Method and system for quantitatively monitoring leakage of high-pressure sealed cavity structure

Abstract

The present application belongs to the technical field of sealed structure health monitoring, and discloses a high-pressure sealed cavity structure leakage quantity quantitative monitoring method and system. The present application establishes a direct mathematical model between the dynamic characteristic parameter with "stress relaxation slope" as the core and the leakage quantity, realizes the accurate numerical output of the leakage quantity in the non-invasive monitoring field. The method solves the industry pain point that the traditional non-invasive technology can only alarm but cannot quantify, enables the engineering personnel to accurately master the severity of the leakage, and accordingly carries out scientific leakage grade division, and provides direct and reliable decision basis for taking differentiated disposal strategies.

Description

Technical Field

[0001] This invention relates to the field of health monitoring technology for sealed structures, specifically to a method and system for quantitative monitoring of leakage in high-pressure sealed cavity structures. Background Technology

[0002] High-pressure sealed cavity structures, such as aerospace wind tunnel chambers, deep-sea exploration chambers, and chemical reaction vessels, are key core equipment in modern industry and high-end equipment. The integrity of their sealing performance directly affects the safe operation of the entire system and the protection of personnel lives. Therefore, effective and reliable leak monitoring of these structures is crucial.

[0003] Currently, existing high-pressure sealed cavity leakage monitoring technologies are mainly divided into the following categories, but they all have significant technical bottlenecks: (1) Invasive monitoring methods have structural safety risks: The current mainstream technology relies on installing pressure sensors or flow sensors by opening holes in the cavity wall. This method inevitably destroys the integrity of the original structure, forming a stress concentration area at the opening, which significantly increases the risk of fatigue failure of the structure under high pressure. More paradoxically, the sensor interface itself may become a new leakage point under extreme working conditions, forming a dilemma of introducing hidden dangers for monitoring. In addition, sensors that directly contact the medium are susceptible to corrosion, blockage and high-temperature aging, resulting in high maintenance costs and low reliability throughout the entire life cycle. (2) Non-invasive monitoring methods cannot achieve quantitative assessment: To solve the structural damage problem of invasive monitoring, technologies such as ultrasonic detection and infrared thermal imaging are applied. However, these technologies are limited by their principles and can usually only make a qualitative judgment on whether there is a leak or roughly locate the leak area, and cannot output specific leakage values. This makes it difficult for engineers to distinguish the risk levels of "micro-leakage", "medium-sized leakage" and "large leakage", thus making it impossible to formulate targeted maintenance or emergency response strategies and meet the high standards of safety management. (3) Existing stress monitoring resources are not effectively used for sealing performance assessment: Many high-pressure sealing cavities have deployed structural health monitoring systems (such as distributed strain sensors) to monitor the overall stress and deformation state of the cavity. However, these systems currently only serve structural strength assessment, and there is a lack of effective correlation models between the massive amount of stress data and "sealing performance".

[0004] In view of this, the present invention is proposed. Summary of the Invention

[0005] The present invention aims to solve at least one of the above technical problems, and provides a method and system for quantitative monitoring of leakage in high-pressure sealed cavity structures.

[0006] To achieve the above objectives, the first technical solution adopted by the present invention is as follows:

[0007] A quantitative monitoring method for leakage in high-pressure sealed cavity structures includes:

[0008] Real-time acquisition of the original stress signal on the surface of the high-pressure sealing cavity;

[0009] Based on the original stress signal, the stress relaxation slope is calculated, and at least one set of feature parameters related to the dynamic change of the stress relaxation slope are extracted.

[0010] Using at least one set of the aforementioned characteristic parameters as direct input variables, the quantitative leakage of the sealed cavity is calculated through a preset leakage calculation model.

[0011] Preferably, the characteristic parameters related to the dynamic change of the stress relaxation slope include: the absolute value of the stress relaxation slope, the duration of stress relaxation, and the length of the stress anomaly region.

[0012] Preferably, the leakage calculation model is as follows: Where Q is the leakage flow rate, K is the comprehensive correction factor, S is the absolute value of the stress relaxation slope, and T is the total leakage flow rate. relax ρ is the stress relaxation duration, L is the length of the stress anomaly region, ΔP is the pressure difference between the inside and outside of the high-pressure sealing cavity, and ρ is the density of the sealing medium.

[0013] Preferably, before extracting the feature parameters, the method further includes: performing wavelet packet threshold filtering on the original stress signal to obtain a denoised stress signal; and calculating the stress relaxation slope based on the denoised stress signal.

[0014] Preferably, the specific formula for wavelet packet threshold filtering is as follows: ,in, Here, j represents the denoised stress signal, j is the wavelet packet decomposition level, and k is the frequency band index of the j-th level. Let be the wavelet packet coefficients of the j-th layer and k-th frequency band. Here, I(⋅) is the db4 wavelet basis function, and I(⋅) is the indicator function. This is an adaptive threshold.

[0015] Preferably, in the step of calculating the stress relaxation slope, when multiple consecutive sampling points of the stress relaxation slope are detected to be below a preset negative threshold, leakage is determined to have occurred, and the extraction of the feature parameters is triggered.

[0016] Preferably, strain sensors are deployed on the surface of the sealed cavity to collect the original stress signal on the surface of the high-pressure sealed cavity in real time.

[0017] Preferably, the strain sensor is a distributed strain sensor.

[0018] The second technical solution adopted in this invention is:

[0019] A quantitative monitoring system for leakage in high-pressure sealed cavity structures includes:

[0020] The signal acquisition module is used to acquire the original stress signal on the surface of the high-pressure sealed cavity in real time;

[0021] The calculation and extraction module is used to calculate the stress relaxation slope based on the original stress signal and extract at least one set of feature parameters related to the dynamic change of the stress relaxation slope.

[0022] The calculation module is used to take at least one set of the characteristic parameters as direct input variables and calculate the quantitative leakage of the sealed cavity through a preset leakage calculation model.

[0023] Preferably, before calculating the stress relaxation slope, the calculation and extraction module is also used to perform wavelet packet threshold filtering on the original stress signal.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] This invention establishes a direct mathematical model between dynamic characteristic parameters centered on the "stress relaxation slope" and leakage volume, enabling precise numerical output of leakage volume in the field of non-invasive monitoring. This method addresses the industry pain point of traditional non-invasive technologies, which can only issue alarms but not provide quantitative data. It allows engineers to accurately determine the severity of leaks and scientifically classify them into different levels, providing a direct and reliable basis for differentiated handling strategies.

[0026] This invention, by calculating the stress relaxation slope in real time and setting trigger conditions, can instantly capture the dynamic release process of the stress field in the early stages of a leak. Its response speed is far faster than traditional methods relying on pressure balancing or manual inspection, meeting the safety requirements of "early detection and early response" for high-pressure equipment. Simultaneously, through advanced signal processing techniques such as wavelet packet threshold filtering, it can effectively suppress environmental interference such as mechanical vibration, ensuring the stability and accuracy of monitoring results under complex operating conditions and overcoming the limitations of infrared and ultrasonic technologies that are susceptible to environmental influences.

[0027] This invention completely abandons the traditional method of installing sensors by opening holes in the cavity. By reusing the existing distributed strain sensors on the cavity surface for monitoring, the integrity of the cavity structure is fully maintained, fundamentally eliminating the possibility of leakage risks and structural weak points introduced by the monitoring itself. Attached Figure Description

[0028] Figure 1 A flowchart illustrating the method for quantitative monitoring of leakage in a high-pressure sealed cavity structure provided in this embodiment of the invention;

[0029] Figure 2A schematic diagram of the structure of the high-pressure sealed cavity structure leakage quantitative monitoring system provided in the embodiments of the present invention;

[0030] Figure 3 This is a schematic block diagram of an example electronic device 300 according to an embodiment of the present invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] refer to Figure 1 The first embodiment of the present invention provides a method for quantitative monitoring of leakage in a high-pressure sealed cavity structure, comprising:

[0033] S101, real-time acquisition of the original stress signal on the surface of the high-pressure sealing cavity.

[0034] The purpose of this step is to obtain the most basic mechanical state information of the sealed cavity structure under high-pressure conditions, providing a data foundation for all subsequent analyses. Its core is to capture the dynamic signals of minute, rapid changes in local stress within the cavity caused by internal fluid leakage.

[0035] The original stress signal on the surface of the high-pressure sealed cavity can be acquired in real time by strain sensors deployed on the surface of the cavity. Here, "strain sensor" refers to a device capable of converting the mechanical strain of a structural surface into a measurable electrical or optical signal. In this invention, a distributed strain sensor is preferred. Its "distributed" characteristic means that, unlike traditional point sensors, it has the ability to spatially locate the leakage source.

[0036] "Sealed cavity surface" refers to the outer wall surface of a structure that bears internal pressure. Monitoring stress changes at this location is a non-invasive method.

[0037] The selection, deployment, and signal acquisition of specific sensor models are all common practices in this field. The existing distributed network within the high-pressure sealed cavity, serving the "structural health monitoring" system, can be utilized to monitor sealing performance without adding any new hardware or altering the structure.

[0038] S102, based on the original stress signal, calculate the stress relaxation slope and extract at least one set of feature parameters related to the dynamic change of the stress relaxation slope.

[0039] This step is the core of this invention's transition from "static monitoring" to "dynamic diagnosis." Its purpose is to extract dynamic characteristic fingerprints from the noisy raw signal that can directly and sensitively characterize the occurrence of a leak—namely, characteristic parameters related to the stress relaxation slope—providing input for the final quantitative calculation.

[0040] The "stress relaxation slope" refers to the rate of stress change per unit time. When a leak occurs, the escape of high-pressure fluid causes local structural unloading, and the stress drops rapidly, exhibiting a negative slope. Its absolute value directly reflects the severity of the leak.

[0041] "Characteristic parameters" refer to physical quantities extracted from the change in stress relaxation slope that can quantify the leakage process. Key parameters defined in this invention include: absolute value of stress relaxation slope (S): reflecting the instantaneous intensity of stress release (i.e., leakage) caused by the leak; and stress relaxation duration (T). relax ): The time interval from when the leak is detected to the end of the stress relaxation process (e.g., the slope returns to a stable value close to zero), reflecting the continuous effect of the leak process. Stress anomaly region length (L): Determined by the spatial positioning capability of distributed sensors, the spatial length of the sensor segment where significant stress relaxation occurs, characterizing the influence range of the leak source.

[0042] Due to the intense mechanical vibrations and other noise present in high-pressure industrial environments, the signal-to-noise ratio can be as low as 15 dB. Directly differentiating the original signal amplifies the noise, making it impossible to effectively extract the true feature parameters. Therefore, it is best to first perform wavelet packet thresholding filtering on the original stress signal to obtain a denoised stress signal. In some preferred embodiments, wavelet packet thresholding filtering, an advanced signal processing technique, is employed.

[0043] Specifically, the original signal is decomposed into five levels, using the db4 wavelet basis function, and an adaptive threshold is applied to the wavelet packet coefficients of each frequency band. Coefficients with absolute values ​​greater than the threshold are retained, while noise components with values ​​less than the threshold are removed.

[0044] The specific formula for wavelet packet threshold filtering is:

[0045] ,in, Here, j represents the denoised stress signal, j is the wavelet packet decomposition level, and k is the frequency band index of the j-th level. Let be the wavelet packet coefficients of the j-th layer and k-th frequency band. Let I(⋅) be the db4 wavelet basis function, and let I(⋅) be the indicator function (when...). (Take 1 if it is true, otherwise take 0). This is an adaptive threshold.

[0046] In some preferred embodiments, the stress relaxation slope is calculated based on the denoised stress signal, and a reliable criterion is set to automatically identify the occurrence of leakage. Specific details are as follows.

[0047] Instantaneous slope is calculated using the finite difference method: This is a common method for numerically calculating derivatives. Among them, The stress relaxation slope (MPa / s, a negative value indicates a decrease in stress, and the larger the absolute value, the more severe the leakage). Refers to adjacent sampling times ( (corresponding to a sampling frequency of 1kHz). For t i The denoised stress value (MPa) at time 1.

[0048] Leakage Triggering Mechanism: A dynamic triggering condition is defined. When the stress relaxation slope is detected to be below a preset negative threshold for multiple consecutive sampling points, a leak is determined to have occurred, and the extraction of the characteristic parameters is triggered. The specific sampling point format and threshold can be adaptively adjusted by those skilled in the art. As an example, when the stress relaxation slope of 5 consecutive sampling points meets the threshold... The system only determines that a leak has occurred when the time is right. This mechanism of "multiple consecutive points + negative threshold" greatly reduces the probability of false alarms and ensures the reliability of monitoring.

[0049] After leakage is triggered, at least one set of characteristic parameters (S, T) are automatically defined from the stress relaxation slope sequence calculated above. relax These parameters are derived directly from the dynamic changes in stress, without the need for any conversion of intermediate physical quantities.

[0050] S103, using at least one set of the characteristic parameters as direct input variables, the quantitative leakage of the sealed cavity is calculated through a preset leakage calculation model.

[0051] This step is the final manifestation of the technical effect of the present invention. Its purpose is to transform the dynamic characteristic parameters extracted in S102 into specific leakage values ​​(such as L / h) that can be directly used in engineering, so as to realize a direct and quantitative mapping from "physical characteristics" to "engineering parameters".

[0052] The "direct input variable" approach emphasizes skipping all intermediate physical parameters that are difficult to measure directly online, such as "leakage area," "crack width," and "contact stress," and establishing an end-to-end mathematical model from stress relaxation characteristics to leakage amount.

[0053] "Preset leakage calculation model" refers to a formula stored in the system beforehand that describes the mathematical relationship between characteristic parameters and leakage.

[0054] For the embodiments of the present invention, the leakage calculation model is as follows:

[0055] Where Q is the leakage flow rate, K is the comprehensive correction factor, S is the absolute value of the stress relaxation slope, and T is the total leakage flow rate. relax ρ is the stress relaxation duration, L is the length of the stress anomaly region, ΔP is the pressure difference between the inside and outside of the high-pressure sealing cavity, and ρ is the density of the sealing medium.

[0056] The theoretical basis of the leakage calculation model is as follows:

[0057] Relationship between stress relaxation and leakage energy: stress release energy caused by leakage (Energy is proportional to the absolute value of the slope and the duration), where Represents proportionality;

[0058] Fluid leakage flow rate formula: Orifice leakage flow rate (A is the leakage area, C) d (where f is the flow coefficient, set empirically), and A∝L⋅f (f is the equivalent leakage width);

[0059] Experimental calibration: Through experiments using a standard leak hole (known diameter), it was found that f∝S⋅T relax Therefore, the leakage calculation model is obtained by merging the constant terms.

[0060] This model is not a purely empirical formula; its theoretical basis lies in integrating solid mechanics (energy released during stress relaxation) and fluid mechanics (orifice leakage flow rate), and experimental verification shows that the equivalent size of the leakage channel is... Proportional.

[0061] Through the detailed implementation of the above three steps, the embodiments of the present invention fully realize non-invasive, high-precision, quantitative real-time monitoring of leakage in high-pressure sealed cavity structures. Those skilled in the art can implement the present invention and obtain its beneficial effects based on the above description, combined with specific industrial scenarios and equipment parameters.

[0062] refer to Figure 2 The second embodiment of the present invention provides a quantitative monitoring system 200 for leakage of high pressure sealed cavity structure, which includes a signal acquisition module 201, a calculation and extraction module 202, and a calculation module 203. The specific functions of each module are described below.

[0063] The signal acquisition module 201 is used to acquire the original stress signal on the surface of the high-pressure sealing cavity in real time.

[0064] The calculation and extraction module 202 is used to calculate the stress relaxation slope based on the original stress signal and extract at least one set of feature parameters related to the dynamic change of the stress relaxation slope.

[0065] The calculation module 203 is used to take at least one set of the characteristic parameters as direct input variables and calculate the quantitative leakage of the sealed cavity through a preset leakage calculation model.

[0066] In some preferred embodiments, the calculation and extraction module is further used to perform wavelet packet threshold filtering on the original stress signal before calculating the stress relaxation slope.

[0067] Based on the above embodiments, the present invention also provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps in the method for quantitative monitoring of leakage of high-pressure sealed cavity structure in the first embodiment.

[0068] Figure 3 A schematic block diagram of an example electronic device 300 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0069] like Figure 3 As shown, the electronic device 300 may include a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 302 or a computer program loaded from a storage unit 308 into a random access memory (RAM) 303. The RAM 303 may also store various programs and data required for the operation of the electronic device 300. The computing unit 301, the ROM 302, and the RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0070] Multiple components in electronic device 300 are connected to input / output (I / O) interface 305, including: input unit 306, such as keyboard, mouse, etc.; output unit 307, such as various types of monitors, speakers, etc.; storage unit 308, such as disk, optical disk, etc.; and communication unit 309, such as network card, modem, wireless transceiver, etc. Communication unit 309 allows electronic device 300 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0071] The computing unit 301 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 301 performs the various methods and processes described above, such as the method for quantitative monitoring of leakage in a high-pressure sealed cavity structure. For example, in some embodiments, the method for quantitative monitoring of leakage in a high-pressure sealed cavity structure can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 300 via read-only memory (ROM) 302 and / or communication unit 309. When the computer program is loaded into random access memory (RAM) 303 and executed by the computing unit 301, one or more steps of the method for quantitative monitoring of leakage in a high-pressure sealed cavity structure described above can be performed. Alternatively, in other embodiments, the computing unit 301 may be configured by any other suitable means (e.g., by means of firmware) to perform a method for quantitatively monitoring leakage in a high-pressure sealed cavity structure.

Claims

1. A method for quantitatively monitoring leakage in a high-pressure sealed cavity structure, characterized in that, include: Real-time acquisition of the original stress signal on the surface of the high-pressure sealing cavity; Based on the original stress signal, the stress relaxation slope is calculated, and at least one set of feature parameters related to the dynamic change of the stress relaxation slope are extracted, including: the absolute value of the stress relaxation slope, the stress relaxation duration, and the length of the stress anomaly region. Using at least one set of the aforementioned characteristic parameters as direct input variables, the quantitative leakage of the sealed cavity is calculated through a preset leakage calculation model. The leakage calculation model is as follows: Where Q is the leakage flow rate, K is the comprehensive correction factor, S is the absolute value of the stress relaxation slope, and T is the total leakage flow rate. relax ρ is the stress relaxation duration, L is the length of the stress anomaly region, ΔP is the pressure difference between the inside and outside of the high-pressure sealing cavity, and ρ is the density of the sealing medium.

2. The method for quantitative monitoring of leakage in a high-pressure sealed cavity structure as described in claim 1, characterized in that, Before extracting the feature parameters, the method further includes: performing wavelet packet threshold filtering on the original stress signal to obtain a denoised stress signal; and calculating the stress relaxation slope based on the denoised stress signal.

3. The method for quantitative monitoring of leakage in a high-pressure sealed cavity structure as described in claim 2, characterized in that, The specific formula for wavelet packet threshold filtering is: ,in, Here, j represents the denoised stress signal, j is the wavelet packet decomposition level, and k is the frequency band index of the j-th level. Let be the wavelet packet coefficients of the j-th layer and k-th frequency band. Here, I(⋅) is the db4 wavelet basis function, and I(⋅) is the indicator function. This is an adaptive threshold.

4. The method for quantitative monitoring of leakage in a high-pressure sealed cavity structure as described in claim 1, characterized in that, In the step of calculating the stress relaxation slope, when multiple consecutive sampling points of the stress relaxation slope are detected to be below a preset negative threshold, leakage is determined to have occurred, and the extraction of the feature parameters is triggered.

5. The method for quantitative monitoring of leakage in a high-pressure sealed cavity structure as described in claim 1, characterized in that, The original stress signal on the surface of the high-pressure sealed cavity is collected in real time by strain sensors deployed on the surface of the sealed cavity.

6. The method for quantitative monitoring of leakage in a high-pressure sealed cavity structure as described in claim 5, characterized in that, The strain sensor is a distributed strain sensor.

7. A quantitative monitoring system for leakage in a high-pressure sealed cavity structure, characterized in that, Include: The signal acquisition module is used to acquire the original stress signal on the surface of the high-pressure sealed cavity in real time; The calculation and extraction module is used to calculate the stress relaxation slope based on the original stress signal and extract at least one set of feature parameters related to the dynamic change of the stress relaxation slope, including: the absolute value of the stress relaxation slope, the stress relaxation duration, and the length of the stress anomaly region. The calculation module is used to take at least one set of the aforementioned characteristic parameters as direct input variables and calculate the quantitative leakage of the sealed cavity using a preset leakage calculation model; the leakage calculation model is as follows: Where Q is the leakage flow rate, K is the comprehensive correction factor, S is the absolute value of the stress relaxation slope, and T is the total leakage flow rate. relax ρ is the stress relaxation duration, L is the length of the stress anomaly region, ΔP is the pressure difference between the inside and outside of the high-pressure sealing cavity, and ρ is the density of the sealing medium.

8. The quantitative monitoring system for leakage of a high-pressure sealed cavity structure as described in claim 7, characterized in that, Before calculating the stress relaxation slope, the calculation and extraction module is also used to perform wavelet packet threshold filtering on the original stress signal.

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