A calculation method for automatic piecewise processing of the volume curve of the containment leakage rate

Abstract

The present invention relates to a calculation method for automatically segmenting the volume curve of the containment leakage rate, including: S1. Reading the first array and performing 3-fold standard deviation cyclic rejection on the data in the first array until the remaining data in the first array are all within the range of 3 times the standard deviation of the remaining data in the first array, to obtain the second array; S2. Judging whether the number of data in the second array is greater than or equal to the first preset value. If it is greater than or equal to the first preset value, the data in the second data are fitted by the least squares method to obtain the leakage rate Qld and the uncertainty dQld of the second array; S3. Judging whether the uncertainty dQld of the second array is greater than or equal to the second preset value. If the uncertainty dQld of the second array is greater than or equal to the second preset value, the preset automatic segmentation processing strategy is adopted to obtain the leakage rate value Qld of the final segmented curve.

Description

Technical Field

[0001] The present invention relates to the technical field of online monitoring of the leakage rate of a nuclear power plant containment, and particularly relates to a calculation method for automatically segmenting the volume curve of the containment leakage rate. Background Art

[0002] The containment is the last physical barrier for a nuclear power plant to prevent the leakage of radioactive substances. There are three means to supervise its integrity: the overall Class A test of the containment once every 10 years; the periodic tests of the Class B and C sealing performance of the containment during refueling outages; and the online monitoring of the containment leakage during reactor operation. Among them, the online monitoring of the containment leakage rate is the only method for supervising the integrity of the containment during reactor operation at present. Its monitoring results are directly related to the safety of the nuclear island and whether the nuclear power plant can be started and stopped normally. In order to ensure the integrity and sealing performance of the containment, it is necessary to conduct the sealing test of the containment regularly. During the normal operation of the unit, it is necessary to monitor the change of the containment sealing performance in real time. The online monitoring system of the containment leakage rate of a nuclear power plant (EPP / CLM) is to monitor the sealing performance of the containment by calculating the leakage rate of the containment under the normal operating conditions of the unit, and to notify the power station operator to take necessary actions in time when the leakage rate reaches the operating limit. Under the normal operating conditions of the unit, the pressure difference between the inside and outside of the containment cycles periodically between -4 kPa and +6 kPa(g) (guaranteed by the containment atmosphere monitoring system). At this time, the factors affecting the change of the internal pressure of the containment include the working exhaust and leakage exhaust of the pneumatic equipment inside the containment, parasitic gases (mainly from the RND nuclear island nitrogen distribution system), and the leakage of penetrations in the presence of the pressure difference between the inside and outside of the containment, etc.

[0003] The containment leakage rate online monitoring system calculates the containment leakage rate based on the principle of gas mass conservation inside the containment. The basic calculation logic of the system is as follows: (1) Half-hour data acquisition and processing - DVH: By collecting the temperature, humidity, pressure inside the containment, pressure outside the containment, and compressed air flow every half hour, the change value DVH of the volume inside the containment in half an hour is calculated through the mass conservation equation, Dalton's law of partial pressures, and the ideal gas equation; (2) Daily calculation and processing - Qld: The system performs a daily calculation once a day. The 48 half-hour volume change values DVH are linearly fitted to obtain the leakage rate Qld value for the current day; (3) Daily calculation and processing - Ql60: The daily average pressure difference ΔP between the inside and outside of the containment and the daily leakage rate Qld values for the recent 20 days are linearly fitted to obtain the leakage rate Ql60 corresponding to the pressure difference ΔP = 60 hPa between the inside and outside of the containment. Finally, the status of the containment leakage rate is determined based on the Ql60 index in the power plant operation specification. When performing the DVH-t curve fitting operation in the second step of the leakage rate calculation, due to various factors, the DVH-t curve may not be smooth, which may lead to the calculation of a non-representative slope (leakage rate Qld). These factors may include: intermittent leakage during the day; thermodynamic effects (P, T, H) related to control actions; pneumatic valve actions; sensor problems; ETY / CAM emissions; in the original processing scheme, the system does not consider the non-smoothness of the DVH-t curve and directly fits it according to a single straight line. The calculated uncertainty dQld is very large, and the leakage rate Qld calculated in this way is not representative and cannot characterize the true leakage rate of the containment on the current day; after the operator discovers a high uncertainty dQld by checking the daily report, the operator manually segments the curve by observing the DVH-t curve to select the segmentation points, fits the two curves before and after the segmentation points to obtain two leakage rates Qld, and combines experience to select the smaller leakage rate Qld as the leakage rate value for the current day. This processing method is inefficient. The manually calculated Qld cannot be included in the curve fitting Ql60, and the online operation of the leakage rate lacks the data of the artificial fitting of the non-smooth DVH-t curve on the current day, resulting in missing calculation data; in addition, this manual calculation method has very high requirements for maintenance engineers. Some curve segmentation points are difficult to identify by the naked eye. The manual calculation work is cumbersome and inefficient, and the manual calculation results cannot be incorporated into the system's online calculation process, which has a great impact on the judgment of Ql60. Summary of the Invention

[0004] (1) Technical problems to be solved

[0005] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present invention provides a calculation method for automatically segmenting the volume curve of the containment leakage rate, which solves the technical problem that the calculated leakage rate Qld in the prior art is not representative and cannot characterize the true leakage rate of the containment on the current day.

[0006] (2) Technical solutions

[0007] To achieve the above object, the main technical solutions adopted by the present invention include:

[0008] An embodiment of the present invention provides a calculation method for automatically segmenting the volume curve of the containment leakage rate, including:

[0009] S1. Read a first array from the database, and perform 3 - standard - deviation cyclic rejection on the data in the first array until the remaining data in the first array are all within the range of 3 times the standard deviation of the remaining data in the first array, obtaining a second array;

[0010] The first array includes 48 half - hour time and volume change values DVH;

[0011] S2. Judge whether the number of data in the second array is greater than or equal to a first preset value. If the number of data in the second array is greater than or equal to the first preset value, perform least - squares fitting on the data in the second data to obtain the leakage rate Qld and uncertainty dQld of the second array;

[0012] S3. Judge whether the uncertainty dQld of the second array is greater than or equal to a second preset value. If the uncertainty dQld of the second array is greater than or equal to the second preset value, adopt a preset automatic segmentation processing strategy to obtain the leakage rate value Qld of the final segmented curve.

[0013] Preferably, the method further includes:

[0014] S4. Perform linear fitting on the daily average pressure difference ΔP between the inside and outside of the shell in the recent 20 days and the leakage rate value Qld of the final segmented curve every day to obtain the leakage rate Ql60 corresponding to ΔP = 60 hPa between the inside and outside of the shell, and determine the state of the containment leakage rate according to the Ql60 index.

[0015] Preferably, the S3 specifically includes:

[0016] S31. Judge whether the uncertainty dQld of the second array is greater than or equal to a second preset value;

[0017] S32. If the uncertainty dQld of the second array is greater than or equal to the second preset value, adopt a preset automatic segmentation processing strategy to obtain the leakage rate value Qld of the final segmented curve.

[0018] Preferably, the S32 specifically includes:

[0019] S321. Divide the first array into a front - segment array and a rear - segment array;

[0020] Wherein, set i = 1;

[0021] The front - segment array includes: the first half - hour time and volume change value DVH in the first array to the i - th half - hour time and volume change value DVH;

[0022] The rear - segment array includes: the i - th half - hour time and volume change value DVH in the first array to the 48 - th half - hour time and volume change value DVH;

[0023] S322. Adopt a pre - set first strategy to obtain the leakage rate value Qldf and uncertainty dQldf of the front - segment array;

[0024] S323. Adopt a pre - set second strategy to obtain the leakage rate value Qldr and uncertainty dQldr of the rear - segment array;

[0025] S324. Based on the leakage rate value Qldf, uncertainty dQldf of the front - segment array, and the leakage rate value Qldr, uncertainty dQldr of the rear - segment array, determine the minimum uncertainty dQldmin when i is the current value;

[0026] S325. Increase the value of i by 1, repeat steps S321 - S324 until i = 48, and obtain the leakage rate value Qld of the segmented curve corresponding to the minimum value of the minimum uncertainty dQldmin among 1 to 48 of i as the final leakage rate value Qld of the segmented curve.

[0027] Preferably, the S322 specifically includes:

[0028] S3221. Judge whether the number of data in the front - segment array is greater than or equal to a first pre - set value. If not, execute S323;

[0029] S3222. If the number of data in the front - segment array is greater than or equal to the first pre - set value, perform a 3 - times standard - deviation cyclic rejection on the data in the front - segment array until the remaining data in the front - segment array after rejection are all within the range of 3 times the standard deviation of the remaining data in the front - segment array after rejection, and obtain the front - segment array after rejection;

[0030] S3223. Judge whether the number of data in the front - segment array after rejection is greater than or equal to the first pre - set value. If less, execute S323;

[0031] If the number of data in the front - segment array after rejection is greater than or equal to the first pre - set value, use the least - squares method to fit and calculate the front - segment array after rejection to obtain the leakage rate value Qldf and uncertainty dQldf of the front - segment array.

[0032] Preferably, S323 specifically includes:

[0033] S3231. Determine whether the number of data in the latter segment array is greater than or equal to a first preset value. If not satisfied, execute S324;

[0034] S3232. If the number of data in the latter segment array is greater than or equal to the first preset value, perform 3 - standard - deviation cyclic rejection on the data in the latter segment array until all the remaining data after rejection in the latter segment array are within the range of 3 times the standard deviation of the remaining data after rejection in the latter segment array, obtaining the latter segment array after rejection;

[0035] S3233. Determine whether the number of data in the latter segment array after rejection is greater than or equal to the first preset value. If less, execute S324;

[0036] If the number of data in the latter segment array after rejection is greater than or equal to the first preset value, use the least - squares method to fit and calculate the latter segment array to obtain the leakage rate value Qldr and uncertainty dQldr of the latter segment array.

[0037] Preferably, the minimum uncertainty dQldmin when i is the current value in S324 is the minimum value of the uncertainty dQldf of the former segment array and the uncertainty dQldr of the latter segment array when i is the current value.

[0038] Preferably, the first preset value is 12.

[0039] Preferably, the second preset value is 3.

[0040] Preferably, in S2, if the number of data in the second array is less than the first preset value, the subsequent calculation process is not performed and the leakage rate value of the day is directly set to invalid.

[0041] (III) Beneficial effects

[0042] The beneficial effects of the present invention are as follows: For a calculation method for automatically segmenting the volume curve of the containment leakage rate in the present invention, since step S3 is adopted to determine whether the uncertainty dQld of the second array is greater than or equal to a second preset value, if the uncertainty dQld of the second array is greater than or equal to the second preset value, a preset automatic segmentation processing strategy is adopted to obtain the leakage rate value Qld of the final segmented curve. Compared with the prior art, a calculation method of curve segmentation point scanning is adopted, and the segmentation point with the minimum uncertainty of the segmented fitting curve is used as the judgment basis for automatic calculation of the optimal segmentation point, improving the accuracy and timeliness of calculating Ql60 by the on-line monitoring system of the containment leakage rate when encountering a non-smooth DVH-t curve, reducing the intervention work of engineers in this working condition, and greatly improving the ability of the on-line monitoring system of the containment leakage rate to calculate and adapt to the non-smooth DVH-t curve working condition. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a flowchart of a calculation method for automatically segmenting the volume curve of the containment leakage rate in the present invention;

[0044] Figure 2 It is a schematic diagram of the calculation process of the on-line monitoring system of the containment leakage rate in the prior art;

[0045] Figure 3 It is a flowchart of a calculation method for automatically segmenting the volume curve of the containment leakage rate in the second embodiment of the present invention;

[0046] Figure 4 It is a schematic diagram of the specific steps in step 6 in the second embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0047] In order to better explain the present invention for easy understanding, the present invention will be described in detail below in conjunction with the accompanying drawings through specific embodiments.

[0048] In order to better understand the above technical solutions, the exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present invention can be understood more clearly and thoroughly, and the scope of the present invention can be fully conveyed to those skilled in the art.

[0049] In this embodiment, EPP / CLM: Containment leakage rate online monitoring system; T: Temperature value inside the containment; Pcont: Pressure value inside the containment; Patm: Pressure value outside the containment; ΔP: Pressure difference between inside and outside the containment (Pcont - Patm); DVH: Volume change value of the containment in half an hour; DVH-t: Two-dimensional curve with time as the abscissa and the volume change value of the containment as the ordinate; Qld: Daily leakage rate value of the containment; dQld: Uncertainty of the leakage rate, where dQldmin is the minimum leakage rate uncertainty, dQldf is the leakage rate uncertainty corresponding to the first half of the segmented array, and dQldr is the leakage rate uncertainty corresponding to the second half of the segmented array; Ql60: Leakage volume of the containment when the pressure difference between inside and outside is 60 hPa, with the unit of Nm3; ETY / CAM: Containment gas emission system.

[0050] Embodiment 1

[0051] See Figure 1 , this embodiment provides a calculation method for automatic segmentation processing of the containment leakage rate volume curve, including:

[0052] S1. Read the first array from the database, and perform 3 times standard deviation cyclic rejection on the data in the first array until the remaining data in the first array are all within the range of 3 times the standard deviation of the remaining data in the first array, to obtain the second array.

[0053] The first array includes 48 half-hour time and volume change values DVH.

[0054] S2. Judge whether the number of data in the second array is greater than or equal to the first preset value. If the number of data in the second array is greater than or equal to the first preset value, perform least squares fitting on the data in the second data to obtain the leakage rate Qld and uncertainty dQld of the second array.

[0055] S3. Judge whether the uncertainty dQld of the second array is greater than or equal to the second preset value. If the uncertainty dQld of the second array is greater than or equal to the second preset value, adopt the preset automatic segmentation processing strategy to obtain the leakage rate value Qld of the final segmented curve.

[0056] The method further includes:

[0057] S4. Perform linear fitting on the daily average pressure difference ΔP between inside and outside the shell in the recent 20 days and the leakage rate value Qld of the final segmented curve every day to obtain the leakage rate Ql60 corresponding to the pressure difference ΔP = 60 hPa between inside and outside the shell, and judge the state of the containment leakage rate according to the Ql60 index.

[0058] In the actual application of this embodiment, S3 specifically includes:

[0059] S31. Determine whether the uncertainty dQld of the second array is greater than or equal to a second preset value.

[0060] S32. If the uncertainty dQld of the second array is greater than or equal to the second preset value, then adopt a preset automatic segmentation processing strategy to obtain the leakage rate value Qld of the final segmented curve.

[0061] Specifically, S32 specifically includes:

[0062] S321. Divide the first array into a front - segment array and a back - segment array.

[0063] Among them, set i = 1.

[0064] The front - segment array includes: the first half - hour time and volume change value DVH to the i - th half - hour time and volume change value DVH in the first array.

[0065] The back - segment array includes: the i - th half - hour time and volume change value DVH to the 48 - th half - hour time and volume change value DVH in the first array.

[0066] S322. Adopt a preset first strategy to obtain the leakage rate value Qldf and uncertainty dQldf of the front - segment array.

[0067] S323. Adopt a preset second strategy to obtain the leakage rate value Qldr and uncertainty dQldr of the back - segment array.

[0068] S324. Based on the leakage rate value Qldf, uncertainty dQldf of the front - segment array, and the leakage rate value Qldr, uncertainty dQldr of the back - segment array, determine the minimum uncertainty dQldmin when i is the current value.

[0069] S325. Increase the value of i by 1, and repeat steps 321 - 324 until i = 48, and obtain the leakage rate value Qld of the segmented curve corresponding to the minimum value of the minimum uncertainty dQldmin among i from 1 to 48 as the leakage rate value Qld of the final segmented curve.

[0070] Preferably, S322 specifically includes:

[0071] S3221. Determine whether the number of data in the front - segment array is greater than or equal to a first preset value. If not satisfied, execute S323.

[0072] S3222. If the number of data in the previous segment array is greater than or equal to the first preset value, perform 3 - standard - deviation cyclic rejection on the data in the previous segment array until all the remaining data in the previous segment array after rejection are within the range of 3 times the standard deviation of the remaining data in the previous segment array after rejection, obtaining the previous segment array after rejection.

[0073] S3223. Determine whether the number of data in the previous segment array after rejection is greater than or equal to the first preset value. If it is less, execute S323.

[0074] If the number of data in the previous segment array after rejection is greater than or equal to the first preset value, use the least - squares method to fit and calculate the previous segment array to obtain the leakage rate value Qldf and uncertainty dQldf of the previous segment array.

[0075] Preferably, S323 specifically includes:

[0076] S3231. Determine whether the number of data in the latter segment array is greater than or equal to the first preset value. If it does not meet the requirement, execute S324.

[0077] S3232. If the number of data in the latter segment array is greater than or equal to the first preset value, perform 3 - standard - deviation cyclic rejection on the data in the latter segment array until all the remaining data in the latter segment array after rejection are within the range of 3 times the standard deviation of the remaining data in the latter segment array after rejection, obtaining the latter segment array after rejection.

[0078] S3233. Determine whether the number of data in the latter segment array after rejection is greater than or equal to the first preset value. If it is less, execute S324.

[0079] If the number of data in the latter segment array after rejection is greater than or equal to the first preset value, use the least - squares method to fit and calculate the latter segment array to obtain the leakage rate value Qldr and uncertainty dQldr of the latter segment array.

[0080] Specifically, the minimum uncertainty dQldmin when i is the current value in S324 is the minimum value of the uncertainty dQldf of the previous segment array and the uncertainty dQldr of the latter segment array when i is the current value.

[0081] Among them, the first preset value is 12. The second preset value is 3.

[0082] A calculation method for automatically segmenting the volume curve of the containment leakage rate in this embodiment. Since it is determined in step S3 whether the uncertainty dQld of the second array is greater than or equal to a second preset value, if the uncertainty dQld of the second array is greater than or equal to the second preset value, a preset automatic segmentation processing strategy is adopted to obtain the leakage rate value Qld of the final segmented curve. Compared with the prior art, a calculation method of curve segmentation point scanning is adopted, and the segmentation point with the smallest uncertainty of the fitted curve after segmentation is used as the judgment basis for automatic calculation of the optimal segmentation point, improving the accuracy and timeliness of calculating Ql60 by the on-line monitoring system of the containment leakage rate when encountering a non-smooth DVH-t curve, reducing the intervention work of engineers in this working condition, and greatly improving the ability of the on-line monitoring system of the containment leakage rate to calculate and adapt to the non-smooth DVH-t curve working condition.

[0083] Embodiment 2

[0084] The on-line monitoring system of the containment leakage rate calculates the containment leakage rate based on the principle of mass conservation of the gas inside the containment. See Figure 2 , the basic calculation logic of the system is:

[0085] (1) Half-hour data acquisition and processing - DVH: The change value DVH of the volume inside the containment in half an hour is calculated by collecting the temperature, humidity, pressure, pressure outside the containment, and compressed air flow inside the containment every half an hour through the mass conservation equation, Dalton's law of partial pressures, and the ideal gas equation.

[0086] (2) Daily calculation and processing - Qld: The system performs a daily calculation once a day, and linearly fits 48 half-hour volume change values DVH to obtain the leakage rate Qld value for the day.

[0087] (3) Daily calculation and processing - Ql60: The daily average pressure difference ΔP between the inside and outside of the containment and the daily leakage rate Qld values in the recent 20 days are linearly fitted to obtain the leakage rate Ql60 corresponding to the pressure difference ΔP between the inside and outside of the containment of 60 hPa. Finally, the state of the containment leakage rate is determined according to the Ql60 index in the power plant operation specification book.

[0088] In this Embodiment 2, automatic segmentation processing is performed on the non-smooth situation of the DVH-t curve in the above step (2), and the segmentation point information is searched; the calculation result can participate in the calculation and evaluation process of the on-line monitoring system of the containment leakage rate, and the effective segmentation processing of the non-smooth curve improves the accuracy and timeliness of the calculation of the on-line monitoring system of the containment leakage rate.

[0089] This embodiment provides a calculation method for automatically segmenting the volume curve of the containment leakage rate, and uses the segmentation point with the smallest uncertainty of the fitted curve after segmentation as the judgment basis for automatic calculation of the optimal segmentation point. See Figure 3, the specific implementation plan for step (2) in the calculation logic of the containment leakage rate online monitoring system is as follows:

[0090] Step 1: Read from the database the array of 48 half-hour time and volume change values DVH(1→48) generated in step (1) of the calculation logic.

[0091] Step 2: Perform a 3-sigma loop rejection on the obtained array until the remaining array after rejection is within the 3-sigma range. The purpose of performing the loop rejection is to eliminate the random errors introduced by the instrument or the signal measurement loop.

[0092] Step 3: Compare the number N of the remaining data after the 3-sigma loop rejection. If the number N is greater than or equal to the number Nmin of DVH for effectively calculating the leakage rate (which is the first preset value, defaulting to 12), then continue with the subsequent calculation process; otherwise, do not perform the subsequent calculation process and directly set the leakage rate value for the day to invalid.

[0093] Step 4: Use the remaining data after the 3-sigma loop rejection for least squares fitting to calculate the leakage rate Qld and the uncertainty dQld.

[0094] Step 5: Compare the uncertainty dQld. If the uncertainty is greater than or equal to K0 (which is the second preset value, the uncertainty determination value, defaulting to 3 and adjustable according to specific requirements), then trigger the automatic segmentation processing algorithm; otherwise, it is considered that the uncertainty of the calculated leakage rate for the day meets the system uncertainty requirements.

[0095] Step 6: In the process of the automatic segmentation processing algorithm, use the original array of 48 half-hour time and volume change values DVH(1→48) generated in step (1) of the calculation logic. Traverse the data using the loop index i. In each traversal, divide the original data into two groups, namely the front-segment array DVH(1→i) and the back-segment array DVH(i→48);

[0096] See Figure 4 , step 6 in this embodiment includes:

[0097] Step 6-1: First, process the front-segment array DVH(1→i). Determine whether the length of the front-segment array DVH(1→i) is greater than or equal to the minimum number Nmin of DVH for effectively calculating the leakage rate (which is the first preset value, defaulting to 12). If it is satisfied, then execute the next process; otherwise, skip the subsequent calculation steps and directly execute step 6-5.

[0098] Step 6-2: Perform a 3-sigma loop rejection on the back-segment array DVH(1→i) until the remaining array after rejection is within the 3-sigma range.

[0099] Step 6-3: Compare the length of the front-segment array DVH(1→i)' after cyclic rejection (i.e., compare the number of data in the front-segment array after cyclic rejection). If the number is greater than or equal to the minimum number Nmin (default is 12) of DVHs for effectively calculating the leakage rate, then execute the next process; otherwise, skip the subsequent calculation steps and directly execute Step 6-5.

[0100] Step 6-4: Use the least squares method to fit and calculate the leakage rate value Qldf and uncertainty dQldf of the front-segment array.

[0101] Step 6-5: Process the rear-segment array DVH(i→N), and determine whether the length of the rear-segment array DVH(i→N) is greater than or equal to the minimum number Nmin (default is 12) of DVHs for effectively calculating the leakage rate. If it is satisfied, then execute the next process; otherwise, skip the subsequent calculation steps and directly execute Step 6-9.

[0102] Step 6-6: Perform a 3-fold standard deviation cyclic rejection on the array DVH(i→N) until the remaining array after rejection is within the 3-fold standard deviation range.

[0103] Step 6-7: Compare the length of the rear-segment array DVH(i→N)' after cyclic rejection (i.e., compare the number of data in the rear-segment array after cyclic rejection). If the length is greater than or equal to the minimum number Nmin (default is 12) of DVHs for effectively calculating the leakage rate, then execute the next process; otherwise, skip the subsequent calculation steps and directly execute Step 6-9.

[0104] Step 6-8: Use the least squares method to fit and calculate the leakage rate value Qldr and uncertainty dQldr of the rear-segment array.

[0105] Step 6-9: Record the Qld value corresponding to the minimum uncertainty dQldmin and the loop index i (i.e., the current optimal segmentation point) corresponding to the current i, and execute the next loop.

[0106] The minimum uncertainty dQldmin corresponding to the current i is: the minimum value between the uncertainty dQldf of the front-segment array and the uncertainty dQldr of the rear-segment array when i is at the current value.

[0107] Step 7: After the automatic search for the segmentation loop is completed, obtain the leakage rate value Qld of the segmentation curve corresponding to the minimum dQld and the optimal segmentation point i, and the automatic segmentation calculation algorithm operation is completed.

[0108] After the above automatic segmentation process is completed for Qld and dQld, continue with the operation process of Step (3) to perform the Ql60 calculation.

[0109] In the second embodiment, the original data is traversed in a loop, and the 3-fold standard deviation loop rejection and least squares fitting methods are combined to find the possible segmentation points of the optimal DVH-t curve. Whether to perform segmentation operations on the DVH-t curve is automatically judged by the uncertainty dQld, and the calculation results are referenced in the system, improving the accuracy and timeliness of calculating Ql60 by the in-containment leakage rate online monitoring system when encountering an uneven DVH-t curve, reducing the intervention work of engineers in this working condition, and greatly improving the ability of the in-containment leakage rate online monitoring system to calculate and adapt to the working condition of an uneven DVH-t curve.

[0110] This embodiment realizes the daily calculation logic - the function of automatically determining whether to segment the DVH-t curve in the Qld curve fitting logic, and automatically calculating the reasonable segmentation points and the daily leakage rate Qld; solves the problem that the original processing scheme directly fits the uneven DVH-t curve to obtain the unrepresentative daily leakage rate Qld, and solves the inefficient processing method of the operator manually calculating and manually judging the curve segmentation points, realizing the function of the in-containment leakage rate online monitoring system to automatically calculate the uneven DVH-t curve.

[0111] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can be implemented in the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can be implemented in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0112] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions.

[0113] It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in the claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention can be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In the claims listing several devices, several of these devices can be embodied by the same piece of hardware. The use of the words first, second, third, etc. is only for convenience of expression and does not denote any order. These words can be understood as part of the element name.

[0114] In addition, it should be noted that in the description of this specification, the descriptions of terms such as "one embodiment", "some embodiments", "embodiment", "example", "specific example", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic descriptions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0115] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications after learning the basic creative concepts. Therefore, the claims should be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0116] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention should also include these modifications and variations.

Claims

1. A calculation method for automatically segmenting the volume curve of the containment leakage rate, characterized in that, Including: S1. Read the first array from the database, and perform 3 - standard - deviation cyclic rejection on the data in the first array until the remaining data after rejection in the first array are all within the range of 3 - standard - deviation of the remaining data after rejection in the first array, obtaining a second array; The first array includes 48 half - hour time and volume change values DVH; S2. Determine whether the number of data in the second array is greater than or equal to a first preset value. If the number of data in the second array is greater than or equal to the first preset value, perform least - squares fitting on the data in the second array to obtain the leakage rate Qld and uncertainty dQld of the second array; S3. Determine whether the uncertainty dQld of the second array is greater than or equal to a second preset value. If the uncertainty dQld of the second array is greater than or equal to the second preset value, adopt a preset automatic segmentation processing strategy to obtain the leakage rate value Qld of the final segmented curve; Among them, if the uncertainty dQld of the second array is greater than or equal to the second preset value, adopt a preset automatic segmentation processing strategy to obtain the leakage rate value Qld of the final segmented curve, specifically including: S321. Divide the first array into a front - segment array and a rear - segment array; where, set i = 1; The front - segment array includes: the first half - hour time and volume change value DVH in the first array to the i - th half - hour time and volume change value DVH; the rear - segment array includes: the i - th half - hour time and volume change value DVH in the first array to the 48 - th half - hour time and volume change value DVH; S322. Obtain the leakage rate value Qldf and uncertainty dQldf of the front - segment array; S323. Obtain the leakage rate value Qldr and uncertainty dQldr of the rear - segment array; S324. Based on the leakage rate value Qldf, uncertainty dQldf of the front - segment array, and the leakage rate value Qldr, uncertainty dQldr of the rear - segment array, determine the minimum uncertainty dQldmin when i is the current value; S325. Increase the value of i by 1, repeat steps 321 - 324 until i = 48, and obtain the leakage rate value Qld of the segmented curve corresponding to the minimum value of the minimum uncertainty dQldmin among i from 1 to 48 as the leakage rate value Qld of the final segmented curve.

2. The calculation method for automatically segmenting the volume curve of the containment leakage rate according to claim 1, characterized in that, The method further includes: S4. Perform linear fitting on the daily average pressure difference ΔP between the inside and outside of the shell in the recent 20 days and the leakage rate value Qld of the final segmented curve every day to obtain the leakage rate Ql60 corresponding to ΔP = 60 hPa between the inside and outside of the shell, and determine the state of the containment leakage rate according to the Ql60 index.

3. The calculation method for automatically segmenting the volume curve of the containment leakage rate according to claim 2, characterized in that, The specific content of S322 includes: S3221. Determine whether the number of data in the front - segment array is greater than or equal to the first preset value. If not, execute S323; S3222. If the number of data in the previous array is greater than or equal to the first preset value, perform 3 - standard - deviation cyclic rejection on the data in the previous array until the remaining data after rejection in the previous array are all within the range of 3 times the standard deviation of the remaining data after rejection in the previous array, obtaining the previous array after rejection; S3223. Determine whether the number of data in the previous array after rejection is greater than or equal to the first preset value. If it is less, execute S323; If the number of data in the previous array after rejection is greater than or equal to the first preset value, use the least - squares method to perform fitting calculation on the previous array after rejection to obtain the leakage rate value Qldf and uncertainty dQldf of the previous array.

4. The calculation method for automatically segmenting the volume curve of the containment leakage rate according to claim 2, characterized in that, S323 specifically includes: S3231. Determine whether the number of data in the subsequent array is greater than or equal to the first preset value. If it does not meet the requirement, execute S324; S3232. If the number of data in the subsequent array is greater than or equal to the first preset value, perform 3 - standard - deviation cyclic rejection on the data in the subsequent array until the remaining data after rejection in the subsequent array are all within the range of 3 times the standard deviation of the remaining data after rejection in the subsequent array, obtaining the subsequent array after rejection; S3233. Determine whether the number of data in the subsequent array after rejection is greater than or equal to the first preset value. If it is less, execute S324; If the number of data in the subsequent array after rejection is greater than or equal to the first preset value, use the least - squares method to perform fitting calculation on the subsequent array after rejection to obtain the leakage rate value Qldr and uncertainty dQldr of the subsequent array.

5. The calculation method for automatically segmenting the volume curve of the containment leakage rate according to claim 2, characterized in that, In S324, when i is the current value, the minimum uncertainty dQldmin is the minimum value of the uncertainty dQldf of the previous array and the uncertainty dQldr of the subsequent array when i is the current value.

6. The calculation method for automatically segmenting the volume curve of the containment leakage rate according to claim 1, characterized in that, The first preset value is 12.

7. The calculation method for automatically segmenting the volume curve of the containment leakage rate according to claim 1, characterized in that, The second preset value is 3.

8. The calculation method for automatically segmenting the volume curve of the containment leakage rate according to claim 1, wherein, In S2, if the number of data in the second array is less than the first preset value, do not perform the subsequent calculation process and directly invalidate the daily leakage rate value.

Images