Pressure sensor calibration method and system

Abstract

The invention discloses a calibration method and system for a pressure sensor, and the method comprises the steps: selecting a plurality of discrete calibration points on a sensing surface of a multi-layer multi-channel sensor; sequentially applying a group of limited preset acting force modes to each point position, wherein the acting force modes comprise tangential uniaxial force parallel to the sensed surface, normal uniaxial force perpendicular to the sensed surface and at least one composite force simultaneously comprising tangential and normal components; response signals of all channels are synchronously collected during each time of force application; and finally, on the basis of all the signals and the corresponding known force application information, calculating to obtain calibration parameters for establishing accurate mapping between the signals and the actual stress. The problem of low calibration efficiency of the pressure sensor is solved, omnidirectional exhaustion is replaced by finite mode test, the calibration precision is guaranteed, the test frequency and time are greatly reduced, and the calibration efficiency of the pressure sensor is remarkably improved.

Description

Technical Field

[0001] This application relates to the field of sensor calibration technology, and in particular to a calibration method and system for a pressure sensor. Background Technology

[0002] As electronic products such as smartphones, laptops, and wearable devices become thinner, lighter, more integrated, and offer more diverse interactions, their internal physical space is being drastically compressed. Under this trend, pressure sensors need to undertake more complex tasks, expanding their functions from simple force measurement to the integration of multiple interaction modalities, including position recognition, sliding trajectory detection, and simulating the tactile feel of mechanical buttons.

[0003] To ensure the accuracy and spatial uniformity of the aforementioned multifunctional measurements, precise calibration of the force-electric response characteristics of the pressure sensor array in three-dimensional space is required. Related techniques typically employ a full-coverage point-by-point calibration method. A high-precision indenter is used to apply known, precise pressure, gradually increasing from small to large, at each pre-defined point on the sensor screen. Each pressure application records data from all sensing units of the sensor. Finally, based on this massive amount of pressure-data records, a dedicated calibration formula is calculated for each sensing unit.

[0004] The calibration time of this full-coverage point-by-point calibration method is directly proportional to the product of the number of calibration points, the pressure gradient levels, and the number of sensor channels. For complex sensor arrays with multiple channels, completing a full-coverage calibration is time-consuming, resulting in low production efficiency. Therefore, there is an urgent need for a calibration method that can significantly shorten calibration time and improve production efficiency while ensuring the calibration accuracy of multi-channel pressure sensors. Summary of the Invention

[0005] This application provides a calibration method and system for a pressure sensor, which solves the problem of low efficiency in the calibration of multi-dimensional force pressure sensors and achieves the effect of improving the calibration efficiency of pressure sensors.

[0006] This application provides a calibration method and system for a pressure sensor. The calibration method for the pressure sensor includes: Step S1: Select multiple discrete calibration points on the sensing surface of the pressure sensor; Step S2: Apply forces of multiple different uniaxial test modes and at least one composite test mode to each calibration point in sequence; The plurality of different single-axis test modes include at least: a first single-axis mode, wherein the direction of the force is parallel to the sensing surface; and a second single-axis mode, wherein the direction of the force is perpendicular to the sensing surface. The force direction corresponding to the at least one composite test mode simultaneously has components that are parallel to and perpendicular to the sensing surface. Step S3: When executing each of the test modes, synchronously acquire the response signals of all the sensor channels; Step S4: Based on the response signals collected when each test mode is executed at each calibration point, and the known force information corresponding to each test mode, the calibration parameters are calculated; the calibration parameters are used to establish a mapping model from the response signal of the sensing channel to the actual force information.

[0007] Optionally, the step of applying forces in multiple different uniaxial test modes in step S2 includes: A first tangential force is applied sequentially to each of the calibration points, the direction of the first tangential force being parallel to the sensing surface; The second tangential force is applied sequentially to each of the calibration points. The direction of the second tangential force is parallel to the sensing surface and not parallel to the direction of the first tangential force. The second single-axis mode force is applied sequentially to each of the calibration points.

[0008] Optionally, the step of sequentially applying the second tangential mode force to each of the calibration points includes: The step of applying the second tangential mode force to each of the calibration points in sequence is repeated at least twice, and the response signals of each sensing channel are collected synchronously during the execution. After all repetitive executions are completed, the signal consistency error of the current calibration point is calculated based on the response signals collected in different executions at the same calibration point. If the signal consistency error exceeds a preset error threshold, the repeatability test of the current calibration point is deemed unqualified, and the current calibration point is marked.

[0009] Optionally, when applying the force of the second single-axis mode, the tilt angle between the sensing surface and the horizontal plane is changed, and the step of sequentially applying the force of the second single-axis mode to each calibration point is performed at each tilt angle.

[0010] Optionally, the step of applying at least one composite test mode force in step S2 includes: A first composite force is applied sequentially to each of the calibration points; wherein, applying the first composite force involves simultaneously applying a component of the force along the direction of the first tangential mode and a component of the force along the direction of the second uniaxial mode to the calibration point. A second composite force is applied sequentially to each of the calibration points; wherein, applying the second composite force involves simultaneously applying a component of the force along the direction of the second tangential mode and a component of the force along the direction of the second uniaxial mode to the calibration point.

[0011] Optionally, when applying the force of the single-axis test mode and the composite test mode, the magnitude of the force is a preset fixed value.

[0012] Optionally, after the step of synchronously acquiring the response signals of all the sensing channels when executing each of the test modes, the method includes: After each data acquisition, it is determined in real time whether the response signal of each sensor channel is within the preset effective signal range; If the response signal exceeds the effective signal range, the data collected in this test mode and at the calibration point is marked as invalid.

[0013] Optionally, step S4 includes: The response signals from all calibration points and all test modes are aligned and integrated with the known force information to construct a calibration dataset; Based on the calibration dataset, a system of linear mapping equations was fitted using the least squares method. Based on the linear mapping equations, a set of coefficient matrices and bias vectors are calculated, and the coefficient matrix and bias vectors are the calibration parameters.

[0014] Optionally, after the step of calculating the calibration parameters, the method includes: Generate signal waveform analysis charts based on the calibration dataset; The response signals collected each time during the construction of the calibration dataset are associated with the corresponding test time, force application mode, load and force application angle information and stored as a test information set; The coefficient matrix, bias vector, signal waveform analysis chart, and test information set are integrated to form a calibration report.

[0015] Furthermore, to achieve the above objectives, embodiments of the present invention also provide a calibration system for a pressure sensor, the system comprising: The pressure detection unit includes multiple sensing channels arranged in multiple layers in space and has a common sensing surface. A rotatable force application platform is configured to apply forces in the first single-axis mode, the second single-axis mode, and the composite test mode sequentially at multiple discrete calibration points defined on the sensing surface. A data acquisition and processing unit, connected to the pressure detection unit, is used to synchronously acquire the response signal of the sensing channel when each test mode is executed; The signal processing and calibration unit is used to calculate calibration parameters based on the acquired response signal and the known force information corresponding to each test mode. The calibration parameters are used to establish a mapping model from the response signal to the actual force information.

[0016] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: For complex pressure sensors with multi-layered, multi-channel structures, multiple discrete calibration points are selected on the sensing surface. A predefined set of finitely many standardized force patterns is sequentially applied to each calibration point. This set of patterns must include a uniaxial tangential force pattern parallel to the sensing surface, a uniaxial normal force pattern perpendicular to the sensing surface, and at least one composite force pattern with both tangential and normal components. Response signals from all sensing channels are simultaneously acquired each time a force pattern is applied. Based on the response signals acquired at all calibration points and under all test modes, and their corresponding known force information, a set of calibration parameters is calculated, thereby establishing an accurate mapping model from the sensor response signal to the actual multi-dimensional force information. This addresses the problem of low calibration efficiency in pressure sensors by replacing the infinite-direction exhaustive design with finite-mode testing. This significantly reduces the number of tests and time while maintaining calibration accuracy, thus substantially improving the calibration efficiency of pressure sensors. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the framework of the pressure sensor calibration method of this application; Figure 2 This is a schematic flowchart of the pressure sensor calibration method of this application; Figure 3 This is a schematic diagram of the pressure sensor calibration system of this application; Figure 4 This is a schematic diagram of the terminal structure of the hardware operating environment involved in one embodiment of this application. Detailed Implementation

[0018] To address the problem of low calibration efficiency in pressure sensors, this application proposes a calibration method and system for pressure sensors. The method includes: selecting multiple discrete calibration points on the sensing surface of a multi-layer, multi-channel sensor; sequentially applying a set of finite preset force patterns to each point, where each pattern must include a tangential uniaxial force parallel to the sensing surface, a normal uniaxial force perpendicular to the sensing surface, and at least one composite force containing both tangential and normal components; simultaneously acquiring the response signals of all channels during each force application; and finally, calculating calibration parameters for establishing an accurate mapping between the signals and the actual applied force based on all signals and the corresponding known force information. By replacing exhaustive testing in all directions with finite-mode testing, calibration efficiency is significantly improved while ensuring accuracy.

[0019] To better understand the above technical solutions, exemplary embodiments of this application will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of this application are shown in the drawings, it should be understood that this application can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of this application and to fully convey the scope of this application to those skilled in the art.

[0020] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0021] Example 1 In this embodiment, a calibration method for a pressure sensor is provided.

[0022] Reference Figure 1-2 The calibration method for the pressure sensor in this embodiment includes the following steps: Step S1: Select multiple discrete calibration points on the sensing surface of the pressure sensor; In this embodiment, the pressure sensor comprises multiple sensing channels arranged in multiple layers in space. The calibrated pressure sensor can be adapted to various devices that require multi-dimensional force sensors, such as precision machining equipment, medical and service robots, intelligent vehicle systems, and consumer electronics interactive devices.

[0023] As an optional implementation, the multiple sensing channels of the pressure sensor have a common sensing surface. When multiple discrete calibration points are selected on the sensing surface, these discrete calibration points need to be evenly distributed within the effective sensing area of ​​the sensing surface to ensure that the final calibration parameters can completely and evenly characterize the response characteristics of the entire area.

[0024] For example, a 3×3 grid can be used as calibration points. If the device has a clearly defined high-frequency interaction area, such as the lower half of a mobile phone screen or a specific button area on a game controller, the density of calibration points can be appropriately increased in these areas for focused calibration.

[0025] Optionally, the selection of calibration points should avoid known abrupt changes in mechanical structure below the sensor, such as support ribs or screw holes, to avoid introducing interference due to abnormal mechanical transmission paths at such locations.

[0026] Step S2: Apply forces of multiple different uniaxial test modes and at least one composite test mode to each calibration point in sequence; In this embodiment, the multiple uniaxial test modes include at least a first uniaxial mode where the force direction is parallel to the sensing surface, and a second uniaxial mode where the force direction is perpendicular to the sensing surface. The force direction of the composite test mode has components parallel to and perpendicular to the sensing surface. The magnitude of the force can be one or more preset fixed values. Using a fixed force value for testing simplifies the complex multivariate calibration problem into a centralized calibration of the force direction, thereby simplifying the testing process and improving calibration efficiency while ensuring characterization accuracy.

[0027] As an optional implementation, the single-axis testing mode includes a first single-axis mode and a second single-axis mode. The first single-axis mode includes a first tangential mode and a second tangential mode. The force directions of both the first and second tangential modes are parallel to the sensing surface, but the force direction of the first tangential mode is not parallel to the force direction of the second tangential mode. By performing these two non-parallel tangential force tests, response data of the pressure sensor under forces in different axes within the plane can be obtained, providing benchmark data for subsequent calculations of calibration parameters that reflect the sensor's comprehensive force characteristics.

[0028] For example, the first tangential mode and the second tangential mode can adopt the standard axis in a spatial rectangular coordinate system. That is, the first tangential mode can be a Y-axis tangential force test, in which the force applied to each calibration point is parallel to the sensing surface and along the positive or negative Y-axis; the second tangential mode can be implemented as an X-axis tangential force test, in which the force applied to each calibration point is parallel to the sensing surface and along the positive or negative X-axis. By sequentially performing the Y-axis and X-axis tangential force tests, the force response data of the pressure sensor in two mutually orthogonal horizontal directions can be obtained.

[0029] Optionally, repeatability verification can be performed when applying the second tangential mode force. This involves repeating the entire process of "sequentially applying the second tangential mode force to each calibration point and simultaneously acquiring the response signal" at least twice, acquiring the response signals from all sensor channels simultaneously during each execution. After all repetitions are completed, for each calibration point, the signal consistency error is calculated based on the multiple sets of response signals acquired in different executions. For example, the standard deviation or maximum deviation between each set of signals is calculated. If the calculated signal consistency error exceeds a preset error threshold, the repeatability test for the current calibration point is deemed unqualified, and the calibration point is marked. Repeatability verification allows for the immediate identification and removal of unreliable data caused by accidental interference, poor contact, or transient equipment instability during the calibration process, thereby improving the overall reliability of the calibration data.

[0030] It should be noted that the process for performing repeatability verification is also applicable to the first tangential mode, or, depending on the actual equipment structure and reliability assessment requirements, to any other single-axis test mode.

[0031] Optionally, when applying the force in the second uniaxial mode, the tilt angle between the sensing surface and the horizontal plane can be changed, and the step of applying the force in the second uniaxial mode to each calibration point can be performed sequentially at each tilt angle. By changing the tilt angle of the sensing surface during testing, measurement errors introduced by changes in gravity components and internal structural stresses under different usage postures of the sensor can be calibrated and compensated, thereby improving the environmental adaptability and robustness of the calibration parameters.

[0032] For example, the second single-axis mode can be a Z-axis normal force test perpendicular to the sensing surface. A rotatable force application platform changes the tilt angle of the pressure sensor's sensing surface relative to the horizontal plane. At each set tilt angle, the steps of sequentially applying a Z-axis normal force to each calibration point and simultaneously acquiring the response signal are performed. By acquiring a dataset of the pressure sensor's response to the same standard normal force under various typical operating postures, signal deviations caused by changes in the gravitational component and the redistribution of internal mechanical stress can be separated and quantified during subsequent calibration parameter calculations, thereby embedding an attitude compensation mechanism into the calibration model. This ensures that the final generated calibration parameters are adaptable to the use of the device in complex real-world scenarios, guaranteeing the accuracy and consistency of the normal force test.

[0033] As another optional implementation, the force of the composite test mode includes a first composite force and a second composite force. Applying the first composite force involves simultaneously applying a component along the force direction of the first tangential mode and a component along the force direction of the second uniaxial mode to the calibration point; applying the second composite force involves simultaneously applying a component along the force direction of the second tangential mode and a component along the force direction of the second uniaxial mode to the calibration point.

[0034] Specifically, for the first combined force test, a tangential force component along the Y-axis and a normal force component along the Z-axis are simultaneously applied to each calibration point. The first combined force test is used to investigate the coupling response characteristics of the pressure sensor when the Y-axis tangential force and the Z-axis normal force act together.

[0035] For the second combined force test, a tangential force component along the X-axis and a normal force component along the Z-axis are simultaneously applied to each calibration point. The second combined force test is used to investigate the coupling response characteristics of the pressure sensor when the X-axis tangential force and the Z-axis normal force act together.

[0036] Optionally, during the first and second combined force tests, the acquired sensor channel response signals can be observed and analyzed. Specifically, the measured signal waveform under the combined force is compared with the signal obtained at the same calibration point under a corresponding single-direction force test. This comparison allows analysis of whether the actual response of the pressure sensor conforms to the ideal linear superposition expectation, or identification of the existence and strength of specific nonlinear coupling effects. Simultaneously, the signal fluctuations throughout the combined force loading and unloading process are observed, focusing on signal stability, repeatability, and the presence of significant hysteresis. This is to evaluate the transient response performance and mechanical hysteresis characteristics of the pressure sensor under complex and dynamic combined force conditions.

[0037] Step S3: When executing each of the test modes, synchronously acquire the response signals of all the sensor channels; In this embodiment, when a specific mode of force is applied to the calibration point, the pressure signals output by all sensor channels are read under the same time reference and converted into electrical signals. This ensures that the data from all sensor channels correspond to the exact same force state.

[0038] As an optional implementation, the output terminals of each sensing channel of the pressure sensor are connected to a multi-channel synchronous data acquisition card. After the force application device completes the application of the target load at a certain calibration point and maintains stability, the host computer software sends the same trigger command to the data acquisition card. Upon receiving the command, the acquisition card simultaneously initiates an analog-to-digital conversion on all its enabled channels, converting the instantaneous analog voltage values ​​of each sensing channel into digital quantities, and then packages and uploads them to the host computer.

[0039] As another optional implementation, after synchronously acquiring the response signal, a real-time data validity judgment step can be performed immediately to ensure data quality at the source of acquisition.

[0040] Specifically, by pre-setting the effective signal range for each sensor channel, after each set of response signals is synchronously acquired, the instantaneous signal value of each sensor channel is compared in real time with the preset effective signal range for that channel. If the response signal of any sensor channel exceeds its corresponding effective signal range, the acquired data is determined to be abnormal. The acquired data for the corresponding test mode and calibration point is then deemed invalid. Data marked as invalid can be automatically excluded in subsequent calibration parameter calculations, achieving early fault diagnosis and data filtering during the calibration process.

[0041] Step S4: Based on the response signals collected when each test mode is executed at each calibration point, and the known applied force information corresponding to each test mode, the calibration parameters are calculated.

[0042] In this embodiment, calibration parameters can be used to establish a mapping model from the response signal of the sensing channel to the actual force information.

[0043] As an optional implementation, response signals from all calibration points and all test modes are aligned and integrated with known force information to construct a calibration dataset. Based on the calibration dataset, a set of linear mapping equations is fitted using the least squares method. According to the set of linear mapping equations, a set of coefficient matrices and bias vectors are calculated, and the coefficient matrix and bias vectors are the calibration parameters.

[0044] For example, suppose there are M sensing channels, and after completing K tests at P calibration points, a total of N sets of data are obtained. Each set of data contains a known 3D force vector and a measured M-dimensional signal vector. A linear model is used to describe the relationship between the signal and the force: Calculated force = coefficient matrix × measured signal + bias vector. Here, the coefficient matrix is ​​a 3x3 matrix to be determined, and the bias vector is a 3D vector to be determined; together, they constitute the calibration parameters to be determined. By constructing all N sets of data into matrix form and using the least squares method, the optimal coefficient matrix and bias vector that minimize the overall error can be calculated in one step. The obtained optimal coefficient matrix and bias vector are the calibration parameters of the pressure sensor. In practical use, the device can convert the acquired signal into accurate force information in real time through simple matrix operations.

[0045] As another optional implementation, after obtaining the calibration parameters, a signal waveform analysis chart is generated based on the calibration dataset. The response signals acquired each time during the construction of the calibration dataset are associated with the corresponding test time, force mode, load, and force application angle information and stored as a test information set. The coefficient matrix, bias vector, signal waveform analysis chart, and test information set are integrated to form a calibration report. This achieves traceability and visualization of the calibration process, transforming a one-time physical test into a digital asset that can be analyzed, verified, and reused over a long period.

[0046] For example, key charts, such as uniaxial force response diagrams, composite force superposition analysis diagrams, and surface uniformity cloud maps, are automatically generated based on calibration data to visually demonstrate sensor performance. Each acquired response signal is then associated with its corresponding test conditions (including time, mode, load, and angle), packaged into a structured test information set to ensure all data traceability. Finally, the aforementioned charts, test information set, calculated calibration parameters (coefficient matrix and bias vector), and management information such as sensor serial number and calibration time are automatically integrated according to a standard template to form a complete electronic calibration report and structured data package.

[0047] In this embodiment, representative calibration points are selected on the sensor's sensing surface, and a finite but complete set of standardized force patterns are applied sequentially: including uniaxial tangential force, uniaxial normal force, and their composite force in a specific direction, while simultaneously acquiring the sensor's full-channel response signals. Based on these signals and known force information, a set of calibration parameters is automatically calculated using a numerical optimization algorithm (such as the least squares method), ultimately generating a complete calibration report containing parameters, analysis charts, and raw data. This finite-mode testing ensures the accuracy of multidimensional force calibration while improving calibration efficiency and establishing a comprehensive quality control and data traceability system.

[0048] Based on the same inventive concept, this application also provides a system corresponding to the method in Embodiment 1, as shown in Embodiment 2.

[0049] Example 2 Based on Embodiment 1, another embodiment of this application is proposed, with reference to... Figure 3 The calibration system for the pressure sensor includes: a pressure detection unit 1, a rotatable force application platform 2, a data acquisition and processing unit 3, and a signal processing and calibration unit 4.

[0050] The pressure detection unit 1 includes multiple sensing channels arranged in multiple layers in space and has a common sensing surface; In this embodiment, the pressure detection unit adopts a layered layout design to optimize the system's ability to perceive multidimensional forces.

[0051] Specifically, the pressure detection unit integrates eight independent sensing channels, arranged in two layers according to spatial location. The upper sensor group contains four sensing channels, numbered CH1, CH2, CH3, and CH4. The lower sensor group contains four sensing channels, numbered CH5, CH6, CH7, and CH8. The upper and lower sensors are arranged in a specific geometric relationship in the horizontal plane, such as being staggered or facing different directions, so that when the sensed surface is subjected to force, the upper and lower sensors can collect differentiated strain signals.

[0052] The rotatable force application platform 2 is configured to apply forces in a first single-axis mode, a second single-axis mode, and a composite test mode sequentially at multiple discrete calibration points defined on the sensing surface. In this embodiment, the rotatable force application platform has a 360-degree rotation function, which can simulate force application scenarios at different tilt angles; its surface can be set with an equidistant grid of force application points, such as 3×3, to support the application of single-direction force or compound-direction force to different points, so as to achieve precise control of the force application position and angle.

[0053] The data acquisition and processing unit 3 is connected to the pressure detection unit and is used to synchronously acquire the response signal of the sensing channel when each test mode is executed. In this embodiment, the data acquisition and processing unit includes a multi-channel data acquisition card and a signal conversion module, which can convert the raw pressure signals of each sensing channel into standard analog signals and acquire them synchronously. At the same time, it can record key data such as the extreme value fluctuation range and fluctuation amplitude of the signal, providing direct quantitative basis for subsequent data quality assessment, sensor performance diagnosis and calibration process monitoring.

[0054] The signal processing and calibration unit 4 is used to calculate calibration parameters based on the acquired response signal and the known applied force information corresponding to each test mode.

[0055] In this embodiment, the signal processing and calibration unit is specifically configured to: integrate all calibration data, fit the mapping relationship using numerical algorithms such as the least squares method, solve for the calibration parameters, generate signal analysis charts and calibration reports, and optionally perform real-time data validity judgment and repeatability verification analysis. The calibration parameters are used to establish a mapping model from the response signal to the actual force information.

[0056] Since the system described in Embodiment 2 of this application is a system used to implement the method of Embodiment 1 of this application, those skilled in the art can understand the specific structure and variations of the system based on the method described in Embodiment 1 of this application, and therefore will not be described again here. All systems used in the method of Embodiment 1 of this application fall within the scope of protection of this application.

[0057] Example 3 In this application embodiment, a calibration device for a pressure sensor is proposed.

[0058] Reference Figure 4 , Figure 4 This is a schematic diagram of the terminal structure of the hardware operating environment involved in one embodiment of this application.

[0059] like Figure 4 As shown, the control terminal may include: a processor 1001, such as a CPU, a network interface 1003, a memory 1004, and a communication bus 1002. The communication bus 1002 is used to enable communication between these components. The network interface 1003 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1004 may be high-speed RAM or stable non-volatile memory, such as disk storage. Alternatively, the memory 1004 may be a storage device independent of the aforementioned processor 1001.

[0060] Those skilled in the art will understand that Figure 4 The terminal structure shown does not constitute a limitation on the terminal and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0061] like Figure 4 As shown, the memory 1004, which serves as a computer storage medium, may include an operating system, a network communication module, and a calibration program for a pressure sensor.

[0062] exist Figure 4 In the hardware structure of the pressure sensor calibration device shown, the processor 1001 can call the pressure sensor calibration program stored in the memory 1004 and perform the following operations: Step S1: Select multiple discrete calibration points on the sensing surface of the pressure sensor; Step S2: Apply forces of multiple different uniaxial test modes and at least one composite test mode to each calibration point in sequence; The plurality of different single-axis test modes include at least: a first single-axis mode, wherein the direction of the force is parallel to the sensing surface; and a second single-axis mode, wherein the direction of the force is perpendicular to the sensing surface. The force direction corresponding to the at least one composite test mode simultaneously has components that are parallel to and perpendicular to the sensing surface. Step S3: When executing each of the test modes, synchronously acquire the response signals of all the sensor channels; Step S4: Based on the response signals collected when each test mode is executed at each calibration point, and the known applied force information corresponding to each test mode, the calibration parameters are calculated.

[0063] Optionally, the processor 1001 may call the calibration program for the pressure sensor stored in the memory 1004, and also perform the following operations: A first tangential force is applied sequentially to each of the calibration points, the direction of the first tangential force being parallel to the sensing surface; The second tangential force is applied sequentially to each of the calibration points. The direction of the second tangential force is parallel to the sensing surface and not parallel to the direction of the first tangential force. The second single-axis mode force is applied sequentially to each of the calibration points.

[0064] Optionally, the processor 1001 may call the calibration program for the pressure sensor stored in the memory 1004, and also perform the following operations: The step of applying the second tangential mode force to each of the calibration points in sequence is repeated at least twice, and the response signals of each sensing channel are collected synchronously during the execution. After all repetitive executions are completed, the signal consistency error of the current calibration point is calculated based on the response signals collected in different executions at the same calibration point. If the signal consistency error exceeds a preset error threshold, the repeatability test of the current calibration point is deemed unqualified, and the current calibration point is marked.

[0065] Optionally, the processor 1001 may call the calibration program for the pressure sensor stored in the memory 1004, and also perform the following operations: When applying the force of the second single-axis mode, the tilt angle between the sensing surface and the horizontal plane is changed, and at each tilt angle, the step of sequentially applying the force of the second single-axis mode to each calibration point is performed.

[0066] Optionally, the processor 1001 may call the calibration program for the pressure sensor stored in the memory 1004, and also perform the following operations: A first composite force is applied sequentially to each of the calibration points; wherein, applying the first composite force involves simultaneously applying a component of the force along the direction of the first tangential mode and a component of the force along the direction of the second uniaxial mode to the calibration point. A second composite force is applied sequentially to each of the calibration points; wherein, applying the second composite force involves simultaneously applying a component of the force along the direction of the second tangential mode and a component of the force along the direction of the second uniaxial mode to the calibration point.

[0067] Optionally, the processor 1001 may call the calibration program for the pressure sensor stored in the memory 1004, and also perform the following operations: When applying the force of the single-axis test mode and the composite test mode, the magnitude of the force is a preset fixed value.

[0068] Optionally, the processor 1001 may call the calibration program for the pressure sensor stored in the memory 1004, and also perform the following operations: After each data acquisition, it is determined in real time whether the response signal of each sensor channel is within the preset effective signal range; If the response signal exceeds the effective signal range, the data collected in this test mode and at the calibration point is marked as invalid.

[0069] Optionally, the processor 1001 may call the calibration program for the pressure sensor stored in the memory 1004, and also perform the following operations: The response signals from all calibration points and all test modes are aligned and integrated with the known force information to construct a calibration dataset; Based on the calibration dataset, a system of linear mapping equations was fitted using the least squares method. Based on the linear mapping equations, a set of coefficient matrices and bias vectors are calculated, and the coefficient matrix and bias vectors are the calibration parameters.

[0070] Optionally, the processor 1001 may call the calibration program for the pressure sensor stored in the memory 1004, and also perform the following operations: Generate signal waveform analysis charts based on the calibration dataset; The response signals collected each time during the construction of the calibration dataset are associated with the corresponding test time, force application mode, load and force application angle information and stored as a test information set; The coefficient matrix, bias vector, signal waveform analysis chart, and test information set are integrated to form a calibration report.

[0071] Furthermore, to achieve the above objectives, embodiments of the present invention also provide a calibration system for a pressure sensor, comprising: The pressure detection unit includes multiple sensing channels arranged in multiple layers in space and has a common sensing surface. A rotatable force application platform is configured to apply forces in the first single-axis mode, the second single-axis mode, and the composite test mode sequentially at multiple discrete calibration points defined on the sensing surface. A data acquisition and processing unit, connected to the pressure detection unit, is used to synchronously acquire the response signal of the sensing channel when each test mode is executed; The signal processing and calibration unit is used to calculate calibration parameters based on the acquired response signal and the known applied force information corresponding to each test mode.

[0072] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0073] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0074] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0075] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1The steps of the function specified in one or more boxes.

[0076] It should be noted that any reference signs placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. This application can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, third, etc., does not indicate any order. These words can be interpreted as names.

[0077] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0078] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of the invention. Therefore, if these modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include these modifications and variations.

Claims

1. A calibration method for a pressure sensor, characterized in that, The pressure sensor comprises multiple sensing channels arranged in multiple layers in space, and the method includes: Step S1: Select multiple discrete calibration points on the sensing surface of the pressure sensor; Step S2: Apply forces of multiple different uniaxial test modes and at least one composite test mode to each calibration point in sequence; The plurality of different single-axis test modes include at least: a first single-axis mode, wherein the direction of the force is parallel to the sensing surface; and a second single-axis mode, wherein the direction of the force is perpendicular to the sensing surface. The force direction corresponding to the at least one composite test mode simultaneously has components that are parallel to and perpendicular to the sensing surface. Step S3: When executing each of the test modes, synchronously acquire the response signals of all the sensor channels; Step S4: Based on the response signals collected when each test mode is executed at each of the calibration points, and the known force information corresponding to each test mode, the calibration parameters are calculated.

2. The method as described in claim 1, characterized in that, The step S2, which involves applying forces in multiple different uniaxial test modes, includes: A first tangential force is applied sequentially to each of the calibration points, the direction of the first tangential force being parallel to the sensing surface; The second tangential force is applied sequentially to each of the calibration points. The direction of the second tangential force is parallel to the sensing surface and not parallel to the direction of the first tangential force. The second single-axis mode force is applied sequentially to each of the calibration points.

3. The method as described in claim 2, characterized in that, The step of sequentially applying the second tangential mode force to each of the calibration points includes: The step of applying the second tangential mode force to each of the calibration points in sequence is repeated at least twice, and the response signals of each sensing channel are collected synchronously during the execution. After all repetitive executions are completed, the signal consistency error of the current calibration point is calculated based on the response signals collected in different executions at the same calibration point. If the signal consistency error exceeds a preset error threshold, the repeatability test of the current calibration point is deemed unqualified, and the current calibration point is marked.

4. The method as described in claim 2, characterized in that, When applying the force of the second single-axis mode, the tilt angle between the sensing surface and the horizontal plane is changed, and at each tilt angle, the step of sequentially applying the force of the second single-axis mode to each calibration point is performed.

5. The method as described in claim 2, characterized in that, The step of applying at least one composite test mode force in step S2 includes: A first composite force is applied sequentially to each of the calibration points; wherein, applying the first composite force involves simultaneously applying a component of the force along the direction of the first tangential mode and a component of the force along the direction of the second uniaxial mode to the calibration point. A second composite force is applied sequentially to each of the calibration points; wherein, applying the second composite force involves simultaneously applying a component of the force along the direction of the second tangential mode and a component of the force along the direction of the second uniaxial mode to the calibration point.

6. The method according to any one of claims 1 to 5, characterized in that, When applying the force of the single-axis test mode and the composite test mode, the magnitude of the force is a preset fixed value.

7. The method as described in any one of claims 1 to 5, characterized in that, After the step of synchronously acquiring the response signals of all the sensor channels when executing each of the test modes, the method includes: After each data acquisition, it is determined in real time whether the response signal of each sensor channel is within the preset effective signal range; If the response signal exceeds the effective signal range, the data collected in this test mode and at the calibration point is marked as invalid.

8. The method as described in claim 1, characterized in that, Step S4 includes: The response signals from all calibration points and all test modes are aligned and integrated with the known force information to construct a calibration dataset; Based on the calibration dataset, a system of linear mapping equations was fitted using the least squares method; Based on the linear mapping equations, a set of coefficient matrices and bias vectors are calculated, and the coefficient matrix and bias vectors are the calibration parameters.

9. The method as described in claim 8, characterized in that, After the step of calculating the calibration parameters, the following steps are included: Generate signal waveform analysis charts based on the calibration dataset; The response signals collected each time during the construction of the calibration dataset are associated with the corresponding test time, force application mode, load and force application angle information and stored as a test information set; The coefficient matrix, bias vector, signal waveform analysis chart, and test information set are integrated to form a calibration report.

10. A calibration system for a pressure sensor, characterized in that, The system includes: The pressure detection unit includes multiple sensing channels arranged in multiple layers in space and has a common sensing surface. A rotatable force application platform is configured to apply forces in the first single-axis mode, the second single-axis mode, and the composite test mode as described in claim 1 sequentially at multiple discrete calibration points defined on the sensing surface. A data acquisition and processing unit, connected to the pressure detection unit, is used to synchronously acquire the response signal of the sensing channel when each test mode is executed; The signal processing and calibration unit is used to calculate calibration parameters based on the acquired response signal and the known applied force information corresponding to each test mode.

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