A method for calculating the threshold value of cavity sealing detection and a method for optimizing sealing detection

Abstract

The present invention discloses a cavity sealing detection threshold calculation method and a sealing detection optimization method, and the specific steps are as follows: step 1, setting test parameters and performing sealing detection on the test cavity, obtaining a second leakage pressure change data group and a first leakage pressure change data group; step 2, performing normal distribution transformation on the first leakage pressure change data group and the second leakage pressure change data group, and obtaining the first leakage pressure change mean value P Δb and the second leakage pressure change mean value P Δa ; Step 3: Select the threshold value P in the threshold selection interval T , and calculate the threshold P T The corresponding detection accuracy; Step 4, determine the threshold P selected in step 3 T Whether the corresponding detection accuracy meets the accuracy requirement. The present invention adopts the introduction of statistical methods to analyze the optimal value range of the threshold and the detection accuracy corresponding to the corresponding threshold by obtaining the distribution of the actual pressure change data.

Description

Technical Field

[0001] The present invention relates to the technical field of sealing detection, and in particular to a cavity sealing detection threshold calculation method and a sealing detection optimization method. Background Art

[0002] There is a wide demand for sealing testing. Many industries such as pharmaceuticals, food, cosmetics packaging, tires, industrial tanks, etc. need to test the sealing of their products. The pressure decay method is one of the most commonly used detection methods. The specific method is to connect the pressure sensor to the cavity to be tested, fill or extract the pressure medium into or out of the cavity to be tested until the pressure sensor detects the set test pressure, and then keep the cavity to be tested in a sealed state. The pressure change value shown by the pressure sensor after a period of time is compared with the threshold set in advance to determine whether the sealing of the cavity is qualified.

[0003] In some applications with high requirements for sealing detection, when the pressure decay method is used to detect the sealing of the tested cavity, the test results (pressure change value) will be affected by factors such as the accuracy of the pressure sensor, changes in ambient temperature, and the sealing of the test device connection. Often, the same container is tested multiple times using the same test instrument, and the results (pressure change value) obtained will fluctuate randomly. When the requirements for sealing detection become higher and higher, the difference between leakage (very small hole) and no leakage becomes less and less obvious, and it will be difficult to formulate the pressure drop value (i.e., threshold) to determine whether there is a leak hole. Whether the threshold setting is accurate or not has a key impact on the accuracy of the test results.

[0004] Therefore, it is urgent to provide a method that can accurately measure and optimize the threshold value to ensure the accuracy of the cavity sealing test results. Summary of the invention

[0005] The purpose of the present invention is to solve the deficiencies in the prior art and to provide a cavity sealing detection threshold calculation method and a sealing detection optimization method.

[0006] The object of the present invention is achieved through the following technical solution: a method for calculating a cavity sealing detection threshold, comprising the following specific steps:

[0007] Step 1, set the test parameters and perform a sealing test on the test cavity, set the test time point, respectively detect the pressure change data of the test cavity over time in the first leakage state and the second leakage state, and obtain multiple groups of first leakage detection data and multiple groups of second leakage detection data; the leakage area of ​​the test cavity in the first leakage state is larger than the leakage area in the second leakage state; select the first leakage pressure change value corresponding to the detection time point in the first leakage detection data as the first leakage pressure change data group, and select the second leakage pressure change value corresponding to the detection time point in the second leakage pressure change data as the second leakage pressure change data group;

[0008] Step 2: Perform normal distribution transformation on the first leakage pressure change data set and the second leakage pressure change data set to obtain the first leakage pressure change mean value P Δb and the second leakage pressure change mean value P Δa ;

[0009] Step 3: Take the first leakage pressure change mean value P Δb and the second leakage pressure change mean value P Δa The interval between is the threshold selection interval, and the threshold P is selected in the threshold selection interval. T , and calculate the threshold P T The corresponding detection accuracy;

[0010] Step 4: Determine the threshold value P selected in step 3 T Whether the corresponding detection accuracy meets the accuracy requirements; if the corresponding detection accuracy meets the accuracy requirements, then output the current threshold P T and test parameters; if the threshold value P that meets the accuracy requirement cannot be obtained within the threshold selection interval in step 3 T， Then adjust the detection time point and repeat steps 2 to 4.

[0011] Preferably, in step 1, after obtaining the first leakage pressure change data group and the second leakage pressure change data group, the data availability is judged;

[0012] If the data availability is judged to be qualified, proceed to the next step; if the data availability is judged to be unqualified, adjust the test parameters and reacquire the first leakage pressure change data set and the second leakage pressure change data set.

[0013] Preferably, data availability is determined by any one of the following methods or a combination of several methods, wherein:

[0014] Method 1: Performing a distribution normality test on the first leakage pressure change data group and the second leakage pressure change data group;

[0015] Method 2: Detecting whether the first leakage pressure change data group and the second leakage pressure change data group overlap;

[0016] Method three: Detect whether the data in the first leakage pressure change data group and the second leakage pressure change data group exceed the set upper limit value.

[0017] Preferably, the test parameters include at least a starting pressure value, a total test time, a temperature difference limit, and a number of test groups.

[0018] As a preferred method, in step 3, the median value of the threshold selection interval is first used as the threshold P T The selected value of the threshold P T If the corresponding detection accuracy does not meet the accuracy requirement, the values ​​on both sides of the median value of the threshold selection interval are taken in turn and used as the threshold P T The selected value of .

[0019] As a preferred embodiment, in step 4, when judging the threshold value P T When the corresponding detection accuracy meets the accuracy requirements, the target accuracy value is set. If the threshold P T The corresponding detection accuracy is greater than or equal to the target accuracy value, then the accuracy requirement is met; if the threshold P T If the corresponding detection accuracy is less than the target accuracy value, the accuracy requirement is not met.

[0020] As a preference, when calculating the threshold value P T When the detection accuracy corresponding to the first leakage pressure change data group is obtained, the normal distribution curve of the first leakage pressure change data group and the normal distribution curve of the second leakage pressure change data group are first obtained, wherein the abscissa of the normal distribution curve is the pressure change value, and the ordinate of the normal distribution curve is the distribution density of the pressure change value; take the threshold value P T The area value enclosed by the horizontal axis and the right side of the normal distribution curve of the first leakage pressure change data group is the detection accuracy of the first leakage of the cavity; the threshold value P T The area value enclosed by the horizontal axis and the left side of the normal distribution curve of the second leakage pressure change data group is the detection accuracy of judging the second leakage of the cavity.

[0021] Preferably, when the test cavity is in the second leakage state, the leakage area on the test cavity is zero.

[0022] Preferably, in step one, a leakage device is installed on the test cavity, the leakage device has a perforated component with a through hole and a closed-hole component matching the through hole, and the perforated component is installed on the test cavity; when obtaining the first leakage detection data, the closed-hole component is taken out from the through hole to make the through hole in an open state; when obtaining the second leakage detection data, the closed-hole component is inserted into the through hole to close the through hole.

[0023] A sealing detection optimization method determines thresholds and test parameters through a cavity sealing detection threshold calculation method.

[0024] The beneficial effects of the present invention are:

[0025] 1. The present invention provides a systematic process to determine the threshold value of the sealing test, and ensures the repeatability and scientificity of the results by setting parameters and conducting actual tests.

[0026] 2. The present invention relies on actual test data to make decisions, rather than based on subjective judgment or empirical rules. In the process of determining thresholds and test parameters, statistical methods are introduced to analyze the optimal value range of the threshold and the detection accuracy corresponding to the corresponding threshold by obtaining the distribution of actual pressure change data. It has a high degree of objectivity and accuracy, which helps to improve the accuracy of sealing detection.

[0027] 3. Through this method, the test threshold can be formulated in combination with the customer's requirements for the process to improve the test efficiency; and the formulation of the threshold has a scientific basis and can be used as part of the software function of the sealing test device. Users can formulate corresponding threshold judgment strategies according to their own needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of a process of the present invention.

[0029] Figure 2 Another schematic diagram of the process of the present invention.

[0030] Figure 3 A schematic diagram of a method for selecting a threshold value according to the present invention.

[0031] Figure 4 This is a schematic diagram showing that the first leakage pressure change data group and the second leakage pressure change data group do not overlap.

[0032] Figure 5 This is a schematic diagram showing the overlap of the first leakage pressure change data set and the second leakage pressure change data set. DETAILED DESCRIPTION

[0033] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0034] Those skilled in the art should understand that, in the disclosure of the present invention, the terms "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the drawings, which are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation. Therefore, the above terms should not be understood as limiting the present invention.

[0035] It is to be understood that the term "one" should be understood as "at least one" or "one or more", that is, in one embodiment, the number of an element may be one, while in another embodiment, the number of the element may be multiple, and the term "one" should not be understood as a limitation on the quantity.

[0036] like Figures 1 to 4 As shown, a method for calculating a cavity sealing detection threshold value is characterized by comprising the following specific steps:

[0037] Step 1, set the test parameters and perform a sealing test on the test cavity, set the test time point, respectively detect the pressure change data of the test cavity over time in the first leakage state and the second leakage state, and obtain multiple groups of first leakage detection data and multiple groups of second leakage detection data; the leakage area of ​​the test cavity in the first leakage state is smaller than the leakage area in the second leakage state; select the first leakage pressure change value corresponding to the detection time point in the first leakage detection data as the first leakage pressure change data group, and select the second leakage pressure change value corresponding to the detection time point in the second leakage pressure change data as the second leakage pressure change data group.

[0038] The test parameters include at least the starting pressure value, the total test time, the temperature difference limit, and the number of test groups. The test cavity is inflated or evacuated by an external inflation or evacuation device so that the pressure inside the test cavity reaches the starting pressure value.

[0039] When the test cavity is in the first leakage state, a through hole with a certain diameter is provided on the test cavity, and the area of ​​the through hole needs to be set in advance; when the cavity is tested for sealing in the first leakage state, the test cavity is connected to the outside atmosphere through the through hole. When the test cavity is in the second leakage state, the area of ​​the through hole on the test cavity is smaller than the area of ​​the through hole in the first leakage state. In this embodiment, in the second leakage state, the area of ​​the through hole on the test cavity is zero, so that the test cavity remains closed.

[0040] During specific operations, a leakage device can be installed on the test cavity. The leakage device has a perforated component with a through hole and a closed-hole component matching the through hole. The perforated component is installed on the test cavity. When obtaining the first leakage detection data, the closed-hole component is taken out from the through hole to make the through hole in an open state. When obtaining the second leakage detection data, the closed-hole component is inserted into the through hole to close the through hole.

[0041] The second air leakage detection data and the first air leakage detection data show the pressure change values ​​of the test cavity corresponding to different time points.

[0042] In this step, after obtaining the first air leakage detection data and the second air leakage detection data, the data availability is judged. If the data availability is judged to be qualified, the next step is performed; if the data availability is judged to be unqualified, the test parameters are adjusted and the first air leakage detection data and the second air leakage detection data are re-acquired. By judging the data availability, abnormal data can be excluded, thereby avoiding the influence of data abnormality on the analysis results, so that better and more accurate analysis and decision results can be obtained.

[0043] In this embodiment, data availability is determined by any one of the following methods or a combination of several methods, wherein:

[0044] Method 1: Perform a normal distribution test on the first and second leakage pressure change data sets. This method is used to detect whether the data conforms to a normal distribution and to find out whether there are abnormal values ​​in the data. If the normal distribution test fails, the data is unavailable and needs to be re-acquired.

[0045] Method 2: Check whether there is any overlap between the first leakage pressure change data set and the second leakage pressure change data set. Theoretically, when the test cavity is in the first leakage state and the second leakage state, the pressure change values ​​corresponding to the same time point are obviously different, and the two sets of data will not overlap. If the two sets of data overlap, it indicates that the data is abnormal, the data is unavailable, and needs to be re-acquired.

[0046] like Figure 3 As shown, Figure 3 If the first leakage pressure change data set and the second leakage pressure change data set do not overlap, then the data does not contain abnormal values ​​and the data is available. Figure 4 As shown, Figure 4 If the first leakage pressure change data set and the second leakage pressure change data set partially overlap, the data has abnormal values ​​and is unusable. Figure 3 and Figure 4 The horizontal axis represents the number of tests, and the vertical axis represents the pressure change value.

[0047] Method 3: Detect whether the pressure change data in the first and second leakage pressure change data groups exceed the set upper limit. If the data in the first and second leakage pressure change data groups exceed the set upper limit, it indicates that the data is abnormal, the data is unavailable, and should be re-acquired.

[0048] The above methods 1 to 3 can be used in random combination, and the accuracy of data availability judgment can be improved by using them in combination. It is worth mentioning that when using them in combination, as long as the result of any one of the methods is unavailable, the data needs to be acquired again.

[0049] Step 2: Perform normal distribution transformation on the first leakage pressure change data set and the second leakage pressure change data set to obtain the first leakage pressure change mean value P Δb and the second leakage pressure change mean value P Δa , and simultaneously calculate the standard deviation of the first leakage pressure change data group and the second leakage pressure change data group.

[0050] Step 3: Take the first leakage pressure change mean value P Δb and the second leakage pressure change mean value P Δa The interval between is the threshold selection interval, and the threshold P is selected in the threshold selection interval. T , and calculate the threshold P T The corresponding detection accuracy.

[0051] Specifically, when calculating the threshold P T When the detection accuracy corresponding to the first leakage pressure change data group is obtained, the normal distribution curve of the first leakage pressure change data group and the normal distribution curve of the second leakage pressure change data group are first obtained (such as Figure 2 As shown), the horizontal coordinate of the normal distribution curve is the pressure change value, and the vertical coordinate of the normal distribution curve is the distribution density of the pressure change value. The threshold value P is taken as T The area value enclosed by the horizontal axis and the right side of the normal distribution curve of the first leakage pressure change data group is the detection accuracy of the first leakage of the cavity; the threshold value P T The area value enclosed by the horizontal axis and the left side of the normal distribution curve of the second leakage pressure change data group is the detection accuracy of judging the second leakage of the cavity.

[0052] Step 4: Determine the threshold value P selected in step 3 T Whether the corresponding detection accuracy meets the accuracy requirements; if the corresponding detection accuracy meets the accuracy requirements, then output the current threshold P T and test parameters; if the threshold value P that meets the accuracy requirement cannot be obtained within the threshold selection interval in step 3 T， Then adjust the detection time point and repeat steps 2 to 4 or steps 1 to 4. Figure 1 As shown, Figure 1 is a flow chart of one of the present invention, which shows that when the threshold value selection interval in step 3 cannot obtain the threshold value P that meets the accuracy requirement, T， Repeat steps 2 to 4. Figure 2 As shown, Figure 2 is a flow chart of one of the present invention, which shows that when the threshold value selection interval in step 3 cannot obtain the threshold value P that meets the accuracy requirement, T， Repeat steps 1 to 4.

[0053] Among them, in the judgment threshold P T When the corresponding detection accuracy meets the accuracy requirements, the target accuracy value is set. If the threshold P T The corresponding detection accuracy is greater than or equal to the target accuracy value, then the accuracy requirement is met; if the threshold P T If the corresponding detection accuracy is less than the target accuracy value, the accuracy requirement is not met. The target accuracy value can be set according to customer requirements.

[0054] For example, in the process of actually determining and optimizing the detection threshold, the target accuracy value can be set to 99%. If the actual detection accuracy is less than 99%, it is necessary to repeat steps 2 to 4 or steps 1 to 4 and redetermine the threshold P. T And calculate the corresponding accuracy, and judge whether the accuracy is qualified again, until the threshold P that meets the accuracy requirement is obtained T。

[0055] Furthermore, when selecting the threshold P T When the specific value of is chosen, the median of the threshold selection interval is selected first, that is, the median value of the threshold selection interval is first used as the threshold P T The selected value of the threshold P T If the corresponding detection accuracy does not meet the accuracy requirement, the values ​​on both sides of the median value of the threshold selection interval are taken in turn and used as the threshold P T The selected value of .

[0056] A sealing detection optimization method determines the threshold and test parameters through a cavity sealing detection threshold calculation method. After the threshold is determined, the pressure change value of the cavity within a set time period is detected. When the pressure change value exceeds the threshold, the cavity is judged to be unqualified in sealing, otherwise, the sealing is qualified.

[0057] Through the method of the present invention, the acceptable probability of false negatives (or accuracy) can be adjusted according to the test process requirements, and the test parameters and thresholds can be optimized while meeting the accuracy requirements. By optimizing the test parameters (such as test time, initial pressure, etc.) and thresholds, the test time and initial pressure can be shortened as much as possible to optimize the test parameters. The shortening of the test time can effectively improve the detection efficiency, and the reduction of the initial pressure can reduce the requirements for the instrument.

[0058] The present invention has the following effects:

[0059] 1. The present invention provides a systematic process to determine the threshold value of the sealing test, and ensures the repeatability and scientificity of the results by setting parameters and conducting actual tests.

[0060] 2. The present invention relies on actual test data to make decisions, rather than based on subjective judgment or empirical rules. In the process of determining thresholds and test parameters, statistical methods are introduced to analyze the optimal value range of the threshold and the detection accuracy corresponding to the corresponding threshold by obtaining the distribution of actual pressure change data. It has a high degree of objectivity and accuracy, which helps to improve the accuracy of sealing detection.

[0061] 3. Through this method, the test threshold can be formulated in combination with the customer's requirements for the process to improve the test efficiency; and the formulation of the threshold has a scientific basis and can be used as part of the software function of the sealing test device. Users can formulate corresponding threshold judgment strategies according to their own needs.

[0062] The present invention is not limited to the above-mentioned optimal implementation mode. Anyone can derive other various forms of products under the inspiration of the present invention. However, no matter what changes are made in the shape or structure, all technical solutions that are the same or similar to those of the present application fall within the protection scope of the present invention.

Claims

1. A method for calculating a cavity sealing detection threshold, characterized in that: The specific steps include: Step 1: setting test parameters and performing a sealing test on the test cavity, setting a test time point, respectively detecting the pressure change data of the test cavity over time in a first leakage state and a second leakage state, and obtaining multiple sets of first leakage test data and multiple sets of second leakage test data; The leakage area of ​​the test cavity in the first leakage state is greater than the leakage area in the second leakage state; Selecting a first leakage pressure change value corresponding to a detection time point in the first leakage detection data as a first leakage pressure change data group, and selecting a second leakage pressure change value corresponding to a detection time point in the second leakage pressure change data as a second leakage pressure change data group; Step 2: Perform normal distribution transformation on the first leakage pressure change data set and the second leakage pressure change data set to obtain the first leakage pressure change mean value P Δb and the second leakage pressure change mean value P Δa ; Step 3: Take the first leakage pressure change mean value P Δb and the second leakage pressure change mean value P Δa The interval between is the threshold selection interval, and the threshold P is selected in the threshold selection interval. T , and calculate the threshold P T The corresponding detection accuracy; Step 4: Determine the threshold value P selected in step 3 T Whether the corresponding detection accuracy meets the accuracy requirements; if the corresponding detection accuracy meets the accuracy requirements, then output the current threshold P T and test parameters; if the threshold value P that meets the accuracy requirement cannot be obtained within the threshold selection interval in step 3 T， Then adjust the detection time point and repeat steps 2 to 4 or repeat steps 1 to 4.

2. A method for calculating a cavity sealing detection threshold according to claim 1, characterized in that: In step 1, after obtaining the first leakage pressure change data set and the second leakage pressure change data set, the data availability is judged; If the data availability is judged to be qualified, proceed to the next step; if the data availability is judged to be unqualified, adjust the test parameters and reacquire the first leakage pressure change data set and the second leakage pressure change data set.

3. A method for calculating a cavity sealing detection threshold according to claim 2, characterized in that: Data availability is determined by any one of the following methods or a combination of the following methods: Method 1: Performing a distribution normality test on the first leakage pressure change data group and the second leakage pressure change data group; Method 2: Detecting whether the first leakage pressure change data group and the second leakage pressure change data group overlap; Method three: Detect whether the data in the first leakage pressure change data group and the second leakage pressure change data group exceed the set upper limit value.

4. A method for calculating a cavity sealing detection threshold according to claim 1, characterized in that: The test parameters include at least a starting pressure value, a total test time, a temperature difference limit, and a number of test groups.

5. The method for calculating the cavity sealing detection threshold according to claim 1, characterized in that: In step 3, the median value of the threshold selection interval is first used as the threshold P T The selected value of the threshold P T If the corresponding detection accuracy does not meet the accuracy requirement, the values ​​on both sides of the median value of the threshold selection interval are taken in turn and used as the threshold P T The selected value of .

6. A method for calculating a cavity sealing detection threshold according to claim 1, characterized in that: In step 4, when judging the threshold P T When the corresponding detection accuracy meets the accuracy requirements, the target accuracy value is set. If the threshold P T The corresponding detection accuracy is greater than or equal to the target accuracy value, then the accuracy requirement is met; if the threshold P T If the corresponding detection accuracy is less than the target accuracy value, the accuracy requirement is not met.

7. A method for calculating a cavity sealing detection threshold according to claim 1, characterized in that: In calculating the threshold P T When the detection accuracy corresponding to the first leakage pressure change data group is obtained, the normal distribution curve of the first leakage pressure change data group and the normal distribution curve of the second leakage pressure change data group are first obtained, wherein the abscissa of the normal distribution curve is the pressure change value, and the ordinate of the normal distribution curve is the distribution density of the pressure change value; take the threshold value P T The area value enclosed by the horizontal axis and the right side of the normal distribution curve of the first leakage pressure change data group is the detection accuracy of the first leakage of the cavity; the threshold value P T The area value enclosed by the horizontal axis and the left side of the normal distribution curve of the second leakage pressure change data group is the detection accuracy of judging the second leakage of the cavity.

8. A method for calculating a cavity sealing detection threshold according to claim 1, characterized in that: When the test cavity is in the second leakage state, the leakage area on the test cavity is zero.

9. A method for calculating a cavity sealing detection threshold according to claim 1, characterized in that: In step one, a leak device is installed on the test cavity, the leak device has a perforated component with a through hole and a closed-hole component matching the through hole, and the perforated component is installed on the test cavity; when obtaining the first leakage detection data, the closed-hole component is taken out from the through hole to make the through hole in an open state; when obtaining the second leakage detection data, the closed-hole component is inserted into the through hole to close the through hole.

10. A sealing detection optimization method, characterized in that: The threshold value and test parameters are determined by the cavity sealing detection threshold value calculation method described in any one of claims 1-8.

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