Method, system, electronic equipment and medium for containment sealing test

Abstract

The present invention provides a method, system, electronic device and storage medium for testing the sealing performance of a containment, which obtain the temperature, humidity and pressure inside the containment at each moment; calculate the dry air mass at each moment to obtain a discrete mass function M(i); fit M(i) to obtain a function M(t) through a preset nonlinear calculation model algorithm, and obtain a real-time leakage rate function L(t) by taking the derivative of M(t); or, take two adjacent acquisition moments as a differential segment, differentiate M(i), obtain the leakage rate of each differential segment, obtain the discrete Li in each acquisition period, and obtain the real-time leakage rate function L(t) by fitting Li through a preset calculation model algorithm; obtain the relationship between pressure and time P(t), and calculate the containment leakage rate under a specified pressure according to L(t) and P(t). The disclosed technical solution obtains a non-constant leakage rate, clarifies the relationship between the leakage rate and pressure, and improves the test accuracy.

Description

Technical Field

[0001] The present invention relates to the field of nuclear power safety technology, and in particular to a method for testing the sealing performance of a containment shell, a system for testing the sealing performance of a containment shell, an electronic device and a computer-readable storage medium. Background Art

[0002] The containment is the last physical barrier to the safety of nuclear power plants, and the containment sealing is an important indicator for measuring the quality of containment installation. At present, the absolute pressure decay method (also known as the "pressure drop method") is the main method used in domestic and foreign tests. The international containment leakage rate test standards are mainly based on the French RCC-G88 and the American ANSI / ANS-56.8-2002, and the domestic containment leakage rate test is carried out in accordance with NB / T20018-2010.

[0003] In domestic and international standards and in the sealing tests of nuclear power plants, the dry air mass change method is used to calculate the leakage rate of the containment. However, in the traditional calculation model given in the past, the calculated leakage rate is a constant value and will not decrease with the decrease in pressure, which is inconsistent with the actual situation. Although in general, for the inner containment with very small leakage, the influence of pressure is ignored as an assumption. However, in the case of large leakage, the pressure inside the containment will drop rapidly with the leakage, and the obvious pressure drop will inevitably have a greater impact on the leakage rate. Therefore, the current calculation model regards the leakage of the containment as a linear process, which is not suitable for places with high leakage rates and has great limitations in engineering applications. Summary of the invention

[0004] The technical problem to be solved by the present invention is to address the above-mentioned deficiencies in the prior art and to provide a method for testing the sealing properties of a containment shell, a system for testing the sealing properties of a containment shell, an electronic device and a computer-readable storage medium. A nonlinear fitting method is used to obtain the leakage rate that varies with time, and the relationship between the leakage rate and the pressure is clarified to obtain the containment shell leakage rate under a precise pressure platform. The test time can be shortened, the test accuracy can be improved, and the negative effects of factors such as external environmental interference and internal environmental fluctuations that affect the calculation of the containment shell leakage rate can be effectively reduced, thereby improving the consistency of the fitted data with the theoretical trend.

[0005] In a first aspect, the present disclosure provides a method for testing the sealing performance of a containment vessel, the method comprising:

[0006] Obtain the temperature, humidity and pressure inside the containment shell at each moment in the containment shell sealing test source acquisition data;

[0007] The mass of dry air gas in the shell at each moment is calculated according to the temperature, humidity and pressure in the shell, and the discrete mass function M(i) is obtained;

[0008] M(i) is fitted by a preset nonlinear calculation model algorithm to obtain a mass-time curve function M(t), and the fitted mass-time curve function M(t) is derived to obtain a real-time leakage rate function L(t); or,

[0009] Take two adjacent acquisition moments as a differential segment, differentiate the dry air gas mass function M(i), calculate the leakage rate of each differential segment, and obtain the discrete leakage rate function Li in each acquisition period. Fit Li through the preset calculation model algorithm to obtain the real-time leakage rate function L(t);

[0010] The relationship between pressure / pressure difference and time P(t) is obtained, and the containment leakage rate under the specified pressure is calculated according to the real-time leakage rate function L(t) and the relationship between pressure / pressure difference and time P(t).

[0011] Further, the nonlinear calculation model algorithm includes an exponential fitting differential leakage rate method;

[0012] The method of fitting M(i) by a preset nonlinear calculation model algorithm to obtain a mass-time curve function M(t), and deriving the fitted mass-time curve function M(t) to obtain a real-time leakage rate function L(t) includes:

[0013] The n sets of source acquisition data to be analyzed (M i , t i ) array, and exponential fitting is performed on it to obtain a continuous "mass-time" function M(t), where the fitting target calculation model used is: M(t) = a·e bt +c;

[0014] The “mass leakage rate-time” function L(t) is obtained by taking a differential derivative of M(t) and adjusting the unit data of the mass leakage rate.

[0015] Further, the nonlinear calculation model algorithm includes a power function fitting differential leakage rate method;

[0016] The method of fitting M(i) by a preset nonlinear calculation model algorithm to obtain a mass-time curve function M(t), and deriving the fitted mass-time curve function M(t) to obtain a real-time leakage rate function L(t) includes:

[0017] The n sets of source acquisition data to be analyzed (M i , t i ) array, and a power function is fitted to it to obtain a continuous "mass-time" function M(t), where the fitting target calculation model used is: M(t) = a·t b +c;

[0018] The “mass leakage rate-time” function L(t) is obtained by taking a differential derivative of M(t) and adjusting the unit data of the mass leakage rate.

[0019] Furthermore, the nonlinear calculation model algorithm includes a point-by-point differential fitting leakage rate method;

[0020] The method of taking two adjacent acquisition moments as a differential segment, differentiating the dry air gas mass function M(i), calculating the leakage rate of each differential segment, obtaining the discrete leakage rate function Li in each acquisition period, and fitting Li through a preset calculation model algorithm to obtain the real-time leakage rate function L(t), includes:

[0021] Collect data for n groups of sources to be analyzed (M i , t i ) array, taking two adjacent acquisition moments as a differential segment, and differentiating the dry air gas mass to obtain n-1 sets of discrete

[0022] Calculate the leakage rate of each micro-segment and obtain the discrete leakage rate function L in each acquisition period i , The unit is % of the gas weight in the containment vessel / day;

[0023] The n-1 discrete L i Combined with the middle moments of n-1 groups of acquisition periods, form n-1 groups of function point data Perform straight-line fitting, exponential fitting or power function fitting to obtain a continuous “mass leakage rate-time” function L(t).

[0024] Furthermore, the relationship P(t) between pressure / pressure difference and time is obtained, and the containment leakage rate under the specified pressure is calculated according to the real-time leakage rate function L(t) and the relationship P(t) between pressure / pressure difference and time, including:

[0025] Combine the shell pressure / shell internal and external pressure difference P in n sets of collected data with the collection time of n sets of collected data to form n sets of function point data, and perform linear fitting, exponential fitting or power function fitting to obtain a continuous "pressure / pressure difference-time" function P(t);

[0026] The specified pressure / pressure difference P to be calculated is selected D Substitute P(t) to get the corresponding collection time t D ;

[0027] The calculated pressure / pressure difference P D The corresponding acquisition time t D Substitute L(t) to obtain pressure / pressure difference P D The corresponding containment leakage rate L D;

[0028] or,

[0029] After obtaining the continuous "pressure / pressure difference-time" function P(t), substitute the function P(t) into L(t) to obtain the "leakage rate-pressure / pressure difference" function L(P);

[0030] The specified pressure / pressure difference P to be calculated is selected D Substitute L(P) to obtain the containment leakage rate L D ;

[0031] or,

[0032] According to the "mass leakage rate-time" function L(t), the discrete series (ti, Li) of all sampling moments are obtained, and ti in the (ti, Li) data is replaced with Pi to obtain the discrete series (Pi, Li);

[0033] The discrete series (Pi, Li) is fitted with a straight line, an exponential function or a power function to obtain the "leakage rate-pressure / pressure difference" function L(P) in which the leakage rate varies with the pressure inside the shell;

[0034] The specified pressure / pressure difference P to be calculated is selected D Substitute L(P) to obtain the containment leakage rate L D .

[0035] Furthermore, the method further comprises:

[0036] Calculate the standard deviation of the leakage rate function L(t) and the containment leakage rate L at the specified pressure. D The standard deviation of

[0037] According to the standard deviation of the leakage rate function L(t) and the containment leakage rate L at the specified pressure D The confidence level leakage rate interval of the containment leakage rate is obtained by combining the standard deviation of

[0038] Among them, the standard deviation σ of the leakage rate function L(t) L1 Obtained by the following formula:

[0039]

[0040] Among them, σ M1 is the standard deviation of the fitting function M(t), M is the pressure inside the shell reaching the specified calculation pressure P D The corresponding dry air mass in the shell at ;

[0041] The containment leakage rate L is obtained under a specified pressure. D The standard deviation of

[0042] If L D Calculated by the function P(t), the containment leakage rate L is obtained at the specified pressure: D The lower limit of error σ L2min and the upper limit σ L2max They are:

[0043] σ L2min =L(pi-σ P2 )-L(Pi)

[0044] σ L2max =L(pi+σ P2 )-L(Pi)

[0045] Among them, σ P2 is the pressure standard deviation of the fitting function P(t);

[0046] Then the N% confidence level leakage rate interval of the containment leakage rate is:

[0047] [L D -k(σ L1 -σ L2min ), L D +k(σ L1 +σ L2max )];

[0048] If L D Calculated by discrete series (Pi, Li), the containment leakage rate L is obtained under the specified pressure. D The standard deviation of is the standard deviation σ brought by the function L(P) L2 ;

[0049] Then the N% confidence level leakage rate interval of the containment leakage rate is:

[0050] [L D -k(σ L1 +σ L2 ), L D +k(σ L1 +σ L2 )]

[0051] Where k is the N% confidence level coefficient.

[0052] In a second aspect, the present disclosure provides a system for testing containment sealing properties, the system comprising:

[0053] An acquisition module, which is configured to acquire the temperature, humidity and pressure inside the containment shell at each moment in the containment shell sealing test source acquisition data;

[0054] A first calculation module is configured to calculate the mass of dry air gas in the shell at each moment according to the temperature, humidity and pressure in the shell to obtain a discrete mass function M(i);

[0055] A fitting module is configured to fit M(i) by a preset nonlinear calculation model algorithm to obtain a mass-time curve function M(t), and to derive the fitted mass-time curve function M(t) to obtain a real-time leakage rate function L(t); or,

[0056] It is set to take two adjacent acquisition moments as a differential segment, differentiate the dry air gas mass function M(i), calculate the leakage rate of each differential segment, obtain the discrete leakage rate function Li in each acquisition period, and fit Li through the preset calculation model algorithm to obtain the real-time leakage rate function L(t);

[0057] The second calculation module is configured to obtain the relationship between pressure / pressure difference and time P(t), and calculate the containment leakage rate under the specified pressure according to the real-time leakage rate function L(t) and the relationship between pressure / pressure difference and time P(t).

[0058] Further, the nonlinear calculation model algorithm includes an exponential fitting differential leakage rate method;

[0059] The fitting module is specifically configured as follows:

[0060] The n sets of source acquisition data to be analyzed (M i , t i ) array, and exponential fitting is performed on it to obtain a continuous "mass-time" function M(t), where the fitting target calculation model used is: M(t) = a·e bt +c;

[0061] The “mass leakage rate-time” function L(t) is obtained by taking a differential derivative of M(t) and adjusting the unit data of the mass leakage rate.

[0062] In a third aspect, the present disclosure provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes a method for a containment sealing test as described in any one of the first aspects.

[0063] In a fourth aspect, the present disclosure provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for testing the sealing properties of a containment vessel as described in any one of the first aspects is implemented.

[0064] Beneficial effects:

[0065] The method for testing the sealing performance of a containment shell, the system for testing the sealing performance of a containment shell, the electronic device and the computer-readable storage medium provided by the present invention have high consistency between the inner shell mass curve after nonlinear fitting and the inner shell mass calculated by actual measurement and small calculation error; the relationship between leakage rate and pressure is clarified, the containment leakage rate under a precise pressure platform is obtained, and the number of tests for the sealing performance of the outer containment shell is reduced, which can shorten the test time, improve the test accuracy and reduce the test cost; at the same time, the negative effects of factors such as external environmental interference and internal environmental fluctuations on the calculation of the containment leakage rate can be effectively reduced, and the consistency of various data after fitting with the theoretical trend can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 A schematic flow chart of a method for testing containment sealing properties provided in Embodiment 1 of the present invention;

[0067] Figure 2 A schematic diagram of calculating the containment leakage rate by three new nonlinear calculation methods provided in the second embodiment of the present invention;

[0068] Figure 3 A schematic diagram of a method for obtaining the “pressure / pressure difference-time” function L(P) provided in Embodiment 2 of the present invention;

[0069] Figure 4 A data diagram of a discrete mass function M(i) in a point-by-point differential fitting leakage rate calculation model provided in the second embodiment of the present invention;

[0070] Figure 5 A data graph of a continuous straight line function L(t) fitted in a calculation model of a point-by-point differential fitting leakage rate method provided in the second embodiment of the present invention;

[0071] Figure 6 A data graph of a continuous straight line function P(t) fitted in a calculation model of a point-by-point differential fitting leakage rate method provided in the second embodiment of the present invention;

[0072] Figure 7 A data graph of a function L(P) obtained by substituting the function P(t) into L(t) in a calculation model of a point-by-point differential fitting leakage rate method provided in the second embodiment of the present invention;

[0073] Figure 8 A data graph of a straight line function L(P) obtained by fitting discrete (Pi, Li) data points in a point-by-point differential fitting leakage rate calculation model provided in the second embodiment of the present invention;

[0074] Fig. 9 A data graph of an exponential function M(t) fitted in a calculation model of an exponential fitting differential leakage rate method provided in the second embodiment of the present invention;

[0075] Fig.10 A data graph of an exponential function L(t) obtained in a calculation model of an exponential fitting differential leakage rate method provided in the second embodiment of the present invention;

[0076] Fig.11 A data diagram of the exponential function P(t) fitted in the calculation model of the exponential fitting differential leakage rate method provided in the second embodiment of the present invention

[0077] Fig.12 A data graph of a function L(P) obtained by substituting the function P(t) into L(t) in an exponential fitting differential leakage rate calculation model provided in the second embodiment of the present invention;

[0078] Fig.13 A data graph of an exponential function L(P) obtained by fitting discrete (Pi, Li) data points in an exponential fitting differential leakage rate calculation model provided in the second embodiment of the present invention;

[0079] Fig.14 A data graph of a power function M(t) fitted in a power function fitting differential leakage rate method calculation model provided in the second embodiment of the present invention;

[0080] Fig.15 A data graph of a power function L(t) obtained in a power function fitting differential leakage rate method calculation model provided in the second embodiment of the present invention;

[0081] Fig.16 A data diagram of a power function P(t) obtained by fitting in a power function fitting differential leakage rate calculation model provided in the second embodiment of the present invention

[0082] Fig.17 A data graph of function L(P) obtained by substituting function P(t) into L(t) in a power function fitting differential leakage rate calculation model provided in the second embodiment of the present invention;

[0083] Fig.18 A data graph of a power function L(P) obtained by fitting discrete (Pi, Li) data points in a power function fitting differential leakage rate calculation model provided in the second embodiment of the present invention;

[0084] Fig.19 This is an architecture diagram of a containment sealing test system provided in Embodiment 3 of the present invention;

[0085] Fig. 20 This is an architecture diagram of an electronic device provided in Embodiment 4 of the present disclosure. DETAILED DESCRIPTION

[0086] In order to enable those skilled in the art to better understand the technical solution of the present disclosure, the present disclosure is further described in detail below in conjunction with the drawings and embodiments. It should be understood that the specific embodiments and drawings described herein are only used to explain the present invention, rather than to limit the present invention.

[0087] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence; and, in the absence of conflict, the embodiments in the present disclosure and the features in the embodiments can be arbitrarily combined with each other.

[0088] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments and are not intended to limit the present disclosure. The singular forms of "a", "said" and "the" used in the embodiments of the present disclosure and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings.

[0089] In the subsequent description, the suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present disclosure, and have no specific meanings. Therefore, "module", "component" or "unit" can be used in a mixed manner.

[0090] In domestic and international standards and in the sealing tests of nuclear power plants, the dry air mass change method is used to calculate the leakage rate of the containment. The calculation process of the main leakage rate is summarized as follows: The calculation process of the main leakage rate is summarized as follows: Obtain the parameters inside the shell and calculate the gas mass inside the shell. Perform a linear fit on the gas mass inside the shell, and the fitting calculation model is: y=ax+b. Among them: y is the gas mass inside the shell, x is the relative time after the start of the measurement test, a is the slope of the fitting line, and b is the intercept of the fitting line. The value of the main leakage rate is L=-2400×a / b. It can be seen that in the traditional calculation model, the calculated leakage rate is a constant value, which will not decrease with the decrease of pressure. Treating the leakage of the containment as a linear process is not suitable for places with high leakage rates, and has great limitations in engineering applications.

[0091] The following specific embodiments are used to describe in detail the technical solution of the present disclosure and how the technical solution of the present disclosure solves the above problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0092] Figure 1 A flow chart of a method for testing the sealing performance of a containment vessel provided in the first embodiment of the present disclosure is shown in FIG. Figure 1 As shown, the method includes:

[0093] Step S101: obtaining the temperature, humidity and pressure inside the containment shell at each moment in the containment shell sealing test source acquisition data;

[0094] Step S102: Calculate the mass of dry air gas in the shell at each moment according to the temperature, humidity and pressure in the shell to obtain a discrete mass function M(i);

[0095] Step S103: fitting M(i) by a preset nonlinear calculation model algorithm to obtain a mass-time curve function M(t), and taking the derivative of the fitted mass-time curve function M(t) to obtain a real-time leakage rate function L(t); or,

[0096] Step S104: taking two adjacent acquisition moments as a differential segment, differentiating the dry air gas mass function M(i), calculating the leakage rate of each differential segment, obtaining the discrete leakage rate function Li in each acquisition period, and fitting Li through a preset calculation model algorithm to obtain the real-time leakage rate function L(t);

[0097] Step S105: Obtain the relationship P(t) between pressure / pressure difference and time, and calculate the containment leakage rate at a specified pressure according to the real-time leakage rate function L(t) and the relationship P(t) between pressure / pressure difference and time.

[0098] When conducting the containment sealing test, including the inner containment sealing test and the outer containment sealing test, the sealing test process can adopt the existing containment sealing test method. After obtaining the source acquisition data, including the temperature, humidity and pressure inside the shell at each moment, the discrete mass function M(i) at each moment is obtained according to the following formula.

[0099]

[0100] Among them, M i is the mass of dry air in the containment, V is the volume of the containment, P vi is the partial pressure of water vapor, P i is the total absolute pressure in the containment, R is the molar gas constant, T i is the average absolute temperature of dry air in the containment.

[0101] When calculating the leakage rate, it can be done in a variety of ways. M(i) can be fitted with a preset nonlinear calculation model algorithm to obtain a mass-time curve function M(t), and then the function M(t) can be differentiated to obtain the real-time leakage rate function L(t); the gas mass series M(i) can also be differentiated in each micro-segment to obtain the leakage rate of each micro-segment, and discrete "mass leakage rate-time" data points Li are obtained, and the continuous "mass leakage rate-time" function L(t) is fitted through these data points; when Li is fitted with a preset calculation model algorithm to obtain the real-time leakage rate function L(t), a straight line fitting can be used. Although L(t) is a straight line fitting, L(t) is not a constant, and therefore, it is still nonlinear relative to M(i).

[0102] Then, the relationship between pressure / pressure difference and time P(t) is obtained, and the containment leakage rate under the specified pressure is calculated according to the real-time leakage rate function L(t) and the relationship between pressure / pressure difference and time P(t). The calculation process can first obtain the "mass leakage rate-pressure" function L(P) according to the real-time leakage rate function L(t) and the relationship between pressure / pressure difference and time P(t). When conducting the test, if the test is for the inner containment, P takes the pressure inside the shell, and if the test is for the outer containment, P takes the pressure difference between the inside and outside of the shell. After inputting the specified pressure, the leakage rate under the specified pressure is obtained according to the function L(P). Alternatively, the time at which the specified pressure is obtained according to P(t), and the leakage rate under the specified pressure is obtained according to the time at which the pressure is and the "mass leakage rate-time" function L(t).

[0103] The disclosed embodiment adopts nonlinear fitting of the curve of the change of the mass inside the shell with time, and the obtained curve function has higher consistency with the mass inside the shell actually measured and calculated, and according to the relationship between pressure and time, the relationship between leakage rate and pressure is clarified, and the containment leakage rate under a precise pressure platform is obtained, which solves the problem that the traditional straight line fitting method ignores the influence of pressure on the leakage rate; and can reduce the number of tests of the sealing performance of the outer containment, shorten the test time, improve the test accuracy, and reduce the test cost; at the same time, it can effectively reduce the negative effects of factors such as external environmental interference and internal environmental fluctuations on the calculation of the containment leakage rate, and improve the consistency of various data after fitting with the theoretical trend.

[0104] Further, the nonlinear calculation model algorithm includes an exponential fitting differential leakage rate method;

[0105] The method of fitting M(i) by a preset nonlinear calculation model algorithm to obtain a mass-time curve function M(t), and deriving the fitted mass-time curve function M(t) to obtain a real-time leakage rate function L(t) includes:

[0106] The n sets of source acquisition data to be analyzed (M i , t i ) array, and exponential fitting is performed on it to obtain a continuous "mass-time" function M(t), where the fitting target calculation model used is: M(t) = a·e bt +c;

[0107] The “mass leakage rate-time” function L(t) is obtained by taking a differential derivative of M(t) and adjusting the unit data of the mass leakage rate.

[0108] The obtained discrete mass function M(i) is subjected to the exponential fitting differential leakage rate method, and the calculation model M(t) = a·e bt +c, and get the mass-time curve function M(t) (that is, determine the fitting parameters a, b, c according to the actual data points), then differentiate M(t), and adjust the mass leakage rate unit data to get the "mass leakage rate-time" function L(t), L(t) = 2400*a·b·e bt / (a·e bt +c); Leakage rate unit: % of gas weight in containment vessel / day; Leakage direction: positive direction indicates leakage from inside the containment vessel to outside the containment vessel, and negative direction indicates leakage from outside the containment vessel to inside the containment vessel.

[0109] The variation trend of the gas mass in the shell obtained by the exponential fitting function is highly consistent with the discrete mass in the shell, and the variation trend of the leakage rate with time and pressure difference is highly consistent with the measured data and theoretical trend.

[0110] Further, the nonlinear calculation model algorithm includes a power function fitting differential leakage rate method;

[0111] The method of fitting M(i) by a preset nonlinear calculation model algorithm to obtain a mass-time curve function M(t), and deriving the fitted mass-time curve function M(t) to obtain a real-time leakage rate function L(t) includes:

[0112] The n sets of source acquisition data to be analyzed (M i , t i ) array, and a power function is fitted to it to obtain a continuous "mass-time" function M(t), where the fitting target calculation model used is: M(t) = a·t b +c;

[0113] The “mass leakage rate-time” function L(t) is obtained by taking a differential derivative of M(t) and adjusting the unit data of the mass leakage rate.

[0114] The obtained discrete mass function M(i) is fitted by the differential leakage rate method using a power function, and the calculation model M(t) = a·t b+c, and get the mass-time curve function M(t) (that is, determine the fitting parameters a, b, c according to the actual data points), then differentiate M(t), and adjust the mass leakage rate unit data to get the "mass leakage rate-time" function L(t), L(t) = 2400*a·b·t b-1 / (a·t b +c).

[0115] When selecting a nonlinear calculation model algorithm, it can be determined based on the mass function M(i) data point graph obtained according to actual conditions, and the nonlinear calculation model algorithm that best fits the graph can be selected.

[0116] Furthermore, the nonlinear calculation model algorithm includes a point-by-point differential fitting leakage rate method;

[0117] The method of taking two adjacent acquisition moments as a differential segment, differentiating the dry air gas mass function M(i), calculating the leakage rate of each differential segment, obtaining the discrete leakage rate function Li in each acquisition period, and fitting Li through a preset calculation model algorithm to obtain the real-time leakage rate function L(t), includes:

[0118] Collect data for n groups of sources to be analyzed (M i , t i ) array, taking two adjacent acquisition moments as a differential segment, and differentiating the dry air gas mass to obtain n-1 sets of discrete

[0119] Calculate the leakage rate of each micro-segment and obtain the discrete leakage rate function L in each acquisition period i , The unit is % of the gas weight in the containment vessel / day;

[0120] The n-1 discrete L i Combined with the middle moments of n-1 groups of acquisition periods, form n-1 groups of function point data Perform straight-line fitting, exponential fitting or power function fitting to obtain a continuous “mass leakage rate-time” function L(t).

[0121] Collection period: the time interval between two adjacent collection times, there are n-1 groups of dt i =t i+1 -t i When linear fitting is used, L(t) is not a constant value but changes with time. Therefore, the entire leakage process determined by calculation is still nonlinear.

[0122] Furthermore, the relationship P(t) between pressure / pressure difference and time is obtained, and the containment leakage rate under the specified pressure is calculated according to the real-time leakage rate function L(t) and the relationship P(t) between pressure / pressure difference and time, including:

[0123] Combine the shell pressure / shell internal and external pressure difference P in n sets of collected data with the collection time of n sets of collected data to form n sets of function point data, and perform linear fitting, exponential fitting or power function fitting to obtain a continuous "pressure / pressure difference-time" function P(t);

[0124] The specified pressure / pressure difference P to be calculated is selected D Substitute P(t) to get the corresponding collection time t D ;

[0125] The calculated pressure / pressure difference P D The corresponding acquisition time t D Substitute L(t) to obtain pressure / pressure difference P D The corresponding containment leakage rate L D ;

[0126] or,

[0127] After obtaining the continuous "pressure / pressure difference-time" function P(t), substitute the function P(t) into L(t) to obtain the "leakage rate-pressure / pressure difference" function L(P);

[0128] The specified pressure / pressure difference P to be calculated is selected D Substitute L(P) to obtain the containment leakage rate L D ;

[0129] or,

[0130] According to the "mass leakage rate-time" function L(t), the discrete series (ti, Li) of all sampling moments are obtained, and ti in the (ti, Li) data is replaced with Pi to obtain the discrete series (Pi, Li);

[0131] The discrete series (Pi, Li) is fitted with a straight line, an exponential function or a power function to obtain the "leakage rate-pressure / pressure difference" function L(P) in which the leakage rate varies with the pressure inside the shell;

[0132] The specified pressure / pressure difference P to be calculated is selected D Substitute L(P) to obtain the containment leakage rate L D .

[0133] In the inner containment test, P is the pressure inside the shell, and in the outer containment test, P is the pressure difference between the inside and outside of the shell. The relationship between pressure and time, P(t), can be a fitted function or a series of discrete data points.

[0134] When the function L(P) is obtained through L(t) and P(t), it can be obtained in the following two ways:

[0135] Method 1: Perform linear fitting, exponential function fitting or power function fitting on (ti, Pi) to obtain the "pressure / pressure difference-time" function P(t), substitute P(t) into L(t) to obtain the nonlinear function L(P) of the leakage rate changing with the pressure inside the shell;

[0136] Linear fitting calculation model selection:

[0137] f(x)=a.x+b

[0138] Exponential fitting calculation model selection:

[0139] f(x)=a·e bx +c

[0140] Power function fitting calculation model selection:

[0141] f(x)=a·x b +c

[0142] Method 2: According to the "mass leakage rate-time" function L(t), the discrete series (ti, Li) of all sampling moments are obtained, and ti in the (ti, Li) data of all sampling moments is replaced by the corresponding Pi to obtain the discrete series (Pi, Li). The discrete series (Pi, Li) is fitted with a straight line, an exponential function or a power function to obtain the linear / nonlinear function L(P) of the leakage rate changing with the pressure inside the shell.

[0143] Linear fitting calculation model selection:

[0144] f(x)=a.x+b

[0145] Exponential fitting calculation model selection:

[0146] f(x)=ae bx +c

[0147] Power function fitting calculation model selection:

[0148] f(x)=a·x b +c

[0149] It should be noted that if the leakage rate obtained by the second method using straight-line fitting is a linear function that changes with the pressure inside the shell, the entire leakage process determined by this calculation is still nonlinear.

[0150] Three new nonlinear calculation models, point-by-point differential fitting leakage rate method, exponential fitting differential leakage rate method and power function fitting differential leakage rate method, are classified according to the "leakage rate-time" nonlinear function solution method. Each classified model has 6 branch algorithms to obtain the "leakage rate-pressure difference" function L(P). Therefore, the embodiment of the present disclosure actually includes 18 sets of containment leakage rate nonlinear calculation method combinations.

[0151] Through a variety of nonlinear calculation methods, the calculation of containment leakage rate under more actual conditions can be met, so that the most suitable method can be selected to obtain calculation results that are consistent with the actual situation.

[0152] The disclosed embodiment may also select a plurality of calculation methods for calculation and take an average value to reduce the error between the calculated value of the main leakage rate and the actual value, thereby improving the accuracy of the calculation result.

[0153] Furthermore, the method further comprises:

[0154] Calculate the standard deviation of the leakage rate function L(t) and the containment leakage rate L at the specified pressure. D The standard deviation of

[0155] According to the standard deviation of the leakage rate function L(t) and the containment leakage rate L at the specified pressure D The confidence level leakage rate interval of the containment leakage rate is obtained by combining the standard deviation of

[0156] Among them, the standard deviation σ of the leakage rate function L(t) L1 Obtained by the following formula:

[0157]

[0158] Among them, σ M1 is the standard deviation of the fitting function M(t), M is the pressure inside the shell reaching the specified calculation pressure P D The corresponding dry air mass in the shell at ;

[0159] The containment leakage rate L is obtained under a specified pressure. D The standard deviation of

[0160] If L D Calculated by the function P(t), the containment leakage rate L is obtained at the specified pressure: D The lower limit of error σ L2min and the upper limit σ L2max They are:

[0161] σ L2min =L(pi-σ P2 )-L(Pi)

[0162] σ L2max =L(pi+σ P2 )-L(Pi)

[0163] Among them, σ P2 is the pressure standard deviation of the fitting function P(t);

[0164] Then the N% confidence level leakage rate interval of the containment leakage rate is:

[0165] [L D -k(σ L1 -σ L2min ), L D +k(σ L1 +σ L2max )];

[0166] If L D Calculated by discrete series (Pi, Li), the containment leakage rate L is obtained under the specified pressure. D The standard deviation of is the standard deviation σ brought by the function L(P) L2 ;

[0167] Then the N% confidence level leakage rate interval of the containment leakage rate is:

[0168] [L D -k( L1 +σ L2 ), L D +k(σ L1 +σ L2 )]

[0169] Where k is the N% confidence level coefficient.

[0170] Since this embodiment performs two nonlinear function fitting calculations on the original data collected in the test, the standard deviation required for calculating the confidence interval in the process of calculating the containment leakage rate is formed by the combination of the effects brought by the two fittings.

[0171] Taking the acquisition system as a whole, the input is the data collected in each acquisition cycle, the method is calculation and analysis, and the output is the leakage rate. The output obtained from each analysis is a random sample obtained after including all possibilities of all elements in the input, and the confidence interval is calculated according to statistical laws. In the above calculation process, when N = 95, the coefficient k is taken as 1.96.

[0172] The disclosed embodiment also adopts nonlinear fitting to curve the change of the mass inside the shell with time, and the obtained curve function has higher consistency with the mass inside the shell actually measured and calculated, and according to the relationship between pressure and time, the relationship between leakage rate and pressure is clarified, and the containment leakage rate under a precise pressure platform is obtained, which solves the problem that the traditional straight line fitting method ignores the influence of pressure on the leakage rate; and can reduce the number of tests of the sealing performance of the outer containment, shorten the test time, improve the test accuracy, and reduce the test cost; at the same time, it can effectively reduce the negative effects of external environmental interference, internal environmental fluctuations and other factors on the calculation of the containment leakage rate, and improve the consistency of various data after fitting with the theoretical trend.

[0173] In order to make the purpose, technical solutions and advantages of the present disclosure more clear, Figure 2-Figure 9 As shown, the second embodiment of the present disclosure provides a method for testing the sealing performance of a containment vessel. The present disclosure further describes the method in detail; Figure 2 The containment leakage rate is calculated by three new nonlinear calculation methods, namely, point-by-point differential fitting leakage rate method, exponential fitting differential leakage rate method, and power function fitting differential leakage rate method; the method of obtaining the gas mass inside the shell is consistent with the traditional leakage rate measurement, but after obtaining the mass inside the shell at each moment, the method of obtaining the leakage rate at each moment by the mass inside the shell at each moment is different; Figure 3 As shown, the “pressure / pressure difference-time” function L(P) can be obtained in two ways:

[0174] Method 1: Perform linear fitting, exponential function fitting or power function fitting on (ti, Pi) to obtain the "pressure / pressure difference-time" function P(t), substitute P(t) into L(t) to obtain the nonlinear function L(P) of the leakage rate changing with the pressure inside the shell;

[0175] Linear fitting calculation model selection:

[0176] f(x)=a·x+b

[0177] Exponential fitting calculation model selection:

[0178] f(x)=a·e bx +c

[0179] Power function fitting calculation model selection:

[0180] f(x)=a·x b +c

[0181] Method 2: Replace ti in the (ti, Li) data at all sampling moments with Pi to obtain discrete (Pi, Li), and perform straight-line fitting, exponential function fitting or power function fitting to obtain the linear / nonlinear function L(P) of the leakage rate changing with the pressure inside the shell.

[0182] Linear fitting calculation model selection:

[0183] f(x)=a.x+b

[0184] Exponential fitting calculation model selection:

[0185] f(x)=a·e bx +c

[0186] Power function fitting calculation model selection:

[0187] f(x)=a·x b +c

[0188] It should be noted that if the leakage rate obtained by the second method using straight-line fitting is a linear function that changes with the pressure inside the shell, the entire leakage process determined by this calculation is still nonlinear.

[0189] It should be noted that the three new nonlinear calculation models are classified according to the solution method of the "leakage rate-time" nonlinear function. Each classified model has 6 branch algorithms to obtain the "leakage rate-pressure difference" function L(P), so it actually includes 18 sets of containment leakage rate nonlinear calculation method combinations.

[0190] This embodiment takes the original data record analysis of the outer containment leakage rate test of Unit 5 of a nuclear power plant as an example to illustrate the calculation process of the three calculation methods of the present invention after data measurement.

[0191] The calculation model and analysis steps of the point-by-point differential fitting leakage rate method are described as follows:

[0192] Step 1: According to the temperature, humidity and pressure in the shell collected from the experimental source data, the mass of dry air gas in the shell at each time is calculated to obtain the discrete mass function M(i); the discrete mass function M(i) is as follows: Figure 4 As shown,

[0193]

[0194] Step 2: For the n sets of collected data to be analyzed, two adjacent collection moments are taken as a differential segment, and the gas mass is differentiated to obtain n-1 sets of discrete (Unit: kg / h);

[0195] The preferred differential model is:

[0196] Step 3: Calculate the leakage rate of each micro-segment and obtain the discrete leakage rate function in each acquisition period

[0197] Leakage unit: % of gas weight in containment / day;

[0198] Leakage direction: positive direction indicates leakage from inside the shell to outside the shell, negative direction indicates leakage from outside the shell to inside the shell;

[0199] Collection period: the time interval between two adjacent collection times, there are n-1 groups in total, dt i =t i+1 -t i ;

[0200] Step 4: Discrete n-1 groups of L i Combined with the middle moments of n-1 groups of acquisition periods, form n-1 groups of function point data Perform linear fitting, exponential fitting or power function fitting to obtain a continuous "mass leakage rate-time" function L(t); use discrete "mass leakage rate-time" data points to fit the continuous "mass leakage rate-time" linear function L(t) as follows: Figure 5 As shown;

[0201] Step 5: Combine the shell pressure / shell internal and external pressure difference P in the n sets of collected data with the collection time of the n sets of collected data to form n sets of function point data, and perform linear fitting, exponential fitting or power function fitting to obtain a continuous "pressure / pressure difference-time" function P(t); use discrete "pressure difference-time" data points to fit the continuous "pressure difference-time" linear function P(t) as follows: Figure 6 shown.

[0202] Step 6: Select the pressure / pressure difference platform P to be calculated D Substitute P(t) to get the corresponding collection time t D .

[0203] Step 7: The calculated pressure / pressure difference platform P D The corresponding acquisition time t D Substitute L(t) to obtain the pressure / pressure difference platform P D The corresponding containment leakage rate L D .

[0204] Step 8: Alternatively to Step 6 and Step 7, you can substitute the function P(t) into L(t) to obtain the "leakage rate-pressure / pressure difference" function L(P). The obtained L(P) is as follows: Figure 7 As shown. The selected pressure / pressure difference platform P to be calculated D Substitute L(P) to obtain the containment leakage rate L D .

[0205] Step 9: Alternatively to Step 4-Step 8, replace ti in the (ti, Li) data at all sampling moments with Pi to obtain discrete (Pi, Li), and perform linear fitting, exponential function fitting or power function fitting to obtain the linear / nonlinear function L(P) of the leakage rate changing with the pressure inside the shell. Fit the discrete (Pi, Li) data points to the "leakage rate-pressure difference" linear function L(P) as follows: Figure 8 shown.

[0206] The calculation model and analysis steps of the exponential fitting differential leakage rate method are described as follows:

[0207] Step 1: According to the temperature, humidity and pressure in the shell collected from the experimental source data, the mass of dry air gas in the shell at each moment is calculated to obtain a discrete mass function M(i);

[0208]

[0209] Step 2: Collect n sets of data to be analyzed (M i , t i ) array, perform exponential fitting on it, and obtain a continuous “quality-time” function M(t);

[0210] The preferred fitting target calculation model is: M(t) = a·e bt +c; the discrete "mass-time" function M(i) is fitted with the continuous "mass-time" exponential function M(t) as follows Fig. 9 As shown;

[0211] Step 3: Differentiate M(t) and adjust the unit data of mass leakage rate to obtain the "mass leakage rate-time" function L(t); Differentiate the continuous "mass-time" function M(t) to obtain the "mass leakage rate-time" exponential function L(t) as follows: Fig.10 As shown;

[0212] Step 4: Combine the shell pressure / shell internal and external pressure difference P in the n sets of collected data with the collection time of the n sets of collected data to form n sets of function point data, and perform linear fitting, exponential fitting or power function fitting to obtain a continuous "pressure / pressure difference-time" function P(t);

[0213] Preferably, when the exponential fitting differential leakage rate method is used, the function P(t) is also fitted with an exponential function, which is more rigorous in theory. The continuous "pressure difference-time" exponential function P(t) is fitted using discrete pressure difference-time data points, such as Fig.11 As shown;

[0214] Step 5: Select the pressure / pressure difference platform P to be calculated D Substitute P(t) to get the corresponding collection time t D ;

[0215] Step 6: The calculated pressure / pressure difference platform P D The corresponding acquisition time t D Substitute L(t) to obtain the pressure / pressure difference platform P D The corresponding containment leakage rate L D ;

[0216] Step 7: Instead of Step 5 and Step 6, the function P(t) can be substituted into L(t) to obtain the "leakage rate-pressure / pressure difference" function L(P). The function P(t) can be substituted into L(t) to obtain the "leakage rate-pressure difference" function L(P) as follows: Fig.12 As shown; the selected pressure / pressure difference platform P to be calculated D Substitute L(P) to obtain the containment leakage rate L D ;

[0217] Step 8: Alternatively to Step 4-Step 7, replace ti in the (ti, Li) data at all sampling moments with Pi to obtain discrete (Pi, Li), and perform linear fitting, exponential function fitting or power function fitting to obtain the linear / nonlinear function L(P) of the leakage rate changing with the pressure inside the shell; fit the discrete (Pi, Li) data points to the "leakage rate-pressure difference" exponential function L(P) as follows: Fig.13 shown.

[0218] The calculation model and analysis steps of the power function fitting differential leakage rate method are described as follows:

[0219] Step 1: According to the temperature, humidity and pressure in the shell collected from the experimental source data, the mass of dry air gas in the shell at each moment is calculated to obtain a discrete mass function M(i);

[0220]

[0221] Step 2: Collect n sets of data to be analyzed (M i , t i ) array, and fit the power function to it to obtain the continuous "mass-time" function M(t);

[0222] The preferred fitting target calculation model is: M(t) = at b +c; discrete "mass-time" function M(i), fitting continuous "mass-time" power function M(t) as Fig.14 As shown;

[0223] Step 3: Differentiate M(t) and adjust the unit data of mass leakage rate to obtain the "mass leakage rate-time" function L(t); Differentiate the continuous "mass-time" function M(t) to obtain the "mass leakage rate-time" function L(t) as follows: Fig.15 As shown;

[0224] Step 4: Combine the shell pressure / shell internal and external pressure difference P in the n sets of collected data with the collection time of the n sets of collected data to form n sets of function point data, and perform linear fitting, exponential fitting or power function fitting to obtain a continuous "pressure / pressure difference-time" function P(t);

[0225] Preferably, when the power function is used to fit the differential leakage rate method, the function P(t) is also fitted with a power function, which is more rigorous in theory; discrete pressure difference-time data points are used to fit the continuous "pressure difference-time" power function P(t) as follows: Fig.16 shown.

[0226] Step 5: Select the pressure / pressure difference platform P to be calculated D Substitute P(t) to get the corresponding collection time t D ;

[0227] Step 6: The calculated pressure / pressure difference platform P D The corresponding acquisition time t D Substitute L(t) to obtain the pressure / pressure difference platform P D The corresponding containment leakage rate L D ;

[0228] Step 7: Instead of Step 5 and Step 6, the function P(t) can be substituted into L(t) to obtain the "leakage rate-pressure / pressure difference" function L(P). The obtained L(P) is as follows: Fig.17 As shown; the selected pressure / pressure difference platform P to be calculated D Substitute L(P) to obtain the containment leakage rate L D ;

[0229] Step 8: Alternatively to Step 4-Step 7, replace ti in the (ti, Li) data at all sampling moments with Pi to obtain discrete (Pi, Li), and perform linear fitting, exponential function fitting or power function fitting to obtain the linear / nonlinear function L(P) of the leakage rate changing with the pressure inside the shell; fit the discrete (Pi, Li) data points to the "leakage rate-pressure difference" power function L(P) as follows: Fig.18 shown.

[0230] Calculation of confidence interval:

[0231] Since each method performs two nonlinear function fitting calculations on the original data collected in the test, the standard deviation required for calculating the confidence interval of the containment leakage rate calculated in this embodiment is a combination of the effects brought about by the two fittings.

[0232] Taking the acquisition system as a whole, the input is the acquisition data of each acquisition cycle, the method is computational analysis, and the output is the leakage rate. The output obtained from each analysis is a random sample obtained after including all possibilities of all elements in the input, and the confidence interval is calculated according to statistical laws.

[0233] A brief description is as follows:

[0234] Part I: Standard deviation of the fitted function M(t).

[0235] The standard deviation σ of the fitting function M(t) M1 , then the standard deviation of the function L(t) is:

[0236]

[0237] M is the pressure inside the shell reaching the specified calculation pressure P D The corresponding dry air mass in the shell at .

[0238] Part 2: According to different ways of obtaining the function L(P), it can be divided into two cases.

[0239] 1. Use method 1: perform linear fitting, exponential function fitting or power function fitting on (ti, Pi) to obtain the "pressure / pressure difference-time" function P(t), substitute P(t) into L(t) to obtain the nonlinear function L(P) of leakage rate changing with the pressure inside the shell.

[0240] The pressure standard deviation σ brought by the fitting function P(t) P2 , then the lower and upper limits of the error brought by the function L(P) are:

[0241] σ L2min =L(pi-σ P2 )-L(Pi)

[0242] σ L2max =L(pi+σ P2 )-L(Pi)

[0243] 2. Use method 2: Replace ti in the (ti, Li) data at all sampling moments with Pi to obtain discrete (Pi, Li), and perform linear fitting, exponential function fitting or power function fitting to obtain the linear function L(P) of the leakage rate changing with the pressure inside the shell.

[0244] The standard deviation of the function L(P) is σ L2 .

[0245] In summary, if the above method 1 is adopted, the N% confidence level leakage rate interval is:

[0246] [L D-k(σ L1 -σ L2min ), L D +k(σ L1 +σ L2max )]

[0247] If the above method 2 is adopted, the N% confidence level leakage rate interval is:

[0248] [L D -k(σ L1 +σ L2 ), L D +k(σ L1 +σ L2 )]

[0249] Where k is the N% confidence level coefficient. When N=95, the coefficient k is 1.96.

[0250] Fig.19 This is a system architecture diagram for a containment sealing test provided in Embodiment 3 of the present disclosure, such as Fig.19 As shown, the system comprises:

[0251] An acquisition module 11 is configured to acquire the temperature, humidity and pressure inside the containment shell at each moment in the containment shell sealing test source acquisition data;

[0252] A first calculation module 12, which is configured to calculate the mass of dry air gas in the shell at each moment according to the temperature, humidity and pressure in the shell, and obtain a discrete mass function M(i);

[0253] A fitting module 13 is configured to fit M(i) by a preset nonlinear calculation model algorithm to obtain a mass-time curve function M(t), and to derive the fitted mass-time curve function M(t) to obtain a real-time leakage rate function L(t); or,

[0254] It is set to take two adjacent acquisition moments as a differential segment, differentiate the dry air gas mass function M(i), calculate the leakage rate of each differential segment, obtain the discrete leakage rate function Li in each acquisition period, and fit Li through the preset calculation model algorithm to obtain the real-time leakage rate function L(t);

[0255] The second calculation module 14 is configured to obtain the relationship between pressure / pressure difference and time P(t), and calculate the containment leakage rate at a specified pressure according to the real-time leakage rate function L(t) and the relationship between pressure / pressure difference and time P(t).

[0256] Further, the nonlinear calculation model algorithm includes an exponential fitting differential leakage rate method;

[0257] The fitting module 13 is specifically configured as follows:

[0258] The n sets of source acquisition data to be analyzed (M i , t i ) array, and exponential fitting is performed on it to obtain a continuous "mass-time" function M(t), where the fitting target calculation model used is: M(t) = a·e bt +c;

[0259] The “mass leakage rate-time” function L(t) is obtained by taking a differential derivative of M(t) and adjusting the unit data of the mass leakage rate.

[0260] Further, the nonlinear calculation model algorithm includes a power function fitting differential leakage rate method;

[0261] The fitting module 13 is specifically configured as follows:

[0262] The n sets of source acquisition data to be analyzed (M i , t i ) array, and a power function is fitted to it to obtain a continuous "mass-time" function M(t), where the fitting target calculation model used is: M(t) = a·t b +c;

[0263] The “mass leakage rate-time” function L(t) is obtained by taking a differential derivative of M(t) and adjusting the unit data of the mass leakage rate.

[0264] Furthermore, the nonlinear calculation model algorithm includes a point-by-point differential fitting leakage rate method;

[0265] The fitting module 13 is specifically configured as follows:

[0266] Collect data for n groups of sources to be analyzed (M i , t i ) array, taking two adjacent acquisition moments as a differential segment, and differentiating the dry air gas mass to obtain n-1 sets of discrete

[0267] Calculate the leakage rate of each micro-segment and obtain the discrete leakage rate function L in each acquisition period i , The unit is % of the gas weight in the containment vessel / day;

[0268] The n-1 discrete L i Combined with the middle moments of n-1 groups of acquisition periods, form n-1 groups of function point data Perform straight-line fitting, exponential fitting or power function fitting to obtain a continuous “mass leakage rate-time” function L(t).

[0269] Furthermore, the second calculation module 14 is specifically configured as follows:

[0270] Combine the shell pressure / shell internal and external pressure difference P in n sets of collected data with the collection time of n sets of collected data to form n sets of function point data, and perform linear fitting, exponential fitting or power function fitting to obtain a continuous "pressure / pressure difference-time" function P(t);

[0271] The specified pressure / pressure difference P to be calculated is selected D Substitute P(t) to get the corresponding collection time t D ;

[0272] The calculated pressure / pressure difference P D The corresponding acquisition time t D Substitute L(t) to obtain pressure / pressure difference P D The corresponding containment leakage rate L D ;

[0273] or,

[0274] After obtaining the continuous "pressure / pressure difference-time" function P(t), substitute the function P(t) into L(t) to obtain the "leakage rate-pressure / pressure difference" function L(P);

[0275] The specified pressure / pressure difference P to be calculated is selected D Substitute L(P) to obtain the containment leakage rate L D ;

[0276] or,

[0277] According to the "mass leakage rate-time" function L(t), the discrete series (ti, Li) of all sampling moments are obtained, and ti in the (ti, Li) data is replaced with Pi to obtain the discrete series (Pi, Li);

[0278] The discrete series (Pi, Li) is fitted with a straight line, an exponential function or a power function to obtain the "leakage rate-pressure / pressure difference" function L(P) in which the leakage rate varies with the pressure inside the shell;

[0279] The specified pressure / pressure difference P to be calculated is selected D Substitute L(P) to obtain the containment leakage rate L D .

[0280] Furthermore, the system further comprises a third calculation module 15,

[0281] The third calculation module 15 is configured to respectively calculate the standard deviation of the leakage rate function L(t) and the containment leakage rate L at a specified pressure. D The standard deviation of

[0282] According to the standard deviation of the leakage rate function L(t) and the containment leakage rate L at the specified pressure D The confidence level leakage rate interval of the containment leakage rate is obtained by combining the standard deviation of

[0283] Among them, the standard deviation σ of the leakage rate function L(t) L1 Obtained by the following formula:

[0284]

[0285] Among them, σ M1 is the standard deviation of the fitting function M(t), M is the pressure inside the shell reaching the specified calculation pressure P D The corresponding dry air mass in the shell at ;

[0286] The containment leakage rate L is obtained under a specified pressure. D The standard deviation of

[0287] If L D Calculated by the function P(t), the containment leakage rate L is obtained at the specified pressure: D The lower limit of error σ L2min and the upper limit σ L2max They are:

[0288] σ L2min =L(pi-σ P2 )-L(Pi)

[0289] σ L2max =L(pi+σ P2 )-L(Pi)

[0290] Among them, σ P2 is the pressure standard deviation of the fitting function P(t);

[0291] Then the N% confidence level leakage rate interval of the containment leakage rate is:

[0292] [L D -k(σ L1 -σ L2min ), L D +k(σ L1 +σ L2max )];

[0293] If L D Calculated by discrete series (Pi, Li), the containment leakage rate L is obtained under the specified pressure. D The standard deviation of is the standard deviation σ brought by the function L(P) L2 ;

[0294] Then the N% confidence level leakage rate interval of the containment leakage rate is:

[0295] [L D -k(σ L1 +σ L2 ), L D +k(σ L1 +σ L2 )]

[0296] Where k is the N% confidence level coefficient.

[0297] The system for the containment sealing test of the disclosed embodiment is used to implement the method for the containment sealing test in method embodiment 1 and embodiment 2, so the description is relatively simple. For details, please refer to the relevant description in the previous method embodiment 1 and embodiment 2, which will not be repeated here.

[0298] In addition, if Fig. 20 As shown, the fourth embodiment of the present disclosure further provides an electronic device, including a memory 100 and a processor 200, wherein the memory 100 stores a computer program, and when the processor 200 runs the computer program stored in the memory 100, the processor 200 executes the above-mentioned various possible methods.

[0299] The memory 100 is connected to the processor 200. The memory 100 may be a flash memory, a read-only memory or other memory, and the processor 200 may be a central processing unit or a single-chip microcomputer.

[0300] In addition, an embodiment of the present disclosure further provides a computer-readable storage medium, on which a computer program is stored, and the computer program is executed by a processor to perform the above-mentioned various possible methods.

[0301] The computer-readable storage medium includes volatile or non-volatile, removable or non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, computer program modules or other data). Computer-readable storage media include, but are not limited to, RAM (Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable read only memory), flash memory or other memory technology, CD-ROM (Compact Disc Read-Only Memory), digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer.

[0302] The present disclosure proposes the most basic nonlinear calculation models of exponential, power function, point-by-point differentiation and other methods. It should be noted that new calculation models generated by simple transformation and superposition without substantial changes in the nonlinear calculation ideas of the present disclosure are all within the scope of protection of this patent.

[0303] It is to be understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of the present disclosure, but the present disclosure is not limited thereto. For those of ordinary skill in the art, various modifications and improvements can be made without departing from the spirit and substance of the present disclosure, and these modifications and improvements are also considered to be within the scope of protection of the present disclosure.

Claims

1. A method for testing the sealing performance of a containment vessel, characterized in that: The method comprises: Obtain the temperature, humidity and pressure inside the containment shell at each moment in the containment shell sealing test source acquisition data; The mass of dry air gas in the shell at each moment is calculated according to the temperature, humidity and pressure in the shell, and the discrete mass function M(i) is obtained; M(i) is fitted by a preset nonlinear calculation model algorithm to obtain a mass-time curve function M(t), and the fitted mass-time curve function M(t) is derived to obtain a real-time leakage rate function L(t); or, Take two adjacent acquisition moments as a differential segment, differentiate the dry air gas mass function M(i), calculate the leakage rate of each differential segment, and obtain the discrete leakage rate function Li in each acquisition period. Fit Li through the preset calculation model algorithm to obtain the real-time leakage rate function L(t); Obtain the relationship between pressure / pressure difference and time P(t), and calculate the containment leakage rate at a specified pressure based on the real-time leakage rate function L(t) and the relationship between pressure / pressure difference and time P(t); Wherein, the nonlinear calculation model algorithm includes an exponential fitting differential leakage rate method, and the mass-time curve function M(t) is obtained by fitting M(i) through a preset nonlinear calculation model algorithm, and the fitted mass-time curve function M(t) is derived to obtain the real-time leakage rate function L(t), including: The n sets of source acquisition data to be analyzed (M i , t i ) array, and exponential fitting is performed on it to obtain a continuous "mass-time" function M(t), where the fitting target calculation model used is: Differentiate M(t) and adjust the mass leakage rate unit data to obtain the "mass leakage rate-time" function L(t). or, The nonlinear calculation model algorithm includes a power function fitting differential leakage rate method; The method of fitting M(i) by a preset nonlinear calculation model algorithm to obtain a mass-time curve function M(t), and deriving the fitted mass-time curve function M(t) to obtain a real-time leakage rate function L(t) includes: The n sets of source acquisition data to be analyzed (M i , t i ) array, and fit the power function to it to obtain the continuous "mass-time" function M(t), where the fitting target calculation model used is: Differentiate M(t) and adjust the unit data of mass leakage rate to obtain the "mass leakage rate-time" function L(t); The method of taking two adjacent acquisition moments as a differential segment, differentiating the dry air gas mass function M(i), calculating the leakage rate of each differential segment, obtaining the discrete leakage rate function Li in each acquisition period, and fitting Li through a preset calculation model algorithm to obtain the real-time leakage rate function L(t), includes: Collect data for n groups of sources to be analyzed (M i , t i ) array, taking two adjacent acquisition moments as a differential segment, and differentiating the dry air gas mass to obtain n-1 sets of discrete Calculate the leakage rate of each micro-segment and obtain the discrete leakage rate function L in each acquisition period i , The unit is % of the gas weight in the containment vessel / day; The n-1 discrete L i Combined with the middle moments of n-1 groups of acquisition periods, form n-1 groups of function point data Perform straight-line fitting, exponential fitting or power function fitting to obtain a continuous "mass leakage rate-time" function L(t).

2. The method according to claim 1, characterized in that The obtaining of the relationship P(t) between pressure / pressure difference and time, and calculating the containment leakage rate at a specified pressure according to the real-time leakage rate function L(t) and the relationship P(t) between pressure / pressure difference and time, include: Combine the shell pressure / shell internal and external pressure difference P in n sets of collected data with the collection time of n sets of collected data to form n sets of function point data, and perform linear fitting, exponential fitting or power function fitting to obtain a continuous "pressure / pressure difference-time" function P(t); The specified pressure / pressure difference P to be calculated is selected D Substitute P(t) to get the corresponding collection time t D ; The calculated pressure / pressure difference P D The corresponding acquisition time t D Substitute L(t) to obtain pressure / pressure difference P D The corresponding containment leakage rate L D ; or, After obtaining the continuous "pressure / pressure difference-time" function P(t), substitute the function P(t) into L(t) to obtain the "leakage rate-pressure / pressure difference" function L(P); The specified pressure / pressure difference P to be calculated is selected D Substitute L(P) to obtain the containment leakage rate L D ; or, According to the "mass leakage rate-time" function L(t), the discrete series (ti, Li) of all sampling moments is obtained, and ti in the (ti, Li) data is replaced with Pi to obtain the discrete series (Pi, Li); The discrete series (Pi, Li) is fitted with a straight line, an exponential function or a power function to obtain the "leakage rate-pressure / pressure difference" function L(P) in which the leakage rate varies with the pressure inside the shell; The specified pressure / pressure difference P to be calculated is selected D Substitute L(P) to obtain the containment leakage rate L D .

3. The method according to claim 2, characterized in that The method further comprises: Calculate the standard deviation of the leakage rate function L(t) and the containment leakage rate L at the specified pressure. D The standard deviation of According to the standard deviation of the leakage rate function L(t) and the containment leakage rate L at the specified pressure D The confidence level leakage rate interval of the containment leakage rate is obtained by combining the standard deviation of Among them, the standard deviation σ of the leakage rate function L(t) L1 Obtained by the following formula: Among them, σ M1 is the standard deviation of the fitting function M(t), M is the pressure inside the shell reaching the specified calculation pressure P D The corresponding dry air mass in the shell at ; The containment leakage rate L is obtained under a specified pressure. D The standard deviation of If L D Calculated by the function P(t), the containment leakage rate L is obtained at the specified pressure: D The lower limit of error σ L2min and the upper limit σ l2max They are: σ L2min =L(Pi-σ P2 )-L(Pi) σ L2max =L(Pi+σ P2 )-L(Pi) Among them, σ P2 is the pressure standard deviation of the fitting function P(t); Then the N% confidence level leakage rate interval of the containment leakage rate is: [L D -k(s L1 -s L2min ),L D +k(σ L1 +s L2max )]; If L D Calculated by discrete series (Pi, Li), the containment leakage rate L is obtained under the specified pressure. D The standard deviation of is the standard deviation σ brought by the function L(P) L2 ; Then the N% confidence level leakage rate interval of the containment leakage rate is: [L D -k(s L1 +s L2 ),L D +k(σ L1 +s L2 )] Where k is the N% confidence level coefficient.

4. A system for testing the sealing performance of a containment vessel, characterized in that: The system comprises: An acquisition module, which is configured to acquire the temperature, humidity and pressure inside the containment shell at each moment in the containment shell sealing test source acquisition data; A first calculation module is configured to calculate the mass of dry air gas in the shell at each moment according to the temperature, humidity and pressure in the shell to obtain a discrete mass function M(i); A fitting module is configured to fit M(i) by a preset nonlinear calculation model algorithm to obtain a mass-time curve function M(t), and to derive the fitted mass-time curve function M(t) to obtain a real-time leakage rate function L(t); or, It is set to take two adjacent acquisition moments as a differential segment, differentiate the dry air gas mass function M(i), calculate the leakage rate of each differential segment, obtain the discrete leakage rate function Li in each acquisition period, and fit Li through the preset calculation model algorithm to obtain the real-time leakage rate function L(t); A second calculation module is configured to obtain a relationship P(t) between pressure / pressure difference and time, and calculate a containment leakage rate at a specified pressure according to a real-time leakage rate function L(t) and the relationship P(t) between pressure / pressure difference and time; Wherein, the nonlinear calculation model algorithm includes an exponential fitting differential leakage rate method, and the mass-time curve function M(t) is obtained by fitting M(i) through a preset nonlinear calculation model algorithm, and the fitted mass-time curve function M(t) is derived to obtain the real-time leakage rate function L(t), including: The n sets of source acquisition data to be analyzed (M i , t i ) array, and exponential fitting is performed on it to obtain a continuous "mass-time" function M(t), where the fitting target calculation model used is: Differentiate M(t) and adjust the mass leakage rate unit data to obtain the "mass leakage rate-time" function L(t). or, The nonlinear calculation model algorithm includes a power function fitting differential leakage rate method; The method of fitting M(i) by a preset nonlinear calculation model algorithm to obtain a mass-time curve function M(t), and deriving the fitted mass-time curve function M(t) to obtain a real-time leakage rate function L(t) includes: The n sets of source acquisition data to be analyzed (M i , t i ) array, and fit the power function to it to obtain the continuous "mass-time" function M(t), where the fitting target calculation model used is: Differentiate M(t) and adjust the unit data of mass leakage rate to obtain the "mass leakage rate-time" function L(t); The method of taking two adjacent acquisition moments as a differential segment, differentiating the dry air gas mass function M(i), calculating the leakage rate of each differential segment, obtaining the discrete leakage rate function Li in each acquisition period, and fitting Li through a preset calculation model algorithm to obtain the real-time leakage rate function L(t), includes: Collect data for n groups of sources to be analyzed (M i , t i ) array, taking two adjacent acquisition moments as a differential segment, and differentiating the dry air gas mass to obtain n-1 sets of discrete Calculate the leakage rate of each micro-segment and obtain the discrete leakage rate function L in each acquisition period i , The unit is % of the gas weight in the containment vessel / day; The n-1 discrete L i Combined with the middle moments of n-1 groups of acquisition periods, form n-1 groups of function point data Perform straight-line fitting, exponential fitting or power function fitting to obtain a continuous "mass leakage rate-time" function L(t).

5. An electronic device, characterized in that: The method comprises a memory and a processor, wherein a computer program is stored in the memory, and when the processor runs the computer program stored in the memory, the processor executes the method for the containment sealing test according to any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for testing the sealing performance of a containment vessel according to any one of claims 1 to 3 is implemented.

Images