Wide-range accelerometer linearity calibration method based on high-speed centrifuge

Abstract

The application relates to a large-range accelerometer linearity calibration method based on a high-speed centrifuge, which comprises the following steps: performing a multi-rotation speed excitation gradient experiment on a first-range accelerometer to obtain first-range gradient experiment data, wherein the first-range accelerometer is installed on the centrifuge; optimizing a weighted radius and a radius weight value of the centrifuge according to the first-range gradient experiment data, and optimizing a centrifuge rotation speed polynomial model according to the optimized weighted radius; performing a multi-rotation speed excitation gradient experiment on a second-range accelerometer to obtain second-range gradient experiment data, and calculating the linearity of the second-range accelerometer according to the optimized radius weight value of the centrifuge, the centrifuge rotation speed polynomial model and the second-range gradient experiment data, wherein the range of the first-range accelerometer is larger than that of the second-range accelerometer. Thus, the problem that the existing accelerometer calibration method cannot perform full-range excitation on a large-range accelerometer and is not conducive to the accurate evaluation of the linearity index is solved.

Description

Technical Field

[0001] This application relates to the field of large-range accelerometer calibration technology, and in particular to a method for linearity calibration of large-range accelerometers based on a high-speed centrifuge. Background Technology

[0002] Accelerometers are widely used in inertial navigation, vibration monitoring, and attitude control, and their output linearity directly affects the measurement accuracy of the system. With the development of technologies such as high-speed aircraft and heavy-duty equipment, the demand for large-range accelerometers with a range exceeding 200G is becoming increasingly urgent. Before they are put into use, linearity calibration must be performed across the entire range to accurately assess the nonlinear deviation between the output and the actual input.

[0003] Existing accelerometer calibration methods are typically based on precision centrifuges. However, due to the centrifuge's own rotational speed and structure, the maximum output acceleration is usually limited to no more than 100G, making it impossible to provide full-scale excitation for accelerometers with ranges exceeding 200G. Hopkinson bars and air cannons generally generate excitations exceeding 5000G, making it difficult to produce precise and controllable quasi-static excitations within the 200G to 1000G range. Furthermore, the pulse duration is extremely short, failing to provide steady-state reading conditions and hindering the accurate evaluation of linearity indicators.

[0004] Therefore, there is an urgent need for a method that can break through the 100G range bottleneck of traditional centrifuges and perform high-precision linearity calibration of accelerometers with ranges of 200G or more under ordinary laboratory conditions. Summary of the Invention

[0005] This application provides a linearity calibration method for large-range accelerometers based on a high-speed centrifuge, in order to solve the problem that existing accelerometer calibration methods cannot perform full-scale excitation on accelerometers with a range of 200G or more, which is not conducive to the accurate evaluation of linearity indicators.

[0006] The first aspect of this application provides a method for linearity calibration of a large-range accelerometer based on a high-speed centrifuge, comprising the following steps: performing a multi-speed excitation gradient experiment on a first-range accelerometer to obtain first-range gradient experimental data, wherein the first-range accelerometer is mounted on a centrifuge rotor; optimizing the weighted radius and radius weight value of the centrifuge based on the first-range gradient experimental data, and optimizing the centrifuge speed polynomial model based on the optimized weighted radius; after removing the first-range accelerometer from the centrifuge and mounting a second-range accelerometer on the centrifuge rotor, performing a multi-speed excitation gradient experiment on the second-range accelerometer to obtain second-range gradient experimental data; calculating the linearity of the second-range accelerometer based on the optimized centrifuge radius weight value, the optimized centrifuge speed polynomial model, and the second-range gradient experimental data, wherein the range of the first-range accelerometer is greater than the range of the second-range accelerometer.

[0007] A second aspect of this application provides a linearity calibration device for a large-range accelerometer based on a high-speed centrifuge, comprising: an experimental data acquisition module for performing multi-speed excitation gradient experiments on a first-range accelerometer to obtain first-range gradient experimental data, wherein the first-range accelerometer is mounted on a centrifuge rotor; an optimization module for optimizing the weighted radius and radius weight value of the centrifuge based on the first-range gradient experimental data, and optimizing the centrifuge speed polynomial model based on the optimized weighted radius; and a calculation module for, after removing the first-range accelerometer from the centrifuge and mounting a second-range accelerometer on the centrifuge rotor, performing multi-speed excitation gradient experiments on the second-range accelerometer to obtain second-range gradient experimental data, and calculating the linearity of the second-range accelerometer based on the optimized centrifuge radius weight value, the optimized centrifuge speed polynomial model, and the second-range gradient experimental data, wherein the range of the first-range accelerometer is greater than the range of the second-range accelerometer.

[0008] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the program to implement the linearity calibration method for a large-range accelerometer based on a high-speed centrifuge as described in the above embodiments.

[0009] In the above embodiments, a multi-speed excitation gradient experiment is performed on the first-range accelerometer to obtain first-range gradient experimental data, wherein the first-range accelerometer is installed on the centrifuge rotor; the weighted radius and radius weight value of the centrifuge are optimized based on the first-range gradient experimental data, and the centrifuge speed polynomial model is optimized based on the optimized weighted radius; after removing the first-range accelerometer from the centrifuge and installing the second-range accelerometer on the centrifuge rotor, a multi-speed excitation gradient experiment is performed on the second-range accelerometer to obtain second-range gradient experimental data; the linearity of the second-range accelerometer is calculated based on the optimized centrifuge radius weight value, the optimized centrifuge speed polynomial model, and the second-range gradient experimental data, wherein the range of the first-range accelerometer is greater than the range of the second-range accelerometer. This solves the problem that existing accelerometer calibration methods cannot provide full-scale excitation for accelerometers with a range of 200G or more, which is not conducive to the accurate evaluation of linearity. By using a general-purpose high-speed centrifuge to generate a large-range excitation of 200G or more, high-precision calibration of the linearity of large-range accelerometers can be achieved under ordinary laboratory conditions.

[0010] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0011] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart illustrating a method for linearity calibration of a large-range accelerometer based on a high-speed centrifuge, according to an embodiment of this application. Figure 2 This is a flowchart of a large-range accelerometer linearity calibration method based on a high-speed centrifuge, according to an embodiment of this application. Figure 3 This is a schematic diagram comparing the set speed and the corrected speed of a centrifuge according to an embodiment of this application; Figure 4 A linear fitting graph of the linearity of the second-range accelerometer provided according to the embodiments of this application; Figure 5 This is an example diagram of a large-range accelerometer linearity calibration device based on a high-speed centrifuge according to an embodiment of this application; Figure 6 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0012] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0013] The linearity calibration method for a large-range accelerometer based on a high-speed centrifuge, according to an embodiment of this application, is described below with reference to the accompanying drawings. To address the problem mentioned in the background art that existing accelerometer calibration methods cannot perform full-scale excitation on accelerometers with ranges above 200G, which is detrimental to the accurate evaluation of linearity indicators, this application provides a linearity calibration method for large-range accelerometers based on a high-speed centrifuge. In this method, a multi-speed excitation gradient experiment is performed on a first-range accelerometer to obtain first-range gradient experimental data, wherein the first-range accelerometer is mounted on the centrifuge rotor. The weighted radius and radius weight value of the centrifuge are optimized based on the first-range gradient experimental data, and the centrifuge speed polynomial model is optimized based on the optimized weighted radius. After removing the first-range accelerometer from the centrifuge and installing a second-range accelerometer on the centrifuge rotor, a multi-speed excitation gradient experiment is performed on the second-range accelerometer to obtain second-range gradient experimental data. The linearity of the second-range accelerometer is calculated based on the optimized centrifuge radius weight value, the optimized centrifuge speed polynomial model, and the second-range gradient experimental data, wherein the range of the first-range accelerometer is greater than the range of the second-range accelerometer. This solves the problem that existing accelerometer calibration methods cannot provide full-scale excitation for accelerometers with a range of 200G or more, which is not conducive to the accurate evaluation of linearity. By using a general-purpose high-speed centrifuge to generate a large-range excitation of 200G or more, high-precision calibration of the linearity of large-range accelerometers can be achieved under ordinary laboratory conditions.

[0014] Specifically, Figure 1 This is a flowchart illustrating a method for linearity calibration of a large-range accelerometer based on a high-speed centrifuge, provided in an embodiment of this application.

[0015] like Figure 1 As shown, the linearity calibration method for a large-range accelerometer based on a high-speed centrifuge includes the following steps: In step S101, a multi-speed excitation gradient experiment is performed on the first-range accelerometer to obtain the first-range gradient experimental data. The first-range accelerometer is installed on the centrifuge rotor.

[0016] In some embodiments, a multi-speed gradient excitation experiment is performed on a first-range accelerometer to obtain first-range gradient experimental data, including: determining the estimated working radius and target excitation acceleration of the centrifuge; calculating the speed gradient of the centrifuge in the first-range accelerometer experiment based on the estimated working radius and target excitation acceleration of the centrifuge according to the centripetal acceleration formula; controlling the centrifuge to operate according to the speed gradient of the centrifuge in the first-range accelerometer experiment, and collecting the output data of the first-range accelerometer under each speed gradient to obtain the first-range gradient experimental data.

[0017] Specifically, a high-speed centrifuge calibration device is first set up, and the first-range accelerometer is installed on the rotor of the centrifuge. The output data of the first-range accelerometer is remotely read and saved through wireless data transmission.

[0018] The battery module and wireless module are fixed in the rotor of a high-speed centrifuge, and the wiring allows the battery module to power both the wireless module and the first-range accelerometer simultaneously.

[0019] Further gravity field experiments were conducted on the first-range accelerometer to collect its output under ±1G conditions, obtain the scaling factor of the first-range accelerometer, and convert the output signal of the first-range accelerometer into an acceleration signal based on the scaling factor.

[0020] The centrifuge speed gradient corresponding to the first range accelerometer is determined as follows: based on the estimated working radius of the centrifuge, the required centrifuge speed is calculated from the target excitation acceleration according to the centripetal acceleration formula, and a set of numerically increasing gradients is designed accordingly. n The centrifuge speed gradient is defined by several rotational speeds, serving as the centrifuge speed gradient corresponding to the first range accelerometer. The estimated working radius is obtained through static geometric measurement or the centrifuge's factory parameters. The centripetal acceleration formula is: the estimated working radius of the centrifuge multiplied by the square of the centrifuge speed equals the target excitation acceleration.

[0021] The centrifuge is further controlled to operate according to the centrifuge speed gradient in the first range accelerometer experiment, and the output data of the first range accelerometer is collected under each speed gradient to obtain the first range gradient experimental data.

[0022] In step S102, the weighted radius and radius weight value of the centrifuge are optimized based on the experimental data of the first range gradient, and the centrifuge speed polynomial model is optimized based on the optimized weighted radius.

[0023] Based on experimental data from the first-range accelerometer and the centrifuge's set speed, with the goal of minimizing the sum of squared relative errors, the working radius weights were first optimized, followed by optimization of the centrifuge speed correction polynomial model. This step employs a phased optimization strategy: first, the optimal working radius fusion method is determined, and then an accurate speed correction model is established to reduce the impact of the high-speed centrifuge's own errors. Using the sum of squared relative errors as the optimization objective avoids the high-range segment dominating the optimization process, resulting in more balanced calibration accuracy across the entire range.

[0024] In some embodiments, optimizing the weighted radius and radius weight value of the centrifuge based on the experimental data of the first range gradient includes: determining the measured acceleration of the first range accelerometer corresponding to each gradient rotation speed based on the experimental data of the first range gradient; and calculating the optimized weighted radius and radius weight value based on the measured acceleration of the first range accelerometer.

[0025] In some embodiments, calculating the optimized weighted radius and radius weight value based on the measured acceleration of the first-range accelerometer includes: calculating the optimized weighted radius and radius weight value using a first minimization formula based on the measured acceleration of the first-range accelerometer, wherein the first minimization formula is: (1) (2) in, ω i For the first i One rotation speed, a i The first range accelerometer i A measured acceleration, r i For the first i An initial working radius, w i For the first i Each radius weight value, r w The optimized weighted radius, n This represents the number of rotational speeds in the centrifuge's speed gradient. m Based on n The speed was calculated to obtain n The first of the initial working radii m indivual.

[0026] In some embodiments, optimizing the centrifuge speed polynomial model based on the optimized weighted radius includes: calculating the optimized centrifuge speed polynomial model using a second minimization formula based on the optimized weighted radius, wherein the second minimization formula is: (3) in,p i For the first i A modified polynomial model of centrifuge speed. r w The optimized weighted radius, a i The first range accelerometer i One measured acceleration.

[0027] In some embodiments, the polynomial model of centrifuge speed is: (4) in, p i For the first i A corrected rotational speed b 2. b 1. b 0 represents the coefficients of a polynomial.

[0028] Specifically, based on centrifuge settings n The centrifuge's centrifuge speed was calculated using the centripetal acceleration formula based on the measured acceleration output of the first-range accelerometer from the experimental data of the increasing rotational speed and the first-range gradient. n An initial working radius is given, where the centripetal acceleration formula is the square of the rotational speed multiplied by the radius, which equals the acceleration. The initial radius is selected from this formula. m Each one is calculated.

[0029] Acceleration prediction by minimizing the weighted radius ω i 2 r w The sum of squared relative errors between the measured and actual accelerations is minimized using the first minimization formula. The optimized weighted radius of the centrifuge is obtained by solving the problem. r w and the optimized m Radius weight value w i .

[0030] Furthermore, a polynomial model for centrifuge speed correction is established: .

[0031] The sum of squared relative errors is minimized using the second minimization formula. Minimize, calculate n A corrected speed p i With 3 polynomial coefficients, the working radius weight and centrifuge speed correction polynomial model can be optimized.

[0032] In step S103, after removing the first-range accelerometer from the centrifuge and installing the second-range accelerometer on the centrifuge rotor, a multi-speed excitation gradient experiment is performed on the second-range accelerometer to obtain the second-range gradient experimental data. Based on the optimized centrifuge radius weight value, the optimized centrifuge speed polynomial model, and the second-range gradient experimental data, the linearity of the second-range accelerometer is calculated, wherein the range of the first-range accelerometer is greater than the range of the second-range accelerometer.

[0033] Specifically, the first-range accelerometer is removed from the centrifuge, and the second-range accelerometer is installed on the rotor of the centrifuge. The output data of the second-range accelerometer is remotely read and saved through wireless data transmission.

[0034] Further gravity field experiments were conducted on the second-range accelerometer to collect its output under ±1G conditions, obtain the scaling factor of the second-range accelerometer, and convert the output signal of the second-range accelerometer into an acceleration signal based on the scaling factor.

[0035] The centrifuge speed gradient corresponding to the second-range accelerometer is determined as follows: based on the estimated working radius of the centrifuge, the required centrifuge speed is calculated from the target excitation acceleration according to the centripetal acceleration formula, and a set of numerically increasing gradients is designed accordingly. n The rotational speeds constitute the centrifuge rotational speed gradient, which serves as the centrifuge rotational speed gradient corresponding to the second-range accelerometer. The estimated working radius is obtained through static geometric measurement or centrifuge factory parameters.

[0036] The centrifuge was further controlled to operate according to the centrifuge speed gradient in the second-range accelerometer experiment, and the output data of the second-range accelerometer was collected at each speed gradient to obtain the experimental data of the second-range gradient.

[0037] In the second-range accelerometer experiment, the upper limit of the acceleration range covered by the rotational speed gradient does not exceed the nominal full scale of the second-range accelerometer.

[0038] Based on the optimized working radius weight and centrifuge speed correction polynomial model, combined with the experimental data of the second range gradient, the linearity of the second range accelerometer is calculated by fitting a straight line, thus achieving high-precision calibration of the linearity of the large range accelerometer under ordinary laboratory conditions.

[0039] In some embodiments, before calculating the linearity of the second-range accelerometer based on the optimized centrifuge radius weight value, the optimized centrifuge speed polynomial model, and the second-range gradient experimental data, the method includes: determining the output acceleration of the second-range accelerometer based on the second-range gradient experimental data, and calculating a new weighted radius based on the output acceleration of the second-range accelerometer and the optimized centrifuge radius weight value; calculating the actual speed of the centrifuge based on the optimized centrifuge speed polynomial model, and calculating the actual excitation acceleration of the centrifuge based on the actual speed of the centrifuge and the new weighted radius; and performing a linear fit between the actual excitation acceleration of the centrifuge and the corresponding output acceleration of the second-range accelerometer to obtain a fitted linear equation.

[0040] In some embodiments, after obtaining the fitted linear equation, the method includes calculating the maximum deviation between the output acceleration of the second-range accelerometer and the fitted linear equation at each gradient rotational speed; and calculating the linearity of the second-range accelerometer based on the maximum deviation between the output acceleration of the second-range accelerometer and the fitted linear equation at each gradient rotational speed.

[0041] In some embodiments, calculating the maximum deviation between the output acceleration of the second-range accelerometer and the fitted linear equation at each gradient rotational speed includes: calculating the maximum deviation between the output acceleration of the second-range accelerometer and the fitted linear equation according to a third minimization formula, wherein the third minimization formula is: (5) in, y i For the second range accelerometer i Each output acceleration, x i For the first i A real incentive acceleration, k and c The parameters are for fitting the straight line.

[0042] In some embodiments, the linearity of the second-range accelerometer is: (6) in, δ Linearity of the second-range accelerometer ，y F Δ represents the maximum acceleration output value of the second-range accelerometer within the excitation acceleration range. y max For the maximum deviation 。

[0043] according to Calculated m Each radius weight value, combined with the weighted radius expression The new weighted radius of the centrifuge is calculated.

[0044] according to The calculated coefficients of the three polynomials b 2. b 1. b 0. Calculate the actual centrifuge speed in the second range gradient experiment, and then combine it with the new weighted radius to obtain... n The actual excitation acceleration is the square of the actual rotational speed multiplied by the new weighted radius.

[0045] based on n The actual acceleration and n The output acceleration of each corresponding second-range accelerometer is fitted using the least squares method to obtain the fitted line equation, where the fitted line equation is: (7) in, y The output acceleration of the second-range accelerometer. x To provide actual incentive acceleration, k and c The parameters are for fitting the straight line.

[0046] The parameters of the fitted straight line are solved by minimizing the error using the third minimization formula. The maximum deviation Δ between the output acceleration of the second-range accelerometer at all velocity test points under the rotational speed gradient and the fitted straight line is calculated. y max .

[0047] Based on the maximum deviation Δ y max The maximum acceleration output value of the second-range accelerometer within the excitation acceleration range y F The linearity of the second-range accelerometer is calculated using equation (6). δ.

[0048] Thus, high-precision calibration of the linearity of large-range accelerometers can be achieved under ordinary laboratory conditions.

[0049] To illustrate the technical problems solved by this application and its beneficial effects, the invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0050] like Figure 2 As shown, in step S1, a high-speed centrifuge calibration device is set up. Specifically, the first-range accelerometer is installed on the rotor of the centrifuge, and the output data of the first-range accelerometer is remotely read and saved through wireless data transmission.

[0051] S11, the battery module and the wireless module are fixed in the rotor of the high-speed centrifuge, and the wiring is made so that the battery module can simultaneously power the wireless module and the first-range accelerometer.

[0052] S12, the first-range accelerometer is installed in the rotor of the high-speed centrifuge, the battery module is connected to provide power, and then the computer is used to remotely read and save the output data of the first-range accelerometer through the wireless module.

[0053] Step S2: Perform a gravity field experiment on the first-range accelerometer to obtain the scaling factor of the first-range accelerometer. Based on the estimated working radius of the centrifuge, calculate the required centrifuge speed from the target excitation acceleration according to the centripetal acceleration formula. In this way, design the centrifuge speed gradient in the first-range accelerometer experiment. Based on the set centrifuge speed gradient in the first-range accelerometer experiment, use a calibration device to perform the first-range accelerometer experiment and obtain the first-range gradient experimental data.

[0054] S21, conduct a gravity field experiment on the first-range accelerometer, and calculate the scaling factor of the first-range accelerometer based on its output under ±1G.

[0055] S22, based on the estimated working radius, roughly calculate the centrifuge speed required to achieve the target excitation acceleration, and design the centrifuge speed gradient, with values ​​increasing incrementally. n One rotational speed. In this embodiment, n Choose 11, and set the speed sequence as 140, 200, 310, 440, 620, 980, 1380, 1690, 1950, 2180, 2390 rpm.

[0056] S23, In this embodiment, the first range accelerometer has a range of 600G. The first range accelerometer experiment is conducted based on the calibration device, and the first range accelerometer gradient experimental data is read and saved by computer.

[0057] Step S3: Based on the experimental data of the first-range accelerometer and the centrifuge speed gradient, with the goal of minimizing the sum of squared relative errors, first optimize the weighted radius and radius weight value of the centrifuge, and then optimize the centrifuge speed correction polynomial model.

[0058] This step employs a phased optimization strategy: first, the optimal working radius fusion method is determined, and then a precise speed correction model is established to reduce the impact of the high-speed centrifuge's own errors. Using the sum of squared relative errors as the optimization objective avoids the high-range segment dominating the optimization process, resulting in more balanced calibration accuracy across the entire range.

[0059] S31, based on the 11 incrementally increasing rotational speeds set for the centrifuge and the corresponding first-range accelerometer outputs, calculates 11 initial working radii, from which the first one is selected.m Each is calculated. In this embodiment, m Choose 3, meaning select the initial working radii corresponding to the first three low-speed points (140, 200, and 310 rpm) for weighted calculation. Set the weighted radius. r w The expression is: .

[0060] S32, by minimizing the sum of squared relative errors between the predicted acceleration and the measured acceleration using the weighted radius, the optimized weighted radius is obtained. r w and 3 weight values w i : .

[0061] S33, Establish a polynomial model for centrifuge speed correction. This embodiment uses a second-order polynomial for speed correction: ; in, p i For the first i A corrected rotational speed b 2. b 1. b 0 represents the polynomial coefficients, and the initial value is set to... b 2=0、 b 1=1、 b 0=0, meaning that the corrected speed is equal to the set speed in the initial state.

[0062] S34 calculates 11 corrected rotational speeds by minimizing the sum of squared relative errors. p i And 3 polynomial coefficients: ; The optimization of the weighted radius and radius weight value of the centrifuge and the centrifuge speed correction polynomial model is achieved.

[0063] exist Figure 3 In this embodiment, after optimization in step S3, the comparison between the centrifuge set speed and the corrected speed is shown in the figure. The horizontal axis represents the set speed, and the vertical axis represents the corrected actual centrifuge speed. The dashed line... y = x This represents the ideal situation where the set speed perfectly matches the actual speed. The solid line is the output curve of the centrifuge speed correction polynomial model obtained through optimization in step S3. Taking the highest speed point as an example, when the set speed is 2390 rpm, the corrected speed is 2364 rpm, with a deviation of approximately 26 rpm.

[0064] Step S4: Take out the first-range accelerometer and install the second-range accelerometer on the centrifuge rotor. Experiment with the second-range accelerometer according to the centrifuge speed gradient corresponding to the second-range accelerometer. Based on the optimized radius weight value and the centrifuge speed correction polynomial model, combined with the experimental data of the second-range gradient, calculate the linearity of the second-range accelerometer by fitting a straight line. Achieve high-precision calibration of the linearity of a large-range accelerometer under ordinary laboratory conditions.

[0065] S41, take out the first-range accelerometer, install the second-range accelerometer on the centrifuge, conduct the experiment according to the set speed gradient of the second range, and obtain the experimental data of the second-range gradient. The upper limit of the excitation acceleration range of the centrifuge shall not exceed the nominal full scale of the second-range accelerometer. The range of the first-range accelerometer is greater than the range of the second-range accelerometer to ensure the accuracy of the reference excitation. The range of the second-range accelerometer is 300G.

[0066] In this embodiment, the nominal full-scale of the second-range accelerometer is 300G, and the upper limit of the excitation acceleration range is approximately 279G, covering 93% of the nominal full-scale.

[0067] S42, based on the three radius weight values ​​obtained in step S32, and combined with the weighted radius expression (1) in step S31, calculate the new weighted radius of the centrifuge.

[0068] S43. Based on the three polynomial coefficients obtained in step S34, calculate the actual centrifuge speed in the second range gradient experiment, and combine the weighted radius obtained in step S42 to calculate 11 actual excitation accelerations.

[0069] S44, based on 11 actual excitation accelerations and the output accelerations of 11 corresponding second-range accelerometers, uses the least squares method to perform linear fitting and obtain the fitted linear equation.

[0070] The parameters of the fitted line are obtained by minimizing the error: .

[0071] Calculate the maximum deviation Δ between the output acceleration of the second-range accelerometer and the fitted straight line for all rotational speed gradients. y max .

[0072] S45, based on the maximum deviation Δ y max The maximum acceleration output value of the second-range accelerometer within the excitation acceleration range y F The linearity was calculated. δ : ; In this embodiment, y F Take the maximum value of the second range accelerometer output within the excitation acceleration range of the centrifuge output, that is, the output value corresponding to the maximum excitation acceleration (approximately 279G) of the centrifuge output.

[0073] This enables high-precision calibration of the linearity of large-range accelerometers under ordinary laboratory conditions.

[0074] like Figure 4 As shown in the figure, after calibration in step S4, the linearity fitting line of the second-range accelerometer in this embodiment is as follows. The nominal full-scale range of the second-range accelerometer is 300G, and the calibration range of this embodiment covers 0-279G. The horizontal axis represents the actual excitation acceleration after error model correction, and the vertical axis represents the accelerometer output acceleration. In the figure, the circles represent the measured accelerometer output values ​​corresponding to each rotational speed point, and the straight line represents the best fitting line obtained by least squares fitting. As can be seen from the figure, the measured data points are evenly distributed on both sides of the fitting line, and the maximum deviation is marked in the figure, corresponding to the output value at an excitation acceleration of approximately 279G. y F =253.195G, the distance of this point from the fitted line is Δ. y max =9.862G. Using the maximum acceleration of 253.195G output by the second-range accelerometer within this acceleration range as a benchmark, the linearity is calculated by substituting it into equation (6). δ The linearity was 3.895%. Calibration results show that the method of this invention effectively calibrated the linearity of the 300G range accelerometer within the 0-279G calibration range.

[0075] In summary, the beneficial effects achieved by this application are as follows: 1. To address the problem that existing methods struggle to achieve high-precision linearity calibration for large-range accelerometers with speeds exceeding 200G, this invention discloses a linearity calibration method for large-range accelerometers based on a high-speed centrifuge. This method utilizes a general-purpose high-speed centrifuge to generate a large-range excitation exceeding 200G. The working radius, radius weight, and centrifuge speed correction polynomial model are pre-optimized through experiments with the first-range accelerometer. The optimized model is then applied to the calibration of the second-range accelerometer, effectively reducing the impact of the high-speed centrifuge's own errors on calibration accuracy. High-precision linearity calibration of large-range accelerometers can be achieved under ordinary laboratory conditions.

[0076] 2. When optimizing the working radius, radius weight, and centrifuge speed correction polynomial model, the sum of squared relative errors is used as the objective function. Compared with the conventional method of minimizing absolute error, this avoids the problem that the optimization process is dominated by the large absolute value of acceleration in the high range segment and the error in the low range segment is ignored. This makes the calibration accuracy more balanced and consistent across the entire range. It is especially suitable for calibration scenarios with a large range and acceleration values ​​in the high and low range segments differing by tens of times. This is beneficial for improving the linearity calibration accuracy of the second-range accelerometer across the entire working range.

[0077] Next, referring to the accompanying drawings, a linearity calibration device for a large-range accelerometer based on a high-speed centrifuge, according to an embodiment of this application, is described.

[0078] Figure 5 This is a block diagram of a large-range accelerometer linearity calibration device based on a high-speed centrifuge, according to an embodiment of this application.

[0079] like Figure 5 As shown, the large-range accelerometer linearity calibration device 10 based on a high-speed centrifuge includes: an experimental data acquisition module 100, an optimization module 200, and a calculation module 300.

[0080] The experimental data acquisition module 100 is used to conduct multi-speed excitation gradient experiments on the first-range accelerometer to obtain first-range gradient experimental data, wherein the first-range accelerometer is installed on the centrifuge rotor; the optimization module 200 is used to optimize the weighted radius and radius weight value of the centrifuge based on the first-range gradient experimental data, and optimize the centrifuge speed polynomial model based on the optimized weighted radius; the calculation module 300 is used to, after removing the first-range accelerometer from the centrifuge and installing the second-range accelerometer on the centrifuge rotor, conduct multi-speed excitation gradient experiments on the second-range accelerometer to obtain second-range gradient experimental data, and calculate the linearity of the second-range accelerometer based on the optimized centrifuge radius weight value, the optimized centrifuge speed polynomial model, and the second-range gradient experimental data, wherein the range of the first-range accelerometer is greater than the range of the second-range accelerometer.

[0081] In some embodiments, the experimental data acquisition module 100 is used to: determine the estimated working radius and target excitation acceleration of the centrifuge; calculate the rotational speed gradient of the centrifuge in the first range accelerometer experiment based on the estimated working radius and target excitation acceleration of the centrifuge and according to the centripetal acceleration formula; control the centrifuge to operate according to the rotational speed gradient of the centrifuge in the first range accelerometer experiment, and collect the output data of the first range accelerometer under each rotational speed gradient to obtain the first range gradient experimental data.

[0082] In some embodiments, the optimization module 200 is used to: determine the measured acceleration of the first-range accelerometer corresponding to each gradient rotational speed based on the experimental data of the first-range gradient; and calculate the optimized weighted radius and radius weight value based on the measured acceleration of the first-range accelerometer.

[0083] In some embodiments, the optimization module 200 is further configured to: calculate the optimized weighted radius and radius weight value based on the measured acceleration of the first-range accelerometer using a first minimization formula, wherein the first minimization formula is: ;

[0084] in, ω i For the first i One rotation speed, a i The first range accelerometer i A measured acceleration, r i For the first i An initial working radius, w i For the first i Each radius weight value, r w The optimized weighted radius, n This represents the number of rotational speeds in the centrifuge's speed gradient. m Based on n The speed was calculated to obtain n The first of the initial working radii m indivual.

[0085] In some embodiments, the optimization module 200 is further configured to: calculate the optimized centrifuge speed polynomial model based on the optimized weighted radius using a second minimization formula, wherein the second minimization formula is: ; in, p i For the first i A modified polynomial model of centrifuge speed. r w The optimized weighted radius, a i The first range accelerometer i One measured acceleration.

[0086] In some embodiments, the polynomial model of centrifuge speed is: ; in,p i For the first i A corrected rotational speed b 2. b 1. b 0 represents the coefficients of a polynomial.

[0087] In some embodiments, before calculating the linearity of the second-range accelerometer based on the optimized centrifuge radius weight value, the optimized centrifuge speed polynomial model, and the second-range gradient experimental data, the calculation module 300 is configured to: determine the output acceleration of the second-range accelerometer based on the second-range gradient experimental data, and calculate a new weighted radius based on the output acceleration of the second-range accelerometer and the optimized centrifuge radius weight value; calculate the actual speed of the centrifuge based on the optimized centrifuge speed polynomial model, and calculate the actual excitation acceleration of the centrifuge based on the actual speed of the centrifuge and the new weighted radius; and perform linear fitting between the actual excitation acceleration of the centrifuge and the corresponding output acceleration of the second-range accelerometer to obtain a fitted linear equation.

[0088] In some embodiments, after obtaining the fitted linear equation, the calculation module 300 is further configured to: calculate the maximum deviation between the output acceleration of the second-range accelerometer and the fitted linear equation at each gradient rotational speed; and calculate the linearity of the second-range accelerometer based on the maximum deviation between the output acceleration of the second-range accelerometer and the fitted linear equation at each gradient rotational speed.

[0089] In some embodiments, the calculation module 300 is further configured to: calculate the maximum deviation between the output acceleration of the second-range accelerometer and the fitted linear equation according to a third minimization formula, wherein the third minimization formula is: ; in, y i For the second range accelerometer i Each output acceleration, x i For the first i A real incentive acceleration, k and c The parameters are for fitting the straight line.

[0090] In some embodiments, the linearity of the second-range accelerometer is: ; in, δ Linearity of the second-range accelerometer ，y F Δ represents the maximum acceleration output value of the second-range accelerometer within the excitation acceleration range. y max For the maximum deviation。

[0091] It should be noted that the foregoing explanation of the embodiment of the linearity calibration method for a large-range accelerometer based on a high-speed centrifuge also applies to the linearity calibration device for a large-range accelerometer based on a high-speed centrifuge in this embodiment, and will not be repeated here.

[0092] According to the linearity calibration device for a large-range accelerometer based on a high-speed centrifuge proposed in this application, a multi-speed excitation gradient experiment is performed on a first-range accelerometer to obtain first-range gradient experimental data, wherein the first-range accelerometer is installed on the centrifuge rotor; the weighted radius and radius weight value of the centrifuge are optimized based on the first-range gradient experimental data, and the centrifuge speed polynomial model is optimized based on the optimized weighted radius; the first-range accelerometer is removed from the centrifuge, a second-range accelerometer is installed on the centrifuge rotor, and a multi-speed excitation gradient experiment is performed on the second-range accelerometer to obtain second-range gradient experimental data; the linearity of the second-range accelerometer is calculated based on the optimized centrifuge radius weight value, the optimized centrifuge speed polynomial model, and the second-range gradient experimental data, wherein the range of the first-range accelerometer is greater than the range of the second-range accelerometer. This solves the problem that existing accelerometer calibration methods cannot provide full-scale excitation for accelerometers with a range of 200G or more, which is not conducive to the accurate evaluation of linearity. By using a general-purpose high-speed centrifuge to generate a large-range excitation of 200G or more, high-precision calibration of the linearity of large-range accelerometers can be achieved under ordinary laboratory conditions.

[0093] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: The memory 601, the processor 602, and the computer program stored on the memory 601 and capable of running on the processor 602.

[0094] When the processor 602 executes the program, it implements the linearity calibration method for a large-range accelerometer based on a high-speed centrifuge provided in the above embodiments.

[0095] Furthermore, electronic devices also include: Communication interface 603 is used for communication between memory 601 and processor 602.

[0096] The memory 601 is used to store computer programs that can run on the processor 602.

[0097] The memory 601 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0098] If the memory 601, processor 602, and communication interface 603 are implemented independently, then the communication interface 603, memory 601, and processor 602 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 6 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0099] Optionally, in a specific implementation, if the memory 601, processor 602, and communication interface 603 are integrated on a single chip, then the memory 601, processor 602, and communication interface 603 can communicate with each other through an internal interface.

[0100] The processor 602 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0101] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0102] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0103] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0104] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequential list of executable instructions for implementing logical functions, and can be specifically implemented in any computer program product for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer program product" can be any means that can contain, store, communicate, propagate, or transmit a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples of computer program products (a non-exhaustive list) include the following: an electrical connection having one or N wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic device, and portable optical disc read-only memory (CDROM). Furthermore, the computer program product can even be paper or other suitable medium on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0105] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0106] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer program product, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0107] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer program product.

[0108] The computer program product mentioned above may be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for calibrating the linearity of a large-range accelerometer based on a high-speed centrifuge, characterized in that, Includes the following steps: A multi-speed excitation gradient experiment was conducted on the first-range accelerometer to obtain the first-range gradient experimental data. The first-range accelerometer was installed on the centrifuge rotor. The weighted radius and radius weight value of the centrifuge are optimized based on the experimental data of the first range gradient, and the centrifuge speed polynomial model is optimized based on the optimized weighted radius. After removing the first-range accelerometer from the centrifuge and installing the second-range accelerometer on the centrifuge rotor, a multi-speed excitation gradient experiment is conducted on the second-range accelerometer to obtain second-range gradient experimental data. Based on the optimized centrifuge radius weight value, the optimized centrifuge speed polynomial model, and the second-range gradient experimental data, the linearity of the second-range accelerometer is calculated, wherein the range of the first-range accelerometer is greater than the range of the second-range accelerometer.

2. The method according to claim 1, characterized in that, A multi-speed gradient excitation experiment was conducted on the first-range accelerometer to obtain the first-range gradient experimental data, including: Determine the estimated working radius and target excitation acceleration of the centrifuge; Based on the centrifuge's estimated working radius and target excitation acceleration, the centrifuge's rotational speed gradient in the first-range accelerometer experiment is calculated according to the centripetal acceleration formula. The centrifuge is controlled to operate according to the centrifuge speed gradient in the first range accelerometer experiment, and the output data of the first range accelerometer is collected at each speed gradient to obtain the first range gradient experimental data.

3. The method according to claim 1, characterized in that, Optimizing the weighted radius and radius weight values ​​of the centrifuge based on the experimental data of the first range gradient includes: Based on the experimental data of the first range gradient, determine the measured acceleration of the first range accelerometer corresponding to each gradient rotation speed; The optimized weighted radius and radius weight value are calculated based on the measured acceleration of the first range accelerometer.

4. The method according to claim 3, characterized in that, The step of calculating the optimized weighted radius and radius weight value based on the measured acceleration of the first range accelerometer includes: Based on the measured acceleration from the first-range accelerometer, the optimized weighted radius and radius weight values ​​are calculated using the first minimization formula, wherein the first minimization formula is: ； ； in, ω i For the first i One rotation speed, a i The first range accelerometer i A measured acceleration, r i For the first i An initial working radius, w i For the first i Each radius weight value, r w The optimized weighted radius, n This represents the number of rotational speeds in the centrifuge's rotational speed gradient. m For based on n The speed was calculated to obtain n The first of the initial working radii m indivual.

5. The method according to claim 1, characterized in that, The polynomial model for optimizing centrifuge speed based on the optimized weighted radius includes: Based on the optimized weighted radius, the optimized centrifuge speed polynomial model is calculated using the second minimization formula, where the second minimization formula is: ； in, p i For the first i A modified polynomial model of centrifuge speed. r w The optimized weighted radius, a i The first range accelerometer i One measured acceleration.

6. The method according to claim 5, characterized in that, The polynomial model for the centrifuge speed is: ； in, p i For the first i A corrected rotational speed b 2. b 1. b 0 represents the coefficients of a polynomial.

7. The method according to claim 1, characterized in that, Before calculating the linearity of the second-range accelerometer based on the optimized centrifuge radius weight value, the optimized centrifuge speed polynomial model, and the second-range gradient experimental data, the following steps are included: The output acceleration of the second range speedometer is determined based on the experimental data of the second range gradient, and a new weighted radius is calculated based on the output acceleration of the second range speedometer and the optimized radius weight value of the centrifuge. The actual rotational speed of the centrifuge is calculated based on the optimized centrifuge rotational speed polynomial model, and the actual excitation acceleration of the centrifuge is calculated based on the actual rotational speed and the new weighted radius. The actual excitation acceleration of the centrifuge is fitted with the corresponding output acceleration of the second-range speedometer to obtain the fitted linear equation.

8. The method according to claim 7, characterized in that, After obtaining the equation of the fitted line, the following is included: Calculate the maximum deviation between the output acceleration of the second-range accelerometer and the fitted linear equation at each gradient rotational speed; The linearity of the second-range accelerometer is calculated based on the maximum deviation between the output acceleration of the second-range accelerometer and the fitted straight line at each gradient rotational speed.

9. The method according to claim 8, characterized in that, The calculation of the maximum deviation between the output acceleration of the second range accelerometer and the fitted linear equation at each gradient rotational speed includes: The maximum deviation between the output acceleration of the second range accelerometer and the fitted linear equation is calculated according to the third minimization formula, wherein the third minimization formula is: ； in, y i For the second range accelerometer i Each output acceleration, x i For the first i A real incentive acceleration, k and c The parameters are for fitting the straight line.

10. The method according to claim 9, characterized in that, The linearity of the second-range accelerometer is: ； in, δ Linearity of the second-range accelerometer ，y F Δ represents the maximum acceleration output value of the second-range accelerometer within the excitation acceleration range. y max This represents the maximum deviation.

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