Application method of a resonant pressure sensor

Abstract

The present invention discloses an application method of a resonant pressure sensor, which relates to the technical field of sensor equipment, and includes the following steps: sensor site selection and environmental modeling, adjustment of the resonant cavity based on environmental modeling, installation of a pressure buffer device after adjustment, configuration of an embedded temperature compensation module in the sensor, multi-frequency resonance mode switching, design of a resonant frequency amplification circuit, real-time diagnosis of abnormal pressure fluctuations, and distributed deployment of a sensor array. The application method of the resonant pressure sensor significantly improves the adaptability and reliability of the resonant pressure sensor in complex environments by embedding a temperature compensation module and a real-time diagnosis mechanism. On the one hand, the temperature compensation module effectively eliminates the influence of frequency drift by using a dynamic adjustment algorithm, and ensures the measurement accuracy of the sensor in a wide temperature range; on the other hand, by introducing acoustic resonance spectrum analysis, real-time early warning of abnormal conditions such as blockage and leakage is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of sensor equipment, and in particular to an application method of a resonant pressure sensor. Background Art

[0002] Resonant pressure sensor is a high-precision measurement device based on the change of resonant frequency. It is widely used in industrial pipelines, aerospace, medical equipment and other scenarios that require real-time monitoring of pressure changes. Compared with traditional pressure sensors, resonant pressure sensors reduce sensitivity to external interference through frequency response and have higher stability and long-term reliability. However, due to the complex and changeable working environment, such as temperature fluctuations, changes in fluid properties, and aging of the equipment itself, the existing technology still has the following deficiencies in adaptability and application depth:

[0003] Impact of temperature drift: Existing technologies lack dynamic compensation for changes in ambient temperature, which makes it difficult to completely eliminate frequency drift and limits the measurement accuracy of sensors in extreme environments.

[0004] Underutilization of acoustic properties: Traditional methods focus only on direct measurement of pressure signals, but fail to utilize the acoustic properties of resonant pressure sensors for abnormality diagnosis, wasting potential sources of information. Summary of the invention

[0005] In view of the deficiencies of the prior art, the present invention provides an application method of a resonant pressure sensor to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides an application method of a resonant pressure sensor, comprising the following steps:

[0008] S1, sensor site selection and environment modeling;

[0009] S2. Adjust the resonant cavity based on environmental modeling;

[0010] S3. Install the pressure buffer device after adjustment;

[0011] S4. After installing the pressure buffer device, configure the embedded temperature compensation module;

[0012] S5. Design multi-frequency resonance mode switching;

[0013] S6. Design a resonant frequency amplification circuit;

[0014] S7, based on the selected multi-frequency resonance mode and the resonance frequency amplification circuit, diagnose abnormal pressure fluctuations in real time;

[0015] S8. Perform distributed deployment of sensor arrays.

[0016] To further optimize the technical solution, in step S1, before installing the sensor, the target environment is analyzed, including pressure distribution, temperature gradient, and fluid properties;

[0017] The modeling tool is used to create a three-dimensional pressure distribution simulation diagram of the target area to predict the pressure variation patterns and noise interference points at different locations.

[0018] To further optimize the technical solution, in step S2, the size and material of the resonant cavity are adjusted for different environmental pressure ranges so that the resonant frequency is most sensitive to the expected pressure range;

[0019] By adjusting the length, width and thickness of the cavity, the resonant frequency can be changed to match the specific application scenario.

[0020] To further optimize the technical solution, in step S4, the embedded temperature compensation module has a built-in dynamic nonlinear correction model, which sets the sensor resonant frequency for the resonant pressure sensor. The drift is affected by the ambient temperature The influence of temperature on the elastic modulus of the resonant cavity , size change and frequency response It has nonlinear characteristics;

[0021] The dynamic nonlinear correction model includes the relationship between temperature and resonant frequency, the nonlinear relationship between elastic modulus and temperature, the relationship between dimensional change and temperature, and a dynamic temperature compensation correction formula.

[0022] To further optimize the technical solution, in the dynamic nonlinear correction model:

[0023] The relationship between temperature and resonant frequency is shown below:

[0024] ;

[0025] in,

[0026] : Nominal resonant frequency, i.e. initial frequency;

[0027] : proportionality factor related to material properties and sensor structure;

[0028] : Elastic modulus as a function of temperature;

[0029] : The expansion / contraction function of the cavity geometry with temperature;

[0030] The nonlinear relationship between elastic modulus and temperature is shown below:

[0031] ;

[0032] in,

[0033] : elastic modulus of the material at reference temperature;

[0034] : nonlinear coefficient related to the thermophysical properties of the material;

[0035] The relationship between dimensional change and temperature is shown below:

[0036] ;

[0037] in,

[0038] : Cavity reference length;

[0039] : Linear expansion coefficient of the material;

[0040] : Changes in the geometric dimensions of the resonant cavity;

[0041] : Changes in temperature.

[0042] The dynamic temperature compensation correction formula is as follows:

[0043] ;

[0044] in,

[0045] : The resonant frequency after correction;

[0046] : Temperature compensation coefficient, dynamically adjusted to adapt to the real-time ambient temperature;

[0047] : Reference temperature, that is, calibration value.

[0048] Further optimizing the technical solution, in step S5, the multi-frequency resonance mode is based on adapting to different pressure measurement requirements, including static pressure monitoring and dynamic pressure fluctuation analysis;

[0049] Static pressure monitoring, the sensor preferentially captures low-frequency stable pressure signals;

[0050] Dynamic pressure fluctuation analysis, enhancing the high frequency response of the sensor to monitor rapidly fluctuating pressures.

[0051] To further optimize the technical solution, in step S6, the resonant frequency amplification circuit is used to amplify the frequency offset signal, thereby improving the measurement accuracy;

[0052] The resonant frequency amplification circuit includes a high-sensitivity frequency filter and a low-noise amplifier to ensure effective extraction of weak signals.

[0053] Further optimizing the technical solution, in step S7, the real-time diagnosis is performed based on the resonance spectrum mode analytical model, in which the frequency response of the sensor resonant sound wave is set to be affected by the pressure , fluid density , Pipeline geometry and fluid velocity The impact of

[0054] The resonance spectrum mode analysis model includes the relationship between the acoustic resonance frequency and pressure, the spectrum shift of abnormal pressure fluctuations, and the real-time acoustic wave mode diagnosis model.

[0055] To further optimize the technical solution, in the resonance spectrum mode analysis model:

[0056] The relationship between the resonant frequency of sound waves and pressure is shown below:

[0057] ;

[0058] in,

[0059] : resonant sound wave frequency;

[0060] : acoustic resonance mode, which is an integer order;

[0061] : The effective length of the pipe length or the resonant cavity inside the sensor;

[0062] : The adiabatic index of the fluid, which is 1.4 in air;

[0063] : Instantaneous pressure of the fluid;

[0064] : fluid density;

[0065] The spectrum shifts due to abnormal pressure fluctuations. When the pressure fluctuates abnormally, the sound wave frequency shifts. , the frequency offset is as follows:

[0066] ;

[0067] in,

[0068] and : Base pressure and density;

[0069] and : Abnormal changes in pressure and density;

[0070] Real-time acoustic wave pattern diagnosis model, introducing the power spectrum density of acoustic waves , and define the outlier factor , the model is as follows:

[0071] ;

[0072] in,

[0073] : The threshold range of frequency deviation is used to limit the diagnostic sensitivity;

[0074] : Spectral weight function, adjusted according to the anomaly type, giving higher weight to high-frequency anomalies;

[0075] : Power spectral density of the acoustic signal, obtained by fast Fourier transform.

[0076] To further optimize the technical solution, in step S8, the sensors are deployed in a distributed manner to form a pressure monitoring network;

[0077] Each sensor operates independently and is connected to the central control unit via a wireless or wired communication module to achieve centralized analysis of data.

[0078] In a second aspect, an embodiment of the present invention provides a computer device, including 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 the application method of a resonant pressure sensor as described in the first aspect of the present invention are implemented.

[0079] 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 applying a resonant pressure sensor as described in the first aspect of the present invention are implemented.

[0080] Compared with the prior art, the present invention provides an application method of a resonant pressure sensor, which has the following beneficial effects:

[0081] The application method of the resonant pressure sensor significantly improves the adaptability and reliability of the resonant pressure sensor in complex environments by embedding a temperature compensation module and a real-time diagnosis mechanism. On the one hand, the temperature compensation module effectively eliminates the influence of frequency drift by using a dynamic adjustment algorithm, ensuring the measurement accuracy of the sensor in a wide temperature range; on the other hand, by introducing acoustic wave resonance spectrum analysis, the acoustic characteristics of the sensor are innovatively transformed into a system abnormality diagnosis tool, realizing real-time early warning of abnormal conditions such as blockage and leakage. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] 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.

[0083] Figure 1 A schematic flow chart of an application method of a resonant pressure sensor proposed by the present invention;

[0084] Figure 2 A schematic flow chart of a dynamic nonlinear correction model in an application method of a resonant pressure sensor proposed by the present invention;

[0085] Figure 3 A schematic flow chart of a resonance spectrum mode analysis model in an application method of a resonance pressure sensor proposed in the present invention. DETAILED DESCRIPTION

[0086] 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.

[0087] 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.

[0088] 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.

[0089] Embodiment 1:

[0090] Reference Figure 1, which is the first embodiment of the present invention, provides an application method of a resonant pressure sensor, comprising the following steps:

[0091] S1. Sensor site selection and environmental modeling

[0092] Site selection is fundamental to sensor performance, especially for resonant pressure sensors, which are sensitive to noise and environmental disturbances. In complex fluid systems, such as pipeline networks or reactors, pressure distribution may vary due to changes in fluid velocity, viscosity, and eddy currents. Through simulation analysis, it is possible to avoid installing sensors in pressure blind spots or areas of severe disturbance, thereby ensuring data stability. During the simulation process, precise fluid dynamic parameters such as viscosity, density, temperature, and boundary conditions need to be input to optimize the sensor installation point.

[0093] In this embodiment, before installing the sensor, the target environment is analyzed, including pressure distribution, temperature gradient, and fluid properties;

[0094] The modeling tool is used to create a three-dimensional pressure distribution simulation diagram of the target area to predict the pressure variation patterns and noise interference points at different locations.

[0095] S2. Adjust the resonant cavity based on environmental modeling

[0096] The geometry and material of the resonant cavity directly determine its frequency sensitivity range. By adjusting the length, width, and thickness of the cavity, the resonant frequency can be changed to match the specific application scenario. For example, in a high-pressure environment, a material with a higher elastic modulus can be selected, and the cavity geometry can be designed to improve the response to high-frequency pressure signals.

[0097] In this embodiment, the size and material of the resonant cavity are adjusted for different environmental pressure ranges so that its resonant frequency is most sensitive to the expected pressure range;

[0098] By adjusting the length, width and thickness of the cavity, the resonant frequency can be changed to match the specific application scenario.

[0099] S3. Install the pressure buffer device after adjustment

[0100] In high-speed fluid or pulsating pressure systems, pressure sensors may be affected by spike interference, which can cause signal distortion. These problems can be effectively alleviated by designing pressure buffer devices, such as micro-cavities or filter membranes. The buffer device can stabilize the fluid pressure distribution by changing the flow direction of the fluid or reducing its kinetic energy.

[0101] In this embodiment, a micro pressure buffer device is installed upstream of the sensor to filter out occasional pressure shocks or spike interferences in the fluid system and ensure measurement stability.

[0102] S4. Configure embedded temperature compensation module in the sensor

[0103] The resonant frequency of the resonant pressure sensor is sensitive to temperature, and temperature fluctuations may cause signal inaccuracy. By embedding a temperature compensation module, the temperature around the sensor can be detected in real time and the signal processing algorithm can be adjusted to correct the frequency drift. Thermistors or thermocouples are used to achieve accurate temperature measurement and are combined with pressure signals for processing.

[0104] In this embodiment, the embedded temperature compensation module has a built-in dynamic nonlinear correction model. The model sets the sensor resonant frequency for the resonant pressure sensor. The drift is affected by the ambient temperature The influence of temperature on the elastic modulus of the resonant cavity , size change and frequency response It has nonlinear characteristics;

[0105] The dynamic nonlinear correction model includes the relationship between temperature and resonant frequency, the nonlinear relationship between elastic modulus and temperature, the relationship between dimensional change and temperature, and a dynamic temperature compensation correction formula.

[0106] Furthermore, in the dynamic nonlinear correction model:

[0107] The relationship between temperature and resonant frequency is shown below:

[0108] ;

[0109] in,

[0110] : Nominal resonant frequency, i.e. initial frequency;

[0111] : proportionality factor related to material properties and sensor structure;

[0112] : Elastic modulus as a function of temperature;

[0113] : The expansion / contraction function of the cavity geometry with temperature;

[0114] The nonlinear relationship between elastic modulus and temperature is shown below:

[0115] ;

[0116] in,

[0117] : elastic modulus of the material at reference temperature;

[0118] : nonlinear coefficient related to the thermophysical properties of the material;

[0119] The relationship between dimensional change and temperature is shown below:

[0120] ;

[0121] in,

[0122] : Cavity reference length;

[0123] : Linear expansion coefficient of the material;

[0124] : Changes in the geometric dimensions of the resonant cavity;

[0125] : Changes in temperature.

[0126] The dynamic temperature compensation correction formula is as follows:

[0127] ;

[0128] in,

[0129] : The resonant frequency after correction;

[0130] : Temperature compensation coefficient, dynamically adjusted to adapt to the real-time ambient temperature;

[0131] : Reference temperature, that is, calibration value.

[0132] S5, multi-frequency resonance mode switching

[0133] Traditional resonant pressure sensors are usually designed for a single resonant frequency, which makes it difficult to take into account different types of pressure signals in complex environments. Through the multi-frequency resonance mode switching design, the sensor can automatically adjust the working mode according to the characteristics of the pressure signal.

[0134] In this embodiment, the multi-frequency resonance mode is based on adapting to different pressure measurement requirements, including static pressure monitoring and dynamic pressure fluctuation analysis;

[0135] Static pressure monitoring, the sensor preferentially captures low-frequency stable pressure signals;

[0136] Dynamic pressure fluctuation analysis, enhancing the high frequency response of the sensor to monitor rapidly fluctuating pressures.

[0137] S6. Design the resonant frequency amplification circuit

[0138] In this embodiment, the resonant frequency amplification circuit is used to amplify the frequency offset signal, thereby improving the measurement accuracy;

[0139] The resonant frequency amplification circuit includes a high-sensitivity frequency filter and a low-noise amplifier to ensure effective extraction of weak signals.

[0140] S7, Real-time diagnosis of abnormal pressure fluctuations

[0141] Resonant pressure sensors generate specific acoustic resonance modes when working. By collecting these resonant sound wave signals and combining them with acoustic analysis algorithms, pressure changes in fluid systems can be diagnosed in real time. For example, in industrial pipelines, abnormal pressure fluctuations may mean blockages or leaks. By analyzing the characteristics of the sound wave spectrum, possible problems can be warned in advance.

[0142] In this embodiment, the real-time diagnosis is performed based on a resonance spectrum mode analytical model, in which the frequency response of the sensor resonant sound wave is set to be affected by the pressure. , fluid density , Pipeline geometry and fluid velocity The impact of

[0143] The resonance spectrum mode analysis model includes the relationship between the acoustic resonance frequency and pressure, the spectrum shift of abnormal pressure fluctuations, and the real-time acoustic wave mode diagnosis model.

[0144] Furthermore, in the resonance spectrum mode analytical model:

[0145] The relationship between the resonant frequency of sound waves and pressure is shown below:

[0146] ;

[0147] in,

[0148] : resonant sound wave frequency;

[0149] : acoustic resonance mode, which is an integer order;

[0150] : The effective length of the pipe length or the resonant cavity inside the sensor;

[0151] : The adiabatic index of the fluid, which is 1.4 in air;

[0152] : Instantaneous pressure of the fluid;

[0153] : fluid density;

[0154] The spectrum shifts due to abnormal pressure fluctuations. When the pressure fluctuates abnormally, the sound wave frequency shifts. , the frequency offset is as follows:

[0155] ;

[0156] in,

[0157] and : Base pressure and density;

[0158] and : Abnormal changes in pressure and density;

[0159] Real-time acoustic wave pattern diagnosis model, introducing the power spectrum density of acoustic waves , and define the outlier factor , the model is as follows:

[0160] ;

[0161] in,

[0162] : The threshold range of frequency deviation is used to limit the diagnostic sensitivity;

[0163] : Spectral weight function, adjusted according to the anomaly type, giving higher weight to high-frequency anomalies;

[0164] : Power spectral density of the acoustic signal, obtained by fast Fourier transform.

[0165] S8. Distributed deployment of sensor arrays

[0166] The monitoring range of a single sensor is limited, especially in large-scale fluid systems such as urban water supply networks or large reactors.

[0167] In this embodiment, the sensors are deployed in a distributed manner to cover a wider area and form a pressure monitoring network;

[0168] Each sensor operates independently and is connected to the central control unit via a wireless or wired communication module to achieve centralized analysis of data.

[0169] Optimize the layout of sensors, improve the measurement accuracy of the overall system through the collaborative work between sensors, and use data fusion algorithms to generate real-time pressure distribution maps.

[0170] Embodiment 2:

[0171] Reference Figure 2-Figure 3, which is the second embodiment of the present invention, and provides a method for using a dynamic nonlinear correction model and a resonant spectrum mode analysis model.

[0172] The dynamic nonlinear correction model, when used, includes:

[0173] Real-time temperature detection:

[0174] High-precision temperature-sensitive elements (such as thermocouples or temperature-sensitive resistors) are arranged around the resonant pressure sensor to detect real-time temperature. The temperature signal is converted into a digital signal through the A / D conversion module and input into the control unit.

[0175] Detected Enter the formula and calculate and dynamic changes.

[0176] It is the reference operating temperature of the sensor, obtained through experimental calibration.

[0177] Frequency drift correction:

[0178] By detection Calculating frequency drift and correction value , dynamically adjust the output of the signal processing algorithm .

[0179] Specific steps:

[0180] First, based on the real-time temperature Calculate the elastic modulus and size changes , substituting it into the frequency drift formula The actual resonant frequency is obtained .

[0181] According to real-time , determine the compensation factor For example, the system can dynamically adjust the temperature according to the rate of change of temperature. , so that it can adapt to drastic temperature fluctuations.

[0182] Finally, the compensated frequency value is output , and applied to pressure signal calculation.

[0183] Dynamic compensation advantages:

[0184] Compared with the traditional linear temperature compensation model, this model uses nonlinear terms and Improved compensation accuracy.

[0185] Dynamic Adjustment The design enhances the system's ability to adapt to different temperature fluctuation environments, such as extreme low or high temperature scenarios.

[0186] By correcting the formula in real time, the model is able to adapt to the aging effects of the resonant cavity after long-term use.

[0187] Compared with the traditional linear correction model, this formula introduces and The dynamic adjustment mechanism makes the compensation capability more flexible and can be automatically optimized according to the environmental fluctuation characteristics without manual intervention.

[0188] The resonance spectrum mode analysis model, when used, comprises:

[0189] Acoustic wave collection at resonant frequency

[0190] The resonant pressure sensor generates a specific sound wave frequency during operation, and collects real-time sound wave signals by embedding a microphone or sound wave detection element. These signals are fed into the signal processing unit for spectrum analysis.

[0191] Get Base value: Under normal system operation, the base resonant frequency is determined by multiple sampling. , and the normal spectrum distribution .

[0192] Real-time sampling: When the fluid system is running, the actual acoustic spectrum is collected and the instantaneous resonant frequency is calculated.

[0193] Frequency offset analysis

[0194] By detecting the instantaneous sound wave frequency The offset , the pressure can be inferred and fluid density These changes usually reflect abnormal conditions of the system, such as pipe blockage, leakage or vibration disturbance.

[0195] Coupling pressure changes with acoustic frequency shifts allows the sensor to both measure pressure and diagnose anomalies through acoustic properties.

[0196] Abnormal Factor Calculation

[0197] The sound spectrum Convert to power spectrum density and calculate the anomaly factor by integral formula .if When a preset threshold (usually determined experimentally) is exceeded, the system will sound an alarm.

[0198] Fault type determination

[0199] According to the frequency shift of the sound wave and abnormal factors Characteristic values ​​of the faults are used to determine different types of faults:

[0200] Blockage: The frequency shift is concentrated in the low frequency area, while the power spectral density Significant decrease.

[0201] Leakage: Sharp spectrum peaks appear in the high frequency region, and Rising sharply.

[0202] Mechanical vibration interference: periodic high-frequency noise appears in the spectrum, and the offset is unstable.

[0203] This model directly uses acoustic characteristics for diagnosis by associating pressure anomalies with acoustic wave frequency shifts, avoiding the limitations of relying solely on pressure signals.

[0204] Embodiment three:

[0205] This embodiment also provides a computer device, which is suitable for the application method of a resonant pressure sensor, 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 the application method of a resonant pressure sensor proposed in the above embodiment.

[0206] This embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, an application method of a resonant pressure sensor as proposed in the above embodiment is implemented.

[0207] 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.

[0208] 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.

[0209] 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.

[0210] 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.

[0211] 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.

[0212] 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. An application method of a resonant pressure sensor, characterized in that: The following steps are involved: S1, sensor site selection and environment modeling; S2. Adjust the resonant cavity based on environmental modeling; S3. Install the pressure buffer device after adjustment; S4. After installing the pressure buffer device, configure the embedded temperature compensation module; The embedded temperature compensation module has a built-in dynamic nonlinear correction model. The model sets the sensor resonant frequency for the resonant pressure sensor. The drift is affected by the ambient temperature The temperature has nonlinear characteristics on the elastic modulus, size change and frequency response of the resonant cavity. The dynamic nonlinear correction model includes the relationship between temperature and resonant frequency, the nonlinear relationship between elastic modulus and temperature, the relationship between dimensional change and temperature, and the dynamic temperature compensation correction formula; S5. Design multi-frequency resonance mode switching; S6. Design a resonant frequency amplification circuit; S7, based on the selected multi-frequency resonance mode and the resonance frequency amplification circuit, diagnose abnormal pressure fluctuations in real time; Real-time diagnosis is performed based on a resonance spectrum mode analytical model in which the frequency response of the sensor resonant sound wave is set to be affected by the instantaneous pressure of the fluid. , fluid density , Pipeline geometry and fluid velocity The impact of The resonance spectrum mode analysis model includes the relationship between the acoustic resonance frequency and pressure, the spectrum shift of abnormal pressure fluctuations, and the real-time acoustic mode diagnosis model; S8. Perform distributed deployment of sensor arrays.

2. The application method of a resonant pressure sensor according to claim 1, characterized in that: In the step S1, before installing the sensor, the target environment is analyzed, including pressure distribution, temperature gradient, and fluid properties; The modeling tool is used to create a three-dimensional pressure distribution simulation diagram of the target area to predict the pressure variation patterns and noise interference points at different locations.

3. The application method of a resonant pressure sensor according to claim 1, characterized in that: In step S2, the size and material of the resonant cavity are adjusted according to different environmental pressure ranges so that the resonant frequency is most sensitive to the expected pressure range; The resonant frequency can be changed by adjusting the length, width and thickness of the cavity.

4. The application method of a resonant pressure sensor according to claim 1, characterized in that: In the dynamic nonlinear correction model: The relationship between temperature and resonant frequency is shown below: ； in, : Nominal resonant frequency, i.e. initial frequency; : frequency response; : proportionality factor related to material properties and sensor structure; : Elastic modulus as a function of temperature; : The expansion / contraction function of the cavity geometry with temperature; The nonlinear relationship between elastic modulus and temperature is shown below: ； in, : elastic modulus of the material at reference temperature; : nonlinear coefficient related to the thermophysical properties of the material; The relationship between dimensional change and temperature is shown below: ； in, : Cavity reference length; : Linear expansion coefficient of the material; : Changes in the geometric dimensions of the resonant cavity; : Change of temperature; The dynamic temperature compensation correction formula is as follows: ； in, : The resonant frequency after correction; : Temperature compensation coefficient, dynamically adjusted to adapt to the real-time ambient temperature; : Reference temperature, that is, calibration value.

5. The application method of a resonant pressure sensor according to claim 1, characterized in that: In step S5, the multi-frequency resonance mode is based on adapting to different pressure measurement requirements, including static pressure monitoring and dynamic pressure fluctuation analysis; Static pressure monitoring, the sensor preferentially captures low-frequency stable pressure signals; Dynamic pressure fluctuation analysis, enhancing the high frequency response of the sensor to monitor rapidly fluctuating pressures.

6. The application method of a resonant pressure sensor according to claim 1, characterized in that: In step S6, the resonant frequency amplification circuit is used to amplify the frequency offset signal, thereby improving the measurement accuracy; The resonant frequency amplification circuit includes a high-sensitivity frequency filter and a low-noise amplifier to ensure effective extraction of weak signals.

7. The application method of a resonant pressure sensor according to claim 1, characterized in that: In the resonance spectrum mode analytical model: The relationship between the resonant frequency of sound waves and pressure is shown below: ； in, : resonant sound wave frequency; : acoustic resonance mode, which is an integer order; : The effective length of the pipe length or the resonant cavity inside the sensor; : The adiabatic index of the fluid, which is 1.4 in air; : Instantaneous pressure of the fluid; : fluid density; The spectrum shifts due to abnormal pressure fluctuations. When the pressure fluctuates abnormally, the sound wave frequency shifts. , the frequency offset is as follows: ； in, and : Base pressure and density; and : Abnormal changes in pressure and density; Real-time acoustic wave pattern diagnosis model, introducing the power spectrum density of acoustic waves , and define the outlier factor , the model is as follows: ； in, : The threshold range of frequency deviation is used to limit the diagnostic sensitivity; : Spectral weight function, adjusted according to the anomaly type, giving higher weight to high-frequency anomalies; : Power spectral density of the acoustic signal, obtained by fast Fourier transform.

8. The application method of a resonant pressure sensor according to claim 1, characterized in that: In the step S8, the sensors are deployed in a distributed manner to form a pressure monitoring network; Each sensor operates independently and is connected to the central control unit via a wireless or wired communication module to achieve centralized analysis of data.

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