloses an inertial measurement unit modeling simulation method and system based on digital twinning. The method comprises the following steps: dividing an inertial measurement unit into six basic components, and constructing a digital twin model corresponding to each basic component in modeling software; importing the digital twin models corresponding to the basic components into a simulation platform library through modeling software; when the inertial measurement unit based on digital twinning performs modeling simulation work, initial parameters required by simulation analysis are provided through an input source, and a gyroscope and an accelerometer perform mathematical solution on the sensed parameters and the initial parameters respectively and then output corresponding gyroscope square wave signals and current signals; the current signal is converted into a voltage signal through the I / F conversion circuit, and the inner DSP circuit converts the collected gyroscope square wave signal and the voltage signal into a gyroscope pulse and an accelerometer pulse respectively and then sends the gyroscope pulse and the accelerometer pulse to the outer DSP circuit so as to convert and output a simulation result required by a user.

Description

Technical Field

[0001] The present invention relates to a general control or regulation system, and in particular to a modeling and simulation method and system of an inertial measurement unit based on digital twins. Background Art

[0002] Digital twin is a technical means to express physical entities with digital virtual entities, and use historical data, real-time data and algorithm models to simulate, verify, predict and control the entire life cycle of physical entities.

[0003] With the development of science and technology and weaponry, the device integration and functional diversity of inertial measurement units are becoming increasingly complex, and the time for research and development and production is gradually reduced, resulting in a sharp increase in the difficulty and economic cost of design, scheduling, testing, work, troubleshooting and maintenance. As computer performance becomes increasingly powerful, it has become possible to digitally model complex equipment, and the digital twin system has become a powerful direction for solving the above pain points. As the core component of the navigation control system, the inertial measurement unit can realize digital twins through modeling and simulation, which can significantly reduce the risks and operation and maintenance costs during production and use, and improve product reliability and production efficiency.

[0004] The inertial measurement unit is a navigation parameter solution system that uses gyroscopes and accelerometers as sensitive devices. It is an autonomous navigation system that does not rely on external information and does not radiate energy to the outside. Moreover, both gyroscopes and accelerometers are precision sensors, and it is difficult to replace physical models with digital virtual models. As a result, in the field of inertial measurement units, the application of digital modeling and related technologies in digital twins is relatively small, and there are no mature engineering modeling and simulation cases. Summary of the invention

[0005] The purpose of the present invention is to disclose a modeling and simulation method and system of an inertial measurement unit based on digital twins, so as to simplify the modeling process and ensure the reliability and scalability of the model.

[0006] To achieve the above-mentioned purpose, the inertial measurement unit modeling and simulation method based on digital twin disclosed in the present invention includes:

[0007] Step S1, dividing the inertial measurement unit into six basic components including input source, gyroscope, accelerometer, I / F conversion circuit, internal DSP circuit, and external DSP circuit, and constructing a digital twin model corresponding to each basic component in the modeling software;

[0008] Step S2: Import the digital twin models corresponding to each basic component into the simulation platform library through modeling software;

[0009] Step S3, modeling and simulation work is performed based on the inertial measurement unit of the digital twin; wherein, when the inertial measurement unit is working, the initial parameters required for the simulation analysis are first provided through the input source, and the initial parameters include latitude, gravity acceleration and three-axis attitude angle. The gyro performs mathematical calculations on the sensitive rotation angular velocity component and the initial parameters and then outputs a gyro square wave signal, and the accelerometer performs mathematical calculations on the sensitive earth rotation acceleration component and the initial parameters and then outputs a current signal, and the current signal is then converted into a voltage signal through the I / F conversion circuit, and then the internal DSP circuit converts the collected three-axis gyro square wave signal and voltage signal into gyro pulses and accelerometer pulses respectively and sends them to the external DSP circuit, and finally the external DSP circuit converts the acquired gyro pulses and accelerometer pulses and outputs the simulation results required by the user in the three-axis directions.

[0010] Preferably, the three-axis attitude angle is composed of azimuth angle α, pitch angle β, and roll angle γ. The attitude angle azimuth α is defined as positive clockwise, and the pitch angle β and roll angle γ are defined as positive counterclockwise. The attitude conversion matrix from the carrier coordinate system b based on the right front to the navigation coordinate system n based on the northeast sky is: as follows:

[0011]

[0012] The components of the Earth's rotational angular velocity that the gyroscope senses are as follows:

[0013]

[0014] The Earth's rotation acceleration components that the accelerometer is sensitive to are as follows:

[0015]

[0016] Where g is the local gravitational acceleration, ω ie is the angular velocity of the earth's rotation, Δt is the sampling time, L is the local latitude, f bx 、f by 、f bz are the acceleration components of the three axes in the b-coordinate system corresponding to each sampling time, ω bx ,ω by ,ω bz The components of the angular velocity corresponding to each sampling time in the three direction axes in the b coordinate system are output respectively.

[0017] Preferably, the process of modeling the gyroscope includes:

[0018] Through the theoretical sensitivity increment of the angular velocity channel and the inverse operation of error compensation, the theoretical output pulses of the gyroscope in the three-axis directions per Δt time are obtained as gyrox, gyroy and gyroz respectively, and the formula is as follows:

[0019]

[0020] Among them, E1x, E1y, and E1z are the scale factors of the gyro in the three-axis directions, Ezx, Eyx, Ezy, Exy, Eyz, and Exz are the gyro installation errors of the projection of the rear axis angular velocity on the front axis in the subscript, and D0x, D0y, and D0z represent the gyro zero bias in the three-axis directions respectively;

[0021] The error expression of the gyroscope is:

[0022] G x '=δ ωbx Δt+(Δ SFx Δt)gyrox+n0Δt+gyrox;

[0023] G y '=δ ωby Δt+(Δ SFy Δt)gyroy+n0Δt+gyroy;

[0024] G z '=δ ωbz Δt+(Δ SFz Δt)gyroz+n0Δt+gyroz;

[0025] G x ', G y ', G z ' are the pulses with errors corresponding to each sampling time in the three-axis direction, n0 is the random noise error, Δ SFx , Δ SFy , Δ SFz are the scale errors in the three-axis directions, δ ωbx , δ ωby , δ ωbz They are the zero bias errors in the three-axis directions, and the zero bias errors in each direction include the residual temperature sensitive item, the magnetic sensitive item and the constant part; the scale error in each direction includes the constant part and the linear change part related to the input.

[0026] Preferably, the random noise is white noise, and the bias error is taken as a constant value.

[0027] Preferably, in the process of modeling the accelerometer, the accelerometer is equivalent to a linear model related to gravity acceleration, specifically:

[0028] f = A × g × I;

[0029] Where f is the input angular acceleration increment corresponding to each sampling time, A is the proportional coefficient, and I is the current.

[0030] Preferably, in the process of modeling the I / F conversion circuit, the I / F conversion circuit is equivalent to an integration circuit, and the input current is integrated to obtain the integrated voltage, and the formula is as follows:

[0031]

[0032] Among them, K is the time constant, C is the charging and discharging capacitance, and U is the voltage.

[0033] Preferably, the process of modeling the internal DSP circuit includes:

[0034] The gyro shake signal is regarded as a sinusoidal pulse signal with relatively fixed frequency and value, and the gyro shake signal is added to the gyro pulse signal. The calculation formula is:

[0035] G = G' + J*sin(2πW*T);

[0036] Where G is the gyro pulse in each sampling period after adding jitter, G′ is the gyro output pulse in each sampling period, J is the jitter amplitude, W is the jitter frequency, and T is the running time;

[0037] At the same time, the pulse calculation model is equivalent to:

[0038]

[0039] Among them, N is the meter pulse corresponding to each sampling period, U0 is the charge and discharge voltage, B is the multiplier related to the charge and discharge capacitance value, if0 is the meter zero bias, It is the whole machine magnification.

[0040] Preferably, in the process of modeling the external DSP circuit, the 2K synchronization signal is accumulated into a 10ms synchronization signal and then output as incremental data, which specifically includes:

[0041] Step A: Use FIR filter to filter out the high-frequency gyro jitter signal and retain the low-frequency effective angular velocity signal. The digital filtering formula is as follows:

[0042] y k =b0x k +b1x k-1 +b2x k-2 +...+b n x k-n ;

[0043] Among them, x k 、x k-1 、x k-2 ...x k-n are the gyro and adder pulses at time k, k-1, k-2…kn respectively; correspondingly, y kis the pulse after gyro and table filtering at time k; b0, b1, b2...b n is the filter parameter;

[0044] Step B: Perform targeted notching on the gyro jitter signal. The notch filter design formula is as follows:

[0045] y′ k = b0x′ k +b1x′ k-1 +b2x′ k-2 -a1y′ k-1 -a2y′ k-2 ;

[0046] x′ k , x′ k-1 , x′ k-2 are the pulses after gyro filtering at time k, k-1, and k-2 respectively; y′ k , y′ k-1 , y′ k-2 are the gyro notch post-pulses at time k, k-1, and k-2 respectively; a1 and a2 are notch filter parameters;

[0047] Step C: Dynamic error compensation processing

[0048] The pulses of the gyro and accelerometer after k notch at a certain moment are gyrox k ,gyroy k ,gyroz k , accx k ,accy k ,accz k , the accelerometer pulse symmetry is used for compensation, and the compensation method is as follows:

[0049]

[0050] Among them, K2x, K2y, and K2z are the calibrated quadratic terms;

[0051] According to the calibration parameters, the error compensation is performed according to the following formula to obtain the compensated 2k angular increment ω k and speed increment a k :

[0052]

[0053]

[0054] Among them, ω xk ,ω yk ,ω zk is the angle increment every 10ms, a xk 、a yk、a zk is the speed increment every 10 ms, K1x, K1y, K1z are the calibrated primary items, Kzx, Kyx, Kzy, Kxy, Kyz, Kxz are the installation errors of the angular velocity of the rear axle projected on the front axle in the subscript respectively.

[0055] Preferably, the modeling software adopts mWorks modeling software.

[0056] To achieve the above objectives, the present invention also discloses an inertial measurement unit modeling and simulation system based on digital twins, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above method when executing the computer program.

[0057] The present invention has the following beneficial effects:

[0058] 1. The digital decomposition of the inertial measurement unit has been completed, and the physical model has been digitally modeled based on the actual situation of engineering applications, realizing the function and performance simulation of the digital model for the physical entity, and achieving the equivalent consistency between the digital model and the physical entity.

[0059] 2. It can be used to reflect the properties, functions, performance and comprehensive coverage testing capabilities of the physical product of the inertial measurement unit in the real environment, and can modify and repeatedly optimize the product design in real time based on the simulation results, shortening the R&D cycle and reducing R&D costs.

[0060] 3. Through digital twin technology, a digital model of the inertial measurement unit can be established. By using digital models, sensor updates, operation history and other data, multi-disciplinary, multi-physical quantity, multi-scale, and multi-probability simulation processes can be integrated to complete mapping in the virtual space, and the twin equipment can be driven to run synchronously with the physical equipment. The data and parameters of the equipment operation can be comprehensively and truly collected and recorded, and the large amount of data output can be used to predict faults or provide a reference for product maintenance.

[0061] 4. Inertial measurement unit is a kind of precision electromechanical equipment with extremely high requirements for mission success rate. Testing is an important part of its production calibration process. However, due to the complex mission environment profile of the inertial measurement unit and factors such as mission nodes and resource limitations, various faults often occur in the product during use due to incomplete test coverage. By making good use of the information fusion of the physical and digital domains using digital twin technology and running simulation programs based on the computer's mathematical model, the limitations caused by insufficient allocation of time, space and other resources can be avoided to the greatest extent, and the experimental test status of the twin entity can be predicted or reproduced on the digital twin model, maximizing test coverage at the system level.

[0062] 5. The modeling method of the six basic components can be extended and applied to other types of basic components and system expansions. It has strong transplantation capabilities and wide applicability, can meet different needs, and bring more efficient and convenient digital twin solutions to the entire industry.

[0063] The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The drawings constituting a part of this application are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0065] Figure 1 It is a schematic diagram of the composition of the mathematical twin model of the inertial measurement unit disclosed in an embodiment of the present invention.

[0066] Figure 2 It is a schematic flow chart of the inertial measurement unit modeling and simulation method based on digital twin disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0067] The embodiments of the present invention are described in detail below with reference to the accompanying drawings, but the present invention can be implemented in many different ways as defined and covered by the claims.

[0068] Example 1

[0069] This embodiment discloses a modeling and simulation method of an inertial measurement unit based on digital twins, such as Figure 1 As shown, the schematic diagram of the inertial measurement unit model based on digital twins in the embodiment of the present invention is as follows Figure 1 As shown, it is divided into six parts, including input source, gyroscope, accelerometer, I / F conversion circuit, internal DSP circuit and external DSP circuit.

[0070] When the inertial measurement unit is working, it first provides the initial parameters required for simulation analysis through the input source. The initial parameters include latitude, gravity acceleration and three-axis attitude angle. The initial parameters are mathematically solved with the signals sensed by the gyroscope and accelerometer. The gyroscope outputs a gyro signal and the accelerometer outputs a current signal. The current signal is converted into a voltage signal through the I / F conversion circuit. The internal DSP circuit then performs signal acquisition and converts the voltage signal into a gyroscope pulse and an accelerometer pulse, which are sent to the external DSP circuit. Finally, the external DSP circuit obtains the gyroscope pulse and the accelerometer pulse, and outputs the final simulation result after processing.

[0071] The following are the specific steps of modeling and simulation of the present invention:

[0072] Step 1: Input Source Modeling

[0073] One of the key initial conditions for the inertial measurement unit based on the digital twin model to simulate the real physical process of inertial navigation is to determine the initial position information through initial parameters. The input source provides the initial parameters for simulation analysis and calculation as input information for simulating inertial navigation. Among them, the initial parameters include latitude, gravity acceleration and three-axis attitude angle, which is specifically composed of azimuth angle α, pitch angle β and roll angle γ.

[0074] Define the attitude angle α as positive clockwise, the pitch angle β and the roll angle γ (positive counterclockwise), and the attitude conversion matrix from the carrier coordinate system b (right front upper) to the navigation coordinate system n (northeast sky) is as follows:

[0075]

[0076] The definitions of the navigation coordinate system and the carrier coordinate system and the conversion between them are common sense in engineering applications and will not be elaborated on here. The angular velocity components of the earth's rotation sensed by the gyroscope are as follows:

[0077]

[0078] The Earth's rotation acceleration components that the accelerometer is sensitive to are as follows:

[0079]

[0080] In the above formula, g is the local gravitational acceleration, ω is ie is the angular velocity of the earth's rotation, Δt is the sampling time, L is the local latitude, f bx 、f by 、f bz are the acceleration components of the three axes in the b-coordinate system corresponding to each sampling time, ω bx ,ω by ,ω bz The components of the angular velocity corresponding to each sampling time in the three direction axes in the b coordinate system are output respectively.

[0081] Step 2: Modeling the Gyro

[0082] Through the theoretical sensitivity increment of the angular velocity channel and the inverse operation of error compensation, the theoretical output pulses of the gyroscope in the three-axis directions per Δt time are obtained as gyrox, gyroy and gyroz respectively, and the formula is as follows:

[0083]

[0084] Among them, E1x, E1y, and E1z are the scale factors of the gyro in the three-axis directions, Ezx, Eyx, Ezy, Exy, Eyz, and Exz are the gyro installation errors of the projection of the rear axle angular velocity on the front axle in the subscripts, and D0x, D0y, and D0z represent the gyro zero bias in the three-axis directions, respectively.

[0085] The error expression of the gyroscope is:

[0086] G x '=δ ωbx Δt+(Δ SFx Δt)gyrox+n0Δt+gyrox;

[0087] G y '=δ ωby Δt+(Δ SFy Δt)gyroy+n0Δt+gyroy;

[0088] G z '=δ ωbz Δt+(Δ SFz Δt)gyroz+n0Δt+gyroz;

[0089] G x ', G y ', G z ' are the pulses with errors corresponding to each sampling time in the three-axis direction, n0 is the random noise error, Δ SFx , Δ SFy , Δ SFz are the scale errors in the three-axis directions, δ ωbx , δ ωby , δ ωbz They are the zero bias errors in the three-axis directions, and the zero bias errors in each direction include the residual temperature sensitive item, the magnetic sensitive item and the constant part; the scale error in each direction includes the constant part and the linear change part related to the input.

[0090] Based on the long-term research of the applicant in this case, it is found that random noise is white noise and the bias error is taken as a constant. Therefore, the error parameters are identified by the least square method to obtain the error parameters of the gyroscope. The formula can be used to achieve accurate digital modeling of the gyroscope that meets the requirements of engineering use.

[0091] Step 3: Accelerometer Modeling

[0092] In the process of modeling the accelerometer, the applicant of this case summarized and found that the error parameters of the accelerometer can be obtained by using the least square method to identify the above error parameters based on a large amount of accelerometer test data used in multiple projects. The formula can be used to achieve accurate digital modeling of the accelerometer that meets the needs of engineering use; that is, the accelerometer is equivalent to a linear model related to gravity acceleration, specifically:

[0093] f = A × g × I;

[0094] Where f is the input angular acceleration increment corresponding to each sampling time, A is the proportional coefficient, and I is the current.

[0095] Step 4: I / F conversion circuit modeling

[0096] The applicant of this case has studied the I / F conversion circuit principle and test data and concluded that the I / F conversion circuit can be equivalent to an integration circuit, which integrates the input current to obtain the integrated voltage. The formula is as follows:

[0097]

[0098] Among them, K is the time constant, C is the charging and discharging capacitance, and U is the voltage.

[0099] Step 5: Internal DSP Circuit Modeling

[0100] The internal DSP circuit mainly adds a machine jitter signal to the gyro pulse to make the gyro pulse closer to the real laser gyro output; at the same time, the voltage after IF conversion is calculated to obtain the added pulse value.

[0101] Step 5.1: Machine jitter signal model

[0102] The gyro jitter signal is a sinusoidal pulse signal with relatively fixed frequency and value. The formula for adding the jitter signal to the gyro pulse signal is as follows:

[0103] G = G' + J*sin(2πW*T);

[0104] Wherein, G is the gyro pulse of each sampling period after adding jitter, G′ is the gyro output pulse of each sampling period, J is the jitter amplitude, W is the jitter frequency, and T is the running time.

[0105] Step 5.2: Equivalently convert the pulse calculation model of the meter to:

[0106]

[0107] Among them, N is the meter pulse corresponding to each sampling period, U0 is the charge and discharge voltage, B is the multiplier related to the charge and discharge capacitance value, if0 is the meter zero bias, It is the whole machine magnification.

[0108] Step 6: External DSP circuit modeling

[0109] Preferably, the external DSP circuit mainly filters the gyro and accelerometer pulses, performs gyro pulse notching and dynamic error compensation, and outputs a simulation output result accumulated to 10ms.

[0110] Step 6.1: Filtering

[0111] Multi-order filtering mainly uses FIR filters to filter out the high-frequency gyro jitter signal and retain the low-frequency effective angular velocity signal. The digital filtering formula is as follows:

[0112] y k =b0x k +b1x k-1 +b2x k-2 +...+b n x k-n ;

[0113] Among them, x k 、x k-1 、x k-2 ...x k-n are the gyro and adder pulses at time k, k-1, k-2…kn respectively; correspondingly, y k is the pulse after gyro and table filtering at time k; b0, b1, b2...b n are the filter parameters.

[0114] Step 6.2: Perform targeted notching on the gyro jitter signal. The notch filter design formula is as follows:

[0115] y k ′=b0x′ k +b1x′ k-1 +b2x′ k-2 -a1y′ k-1 -a2y′ k-2 ;

[0116] x′ k , x′ k-1 , x′ k-2 are the pulses after gyro filtering at time k, k-1, and k-2 respectively; y′ k , y′ k-1 , y′ k-2 are the gyro notch post-pulses at time k, k-1, and k-2 respectively; a1 and a2 are notch filter parameters.

[0117] Step 6.3: Dynamic error compensation processing

[0118] The pulses of the gyro and accelerometer after k notch at a certain moment are gyroxk ,gyroy k ,gyroz k , accx k ,accy k ,accz k , the accelerometer pulse symmetry is used for compensation, and the compensation method is as follows:

[0119]

[0120] Among them, K2x, K2y, and K2z are calibrated additive quadratic terms.

[0121] According to the calibration parameters, the error compensation is performed according to the following formula to obtain the compensated 2k angular increment ω k and speed increment a k :

[0122]

[0123]

[0124] Among them, ω xk ,ω yk ,ω zk is the angle increment every 10ms, a xk 、a yk 、a zk is the speed increment every 10 ms, K1x, K1y, K1z are the calibrated primary items, Kzx, Kyx, Kzy, Kxy, Kyz, Kxz are the installation errors of the angular velocity of the rear axle projected on the front axle in the subscript respectively.

[0125] In the above steps, the so-called "increment" refers to the change in the current accumulated period compared with the previous period; in different application scenarios,

[0126] Step 7: Model storage

[0127] First, create a blank model file of the basic component in mWorks and design the corresponding graphical interface of the component. Then, based on the aforementioned mathematical model conversion in the model file, implement the basic functions of each component by writing program code. Finally, set parameters according to the actual component to build the digital twin model corresponding to the actual component.

[0128] After the digital twin model of the six basic components of the inertial measurement unit is built, it can be imported into the simulation platform library through the modeling software mWorks. mWorks modeling software is a digital twin simulation tool widely recognized and used in the field of engineering modeling. It allows modelers to use simple program codes to implement tedious mathematical derivations, which helps engineering designers focus on the physical system itself, simplifies the digital modeling process, and improves the efficiency of digital twin modeling.

[0129] After all the above steps, the modeling and simulation of the inertial measurement unit based on digital twins can be completed.

[0130] In summary, the method of this embodiment can be summarized as follows: Figure 2 The following core steps are shown, which include:

[0131] Step S1, divide the inertial measurement unit into six basic components including input source, gyroscope, accelerometer, I / F conversion circuit, internal DSP circuit, and external DSP circuit, and build a digital twin model corresponding to each basic component in the modeling software.

[0132] Step S2: Import the digital twin models corresponding to each basic component into the simulation platform library through modeling software.

[0133] Step S3, modeling and simulation work is performed based on the inertial measurement unit of the digital twin; wherein, when the inertial measurement unit is working, the initial parameters required for the simulation analysis are first provided through the input source, and the initial parameters include latitude, gravity acceleration and three-axis attitude angle. The gyro performs mathematical calculations on the sensitive rotation angular velocity component and the initial parameters and then outputs a gyro square wave signal, and the accelerometer performs mathematical calculations on the sensitive earth rotation acceleration component and the initial parameters and then outputs a current signal, and the current signal is then converted into a voltage signal through the I / F conversion circuit, and then the internal DSP circuit converts the collected three-axis gyro square wave signal and voltage signal into gyro pulses and accelerometer pulses respectively and sends them to the external DSP circuit, and finally the external DSP circuit converts the acquired gyro pulses and accelerometer pulses and outputs the simulation results required by the user in the three-axis directions.

[0134] Example 2

[0135] Corresponding to Example 1, this embodiment discloses an inertial measurement unit modeling and simulation system based on digital twins, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the above embodiment when executing the computer program.

[0136] In summary, the inertial measurement unit modeling and simulation method and system based on digital twin disclosed in the embodiments of the present invention have at least the following beneficial effects:

[0137] 1. The digital decomposition of the inertial measurement unit has been completed, and the physical model has been digitally modeled based on the actual situation of engineering applications, realizing the function and performance simulation of the digital model for the physical entity, and achieving the equivalent consistency between the digital model and the physical entity.

[0138] 2. It can be used to reflect the properties, functions, performance and comprehensive coverage testing capabilities of the physical product of the inertial measurement unit in the real environment, and can modify and repeatedly optimize the product design in real time based on the simulation results, shortening the R&D cycle and reducing R&D costs.

[0139] 3. Through digital twin technology, a digital model of the inertial measurement unit can be established. By using digital models, sensor updates, operation history and other data, multi-disciplinary, multi-physical quantity, multi-scale, and multi-probability simulation processes can be integrated to complete mapping in the virtual space, and the twin equipment can be driven to run synchronously with the physical equipment. The data and parameters of the equipment operation can be comprehensively and truly collected and recorded, and the large amount of data output can be used to predict faults or provide a reference for product maintenance.

[0140] 4. Inertial measurement unit is a kind of precision electromechanical equipment with extremely high requirements for mission success rate. Testing is an important part of its production calibration process. However, due to the complex mission environment profile of the inertial measurement unit and factors such as mission nodes and resource limitations, various faults often occur in the product during use due to incomplete test coverage. By making good use of the information fusion of the physical and digital domains using digital twin technology and running simulation programs based on the computer's mathematical model, the limitations caused by insufficient allocation of time, space and other resources can be avoided to the greatest extent, and the experimental test status of the twin entity can be predicted or reproduced on the digital twin model, maximizing test coverage at the system level.

[0141] 5. The modeling method of the six basic components can be extended and applied to other types of basic components and system expansions. It has strong transplantation capabilities and wide applicability, can meet different needs, and bring more efficient and convenient digital twin solutions to the entire industry.

[0142] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A modeling and simulation method of an inertial measurement unit based on digital twins, characterized in that: include: Step S1, dividing the inertial measurement unit into six basic components including input source, gyroscope, accelerometer, I / F conversion circuit, internal DSP circuit, and external DSP circuit, and constructing a digital twin model corresponding to each basic component in the modeling software; Step S2: Import the digital twin models corresponding to each basic component into the simulation platform library through modeling software; Step S3, modeling and simulation work is performed based on the inertial measurement unit of the digital twin; wherein, when the inertial measurement unit is working, the initial parameters required for the simulation analysis are first provided through the input source, and the initial parameters include latitude, gravity acceleration and three-axis attitude angle. The gyro performs mathematical calculations on the sensitive rotation angular velocity component and the initial parameters and then outputs a gyro square wave signal, and the accelerometer performs mathematical calculations on the sensitive earth rotation acceleration component and the initial parameters and then outputs a current signal, and the current signal is then converted into a voltage signal through the I / F conversion circuit, and then the internal DSP circuit converts the collected three-axis gyro square wave signal and voltage signal into gyro pulses and accelerometer pulses respectively and sends them to the external DSP circuit, and finally the external DSP circuit converts the acquired gyro pulses and accelerometer pulses and outputs the simulation results required by the user in the three-axis directions.

2. The method according to claim 1, characterized in that The three-axis attitude angle is composed of azimuth angle α, pitch angle β, and roll angle γ. The attitude angle azimuth α is defined as positive clockwise, and the pitch angle β and roll angle γ are positive counterclockwise. The attitude conversion matrix from the carrier coordinate system b based on the right front to the navigation coordinate system n based on the northeast sky is as follows: The components of the Earth's rotational angular velocity that the gyroscope senses are as follows: The Earth's rotation acceleration components that the accelerometer is sensitive to are as follows: Where g is the local gravitational acceleration, ω ie is the angular velocity of the earth's rotation, Δt is the sampling time, L is the local latitude, f bx 、f by 、f bz are the acceleration components of the three axes in the b-coordinate system corresponding to each sampling time, ω bx ,ω by ,ω bz The components of the angular velocity corresponding to each sampling time in the three direction axes in the b coordinate system are output respectively.

3. The method according to claim 2, characterized in that The process of modeling the gyroscope includes: Through the theoretical sensitivity increment of the angular velocity channel and the inverse operation of error compensation, the theoretical output pulses of the gyroscope in the three-axis directions per Δt time are obtained as gyrox, gyroy and gyroz respectively, and the formula is as follows: Among them, E1x, E1y, and E1z are the scale factors of the gyro in the three-axis directions, Ezx, Eyx, Ezy, Exy, Eyz, and Exz are the gyro installation errors of the projection of the rear axis angular velocity on the front axis in the subscript, and D0x, D0y, and D0z represent the gyro zero bias in the three-axis directions respectively; The error expression of the gyroscope is: G x '=d ωbx Δt+(Δ SFx Δt)gyrox+n0Δt+gyrox; G y '=d ωby Δt+(Δ SFy Δt)gyroy+n0Δt+gyroy; G z '=d ωbz Δt+(Δ SFz Δt)gyro+n0Δt+gyro; G x ', G y ', G z ' are the pulses with errors corresponding to each sampling time in the three-axis direction, n0 is the random noise error, Δ SFx , Δ SFy , Δ SFz are the scale errors in the three-axis directions, δ ωbx , δ ωby , δ ωbz They are the zero bias errors in the three-axis directions, and the zero bias errors in each direction include the residual temperature sensitive item, the magnetic sensitive item and the constant part; the scale error in each direction includes the constant part and the linear change part related to the input.

4. The method according to claim 3, characterized in that The random noise is white noise and the bias error is taken as a constant.

5. The method according to claim 3 or 4, characterized in that: In the process of modeling the accelerometer, the accelerometer is equivalent to a linear model related to gravity acceleration, specifically: f = A × g × I; Where f is the input angular acceleration increment corresponding to each sampling time, A is the proportional coefficient, and I is the current.

6. The method according to claim 5, characterized in that In the process of modeling the I / F conversion circuit, the I / F conversion circuit is equivalent to an integration circuit, and the input current is integrated to obtain the integrated voltage. The formula is as follows: Among them, K is the time constant, C is the charging and discharging capacitance, and U is the voltage.

7. The method according to claim 6, characterized in that The process of modeling the internal DSP circuit includes: The gyro shake signal is regarded as a sinusoidal pulse signal with relatively fixed frequency and value, and the gyro shake signal is added to the gyro pulse signal. The calculation formula is: G = G' + J*sin(2πW*T); Where G is the gyro pulse in each sampling period after adding jitter, G′ is the gyro output pulse in each sampling period, J is the jitter amplitude, W is the jitter frequency, and T is the running time; At the same time, the pulse calculation model is equivalent to: Among them, N is the meter pulse corresponding to each sampling period, U0 is the charge and discharge voltage, B is the multiplier related to the charge and discharge capacitance value, if0 is the meter zero bias, It is the whole machine magnification.

8. The method according to claim 7, characterized in that In the process of external DSP circuit modeling, the 2K synchronization signal is accumulated into a 10ms synchronization signal and then output as incremental data, including: Step A: Use FIR filter to filter out the high-frequency gyro jitter signal and retain the low-frequency effective angular velocity signal. The digital filtering formula is as follows: y k =b0x k +b1x k-1 +b2x k-2 +...+b n x k-n ; Among them, x k 、x k-1 、x k-2 ...x k-n are the gyro and adder pulses at time k, k-1, k-2…kn respectively; correspondingly, y k is the pulse after gyro and table filtering at time k; b0, b1, b2...b n is the filter parameter; Step B: Perform targeted notching on the gyro jitter signal. The notch filter design formula is as follows: y′ k =b0x′ k +b1x′ k-1 +b2x′ k-2 -a1y′ k-1 -a2y′ k-2 ; x′ k , x′ k-1 , x′ k-2 are the pulses after gyro filtering at time k, k-1, and k-2 respectively; y′ k , y′ k-1 , y′ k-2 are the gyro notch post-pulses at time k, k-1, and k-2 respectively; a1 and a2 are notch filter parameters; Step C: Dynamic error compensation processing The pulses of the gyro and accelerometer after k notch at a certain moment are gyrox k ,gyroy k ,gyroz k , accx k ,accy k , accz k , the accelerometer pulse symmetry is used for compensation, and the compensation method is as follows: Among them, K2x, K2y, and K2z are the calibrated quadratic terms; According to the calibration parameters, the error compensation is performed according to the following formula to obtain the compensated 2k angular increment ω k and speed increment a k : Among them, ω xk ,ω yk ,ω zk is the angle increment every 10ms, a xk 、a yk 、a zk is the speed increment every 10 ms, K1x, K1y, K1z are the calibrated primary items, Kzx, Kyx, Kzy, Kxy, Kyz, Kxz are the installation errors of the angular velocity of the rear axle projected on the front axle in the subscript respectively.

9. The method according to claim 1, characterized in that: The modeling software adopts mWorks modeling software.

10. An inertial measurement unit modeling and simulation system based on digital twins, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 9 is implemented.

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