Wireless inclinometer self-correction method and system based on multi-sensor fusion

Abstract

The invention relates to the technical field of inclinometer real-time correction, in particular to a wireless inclinometer self-correction method and system based on multi-sensor fusion, and the method comprises the steps: carrying out the temperature compensation test of a wireless inclinometer, obtaining a temperature compensation model, carrying out the parameter measurement of the wireless inclinometer, obtaining a three-axis acceleration set, a three-axis angular velocity set and a measurement temperature, and carrying out the real-time correction of the inclinometer. Performing temperature compensation on the three-axis acceleration set by using a measured temperature and temperature compensation model to obtain a target acceleration set, if a static state judgment result is a non-static state, performing angular velocity attitude calculation based on the original attitude angle deviation set and the three-axis angular velocity set to obtain corrected inclinometry data, and if the static state judgment result is a non-static state, performing angular velocity attitude calculation based on the original attitude angle deviation set and the three-axis angular velocity set to obtain corrected inclinometry data; and if so, obtaining corrected inclinometry data and a current attitude angle deviation group. According to the invention, the measurement precision and stability of the inclinometer in variable-temperature and dynamic environments can be improved, and the accumulative error of attitude estimation is reduced.

Description

Technical Field

[0001] This invention relates to the field of real-time inclinometer calibration technology, and in particular to a self-calibration method and system for wireless inclinometers based on multi-sensor fusion. Background Technology

[0002] In fields such as geological exploration, structural health monitoring, and attitude control of industrial equipment, the measurement accuracy of wireless inclinometers is crucial. Since the ambient temperature in these application scenarios often fluctuates, and the equipment itself may be in a state of alternating static and dynamic operation, ensuring that the inclinometer can output stable and accurate attitude data under various complex working conditions has become a key technical challenge.

[0003] Traditional techniques typically rely on a single sensor for attitude calculation or employ simple static calibration. This approach has significant drawbacks. On the one hand, it is difficult to overcome the measurement drift caused by temperature changes in the sensor. On the other hand, it cannot effectively distinguish between the stationary and moving states of the device, thereby introducing large errors under dynamic interference and leading to a decrease in attitude tracking accuracy. Summary of the Invention

[0004] This invention provides a self-calibration method for a wireless inclinometer based on multi-sensor fusion and a computer-readable storage medium. Its main purpose is to improve the measurement accuracy and stability of the inclinometer under varying temperature and dynamic environments, and to reduce the cumulative error of attitude estimation.

[0005] To achieve the above objectives, the present invention provides a self-calibration method for a wireless inclinometer based on multi-sensor fusion, comprising:

[0006] Construct a wireless inclinometer, which includes a three-axis accelerometer, a gyroscope, and a temperature sensor;

[0007] Temperature compensation tests were conducted on the wireless inclinometer to obtain a temperature compensation model, which includes a set of compensation coefficient variation curves.

[0008] Parameters were measured using a wireless inclinometer to obtain triaxial acceleration sets, triaxial angular velocity sets, and measured temperature.

[0009] The original attitude angle deviation set of the gyroscope is obtained, and the temperature compensation of the three-axis acceleration set is performed using the measured temperature and temperature compensation model to obtain the target acceleration set.

[0010] The stationary state is determined based on the target acceleration set, and the stationary state determination result is obtained, which is either stationary or non-stationary.

[0011] If the static state determination result is a non-static state, then the angular velocity attitude is calculated based on the original attitude angle deviation set and the three-axis angular velocity set to obtain the corrected inclination measurement data;

[0012] If the static state determination result is static, then the corrected inclinometer data and the current attitude angle deviation group are obtained based on the target acceleration set and the original attitude angle deviation group.

[0013] The self-calibration of the wireless inclinometer based on multi-sensor fusion is completed based on the calibrated inclinometer data and the current attitude angle deviation group.

[0014] Optionally, the temperature compensation test of the wireless inclinometer to obtain a temperature compensation model includes:

[0015] The ambient temperature range is determined based on the wireless inclinometer. Discrete temperatures are selected within the ambient temperature range to obtain a discrete ambient temperature set, which includes multiple discrete ambient temperatures.

[0016] A temperature compensation device is constructed, comprising: a turntable base, a temperature control box, and a wireless inclinometer. The turntable base is installed at the center of the temperature control box, and the wireless inclinometer is installed on the turntable surface of the turntable base.

[0017] Discrete ambient temperatures are extracted sequentially from the discrete ambient temperature set, and the extracted discrete ambient temperatures are recorded as the ambient temperatures to be compensated.

[0018] Temperature compensation is performed on the wireless inclinometer using a temperature compensation device and the ambient temperature to be compensated, and temperature compensation data is obtained. The temperature compensation data includes: a triaxial compensation coefficient set and a drift compensation coefficient set.

[0019] By summarizing the temperature compensation data corresponding to each discrete ambient temperature, a temperature compensation dataset is obtained.

[0020] A temperature compensation model is obtained by fitting the temperature compensation dataset and the discrete ambient temperature set.

[0021] Optionally, the step of using a temperature compensation device and the ambient temperature to be compensated to perform temperature compensation on the wireless inclinometer to obtain temperature compensation data includes:

[0022] The wireless inclinometer is fixed to the rotating base of the temperature compensation device to obtain a fixed inclinometer.

[0023] Based on the ambient temperature to be compensated and the temperature control box, the temperature environment of the fixed inclinometer is regulated to obtain the temperature-controlled inclinometer.

[0024] Set up a set of inclinometer compensation positions, which includes multiple inclinometer compensation positions;

[0025] For each inclinometer compensation position in the inclinometer compensation position set, the actual acceleration is calculated to obtain the actual triaxial acceleration set. The actual triaxial acceleration set includes multiple actual triaxial acceleration groups, and the actual triaxial acceleration groups correspond one-to-one with the inclinometer compensation positions.

[0026] The temperature-controlled inclinometer is rotated using a turntable base to obtain the test inclinometer.

[0027] Based on the triaxial accelerometer and the inclinometer compensation position set in the wireless inclinometer, the acceleration of the test inclinometer is collected to obtain multiple sets of measured triaxial accelerations. Each set of test triaxial accelerations includes multiple sets of test triaxial accelerations.

[0028] Temperature compensation data is obtained by performing temperature compensation calculations based on multiple sets of measured triaxial accelerations and actual triaxial acceleration sets.

[0029] Optionally, the step of performing temperature compensation calculations based on multiple sets of measured triaxial accelerations and the actual triaxial acceleration set to obtain temperature compensation data includes:

[0030] For each of the multiple sets of measured triaxial accelerations, perform the following operation:

[0031] A set of temperature compensation equations is constructed based on the measured triaxial acceleration set and the actual triaxial acceleration set. The set of temperature compensation equations includes multiple temperature compensation equations, and each temperature compensation equation includes: a set of triaxial coefficients to be compensated and a set of drift coefficients to be compensated.

[0032] The temperature compensation equation set is obtained by summarizing the temperature compensation equation set corresponding to each set of triaxial acceleration measurements;

[0033] The temperature compensation data is obtained by solving the set of temperature compensation equations for the triaxial coefficients to be compensated and the drift coefficients to be compensated.

[0034] Optionally, the step of fitting the temperature compensation model based on the temperature compensation dataset and the discrete ambient temperature set includes:

[0035] A set of parameters to be compensated is set based on a temperature compensation dataset, wherein the set of parameters to be compensated includes multiple parameters to be compensated;

[0036] For each parameter to be compensated in the parameter set, perform the following operation:

[0037] Based on the parameter to be compensated, extract a set of similar compensation coefficients from the temperature compensation dataset. The set of similar compensation coefficients includes multiple similar compensation coefficients, and the similar compensation coefficients correspond to the parameter to be compensated.

[0038] Curve fitting is performed based on a set of similar compensation coefficients and a set of discrete ambient temperatures to obtain a curve of the change in compensation coefficients. The horizontal axis of the curve of the change in compensation coefficients represents the discrete ambient temperature, and the vertical axis of the curve of the change in compensation coefficients represents the similar compensation coefficients.

[0039] Summarize the compensation coefficient change curves corresponding to each parameter to be compensated to obtain a set of compensation coefficient change curves;

[0040] A temperature compensation model is constructed based on a set of compensation coefficient variation curves.

[0041] Optionally, the step of using a measured temperature and a temperature compensation model to perform temperature compensation on the triaxial acceleration set to obtain the target acceleration set includes:

[0042] Perform the following operation on each triaxial acceleration group in the triaxial acceleration group set:

[0043] Based on the measured temperature, coordinate points are indexed in the set of compensation coefficient change curves of the temperature compensation model to obtain the target compensation coefficient coordinate point set.

[0044] Identify the target compensation coefficient set based on the target compensation coefficient coordinate point set;

[0045] The triaxial acceleration set is compensated using the target compensation coefficient set to obtain the target acceleration set;

[0046] Summarize the target acceleration groups corresponding to each triaxial acceleration group to obtain the target acceleration group set.

[0047] Optionally, the step of determining the stationary state based on the target acceleration set to obtain the stationary state determination result includes:

[0048] Coaxial data is extracted based on the target acceleration set to obtain multiple coaxial acceleration sets;

[0049] Variance calculation is performed on multiple coaxial acceleration sets to obtain multiple coaxial standard deviations, and mean calculation is performed on multiple coaxial standard deviations to obtain the coaxial standard mean deviation;

[0050] If the standard mean deviation of the coaxial line is greater than the preset static standard deviation, the non-static state is recorded as the static state determination result.

[0051] If the standard mean deviation of the coaxial axis is not greater than the standard deviation of the stationary state, then the stationary state is recorded as the stationary state determination result.

[0052] Optionally, the step of calculating angular velocity attitude based on the original attitude angle deviation set and the three-axis angular velocity set to obtain corrected inclinometer data includes:

[0053] The three-axis angular velocity set is corrected based on the original attitude angle deviation set to obtain the corrected angular velocity set.

[0054] For each corrected angular velocity group in the corrected angular velocity group set, perform the following operation:

[0055] The angular velocity acquisition interval is obtained, and the product of the angular velocity acquisition interval and the corrected angular velocity group is calculated to obtain the attitude angle change value group.

[0056] Summarize each group of attitude angle changes to obtain a set of attitude angle change groups;

[0057] The attitude angle change set is coaxially accumulated to obtain the current angle change set. Based on the current angle change set and the preset historical attitude angle set, the current attitude is estimated to obtain the estimated attitude angle set.

[0058] The estimated attitude angle set is denoted as the corrected inclinometer data.

[0059] Optionally, the step of obtaining the corrected inclinometer data and the current attitude angle deviation group based on the target acceleration set and the original attitude angle deviation group includes:

[0060] Identify the current acceleration group in the target acceleration group set;

[0061] Based on the current acceleration set, the attitude of the inclinometer is calculated to obtain the current attitude angle set, and the current attitude angle set is recorded as the corrected inclinometer data.

[0062] The current angular velocity group is identified in the three-axis angular velocity group set. Based on the current angular velocity group and the current attitude angle group, the original attitude angle deviation group is iteratively updated to obtain the current attitude angle deviation group.

[0063] To achieve the above objectives, the present invention also provides a self-calibration system for a wireless inclinometer based on multi-sensor fusion, comprising:

[0064] The compensation model construction module is used to construct a wireless inclinometer, which includes a three-axis accelerometer, a gyroscope, and a temperature sensor. Temperature compensation tests are performed on the wireless inclinometer to obtain a temperature compensation model, which includes a set of compensation coefficient variation curves.

[0065] The acceleration parameter measurement module is used to measure parameters using a wireless inclinometer to obtain a triaxial acceleration set, a triaxial angular velocity set, and a measured temperature. It also obtains the original attitude angle deviation set of the gyroscope and uses the measured temperature and temperature compensation model to perform temperature compensation on the triaxial acceleration set to obtain the target acceleration set.

[0066] The stationary state determination module is used to determine the stationary state based on the target acceleration set and obtain the stationary state determination result, which is either stationary or non-stationary.

[0067] The attitude deviation calculation module is used to perform angular velocity attitude calculation based on the original attitude angle deviation set and the three-axis angular velocity set to obtain corrected inclinometer data. If the static state determination result is static, then the corrected inclinometer data and the current attitude angle deviation set are obtained based on the target acceleration set and the original attitude angle deviation set.

[0068] To address the above problems, the present invention also provides an electronic device, the electronic device comprising:

[0069] Memory, storing at least one instruction;

[0070] The processor executes the instructions stored in the memory to implement the self-calibration method for wireless inclinometers based on multi-sensor fusion described above.

[0071] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the aforementioned self-calibration method for a wireless inclinometer based on multi-sensor fusion.

[0072] To address the problems described in the background art, this invention first performs temperature compensation testing on a wireless inclinometer to obtain a temperature compensation model. This step establishes the temperature compensation model through discrete temperature testing and curve fitting. Compared to the simple calibration in existing technologies that ignore the influence of temperature, this effectively suppresses sensor drift caused by temperature changes, improving the measurement accuracy and reliability of the inclinometer in variable temperature environments. Next, the original attitude angle deviation set of the gyroscope is obtained, and the temperature compensation model is used to perform temperature compensation on the three-axis acceleration set to obtain the target acceleration set. This step applies the temperature compensation model to correct the acceleration data in real time, overcoming the acceleration measurement deviation caused by temperature fluctuations in existing methods. This provides a more accurate input for multi-sensor fusion and reduces the cumulative error in subsequent attitude calculations. Furthermore, this invention determines the stationary state based on the target acceleration set, obtaining the stationary state determination result. This step uses the mean of the coaxial standard deviation for stationary state determination. Compared to traditional fixed threshold methods, the stationary state determination method improves the accuracy of state recognition and avoids attitude calculation errors caused by misjudgment. If the stationary state determination result is a non-stationary state, angular velocity attitude calculation is performed based on the original attitude angle deviation set and the three-axis angular velocity set to obtain corrected inclinometer data. In the non-stationary state, attitude tracking is achieved through the integral of the angular velocity with deviation correction, combining the dynamic response advantage of the gyroscope, thereby reducing the accumulation of drift error in traditional gyroscope integration and improving the attitude estimation accuracy in motion. If the stationary state determination result is a stationary state, corrected inclinometer data and the current attitude angle deviation set are obtained based on the target acceleration set and the original attitude angle deviation set. In the stationary state, the gyroscope deviation is calibrated using accelerometer data, achieving real-time self-correction. Compared to existing technologies that rely on external references or periodic calibration, this enhances the stability and autonomy of the wireless inclinometer in long-term operation. Therefore, this invention can improve the measurement accuracy and stability of the inclinometer in variable temperature and dynamic environments and reduce the cumulative error of attitude estimation. Attached Figure Description

[0073] Figure 1 This is a flowchart illustrating a self-calibration method for a wireless inclinometer based on multi-sensor fusion, provided in an embodiment of the present invention.

[0074] Figure 2 A functional block diagram of a wireless inclinometer self-calibration system based on multi-sensor fusion provided in an embodiment of the present invention;

[0075] Figure 3 This is a schematic diagram of the structure of an electronic device that implements the self-calibration method of a wireless inclinometer based on multi-sensor fusion, according to an embodiment of the present invention.

[0076] Explanation of reference numerals in the attached figures:

[0077] 10. Electronic device; 11. Processor; 12. Memory; 13. Bus.

[0078] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0079] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0080] This application provides a self-calibration method for a wireless inclinometer based on multi-sensor fusion. The execution entity of this self-calibration method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the self-calibration method for a wireless inclinometer based on multi-sensor fusion can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0081] Reference Figure 1 The diagram shown is a flowchart illustrating a self-calibration method for a wireless inclinometer based on multi-sensor fusion according to an embodiment of the present invention. In this embodiment, the self-calibration method for a wireless inclinometer based on multi-sensor fusion includes:

[0082] S1. Construct a wireless inclinometer, which includes a three-axis accelerometer, a gyroscope, and a temperature sensor.

[0083] As is clear, the wireless inclinometer refers to an integrated electronic device used to measure the attitude and tilt angle of an object. This wireless inclinometer includes a three-axis accelerometer, a gyroscope, and a temperature sensor. The three-axis accelerometer is a sensor capable of simultaneously measuring acceleration along three mutually perpendicular axes (x-axis, y-axis, and z-axis), such as a MEMS three-axis accelerometer. The gyroscope is a sensor used to measure the angular velocity of an object rotating around three mutually perpendicular axes, such as a MEMS gyroscope. The temperature sensor is a sensor used to monitor the internal temperature of the wireless inclinometer, such as a digital temperature sensor. The wireless inclinometer also includes a wireless transmission unit, which is a communication module for remote data transmission, used to send data collected by the wireless inclinometer (such as subsequent correction inclinometer data) to an external receiving device, such as a LoRa module, Wi-Fi module, or Bluetooth module.

[0084] S2. Perform temperature compensation tests on the wireless inclinometer to obtain a temperature compensation model, which includes a set of compensation coefficient variation curves.

[0085] Understandably, the temperature compensation model refers to a database consisting of a set of compensation coefficient variation curves. This temperature compensation model is used to perform temperature compensation on the data collected by the triaxial accelerometer in the wireless inclinometer (such as the subsequent triaxial accelerometer set).

[0086] In detail, the temperature compensation test of the wireless inclinometer to obtain a temperature compensation model includes:

[0087] The ambient temperature range is determined based on the wireless inclinometer. Discrete temperatures are selected within the ambient temperature range to obtain a discrete ambient temperature set, which includes multiple discrete ambient temperatures.

[0088] A temperature compensation device is constructed, comprising: a turntable base, a temperature control box, and a wireless inclinometer. The turntable base is installed at the center of the temperature control box, and the wireless inclinometer is installed on the turntable surface of the turntable base.

[0089] Discrete ambient temperatures are extracted sequentially from the discrete ambient temperature set, and the extracted discrete ambient temperatures are recorded as the ambient temperatures to be compensated.

[0090] Temperature compensation is performed on the wireless inclinometer using a temperature compensation device and the ambient temperature to be compensated, and temperature compensation data is obtained. The temperature compensation data includes: a triaxial compensation coefficient set and a drift compensation coefficient set.

[0091] By summarizing the temperature compensation data corresponding to each discrete ambient temperature, a temperature compensation dataset is obtained.

[0092] A temperature compensation model is obtained by fitting the temperature compensation dataset and the discrete ambient temperature set.

[0093] It should be explained that the operating ambient temperature range refers to the numerical range of the ambient temperature in the application scenario of the wireless inclinometer. For example, in a downhole measurement application in an oil field, the ambient temperature may vary between -10℃ and 50℃, so the operating ambient temperature range is -10℃ to 50℃. The discrete ambient temperature set refers to the set of temperature points selected from the operating ambient temperature range at certain intervals. Discrete temperature selection for the operating ambient temperature range means selecting a number of test temperature points at certain temperature intervals (e.g., 10℃) within the continuous operating ambient temperature range to obtain the discrete ambient temperature set. For example, in the range of -10℃ to 50℃, selecting a point every 10℃ results in the discrete ambient temperature set {-10℃, 0℃, 10℃, 20℃, 30℃, 40℃, 50℃}. The temperature compensation device refers to an experimental apparatus used to obtain the error relationship between the readings of the triaxial accelerometer and the actual acceleration of a wireless inclinometer by changing its attitude under a controlled temperature environment. The turntable base is a rotatable platform with controllable rotation angle and rate, used to rotate the wireless inclinometer to various test attitudes (i.e., inclinometer compensation positions). The temperature control chamber is a sealed enclosure that controls the internal ambient temperature, providing a stable temperature for the wireless inclinometer to be compensated. The temperature compensation data refers to a set of triaxial compensation coefficients and drift compensation coefficients; the methods for obtaining these coefficients will be described in subsequent embodiments.

[0094] In detail, the process of using a temperature compensation device and the ambient temperature to compensate for the temperature of the wireless inclinometer, and obtaining temperature compensation data, includes:

[0095] The wireless inclinometer is fixed to the rotating base of the temperature compensation device to obtain a fixed inclinometer.

[0096] Based on the ambient temperature to be compensated and the temperature control box, the temperature environment of the fixed inclinometer is regulated to obtain the temperature-controlled inclinometer.

[0097] Set up a set of inclinometer compensation positions, which includes multiple inclinometer compensation positions;

[0098] For each inclinometer compensation position in the inclinometer compensation position set, the actual acceleration is calculated to obtain the actual triaxial acceleration set. The actual triaxial acceleration set includes multiple actual triaxial acceleration groups, and the actual triaxial acceleration groups correspond one-to-one with the inclinometer compensation positions.

[0099] The temperature-controlled inclinometer is rotated using a turntable base to obtain the test inclinometer.

[0100] Based on the triaxial accelerometer and the inclinometer compensation position set in the wireless inclinometer, the acceleration of the test inclinometer is collected to obtain multiple sets of measured triaxial accelerations. Each set of test triaxial accelerations includes multiple sets of test triaxial accelerations.

[0101] Temperature compensation data is obtained by performing temperature compensation calculations based on multiple sets of measured triaxial accelerations and actual triaxial acceleration sets.

[0102] Understandably, the fixed inclinometer refers to a wireless inclinometer fixed to a rotating base of a turntable. The turntable base is fixed by using a clamp to mount the wireless inclinometer on the rotating surface of the turntable base, ensuring no relative movement between the wireless inclinometer and the turntable base. The temperature-controlled inclinometer refers to a fixed inclinometer after temperature environment regulation. Temperature environment regulation of the fixed inclinometer based on the ambient temperature to be compensated and the temperature control box means setting the temperature in the temperature control box to the ambient temperature to be compensated, and denoting the fixed inclinometer in the temperature control box after temperature setting as the temperature-controlled inclinometer. The inclinometer compensation position set refers to a collection of multiple inclinometer compensation positions. The inclinometer compensation position refers to a manually set attitude position of the wireless inclinometer, such as a horizontal position, a vertical position, or a position at a 45-degree angle to both the horizontal and vertical. The true triaxial acceleration set refers to a collection of multiple true triaxial acceleration sets. Specifically, a true triaxial acceleration set refers to the set of triaxial accelerations (acceleration on the x-axis, y-axis, and z-axis) of a wireless inclinometer when the inclinometer compensation position is stationary. This true triaxial acceleration is determined by the components of the wireless inclinometer's own gravity on the three coordinate axes. For example, if the inclinometer compensation position is horizontal, the true triaxial accelerations of the wireless inclinometer are: the true accelerations on the x-axis and y-axis are both 0, and the true acceleration on the z-axis is the gravitational acceleration. This true triaxial acceleration set serves as a reference value and is compared with the actual measured values ​​of subsequent triaxial accelerometers (i.e., the measured triaxial acceleration set) to calculate the temperature compensation data.

[0103] Furthermore, the test inclinometer refers to a rotating temperature-controlled inclinometer. The rotation operation using a turntable base refers to controlling the turntable base to rotate sequentially to each designated inclinometer compensation position according to the inclinometer compensation position set and hold it briefly, so that a triaxial accelerometer can measure the set of triaxial accelerations at that compensation position. The set of triaxial accelerations refers to a collection of multiple test triaxial acceleration sets, where each test triaxial acceleration set refers to the set of triaxial accelerations detected by the triaxial accelerometer at a certain inclinometer compensation position during rotation, and the direction of these test triaxial accelerations is the same as the aforementioned actual triaxial accelerations. The above-mentioned method for acquiring acceleration data from the test inclinometer based on the triaxial accelerometer and inclinometer compensation position set in the wireless inclinometer is as follows: when the turntable rotating base rotates the test inclinometer and stabilizes it at a certain inclinometer compensation position, the test triaxial acceleration set output by the triaxial accelerometer at this time is read and recorded through its built-in wireless transmission unit. All the test triaxial acceleration sets at the inclinometer compensation positions constitute a test triaxial acceleration set. The above operation is repeated to obtain multiple test triaxial acceleration sets.

[0104] In detail, the temperature compensation calculation based on multiple sets of measured triaxial accelerations and the actual triaxial acceleration sets to obtain temperature compensation data includes:

[0105] For each of the multiple sets of measured triaxial accelerations, perform the following operation:

[0106] A set of temperature compensation equations is constructed based on the measured triaxial acceleration set and the actual triaxial acceleration set. The set of temperature compensation equations includes multiple temperature compensation equations, and each temperature compensation equation includes: a set of triaxial coefficients to be compensated and a set of drift coefficients to be compensated.

[0107] The temperature compensation equation set is obtained by summarizing the temperature compensation equation set corresponding to each set of triaxial acceleration measurements;

[0108] The temperature compensation data is obtained by solving the set of temperature compensation equations for the triaxial coefficients to be compensated and the drift coefficients to be compensated.

[0109] It should be explained that the temperature compensation equation set refers to a collection of multiple temperature compensation equations. Each temperature compensation equation is a transformation equation between a measured triaxial acceleration set and its corresponding real triaxial acceleration set. The measured triaxial acceleration set and the real triaxial acceleration set corresponding to the same temperature compensation equation correspond to the same inclinometer compensation position. The triaxial coefficient set to be compensated refers to a collection of multiple triaxial coefficients to be compensated. These coefficients are used to correct errors such as sensitivity and non-orthogonality of each axis of the triaxial accelerometer. The drift coefficient set to be compensated refers to a collection of multiple drift coefficients to be compensated. These drift coefficients are used to correct the zero-bias error of each axis of the triaxial accelerometer. The form of the above temperature compensation equations is:

[0110]

[0111] in, , and These represent the x-axis acceleration, y-axis acceleration, and z-axis acceleration in a real triaxial acceleration set, respectively. , and These represent the x-axis acceleration, y-axis acceleration, and z-axis acceleration measured in the triaxial acceleration group. , , , , , , , and All represent the triaxial coefficients to be compensated in the triaxial coefficient group to be compensated. , and All represent the drift coefficients to be compensated in the set of drift coefficients to be compensated. The above-mentioned solution of the set of temperature compensation equations for the set of triaxial coefficients to be compensated and the set of drift coefficients to be compensated refers to the following: applying mathematical optimization algorithms such as the least squares method to perform fitting calculations, thereby obtaining the optimal solution of the set of triaxial coefficients to be compensated (i.e., the triaxial compensation coefficient set) and the optimal solution of the set of drift coefficients to be compensated (i.e., the drift compensation coefficient set). Summarizing the set of triaxial compensation coefficients and the set of drift compensation coefficients, the temperature compensation data is obtained.

[0112] In detail, the step of fitting the temperature compensation model based on the temperature compensation dataset and the discrete ambient temperature set to obtain the temperature compensation model includes:

[0113] A set of parameters to be compensated is set based on a temperature compensation dataset, wherein the set of parameters to be compensated includes multiple parameters to be compensated;

[0114] For each parameter to be compensated in the parameter set, perform the following operation:

[0115] Based on the parameter to be compensated, extract a set of similar compensation coefficients from the temperature compensation dataset. The set of similar compensation coefficients includes multiple similar compensation coefficients, and the similar compensation coefficients correspond to the parameter to be compensated.

[0116] Curve fitting is performed based on a set of similar compensation coefficients and a set of discrete ambient temperatures to obtain a curve of the change in compensation coefficients. The horizontal axis of the curve of the change in compensation coefficients represents the discrete ambient temperature, and the vertical axis of the curve of the change in compensation coefficients represents the similar compensation coefficients.

[0117] Summarize the compensation coefficient change curves corresponding to each parameter to be compensated to obtain a set of compensation coefficient change curves;

[0118] A temperature compensation model is constructed based on a set of compensation coefficient variation curves.

[0119] It should be explained that the set of parameters to be compensated refers to a collection of multiple parameters to be compensated. Here, a parameter to be compensated refers to a triaxial compensation coefficient or drift compensation coefficient appearing in the temperature compensation data set, for example, in the temperature compensation equation mentioned above. , , , Equal coefficients. The set of similar compensation coefficients refers to a collection of similar compensation coefficients corresponding to multiple different discrete ambient temperatures. These similar compensation coefficients are triaxial compensation coefficients or drift compensation coefficients that have a coefficient position relative to the parameter to be compensated. For example, a temperature compensation dataset is: {at -10℃: { 1.02, : 0.01, ...}; at 0℃: { 1.015 : 0.008, ...}; at 10℃: { 1.018 : 0.009, ...}}, where, regarding the parameter to be compensated The set of similar compensation coefficients is: {1.02, 1.015, 1.018}. The compensation coefficient variation curve refers to the curve representing the relationship between the similar compensation coefficients and the discrete ambient temperature. The above-mentioned construction of a temperature compensation model based on the set of compensation coefficient variation curves refers to storing the set of compensation coefficient variation curves; the stored database is the temperature compensation model.

[0120] S3. Parameters are measured using a wireless inclinometer to obtain triaxial acceleration sets, triaxial angular velocity sets, and measured temperature.

[0121] It is clear that the aforementioned triaxial acceleration set refers to a collection of multiple triaxial acceleration sets measured by the triaxial accelerometer in the wireless inclinometer during a certain period of time in practical applications. The triaxial directions of this triaxial acceleration set are the same as those of the aforementioned actual triaxial acceleration set and the measured triaxial acceleration set. The aforementioned triaxial angular velocity set refers to a collection of multiple triaxial angular velocity sets measured by the gyroscope in the wireless inclinometer during a certain period of time in practical applications. The triaxial angular velocity set refers to the numerical set of angular velocity values ​​of an object rotating around the x, y, and z coordinate axes measured by the gyroscope. The three axial directions (i.e., x-axis, y-axis, and z-axis) of this triaxial angular velocity are the same as the three axial directions of the triaxial acceleration set. The aforementioned measured temperature refers to the average ambient temperature measured by the temperature sensor in the wireless inclinometer during a certain period of time in practical applications.

[0122] S4. Obtain the original attitude angle deviation set of the gyroscope, and use the measured temperature and temperature compensation model to perform temperature compensation on the triaxial acceleration set to obtain the target acceleration set.

[0123] It should be explained that the original attitude angle deviation set refers to the current attitude angle deviation set of the gyroscope during the previous parameter measurement. That is, the original attitude angle deviation set and the current attitude angle deviation set iterate over each other. The calculation method of the current attitude angle deviation set will be explained in subsequent embodiments. The aforementioned original attitude angle deviation set represents the estimated cumulative error of the attitude angles (such as pitch, roll, and yaw angles) caused by drift and other factors during the previous parameter measurement cycle. This original attitude angle deviation set includes the original attitude angle deviations corresponding to the three axes. The target acceleration set refers to the three-axis acceleration set after temperature compensation.

[0124] In detail, the process of using a measured temperature and a temperature compensation model to perform temperature compensation on the triaxial acceleration set to obtain the target acceleration set includes:

[0125] Perform the following operation on each triaxial acceleration group in the triaxial acceleration group set:

[0126] Based on the measured temperature, coordinate points are indexed in the set of compensation coefficient change curves of the temperature compensation model to obtain the target compensation coefficient coordinate point set.

[0127] Identify the target compensation coefficient set based on the target compensation coefficient coordinate point set;

[0128] The triaxial acceleration set is compensated using the target compensation coefficient set to obtain the target acceleration set;

[0129] Summarize the target acceleration groups corresponding to each triaxial acceleration group to obtain the target acceleration group set.

[0130] It should be explained that the target compensation coefficient coordinate point set refers to a collection of multiple target compensation coefficient coordinate points, where each target compensation coefficient coordinate point refers to the coordinate point corresponding to the measured temperature on a certain compensation coefficient variation curve. The specific steps for indexing coordinate points based on the measured temperature within the compensation coefficient variation curve set of the temperature compensation model are as follows: Extract the compensation coefficient variation curves sequentially from the set; query the coordinate point whose horizontal axis is the measured temperature within the compensation coefficient variation curve; this coordinate point is the target compensation coefficient coordinate point; summarize these target compensation coefficient coordinate points to obtain the target compensation coefficient coordinate point set. The target compensation coefficient set refers to a collection of multiple target compensation coefficients, where each target compensation coefficient refers to the vertical coordinate value of a target compensation coefficient coordinate point. The above-mentioned use of the target compensation coefficient set to compensate the triaxial acceleration group, obtaining the target acceleration group, refers to: substituting the target compensation coefficient set and the triaxial acceleration group into the above-mentioned temperature compensation equation, where the target compensation coefficient set is substituted into the position of the triaxial coefficient group to be compensated and the drift coefficient group to be compensated in the temperature compensation equation. The triaxial acceleration group is substituted into the position of the measured triaxial acceleration group in the temperature compensation equation. The acceleration set output by the temperature compensation equation after substitution is the target acceleration set.

[0131] S5. Determine the stationary state based on the target acceleration set to obtain the stationary state determination result, which is either stationary or non-stationary.

[0132] It is clear that the static state determination result refers to the judgment result obtained after static state determination. In this case, static state means that the wireless inclinometer is in a static state, and non-static state means that the wireless inclinometer is not in a static state.

[0133] In detail, the step of determining the stationary state based on the target acceleration set to obtain the stationary state determination result includes:

[0134] Coaxial data is extracted based on the target acceleration set to obtain multiple coaxial acceleration sets;

[0135] Variance calculation is performed on multiple coaxial acceleration sets to obtain multiple coaxial standard deviations, and mean calculation is performed on multiple coaxial standard deviations to obtain the coaxial standard mean deviation;

[0136] If the standard mean deviation of the coaxial line is greater than the preset static standard deviation, the non-static state is recorded as the static state determination result.

[0137] If the standard mean deviation of the coaxial axis is not greater than the standard deviation of the stationary state, then the stationary state is recorded as the stationary state determination result.

[0138] It should be explained that the coaxial acceleration set refers to a collection of accelerations representing the same coordinate axis. Specifically, coaxial data extraction based on the target acceleration set means extracting the acceleration values ​​corresponding to the same coordinate axis from each target acceleration group within the target acceleration set, thus forming three independent coaxial acceleration sets for the X-axis, Y-axis, and Z-axis. For example, if a target acceleration set is {(1.02, 0.11, 9.85), (0.99, 0.08, 9.87), (1.01, 0.10, 9.86)}, then the coaxial acceleration set for the x-axis is {1.02, 0.99, 1.01}. The coaxial standard deviation refers to the standard deviation of a certain coaxial acceleration set. The coaxial standard mean deviation refers to the average of multiple coaxial standard deviations. The static standard deviation refers to a pre-set empirical threshold used to determine whether the wireless inclinometer is in a static state. When the coaxial standard deviation is greater than the static standard deviation, it indicates that the wireless inclinometer is not in a static state. The static standard deviation can be set based on experiments with a triaxial accelerometer in a static state, for example, it can be set to 0.05 m / s².

[0139] S6. If the static state determination result is a non-static state, then the angular velocity attitude is calculated based on the original attitude angle deviation group and the three-axis angular velocity group to obtain the corrected inclination measurement data.

[0140] It is clear that the corrected inclinometer data refers to the attitude angle data (such as pitch angle, roll angle, etc.) detected by the wireless inclinometer after correction. During the operation of the wireless inclinometer, it may be subject to dynamic interference such as construction vibration and vehicle traffic. At this time, the wireless inclinometer is in motion. In this operating state, the value measured by the triaxial accelerometer includes the combination of motion acceleration and gravitational acceleration, and it is impossible to accurately separate the gravitational component used for attitude calculation, which reduces the accuracy of the triaxial accelerometer. Therefore, the data measured by the gyroscope (i.e., the triaxial angular velocity set) can be integrated to calculate the attitude change. However, due to the zero-point drift and temperature drift of the gyroscope, the attitude angle calculated by the gyroscope will accumulate errors over time. Therefore, when the wireless inclinometer is in a stationary state, the data measured by the triaxial accelerometer in this stationary state can be used to calibrate the gyroscope in real time (such as the subsequent step of obtaining the current attitude angle deviation set in a stationary state), thereby correcting the attitude angle deviation of the gyroscope and suppressing the accumulation of errors.

[0141] In detail, the step of calculating angular velocity attitude based on the original attitude angle deviation set and the three-axis angular velocity set to obtain corrected inclinometer data includes:

[0142] The three-axis angular velocity set is corrected based on the original attitude angle deviation set to obtain the corrected angular velocity set.

[0143] For each corrected angular velocity group in the corrected angular velocity group set, perform the following operation:

[0144] The angular velocity acquisition interval is obtained, and the product of the angular velocity acquisition interval and the corrected angular velocity group is calculated to obtain the attitude angle change value group.

[0145] Summarize each group of attitude angle changes to obtain a set of attitude angle change groups;

[0146] The attitude angle change set is coaxially accumulated to obtain the current angle change set. Based on the current angle change set and the preset historical attitude angle set, the current attitude is estimated to obtain the estimated attitude angle set.

[0147] The estimated attitude angle set is denoted as the corrected inclinometer data.

[0148] It should be explained that the corrected angular velocity set refers to the corrected three-axis angular velocity set. The specific steps of the correction are as follows: extract the three-axis angular velocity sets sequentially from the three-axis angular velocity set, add the x-axis, y-axis, and z-axis angular velocities from the original attitude angle deviation set to the x-axis, y-axis, and z-axis angular velocities from the three-axis angular velocity sets, respectively. The result is the corrected angular velocity set. Summarize this corrected angular velocity set to obtain the corrected angular velocity set. The angular velocity acquisition interval refers to the acquisition time interval between two adjacent three-axis angular velocity sets acquired by the gyroscope. The attitude angle change value set refers to the collection of multiple attitude angle change values. The attitude angle change value is the product of a certain corrected angular velocity and the angular velocity acquisition interval. This attitude angle change value represents the small angle (in radians) that the wireless inclinometer rotates around the x, y, or z axis during the angular velocity acquisition interval.

[0149] Furthermore, the current angle change group refers to the set of total angle deviations on the three coordinate axes obtained after coaxial angle accumulation. This current angle change group represents the cumulative error of the gyroscope on the three coordinate axes during the time period of measuring the three-axis angular velocity set. The coaxial angle accumulation of the attitude angle change set mentioned above refers to accumulating all attitude angle changes belonging to the same coordinate axis within the attitude angle change set to obtain three current angle changes corresponding to the three coordinate axes, i.e., the current angle change group. The historical attitude angle group refers to the attitude angle group of the wireless inclinometer before acquiring the three-axis angular velocity set; that is, the historical attitude angle group is the previously acquired calibration inclinometer data (i.e., the estimated attitude angle group here or the current attitude angle group in subsequent embodiments). The current attitude estimation based on the current angle change group and the preset historical attitude angle group refers to adding the angles of the three coordinate axes in the historical attitude angle group to the current angle change of the corresponding coordinate axis in the current angle change group; the resulting angles of the three coordinate axes constitute the estimated attitude angle group.

[0150] S7. If the static state determination result is static, then obtain the corrected inclinometer data and the current attitude angle deviation group based on the target acceleration set and the original attitude angle deviation group.

[0151] It needs to be explained that when the static state determination result is static, the target acceleration set measured by the triaxial accelerometer is relatively accurate. The target acceleration set at this time can be used to obtain the correction inclination data. At the same time, in order to make the angular velocity integral result of the gyroscope more accurate in the subsequent non-static state (that is, to make the above-mentioned step of multiplying based on the angular velocity acquisition interval and the corrected angular velocity set more accurate), the target acceleration set can be used to calculate the deviation of the gyroscope. The deviation obtained by the deviation calculation (i.e. the current attitude angle deviation set) is used as the original attitude angle deviation set in the next non-static state, so as to correct the drift error of the gyroscope in real time.

[0152] Specifically, the acquisition of corrected inclinometer data and current attitude angle deviation data based on the target acceleration set and the original attitude angle deviation set includes:

[0153] Identify the current acceleration group in the target acceleration group set;

[0154] Based on the current acceleration set, the attitude of the inclinometer is calculated to obtain the current attitude angle set, and the current attitude angle set is recorded as the corrected inclinometer data.

[0155] The current angular velocity group is identified in the three-axis angular velocity group set. Based on the current angular velocity group and the current attitude angle group, the original attitude angle deviation group is iteratively updated to obtain the current attitude angle deviation group.

[0156] It needs to be explained that the "current acceleration group" refers to the latest target acceleration group collected in the target acceleration group set, that is, the target acceleration group that is ranked last in the target acceleration group set. The "current attitude angular velocity group" refers to the attitude angle data group composed of pitch angle, roll angle, etc., obtained after the inclinometer attitude calculation. The above-mentioned inclinometer attitude calculation based on the current acceleration group means: according to the components of gravitational acceleration on the three coordinate axes measured by the triaxial accelerometer in a stationary state (i.e., the current acceleration group), the attitude angle of the wireless inclinometer relative to the horizontal reference plane is calculated through trigonometric function relationships. For example: a certain current acceleration group is: ( , , Then the pitch angle Through formula Calculate the roll angle Through formula The calculation involves iteratively updating the original attitude angle deviation group based on the current angular velocity group and the current attitude angle group. This means subtracting the current attitude angle of the corresponding coordinate axis from each current angular velocity in the current angular velocity group. The difference obtained is the measurement deviation value of the gyroscope on the corresponding coordinate axis at this time. The set of differences corresponding to each current angular velocity is denoted as the current attitude angle deviation group. Then, the current attitude angle deviation group is stored in the storage location corresponding to the original attitude angle deviation group, and the original attitude angle deviation group is replaced, thereby completing the iterative update of the original attitude angle deviation group.

[0157] S8. Based on the corrected inclinometer data and the current attitude angle deviation group, complete the self-calibration of the wireless inclinometer based on multi-sensor fusion.

[0158] It is clear that when the wireless inclinometer is in a non-stationary state, the data measured by the gyroscope can be corrected by the current attitude angle deviation group here.

[0159] To address the problems described in the background art, this invention first performs temperature compensation testing on a wireless inclinometer to obtain a temperature compensation model. This step establishes the temperature compensation model through discrete temperature testing and curve fitting. Compared to the simple calibration in existing technologies that ignore the influence of temperature, this effectively suppresses sensor drift caused by temperature changes, improving the measurement accuracy and reliability of the inclinometer in variable temperature environments. Next, the original attitude angle deviation set of the gyroscope is obtained, and the temperature compensation model is used to perform temperature compensation on the three-axis acceleration set to obtain the target acceleration set. This step applies the temperature compensation model to correct the acceleration data in real time, overcoming the acceleration measurement deviation caused by temperature fluctuations in existing methods. This provides a more accurate input for multi-sensor fusion and reduces the cumulative error in subsequent attitude calculations. Furthermore, this invention determines the stationary state based on the target acceleration set, obtaining the stationary state determination result. This step uses the mean of the coaxial standard deviation for stationary state determination. Compared to traditional fixed threshold methods, the stationary state determination method improves the accuracy of state recognition and avoids attitude calculation errors caused by misjudgment. If the stationary state determination result is a non-stationary state, angular velocity attitude calculation is performed based on the original attitude angle deviation set and the three-axis angular velocity set to obtain corrected inclinometer data. In the non-stationary state, attitude tracking is achieved through the integral of the angular velocity with deviation correction, combining the dynamic response advantage of the gyroscope, thereby reducing the accumulation of drift error in traditional gyroscope integration and improving the attitude estimation accuracy in motion. If the stationary state determination result is a stationary state, corrected inclinometer data and the current attitude angle deviation set are obtained based on the target acceleration set and the original attitude angle deviation set. In the stationary state, the gyroscope deviation is calibrated using accelerometer data, achieving real-time self-correction. Compared to existing technologies that rely on external references or periodic calibration, this enhances the stability and autonomy of the wireless inclinometer in long-term operation. Therefore, this invention can improve the measurement accuracy and stability of the inclinometer in variable temperature and dynamic environments and reduce the cumulative error of attitude estimation.

[0160] like Figure 2 The diagram shown is a functional block diagram of a wireless inclinometer self-calibration system based on multi-sensor fusion provided in an embodiment of the present invention.

[0161] The wireless inclinometer self-calibration system 100 based on multi-sensor fusion described in this invention can be installed in an electronic device. Depending on the functions implemented, the wireless inclinometer self-calibration system 100 may include a compensation model construction module 101, an acceleration parameter measurement module 102, a stationary state determination module 103, and an attitude deviation calculation module 104. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0162] The compensation model construction module 101 is used to construct a wireless inclinometer, wherein the wireless inclinometer includes a three-axis accelerometer, a gyroscope and a temperature sensor. Temperature compensation tests are performed on the wireless inclinometer to obtain a temperature compensation model, wherein the temperature compensation model includes a set of compensation coefficient variation curves.

[0163] The acceleration parameter measurement module 102 is used to measure parameters using a wireless inclinometer to obtain a set of three-axis accelerations, a set of three-axis angular velocities, and a measured temperature. It also obtains the original attitude angle deviation set of the gyroscope and uses the measured temperature and a temperature compensation model to perform temperature compensation on the set of three-axis accelerations to obtain the target acceleration set.

[0164] The stationary state determination module 103 is used to determine the stationary state based on the target acceleration set and obtain the stationary state determination result, wherein the stationary state determination result is: stationary state or non-stationary state.

[0165] The attitude deviation calculation module 104 is used to perform angular velocity attitude calculation based on the original attitude angle deviation set and the three-axis angular velocity set to obtain corrected inclination data. If the static state determination result is static, then the corrected inclination data and the current attitude angle deviation set are obtained based on the target acceleration set and the original attitude angle deviation set.

[0166] In detail, the modules in the wireless inclinometer self-calibration system 100 based on multi-sensor fusion described in this embodiment of the invention employ the same methods as described above. Figure 1 The method used is the same as the self-calibration method for wireless inclinometers based on multi-sensor fusion described above, and can produce the same technical effect, so it will not be repeated here.

[0167] like Figure 3 The diagram shown is a structural schematic of an electronic device that implements a self-calibration method for a wireless inclinometer based on multi-sensor fusion, according to an embodiment of the present invention.

[0168] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and capable of running on the processor 10, such as a self-calibration method program for a wireless inclinometer based on multi-sensor fusion.

[0169] The memory 11 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the electronic device 1. Furthermore, the memory 11 includes both internal storage units and external storage devices of the electronic device 1. The memory 11 can be used not only to store application software and various types of data installed on the electronic device 1, such as the code of a self-calibration method program for a wireless inclinometer based on multi-sensor fusion, but also to temporarily store data that has been output or will be output.

[0170] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., a self-calibration method program for a wireless inclinometer based on multi-sensor fusion) and calls data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

[0171] The bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0172] Figure 3 Only electronic devices with components are shown; it will be understood by those skilled in the art that... Figure 3The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0173] For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) to power the various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0174] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish communication connections between the electronic device 1 and other electronic devices.

[0175] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), and optionally, a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device 1 and to display a visual user interface.

[0176] The self-calibration method program for a wireless inclinometer based on multi-sensor fusion, stored in the memory 11 of the electronic device 1, is a combination of multiple instructions. When run in the processor 10, it can achieve the following:

[0177] Construct a wireless inclinometer, which includes a three-axis accelerometer, a gyroscope, and a temperature sensor;

[0178] Temperature compensation tests were conducted on the wireless inclinometer to obtain a temperature compensation model, which includes a set of compensation coefficient variation curves.

[0179] Parameters were measured using a wireless inclinometer to obtain triaxial acceleration sets, triaxial angular velocity sets, and measured temperature.

[0180] The original attitude angle deviation set of the gyroscope is obtained, and the temperature compensation of the three-axis acceleration set is performed using the measured temperature and temperature compensation model to obtain the target acceleration set.

[0181] The stationary state is determined based on the target acceleration set, and the stationary state determination result is obtained, which is either stationary or non-stationary.

[0182] If the static state determination result is a non-static state, then the angular velocity attitude is calculated based on the original attitude angle deviation set and the three-axis angular velocity set to obtain the corrected inclination measurement data;

[0183] If the static state determination result is static, then the corrected inclinometer data and the current attitude angle deviation group are obtained based on the target acceleration set and the original attitude angle deviation group.

[0184] The self-calibration of the wireless inclinometer based on multi-sensor fusion is completed based on the calibrated inclinometer data and the current attitude angle deviation group.

[0185] Specifically, the processor 10's implementation method for the above instructions can be found in [reference needed]. Figures 1 to 3 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0186] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0187] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor of an electronic device, can perform the following:

[0188] Construct a wireless inclinometer, which includes a three-axis accelerometer, a gyroscope, and a temperature sensor;

[0189] Temperature compensation tests were conducted on the wireless inclinometer to obtain a temperature compensation model, which includes a set of compensation coefficient variation curves.

[0190] Parameters were measured using a wireless inclinometer to obtain triaxial acceleration sets, triaxial angular velocity sets, and measured temperature.

[0191] The original attitude angle deviation set of the gyroscope is obtained, and the temperature compensation of the three-axis acceleration set is performed using the measured temperature and temperature compensation model to obtain the target acceleration set.

[0192] The stationary state is determined based on the target acceleration set, and the stationary state determination result is obtained, which is either stationary or non-stationary.

[0193] If the static state determination result is a non-static state, then the angular velocity attitude is calculated based on the original attitude angle deviation set and the three-axis angular velocity set to obtain the corrected inclination measurement data;

[0194] If the static state determination result is static, then the corrected inclinometer data and the current attitude angle deviation group are obtained based on the target acceleration set and the original attitude angle deviation group.

[0195] The self-calibration of the wireless inclinometer based on multi-sensor fusion is completed based on the calibrated inclinometer data and the current attitude angle deviation group.

[0196] In the embodiments provided by this invention, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and actual implementations may have other classification methods.

[0197] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0198] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0199] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0200] Finally, it should be noted that the above 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 preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A self-calibration method for a wireless inclinometer based on multi-sensor fusion, characterized in that, The method includes: Construct a wireless inclinometer, which includes a three-axis accelerometer, a gyroscope, and a temperature sensor; Temperature compensation tests were conducted on the wireless inclinometer to obtain a temperature compensation model, which includes a set of compensation coefficient variation curves. Parameters were measured using a wireless inclinometer to obtain triaxial acceleration sets, triaxial angular velocity sets, and measured temperature. The original attitude angle deviation set of the gyroscope is obtained, and the temperature compensation of the three-axis acceleration set is performed using the measured temperature and temperature compensation model to obtain the target acceleration set. The stationary state is determined based on the target acceleration set, and the stationary state determination result is obtained, which is either stationary or non-stationary. If the static state determination result is a non-static state, then the angular velocity attitude is calculated based on the original attitude angle deviation set and the three-axis angular velocity set to obtain the corrected inclination measurement data; If the static state determination result is static, then the corrected inclinometer data and the current attitude angle deviation group are obtained based on the target acceleration set and the original attitude angle deviation group. The self-calibration of the wireless inclinometer based on multi-sensor fusion is completed based on the calibrated inclinometer data and the current attitude angle deviation group.

2. The self-calibration method for wireless inclinometers based on multi-sensor fusion as described in claim 1, characterized in that, The temperature compensation test of the wireless inclinometer, resulting in a temperature compensation model, includes: The ambient temperature range is determined based on the wireless inclinometer. Discrete temperatures are selected within the ambient temperature range to obtain a discrete ambient temperature set, which includes multiple discrete ambient temperatures. A temperature compensation device is constructed, comprising: a turntable base, a temperature control box, and a wireless inclinometer. The turntable base is installed at the center of the temperature control box, and the wireless inclinometer is installed on the turntable surface of the turntable base. Discrete ambient temperatures are extracted sequentially from the discrete ambient temperature set, and the extracted discrete ambient temperatures are recorded as the ambient temperatures to be compensated. Temperature compensation is performed on the wireless inclinometer using a temperature compensation device and the ambient temperature to be compensated, and temperature compensation data is obtained. The temperature compensation data includes: a triaxial compensation coefficient set and a drift compensation coefficient set. By summarizing the temperature compensation data corresponding to each discrete ambient temperature, a temperature compensation dataset is obtained. A temperature compensation model is obtained by fitting the temperature compensation dataset and the discrete ambient temperature set.

3. The self-calibration method for wireless inclinometers based on multi-sensor fusion as described in claim 2, characterized in that, The process of using a temperature compensation device and the ambient temperature to compensate for the temperature of the wireless inclinometer to obtain temperature compensation data includes: The wireless inclinometer is fixed to the rotating base of the temperature compensation device to obtain a fixed inclinometer. Based on the ambient temperature to be compensated and the temperature control box, the temperature environment of the fixed inclinometer is regulated to obtain the temperature-controlled inclinometer. Set up a set of inclinometer compensation positions, which includes multiple inclinometer compensation positions; For each inclinometer compensation position in the inclinometer compensation position set, the actual acceleration is calculated to obtain the actual triaxial acceleration set. The actual triaxial acceleration set includes multiple actual triaxial acceleration groups, and the actual triaxial acceleration groups correspond one-to-one with the inclinometer compensation positions. The temperature-controlled inclinometer is rotated using a turntable base to obtain the test inclinometer. Based on the triaxial accelerometer and the inclinometer compensation position set in the wireless inclinometer, the acceleration of the test inclinometer is collected to obtain multiple sets of measured triaxial accelerations. Each set of test triaxial accelerations includes multiple sets of test triaxial accelerations. Temperature compensation data is obtained by performing temperature compensation calculations based on multiple sets of measured triaxial accelerations and actual triaxial acceleration sets.

4. The self-calibration method for a wireless inclinometer based on multi-sensor fusion as described in claim 3, characterized in that, The temperature compensation calculation is performed based on multiple sets of measured triaxial accelerations and the actual triaxial acceleration set to obtain temperature compensation data, including: For each of the multiple sets of measured triaxial accelerations, perform the following operation: A set of temperature compensation equations is constructed based on the measured triaxial acceleration set and the actual triaxial acceleration set. The set of temperature compensation equations includes multiple temperature compensation equations, and each temperature compensation equation includes: a set of triaxial coefficients to be compensated and a set of drift coefficients to be compensated. The temperature compensation equation set is obtained by summarizing the temperature compensation equation set corresponding to each set of triaxial acceleration measurements; The temperature compensation data is obtained by solving the set of temperature compensation equations for the triaxial coefficients to be compensated and the drift coefficients to be compensated.

5. The self-calibration method for a wireless inclinometer based on multi-sensor fusion as described in claim 4, characterized in that, The step of fitting data based on the temperature compensation dataset and the discrete environmental temperature set to obtain the temperature compensation model includes: A set of parameters to be compensated is set based on a temperature compensation dataset, wherein the set of parameters to be compensated includes multiple parameters to be compensated; For each parameter to be compensated in the parameter set, perform the following operation: Based on the parameter to be compensated, extract a set of similar compensation coefficients from the temperature compensation dataset. The set of similar compensation coefficients includes multiple similar compensation coefficients, and the similar compensation coefficients correspond to the parameter to be compensated. Curve fitting is performed based on a set of similar compensation coefficients and a set of discrete ambient temperatures to obtain a curve of the change in compensation coefficients. The horizontal axis of the curve of the change in compensation coefficients represents the discrete ambient temperature, and the vertical axis of the curve of the change in compensation coefficients represents the similar compensation coefficients. Summarize the compensation coefficient change curves corresponding to each parameter to be compensated to obtain a set of compensation coefficient change curves; A temperature compensation model is constructed based on a set of compensation coefficient variation curves.

6. The self-calibration method for a wireless inclinometer based on multi-sensor fusion as described in claim 5, characterized in that, The method of using temperature measurement and a temperature compensation model to perform temperature compensation on the triaxial acceleration set to obtain the target acceleration set includes: Perform the following operation on each triaxial acceleration group in the triaxial acceleration group set: Based on the measured temperature, coordinate points are indexed in the set of compensation coefficient change curves of the temperature compensation model to obtain the target compensation coefficient coordinate point set. Identify the target compensation coefficient set based on the target compensation coefficient coordinate point set; The triaxial acceleration set is compensated using the target compensation coefficient set to obtain the target acceleration set; Summarize the target acceleration groups corresponding to each triaxial acceleration group to obtain the target acceleration group set.

7. The self-calibration method for a wireless inclinometer based on multi-sensor fusion as described in claim 6, characterized in that, The step of determining the stationary state based on the target acceleration set to obtain the stationary state determination result includes: Coaxial data is extracted based on the target acceleration set to obtain multiple coaxial acceleration sets; Variance calculation is performed on multiple coaxial acceleration sets to obtain multiple coaxial standard deviations, and mean calculation is performed on multiple coaxial standard deviations to obtain the coaxial standard mean deviation; If the standard mean deviation of the coaxial line is greater than the preset static standard deviation, the non-static state is recorded as the static state determination result. If the standard mean deviation of the coaxial axis is not greater than the standard deviation of the stationary state, then the stationary state is recorded as the stationary state determination result.

8. The self-calibration method for a wireless inclinometer based on multi-sensor fusion as described in claim 7, characterized in that, The angular velocity attitude calculation based on the original attitude angle deviation set and the three-axis angular velocity set yields corrected inclination measurement data, including: The three-axis angular velocity set is corrected based on the original attitude angle deviation set to obtain the corrected angular velocity set. For each corrected angular velocity group in the corrected angular velocity group set, perform the following operation: The angular velocity acquisition interval is obtained, and the product of the angular velocity acquisition interval and the corrected angular velocity group is calculated to obtain the attitude angle change value group. Summarize each group of attitude angle changes to obtain a set of attitude angle change groups; The attitude angle change set is coaxially accumulated to obtain the current angle change set. Based on the current angle change set and the preset historical attitude angle set, the current attitude is estimated to obtain the estimated attitude angle set. The estimated attitude angle set is denoted as the corrected inclinometer data.

9. The self-calibration method for a wireless inclinometer based on multi-sensor fusion as described in claim 8, characterized in that, The process of obtaining corrected inclinometer data and current attitude angle deviation data based on the target acceleration set and the original attitude angle deviation set includes: Identify the current acceleration group in the target acceleration group set; Based on the current acceleration set, the attitude of the inclinometer is calculated to obtain the current attitude angle set, and the current attitude angle set is recorded as the corrected inclinometer data. The current angular velocity group is identified in the three-axis angular velocity group set. Based on the current angular velocity group and the current attitude angle group, the original attitude angle deviation group is iteratively updated to obtain the current attitude angle deviation group.

10. A self-calibration system for a wireless inclinometer based on multi-sensor fusion, characterized in that, The system includes: The compensation model construction module is used to construct a wireless inclinometer, which includes a three-axis accelerometer, a gyroscope, and a temperature sensor. Temperature compensation tests are performed on the wireless inclinometer to obtain a temperature compensation model, which includes a set of compensation coefficient variation curves. The acceleration parameter measurement module is used to measure parameters using a wireless inclinometer to obtain a triaxial acceleration set, a triaxial angular velocity set, and a measured temperature. It also obtains the original attitude angle deviation set of the gyroscope and uses the measured temperature and temperature compensation model to perform temperature compensation on the triaxial acceleration set to obtain the target acceleration set. The stationary state determination module is used to determine the stationary state based on the target acceleration set and obtain the stationary state determination result, which is either stationary or non-stationary. The attitude deviation calculation module is used to perform angular velocity attitude calculation based on the original attitude angle deviation set and the three-axis angular velocity set to obtain corrected inclinometer data. If the static state determination result is static, then the corrected inclinometer data and the current attitude angle deviation set are obtained based on the target acceleration set and the original attitude angle deviation set.

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