Pressure decay test method and system based on gas elastic compensation

Abstract

The application discloses a pressure decay test method and system based on gas elastic compensation, and relates to the field of sealing pressure test. The method comprises the following steps: connecting a to-be-tested sealed container to a test cavity provided with a gas elastic compensation module, applying a preset pressure test signal first, collecting pressure response and volume change data to identify elastic characteristic parameters of the container; then inflating the test cavity and the container to a target test pressure and entering constant pressure detection, adjusting the compensation amount in real time through pressure feedback control to maintain constant pressure and record the total compensation flow; calculating the theoretical elastic compensation flow based on the elastic characteristic parameters and the real-time pressure, and deducting the total compensation flow to obtain the net compensation flow, thereby determining the leakage rate and comparing it with the integrity standard to realize sealing judgment. Thus, the decoupling of leakage and elastic deformation effect can be realized under the condition of complex elastic structure and small head space, and the detection accuracy and consistency are improved.

Description

Technical Field

[0001] This application relates to the field of sealing pressure testing technology, and in particular to a pressure decay testing method and system based on gas elastic compensation. Background Technology

[0002] In the pharmaceutical and aseptic medical fields, rapid transfer ports (RTPs) are critical components for the safe exchange of materials between isolators and the external environment. To ensure the integrity of sterile barriers, regulatory requirements (such as GMP and FDA guidelines) mandate periodic integrity testing of these container closure systems (CCS). Currently, the industry commonly uses the non-destructive pressure decay method. Its basic principle involves inflating the container under test to a predetermined pressure, cutting off the gas supply, and monitoring the pressure drop over time to determine if a leak exists. This method is widely used due to its simplicity and high degree of automation.

[0003] However, the traditional pressure decay method has significant technical drawbacks when applied to complex structures such as RTP interfaces. RTP interfaces typically consist of components such as sealing rings, flanges, and interlocking rings, most of which are made of high-molecular-weight elastic materials. During pressurization testing, these materials undergo creep or elastic expansion, leading to an increase in the internal volume of the container. According to the ideal gas law, this increase in volume directly results in a pressure drop. This "false pressure drop" caused by deformation can be confused with the actual leakage pressure drop. Conversely, the elastic recoil of the container during the pressure holding phase can compensate for some of the pressure drop caused by leakage, thus masking minor leaks (i.e., the "elastic compensation effect").

[0004] Furthermore, the RTP interface is often filled with liquid or powder, resulting in very limited remaining compressible gas space (head space), which causes the pressure signal to decay extremely quickly and become unstable. At the same time, even small temperature fluctuations in the testing environment can cause changes in gas pressure, which, in the absence of an effective compensation mechanism, can easily lead to misjudgments (false negatives or false positives). Summary of the Invention

[0005] This application provides a pressure decay test method, system, storage medium, computer program product, and electronic device based on gas elastic compensation, which at least solves the problem in the prior art that leakage signals are difficult to effectively distinguish from non-leakage signals caused by material deformation and environmental disturbances in the integrity test of complex elastic sealing structures, resulting in insufficient reliability of test results.

[0006] In a first aspect, embodiments of this application provide a pressure attenuation testing method based on gas elastic compensation. The method includes: connecting a sealed container to be tested to a test chamber equipped with a gas elastic compensation module; applying a preset pressure test signal to the sealed container to be tested; acquiring pressure response data and volume change data in response to the pressure test signal to calculate and obtain the elastic characteristic parameters of the sealed container to be tested; injecting gas into the test chamber and the sealed container to be tested until the pressure inside the chamber reaches a preset target test pressure, and entering a constant pressure detection stage; in the constant pressure detection stage, using the gas elastic compensation module to perform pressure feedback control, adjusting the pressure in real time... The system adjusts the compensation amount to maintain the pressure within the test chamber at the target test pressure and records the total compensation flow rate data required to maintain the target test pressure in real time. Based on the elastic characteristic parameters and the real-time monitored pressure data, it calculates the theoretical elastic compensation flow rate caused by the elastic deformation of the sealed container under test under the current pressure environment. The theoretical elastic compensation flow rate is subtracted from the total compensation flow rate data in real time to obtain the net make-up gas flow rate reflecting the actual leakage situation of the sealed container under test. The leakage rate is determined according to the change characteristics of the net make-up gas flow rate over time, and the leakage rate is compared with a preset integrity standard to determine the sealing integrity of the sealed container under test.

[0007] Secondly, embodiments of this application provide a pressure decay testing system based on gas elastic compensation. The system includes: a pre-test calibration unit, used to connect a sealed container to be tested to a test chamber equipped with a gas elastic compensation module, and to obtain pressure response data and volume change data in response to the pressure test signal by applying a preset pressure test signal to the sealed container to be tested, so as to calculate and obtain the elastic characteristic parameters of the sealed container to be tested; a pressure construction and initialization unit, used to inject gas into the test chamber and the sealed container to be tested until the pressure inside the chamber reaches a preset target test pressure, and then enter a constant pressure detection stage; and a constant pressure feedback compensation unit, used to perform pressure feedback control using the gas elastic compensation module during the constant pressure detection stage, and to adjust the pressure in real time. The test chamber is equipped with a compensation unit to maintain the pressure within the test chamber at the target test pressure and to record the total compensation flow rate required to maintain the target test pressure in real time. An elastic model calculation unit is used to calculate the theoretical elastic compensation flow rate caused by the elastic deformation of the sealed container under the current pressure environment based on the elastic characteristic parameters and the real-time monitored pressure data. A net flow rate analysis unit is used to subtract the theoretical elastic compensation flow rate from the total compensation flow rate data in real time to obtain the net make-up gas flow rate reflecting the actual leakage situation of the sealed container under test. An integrity assessment and determination unit is used to determine the leakage rate based on the change characteristics of the net make-up gas flow rate over time and compare the leakage rate with a preset integrity standard to determine the sealing integrity of the sealed container under test.

[0008] Thirdly, an electronic device is provided, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the steps of the pressure decay test method based on gas elasticity compensation according to any embodiment of the present application.

[0009] Fourthly, embodiments of this application provide a storage medium storing a computer program thereon, characterized in that, when the program is executed by a processor, it implements the steps of the pressure decay test method based on gas elastic compensation according to any embodiment of this application.

[0010] Fifthly, embodiments of this application provide a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the pressure decay test method based on gas elasticity compensation according to any embodiment of this application.

[0011] The pressure attenuation testing method and system based on gas elastic compensation provided in this application can achieve at least the following technical effects: (1) By simultaneously acquiring and modeling the pressure response and volume change of the sealed container under test before testing, elastic characteristic parameters that can characterize its elastic deformation law are obtained. This allows the gas state changes caused by material elastic expansion, creep and shrinkage in the subsequent testing stage to be quantified and transformed into a calculable "elastic contribution". As a result, the testing system no longer relies on the apparent change of a single pressure signal to indirectly infer the state, but establishes a parameterized benchmark that matches the elastic behavior of the structure, fundamentally improving the identifiability and predictability of the influence of structural deformation during the testing process.

[0012] (2) Pressure feedback control of the gas elastic compensation module is introduced in the constant pressure detection stage, transforming the detection observation from "pressure attenuation" to "compensation flow rate required to maintain the target pressure". Based on this, the theoretical elastic compensation flow rate is calculated in real time in combination with the above-mentioned elastic characteristic parameters, and the net replenishment gas flow rate is dynamically extracted from the total compensation flow rate. This net replenishment gas flow rate has a direct correspondence with the actual gas loss, and can maintain a stable quantitative output even under conditions where the head space is limited and the signal changes rapidly and is prone to fluctuation; thus, the quantitative accuracy and robustness of the judgment of minor leaks are significantly improved.

[0013] This technical solution uses "pressure-compensated flow rate" as a subjective measurement and introduces a subtraction mechanism driven by elastic characteristic parameters to effectively decouple the elastic deformation effect from the actual leakage effect. This transforms integrity assessment from an assessment of apparent pressure changes susceptible to the coupling of structural and operating conditions to an evaluation of the net air supply volume after elastic correction, significantly improving the reliability, batch consistency, and engineering applicability of testing in complex sealing interface scenarios. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 A flowchart is shown as an example of a pressure decay test method based on gas elastic compensation according to an embodiment of this application; Figure 2 A schematic diagram illustrating an example of a testing system in a method according to an embodiment of this application is shown. Figure 3 A schematic diagram illustrating the principle mechanism of an example pressure decay test method based on gas elastic compensation according to an embodiment of this application is shown. Figure 4 A schematic diagram showing the comparison of test data for different methods in a simulation experimental environment is presented; Figure 5 A schematic diagram comparing the relative measurement error distributions of different methods under three typical elastic conditions based on Monte Carlo simulation is shown. Figure 6 A structural block diagram of an example pressure decay testing system based on gas elastic compensation according to an embodiment of this application is shown. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0017] It should be noted that although the pressure decay method is widely adopted due to its non-destructive and automated advantages, the technology still faces profound physical challenges and application limitations when detecting minute leaks in RTP interfaces and similar complex polymer components.

[0018] Firstly, regarding the accuracy interference mechanism of the pressure decay method itself, the rheological properties and thermodynamic effects of the material are the core factors leading to misjudgments. Related research indicates that when the test object involves polymeric elastic materials such as sealing rings and flanges, the pressurization process not only induces instantaneous elastic deformation but also time-dependent viscoelastic creep. This microscopic volume expansion dynamically changes the total volume within the test chamber. According to the ideal gas law, the nonlinear change in volume will generate pressure fluctuation signals in the same or opposite direction as the leakage pressure drop, thus masking real minute leaks or generating false alarms. Especially when the RTP interface is filled with liquid or powder media, the remaining headspace is extremely small, making the system highly sensitive to temperature fluctuations. Existing technical analysis shows that, in the absence of a dynamic thermal compensation mechanism, the thermal effect generated by compressed gas or slight environmental temperature differences are sufficient to cause significant drift in pressure readings, leading to deviations from the true value in the detection results.

[0019] Secondly, in order to overcome the aforementioned limitations of the pressure attenuation method, the industry has attempted to introduce various alternative detection technologies. However, these technologies all have unavoidable technical defects when adapting to the special operating conditions of the RTP interface: 1) Vacuum attenuation technology: Although this technology is more sensitive than positive pressure attenuation in some scenarios, in RTP systems involving the transport of powder or liquid formulations, a negative pressure environment can easily cause formulation particles or liquids to be drawn in and block tiny leakage pores, resulting in false negatives. In addition, this method usually has a long detection cycle and relatively high equipment costs, making it difficult to meet the needs of online rapid detection.

[0020] 2) High Voltage Discharge (HVLD): This technology uses high voltage scanning to detect micropores and is relatively sensitive to liquid products. However, RTP interfaces are usually made of composite materials such as metal, glass, and polymers, and the detection sensitivity of HVLD technology decreases significantly at the interface between different materials. Furthermore, if air bubbles are present inside the interface or the liquid does not completely cover the leak point, this technology also has a large detection blind zone.

[0021] 3) Mass flow rate detection technology: Some industrial practices use the mass flow rate method to quantify leakage by monitoring the amount of gas required to maintain a constant pressure. Although this method solves the quantitative problem of large-volume containers to some extent, most current commercial flow detection equipment ignores the "dynamic volume" changes caused by the elastic deformation of the measured object. For highly elastic RTP components, it is still unable to distinguish between "false flow" caused by material creep and the actual leakage flow.

[0022] 4) Tracer gas method (e.g., helium / hydrogen detection): Although mass spectrometry has extremely high sensitivity in detecting tracer gases and can locate leaks, this method is highly dependent on expensive precision instruments, and rare gases such as helium are costly. More importantly, introducing external tracer gases into a sterile isolator environment may increase the risk of damage to the sterile barrier or introduce additional cross-contamination hazards, which does not meet the stringent requirements of the pharmaceutical industry for process simplicity and sterility.

[0023] Therefore, there is currently a lack of a test scheme for the sealing integrity of RTP interface that can effectively decouple elastic deformation interference, adapt to the thermodynamic fluctuations of small head space, and has low cost and high reliability.

[0024] It should be understood that the above description of the relevant technologies is intended only to help the public better understand the inventive spirit and motivation of this application, and is not intended to limit this application. Furthermore, the technical solutions described in the above-mentioned relevant technologies are not prior art, and may also be undisclosed technical solutions, such as those under research or in the laboratory stage.

[0025] The technical solutions in this application, including the collection, storage, use, processing, transmission, provision, and disclosure of users' personal information, comply with relevant laws and regulations and do not violate public order and good morals.

[0026] Figure 1 A flowchart illustrating an example of a pressure decay test method based on gas elastic compensation according to an embodiment of this application is shown.

[0027] Regarding the execution subject of the method in this application embodiment, it can be any controller or processor with computing or processing capabilities, such as an integrity testing platform controller. It acquires detection signals from pressure / flow sensors (and displacement or equivalent volume measurement units for characterizing volume changes) and performs computational processing. Simultaneously, it drives the mass flow controller, proportional valve / solenoid valve, and related actuators in the gas elastic compensation module to achieve constant pressure closed-loop regulation, compensation amount control, data recording, and judgment result output. Thus, it performs seal integrity testing on containers with elastic components (such as rapid transfer ports (RTPs) in the pharmaceutical industry, soft bags, or components with flexible seals).

[0028] In some examples, it may be integrated into an electronic device or terminal through software, hardware, or a combination of both, and the type of terminal or electronic device may be diverse.

[0029] like Figure 1As shown, in step S110, the sealed container to be tested is connected to the test chamber equipped with a gas elasticity compensation module. By applying a preset pressure test signal to the sealed container to be tested, pressure response data and volume change data in response to the pressure test signal are obtained, so as to calculate and obtain the elastic characteristic parameters of the sealed container to be tested.

[0030] Specifically, firstly, the physical environment for testing is constructed. The sealed container under test is airtightly connected to the test chamber of the testing system via a dedicated leak-free fixture conforming to its geometry or a standard pneumatic interface, ensuring that the connection interface itself is leak-free. This creates a connected, closed test volume system between the test chamber and the interior of the sealed container under test. At this point, the gas elastic compensation module in the testing system is in standby mode. This module can employ precision actuators such as high-precision micro-flow proportional valves, piezoelectric valves, or servo motor-driven variable volume bellows.

[0031] Subsequently, the pre-test calibration logic is executed. The control system instructs the gas elastic compensation module to apply a preset pressure test signal to the closed system, such as a short-lived, small pressure step or a pressure disturbance of a specific frequency. Excited by this, the flexible wall or elastic sealing ring of the sealed container under test will produce corresponding transient elastic deformation. The system's built-in high-frequency pressure sensor and flow / displacement sensor synchronously acquire pressure response data (i.e., dynamic changes in pressure over time) and volume change data generated by the compensation module's actions during this process. The processor receives this data and uses a preset system identification algorithm (such as least squares method or transfer function analysis) to analyze the dynamic correlation between pressure changes and volume changes, thereby calculating and locking the elastic characteristic parameters of the specific sealed container under test. These characteristic parameters quantify the container's "pressure-volume" sensitivity under the current assembly conditions.

[0032] In step S120, gas is injected into the test chamber and the sealed container to be tested until the pressure inside the chamber reaches the preset target test pressure, and then the constant pressure test stage begins.

[0033] The steps in this embodiment aim to establish a standard constant pressure test condition. The test system controls the main gas source valve to open, injecting clean, dry test gas (usually compressed air or nitrogen) into the test chamber and the sealed container under test. The inflation process continues until the value monitored by the pressure sensor in the chamber reaches the preset target test pressure. This target test pressure is usually set based on the design pressure limit, operating pressure, or relevant industry regulations and standards (such as the guidelines for the sealing validation of aseptic pharmaceutical packaging systems) of the product under test.

[0034] Once the internal pressure reaches the target value, the system cuts off the main inflation circuit and smoothly switches from rapid inflation mode to constant pressure detection mode. It is worth noting that the constant pressure detection stage in this embodiment differs from the "passive decay observation" of the traditional pressure decay method; it is a dynamic "active maintenance process." During this stage, the system uses closed-loop control to prepare for any minute pressure fluctuations caused by minor leaks or creep of the container material.

[0035] In step S130, during the constant pressure detection stage, the gas elastic compensation module is used to perform pressure feedback control. The compensation amount is adjusted in real time to maintain the pressure in the test chamber at the target test pressure, and the total compensation flow rate data required to maintain the target test pressure is recorded in real time.

[0036] In the embodiments of this application, after the constant pressure detection stage, active control is used to maintain a constant pressure within the chamber. The system utilizes a gas elastic compensation module to activate a highly sensitive pressure feedback control loop (Closed-loop Control), which uses a high-precision pressure sensor to monitor the deviation between the current chamber pressure and the target test pressure in real time at an extremely high sampling rate. Once a slight downward trend in pressure is detected (this downward trend may originate from gas leakage or from volume increase caused by creep of the container material), the controller immediately generates control commands to drive the gas elastic compensation module to operate—for example, by slightly adjusting the opening of the gas replenishment valve or by finely adjusting the volume of the gasbag through a mechanical structure—to compensate for the lost pressure potential energy and strictly maintain the chamber pressure near the target value.

[0037] During this process, the system no longer focuses on the rate of pressure decrease (because the pressure has been compensated to maintain a constant level), but instead focuses on monitoring the "compensation control quantity" output by the system to maintain this constant pressure. The sensor measures and records the output action of the compensation module in real time, forming total compensation flow data that varies over time. This data physically represents the total amount of gas or equivalent volume injected by the system to resist leakage and offset volume changes; it is a comprehensive physical quantity that includes both actual leakage and elastic disturbances.

[0038] In step S140, based on the elastic characteristic parameters and real-time monitored pressure data, the theoretical elastic compensation flow rate caused by the elastic deformation of the sealed container under test is calculated under the current pressure environment.

[0039] It should be noted that although the pressure is kept constant on a macroscopic level, the pressure inside the cavity actually fluctuates within a very small range due to the slight lag of the control system, the background noise of the sensors, and the viscoelastic creep characteristics of the polymer material under constant pressure load.

[0040] Specifically, by calling the acquired elastic characteristic parameters and combining them with the real-time monitored micro-pressure fluctuation data, the system uses a mathematical model to inversely extrapolate the volume change at the current moment caused solely by the elastic breathing of the container wall (i.e., volume expansion and contraction due to small pressure fluctuations) or the inherent creep characteristics of the material. The system converts this theoretical volume change into an equivalent gas flow rate, i.e., the theoretical elastic compensation flow rate. This flow rate value represents the compensation flow rate component that the system should theoretically output under the assumption that the container is absolutely sealed and only has elastic deformation physical characteristics.

[0041] In step S150, the theoretical elastic compensation flow is subtracted from the total compensation flow data in real time to obtain the net make-up gas flow that reflects the actual leakage situation of the sealed container under test.

[0042] In this embodiment, based on the principle of flow superposition, the total compensation flow data recorded in step S130 is actually a vector superposition of the "actual leakage flow" and the "elastic-induced flow". In order to extract the actual leakage information, the processor performs real-time differential operation to subtract the theoretical elastic compensation flow calculated in step S140 from the total compensation flow data point by point.

[0043] Through this decoupling operation, the system successfully isolates the non-leakage flow component caused by seal creep, expansion or contraction of the container's soft walls. The remaining flow data obtained after processing is defined as the net make-up gas flow rate. This net make-up gas flow rate is physically purer, directly reflecting the true physical rate at which gas escapes to the outside through the micropores on the sealing barrier. This effectively eliminates the masking or misleading effect of elastic material properties on the test results, significantly improving the signal-to-noise ratio.

[0044] In step S160, the leakage rate is determined based on the change characteristics of the net replenishment gas flow rate over time, and the leakage rate is compared with a preset integrity standard to determine the sealing integrity of the sealed container under test.

[0045] Here, the system performs a final analysis on the net makeup gas flow rate data generated over time. Since elastic disturbances have been removed, the net makeup gas flow rate curve should exhibit clear physical characteristics in the steady-state phase (e.g., for leak-free products, its value should converge to near the system background noise floor; for leaking products, its value should stabilize at a positive level that reflects the size of the leak orifice).

[0046] For example, a quantified leakage rate is extracted from the net make-up gas flow data according to a preset numerical analysis algorithm (such as steady-state mean calculation, linear regression slope analysis, etc.). Then, the calculated leakage rate is compared with a preset integrity standard (i.e., the maximum allowable leakage limit threshold). If the leakage rate is less than the standard, the system determines that the seal integrity of the sealed container under test is qualified and outputs a pass signal; otherwise, it is determined to be unqualified and triggers an audible and visual alarm, thereby completing the deterministic testing of the RTP interface or sterile container.

[0047] Figure 2 A schematic diagram illustrating an example of a testing system in a method according to an embodiment of this application is shown.

[0048] like Figure 2 As shown, the testing system mainly constructs a fluid-connected loop including a gas supply component, a core test chamber, and a gas elastic compensation module. The gas source is connected to the inlet of the test chamber via a main valve, used to inject test gas into the test chamber at the initial stage of testing to establish the target pressure. Inside the test chamber, a sealed space is formed to accommodate a sealed test container (such as an RTP interface component). This sealed space is connected to a high-frequency pressure sensor via pipeline, used to collect instantaneous pressure change signals within the test loop in real time.

[0049] Connected to the test chamber is a gas elastic compensation module, which serves as the core actuator for maintaining constant pressure in the system. This module integrates a variable volume mechanism (such as a bellows or piston assembly) driven by a control actuator, as well as a precision flow meter for measuring gas flow. The control actuator is configured to precisely drive the variable volume mechanism to perform mechanical expansion and contraction actions according to control commands, thereby physically fine-tuning the effective volume of the test loop or adding trace amounts of gas to the loop. The precision flow meter is connected in series or parallel in the compensation path to monitor and provide real-time feedback of the compensation flow data generated by the compensation actions.

[0050] The system's control unit establishes electrical connections with the pressure sensor, precision flow meter, and control actuator, thus constructing a complete data acquisition and feedback control closed loop. During constant pressure detection, the control unit receives the pressure signal from the pressure sensor in real time and calculates the pressure deviation based on a preset PID control algorithm and elastic feedforward model. It then sends a drive signal to the control actuator. The control actuator responds to this signal by adjusting the action state of the variable volume mechanism to dynamically offset pressure fluctuations caused by elastic deformation or leakage of the tested container. Simultaneously, the control unit records the total compensation flow rate fed back by the precision flow meter, providing data support for leakage rate calculation.

[0051] Regarding the details of calculating the elastic characteristic parameters of the sealed container under test in step S110, in some examples of embodiments of this application, firstly, with the sealed container under test (e.g., RTP interface component) hermetically connected to the test chamber and under a preset initial calibration pressure, the gas elastic compensation module is controlled to generate a precise volumetric step disturbance. And the resulting intracavity pressure step response is simultaneously acquired using sensors. .

[0052] For example, after the sealed container under test is airtightly connected to the test chamber, the system first performs pre-inflation or de-inflation to bring the pressure inside the test chamber and the sealed container under test to a preset initial calibration pressure. , here The pressure should be chosen to be close to the subsequent target test pressure to ensure that the identified elastic characteristics represent actual working conditions. After the system reaches quasi-static equilibrium, the controller instructs the high-precision actuator (such as a linear motor-driven bellows or precision piston) in the gas elastic compensation module to perform a rapid and precise mechanical action, generating a known volumetric step disturbance. The volumetric step perturbation The application process should be instantaneous (e.g., completed within tens of milliseconds), which expresses the input of a clear volumetric excitation signal to the closed system under test.

[0053] It should be noted that the reason for choosing a "step" signal instead of a "ramp" signal in the steps of this embodiment is that the step signal can maximize the excitation of the transient elastic response of the system, while minimizing the interference of the viscoelastic creep of the polymer material (which occurs slowly over time) on the identification of elastic parameters, thereby ensuring that the acquired data mainly reflects the "instantaneous elastic stiffness" of the material.

[0054] Furthermore, based on the ideal gas law and the principle of volume conservation, a calculation model for elastic characteristic parameters is constructed, and the elastic response coefficient of the sealed container under test is analytically obtained. .

[0055] Specifically, while applying the volumetric perturbation, a high-frequency pressure sensor placed inside the test chamber simultaneously acquires the resulting pressure step response within the chamber. For an ideal rigid container, volume compression leads to a significant increase in pressure; however, for an RTP container with elastic walls (such as rubber seals and flexible connectors), some of the pressure potential energy is "absorbed" by the elastic expansion of the container walls, resulting in a smaller observed pressure increase. It is less than the theoretical stiffness value.

[0056] To quantify these "pressure absorption" or "elastic buffering" characteristics, this embodiment constructs a calculation model for elastic characteristic parameters based on the ideal gas law and the principle of volume conservation. This model compares the actually observed pressure-volume change relationship with the ideal gas behavior under theoretical geometric volumes, analytically obtaining the elastic response coefficient of the sealed container under test. .

[0057] Equation (1) In the formula, The initial total geometric volume of the test chamber and the sealed container under test can be obtained through previous geometric measurements or standard calibration. This is the absolute pressure value for the initial calibration pressure (note that absolute pressure is used here to comply with the requirements of the gas law).

[0058] Here, the elastic response coefficient This is a dimensionless elastic characteristic parameter used to quantitatively characterize the pressure-volume response of the sealed container under test under the current pressure environment. It characterizes the "compression compliance" of the system under test relative to an ideal rigid system. This indicates that the container is close to rigid; if The larger the value, the more significant the elastic deformation of the container under the current pressure (i.e., "softer").

[0059] It should be noted that equation (1) expresses a normalized correction to Boyle's law. Under small perturbations, the bulk modulus of an ideal gas is proportional to its pressure. The terms in the formula... This represents the theoretical pressure change rate (rigid reference) that should be caused by a unit volume change under the current operating conditions, while This is the measured volume-pressure ratio. The product of the two eliminates the influence of the test pressure level and container size, directly extracting the elastic characteristics determined by the material properties, thereby achieving a standardized measurement of the elastic behavior of RTP interfaces of different specifications and batches.

[0060] By employing the elastic parameter identification method based on a combination of volumetric step perturbation and a normalized state equation model, this embodiment achieves in-situ, rapid, and quantitative calibration of the "structural stiffness" of complex elastic components such as RTP interfaces. Thus, on the one hand, the correlation between structural elasticity and test pressure is decoupled by introducing dimensionless coefficients. This makes the test results no longer limited to a specific inflation pressure level, improving the versatility of the algorithm. On the other hand, it realizes the establishment of a personalized benchmark of "what is measured is what is calculated", that is, before each test, the elastic parameters are obtained in real time based on the current actual assembly state (such as the aging degree of the sealing ring and the flange tightening force), rather than relying on historical experience values, thereby effectively eliminating baseline drift caused by batch differences or ambient temperature.

[0061] Regarding the implementation details of pressure feedback control using the gas elasticity compensation module in step S130, in some examples of embodiments of this application, in order to overcome the response lag problem of traditional single PID control when dealing with polymer elastic materials, a composite pressure control model based on a feedforward-feedback mechanism is constructed. The current pressure value in the test chamber is collected in real time by a pressure sensor. And calculate the current pressure value and the target test pressure. Pressure deviation between .

[0062] Specifically, first, the system activates a high-frequency sampling circuit to collect the current instantaneous pressure value in real time through pressure sensors placed inside the test chamber. At the same time, the processor calculates the current pressure value and the preset target test pressure in real time. Pressure deviation between This pressure deviation directly reflects the degree of system pressure deviation at the current moment, and its sources include actual gas leakage, elastic creep expansion of the container, and environmental thermal noise interference. This pressure deviation signal not only serves as the input for subsequent feedback control but is also a key indicator for evaluating the steady-state accuracy of the control system.

[0063] Then, the pressure deviation is handled using a PID controller. Generate feedback control components , This section represents the control commands generated by the system to correct for existing pressure errors; it can be used to eliminate random and steady-state errors. The PID controller dynamically adjusts the control input by proportionally amplifying, integrally accumulating, and derivative predicting the deviation. Equation (2) In the formula, These are the proportional coefficient, integral coefficient, and differential coefficient, respectively. Specifically, the proportional coefficient... Used to adjust the system's response speed to the current error. The larger the value, the faster the response, but an excessively large value may cause system oscillations; integral coefficient Used to eliminate steady-state error (static error) of the system, ensuring that the pressure eventually stabilizes precisely at the target value by accumulating historical errors; differential coefficients This feedback mechanism is used to predict the trend of error changes and provides proactive control, helping to suppress pressure overshoot caused by elastic deformation of the RTP interface. It primarily handles dynamic disturbances "not predicted by the model," such as real leakage fluctuations or random sensor noise, ensuring system robustness.

[0064] An elastic feedforward compensation mechanism is introduced, and an elastic prediction model is constructed based on elastic characteristic parameters. The feedforward compensation component used to offset the inherent elastic deformation of the sealed container under test is then calculated. .

[0065] Specifically, to further counteract the drag effect of the inherent elastic deformation of the sealed container under test on the pressure build-up process, this embodiment introduces an elastic feedforward compensation mechanism. This is based on the elastic characteristic parameters (i.e., elastic response coefficients) obtained in step S110. The system constructs an elastic prediction model to pre-calculate the target pressure. The elastic volume expansion that will inevitably occur in the container is converted into a feedforward compensation component. . Next, the feedback control component With feedforward compensation components Linear superposition is performed to generate the final driving signal. .

[0066] Equation (3) In the formula, This is the feedforward compensation gain coefficient, such as a preset conversion coefficient, used to convert the elastic deformation prediction value into the drive signal amplitude, which can be directly recognized by the actuator.

[0067] Here, the final drive signal It can be directly supplied to the actuator of the gas elastic compensation module (such as the drive voltage of the motor or the PWM signal). In equation (3), the term This forms the "reference base" for control, which tells the actuator, "Regardless of whether there is a leak, the container will expand by this much under pressure; please pre-output this compensation amount." This constitutes a "fine-tuning correction," used to fill the pressure gap caused by prediction deviations and actual leakage.

[0068] Furthermore, based on the final driving signal The driving gas elastic compensation module performs physical compensation actions; these actions include fine-tuning the effective volume of the test chamber or making minor adjustments to the gas mass within the chamber, in order to achieve active suppression and dynamic balance of pressure fluctuations.

[0069] Specifically, this action includes driving a variable volume mechanism (such as a bellows) to compress or extend to fine-tune the effective volume of the test chamber, or controlling the opening of a micro-flow valve to make minor adjustments to the gas mass within the chamber. By employing a combined action of feedforward preset and feedback fine-tuning, the system can achieve active suppression and dynamic balance of pressure fluctuations, ensuring that the pressure within the test chamber is locked and maintained at the target test pressure within a very short time, creating ideal constant pressure conditions for subsequent flow observation.

[0070] Through the embodiments of this application, the aforementioned composite pressure control strategy based on a feedforward-feedback mechanism significantly improves the pressure control response speed and steady-state accuracy for highly elastic RTP components. Utilizing the elastic feedforward channel, the system can control based on pre-identified elastic parameters. This system "predicts" and compensates for most of the volume loss caused by the elastic expansion of the material, thus avoiding the pressure drop or excessive settling time problems caused by integral lag in traditional pure PID control. Simultaneously, it eliminates residual errors and random disturbances by incorporating the PID feedback channel. Therefore, by employing a dual-channel control mechanism, the nonlinear hysteresis effect caused by the viscoelasticity of polymer materials is effectively overcome, enabling the testing system to enter a true "quasi-static constant pressure" state in a very short time. This not only significantly shortens the testing cycle but also precisely maps the compensation actions required to maintain pressure into drive signals.

[0071] Regarding the implementation details of calculating the theoretical elastic compensation flow rate in step S140, in some examples of embodiments of this application, in order to accurately distinguish between gas loss caused by leakage and volume change caused by container material characteristics, firstly, a viscoelastic dynamic model is constructed for the material characteristics of the sealed container under test (especially the polymer seal of the RTP interface) to decouple the non-leakage volume drift caused by pressure fluctuation and material creep in real time.

[0072] Here, the core purpose of the viscoelastic dynamics model is to decouple in real time the non-leakage volume drift caused by the small pressure fluctuations (high-frequency perturbations) in the test chamber and the time-dependent creep (low-frequency drift) of the material itself.

[0073] Unlike traditional static compensation, which only considers a fixed coefficient of volume expansion, the model in this embodiment treats the container as a dynamic "breathing body." The system receives high-precision pressure data sequences monitored in real time and uses a differential algorithm to calculate the instantaneous rate of change of pressure. By substituting these dynamic variables into the model, the system can quantify how much volume change occurs within the current millisecond-level time window simply because "pressure has changed" or "material has relaxed."

[0074] Then, the real-time monitored pressure data is substituted into the viscoelastic dynamics model to calculate the theoretical elastic compensation flow rate. This flow rate value does not represent the actual physical flow of gas, but rather the portion of the flow that the system should have supplied to the elastic deformation of the container in order to maintain a constant pressure.

[0075] Equation (4) In the formula, The rate of change of real-time pressure; The viscoelastic drift coefficient (or rheological admittance coefficient) is a preset value based on the material properties of the sealed container under test. It expresses the volumetric drift rate under a unit pressure difference and is used to calculate the volumetric drift caused by pressure deviation. The resulting viscoelastic damping component compensates for the volumetric creep caused by the material's hysteresis effect.

[0076] Regarding the explanation of equation (4), its first term The instantaneous elastic response component describes the "breathing effect" of the container; when the control system adjusts the pressure, it is inevitably accompanied by tiny pressure fluctuations. For flexible containers, a slight increase in pressure will result in a slight expansion of volume, and vice versa. This method accurately calculates this volumetric throughput that occurs instantly with pressure fluctuations, preventing pressure regulation noise in the control process from being misinterpreted as leakage flow.

[0077] Second item For the viscoelastic damping component, where These are empirical or calibration coefficients preset based on the material properties of the sealed container under test (such as rubber hardness and relaxation time constant), used to convert pressure deviation into creep flow rate. They describe the material's "hysteresis" or "creep," which occurs even when the pressure no longer changes ( If the current pressure deviates from the target pressure, the polymer material will still slowly change shape due to stress relaxation. This feature compensates for this slow volume drift caused by the material's viscoelastic memory, ensuring that the baseline does not shift during long-term micro-leakage tests.

[0078] Through the embodiments of this application, a viscoelastic dynamic model containing instantaneous breathing and hysteretic creep terms is constructed and applied, realizing the reconstruction of the dynamic volumetric response of complex elastic components such as RTP interfaces under constant pressure fields. This mathematically orthogonally separates the previously mixed "physical leakage flow" and "structural deformation flow." In particular, by introducing the derivative term of the pressure change rate, the system can effectively filter out spurious flow signals induced by minute pressure oscillations during PID control, significantly reducing the system's flow observation noise floor under high-sensitivity detection conditions. Simultaneously, the addition of a damping compensation term effectively suppresses long-term measurement drift caused by material stress relaxation, preventing the detection results from deteriorating with prolonged testing time. This fundamentally solves the problem that traditional pressure decay methods cannot distinguish between "true leaks" and "soft expansion," significantly improving the ability and confidence in detecting minute leaks.

[0079] Regarding the implementation details of calculating the net replenishment gas flow rate in step S150, in some examples of embodiments of this application, in order to further eliminate the interference of ambient temperature fluctuations and gas compression heat on the detection of trace leaks, the system performs a thermodynamic interference compensation step. First, a high-precision temperature sensor arranged in the test chamber is used to monitor the rate of temperature change of the gas in the chamber in real time. And combined with the initial total geometric volume of the test cavity and the coefficient of thermal expansion of the test gas Calculate the thermal expansion compensation flow rate caused by thermal effects. .

[0080] Specifically, the instantaneous temperature change rate of the gas inside the chamber is monitored in real time using a high-precision, low-heat-capacity temperature sensor (such as a platinum resistance thermometer Pt100 or a thermistor) placed inside the test chamber. Furthermore, the system incorporates the initial total geometric volume of the test chamber. and the standard coefficient of thermal expansion of the test gas used (such as dry air or nitrogen). Using the differential form of Charles's Law, the equivalent flow rate corresponding to the gas volume expansion or contraction caused by thermal effects at the current moment can be calculated, i.e., the thermal expansion compensation flow rate. .

[0081] Equation (5) in, A positive value indicates that the gas expands due to increased temperature, and the system needs to reduce the amount of gas supplied; a negative value indicates that the gas contracts due to decreased temperature, and the system needs to supply additional gas. The coefficient of thermal expansion of the gas being tested is usually taken as the reciprocal of the current absolute temperature of the gas (i.e., 1 / T). For example, it is about 1 / 273.15 under standard conditions and about 1 / 298.15 at room temperature (25°C).

[0082] In equation (5), even if the container is completely sealed and does not deform, the only effect is temperature change. The gas inside the cavity will also undergo volume changes. This must be deducted, otherwise in precision testing, even a tiny temperature rise (e.g., 0.1°C) could produce false flow rates enough to mask minor leaks.

[0083] Then, obtain the background leakage traffic of the test system itself. The background leakage flow rate is baseline data that is pre-measured and stored when the test system is under no-load and regulated voltage.

[0084] It should be noted that this background leakage flow... It is not a real-time calculated value, but rather a baseline data measured in advance through long-term operation and stored in the system memory when the test system is unloaded (i.e., not connected to the container under test or connected to a leak-free standard component), under stable pressure and thermal equilibrium. It represents the inherent trace leakage rate of the test pipeline, valve interface and sensor itself, and belongs to the system's "baseline noise".

[0085] Furthermore, a full-source flow conservation decoupling model is constructed, based on the principle of mass conservation, from the total compensation flow data recorded during the constant pressure detection stage. Synchronous stripping of theoretical elastic compensation flow Thermal expansion compensation flow rate and background leakage traffic This allows for the reconstruction of the net makeup gas flow rate, which is only related to the actual leakage. .

[0086] Equation (6) In equation (6), by subtracting the known interference terms one by one, the remaining residual is the "true leakage". It should be noted that when the temperature rises and causes the gas to expand, the actual amount injected into the system... The leakage rate will decrease, therefore the thermal expansion compensation term needs to be added to the decoupling model to restore the true leakage baseline.

[0087] By implementing the aforementioned signal decoupling strategy based on thermodynamic compensation and full-source flow conservation, high-purity extraction of minute leakage signals is achieved under complex physical field interference. In this embodiment, the system no longer assumes that the test environment is ideally isothermal or absolutely airtight, but actively quantifies and eliminates two common environmental error sources: temperature drift and system background. By combining the elastic decoupling of the preceding steps, a complete multi-physics field error correction system is constructed, ensuring that the final obtained net makeup gas flow rate... It has extremely high physical confidence. Even under harsh conditions such as large temperature fluctuations in the test environment or the presence of trace background leakage in the test system itself, this method can still guarantee zero-point stability and resolution of leak detection, effectively avoiding false positives caused by environmental thermal noise, and significantly improving the robustness and environmental adaptability of RTP interface seal integrity testing.

[0088] Regarding the implementation details of determining the leakage rate in step S160, in some examples of embodiments of this application, in order to further eliminate the influence of sensor background noise and fluid micro-turbulence on the measurement results, the net makeup air flow rate is... Time series data undergoes signal denoising preprocessing: if high-frequency random noise is detected, a moving average filter or Gaussian filter algorithm is applied to improve the data signal-to-noise ratio.

[0089] Specifically, the system detects high-frequency components in the signal. If high-frequency random noise is present, a moving average filter or Gaussian filter algorithm can be applied to smooth the original data. This effectively improves the signal-to-noise ratio (SNR) of the data while preserving the trend of flow changes, and prevents individual outliers from biasing subsequent calculations.

[0090] Then, time-domain morphological analysis is performed on the preprocessed data: the transient response stage that characterizes the inflation build-up process is identified and eliminated, and the steady-state detection stage that characterizes the actual leakage features is locked.

[0091] It should be noted that due to the physical inertia of gas path switching and pressure build-up, the flow rate curve typically exhibits a pattern of "initial surge followed by oscillation and then stabilization." The system automatically identifies and eliminates the transient response phase characterizing the inflation build-up process by recognizing the derivative characteristics of the flow rate change, accurately pinpointing the steady-state detection phase characterizing the actual leakage. Only data segments within the steady-state phase are selected as valid samples for subsequent calculations, thus logically eliminating non-steady-state errors during the system's dynamic adjustment process.

[0092] Subsequently, numerical analysis is performed on the data in the steady-state detection phase, and the leakage rate is determined by executing flow statistical analysis strategy or volume regression analysis strategy.

[0093] Here, for data locked in the steady-state detection phase, this embodiment provides two optional numerical analysis strategies to determine the final leakage rate. The system can automatically select and execute the strategy based on the current noise level or user settings.

[0094] On the one hand, traffic statistics and analysis strategies include: Calculate the net make-up gas flow rate The arithmetic mean of the values ​​during the steady-state detection phase is used as the leakage rate.

[0095] It should be noted that the flow statistics analysis strategy is suitable for scenarios with high signal-to-noise ratio and stable operating conditions. The system directly calculates the net makeup gas flow rate. The arithmetic mean or steady-state regression mean within the steady-state time window. Since this value has already been adjusted for elastic and thermal disturbances, its mean can directly represent the average gas leakage per unit time, and it can be directly output as the leakage rate.

[0096] On the other hand, volume regression analysis strategies include: First, regarding the net gas supply flow rate Time integration is performed during the steady-state detection phase to construct a cumulative leakage volume curve. .

[0097] It should be noted that the volume regression analysis strategy is suitable for high-sensitivity detection scenarios with minute leaks or large signal fluctuations, converting "instantaneous flow rate" into "cumulative volume" for analysis. The processor first analyzes the net make-up gas flow rate during the steady-state phase. Numerical time integration was performed to construct a cumulative leakage volume curve that monotonically increases with time. .

[0098] Equation (7) In the formula, This marks the start of the steady-state detection phase. This is the time integration variable.

[0099] In equation (7), the integral operation has a natural "low-pass filtering" characteristic. Even The signal exhibits random fluctuations around zero (white noise). Through integration, the positive and negative noise cancel each other out, resulting in a volumetric curve. It exhibits a very smooth linear characteristic.

[0100] Furthermore, the least squares method was used to analyze the cumulative leakage volume curve. Perform linear regression fitting, calculate the slope of the fitted line, and determine the slope as the leakage rate.

[0101] It should be noted that, under constant pressure conditions, the leakage flow rate is theoretically constant for a fixed leakage orifice diameter; therefore, the cumulative volume change over time should be a straight line. The system calculates the slope of this fitted line and determines this slope as the final leakage rate. From a physical perspective, the derivative of volume with respect to time is the flow rate (…). By integrating first and then calculating the slope, the method actually utilizes data points from the entire time period to jointly determine an optimal leakage value, rather than relying on a single reading at a certain moment, which also greatly reduces the weight of random errors.

[0102] This application introduces a dual data processing mechanism of "integral transform-linear regression" to perform process trend analysis in the leakage rate determination stage. Specifically, the traditional direct flow averaging method is easily affected by occasional pressure fluctuations or electromagnetic interference. However, the volume regression strategy in this embodiment utilizes the inherent noise smoothing characteristics of integral operations to convert high-frequency fluctuating flow signals into smooth volume growth signals, effectively filtering out random white noise. Furthermore, by fitting the slope using the least squares method, the information redundancy of all data points in the steady-state stage is utilized, resulting in a highly statistically robust leakage rate output. In particular, for the detection of minute leaks at RTP interfaces, even when the net flow signal is extremely weak and submerged in background noise, a significant volume trend can still be accumulated through long-term integration, thereby greatly improving the sensitivity lower limit and result repeatability of the detection system.

[0103] As a further preferred embodiment of this application, before determining the sealing integrity of the sealed container under test, in order to ensure the validity of the test data itself and prevent misjudgment due to sudden environmental changes, a process statistical controlled state monitoring step can also be performed.

[0104] More specifically, a statistical process control model based on the Cumulative Sum (CUSUM) is first constructed, which is particularly suitable for detecting small shifts in the process mean. The system sets an initial cumulative statistic. And the net make-up gas flow rate during the steady-state detection phase Discretize into data sequence The discretization sampling frequency here should be high enough (e.g., >10Hz) to capture any transient disturbances. By initializing the statistics, the system establishes a "zero-drift" baseline state, ready to begin quality assessment of each new frame of incoming traffic data.

[0105] Then, for the discretized flow data sequence, recursive calculations are performed to generate real-time state statistics. It follows the unilateral CUSUM algorithm logic as follows: Equation (8) In the formula, This represents the net make-up gas flow rate at the current sampling time; This is the steady-state baseline mean of the current data sequence, used to characterize the current center of leakage level. Under ideal steady-state conditions, this value should be a constant (i.e., the true average leakage rate). This is a preset drift tolerance parameter used to filter background white noise within an allowable range. For example, A preset statistical threshold value (which can be 0.5 times the standard deviation of system noise) can be used, and its physical function is equivalent to a "filter" to remove background white noise within the allowable range.

[0106] here, Indicates the current time The real-time cumulative status; The previous sampling time The accumulated amount reflects the memorization of the algorithm. In equation (8), if The deviation is less than the tolerance. The calculated result may be negative. In this case, Resetting it to 0 ensures that the error only occurs when the deviation consistently and significantly exceeds the noise level. Only then will cumulative growth begin.

[0107] Then, monitor the real-time status statistics. ,when Exceeding the preset judgment threshold At this point, the current constant pressure testing process is determined to be in a state of statistical out of control. This state is triggered because a non-random, systematic bias has occurred during the testing process.

[0108] Furthermore, in response to statistical runaway states, the system identifies sudden external disturbances (such as operator touching the test bench or sudden changes in ambient temperature) or system mechanical instability (such as momentary slippage of the sealing ring) affecting the testing process, and triggers a process anomaly alarm signal to mark the current test data as invalid, preventing environmental interference from being misjudged as product leakage. At this point, the controller immediately triggers the process anomaly alarm signal and automatically marks the current test data as "invalid," forcibly terminating the subsequent pass / fail determination process. This effectively constructs a firewall for data integrity, preventing false flow fluctuations caused by environmental interference from being misjudged as actual product leakage.

[0109] This application introduces a statistical process control state monitoring mechanism based on the CUSUM algorithm, adding a "process quality monitoring" dimension to the traditional "result judgment." By utilizing the cumulative sum algorithm's memory and amplification effect on minute deviations, it can highly sensitively capture systematic drifts or step disturbances submerged in conventional noise. Unlike traditional threshold alarms, this embodiment does not look at whether a single point exceeds the limit, but rather whether the "trend" is abnormal. This intelligent process self-inspection capability enables the testing system to automatically distinguish between two fundamentally different physical situations: "product leakage" and "environmental disorder." This significantly reduces the false positive rate caused by vibration, airflow, or temperature shocks in industrial settings, improving the reliability and data compliance of the RTP interface online detection system.

[0110] Regarding the implementation details of determining the seal integrity by standard comparison in step S160, in some examples of embodiments of this application, when using leakage rate to determine the seal integrity, in order to avoid misjudgment caused by environmental changes due to fixed threshold, the system first performs the extraction step of the system's inherent noise standard deviation.

[0111] Specifically, obtain the preset target leakage rate benchmark. (For sterile containers requiring zero leakage, this value is typically set to 0 or close to the detection limit), and a net make-up gas flow rate data sequence during the steady-state detection phase is selected. The standard deviation of the system's inherent noise is obtained by calculating its statistical distribution dispersion. .

[0112] Equation (9) In the formula, This represents the total number of data points (i.e., the total number of data points collected during the steady-state detection phase). This is the arithmetic mean of the net supplementary airflow during this stage. This allows for the practical measurement of the current "signal-to-noise ratio environment," assuming the environment is very quiet. Very small; if the environment is noisy, This is significant, providing an objective basis for subsequent dynamic adjustments to the judgment criteria.

[0113] Then, based on the principle of statistical normal distribution, an adaptive decision threshold that can dynamically adapt to the current test signal-to-noise ratio is constructed. .

[0114] Equation (10) In the formula, The weighting coefficients related to the preset confidence level, item This constitutes a safety confidence margin for suppressing random noise interference.

[0115] Furthermore, the leakage rate With adaptive decision threshold Comparison: On the one hand, if If the leak level of the sealed container under test does not deviate significantly from the target leak rate benchmark in a statistically significant manner, the seal integrity is confirmed to be qualified. This means that even if a slightly positive value is measured, the system still considers it qualified because the value is still within the allowable fluctuation range of noise (confidence interval).

[0116] On the other hand, if If the leak is statistically significant, the sealed container under test is deemed to have failed the seal integrity test.

[0117] This application employs an adaptive threshold determination strategy based on noise statistical characteristics, introducing a dynamic signal-to-noise ratio sensing mechanism. This allows the determination criteria to adjust according to fluctuations in ambient noise. In quiet environments, the threshold automatically tightens, significantly improving the detection sensitivity for minute leaks; in noisy environments, the threshold is appropriately relaxed (automatically increasing the safety margin). This effectively shields against non-leakage-related random interference, thereby significantly reducing the false positive rate. Therefore, by employing a scientific judgment logic based on statistical significance testing, the test results no longer rely on the operator's subjective experience or rigid standards, but are based on objective data distribution characteristics, greatly improving the confidence and compliance of the RTP interface seal integrity test results.

[0118] Figure 3 A schematic diagram illustrating the principle mechanism of an example pressure decay test method based on gas elastic compensation according to an embodiment of this application is shown.

[0119] like Figure 3 As shown, the testing mechanism is divided into four logical modules: input area, core processing and model area, control and constraint area, and output and result area. The input area is responsible for constructing the physical test environment, sealing the RTP port under test to the sealed test chamber and injecting gas. The core processing and model area collects system pressure signals in real time through a pressure monitoring unit, measures the replenishment gas flow rate using a high-precision flow meter, and performs physical compensation actions using an elastic gasbag (i.e., a gas elastic compensation module). These physical quantities are transmitted to the control and constraint area, where the elastic coefficient (i.e., elastic characteristic parameter) is first obtained through a pre-test calibration process. Then, a PID controller combined with a feedforward model generates a precise control signal that is fed back to the core processing area to maintain a constant pressure. Simultaneously, the compensation algorithm module comprehensively processes the pressure signal, flow signal, and elastic parameter, performing gas law calculations to eliminate interference components. Finally, the decoupled data flows to the output and result area, generating the net flow rate (mbar·L / s) reflecting the actual leakage situation and a final integrity assessment report.

[0120] To verify the superiority of the pressure decay testing method based on gas elastic compensation proposed in this application, and to analyze its detection accuracy and stability under different elastic conditions, this application constructs a co-simulation model that includes the elastic modulus characteristics of the RTP interface, gas thermodynamic behavior, and PID closed-loop control logic. This model sets the container under test to have a specific initial volume. and initial pressure The elastic cavity was designed, and a preset real leakage rate was introduced into the simulation. (For example, about and different container elastic coefficients This is to simulate the dynamic response of the effective volume of a container under pressure changes.

[0121] Based on this simulation model, numerical discretization methods (such as the Euler method) are used to solve the differential equation of pressure decay to compare the detection mechanisms of the two methods. For the traditional pressure decay method, the simulation focuses on analyzing the pressure-time decay trend and the resulting leakage rate estimation deviation when the elastic deformation of the container is ignored (i.e., the volume is assumed to be constant). For the new method in this application, the simulation simulates the dynamic process of direct air replenishment under constant pressure conditions through PID feedback, and subtracts the theoretical elastic flow rate calculated from the elastic characteristic parameters from the total replenishment flow rate to obtain the net replenishment flow rate.

[0122] The comparative results of simulation experiments are typically presented using time-domain response curves and error distribution heatmaps. The time-domain curves visually reflect the stability of the new method in suppressing elastic disturbances, while the error heatmap further illustrates the leakage rate. and elasticity coefficient Within the constructed two-dimensional parameter space, the difference between the baseline method error and the new method error was calculated and displayed. Analysis shows that as the elastic coefficient... With the increase of elastic modulus, the detection error of traditional methods shows a significant upward trend. However, the gas elasticity compensation strategy of this application can maintain a low relative error under a wide range of elastic modulus and leakage rate combinations, thus theoretically verifying the effectiveness of this method for leak detection of complex elastic containers.

[0123] Figure 4 A comparative diagram of test data from different methods under a simulation environment is shown. This diagram illustrates the dynamic response characteristics of the traditional pressure decay method (baseline method) and the gas elastic compensation method proposed in this application under the same elastic container operating conditions and preset leakage rate. The horizontal axis represents the test time, the left vertical axis represents the pressure deviation relative to the target pressure, and the right vertical axis represents the accumulated compensation volume. The blue dashed line in the figure represents the pressure response of the traditional baseline method. It can be clearly observed that the significant "tailing effect" caused by the viscoelastic creep of the container material results in a substantial deviation of the pressure from the reference zero point even without additional leakage, forming a spurious pressure drop.

[0124] like Figure 4As shown in the figure, the blue solid line represents the pressure response within the test chamber using the method of this application. Thanks to the PID active feedback control mechanism, the system successfully overcomes elastic interference, maintaining the pressure deviation consistently near zero. Although there are minor "high-frequency jitters" due to sensor noise and rapid adjustment, the overall system remains in a controlled constant pressure state. Based on this, the red solid line in the figure shows the trend of the "cumulative compensation volume" calculated by the method of this application over time. This curve exhibits extremely high linearity, indicating that the net flow output after decoupling is stable. The system can accurately determine the leakage rate by performing linear regression on this curve (i.e., calculating the slope), thus verifying the technical advantages of this method in suppressing elastic interference and improving measurement stability.

[0125] Figure 5 The diagram shows a comparison of the relative measurement error distribution of different methods under three typical elastic conditions based on Monte Carlo simulation. The diagram, in the form of a violin plot, intuitively shows the performance difference between the gas elasticity compensation method (red distribution) proposed in this application and the traditional baseline pressure decay method (gray distribution) under three typical conditions: "low elasticity (rigid metal container)," "medium elasticity (semi-rigid plastic)," and "high elasticity (RTP interface with large area rubber seals)."

[0126] like Figure 5 As shown, with the increase of the system's elastic modulus, the measurement error of the traditional baseline method diverges exponentially; especially under the high elasticity RTP condition, its average error even reaches -60%, indicating that the traditional method cannot distinguish between elastic expansion and gas leakage, resulting in a serious underestimation of leakage (false negative).

[0127] In contrast, the error distribution (red area) obtained using the method of this application maintains a convergence pattern centered at 0% under all operating conditions, proving that the decoupling of leakage measurement and container elasticity is successfully achieved through real-time physical compensation. It is worth noting that under low elasticity (rigidity) conditions, the error dispersion of the method of this application is slightly higher than that of the traditional method (controlled within ±2%). This is because the active gas replenishment operation introduces a small additional mechanical disturbance, while the traditional method is only affected by sensor electronic noise. However, this slight sacrifice in accuracy yields unparalleled adaptability to highly elastic systems. This engineering trade-off has extremely high practical value for solving the testing challenges of complex components such as RTP interfaces.

[0128] Simulation results demonstrate that the gas elastic compensation-based testing method proposed in this application fundamentally reconstructs the physical boundary conditions for leak detection by transforming the traditional "passive pressure decay observation" into "net flow measurement under active volume maintenance." Although active control introduces minor mechanical disturbances (such as a slight increase in background noise), it successfully overcomes the elastic masking effect of the RTP interface material, achieving high linearity response and zero-point stability under all operating conditions. This provides a definite technical path for solving complex seal detection in aseptic isolation systems.

[0129] At the implementation level, this method introduces a gas elastic compensation module (such as a servo-driven variable volume mechanism) to replace the traditional static test chamber, achieving real-time physical compensation for volume fluctuations caused by elastic deformation and thermal effects of the specimen. By employing a mechanism coupling constant pressure control and micro-flow measurement, supplemented by a feedforward compensation strategy based on elastic characteristic parameters, it overcomes the sensitivity bottleneck of the traditional pressure attenuation method under limited head space and elastic interference, achieving direct and quantitative measurement of leakage flow and significantly improving the reproducibility of test results.

[0130] Furthermore, at the algorithm level, this method constructs an adaptive compensation model that incorporates viscoelastic decoupling and full-source flow conservation. Through volume regression analysis and dynamic threshold determination, it effectively improves the robustness of data processing.

[0131] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of combined actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Secondly, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application. In the above embodiments, the descriptions of each embodiment have their own emphasis; for parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0132] Figure 6 A structural block diagram of an example pressure decay testing system based on gas elastic compensation according to an embodiment of this application is shown.

[0133] like Figure 6 As shown, the pressure decay test system 600 based on gas elastic compensation includes a pre-test calibration unit 610, a pressure construction and initialization unit 620, a constant pressure feedback compensation unit 630, an elastic model calculation unit 640, a net flow analysis unit 650, and an integrity assessment and judgment unit 660.

[0134] The pre-test calibration unit 610 is used to connect the sealed container under test to the test chamber equipped with a gas elasticity compensation module. By applying a preset pressure test signal to the sealed container under test, it obtains pressure response data and volume change data in response to the pressure test signal, so as to calculate and obtain the elastic characteristic parameters of the sealed container under test.

[0135] The pressure building and initialization unit 620 is used to inject gas into the test chamber and the sealed container under test until the pressure inside the chamber reaches the preset target test pressure, and then enter the constant pressure detection stage.

[0136] The constant pressure feedback compensation unit 630 is used to perform pressure feedback control using the gas elastic compensation module during the constant pressure detection stage. It adjusts the compensation amount in real time to maintain the pressure in the test chamber at the target test pressure and records the total compensation flow rate data required to maintain the target test pressure in real time.

[0137] The elastic model calculation unit 640 is used to calculate the theoretical elastic compensation flow rate caused by the elastic deformation of the sealed container under test under the current pressure environment, based on the elastic characteristic parameters and the real-time monitored pressure data.

[0138] The net flow analysis unit 650 is used to subtract the theoretical elastic compensation flow from the total compensation flow data in real time to obtain the net gas supply flow that reflects the actual leakage situation of the sealed container under test.

[0139] The integrity assessment and determination unit 660 is used to determine the leakage rate based on the change characteristics of the net make-up air flow rate over time, and compare the leakage rate with a preset integrity standard to determine the sealing integrity of the sealed container under test.

[0140] In some embodiments, this application provides a non-volatile computer-readable storage medium storing one or more programs including execution instructions. The execution instructions can be read and executed by an electronic device (including but not limited to a computer, server, or network device) to perform the steps of any of the pressure decay test methods based on gas elasticity compensation described above.

[0141] In some embodiments, this application also provides a computer program product, the computer program product including a computer program stored on a non-volatile computer-readable storage medium, the computer program including program instructions, which, when executed by a computer, cause the computer to perform the steps of any of the above-described pressure decay test methods based on gas elasticity compensation.

[0142] In some embodiments, this application also provides an electronic device comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform steps of a pressure decay test method based on gas elasticity compensation.

[0143] The above-described product can perform the methods provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects for performing the methods. Technical details not described in detail in this embodiment can be found in the methods provided in the embodiments of this application.

[0144] The electronic devices in this application can exist in various forms, including but not limited to: mobile communication devices, ultra-mobile personal computer devices, portable entertainment devices, or other airborne electronic devices with data interaction functions.

[0145] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0146] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software plus a general-purpose hardware platform, or of course, using hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0147] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A pressure decay test method based on gas elastic compensation, characterized in that, The method includes: The sealed container under test is connected to a test chamber equipped with a gas elasticity compensation module. A preset pressure test signal is applied to the sealed container under test, and pressure response data and volume change data in response to the pressure test signal are obtained in order to calculate and obtain the elastic characteristic parameters of the sealed container under test. Gas is injected into the test chamber and the sealed container to be tested until the pressure inside the chamber reaches the preset target test pressure, and then the constant pressure test stage begins. During the constant pressure detection phase, the gas elastic compensation module is used to perform pressure feedback control. The compensation amount is adjusted in real time to maintain the pressure in the test chamber at the target test pressure, and the total compensation flow rate data required to maintain the target test pressure is recorded in real time. Based on the elastic characteristic parameters and real-time monitored pressure data, the theoretical elastic compensation flow rate caused by the elastic deformation of the sealed container under test is calculated under the current pressure environment. The theoretical elastic compensation flow is subtracted from the total compensation flow data in real time to obtain the net make-up gas flow that reflects the actual leakage of the sealed container under test. The leakage rate is determined based on the change characteristics of the net replenishment gas flow rate over time, and the leakage rate is compared with a preset integrity standard to determine the sealing integrity of the sealed container under test.

2. The method according to claim 1, characterized in that, The step of applying a preset pressure test signal to the sealed container under test, acquiring pressure response data and volume change data in response to the pressure test signal, and calculating and acquiring the elastic characteristic parameters of the sealed container under test includes: With the sealed container under test connected to the test chamber and under a preset initial calibration pressure, the gas elastic compensation module is controlled to generate a precise volumetric step disturbance. And the resulting intracavity pressure step response is simultaneously acquired using sensors. ; Based on the ideal gas law and the principle of volume conservation, a calculation model for elastic characteristic parameters is constructed, and the elastic response coefficient of the sealed container under test is analytically obtained. : ， In the formula, This represents the initial total geometric volume of the test chamber and the sealed container under test. The absolute pressure value of the initial calibration pressure; the elastic response coefficient It is a dimensionless elastic characteristic parameter used to quantitatively characterize the pressure-volume response characteristics of the sealed container under test under the current pressure environment.

3. The method according to claim 2, characterized in that, The step of using the gas elastic compensation module to perform pressure feedback control, and adjusting the compensation amount in real time to maintain the pressure in the test chamber at the target test pressure, includes: A composite pressure control model based on a feedforward-feedback mechanism is constructed, and the current pressure value in the test chamber is acquired in real time through a pressure sensor. And calculate the current pressure value and the target test pressure. Pressure deviation between ; Using a PID controller to handle pressure deviation Generate feedback control components : ， In the formula, These are the proportional coefficient, integral coefficient, and differential coefficient, respectively. An elastic feedforward compensation mechanism is introduced, and an elastic prediction model is constructed based on the elastic characteristic parameters to calculate the feedforward compensation component used to offset the inherent elastic deformation of the sealed container under test. ; The feedback control component With the feedforward compensation component Linear superposition is performed to generate the final driving signal. : ， In the formula, This is the feedforward compensation gain coefficient, used to convert the predicted elastic deformation value into the amplitude of the driving signal; Based on the final driving signal The gas elastic compensation module is driven to perform physical compensation actions; the physical compensation actions include fine-tuning the effective volume of the test chamber or making slight adjustments to the gas mass in the chamber, so as to achieve active suppression and dynamic balance of pressure fluctuations.

4. The method according to claim 2, characterized in that, The calculation of the theoretical elastic compensation flow rate caused by the elastic deformation of the sealed container under test under the current pressure environment, based on the elastic characteristic parameters and real-time monitored pressure data, includes: A viscoelastic dynamic model is constructed based on the material properties of the sealed container under test to decouple the non-leakage volume drift caused by pressure fluctuations and material creep in real time. Substitute the real-time monitored pressure data into the viscoelastic dynamics model to calculate the theoretical elastic compensation flow rate. : ， In the formula, The rate of change of real-time pressure; A viscoelastic drift coefficient, preset based on the material properties of the sealed container under test, is used to calculate the pressure deviation. The resulting viscoelastic damping component compensates for the volumetric creep caused by the material's hysteresis effect.

5. The method according to claim 4, characterized in that, The step of subtracting the theoretical elastic compensation flow from the total compensation flow data in real time to obtain the net make-up gas flow reflecting the actual leakage situation of the sealed container under test includes: Perform the thermodynamic interference compensation step: Use a high-precision temperature sensor arranged in the test chamber to monitor the rate of temperature change of the gas in the chamber in real time. And combined with the initial total geometric volume of the test cavity and the coefficient of thermal expansion of the test gas Calculate the thermal expansion compensation flow rate caused by thermal effects. : ， Obtain the background leakage traffic of the test system itself. The background leakage flow rate is baseline data that has been pre-measured and stored when the test system is under no-load and stable voltage conditions; Construct a full-source flow conservation decoupling model, based on the principle of mass conservation, from the total compensated flow data recorded during the constant pressure detection stage. The theoretical elastic compensation flow rate is simultaneously stripped from the middle. The thermal expansion compensation flow rate and the background leakage flow This allows for the reconstruction of the net makeup gas flow rate, which is only related to the actual leakage. : 。 6. The method according to claim 5, characterized in that, The step of determining the leakage rate based on the characteristics of the change in net makeup gas flow rate over time includes: The net replenishment gas flow rate Time series data undergoes signal denoising preprocessing: if high-frequency random noise is detected, a moving average filter or Gaussian filter algorithm is applied to improve the data signal-to-noise ratio; Perform time-domain morphological analysis on the preprocessed data: identify and remove the transient response stage that characterizes the inflation build-up process, and lock in the steady-state detection stage that characterizes the actual leakage characteristics; Numerical analysis is performed on the data in the steady-state detection phase, and the leakage rate is determined by executing a flow statistical analysis strategy or a volume regression analysis strategy. The traffic statistics and analysis strategy includes: Calculate the net makeup gas flow rate The arithmetic mean of the values ​​during the steady-state detection phase is used as the leakage rate. The volume regression analysis strategy includes: The net replenishment gas flow rate Time integration is performed during the steady-state detection phase to construct a cumulative leakage volume curve. : ， In the formula, This is the start time of the steady-state detection phase. For time integration variables; The cumulative leakage volume curve was then analyzed using the least squares method. Perform linear regression fitting, calculate the slope of the fitted line, and determine the slope as the leakage rate.

7. The method according to claim 6, characterized in that, Before determining the seal integrity of the sealed container under test, the method further includes a process statistical controlled state monitoring step: Construct a statistical process control model based on cumulative sums and set the initial cumulative statistic. and the net replenishment gas flow rate during the steady-state detection phase. Discretize into data sequence Perform recursive calculations to generate real-time state statistics. : ， In the formula, This represents the net make-up gas flow rate at the current sampling time; This is the steady-state baseline mean of the current data sequence, used to characterize the current center of the leakage level; This is a preset drift tolerance parameter used to filter background white noise within the allowable range; Real-time monitoring of the real-time status statistics ,when Exceeding the preset judgment threshold At that time, it was determined that the current constant pressure detection process was in a state of statistical out-of-control. In response to the aforementioned statistical runaway state, the system identifies sudden external disturbances or system mechanical instability that are not related to leakage during the testing process and triggers a process anomaly alarm signal to mark the current test data as invalid, in order to prevent environmental interference from being mistaken for product leakage.

8. The method according to claim 7, characterized in that, The step of comparing the leakage rate with a preset integrity standard to determine the seal integrity of the sealed container under test includes: Obtain the preset target leakage rate benchmark And select the net make-up gas flow rate data sequence during the steady-state detection phase. The standard deviation of the system's inherent noise is obtained by calculating its statistical distribution dispersion. : ， In the formula, The total number of data points. This is the arithmetic mean of the net replenishment airflow during this stage; Based on the principle of statistical normal distribution, an adaptive decision threshold that can dynamically adapt to the current test signal-to-noise ratio is constructed. : ， In the formula, The weighting coefficients related to the preset confidence level, item This constitutes a safety confidence margin for suppressing random noise interference. Leakage rate With the adaptive judgment threshold Comparison: like If the leakage level of the sealed container under test does not deviate significantly from the target leakage rate benchmark in a statistically significant manner, the seal integrity is confirmed to be qualified. like If the leak is statistically significant, the sealed container under test is determined to have a defect, and the seal integrity is deemed unqualified.

9. A pressure decay testing system based on gas elastic compensation, characterized in that, The system includes: The pre-test calibration unit is used to connect the sealed container under test to the test chamber equipped with a gas elasticity compensation module. By applying a preset pressure test signal to the sealed container under test, it obtains pressure response data and volume change data in response to the pressure test signal, so as to calculate and obtain the elastic characteristic parameters of the sealed container under test. The pressure building and initialization unit is used to inject gas into the test chamber and the sealed container under test until the pressure inside the chamber reaches the preset target test pressure and enters the constant pressure detection stage. A constant pressure feedback compensation unit is used to perform pressure feedback control using the gas elastic compensation module during the constant pressure detection stage. It adjusts the compensation amount in real time to maintain the pressure in the test chamber at the target test pressure and records the total compensation flow rate data required to maintain the target test pressure in real time. The elastic model calculation unit is used to calculate the theoretical elastic compensation flow rate caused by the elastic deformation of the sealed container under test under the current pressure environment, based on the elastic characteristic parameters and real-time monitored pressure data. The net flow analysis unit is used to subtract the theoretical elastic compensation flow from the total compensation flow data in real time to obtain the net gas supply flow that reflects the actual leakage of the sealed container under test. The integrity assessment and determination unit is used to determine the leakage rate based on the change characteristics of the net make-up air flow rate over time, and compare the leakage rate with a preset integrity standard to determine the sealing integrity of the sealed container under test.

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