A method for determining a calibration scheme of a pressure sensor

Abstract

The present invention discloses a method for determining a calibration scheme of a pressure sensor, which relates to the technical field of sensor devices and includes the following steps: clarifying the working conditions of the sensor, selecting a suitable reference device, setting pressure loading points, constructing a dynamic pressure loading module, evaluating the performance of the sensor under complex working conditions through environmental simulation, conducting an overload test for extreme conditions, conducting a long-term stability test, constructing a non-calibration working condition verification model, and optimizing the calibration strategy with an intelligent algorithm to complete the calibration scheme of the pressure sensor. The method for determining the calibration scheme of the pressure sensor systematically integrates static calibration, dynamic response testing, environmental simulation, and non-calibration working condition verification by constructing a non-calibration working condition verification model and combining a multi-point pressure loading strategy, a dynamic pressure loading module, and an overload test. At the same time, an intelligent algorithm is introduced to optimize the calibration strategy to compensate and correct the multi-factor interaction under complex working conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of sensor devices, and particularly to a method for determining a calibration scheme for a pressure sensor. Background Art

[0002] Pressure sensors are key devices in fields such as industry, aerospace, and medical, and their calibration accuracy directly affects the reliability of applications. Traditional calibration methods for pressure sensors mainly focus on static calibration, and static characteristic tests are carried out by loading and unloading pressures at multiple points. However, modern application scenarios often involve complex working conditions, including rapid dynamic pressure changes, high noise interference, and multi-factor environmental interactions (such as temperature, humidity, vibration, etc.). Traditional calibration methods are difficult to comprehensively reflect the performance of sensors in actual use. In addition, existing calibration schemes often lack a comprehensive evaluation of dynamic response characteristics, overpressure protection capabilities, and long-term stability, resulting in a significant deviation between the calibration results and actual applications. At the same time, during the static calibration process, the compensation ability for non-linearity and multi-factor interaction effects is weak, and it cannot meet the requirements of high precision and complexity. Summary of the Invention

[0003] Aiming at the deficiencies of the prior art, the present invention provides a method for determining a calibration scheme for a pressure sensor to solve the problems raised in the above background art.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] In a first aspect, an embodiment of the present invention provides a method for determining a calibration scheme for a pressure sensor, including the following steps:

[0006] S1. Define the working conditions of the sensor;

[0007] S2. Select a suitable reference device based on the working conditions;

[0008] S3. After the reference device is determined, set the pressure loading points;

[0009] S4. After loading pressures at multiple points, construct a dynamic pressure loading module to verify the dynamic response characteristics of the sensor;

[0010] S5. After verifying the dynamic response characteristics, evaluate the performance of the sensor under complex working conditions through environmental simulation;

[0011] S6. After the environmental simulation evaluation, conduct an overload test for extreme conditions;

[0012] S7. After the overload test, conduct a long-term stability test;

[0013] S8. After the long-term stability test, construct a non-calibration working condition verification model to ensure the applicability of the calibration results;

[0014] S9. Based on the data for validating and correcting the model under non-calibration conditions, combined with intelligent algorithms to optimize the calibration strategy, complete the calibration scheme for the pressure sensor.

[0015] Further optimize this technical solution. In step S1, before designing the calibration scheme, clarify the working conditions of the sensor, including the pressure range, medium type, temperature, and humidity range.

[0016] The clarified working conditions are used to determine the pressure loading points for subsequent tests, the selection of reference equipment, and the requirements for simulating environmental factors.

[0017] For sensors working in high-temperature and high-pressure environments, add additional calibration conditions, including high-temperature-resistant reference equipment or temperature compensation mechanisms.

[0018] Further optimize this technical solution. In step S2, select a high-precision reference pressure source and standard device as the calibration basis, and at the same time, the reference pressure source and standard device match the working conditions of the sensor to be calibrated.

[0019] When the working medium is a corrosive liquid, select a corrosion-resistant reference pressure source.

[0020] Further optimize this technical solution. In step S3, design a multi-point pressure loading strategy to set the pressure loading points. The multi-point pressure loading strategy includes:

[0021] Test the linearity and repeatability of the sensor through multiple pressure points within the full range, including pressure points of 0%, 25%, 50%, 75%, and 100%.

[0022] Increase the test point density in key intervals, including the refined distribution of pressure values below 100 kPa, for evaluating the characteristics of the sensitive area.

[0023] Design cyclic tests for loading and unloading, and detect the hysteresis phenomenon of the sensor.

[0024] Further optimize this technical solution. In step S4, the dynamic pressure loading module simulates rapid pressure changes under real working conditions, including sine waves and step signals.

[0025] Generate dynamic pressure changes by using a programmable pressure regulating device, and record the response time, overshoot situation, and dynamic deviation of the sensor.

[0026] Further optimize this technical solution. In step S5, the environmental simulation includes:

[0027] Simulate the influence of environmental changes on the performance of the sensor. The environmental changes include changes in temperature, humidity, and vibration.

[0028] Perform temperature cycling through an environmental test chamber and record the drift of the sensor output signal;

[0029] Apply a pressure signal on a vibration table and observe the interference of vibration on the output stability;

[0030] Verify the sensor sealing performance through a humidity control chamber.

[0031] Further optimize this technical solution. In step S6, the overload test is used to evaluate the limit performance and protection mechanism of the sensor. The test includes:

[0032] When gradually increasing the pressure to 1.5 - 2 times the rated pressure, observe the output change and reset ability of the sensor, and control the loading rate to avoid damaging the sensor;

[0033] Verify the safety and durability of the sensor by testing whether the protection mechanism is triggered and the sensor can return to the normal state under overpressure conditions.

[0034] Further optimize this technical solution. In step S8, the non - calibrated working condition verification model is as follows:

[0035] ;

[0036] Where,

[0037] : Comprehensive error, used to measure the overall deviation of the sensor under complex working conditions;

[0038] : Static calibration error, resulting from the deviation between the static calibration curve and the actual pressure;

[0039] : Dynamic response error, reflecting the hysteresis, overshoot or undershoot phenomenon of the sensor under rapid pressure changes;

[0040] : Random noise error, the output fluctuation caused by high - frequency noise in the pressure signal;

[0041] : Temperature influence error, simulating the pressure drift caused by environmental temperature changes;

[0042] : Interaction error, the non - linear deviation caused by the coupling effect between various influencing factors.

[0043] Further optimize this technical solution. When using the non - calibrated working condition verification model, it includes:

[0044] Collect complex working condition signal data: including pressure signals under simulated non - calibrated working conditions;

[0045] Sub - item error calculation: Calculate each sub - item error;

[0046] Calculate the comprehensive error: Comprehensively calculate each sub - item error;

[0047] Correction under non - calibrated working conditions: Compensate the sensors with errors;

[0048] Verify the correction result: Verify whether the correction effect meets the standard.

[0049] Further optimize this technical solution. In step S9, the intelligent algorithm for optimizing the calibration strategy includes:

[0050] Use machine learning algorithms to establish a mathematical model of the sensor performance. The model predicts the sensor output performance under untested conditions and automatically optimizes the pressure point settings, compensation methods, and drift correction strategies during the calibration process.

[0051] In a second aspect, an embodiment of the present invention provides a computer device, including a memory and a processor. The memory stores a computer program, where: when the computer program instructions are executed by the processor, the steps of a method for determining a pressure sensor calibration scheme as described in the first aspect of the present invention are implemented.

[0052] In a third aspect, an embodiment of the present invention provides a computer - readable storage medium, on which a computer program is stored, where: when the computer program instructions are executed by the processor, the steps of a method for determining a pressure sensor calibration scheme as described in the first aspect of the present invention are implemented.

[0053] Compared with the prior art, the present invention provides a method for determining a pressure sensor calibration scheme, having the following beneficial effects:

[0054] This method for determining a pressure sensor calibration scheme systematically integrates static calibration, dynamic response testing, environmental simulation, and non - calibrated working condition verification by constructing a non - calibrated working condition verification model, combining a multi - point pressure loading strategy, a dynamic pressure loading module, and an overload test. At the same time, an intelligent algorithm is introduced to optimize the calibration strategy to compensate and correct the multi - factor interaction under complex working conditions. This scheme significantly improves the comprehensiveness and applicability of sensor calibration, ensures that the calibration results are more in line with the actual usage scenarios, and provides a new solution for the performance verification and reliability improvement of high - precision pressure sensors. Brief Description of the Drawings

[0055] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0056] Figure 1 It is a schematic flowchart of a method for determining a calibration scheme for a pressure sensor proposed by the present invention;

[0057] Figure 2 It is a schematic flowchart of a non-calibration working condition verification model in a method for determining a calibration scheme for a pressure sensor proposed by the present invention. Specific embodiments

[0058] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will make a detailed description of the specific embodiments of the present invention with reference to the accompanying drawings of the specification.

[0059] In the following description, many specific details are set forth to facilitate a thorough understanding of the present invention. However, the present invention can also be implemented in other ways different from those described herein. Those skilled in the art can make similar generalizations without departing from the spirit of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0060] Secondly, the so-called "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that can be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selectively exclusive embodiment from other embodiments.

[0061] Embodiment 1:

[0062] Referring to Figures 1 to 2 , which is the first embodiment of the present invention. This embodiment provides a method for determining a calibration scheme for a pressure sensor, including the following steps:

[0063] S1. Define the working conditions of the sensor

[0064] In this embodiment, before designing the calibration scheme, the working conditions of the sensor are defined, including the pressure range, medium type, temperature, and humidity range.

[0065] The defined working conditions are used to determine the pressure loading points for subsequent tests, the selection of reference equipment, and the requirements for simulating environmental factors.

[0066] For sensors working in high-temperature and high-pressure environments, additional calibration conditions are added, including high-temperature-resistant reference equipment or temperature compensation mechanisms.

[0067] S2. Select a suitable reference device based on the working conditions

[0068] In this embodiment, selecting a high-precision and stable reference pressure source and standard device is the key to ensuring calibration accuracy. The reference pressure source can be a pneumatic pressure pump, a hydraulic pump, or an electronic pressure calibrator. When selecting a high-precision reference pressure source and standard device as the calibration basis, its resolution, linearity, and drift characteristics also need to be considered. At the same time, the reference pressure source and standard device match the working conditions of the sensor to be calibrated;

[0069] When the working medium is a corrosive liquid, select a corrosion-resistant reference pressure source, and the calibration certificates of the accuracy and range of the reference device are within the validity period.

[0070] S3. After determining the reference device, set the pressure loading points

[0071] In this embodiment, a multi-point pressure loading strategy is designed to set the pressure loading points to ensure a comprehensive test of the non-linear response characteristics of the pressure sensor. The multi-point pressure loading strategy includes:

[0072] Test the linearity and repeatability of the sensor through multiple pressure points within the full range, including five main points of 0%, 25%, 50%, 75%, and 100%.

[0073] Increase the test point density in the key interval, including the refined distribution of pressure values below 100 kPa, for evaluating the characteristics of the sensitive area.

[0074] Design a cyclic test of loading and unloading, and detect the hysteresis phenomenon of the sensor.

[0075] The pressure loading strategy directly affects the integrity of the test data and the fitting accuracy of the calibration curve, and is an important part of the calibration scheme.

[0076] S4. After multi-point pressure loading, construct a dynamic pressure loading module to verify the dynamic response characteristics of the sensor

[0077] In this embodiment, to further verify the dynamic response characteristics of the sensor, the dynamic pressure loading module simulates rapid pressure changes under real working conditions, including sine waves and step signals;

[0078] Generate dynamic pressure changes by using a programmable pressure regulating device, and record the response time, overshoot, and dynamic deviation of the sensor. This test method is especially suitable for detecting the performance of high-frequency response sensors and can evaluate whether they meet the requirements of actual applications. The addition of the dynamic module can significantly improve the comprehensiveness and practicality of the calibration scheme.

[0079] S5. After verifying the dynamic response characteristics, evaluate the performance of the sensor under complex working conditions through environmental simulation.

[0080] In this embodiment, the environmental simulation includes:

[0081] Simulate the influence of environmental changes on the performance of the sensor. The environmental changes include changes in temperature, humidity, and vibration;

[0082] Conduct temperature cycling through an environmental test chamber and record the drift of the output signal of the sensor;

[0083] Apply a pressure signal on a vibration table and observe the interference of vibration on the output stability;

[0084] Verify the sealing performance of the sensor through a humidity control box.

[0085] S6. After the environmental simulation evaluation, conduct an overload test for extreme conditions

[0086] In this embodiment, the overload test is used to evaluate the ultimate performance and protection mechanism of the sensor. The test includes:

[0087] When gradually increasing the pressure to 1.5 - 2 times the rated pressure, observe the output change and reset ability of the sensor, and control the loading rate to avoid damaging the sensor.

[0088] Verify the safety and durability of the sensor by testing whether the protection mechanism is triggered and the sensor can return to the normal state under overpressure conditions.

[0089] Not only test the ultimate performance of the sensor, but also provide a basis for safety assessment in practical applications.

[0090] S7. After the overload test, conduct a long-term stability test

[0091] In this embodiment, operate for 72 hours or longer under a constant pressure, and monitor the drift trend of the output signal of the sensor. Analyze the stability and noise characteristics of the long-term signal, and judge whether it meets the stability requirements of the application scenario. If significant drift is found, further analyze in combination with the temperature and electrical characteristics of the sensor, and adjust the calibration data according to the results. Focus on the long-term performance and provide users with a realistic long-term usage expectation.

[0092] S8. After the long-term stability test, construct a non-calibrated working condition verification model to ensure the applicability of the calibration result

[0093] In this embodiment, the non-calibrated working condition verification model is as follows:

[0094] ;

[0095] Wherein,

[0096] : Composite error, used to measure the overall deviation of the sensor under complex working conditions;

[0097] : Static calibration error, resulting from the deviation between the static calibration curve and the actual pressure;

[0098] : Dynamic response error, reflecting the hysteresis, overshoot or undershoot of the sensor under rapid pressure changes (such as step signals or oscillatory signals);

[0099] : Random noise error, the output fluctuation caused by high-frequency noise in the pressure signal;

[0100] : Temperature influence error, the pressure drift caused by simulating the change of ambient temperature;

[0101] : Interaction error, the non-linear deviation caused by the coupling effect between various influencing factors.

[0102] Further, when the non-calibration working condition verification model is used, it includes:

[0103] Collect signal data of complex working conditions

[0104] Simulate the pressure signal under non-calibration working conditions, including:

[0105] Rapidly changing step pressure signal (to verify dynamic response).

[0106] Oscillatory signal with superimposed sine wave (to simulate mechanical vibration).

[0107] Random high-frequency noise superimposed signal (to simulate the complex environment where the sensor is located).

[0108] Load these signals as inputs into the sensor under test and the reference sensor, and simultaneously collect their output values.

[0109] Sub-item error calculation

[0110] Static calibration error :

[0111] Compare the calibration curve value and the actual output value of the sensor under static working conditions:

[0112]

[0113] Among them, is the reference pressure, is the actual output of the sensor.

[0114] Dynamic response error :

[0115] Calculate through the step signal response time and the overshoot amplitude :

[0116]

[0117] wherein, is the weight factor, which is adjusted according to the actual application requirements.

[0118] Random noise error :

[0119] Extract the high-frequency noise component using the signal power spectral density (PSD) and calculate:

[0120]

[0121] wherein, is the noise frequency range.

[0122] Temperature influence error :

[0123] According to the temperature drift characteristic curve of the sensor, fit out the drift coefficient through the laboratory verification data :

[0124]

[0125] wherein, is the temperature change.

[0126] Interaction error :

[0127] According to the multi-factor coupling test under composite conditions, describe it using a high-order fitting method (such as polynomial fitting):

[0128]

[0129] wherein, are the error source factors respectively, is the interaction coefficient.

[0130] Calculate the comprehensive error

[0131] Substitute each sub-item error into the comprehensive error formula to obtain the overall deviation value of the sensor under non-calibration working conditions . The smaller this value is, the stronger the applicability of the sensor under complex working conditions.

[0132] Correction under non-calibration working conditions

[0133] Comparison With static calibration error :

[0134] If is greater than the threshold value, it indicates that the dynamic environment has a significant impact on the sensor.

[0135] According to the weight contribution, adjust the compensation algorithm of the calibration curve. For example:

[0136] For sensors with large dynamic errors, use the response compensation algorithm.

[0137] For sensors with significant temperature drift, add an environmental compensation module.

[0138] Verify the correction result

[0139] Place the corrected sensor under non-calibration working conditions again to verify whether it decreases and whether the correction effect meets the standard. Iteratively optimize in this way to finally obtain a calibration model suitable for complex working conditions.

[0140] The final output of this model is the corrected data.

[0141] S9. Based on the data verified and corrected by the model under non-calibration working conditions, combined with intelligent algorithms to optimize the calibration strategy, complete the pressure sensor calibration scheme

[0142] In this embodiment, the intelligent algorithm for optimizing the calibration strategy includes:

[0143] Use machine learning algorithms to establish a mathematical model of sensor performance. The model predicts the output performance of the sensor under untested conditions and automatically optimizes the pressure point settings, compensation methods, and drift correction strategies during calibration. The introduction of intelligent algorithms improves the calibration efficiency and accuracy, and at the same time reduces the resource consumption of actual calibration, which is an important direction for future calibration technologies.

[0144] Embodiment 2:

[0145] This embodiment also provides a computer device, applicable to the situation of a method for determining a pressure sensor calibration scheme, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement a method for determining a pressure sensor calibration scheme as proposed in the above embodiment.

[0146] This embodiment also provides a storage medium, on which a computer program is stored. When the program is executed by the processor, it implements a method for determining a pressure sensor calibration scheme as proposed in the above embodiment.

[0147] The computer device may be a terminal, which includes a processor, a memory, a communication interface, a display screen, and an input device connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a carrier network, NFC (Near Field Communication), or other technologies. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or buttons, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0148] If a function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs, etc., which can store program codes.

[0149] The logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch instructions from the instruction execution system, apparatus, or device and execute the instructions), or in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device.

[0150] More specific examples (a non-exhaustive list) of computer-readable media include the following: electrical connections (electronic devices) having one or more wirings, portable computer diskettes (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber devices, and portable compact disc read-only memory (CDROM). Additionally, the computer-readable media can even be paper or other suitable media on which a program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing it as appropriate, and then storing it in a computer memory.

[0151] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, the multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), and the like.

[0152] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A method for determining a calibration scheme of a pressure sensor, characterized in that, It includes the following steps: S1. Define the working conditions of the sensor; S2. Based on the working conditions, select a suitable reference device; S3. After determining the reference device, set the pressure loading points; S4. After multi-point pressure loading, construct a dynamic pressure loading module to verify the dynamic response characteristics of the sensor; S5. After verifying the dynamic response characteristics, evaluate the performance of the sensor under complex working conditions through environmental simulation; S6. After environmental simulation evaluation, conduct an overload test for extreme conditions; S7. After the overload test, conduct a long-term stability test; S8. After the long-term stability test, construct a non-calibrated working condition verification model to ensure the applicability of the calibration results; Calculate the sub-item errors in the non-calibrated working condition verification model, including: static calibration error, dynamic response error, random noise error, temperature influence error, interaction error; The non-calibrated working condition verification model is as follows: ； Wherein, : Composite error, used to measure the overall deviation of the sensor under complex working conditions; : Static calibration error, which comes from the deviation between the static calibration curve and the actual pressure; : Dynamic response error, which reflects the hysteresis, overshoot or undershoot phenomena of the sensor under rapid pressure changes; : Random noise error, the output fluctuation caused by high-frequency noise in the pressure signal, and the high-frequency noise component is extracted by using the signal power spectral density; : Temperature influence error, simulating the pressure drift caused by the change of the ambient temperature. According to the temperature drift characteristic curve of the sensor, the drift coefficient is fitted through the laboratory verification data : ； Among them, is the temperature change amount; : Interaction error, the non-linear deviation caused by the coupling effect between various influencing factors, is described using a high-order fitting method based on multi-factor coupling experiments under composite conditions: ； Among them, are error source factors respectively, is the interaction coefficient; S9. Based on the data corrected by the non-calibrated working condition verification model, combine intelligent algorithms to optimize the calibration strategy to complete the pressure sensor calibration scheme.

2. The method for determining a calibration scheme of a pressure sensor according to claim 1, wherein, In step S1, before designing the calibration scheme, define the working conditions of the sensor, including the pressure range, medium type, temperature, and humidity range; The defined working conditions are used to determine the pressure loading points for subsequent tests, the selection of reference devices, and the requirements for simulating environmental factors; For sensors working in high-temperature and high-pressure environments, add additional calibration conditions, including high-temperature-resistant reference devices or temperature compensation mechanisms.

3. The determination method of a pressure sensor calibration scheme according to claim 1, characterized in that In step S2, select a high-precision reference pressure source and a standard device as the calibration basis, and at the same time, the reference pressure source and the standard device match the working conditions of the sensor to be calibrated; When the working medium is a corrosive liquid, select a corrosion-resistant reference pressure source.

4. The method for determining a calibration scheme of a pressure sensor according to claim 1, characterized in that, In step S3, design a multi-point pressure loading strategy to set the pressure loading points. The multi-point pressure loading strategy includes: Test the linearity and repeatability of the sensor through multiple pressure points within the full range, including pressure points of 0%, 25%, 50%, 75%, and 100%; Increase the test point density in the key interval, including the refined distribution of pressure values below 100 kPa, for evaluating the characteristics of the sensitive area; Design a cyclic test of loading and unloading and detect the hysteresis phenomenon of the sensor.

5. The determination method of a pressure sensor calibration scheme according to claim 1, characterized in that, In step S4, the dynamic pressure loading module simulates the rapid pressure changes under real working conditions, including sine waves and step signals; Generate dynamic pressure changes by using a programmable pressure regulating device and record the response time, overshoot situation, and dynamic deviation of the sensor.

6. The method for determining a calibration scheme of a pressure sensor according to claim 1, wherein In step S5, the environmental simulation includes: Simulate the influence of environmental changes on the performance of the sensor. The environmental changes include changes in temperature, humidity, and vibration; Conduct a temperature cycle through an environmental test chamber and record the drift of the output signal of the sensor; Apply a pressure signal on a vibration table and observe the interference of vibration on the output stability; Verify the sealing performance of the sensor through a humidity control box.

7. A method for determining a calibration scheme of a pressure sensor according to claim 1, characterized in that, In step S6, the overload test is used to evaluate the extreme performance and protection mechanism of the sensor. The test includes: When gradually increasing the pressure to 1.5 - 2 times the rated pressure, observe the output change and reset ability of the sensor, and control the loading rate to avoid damaging the sensor; Verify the safety and durability of the sensor by testing whether the protection mechanism is triggered under overvoltage conditions and whether it can return to the normal state.

8. The determination method of a pressure sensor calibration scheme according to claim 1, characterized in that, When the non-calibration working condition verification model is in use, it includes: Collect complex working condition signal data: including pressure signals under simulated non-calibration working conditions; Calculate sub-item errors: calculate each sub-item error; Calculate the comprehensive error: comprehensively calculate each sub-item error; Correction under non-calibration working conditions: compensate the sensors with errors; Verify the correction result: verify whether the correction effect meets the standard.

9. The determination method of a pressure sensor calibration scheme according to claim 1, characterized in that In step S9, the intelligent algorithm for optimizing the calibration strategy includes: Use machine learning algorithms to establish a mathematical model of the sensor performance. The model predicts the sensor output performance under untested conditions and automatically optimizes the pressure point settings, compensation methods, and drift correction strategies during calibration.

Images