Method, device, equipment and system for mapping acceleration sensor

Abstract

The invention provides a mapping method, device, equipment and system of an acceleration sensor, and relates to the technical field of sensor mapping. According to the invention, the first zero offset with many data points and large possible deviation can be obtained by obtaining the output value when the temperature in the static state continuously changes; based on an arithmetic mean value of output values before and after vertical direction overturning, gravity component interference caused by a possible inclination angle is eliminated, sampling is carried out only at a small number of discrete temperature points, and a second zero offset with few data points and small deviation from the actual zero offset is obtained; further, the difference between the two zero offsets is obtained based on the average value of the difference between the second zero offset and the first zero offset at the same temperature, and the difference is determined as the deviation of the first zero offset relative to the actual zero offset, namely the zero deviation value; and after the first zero offset with the multiple data points is corrected according to the zero offset value, the mapped zero offset with the multiple data points and small offset is obtained.

Description

Technical Field

[0001] This invention relates to the field of sensor calibration technology, and in particular to a calibration method, apparatus, device and system for an accelerometer. Background Technology

[0002] An accelerometer is an inertial sensor that detects the linear acceleration of an object and converts it into a measurable and processable electrical signal. When an object accelerates, the mass within the accelerometer exerts a force on an elastic element due to inertia; the magnitude of this force is proportional to the acceleration. The sensitive element (such as a capacitor) then converts this force into a corresponding electrical signal output. The calibration of an accelerometer, also known as a calibration test, includes, for example, a zero-bias temperature calibration test. Accelerometer performance is highly sensitive to temperature changes; a zero-bias temperature calibration test can determine the actual zero bias at different temperatures, thereby correcting the output value for a more accurate result.

[0003] Current zero-bias temperature calibration tests typically involve placing an accelerometer statically inside a temperature chamber with the measured sensitive axis horizontally positioned. The chamber temperature continuously changes, and the output values ​​of the measured axis from the stationary accelerometer are simultaneously collected. These output values ​​at different temperatures are then used as the zero-bias temperature calibration values, or simply zero-bias. Because the accelerometer remains stationary, continuous sampling is possible during temperature changes, resulting in a large number of data points and high testing efficiency. However, this method requires a high degree of horizontality when placing the accelerometer. If there is any tilt, the gravitational component will cause the measured zero-bias to be greater than the actual zero-bias. Therefore, the accuracy and reliability of current zero-bias temperature calibration tests are relatively poor. Summary of the Invention

[0004] This invention provides a calibration method, apparatus, device, and system for an accelerometer to address the problem of poor accuracy in existing zero-bias temperature calibration testing methods.

[0005] In a first aspect, embodiments of the present invention provide a calibration method for an accelerometer, comprising: within a target temperature range, acquiring the output value of the accelerometer in a stationary state when the temperature changes continuously, as a first zero bias; at multiple discrete temperature points within the target temperature range, acquiring half of the sum of the output values ​​of the accelerometer before and after vertical rotation, as a second zero bias; taking the average of the difference between the second zero bias at each discrete temperature point and the corresponding first zero bias at the same temperature as a zero deviation value; and adding the first zero bias of the target temperature range to the zero deviation value to obtain the accelerometer calibration zero bias.

[0006] In one possible implementation, obtaining half of the sum of the output values ​​of the accelerometer before and after vertical rotation at multiple discrete temperature points within the target temperature range as the second zero bias includes: obtaining a first direction output value of the accelerometer before vertical rotation and a second direction output value after vertical rotation at multiple discrete temperature points within the target temperature range; and for any discrete temperature point, taking half of the sum of the first direction output value and the second direction output value as the second zero bias at that discrete temperature point.

[0007] In one possible implementation, after acquiring the first direction output value of the accelerometer before vertical rotation and the second direction output value after vertical rotation at multiple discrete temperature points within the target temperature range, the method further includes: for any discrete temperature point, dividing half of the difference between the first direction output value and the second direction output value by the gravitational acceleration as a scaling factor for that discrete temperature point.

[0008] In one possible implementation, acquiring the first direction output value of the accelerometer before vertical rotation and the second direction output value after vertical rotation at multiple discrete temperature points within the target temperature range includes: at any of the discrete temperature points, rotating the vertical direction multiple times and acquiring the output values ​​before and after rotation; taking the average of the upward vertical output values ​​as the first direction output value of the accelerometer before vertical rotation; and taking the average of the downward vertical output values ​​as the second direction output value of the accelerometer after vertical rotation.

[0009] In one possible implementation, using the average difference between the second zero bias and the corresponding first zero bias at each discrete temperature point as the zero bias value includes: dividing the target temperature range into multiple temperature intervals; for any given temperature interval, using the average difference between the second zero bias and the corresponding first zero bias at each discrete temperature point within that temperature interval as the zero bias value for that temperature interval; correspondingly, adding the zero bias value to the first zero bias of the target temperature range as the zero bias after accelerometer calibration includes: for any given temperature interval, adding the zero bias value to the first zero bias of that temperature interval as the zero bias after accelerometer calibration for that temperature interval.

[0010] In one possible implementation, adding a zero deviation value to the first zero bias of the target temperature range to obtain the zero bias after accelerometer calibration includes: fitting a first zero bias temperature relationship based on the first zero bias of the target temperature range; and adding a zero deviation value to the first zero bias temperature relationship to obtain the zero bias after accelerometer calibration.

[0011] In one possible implementation, adding a zero deviation value to the first zero bias of the target temperature range to obtain the zero bias after accelerometer calibration includes: adding a zero deviation value to the first zero bias of each temperature point within the target temperature range to obtain a corrected zero bias dataset; and fitting a corrected zero bias temperature relationship based on the corrected zero bias dataset to obtain the corrected zero bias after accelerometer calibration.

[0012] In one possible implementation, the target temperature range is -40°C to 90°C.

[0013] Secondly, embodiments of the present invention provide a calibration device for an accelerometer, comprising: a first acquisition module, configured to acquire the output value of the accelerometer in a stationary state when the temperature changes continuously within a target temperature range, as a first zero bias; a second acquisition module, configured to acquire half of the sum of the output values ​​of the accelerometer before and after vertical rotation at multiple discrete temperature points within the target temperature range, as a second zero bias; a difference calculation module, configured to calculate the average value of the difference between the second zero bias at each discrete temperature point and the first zero bias at the corresponding temperature, as a zero deviation value; and a correction module, configured to add the zero deviation value to the first zero bias of the target temperature range, as the zero bias after accelerometer calibration.

[0014] Thirdly, embodiments of the present invention provide an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method described in the first aspect or any possible implementation thereof.

[0015] Fourthly, embodiments of the present invention provide a calibration system, including the electronic equipment described in the third aspect; and further including a temperature chamber without a turntable and a temperature chamber with a turntable for providing a temperature environment for an accelerometer.

[0016] Fifthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in the first aspect or any possible implementation thereof.

[0017] In a sixth aspect, embodiments of the present invention provide a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect or any possible implementation thereof.

[0018] This invention provides a first zero bias by acquiring the output value during continuous temperature changes in a static state. This first zero bias has many data points but may have a large deviation. Based on the arithmetic mean of the output values ​​before and after vertical flipping, interference from the gravitational component caused by the tilt angle is eliminated. Furthermore, sampling is only performed at a small number of discrete temperature points, resulting in a second zero bias with fewer data points but a smaller deviation from the actual zero bias. Further, based on the average difference between the second and first zero biases at the same temperature, the difference between the two zero biases is determined as the magnitude of the deviation of the first zero bias relative to the actual zero bias, i.e., the zero bias value. After correcting the first zero bias with many data points according to the zero bias value, a post-calibration zero bias with many data points and a smaller deviation is obtained. This invention improves the accuracy of the post-calibration zero bias while maintaining the advantage of having many data points in existing methods. Attached Figure Description

[0019] Figure 1 This is an application scenario diagram of the calibration method for the accelerometer provided in the embodiments of the present invention; Figure 2 This is another application scenario diagram of the accelerometer calibration method provided in the embodiments of the present invention; Figure 3 This is a flowchart illustrating the implementation of the calibration method for an accelerometer provided in this embodiment of the invention. Figure 4 This is a schematic diagram of the first zero-bias curve provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the second zero-bias curve provided in an embodiment of the present invention; Figure 6 This is a comparative schematic diagram of the first zero bias and the second zero bias provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of the zero-bias curve after calibration provided in an embodiment of the present invention; Figure 8 This is a schematic diagram of the structure of the calibration device for the accelerometer provided in an embodiment of the present invention; Figure 9 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0020] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0021] Figure 1 This is an application scenario diagram of the accelerometer calibration method provided in an embodiment of the present invention. For example... Figure 1As shown, in the existing zero-bias temperature calibration test method, the test axis of the accelerometer is placed horizontally, that is, the test axis is as parallel to the horizontal direction as possible. The angle between the horizontal direction and the direction of gravity is 90 degrees, and the component of gravity in the horizontal direction is 0. Therefore, the external force on the horizontally placed test axis is 0. At this time, it remains stationary, and the output value of the accelerometer can represent the accurate actual zero bias.

[0022] A horizontal accelerometer is placed statically inside a temperature chamber. As the temperature inside the chamber continuously changes, the temperature of the accelerometer also continuously changes. Since only the temperature changes, the force state of the accelerometer remains constant at all times. Therefore, samples can be collected at as many temperature points as possible. The number of temperature-output value data points acquired is mainly limited by the sampling frequency. With a sufficient number of data points, and with adjacent temperature points close enough to each other, a curve closely resembling the actual zero bias versus temperature change can be formed. In summary, the existing zero bias temperature calibration test method has the advantage of having a large number of data points.

[0023] It should be noted that the advantage of having more data points is essentially that more data points can be measured within the same time period. For example, compared to the method that requires changing the force state of the accelerometer at each temperature point, the above-mentioned static zero-bias temperature calibration test method does not require changing the force state of the accelerometer at each temperature point and can directly sample the output value. Therefore, the test efficiency is higher, and more data points can be measured within the same time period.

[0024] In addition, the zero-bias temperature calibration test method described above uses a simple temperature chamber structure, which can be a common temperature chamber, and its volume is large enough to load a large number of products at once. Therefore, the test efficiency is high and it is suitable for mass production.

[0025] Figure 2 This is another application scenario diagram of the accelerometer calibration method provided in this embodiment of the invention. (Refer to...) Figure 2 However, if the axis to be measured is not strictly horizontal, and there is a certain angle θ between the axis to be measured and the horizontal direction, the gravitational acceleration g will produce a gravitational component along the axis to be measured. At this point, the sensor output will be superimposed with the influence of this component, causing a deviation between the measured apparent zero bias and the true zero bias. The magnitude and direction of the deviation depend on the direction of the angle. The gravitational component caused by the tilt angle will cause the apparent zero bias to shift in the direction of the gravitational component. Whether the shift is larger or smaller depends on the tilt direction of the axis being measured and the sign of the true zero bias.

[0026] Existing methods typically improve the flatness of the test platform, reduce the platform tilt angle, or reduce the tilt angle during installation; this places high demands on the accuracy of the test platform and test fixtures.

[0027] This invention, by combining scaling factor testing steps, corrects the zero-bias temperature calibration test results of the static method, thereby solving the problem of poor accuracy in existing zero-bias temperature calibration test methods.

[0028] Figure 3 This is a flowchart illustrating the implementation of the calibration method for an accelerometer provided in this embodiment of the invention. (Refer to...) Figure 3 This invention provides a calibration method for an accelerometer, comprising: Step 301: Within the target temperature range, acquire the output value of the accelerometer in a stationary state when the temperature changes continuously, and use it as the first zero bias.

[0029] It should be noted that the method for determining the first zero bias in step 301 is essentially the same as the zero bias temperature calibration test method in the static mode. The axis of the accelerometer to be measured needs to be as parallel as possible to the horizontal direction, but it is not required that the angle between the axis of the accelerometer to be measured and the horizontal direction be absolutely zero. The accelerometer can use a platform and mounting fixture of ordinary precision. The gravitational component interference caused by the tilt angle of the axis of the accelerometer to be measured will be eliminated in subsequent steps.

[0030] For example, the accelerometer is placed in a temperature chamber. The temperature of the temperature chamber changes continuously, resulting in a continuous change in the temperature of the accelerometer.

[0031] Figure 4 This is a schematic diagram of the first zero-bias curve provided in an embodiment of the present invention. (Refer to...) Figure 4 For example, when acquiring the output value of an accelerometer, the current temperature is simultaneously acquired to obtain the output value of the accelerometer at a certain temperature, which is used as the first zero bias at that temperature. Regarding the output value, the accelerometer typically senses acceleration and outputs data characterizing the acceleration; that is, the output value is the data characterizing the acceleration output by the accelerometer.

[0032] For example, the acceleration sensor is a MEMS (Micro Electromechanical System) acceleration sensor.

[0033] In some embodiments, the target temperature range is -40°C to 90°C.

[0034] Step 302: At multiple discrete temperature points within the target temperature range, obtain half of the sum of the output values ​​of the accelerometer before and after vertical rotation, and use it as the second zero bias. Figure 5 This is a schematic diagram of the second zero-bias curve provided in an embodiment of the present invention; refer to Figure 5It should be noted that the target temperature range in step 301 and the target temperature range in step 302 are the same temperature range. The difference lies in that step 302 selects a small number of discrete temperature points within the target temperature range for testing. Because the sampling in step 301 is periodic, the data obtained in step 301 is essentially discrete as well. However, the sampling period is small enough and the two adjacent temperature points are close enough that it can be approximated as a continuous temperature change. In other words, the distance between two temperature points in step 302 is much greater than the distance between two temperature points in step 301. For example, in step 302, an output value is obtained for each discrete temperature point every 10°C, while in step 301, an output value is obtained every 0.5°C.

[0035] It should be further noted that the use of a small number of discrete temperature point sampling points in step 302 is due to limitations imposed by the physical structure and testing efficiency. The testing process will be explained below.

[0036] In some embodiments, step 301 uses a standard temperature chamber without a turntable to continuously change the temperature of the accelerometer within the target temperature range, and obtains the output value of the accelerometer in a stationary state during the continuous temperature change, as the first zero bias. Step 302 uses a temperature chamber with a turntable to sequentially maintain the temperature of the accelerometer at multiple discrete temperature points within the target temperature range, and obtains half of the sum of the output values ​​of the accelerometer before and after vertical rotation at each discrete temperature point, as the second zero bias.

[0037] The dual-temperature chamber method is particularly suitable for large-scale continuous production processes, and can significantly improve production efficiency. The following is a detailed explanation.

[0038] Based on a temperature chamber with a turntable, the temperature is controlled with a discrete temperature point as the target temperature (e.g., changing from 0℃ to 10℃). After the temperature stabilizes at the target temperature, the output value is measured in one direction first. Then, the chamber is rotated 180°, and after the force stabilizes, the output value is measured in the other direction after rotating 180°. Because the direction needs to be rotated, it is necessary to ensure that the temperature is the same when the output value is collected before and after the rotation. Therefore, the isothermal phase after each change of target temperature is relatively long, and the testing efficiency of a single temperature point is low.

[0039] Furthermore, the temperature chamber with a turntable has a more complex structure and higher equipment cost. Because it needs to be rotated vertically, its volume is smaller, limiting the number of sensors it can accommodate, which in turn restricts testing efficiency. To improve efficiency, the number of temperature points tested should be limited, and the overall testing time should not be too long. This can be achieved by reducing the number of discrete temperature measurement points and increasing the distance between two temperature points. In other words, the second zero bias obtained in step 302 is more accurate, and although the number of data points is smaller, it results in higher production efficiency in large-scale continuous production.

[0040] The following explains how half the sum of the output values ​​before and after a vertical rotation can represent zero bias. It's important to note that a vertical rotation means a 180° rotation in the vertical direction. For example, if the normal direction of the upper surface of the accelerometer points upwards, a 180° vertical rotation will cause the normal direction to point downwards. As another example, if the positive direction of the measured axis of the accelerometer points to the left, a 180° vertical rotation will cause the positive direction of the measured axis to point to the right.

[0041] Assuming the accelerometer's measured axis has a fixed tilt angle, this causes the gravitational acceleration g to produce a component g on the measured axis. x The sensor output model is V=S a+B, where S represents the scale factor and a represents the input acceleration of the axis to be measured (here, the gravitational component g). x B represents the true zero bias, the output value when there is no input acceleration; V represents the actual output value of the sensor.

[0042] Before flipping, the axis under test is along the gravitational component g. x In the positive direction, the input acceleration is +g x The output value is: V1=S g x +B.

[0043] After being vertically flipped 180°, the direction of the axis under test is completely reversed, and the gravitational component becomes... g x The input acceleration is g x The output value is: V2=S ( gx)+B.

[0044] Add the output values ​​before and after the flip and take half of each value:

[0045] After calculation, the gravity component related term S gx offset:

[0046] Regardless of whether the sensor is tilted, as long as it is rotated vertically by 180°, the gravitational component of the sensitive axis will change from +gx to... The summation of gx and gx cancels each other out, eliminating the systematic error caused by the tilt angle. The calculated result is only equal to the true zero bias B, and is independent of the scaling factor and the gravitational component. Therefore, this average value can accurately characterize the zero bias of the sensor at this temperature point, i.e., the second zero bias.

[0047] In one possible implementation, the second zero bias at each discrete temperature point can be calculated as soon as the output value at that discrete temperature point is obtained.

[0048] Alternatively, all the collected discrete temperature point output values ​​can be acquired in batches, and then the second zero bias at each discrete temperature point can be calculated uniformly. See the next embodiment for details.

[0049] In one possible implementation, obtaining half of the sum of the output values ​​of the accelerometer before and after vertical rotation at multiple discrete temperature points within the target temperature range as the second zero bias includes: obtaining a first direction output value of the accelerometer before vertical rotation and a second direction output value after vertical rotation at multiple discrete temperature points within the target temperature range; and for any discrete temperature point, taking half of the sum of the first direction output value and the second direction output value as the second zero bias at that discrete temperature point.

[0050] The next embodiment involves multiple acquisitions and group averaging of the vertical flip acquisition output value to offset random noise and single flip operation errors, making the final first and second direction output values ​​closer to the real state.

[0051] In one possible implementation, acquiring the first direction output value of the accelerometer before vertical rotation and the second direction output value after vertical rotation at multiple discrete temperature points within the target temperature range includes: at any of the discrete temperature points, rotating the vertical direction multiple times and acquiring the output values ​​before and after rotation; taking the average of the upward vertical output values ​​as the first direction output value of the accelerometer before vertical rotation; and taking the average of the downward vertical output values ​​as the second direction output value of the accelerometer after vertical rotation.

[0052] It should be noted that when operating at any discrete temperature point, the accelerometer must first be placed at that temperature and kept at thermal equilibrium to avoid temperature drift affecting the output value. Each vertical rotation is a 180° rotation around a horizontal axis perpendicular to the axis under test, ensuring that the axis under test points vertically upward before the rotation (e.g., the first direction) and vertically downward after the rotation (e.g., the second direction), and that the gravitational components are equal in magnitude and opposite in direction in both rotations.

[0053] Instead of a single flip, the flipping operation is repeated multiple times at the same temperature point, such as 5 or 10 times. During each flip, the output value when vertically upward and the output value when vertically downward are recorded respectively. Vertically upward and downward are two different input states, for example, corresponding to the gravitational component +gx and... gx. Furthermore, the arithmetic mean is calculated for all output values ​​in the first direction (e.g., vertically upward), and the arithmetic mean is calculated for all output values ​​in the second direction (e.g., vertically downward).

[0054] Sensor output can be affected by random noise such as instantaneous circuit fluctuations and minor environmental vibrations, and single-sample values ​​may contain deviations. The embodiments of this invention, by averaging multiple samples, can significantly reduce the interference of random noise, making the output value closer to the true steady-state output value at that temperature point.

[0055] In addition, in actual operation, a single flip may have an angular deviation (e.g., not rotating exactly 180°), resulting in the gravitational component not being completely reversed. After multiple flips, the effect of the angular deviation will be averaged out (some flip angles are slightly greater than 180°, and some are slightly less), further improving the accuracy of the direction output value.

[0056] Step 303: Take the average value of the difference between the second zero bias and the corresponding first zero bias at each discrete temperature point as the zero bias value; Figure 6 This is a comparative schematic diagram of the first and second zero biases provided in an embodiment of the present invention; see reference. Figure 6 Since both steps 301 and 302 involve sampling within the target temperature range, the discrete temperature points in step 302 overlap with the continuous temperatures in step 301. For example, if a first zero bias is obtained at 10℃ in step 301, a second zero bias is also obtained at 10℃ in step 302. That is, the second zero bias at 10℃ corresponds to the first zero bias at the same temperature of 10℃. It should be noted that even if a discrete temperature point does not have a completely corresponding temperature, as long as there is a temperature with a small difference from that discrete temperature point, it can be considered a corresponding temperature. For example, if the discrete temperature point in step 302 is 20℃, the closest temperature in step 301 is only 20.1℃. Since the difference is 0.1℃, the difference is small, and these two temperatures can be considered the same temperature. Of course, in actual production operations, temperature measurement points are preset, and usually each discrete temperature point is assigned a corresponding temperature.

[0057] The second zero bias is obtained through vertical flipping. Essentially, it represents the true zero bias at that temperature point. The flipping operation cancels out the gravitational component interference caused by the tilt angle, resulting in an accurate reflection of the sensor's output reference when there is no input acceleration. The first zero bias is the sensor's output value when the temperature is continuously changing and the sensor is stationary. Essentially, it represents the apparent zero bias at that temperature point. Because it does not eliminate interference from the tilt angle gravitational component, instantaneous drift during continuous temperature measurement, and minor environmental vibrations, the result may deviate from the true zero bias. Therefore, at the same temperature, the difference between the second and first zero biases represents the deviation of the first zero bias from the true zero bias.

[0058] When the first zero bias is small, it needs to be corrected upwards to approach the true zero bias. When the first zero bias is large, it needs to be corrected downwards to approach the true zero bias. When the first zero bias is exactly equal to the true zero bias, there is no deviation.

[0059] In step 303, the average value of the difference between each discrete temperature point is taken as the zero deviation value. The purpose is to eliminate the random fluctuations of the difference between different discrete temperature points, such as the accidental operation error at a certain temperature point, and to obtain a universal correction benchmark for the entire temperature range. This average value is used to uniformly correct all the first zero deviations within the target temperature range, so that the corrected zero deviation has both continuous temperature coverage and high precision.

[0060] In some embodiments, for any discrete temperature point, the difference between the second zero bias at that discrete temperature point and the first zero bias at the corresponding temperature is obtained; the arithmetic mean of the differences between the second zero bias at all discrete temperature points and the first zero bias at the corresponding temperature is calculated; and the arithmetic mean is taken as the zero bias value. The above embodiment averages the differences between the two zero biases at all discrete temperature points, which is applicable when the differences between the two zero biases are basically consistent at various temperatures.

[0061] Step 304: Add the zero deviation value to the first zero bias of the target temperature range and use it as the zero bias after the accelerometer is calibrated.

[0062] Figure 7 This is a schematic diagram of the zero-bias curve after calibration provided in an embodiment of the present invention; refer to Figure 7 In some embodiments, the first zero bias of each temperature within the target temperature range is added to the zero deviation value to obtain the post-calibration zero bias of each temperature within the target temperature range, which is used as the post-calibration zero bias of the accelerometer.

[0063] It should be noted that the method of adding the first zero bias to the zero deviation value in step 304 is related to the calculation method of the zero deviation value in step 303.

[0064] The zero-bias value is the "average difference between the true zero-bias and the first zero-bias," representing the average deviation of the first zero-bias from the true zero-bias across the entire temperature range. Specifically, step 303 obtains the zero-bias value level for a few discrete temperature points. The main reason for the zero-bias value is the fixed tilt angle of the accelerometer. Since the tilt angle of the accelerometer is relatively fixed, the zero-bias values ​​are similar at different temperatures. Therefore, through step 304, the zero-bias under continuous temperature variation within the target temperature range can be obtained, i.e., the calibrated zero-bias with many data points and small deviations.

[0065] In one possible implementation, after obtaining the zero bias of each temperature within the target temperature range in step 304, a correspondence table between temperature and zero bias can be established. Subsequently, the zero bias of the accelerometer at the real-time temperature can be determined by looking up the table, thereby correcting the output value of the accelerometer.

[0066] Besides the table lookup method mentioned above, the relationship between the zero bias of the accelerometer and temperature can also be obtained through curve fitting. Two methods are given below.

[0067] This embodiment illustrates how to construct a correlation model between the zero bias of an accelerometer and temperature through curve fitting to achieve zero bias correction across the entire temperature range. The aforementioned method has obtained the zero bias value through discrete temperature point calibration. This embodiment provides two fitting implementation paths. The core difference lies in the order of operations for zero bias value correction and curve fitting. Both methods can output a usable zero bias-temperature relationship, but their logical essence and applicable scenarios differ.

[0068] In one possible implementation, adding a zero deviation value to the first zero bias of the target temperature range to obtain the zero bias after accelerometer calibration includes: fitting a first zero bias temperature relationship based on the first zero bias of the target temperature range; and adding a zero deviation value to the first zero bias temperature relationship to obtain the zero bias after accelerometer calibration.

[0069] The first zero bias here is the output value of the sensor in a static state during continuous temperature change. It has the characteristic of continuous coverage of the entire temperature range, but it is affected by factors such as tilt angle gravity component and instantaneous temperature drift, and has a systematic deviation from the true zero bias.

[0070] During fitting, first-order, second-order, or higher-order polynomials can be selected based on the trend characteristics of the data. The purpose of fitting is to extract the overall trend of the first zero bias with temperature change, rather than pursuing absolute accuracy for individual data points. Therefore, the fitting process can naturally smooth out random noise in the first zero bias.

[0071] The logic of this implementation is to first extract the trend and then perform unified calibration. The zero-bias value is the average of the true zero bias and the first zero-bias value at discrete temperature points across the entire temperature range. Its physical meaning is the global average deviation of the first zero bias relative to the true zero bias. Since the temperature relationship of the first zero bias has already characterized the trend of zero bias changing with temperature, adding the zero-bias value to this relationship is essentially rigidly shifting this trend line along the zero-bias axis to make it approximate the temperature trend of the true zero bias. The advantage of this method is that the fitting operation precedes the correction operation. Random noise in the first zero bias can be smoothed first by fitting, and then the deviation calibration is performed. The final relationship has good smoothness and is suitable for scenarios with high requirements for the smoothness of the zero bias trend. At the same time, it does not require correction calculations for a massive number of continuous temperature points one by one, resulting in higher computational efficiency.

[0072] In one possible implementation, adding a zero deviation value to the first zero bias of the target temperature range to obtain the zero bias after accelerometer calibration includes: adding a zero deviation value to the first zero bias of each temperature point within the target temperature range to obtain a corrected zero bias dataset; and fitting a corrected zero bias temperature relationship based on the corrected zero bias dataset to obtain the corrected zero bias after accelerometer calibration.

[0073] The logic of this implementation is to first calibrate individual points and then extract trends. Compared to the first implementation, this method first corrects the deviation of each first zero-bias data point, and then performs fitting based on the corrected dataset. Essentially, it first eliminates the global average deviation of each data point, and then extracts the trend of zero-bias changes with temperature from the corrected data. The advantage of this method is that the zero-bias data at each temperature point has undergone deviation compensation, the original data fitted is closer to the true zero-bias, and the resulting relationship better reflects the characteristics of the true zero-bias at each temperature point; if there are special deviations in local temperature ranges in the first zero-bias, the corrected data can also reflect these local characteristics in the fitting, making it suitable for scenarios with high requirements for single-point zero-bias accuracy.

[0074] Both implementation methods ultimately aim to construct an accurate zero-bias-temperature relationship. Their difference stems from the different orders of correction and fitting, leading to different data processing logics. The noise handling logic differs: Method 1 first fits and smooths the noise before correcting the trend, resulting in a smoother relationship; Method 2 corrects the data first before fitting the trend, resulting in better accuracy for single-point data. The trend extraction benchmarks differ: Method 1 performs overall calibration based on a biased trend; Method 2 extracts the true trend based on calibrated single-point data. The applicable scenarios differ: Method 1 is suitable for engineering applications requiring rapid acquisition of smooth trends; Method 2 is suitable for high-precision calibration scenarios that prioritize single-point zero-bias accuracy.

[0075] This invention obtains a first zero bias by acquiring the output value when the temperature changes continuously in a static state, which has many data points but may have large deviations. The arithmetic mean of the output values ​​before and after vertical flipping eliminates the interference of the gravitational component caused by the tilt angle, and samples are only taken at a small number of discrete temperature points, resulting in a second zero bias with fewer data points but smaller deviations from the actual zero bias. Furthermore, based on the average difference between the second and first zero biases at the same temperature, the difference between the two zero biases is obtained and determined as the magnitude of the deviation of the first zero bias from the actual zero bias, i.e., the zero bias value. After correcting the first zero bias with many data points according to the zero bias value, a calibrated zero bias with many data points and smaller deviations is obtained.

[0076] The vertical flipping and averaging operation not only eliminates the interference of gravitational components from accidental tilt angles, but also counteracts the systematic errors caused by the fixed tilt angle of the sensor installation. After flipping 180°, the sign of the gravitational component is reversed, and averaging can eliminate this fixed interference term, thus improving the reliability of the second zero bias reference.

[0077] The corrected zero bias combines continuous temperature coverage with high accuracy, resolving the contradiction between low accuracy of traditional continuous sampling and discontinuous discrete sampling. It can be directly used for real-time compensation across the entire temperature range without additional interpolation calculations, thus reducing the complexity of subsequent correction models.

[0078] Discrete temperature point sampling requires only a small number of test stations. Compared with continuous high-precision calibration throughout the entire process, it significantly shortens the test time and reduces the temperature control load on the equipment. While ensuring the calibration effect, it significantly improves the efficiency of engineering testing and saves test costs.

[0079] Furthermore, the 180° rotation test process can be reused with the scaling factor test process, without requiring a separate accelerometer test step. Only steps 303 and 304 need to be added in the subsequent data processing steps. Due to the high efficiency of the data processing itself, it has almost no impact on overall production efficiency in actual production applications.

[0080] The following examples illustrate how to reuse the scaling factor test process. These examples reuse the scaling factor test and the aforementioned zero-bias test flipping process, eliminating the need for additional physical sensor testing steps. Computation is supplemented only through subsequent data processing, ensuring test accuracy while minimizing the impact on production efficiency, thus adapting to the actual needs of mass production scenarios.

[0081] In one possible implementation, after acquiring the first direction output value of the accelerometer before vertical rotation and the second direction output value after vertical rotation at multiple discrete temperature points within the target temperature range, the method further includes: for any discrete temperature point, dividing half of the difference between the first direction output value and the second direction output value by the gravitational acceleration as a scaling factor for that discrete temperature point.

[0082] It should be noted that after completing the acquisition and averaging of the first and second direction output values ​​at any discrete temperature point, the following calculation is performed for that temperature point: based on the acquired first and second direction output values, the difference between the two is calculated, half of the difference is taken, and then divided by the gravitational acceleration. The result is the scaling factor of the sensor at that discrete temperature point.

[0083] It's important to further clarify that the physical meaning of the scaling factor is the ratio of the change in sensor output to the change in input acceleration. Its calculation logic essentially utilizes the reverse characteristic of the gravitational component after flipping to cancel out zero-bias interference and accurately extract the correspondence between output and acceleration. After a 180° vertical flip, the magnitude of the gravitational acceleration component acting on the sensor's sensitive axis remains unchanged, but its direction is completely reversed (i.e., it changes from a positive gravitational component to a negative gravitational component). This known change in acceleration provides an input benchmark for the scaling factor calculation. The difference between the output values ​​in the first and second directions precisely corresponds to the change in output under positive and negative gravitational component inputs, and this change is only related to the scaling factor and gravitational acceleration. Zero bias, as a constant offset, cancels out each other in the difference calculation and does not interfere with the scaling factor result. Taking half of the difference is a normalization process for the output change under bidirectional gravity component input, so that it corresponds to the output response when there is a single direction of gravity acceleration input. Then, dividing by the known quantity of gravity acceleration, the scaling factor of the sensor at that temperature point can be derived in reverse.

[0084] In the aforementioned zero-bias test, the output values ​​of the accelerometer in the first direction before vertical rotation and the output values ​​in the second direction after vertical rotation were collected at multiple discrete temperature points within the target temperature range (this may include multiple rotation grouping and averaging operations). The core data required for the scaling factor test are precisely these two sets of collected output values. Both are based on the same batch of discrete temperature points, the same rotation operation procedure, and the same set of sensor output data, thus possessing data homogeneity.

[0085] The flip operation can provide data to offset the interference of gravity component for zero bias testing, and can also provide the output benchmark corresponding to the known input acceleration (gravitational acceleration) for scaling factor testing. One set of physical operations can support the testing of two parameters at the same time, avoiding the redundancy of steps caused by repeated testing.

[0086] This embodiment only requires adding a scaling factor calculation step (i.e., the new calculation logic beyond steps 303 and 304) to the data processing stage of the zero-bias test. The data processing itself is highly efficient, and the automated calculation of batch data will not significantly increase the overall testing time. Therefore, in practical production applications, it has almost no impact on the overall production efficiency of sensor calibration, balancing testing accuracy and mass production cycle time. This method is particularly suitable for accelerometers where the scaling factor changes monotonically with temperature, but the zero bias does not.

[0087] The next embodiment addresses scenarios where the difference between the second zero bias and the first zero bias varies significantly at different temperatures. It provides a segmented zero bias correction scheme, which, instead of a uniform zero bias calculation method across the entire temperature range, divides the range based on the temperature characteristics of the difference to achieve precise correction within the range. This solves the problem of insufficient accuracy in some temperature segments caused by average correction across the entire temperature range.

[0088] In the aforementioned embodiments, the average value of the differences between discrete temperature points across the entire temperature range is used as the zero deviation value. This implicitly assumes that the difference between the second and first zero deviations fluctuates minimally across the entire target temperature range, and that the globally averaged deviation value can meet the correction requirements of all temperature points. However, in actual calibration, due to the material properties of the core components of the accelerometer and the temperature drift characteristics of the circuit, the difference between the second and first zero deviations is not constant but exhibits significant segmental differences with temperature. For example, the difference is smaller in the low-temperature range, moderate in the medium-temperature range, and significantly larger in the high-temperature range. If the zero deviation value, averaged across the entire temperature range, is still used for uniform correction, some temperature segments will be over-corrected while others will be under-corrected, failing to guarantee the consistent accuracy of the zero deviation correction across the entire temperature range. Therefore, this embodiment proposes a temperature range division correction method to achieve precise matching between the deviation value and temperature characteristics.

[0089] In one possible implementation, the average difference between the second zero bias and the corresponding first zero bias at each discrete temperature point is used as the zero bias value, including: Step 3031: Divide the target temperature range into multiple temperature intervals; It should be noted that the basis for dividing the temperature ranges is the consistency of the trend of the temperature difference: continuous temperature ranges with similar trends and small fluctuations in the temperature difference are divided into independent temperature ranges. The inflection point temperature of the temperature difference can be selected as the boundary point of the range. For example, the inflection point of the temperature difference between the low-temperature and medium-temperature ranges, or the inflection point of the temperature difference between the medium-temperature and high-temperature ranges, to ensure that the temperature difference within each range has similar characteristics and to avoid large fluctuations in the temperature difference within the range.

[0090] Step 3032: For any of the temperature ranges, the average value of the difference between the second zero deviation and the first zero deviation of each discrete temperature point within the temperature range is taken as the zero deviation value of the temperature range. For any divided temperature range, select all discrete temperature points within the range and extract the second zero deviation - first zero deviation value corresponding to each point; calculate the average value of all differences within the range and define the average value as the range zero deviation value of the temperature range.

[0091] The essence of this step is to refine the global average correction into an interval average correction. Since the trend of difference changes is consistent within the same temperature interval, the average difference within the interval can more accurately represent the degree of deviation of the first zero bias from the true zero bias within that interval. Compared with the deviation value of the average across the entire temperature range, the interval zero bias value has stronger adaptability.

[0092] Accordingly, adding the zero deviation value to the first zero bias of the target temperature range as the zero bias after accelerometer calibration includes: for any of the temperature ranges, adding the zero deviation value of the temperature range to the first zero bias of the temperature range as the zero bias after accelerometer calibration for that temperature range.

[0093] Based on the division of the corresponding temperature range, a segmented correction is performed on the first zero bias within the target temperature range. For example, the temperature range to which any first zero bias to be corrected belongs is determined; the first zero bias is added to the interval zero deviation value of the corresponding temperature range to obtain the calibration-post zero bias corresponding to the first zero bias.

[0094] It should be noted that the logic of this correction operation is the same as the aforementioned full-temperature range correction, but the correction benchmark is a range-specific deviation, ensuring that the correction amount for each temperature range can match the difference characteristics of that range.

[0095] This embodiment effectively solves the problem of correction accuracy when the two zero deviation values ​​differ greatly with temperature by dividing the temperature range and calculating the zero deviation value of the range.

[0096] The above examples illustrate a "dual-temperature chamber, dual-process" solution, which is particularly suitable for large-scale continuous production scenarios.

[0097] 1. Procedure A: In a standard temperature chamber, the sensor remains stationary, and continuous temperature sampling is performed. Advantages: Data points are continuous and dense, capturing the complete zero-bias relationship with temperature. Disadvantages: Due to the uncontrollable sensor tilt angle (temperature chamber platform levelness, clamping tilt angle), the zero-bias data includes an unknown and fixed gravitational component deviation.

[0098] 2. Procedure B: In a temperature chamber with a turntable, measurements are taken at discrete temperature points by inversion (±1g input). Advantages: Calculations using +g and -g measurements eliminate the influence of tilt angle, yielding high-precision zero bias and scale factor true values ​​at that temperature point. Disadvantages: Limited by equipment cost and efficiency, measurements can only be taken at a few discrete temperature points.

[0099] The two processes are performed on different physical devices (temperature chambers), and the mounting reference planes (levelness) of these two devices may differ. Therefore, the zero-bias curve containing tilt error measured in process A is based on a different gravitational acceleration reference frame than the high-precision discrete zero-bias point that eliminates tilt error measured in process B. Using two sets of data with different references to fit and compensate the same sensor will introduce uncorrectable systematic errors, resulting in a deterioration in the final compensation effect.

[0100] The following embodiments integrate the core capabilities of Process A and Process B into the same temperature chamber environment. Specifically, continuous sampling and precise discrete point calibration are performed simultaneously in an integrated device with continuous temperature variation and controllable rotation functions. High-precision data from the discrete points (eliminating the influence of the device's tilt angle) are used to correct the reference offset of the continuous zero-bias curve obtained under the same device, thereby obtaining a unified, continuous, and accurate zero-bias-temperature compensation curve.

[0101] In one possible implementation, step 301 uses a temperature chamber with a turntable to continuously change the temperature of the accelerometer within the target temperature range, and acquires the output value of the accelerometer in a stationary state during the continuous temperature change, as the first zero bias. Step 302 uses the same temperature chamber with a turntable to sequentially maintain the temperature of the accelerometer at multiple discrete temperature points within the target temperature range, and acquires half of the sum of the output values ​​of the accelerometer before and after vertical rotation at each discrete temperature point, as the second zero bias.

[0102] The above implementation method, using integrated equipment testing, is suitable for applications testing a small number of products. For example, when the number of products under test is less than the single-state capacity of a temperature chamber with a turntable.

[0103] In some embodiments, the temperature-controlled environment integrates a flipping device; an accelerometer is fixed to the flipping device within the temperature-controlled environment, such that its sensitive axis to be measured is perpendicular to the rotation axis of the flipping device; a calibration method for an accelerometer includes: setting a target temperature range and a rate of change; activating temperature control to continuously change the ambient temperature from an initial temperature to a final temperature at the set rate; continuously acquiring the output value of the accelerometer during the continuous temperature change to obtain a first output data sequence; and controlling the flipping device to operate when the temperature reaches multiple preset discrete calibration temperature points during the continuous temperature change. The accelerometer's sensing axis is sequentially positioned in a first direction and a second direction opposite to the first direction, and stable output values ​​in these two directions are acquired. The first and second directions are opposite to the direction of gravitational acceleration. Based on the first output data sequence, an initial zero bias-temperature relationship curve is fitted and generated. For each discrete calibration temperature point, a reference zero bias value at that temperature point is calculated based on the output values ​​in the first and second directions acquired at that point. According to multiple reference zero bias values ​​and their corresponding temperatures, the initial zero bias-temperature relationship curve is corrected to generate a zero bias-temperature compensation curve.

[0104] The accelerometer calibration method provided in this invention firstly achieves a unified test benchmark, eliminating systematic errors. This invention integrates continuous temperature-varying sampling with precise discrete point flipping measurement into the same physical device and the same test procedure. All data (including continuous data that may contain tilt errors and discrete high-precision data with tilt errors eliminated) are obtained based on the exact same gravitational acceleration benchmark and installation state. This makes the calibration of continuous curves using high-precision discrete data have strict physical significance, solving the compensation coupling error problem caused by inconsistent benchmarks in traditional "dual-temperature chamber" schemes.

[0105] Second, while ensuring high accuracy, this invention efficiently acquires continuous temperature characteristic curves. Through a single continuous temperature variation process, it simultaneously obtains dense continuous sampling data and high-precision calibration data for multiple discrete temperature points. Using this discrete high-precision data, the continuously acquired curves are corrected, ultimately resulting in a zero-bias-temperature compensation curve that possesses both continuous characteristics and a high-precision reference.

[0106] Third, this method improves overall testing efficiency and equipment utilization. It simultaneously calibrates two core parameters—zero bias and scaling factor—in a single, continuous test, avoiding the time required for sensor transfer between two devices. While achieving superior data quality (uniform benchmark, continuous curves), it reduces total equipment downtime, contributing to lower production costs.

[0107] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0108] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0109] Figure 8 A schematic diagram of the calibration device for an accelerometer provided in an embodiment of the present invention is shown. For ease of explanation, only the parts related to the embodiment of the present invention are shown, and are described in detail below: like Figure 8 As shown, a calibration device 8 for an accelerometer includes: The first acquisition module 81 is used to acquire the output value of the accelerometer in a stationary state when the temperature changes continuously within the target temperature range, and use it as the first zero bias. The second acquisition module 82 is used to acquire half of the sum of the output values ​​of the accelerometer before and after vertical rotation at multiple discrete temperature points within the target temperature range, as the second zero bias. The difference calculation module 83 is used to take the average value of the difference between the second zero bias and the corresponding first zero bias at each discrete temperature point as the zero bias value. The correction module 84 is used to add the zero deviation value to the first zero bias of the target temperature range, and use it as the zero bias after the accelerometer is calibrated.

[0110] This invention obtains a first zero bias by acquiring the output value when the temperature changes continuously in a static state, which has many data points but may have large deviations. The arithmetic mean of the output values ​​before and after vertical flipping eliminates the interference of the gravitational component caused by the tilt angle, and samples are only taken at a small number of discrete temperature points, resulting in a second zero bias with fewer data points but smaller deviations from the actual zero bias. Furthermore, based on the average difference between the second and first zero biases at the same temperature, the difference between the two zero biases is obtained and determined as the magnitude of the deviation of the first zero bias from the actual zero bias, i.e., the zero bias value. After correcting the first zero bias with many data points according to the zero bias value, a calibrated zero bias with many data points and smaller deviations is obtained.

[0111] Figure 9 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. For example... Figure 9 As shown, the electronic device 9 of this embodiment includes a processor 90 and a memory 91. The memory 91 stores a computer program 92. When the processor 90 executes the computer program 92, it implements the steps in the various method embodiments described above. Alternatively, when the processor 90 executes the computer program 92, it implements the functions of each module / unit in the various device embodiments described above.

[0112] For example, computer program 92 may be divided into one or more modules / units, which are stored in memory 91 and executed by processor 90 to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 92 in electronic device 9.

[0113] Electronic device 9 may include, but is not limited to, processor 90 and memory 91. Those skilled in the art will understand that... Figure 9 This is merely an example of electronic device 9 and does not constitute a limitation on electronic device 9. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device 9 may also include input / output devices, network access devices, buses, etc.

[0114] The processor 90 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0115] The memory 91 can be an internal storage unit of the electronic device 9, such as a hard disk or RAM. The memory 91 can also be an external storage device of the electronic device 9, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory 91 can include both internal and external storage units of the electronic device 9. The memory 91 is used to store the computer program 92 and other programs and data required by the electronic device 9. The memory 91 can also be used to temporarily store data that has been output or will be output.

[0116] For the sake of simplicity and clarity, only the above-described functional modules / units are used as examples. In practical applications, the functions described above can be assigned to different functional modules / units as needed. These modules / units can be implemented in hardware, software, or a combination of both.

[0117] This invention provides a calibration system, including the aforementioned electronic device; it also includes a temperature chamber without a turntable and a temperature chamber with a turntable for providing a temperature environment for an accelerometer.

[0118] This invention also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the methods described in the above-described method embodiments.

[0119] This invention also provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the methods described in the above-described method embodiments.

[0120] Computer programs include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. Computer-readable media can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0121] In the above embodiments, the descriptions of each embodiment have their own emphasis. Parts not detailed or described in a particular embodiment can be referred to in the relevant descriptions of other embodiments. Unless otherwise specified or in conflict with logic, the terminology and / or descriptions between different embodiments are consistent and can be referenced interchangeably. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0122] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for calibrating an accelerometer, characterized in that, include: Within the target temperature range, the output value of the accelerometer in a stationary state is obtained when the temperature changes continuously, and this value is used as the first zero bias. At multiple discrete temperature points within the target temperature range, half of the sum of the output values ​​of the accelerometer before and after vertical rotation is obtained as the second zero bias. The average of the differences between the second zero bias and the corresponding first zero bias at each discrete temperature point is taken as the zero bias value. The zero bias is added to the first zero bias of the target temperature range and used as the zero bias after calibration of the accelerometer.

2. The calibration method for an accelerometer as described in claim 1, characterized in that, At multiple discrete temperature points within the target temperature range, half of the sum of the output values ​​of the accelerometer before and after vertical rotation is obtained as the second zero bias, including: At multiple discrete temperature points within the target temperature range, the first direction output value of the accelerometer before vertical rotation and the second direction output value after vertical rotation are obtained. For any of the discrete temperature points, half of the sum of the first direction output value and the second direction output value is taken as the second zero bias at that discrete temperature point.

3. The calibration method for an accelerometer as described in claim 2, characterized in that, After acquiring the first direction output value of the accelerometer before vertical rotation and the second direction output value after vertical rotation at multiple discrete temperature points within the target temperature range, the method further includes: For any of the discrete temperature points, half of the difference between the output value in the first direction and the output value in the second direction is divided by the gravitational acceleration to obtain the scaling factor for that discrete temperature point.

4. The calibration method for an accelerometer as described in claim 2, characterized in that, At multiple discrete temperature points within the target temperature range, acquiring the first direction output value of the accelerometer before vertical rotation and the second direction output value after vertical rotation includes: At any of the discrete temperature points, the vertical direction is flipped multiple times and the output values ​​before and after the flip are collected. The average value of the output values ​​in each vertical direction is taken as the first direction output value of the accelerometer before it is flipped vertically. The average of the downward output values ​​in each vertical direction is taken as the second output value after the accelerometer is flipped vertically.

5. The calibration method for an accelerometer as described in claim 1, characterized in that, The average difference between the second zero bias and the corresponding first zero bias at each discrete temperature point is used as the zero bias value, including: The target temperature range is divided into multiple temperature zones; For any of the temperature ranges, the average difference between the second zero bias and the first zero bias of each discrete temperature point within the temperature range is taken as the zero bias value of the temperature range. Accordingly, the zero bias is added to the first zero bias of the target temperature range, and the resulting zero bias after accelerometer calibration includes: For any of the aforementioned temperature ranges, the first zero bias of the temperature range is added to the zero deviation value of the temperature range, which is used as the zero bias after calibration of the accelerometer in that temperature range.

6. The calibration method for an accelerometer as described in claim 1, characterized in that, The zero bias after accelerometer calibration is calculated by adding the first zero bias value to the zero bias value within the target temperature range. The first zero-bias temperature relationship is obtained based on the first zero-bias fitting of the target temperature range; Add the zero deviation value to the first zero-bias temperature relationship to obtain the zero bias after accelerometer calibration.

7. The calibration method for an accelerometer as described in claim 1, characterized in that, The zero bias after accelerometer calibration is calculated by adding the first zero bias value to the zero bias value within the target temperature range. Add the zero deviation value to the first zero bias at each temperature point within the target temperature range to obtain the corrected zero bias dataset; The corrected zero-bias temperature relationship was obtained by fitting the corrected zero-bias dataset and used as the zero-bias after calibration of the accelerometer.

8. A calibration device for an accelerometer, characterized in that, include: The first acquisition module is used to acquire the output value of the accelerometer in a stationary state when the temperature changes continuously within the target temperature range, and use it as the first zero bias. The second acquisition module is used to acquire half of the sum of the output values ​​of the accelerometer before and after vertical rotation at multiple discrete temperature points within the target temperature range, as the second zero bias. The difference calculation module is used to take the average of the difference between the second zero bias and the corresponding first zero bias at each discrete temperature point as the zero bias value. The correction module is used to add the zero deviation value to the first zero bias of the target temperature range, and use it as the zero bias after the accelerometer is calibrated.

9. An electronic device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the calibration method of the accelerometer as described in any one of claims 1 to 7.

10. A calibration system, comprising the electronic equipment as described in claim 9; further comprising a temperature chamber without a turntable and a temperature chamber with a turntable for providing a temperature environment for an accelerometer.

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