Method for determining calibration scheme of pressure sensor

Abstract

The invention discloses a method for determining a calibration scheme of a pressure sensor, and relates to the technical field of sensor equipment. Comprising the following steps: determining the working condition of the sensor, selecting adaptive reference equipment, setting a pressure loading point, constructing a dynamic pressure loading module, evaluating the performance of the sensor under a complex working condition through environmental simulation, carrying out an overload test aiming at an extreme condition, carrying out a long-time stability test, and constructing a non-calibration working condition verification model. And optimizing a calibration strategy by an intelligent algorithm to complete a pressure sensor calibration scheme. According to the method for determining the calibration scheme of the pressure sensor, static calibration, dynamic response test, environmental simulation and non-calibration working condition verification are systematically integrated by constructing a non-calibration working condition verification model and combining a multi-point pressure loading strategy, a dynamic pressure loading module and overload test. Meanwhile, an intelligent algorithm is introduced to optimize a calibration strategy, and multi-factor interaction under complex working conditions is compensated and corrected.

Description

Technical Field

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

[0002] Pressure sensors are key components in industries such as industry, aerospace, and medicine, and their calibration accuracy directly affects the reliability of applications. Traditional pressure sensor calibration methods are mainly based on static calibration, which tests static characteristics by loading and unloading pressure 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 fully 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 significant deviations between calibration results and actual applications. At the same time, during the static calibration process, the compensation capability for nonlinear and multi-factor interaction effects is weak, and cannot meet high precision and complexity requirements. Summary of the invention

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

[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 pressure sensor calibration scheme, comprising the following steps:

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

[0007] S2. Select the appropriate reference equipment based on the working conditions;

[0008] S3. After the reference equipment is determined, set the pressure loading point;

[0009] S4. After multi-point pressure loading, a dynamic pressure loading module is constructed 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 environmental simulation evaluation, overload test is performed for extreme conditions;

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

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

[0014] S9. Based on the data of model correction verified by non-calibration working conditions, the calibration strategy is optimized by intelligent algorithm to complete the pressure sensor calibration solution.

[0015] To further optimize the technical solution, in step S1, before designing the calibration scheme, the working conditions of the sensor are clarified, including the pressure range, medium type, temperature and humidity range;

[0016] Clear working conditions are used to determine the pressure loading points, reference equipment selection and environmental factor simulation requirements for subsequent tests;

[0017] Sensors operating in high temperature and high pressure environments add additional calibration conditions, including high temperature reference devices or temperature compensation mechanisms.

[0018] To further optimize the technical solution, in step S2, a high-precision reference pressure source and a standard are selected as the calibration basis, and the reference pressure source and the standard 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] To further optimize the technical solution, in step S3, a multi-point pressure loading strategy is designed to set the pressure loading points, and the multi-point pressure loading strategy includes:

[0021] The linearity and repeatability of the sensor are tested at multiple pressure points within the full range, including 0%, 25%, 50%, 75%, and 100% pressure points;

[0022] Increase the density of test points in key areas, including detailed distribution of pressure values ​​below 100 kPa, to evaluate the characteristics of sensitive areas;

[0023] Design a cyclic test of loading and unloading and detect the hysteresis of the sensor.

[0024] To further optimize the 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] By using a programmable pressure regulator, dynamic pressure changes are generated and the sensor response time, overshoot and dynamic deviation are recorded.

[0026] To further optimize the technical solution, in step S5, the environmental simulation includes:

[0027] Simulate the impact of environmental changes on sensor performance, including changes in temperature, humidity, and vibration;

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

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

[0030] Verify sensor seal performance in a humidity controlled chamber.

[0031] To further optimize the technical solution, in step S6, the overload test is used to evaluate the limit performance and protection mechanism of the sensor, and the test includes:

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

[0033] The safety and durability of the sensor can be verified by testing whether the sensor triggers the protection mechanism under overpressure and can recover to normal state.

[0034] To further optimize the technical solution, in step S8, the non-calibration working condition verification model is as follows:

[0035] ;

[0036] in,

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

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

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

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

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

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

[0043] To further optimize the technical solution, the non-calibration working condition verification model, when used, includes:

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

[0045] Calculation of sub-item errors: Calculate each sub-item error;

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

[0047] Correction under non-calibration conditions: compensation for sensors with errors;

[0048] Verify correction results: Verify whether the correction effect meets the requirements.

[0049] To further optimize the technical solution, in step S9, the intelligent algorithm optimization calibration strategy includes:

[0050] A mathematical model of sensor performance is established using a machine learning algorithm. The model predicts the sensor output performance under untested conditions and automatically optimizes the pressure point setting, compensation method, and drift correction strategy during the calibration process.

[0051] In a second aspect, an embodiment of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, wherein: 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 having a computer program stored thereon, wherein: when the computer program instructions are executed by a 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, which has the following beneficial effects:

[0054] The method for determining the pressure sensor calibration scheme systematically integrates static calibration, dynamic response testing, environmental simulation and non-calibration working condition verification by constructing a non-calibration 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 and compensate for 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 actual usage scenarios, and provides a new solution for performance verification and reliability improvement of high-precision pressure sensors. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0056] Figure 1 A schematic flow chart of a method for determining a pressure sensor calibration scheme proposed by the present invention;

[0057] Figure 2 A schematic flow chart of a non-calibration working condition verification model in a method for determining a pressure sensor calibration scheme proposed in the present invention. DETAILED DESCRIPTION

[0058] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0059] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0060] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0061] Embodiment 1:

[0062] Reference Figure 1-2 , which is the first embodiment of the present invention, provides a method for determining a pressure sensor calibration scheme, comprising the following steps:

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

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

[0065] Clear working conditions are used to determine the pressure loading points, reference equipment selection and environmental factor simulation requirements for subsequent tests.

[0066] Sensors operating in high temperature and high pressure environments add additional calibration conditions, including high temperature reference devices or temperature compensation mechanisms.

[0067] S2. Select appropriate reference equipment based on working conditions

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

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

[0070] S3. After the reference equipment is determined, set the pressure loading point

[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 nonlinear response characteristics of the pressure sensor. The multi-point pressure loading strategy includes:

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

[0073] Increase the density of test points in key areas, including a detailed distribution of pressure values ​​below 100 kPa, to evaluate the characteristics of sensitive areas.

[0074] Design a cyclic test of loading and unloading and detect the hysteresis 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 plan.

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

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

[0078] By using a programmable pressure regulator, dynamic pressure changes are generated and the sensor's response time, overshoot, and dynamic deviation are recorded. This test method is particularly suitable for testing the performance of high-frequency response sensors and can evaluate whether they meet the needs of practical applications. The addition of a dynamic module can significantly improve the comprehensiveness and practicality of the calibration solution.

[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 impact of environmental changes on sensor performance, including changes in temperature, humidity, and vibration;

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

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

[0084] Verify sensor seal performance in a humidity controlled chamber.

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

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

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

[0088] The safety and durability of the sensor can be verified by testing whether the sensor triggers the protection mechanism under overpressure and can recover to normal state.

[0089] It not only tests the extreme performance of the sensor, but also provides a basis for safety assessment in practical applications.

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

[0091] In this embodiment, the sensor output signal drift trend is monitored for 72 hours or longer under constant pressure. The stability and noise characteristics of the long-term signal are analyzed to determine whether it meets the stability requirements of the application scenario. If significant drift is found, further analysis can be performed in combination with the temperature and electrical characteristics of the sensor, and the calibration data can be adjusted based on the results. Focus on long-term performance to provide users with real long-term usage expectations.

[0092] S8. After long-term stability testing, build a non-calibration working condition verification model to ensure the applicability of the calibration results

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

[0094] ;

[0095] in,

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

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

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

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

[0100] : Temperature effect error, simulating the pressure drift caused by ambient temperature changes;

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

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

[0103] Collecting complex working condition signal data

[0104] Simulate pressure signals under non-calibration conditions, including:

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

[0106] An oscillating signal with a superimposed sine wave (simulating mechanical vibration).

[0107] Random high-frequency noise superimposed signal (simulating the complex environment in which the sensor is located).

[0108] These signals are applied as input to the sensor under test and the reference sensor, while their output values ​​are acquired simultaneously.

[0109] Calculation of partial error

[0110] Static calibration error :

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

[0112]

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

[0114] Dynamic response error :

[0115] Response time via step signal and overshoot amplitude calculate:

[0116]

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

[0118] Random noise error :

[0119] The signal power spectral density (PSD) is used to extract the high-frequency noise component and calculate:

[0120]

[0121] in, is the noise frequency range.

[0122] Temperature Effect Error :

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

[0124]

[0125] in, is the temperature change.

[0126] Interaction Error :

[0127] According to the multi-factor coupling test under complex conditions, high-order fitting methods (such as polynomial fitting) are used to describe:

[0128]

[0129] in, are the error source factors, 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 conditions. The smaller the value, the more applicable the sensor is in complex working conditions.

[0132] Correction under non-calibration conditions

[0133] contrast Static calibration error :

[0134] if If it is greater than the threshold, it means 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, a response compensation algorithm is used.

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

[0138] Verify the correction results

[0139] Place the corrected sensor under non-calibration conditions again to verify Whether it is reduced and whether the correction effect meets the standard. Through iterative optimization, a calibration model suitable for complex working conditions is finally obtained.

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

[0141] S9. Based on the data of model correction under non-calibration conditions, the calibration strategy is optimized by combining intelligent algorithms to complete the pressure sensor calibration solution.

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

[0143] A mathematical model of sensor performance is established using machine learning algorithms. The model predicts the sensor output performance under untested conditions and automatically optimizes the pressure point setting, compensation method, and drift correction strategy during the calibration process. The introduction of intelligent algorithms improves calibration efficiency and accuracy while reducing the resource consumption of actual calibration, which is an important direction for future calibration technology.

[0144] Embodiment 2:

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

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

[0147] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through 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 a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0148] If the 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, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

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

[0150] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk case (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored 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, 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 by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit with a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit with a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0152] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for determining a pressure sensor calibration scheme, characterized in that: The following steps are involved: S1. Clarify the working conditions of the sensor; S2. Select the appropriate reference equipment based on the working conditions; S3. After the reference equipment is determined, set the pressure loading point; S4. After multi-point pressure loading, a dynamic pressure loading module is constructed 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, overload test is performed for extreme conditions; S7. After the overload test, a long-term stability test is performed; S8. After long-term stability testing, a non-calibration working condition verification model is constructed to ensure the applicability of the calibration results; S9. Based on the data of model correction verified by non-calibration working conditions, the calibration strategy is optimized by intelligent algorithm to complete the pressure sensor calibration solution.

2. The method for determining a pressure sensor calibration scheme according to claim 1, characterized in that: In the step S1, before designing the calibration scheme, the working conditions of the sensor are clarified, including the pressure range, medium type, temperature and humidity range; Clear working conditions are used to determine the pressure loading points, reference equipment selection and environmental factor simulation requirements for subsequent tests; Sensors operating in high temperature and high pressure environments add additional calibration conditions, including high temperature reference devices or temperature compensation mechanisms.

3. The method for determining a pressure sensor calibration scheme according to claim 1, characterized in that: In step S2, a high-precision reference pressure source and a standard are selected as the calibration basis, and the reference pressure source and the standard 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 pressure sensor calibration scheme according to claim 1, characterized in that: In step S3, a multi-point pressure loading strategy is designed to set the pressure loading points, and the multi-point pressure loading strategy includes: The linearity and repeatability of the sensor are tested at multiple pressure points within the full range, including 0%, 25%, 50%, 75%, and 100% pressure points; Increase the density of test points in key areas, including detailed distribution of pressure values ​​below 100 kPa, to evaluate the characteristics of sensitive areas; Design a cyclic test of loading and unloading and detect the hysteresis of the sensor.

5. The method for determining a pressure sensor calibration scheme according to claim 1, characterized in that: In step S4, the dynamic pressure loading module simulates rapid pressure changes under real working conditions, including sine waves and step signals; By using a programmable pressure regulator, dynamic pressure changes are generated and the sensor response time, overshoot and dynamic deviation are recorded.

6. The method for determining a pressure sensor calibration scheme according to claim 1, characterized in that: In step S5, the environmental simulation includes: Simulate the impact of environmental changes on sensor performance, including changes in temperature, humidity, and vibration; Perform temperature cycling in an environmental test chamber and record the drift of the sensor output signal; Apply a pressure signal on a vibration table to observe the interference of vibration on output stability; Verify sensor seal performance in a humidity controlled chamber.

7. The method for determining a pressure sensor calibration scheme according to claim 1, characterized in that: In step S6, the overload test is used to evaluate the limit performance and protection mechanism of the sensor, and the test includes: When gradually increasing the pressure to 1.5-2 times the rated pressure, observe the output changes and reset ability of the sensor, and control the loading rate to avoid damaging the sensor; The safety and durability of the sensor can be verified by testing whether the sensor triggers the protection mechanism under overpressure and can recover to normal state.

8. The method for determining a pressure sensor calibration scheme according to claim 1, characterized in that: In step S8, the non-calibration working condition verification model is as follows: ； in, : Comprehensive 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 of the sensor under rapid pressure changes; : Random noise error, output fluctuation caused by high-frequency noise in the pressure signal; : Temperature effect error, simulating the pressure drift caused by ambient temperature changes; : Interaction error, nonlinear deviation caused by the coupling effect between various influencing factors.

9. The method for determining a pressure sensor calibration scheme according to claim 8, characterized in that: The non-calibration working condition verification model, when used, includes: Collect complex working condition signal data: including simulating pressure signals under non-calibrated working conditions; Calculation of sub-item errors: Calculate each sub-item error; Calculate the comprehensive error: Calculate the comprehensive error of each sub-item; Correction under non-calibration conditions: compensation for sensors with errors; Verify correction results: Verify whether the correction effect meets the requirements.

10. The method for determining a pressure sensor calibration scheme according to claim 1, characterized in that: In step S9, the intelligent algorithm optimization calibration strategy includes: A mathematical model of sensor performance is established using a machine learning algorithm. The model predicts the sensor output performance under untested conditions and automatically optimizes the pressure point setting, compensation method, and drift correction strategy during the calibration process.

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