Aluminum foil lunch box stamping die air tightness detection method and system

Abstract

The present disclosure provides an air tightness detection method and system for an aluminum foil lunch box stamping die, and relates to the technical field of air tightness detection of stamping dies. The method includes: obtaining a first lunch box stamping die; performing an air tightness detection to obtain an air tightness coefficient of the die size; analyzing the results of ultrasonic detection of the die to obtain an ultrasonic air tightness coefficient of the die; performing N tracer air tightness detections to obtain N tracer detection quantities; constructing a tracer detection evaluation function; performing an air tightness evaluation on the N tracer detection quantities to obtain a tracer air tightness coefficient of the die; and generating an air tightness detection report for the first die. The present disclosure can solve the technical problem in the prior art that the quality of aluminum foil lunch box stamping molding is low due to the low efficiency and accuracy of air tightness detection of aluminum foil lunch box stamping dies, thereby achieving the goal of improving the efficiency and accuracy of air tightness detection and achieving the technical effect of improving the quality of aluminum foil lunch box stamping molding.

Description

Technical Field

[0001] The present invention relates to the technical field of air tightness detection of stamping dies, and in particular to an air tightness detection method and system for stamping dies for aluminum foil lunch boxes. Background Art

[0002] Aluminum foil lunch boxes are used for food packaging and are environmentally friendly, safe, and recyclable. The thickness of the aluminum foil material used to make aluminum foil lunch boxes is 0.025 to 0.09 mm. If the stamping die has poor air tightness, a blanking gap will be generated during the stamping process, causing the wall of the stamped product to sag and the entire product to deform. At present, the existing aluminum foil lunch box stamping die air tightness detection is mostly performed manually, resulting in inaccurate test results and low efficiency in timely detection of air tightness defects.

[0003] In summary, there is a technical problem in the prior art that the quality of the stamping of the aluminum foil lunch box is low due to the low efficiency and accuracy of the airtightness detection of the aluminum foil lunch box stamping die. Summary of the invention

[0004] The present invention provides an aluminum foil lunch box stamping die air tightness detection method and system, which are used to solve the technical problem in the prior art that the efficiency and accuracy of the aluminum foil lunch box stamping die air tightness detection are low, resulting in low quality of the aluminum foil lunch box stamping.

[0005] According to a first aspect of the present disclosure, a method for detecting air tightness of an aluminum foil lunch box stamping mold is provided, comprising: obtaining a first lunch box stamping mold, wherein the first lunch box stamping mold has a mold reference size structural feature with a corresponding mark; based on the mold reference size structural feature, performing air tightness detection on the first lunch box stamping mold according to a mold size air tightness detection algorithm to obtain a mold size air tightness coefficient; performing air tightness detection on the first lunch box stamping mold based on an ultrasonic detection terminal to obtain a mold ultrasonic detection result; performing ultrasonic detection on the mold based on a pre-constructed ultrasonic air tightness evaluation channel and an ultrasonic air tightness fusion function. The results are analyzed to obtain the ultrasonic air tightness coefficient of the mold; a gas tracer detection terminal is connected to perform N tracer air tightness tests on the first lunch box stamping mold to obtain N tracer detection quantities, wherein N is a positive integer greater than 1, and the gas tracer detection terminal includes a multi-source air supply device and a leakage detection device; a tracer detection evaluation function is constructed; based on the tracer detection evaluation function, the air tightness of the N tracer detection quantities is evaluated to obtain the mold tracer air tightness coefficient; based on the mold size air tightness coefficient, the mold ultrasonic air tightness coefficient and the mold tracer air tightness coefficient, a first mold air tightness detection report is generated.

[0006] According to a second aspect of the present disclosure, an aluminum foil lunch box stamping die airtightness detection system is provided, including: a first lunch box stamping die acquisition module, the first lunch box stamping die acquisition module is used to obtain a first lunch box stamping die, and the first lunch box stamping die has a mold reference size structural feature with a corresponding mark; a mold size airtightness coefficient acquisition module, the mold size airtightness coefficient acquisition module is used to perform an airtightness detection on the first lunch box stamping die based on the mold reference size structural feature and according to a mold size airtightness detection algorithm to obtain a mold size airtightness coefficient; a mold ultrasonic detection result acquisition module, the mold ultrasonic detection result acquisition module is used to perform an airtightness detection on the first lunch box stamping die based on an ultrasonic detection terminal to obtain a mold ultrasonic detection result; a mold ultrasonic airtightness coefficient acquisition module, the mold ultrasonic airtightness coefficient acquisition module is used to perform an airtightness detection on the mold based on a pre-constructed ultrasonic airtightness evaluation channel and an ultrasonic airtightness fusion function. The test results are analyzed to obtain the ultrasonic air tightness coefficient of the mold; a tracer detection quantity acquisition module, the tracer detection quantity acquisition module is used to connect to the gas tracer detection terminal to perform N tracer air tightness tests on the first lunch box stamping mold to obtain N tracer detection quantities, wherein N is a positive integer greater than 1, and the gas tracer detection terminal includes a multi-source air supply device and a leakage detection device; a tracer detection evaluation function acquisition module, the tracer detection evaluation function acquisition module is used to construct a tracer detection evaluation function; a mold tracer air tightness coefficient acquisition module, the mold tracer air tightness coefficient acquisition module is used to perform air tightness evaluation on the N tracer detection quantities based on the tracer detection evaluation function to obtain the mold tracer air tightness coefficient; a first mold air tightness detection report acquisition module, the first mold air tightness detection report acquisition module is used to generate a first mold air tightness detection report based on the mold size air tightness coefficient, the mold ultrasonic air tightness coefficient and the mold tracer air tightness coefficient.

[0007] One or more technical solutions provided in the present disclosure have at least the following technical effects or advantages: according to the method adopted in the present disclosure, a first lunch box stamping mold is obtained, and the first lunch box stamping mold has a mold reference size structural feature with a corresponding mark; based on the mold reference size structural feature, the first lunch box stamping mold is subjected to an airtightness test according to a mold size airtightness test algorithm to obtain a mold size airtightness coefficient; based on an ultrasonic detection terminal, the first lunch box stamping mold is subjected to an airtightness test to obtain a mold ultrasonic detection result; based on a pre-constructed ultrasonic airtightness evaluation channel and an ultrasonic airtightness fusion function, the mold ultrasonic detection result is analyzed to obtain a mold ultrasonic airtightness coefficient; a gas tracer detection terminal is connected to perform N times of airtightness tests on the first lunch box stamping mold. Tracer air tightness detection, obtaining N tracer detection quantities, wherein N is a positive integer greater than 1, and the gas tracer detection terminal includes a multi-source air supply device and a gas leakage detection device; constructing a tracer detection evaluation function; based on the tracer detection evaluation function, performing air tightness evaluation on the N tracer detection quantities, obtaining a mold tracer air tightness coefficient; based on the mold size air tightness coefficient, the mold ultrasonic air tightness coefficient and the mold tracer air tightness coefficient, generating a first mold air tightness detection report, solving the technical problem in the prior art that the efficiency and accuracy of the air tightness detection of the aluminum foil lunch box stamping mold are low, resulting in low quality of the stamping and forming of the aluminum foil lunch box, achieving the goal of improving the efficiency and accuracy of the air tightness detection, and achieving the technical effect of improving the stamping and forming quality of the aluminum foil lunch box.

[0008] It should be understood that the contents described in this section are not intended to indicate the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the present disclosure or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0010] Figure 1 A schematic diagram of a flow chart of a method for detecting air tightness of an aluminum foil lunch box stamping die provided in an embodiment of the present disclosure;

[0011] Figure 2 It is a schematic diagram of the process of obtaining the air tightness coefficient of the mold size in the air tightness detection method of the aluminum foil lunch box stamping mold in the embodiment of the present disclosure;

[0012] Figure 3A schematic structural diagram of an aluminum foil lunch box stamping die air tightness detection system provided in an embodiment of the present disclosure.

[0013] Explanation of the accompanying drawings: first lunch box stamping die acquisition module 11, die size airtightness coefficient acquisition module 12, die ultrasonic detection result acquisition module 13, die ultrasonic airtightness coefficient acquisition module 14, tracer detection amount acquisition module 15, tracer detection evaluation function acquisition module 16, die tracer airtightness coefficient acquisition module 17, first die airtightness detection report acquisition module 18. DETAILED DESCRIPTION

[0014] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0015] Embodiment 1

[0016] The method for detecting air tightness of an aluminum foil lunch box stamping die provided in the embodiment of the present disclosure is referred to Figure 1 Illustratively, the method comprises:

[0017] The method provided in the embodiment of the present disclosure includes:

[0018] Obtaining a first lunch box stamping die, wherein the first lunch box stamping die has a corresponding identified die reference dimension structure feature;

[0019] Specifically, the first lunch box stamping mold is a mold to be tested for air tightness of the lunch box stamping mold. Furthermore, the first lunch box stamping mold has a corresponding identified mold reference size structure feature. Among them, the mold reference size structure feature is the design size structure information when the first lunch box stamping mold is produced, that is, the size structure standard when the first lunch box stamping mold is produced. For example, the size structure standard of the first lunch box stamping mold is 220 mm long, 117 mm wide, and 65 mm high.

[0020] Based on the mold reference size structural features, the first lunch box stamping mold is subjected to an airtightness test according to a mold size airtightness test algorithm to obtain a mold size airtightness coefficient;

[0021] Specifically, according to the mold reference size structure characteristics, the first lunch box stamping mold is digitally twinned and modeled through the digital twin platform to obtain the mold reference body. The actual mold size structure information of the first lunch box stamping mold is measured and obtained. According to the actual mold size structure information of the first lunch box stamping mold, the first lunch box stamping mold is digitally twinned and modeled through the digital twin platform to obtain the mold twin. Furthermore, by obtaining the dimensional accuracy of the mold reference body and the mold twin, the mold size airtightness detection algorithm is obtained, and the mold reference body and the mold twin of the first lunch box stamping mold are tested for airtightness, that is, the size comparison is performed precision by precision to obtain the mold size airtightness coefficient.

[0022] Performing air tightness testing on the first lunch box stamping die based on an ultrasonic testing terminal to obtain an ultrasonic testing result of the die;

[0023] Specifically, the first lunch box stamping die is subjected to airtightness testing based on the ultrasonic testing terminal to obtain the ultrasonic testing result of the die. The ultrasonic testing terminal is an ultrasonic flaw detector, which is used to detect possible defects such as pores and cracks on the surface of the first lunch box stamping die, and the obtained ultrasonic testing result of the die is the detected surface defects of the first lunch box stamping die.

[0024] The ultrasonic airtightness coefficient of the mold is obtained by analyzing the ultrasonic testing result of the mold based on the pre-constructed ultrasonic airtightness evaluation channel and the ultrasonic airtightness fusion function;

[0025] Specifically, by connecting to the mold inspection data storage center, obtaining the sample mold ultrasonic inspection result record set and the sample ultrasonic airtightness evaluation record set, supervised training is performed to obtain the ultrasonic airtightness evaluation channel. The mold ultrasonic inspection result is input into the ultrasonic airtightness evaluation channel to obtain the output result. The ultrasonic airtightness fusion function is constructed to obtain the ultrasonic airtightness fusion function, and the output result of the ultrasonic airtightness evaluation channel is input into the ultrasonic airtightness fusion function to obtain the ultrasonic airtightness coefficient of the mold.

[0026] Connecting a gas tracing detection terminal to perform N tracing air tightness tests on the first lunch box stamping die to obtain N tracing detection quantities, wherein N is a positive integer greater than 1, and the gas tracing detection terminal includes a multi-source gas supply device and a gas leakage detection device;

[0027] Specifically, the gas tracer detection terminal includes a multi-source gas supply device and a gas leakage detection device. The gas tracer detection terminal delivers the detection gas into the mold through the multi-source gas supply device, and then uses the gas leakage detection device to detect gas leakage on the mold, and uses the gas leakage amount as the tracer detection amount. For example, the detection gas is nitrogen or other gases.

[0028] Further, the gas tracer detection terminal is connected, and the first lunch box stamping die is subjected to N tracer air tightness tests using the same gas to obtain N tracer detection quantities. Among them, at least more than one tracer air tightness test is performed, so N is a positive integer greater than 1. Accordingly, the purpose of performing N tracer air tightness tests using the same gas can be to control variables.

[0029] Constructing the tracer detection evaluation function;

[0030] Based on the tracer detection evaluation function, the air tightness of the N tracer detection quantities is evaluated to obtain a mold tracer air tightness coefficient;

[0031] A first mold air tightness test report is generated based on the mold size air tightness coefficient, the mold ultrasonic air tightness coefficient and the mold tracing air tightness coefficient.

[0032] Specifically, by constructing a tracer detection evaluation function, it is obtained that the smaller the tracer detection amount, the higher the mold tracer airtightness coefficient. Furthermore, N tracer detection amounts are input into the tracer detection evaluation function, the mean and variance of the N tracer detection amounts are calculated, and airtightness evaluation is performed to obtain the mold tracer airtightness coefficient.

[0033] Furthermore, the mold size air tightness coefficient, the mold ultrasonic air tightness coefficient and the mold tracing air tightness coefficient are combined to generate a first mold air tightness detection report.

[0034] Among them, this embodiment can solve the technical problem in the prior art that the efficiency and accuracy of air tightness detection of the aluminum foil lunch box stamping mold are low, resulting in low quality of aluminum foil lunch box stamping, thereby achieving the goal of improving the efficiency and accuracy of air tightness detection and achieving the technical effect of improving the quality of aluminum foil lunch box stamping.

[0035] The method provided in the embodiment of the present disclosure also includes:

[0036] Connecting to the digital twin platform, modeling based on the mold reference size and structural features to obtain a mold reference body, and dividing the mold reference body into regions to obtain Q sub-reference bodies, where Q is a positive integer greater than 1;

[0037] Obtaining actual mold size and structure information of the first lunch box stamping mold;

[0038] Based on the digital twin platform, modeling is performed according to the actual mold size and structure information to obtain a mold twin;

[0039] Based on the Q sub-reference bodies, evaluating the air tightness of the mold twin body according to the size characteristics, and obtaining Q air tightness values ​​of the size characteristics;

[0040] The Q size characteristic air densities are cleaned to remove the extreme values ​​to obtain the size characteristic air density cleaning results, and the size characteristic air density cleaning results are averaged to generate the mold size air tightness coefficient.

[0041] like Figure 2 As shown, specifically, the digital twin is to use physical models, sensor updates, operation history and other data, integrate simulation technology, and map in three-dimensional space to reflect the full life cycle process of the corresponding physical equipment. Further, the digital twin platform is connected, and the first lunch box stamping mold is digitally twinned according to the mold reference size and structural characteristics to obtain the mold reference body. For example, the digital twin platform has the Ansem Asia Pacific Industrial Digital Twin Product Platform. Further, the mold reference body is divided into regions according to the components to obtain Q sub-reference bodies. Among them, at least more than 1 sub-reference body is included, so Q is a positive integer greater than 1. For example, the Q sub-reference bodies may include a sub-reference body corresponding to the operating table, a sub-reference body corresponding to the stamping machine, and a sub-reference body corresponding to the robotic arm.

[0042] Furthermore, the actual mold size structure information of the first lunch box stamping mold is obtained by using a measuring tool. Furthermore, based on the digital twin platform, digital twin modeling is performed on the first lunch box stamping mold according to the actual mold size structure information to obtain a mold twin.

[0043] Furthermore, according to the Q sub-reference bodies of the mold reference body, Q registrations and positioning are performed in the mold twin respectively, and corresponding Q comparison twins are obtained in the mold twin respectively. According to the actual mold size structure information, the Q sub-reference bodies and the corresponding Q comparison twins are evaluated for size feature airtightness one by one, and Q size feature airtightness values ​​are obtained respectively.

[0044] Furthermore, the Q size characteristic air densities are cleaned by removing the extreme values, that is, a maximum value and a minimum value are deleted from the Q size characteristic air densities to obtain Q-2 size characteristic air density cleaning results, and the Q-2 size characteristic air density cleaning results are averaged, and the average calculation result is used as the mold size air tightness coefficient.

[0045] Among them, obtaining the mold size airtightness coefficient can improve the accuracy of the mold reference body and mold twin body in the dimensional feature airtightness evaluation.

[0046] The method provided in the embodiment of the present disclosure also includes:

[0047] Based on the Q sub-reference volumes, obtaining a first sub-reference volume;

[0048] Performing registration and positioning on the mold twin based on the first sub-reference body to obtain a first comparison twin;

[0049] Based on the actual mold size structure information, the actual mold size accuracy is obtained, and according to the actual mold size accuracy, a reference size evaluation operator is set, wherein the reference size evaluation operator is the actual mold size accuracy, and W is a positive integer greater than 1;

[0050] Based on the reference size evaluation operator, performing a size consistency evaluation on the first sub-reference body and the first comparison twin body to obtain a size consistency evaluation result;

[0051] The size consistency evaluation results are averaged to obtain a first size characteristic air density, and the first size characteristic air density is added to the Q size characteristic air densities.

[0052] Specifically, a first sub-reference body is randomly extracted from the Q sub-reference bodies, and further, the first sub-reference body is aligned and positioned in the mold twin to obtain a first comparison twin body, wherein the first comparison twin body is a mapping of the mold twin body to the first sub-reference body in the mold reference body.

[0053] Further, according to the actual mold size structure information, the actual mold size accuracy of the actual mold size structure information is obtained. For example, the actual mold size structure information of the first lunch box stamping mold includes a length of 2.18 meters, and the actual mold size accuracy is 0.01 meters. Further, according to the actual mold size accuracy , a reference size evaluation operator is set to compare the sizes of the first sub-reference body and the first comparison twin body one by one through the reference size evaluation operator. Wherein, W is a positive integer greater than 1.

[0054] Furthermore, the first sub-reference body and the first comparison twin body are evaluated for size consistency by using the reference size evaluation operator, that is, size comparison is performed to obtain a size consistency evaluation result. For example, the size consistency evaluation result is that the height difference between the first sub-reference body and the first comparison twin body is 0.18 meters.

[0055] Further, the first sub-reference body and the first comparison twin body are evaluated for dimensional consistency multiple times to obtain multiple dimensional consistency evaluation results, and the dimensional consistency evaluation results are averaged, and the average calculation result is used as the first dimensional characteristic air density. Further, according to the method for obtaining the first dimensional characteristic air density, Q-1 dimensional characteristic air densities are obtained in sequence. And the first dimensional characteristic air density is added to the Q dimensional characteristic air densities to obtain Q dimensional characteristic air densities.

[0056] Among them, obtaining Q dimensional characteristic air densities can improve the accuracy of the consistency evaluation results of the mold reference body and the mold twin body.

[0057] The method provided in the embodiment of the present disclosure also includes:

[0058] Constructing the ultrasonic airtightness evaluation channel, wherein the ultrasonic airtightness evaluation channel includes M confidence ultrasonic airtightness evaluators, and the M confidence ultrasonic airtightness evaluators have one-to-one corresponding M airtightness evaluation confidences, and M is a positive integer greater than 1;

[0059] Inputting the ultrasonic detection result of the mold into the ultrasonic airtightness evaluation channel to obtain M ultrasonic airtightness evaluation coefficients output by the M confidence ultrasonic airtightness evaluators;

[0060] Inputting the M ultrasonic airtightness evaluation coefficients into the ultrasonic airtightness fusion function to generate the ultrasonic airtightness coefficient of the mold;

[0061] Wherein, the ultrasonic airtight fusion function is:

[0062] ;

[0063] ;

[0064] in, Characterize the ultrasonic airtightness coefficient of the mold, Characterize the confidence ultrasonic airtightness evaluation coefficient, Characterizes the i-th ultrasonic airtightness evaluation coefficient, Characterizes the i-th airtightness evaluation confidence level corresponding to the i-th ultrasonic airtightness evaluation coefficient, where i is a positive integer and belongs to M.

[0065] Specifically, by connecting to the mold detection data storage center, obtaining the sample mold ultrasonic detection result record set and the sample ultrasonic airtightness evaluation record set, supervised training is performed, and an ultrasonic airtightness evaluation channel is obtained. Multiple airtightness evaluation accuracy rates are obtained through the output results of the ultrasonic airtightness evaluation channel. The multiple airtightness evaluation accuracy rates are sorted from high to low according to the accuracy rate, and the top M ultrasonic airtightness evaluators with high accuracy are extracted and output as M airtightness evaluation confidences, and M confidence ultrasonic airtightness evaluators corresponding to the M airtightness evaluation confidences are obtained. Among them, at least more than 1 airtightness evaluation confidence or confidence ultrasonic airtightness evaluator is included, so M is a positive integer greater than 1.

[0066] Furthermore, the ultrasonic detection result of the mold is used as input data and input into the ultrasonic airtightness evaluation channel, and M ultrasonic airtightness evaluation coefficients are outputted through M confidence ultrasonic airtightness evaluators respectively.

[0067] Furthermore, the M ultrasonic airtightness evaluation coefficients are input into the ultrasonic airtightness fusion function to generate the ultrasonic airtightness coefficient of the mold. Further, the ultrasonic airtightness fusion function is obtained as:

[0068] ;

[0069] ;

[0070] in, Characterize the ultrasonic airtightness coefficient of the mold, Characterize the confidence ultrasonic airtightness evaluation coefficient, Characterizes the i-th ultrasonic airtightness evaluation coefficient, Characterizes the i-th airtightness evaluation confidence corresponding to the i-th ultrasonic airtightness evaluation coefficient, and i is a positive integer, i belongs to M. Further, when the i-th ultrasonic airtightness evaluation coefficient The higher the value, the higher the confidence level of the i-th airtightness evaluation corresponding to the i-th ultrasonic airtightness evaluation coefficient. When the value remains unchanged or is higher, the confidence ultrasonic airtightness evaluation coefficient The higher the confidence of ultrasonic airtightness evaluation coefficient The higher the value, the higher the confidence of the mean value of ultrasonic airtightness evaluation coefficient and the higher the ultrasonic airtightness coefficient of the mold. The higher.

[0071] Among them, obtaining the ultrasonic air tightness coefficient of the mold can improve the accuracy of the air tightness test results.

[0072] The method provided in the embodiment of the present disclosure also includes:

[0073] Connect to the mold inspection data storage center to obtain the sample mold ultrasonic inspection result record set and the sample ultrasonic air tightness evaluation record set;

[0074] Obtaining a plurality of preset learning channels, wherein each preset learning channel includes a preset learning operator;

[0075] Based on the multiple preset learning channels, supervised learning is performed on the sample mold ultrasonic detection result record set and the sample ultrasonic airtightness evaluation record set respectively to obtain multiple ultrasonic airtightness evaluators, and the multiple ultrasonic airtightness evaluators have corresponding multiple airtightness evaluation accuracy rates;

[0076] The multiple ultrasonic airtightness evaluators are sorted based on the multiple airtightness evaluation accuracies, the first M ultrasonic airtightness evaluators are output as the M confident ultrasonic airtightness evaluators, and the M confident ultrasonic airtightness evaluators are labeled according to the multiple airtightness evaluation accuracies to obtain the M airtightness evaluation confidences.

[0077] Specifically, the mold inspection data storage center is connected, and historical mold ultrasonic inspection result record sets and historical ultrasonic airtightness evaluation record sets are randomly extracted as sample mold ultrasonic inspection result record sets and sample ultrasonic airtightness evaluation record sets.

[0078] Further, a plurality of preset learning channels are obtained, wherein each preset learning channel includes a preset learning operator. The preset learning operator is a data learning algorithm, such as a neural network, a decision tree, and the like.

[0079] Furthermore, based on multiple preset learning channels, supervised learning is performed on the sample mold ultrasonic detection result record set and the sample ultrasonic airtightness evaluation record set, respectively. When the output results of the multiple preset learning channels tend to converge, multiple ultrasonic airtightness evaluators are obtained respectively. Among them, the multiple ultrasonic airtightness evaluators have corresponding multiple airtightness evaluation accuracy rates. The multiple airtightness evaluation accuracy rates are verified respectively. The preset analysis accuracy rate is obtained, and the preset analysis accuracy rate can be customized by technicians in this field based on actual conditions, for example: 95%. When the multiple airtightness evaluation accuracy rates are respectively greater than the preset analysis accuracy rates, multiple ultrasonic airtightness evaluators are obtained respectively.

[0080] Furthermore, based on the multiple airtightness evaluation accuracy rates of the multiple ultrasonic airtightness evaluators, the multiple ultrasonic airtightness evaluators are sorted from high to low according to the accuracy rates to obtain an airtightness sorting result. The first M ultrasonic airtightness evaluators in the airtightness sorting result are extracted and output as M confident ultrasonic airtightness evaluators. And according to the M airtightness evaluation accuracy rates corresponding to the M confident ultrasonic airtightness evaluators, the corresponding M confident ultrasonic airtightness evaluators are marked to obtain M airtightness evaluation confidences.

[0081] Among them, obtaining M airtightness evaluation confidences can improve the accuracy of the output results of the M confidence ultrasonic airtightness evaluators.

[0082] The method provided in the embodiment of the present disclosure also includes:

[0083] Based on the multiple preset learning channels, obtaining a first preset learning channel;

[0084] Based on the first preset learning channel, supervised learning is performed on the sample mold ultrasonic detection result record set and the sample ultrasonic airtightness evaluation record set to obtain a first ultrasonic airtightness analyzer;

[0085] Connecting to the mold detection data storage center to obtain an ultrasonic airtightness evaluation test set, and testing the first ultrasonic airtightness analyzer based on the ultrasonic airtightness evaluation test set to obtain a first ultrasonic airtightness analysis accuracy rate;

[0086] Determining whether the first ultrasonic airtightness analysis accuracy is greater than a preset analysis accuracy;

[0087] If the first ultrasonic airtightness analysis accuracy is greater than the preset analysis accuracy, the first ultrasonic airtightness analyzer is set as a first ultrasonic airtightness evaluator, the first ultrasonic airtightness analysis accuracy is identified as the first airtightness evaluation accuracy corresponding to the first ultrasonic airtightness evaluator, and the first ultrasonic airtightness evaluator is added to the multiple ultrasonic airtightness evaluators;

[0088] If the first ultrasonic airtightness analysis accuracy is less than / equal to the preset analysis accuracy, incremental learning is performed on the first ultrasonic airtightness analyzer until the first ultrasonic airtightness evaluator is generated.

[0089] Specifically, a first preset learning channel is obtained by randomly extracting from a plurality of preset learning channels, wherein the first preset learning channel is a neural network model that can be continuously iteratively optimized in machine learning.

[0090] Furthermore, supervised learning is performed on the sample mold ultrasonic detection result record set and the sample ultrasonic airtightness evaluation record set based on the first preset learning channel, and when the output result of the first preset learning channel tends to converge, a first ultrasonic airtightness analyzer is obtained.

[0091] Further, the mold detection data storage center is connected, and the historical ultrasonic airtightness evaluation test set is randomly extracted to obtain the ultrasonic airtightness evaluation test set. The first ultrasonic airtightness analyzer is tested by the ultrasonic airtightness evaluation test set to obtain the first ultrasonic airtightness analysis accuracy. Further, it is determined whether the first ultrasonic airtightness analysis accuracy is greater than the preset analysis accuracy. When the first ultrasonic airtightness analysis accuracy is greater than the preset analysis accuracy, the first ultrasonic airtightness analyzer is obtained. Among them, the preset analysis accuracy can be customized by technicians in this field based on actual conditions, for example: 95%.

[0092] Further, the first ultrasonic airtightness analyzer is set as the first ultrasonic airtightness evaluator, and the first ultrasonic airtightness analysis accuracy is identified as the first airtightness evaluation accuracy corresponding to the first ultrasonic airtightness evaluator. Further, according to the method for obtaining the first ultrasonic airtightness evaluator, multiple ultrasonic airtightness evaluators are obtained, and the first ultrasonic airtightness evaluator is added to the multiple ultrasonic airtightness evaluators for adding to multiple preset learning channels.

[0093] Furthermore, if the accuracy of the first ultrasonic airtightness analysis is less than or equal to the preset analysis accuracy, incremental learning is performed on the first ultrasonic airtightness analyzer until the first ultrasonic airtightness evaluator is generated. Incremental learning is the ability to continuously process continuous information flows in the real world, retain or even integrate and optimize old knowledge while absorbing new knowledge. In this embodiment, supervised learning is continuously re-performed through the sample mold ultrasonic detection result record set and the sample ultrasonic airtightness evaluation record set to adapt to the changes in the output results of the first preset learning channel over time.

[0094] Among them, by obtaining multiple ultrasonic airtightness evaluators, the accuracy of ultrasonic airtightness detection can be improved.

[0095] The method provided in the embodiment of the present disclosure also includes:

[0096] The tracer detection evaluation function is constructed, and the tracer detection evaluation function is:

[0097] ;

[0098] ;

[0099] ;

[0100] in, Characterize the mold tracer air tightness coefficient, Characterizes the reliable tracer detection quantity, n is a positive integer, and n belongs to N, Characterize the nth tracer detection quantity, Tracer detection stability, are the credible tracer weight and the stable tracer weight respectively, and, The sum is 1.

[0101] Specifically, a tracer detection evaluation function is constructed, and the tracer detection evaluation function is:

[0102] ;

[0103] ;

[0104] ;

[0105] in, Characterize the mold tracer air tightness coefficient, Characterizes the reliable tracer detection quantity, n is a positive integer, and n belongs to N, Characterize the nth tracer detection quantity, Tracer detection stability, are the credible tracer weight and the stable tracer weight respectively, and, The sum is 1. Further, when the nth tracer detection amount The fewer the N tracer detections, the The mean value of the reliable tracer detection quantity When the nth tracer detection amount Trusted tracer detection The smaller the variance, the more stable the tracer detection. The higher the credible tracer detection and tracer detection stability Tightness coefficient with mold tracer Have an opposite correlation.

[0106] Among them, the accuracy of obtaining the tracer airtightness coefficient can be improved through the tracer detection evaluation function.

[0107] The method provided in the embodiment of the present disclosure also includes:

[0108] Obtaining a mold airtightness constraint condition, wherein the mold airtightness constraint condition is that the mold size airtightness coefficient satisfies the mold size airtightness constraint interval, and the mold ultrasonic airtightness coefficient satisfies the mold ultrasonic airtightness constraint interval, and the mold tracing airtightness coefficient satisfies the mold tracing airtightness constraint interval;

[0109] Determining whether the first mold air tightness test report meets the mold air tightness constraint condition;

[0110] If the first mold air tightness detection report does not meet the mold air tightness constraint condition, a first air tightness warning signal is generated.

[0111] Specifically, the mold airtightness constraint condition is obtained, wherein the mold airtightness constraint condition is that the mold size airtightness coefficient satisfies the mold size airtightness constraint interval, and the mold ultrasonic airtightness coefficient satisfies the mold ultrasonic airtightness constraint interval, and the mold tracing airtightness coefficient satisfies the mold tracing airtightness constraint interval, and the mold size airtightness coefficient, the mold ultrasonic airtightness coefficient, and the mold tracing airtightness coefficient all satisfy the corresponding airtightness constraint interval. Further, the mold detection data storage center is connected, and the mold size airtightness constraint interval, the mold ultrasonic airtightness constraint interval, and the mold tracing airtightness constraint interval are obtained according to the historical mold detection data storage records of the mold detection data storage center.

[0112] Further, it is determined whether the mold size air tightness coefficient, the mold ultrasonic air tightness coefficient, and the mold tracing air tightness coefficient in the first mold air tightness detection report meet the corresponding air tightness constraint interval in the mold air tightness constraint condition.

[0113] Furthermore, if the mold size air tightness coefficient, mold ultrasonic air tightness coefficient, and mold tracing air tightness coefficient in the first mold air tightness detection report do not meet the corresponding air tightness constraint intervals in the mold air tightness constraint conditions, indicating that the air tightness of the first lunch box stamping mold is poor, a first air tightness warning signal is generated for air tightness maintenance.

[0114] Among them, judging whether the first mold airtightness detection report satisfies the mold airtightness constraint condition can improve the efficiency of the airtightness detection.

[0115] Embodiment 2

[0116] Based on the same inventive concept as the method for detecting air tightness of the aluminum foil lunch box stamping die in the aforementioned embodiment, Figure 3 For illustration, the present disclosure also provides an aluminum foil lunch box stamping die air tightness detection system, the system comprising:

[0117] A first lunch box stamping die obtaining module 11, wherein the first lunch box stamping die obtaining module 11 is used to obtain a first lunch box stamping die, and the first lunch box stamping die has a mold reference size structure feature corresponding to the mark;

[0118] A mold size air tightness coefficient obtaining module 12, wherein the mold size air tightness coefficient obtaining module 12 is used to perform air tightness detection on the first lunch box stamping mold based on the mold reference size structural characteristics and according to a mold size air tightness detection algorithm to obtain the mold size air tightness coefficient;

[0119] A mold ultrasonic detection result obtaining module 13, wherein the mold ultrasonic detection result obtaining module 13 is used to perform airtightness detection on the first lunch box stamping mold based on an ultrasonic detection terminal to obtain a mold ultrasonic detection result;

[0120] A mold ultrasonic airtightness coefficient obtaining module 14, wherein the mold ultrasonic airtightness coefficient obtaining module 14 is used to analyze the mold ultrasonic detection result based on a pre-constructed ultrasonic airtightness evaluation channel and an ultrasonic airtightness fusion function to obtain the mold ultrasonic airtightness coefficient;

[0121] A tracer detection quantity acquisition module 15, which is used to connect to a gas tracer detection terminal to perform N tracer air tightness tests on the first lunch box stamping die to obtain N tracer detection quantities, wherein N is a positive integer greater than 1, and the gas tracer detection terminal includes a multi-source gas supply device and a gas leakage detection device;

[0122] A tracer detection evaluation function obtaining module 16, wherein the tracer detection evaluation function obtaining module 16 is used to construct a tracer detection evaluation function;

[0123] A mold tracer airtightness coefficient obtaining module 17, wherein the mold tracer airtightness coefficient obtaining module 17 is used to perform airtightness evaluation on the N tracer detection quantities based on the tracer detection evaluation function to obtain a mold tracer airtightness coefficient;

[0124] The first mold air tightness test report obtaining module 18 is used to generate a first mold air tightness test report based on the mold size air tightness coefficient, the mold ultrasonic air tightness coefficient and the mold tracing air tightness coefficient.

[0125] Furthermore, the system further comprises:

[0126] A mold reference body acquisition module, the mold reference body acquisition module is used to connect to the digital twin platform, perform modeling based on the mold reference size and structural features, obtain a mold reference body, and divide the mold reference body into regions to obtain Q sub-reference bodies, where Q is a positive integer greater than 1;

[0127] An actual mold size structure information obtaining module, the actual mold size structure information obtaining module is used to obtain the actual mold size structure information of the first lunch box stamping mold;

[0128] A mold twin acquisition module, wherein the mold twin acquisition module is used to perform modeling based on the digital twin platform and according to the actual mold size and structure information to obtain a mold twin;

[0129] A dimension feature air tightness obtaining module, wherein the dimension feature air tightness obtaining module is used to evaluate the dimension feature air tightness of the mold twin based on the Q sub-reference bodies, and obtain Q dimension feature air tightnesses;

[0130] A cleaning result mean calculation module is used to perform extreme cleaning on the Q size characteristic air densities to obtain size characteristic air density cleaning results, and perform mean calculation on the size characteristic air density cleaning results to generate the mold size air tightness coefficient.

[0131] Furthermore, the system further comprises:

[0132] A first sub-reference volume obtaining module, the first sub-reference volume obtaining module is used to obtain a first sub-reference volume based on the Q sub-reference volumes;

[0133] A first comparison twin acquisition module, wherein the first comparison twin acquisition module is used to align and position the mold twin based on the first sub-reference body to obtain a first comparison twin;

[0134] An actual mold size accuracy obtaining module, the actual mold size accuracy obtaining module is used to obtain the actual mold size accuracy based on the actual mold size structure information, and set a reference size evaluation operator according to the actual mold size accuracy, wherein the reference size evaluation operator is the actual mold size accuracy, and W is a positive integer greater than 1;

[0135] A dimension consistency evaluation result obtaining module, wherein the dimension consistency evaluation result obtaining module is used to perform dimension consistency evaluation on the first sub-reference body and the first comparison twin body based on the reference dimension evaluation operator to obtain a dimension consistency evaluation result;

[0136] A first size characteristic air density obtaining module is used to calculate the mean of the size consistency evaluation results to obtain a first size characteristic air density, and add the first size characteristic air density to the Q size characteristic air densities.

[0137] Furthermore, the system further comprises:

[0138] An ultrasonic airtightness evaluation channel construction module, wherein the ultrasonic airtightness evaluation channel construction module is used to construct the ultrasonic airtightness evaluation channel, wherein the ultrasonic airtightness evaluation channel includes M confidence ultrasonic airtightness evaluators, and the M confidence ultrasonic airtightness evaluators have one-to-one corresponding M airtightness evaluation confidences, and M is a positive integer greater than 1;

[0139] An ultrasonic airtightness evaluation channel processing module, the ultrasonic airtightness evaluation channel processing module is used to input the mold ultrasonic detection result into the ultrasonic airtightness evaluation channel to obtain M ultrasonic airtightness evaluation coefficients output by the M confidence ultrasonic airtightness evaluators;

[0140] An ultrasonic airtightness fusion function processing module, the ultrasonic airtightness fusion function processing module is used to input the M ultrasonic airtightness evaluation coefficients into the ultrasonic airtightness fusion function to generate the ultrasonic airtightness coefficient of the mold;

[0141] An ultrasonic airtight fusion function construction module, wherein the ultrasonic airtight fusion function construction module is used, and the ultrasonic airtight fusion function is:

[0142] ;

[0143] ;

[0144] An ultrasonic airtightness fusion function analysis module, wherein the ultrasonic airtightness fusion function analysis module is used in: Characterize the ultrasonic airtightness coefficient of the mold, Characterize the confidence ultrasonic airtightness evaluation coefficient, Characterizes the i-th ultrasonic airtightness evaluation coefficient, Characterizes the i-th airtightness evaluation confidence level corresponding to the i-th ultrasonic airtightness evaluation coefficient, where i is a positive integer and belongs to M.

[0145] Furthermore, the system further comprises:

[0146] A sample mold ultrasonic test result record set acquisition module, the sample mold ultrasonic test result record set acquisition module is used to connect to the mold test data storage center to obtain the sample mold ultrasonic test result record set and the sample ultrasonic air tightness evaluation record set;

[0147] A preset learning operator obtaining module, wherein the preset learning operator obtaining module is used to obtain a plurality of preset learning channels, wherein each preset learning channel includes a preset learning operator;

[0148] A plurality of preset learning channel acquisition modules, wherein the plurality of preset learning channel acquisition modules are used to perform supervised learning on the sample mold ultrasonic detection result record set and the sample ultrasonic airtightness evaluation record set based on the plurality of preset learning channels, respectively, to obtain a plurality of ultrasonic airtightness evaluators, and the plurality of ultrasonic airtightness evaluators have corresponding plurality of airtightness evaluation accuracy rates;

[0149] An airtightness evaluation confidence acquisition module is used to sort the multiple ultrasonic airtightness evaluators based on the multiple airtightness evaluation accuracy rates, output the first M ultrasonic airtightness evaluators as the M confident ultrasonic airtightness evaluators, and mark the M confident ultrasonic airtightness evaluators according to the multiple airtightness evaluation accuracy rates to obtain the M airtightness evaluation confidence rates.

[0150] Furthermore, the system further comprises:

[0151] A first preset learning channel obtaining module, the first preset learning channel obtaining module is used to obtain a first preset learning channel based on the multiple preset learning channels;

[0152] A first ultrasonic airtightness analyzer acquisition module, wherein the first ultrasonic airtightness analyzer acquisition module is used to perform supervised learning on the sample mold ultrasonic detection result record set and the sample ultrasonic airtightness evaluation record set based on the first preset learning channel to obtain a first ultrasonic airtightness analyzer;

[0153] A first ultrasonic airtightness analysis accuracy acquisition module, the first ultrasonic airtightness analysis accuracy acquisition module is used to connect to the mold detection data storage center, obtain an ultrasonic airtightness evaluation test set, and test the first ultrasonic airtightness analyzer based on the ultrasonic airtightness evaluation test set to obtain a first ultrasonic airtightness analysis accuracy;

[0154] A first ultrasonic airtightness analysis accuracy judgment module, wherein the first ultrasonic airtightness analysis accuracy judgment module is used to judge whether the first ultrasonic airtightness analysis accuracy is greater than a preset analysis accuracy;

[0155] A plurality of ultrasonic airtightness evaluator acquisition modules, wherein the plurality of ultrasonic airtightness evaluator acquisition modules are used to set the first ultrasonic airtightness analyzer as a first ultrasonic airtightness evaluator if the first ultrasonic airtightness analysis accuracy is greater than the preset analysis accuracy, identify the first ultrasonic airtightness analysis accuracy as a first airtightness evaluation accuracy corresponding to the first ultrasonic airtightness evaluator, and add the first ultrasonic airtightness evaluator to the plurality of ultrasonic airtightness evaluators;

[0156] An incremental learning module, wherein the incremental learning module is used to perform incremental learning on the first ultrasonic airtightness analyzer until the first ultrasonic airtightness evaluator is generated if the accuracy of the first ultrasonic airtightness analysis is less than / equal to the preset analysis accuracy.

[0157] Furthermore, the system further comprises:

[0158] A tracer detection evaluation function construction module, the tracer detection evaluation function construction module is used to construct the tracer detection evaluation function, the tracer detection evaluation function is:

[0159] ;

[0160] ;

[0161] ;

[0162] A tracer detection evaluation function construction processing module, wherein the tracer detection evaluation function construction processing module is used in: Characterize the mold tracer air tightness coefficient, Characterizes the reliable tracer detection quantity, n is a positive integer, and n belongs to N, Characterize the nth tracer detection quantity, Tracer detection stability, are the credible tracer weight and the stable tracer weight respectively, and, The sum is 1.

[0163] Furthermore, the system further comprises:

[0164] A mold airtightness constraint condition obtaining module, wherein the mold airtightness constraint condition obtaining module is used to obtain the mold airtightness constraint condition, wherein the mold airtightness constraint condition is that the mold size airtightness coefficient satisfies the mold size airtightness constraint interval, and the mold ultrasonic airtightness coefficient satisfies the mold ultrasonic airtightness constraint interval, and the mold tracing airtightness coefficient satisfies the mold tracing airtightness constraint interval;

[0165] A mold air tightness constraint condition judgment module, the mold air tightness constraint condition judgment module is used to judge whether the first mold air tightness detection report meets the mold air tightness constraint condition;

[0166] The first airtightness warning signal obtaining module is used to generate a first airtightness warning signal if the first mold airtightness detection report does not meet the mold airtightness constraint condition.

[0167] The specific example of the method for detecting air tightness of the aluminum foil lunch box stamping die in the aforementioned embodiment 1 is also applicable to the air tightness detection system for the aluminum foil lunch box stamping die in this embodiment. Through the aforementioned detailed description of the method for detecting air tightness of the aluminum foil lunch box stamping die, those skilled in the art can clearly know the air tightness detection system for the aluminum foil lunch box stamping die in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0168] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of this disclosure can be achieved, and this document is not limited here.

[0169] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for detecting air tightness of aluminum foil lunch box stamping die, characterized in that: The method comprises: Obtaining a first lunch box stamping die, wherein the first lunch box stamping die has a corresponding identified die reference dimension structure feature; Based on the mold reference size structural features, the first lunch box stamping mold is subjected to an airtightness test according to a mold size airtightness test algorithm to obtain a mold size airtightness coefficient; Performing air tightness testing on the first lunch box stamping die based on an ultrasonic testing terminal to obtain an ultrasonic testing result of the die; The ultrasonic airtightness coefficient of the mold is obtained by analyzing the ultrasonic testing result of the mold based on the pre-constructed ultrasonic airtightness evaluation channel and the ultrasonic airtightness fusion function; Connecting a gas tracing detection terminal to perform N tracing air tightness tests on the first lunch box stamping die to obtain N tracing detection quantities, wherein N is a positive integer greater than 1, and the gas tracing detection terminal includes a multi-source gas supply device and a gas leakage detection device; Constructing the evaluation function of tracer detection; Based on the tracer detection evaluation function, the air tightness of the N tracer detection quantities is evaluated to obtain a mold tracer air tightness coefficient; Generate a first mold air tightness test report based on the mold size air tightness coefficient, the mold ultrasonic air tightness coefficient and the mold tracing air tightness coefficient; Among them, based on the mold reference size structural features, the first lunch box stamping mold is tested for air tightness according to the mold size air tightness detection algorithm to obtain the mold size air tightness coefficient, including: Connecting to the digital twin platform, modeling based on the mold reference size and structural features to obtain a mold reference body, and dividing the mold reference body into regions to obtain Q sub-reference bodies, where Q is a positive integer greater than 1; Obtaining actual mold size and structure information of the first lunch box stamping mold; Based on the digital twin platform, modeling is performed according to the actual mold size and structure information to obtain a mold twin; Based on the Q sub-reference bodies, evaluating the air tightness of the mold twin body according to the size characteristics, and obtaining Q air tightness values ​​of the size characteristics; Performing extreme value cleaning on the Q size characteristic air densities to obtain size characteristic air density cleaning results, and performing mean calculation on the size characteristic air density cleaning results to generate the mold size air tightness coefficient; The ultrasonic airtightness coefficient of the mold is obtained by analyzing the ultrasonic detection result of the mold based on the pre-constructed ultrasonic airtightness evaluation channel and the ultrasonic airtightness fusion function, including: Constructing the ultrasonic airtightness evaluation channel, wherein the ultrasonic airtightness evaluation channel includes M confidence ultrasonic airtightness evaluators, and the M confidence ultrasonic airtightness evaluators have one-to-one corresponding M airtightness evaluation confidences, and M is a positive integer greater than 1; Inputting the ultrasonic detection result of the mold into the ultrasonic airtightness evaluation channel to obtain M ultrasonic airtightness evaluation coefficients output by the M confidence ultrasonic airtightness evaluators; Inputting the M ultrasonic airtightness evaluation coefficients into the ultrasonic airtightness fusion function to generate the ultrasonic airtightness coefficient of the mold; Wherein, the ultrasonic airtight fusion function is: ； ； in, Characterize the ultrasonic airtightness coefficient of the mold, Characterize the confidence ultrasonic airtightness evaluation coefficient, Characterizes the i-th ultrasonic airtightness evaluation coefficient, Characterizes the i-th airtightness evaluation confidence corresponding to the i-th ultrasonic airtightness evaluation coefficient, and i is a positive integer, i belongs to M; Wherein, constructing the ultrasonic airtightness evaluation channel includes: Connect to the mold inspection data storage center to obtain the sample mold ultrasonic inspection result record set and the sample ultrasonic air tightness evaluation record set; Obtaining a plurality of preset learning channels, wherein each preset learning channel includes a preset learning operator; Based on the multiple preset learning channels, supervised learning is performed on the sample mold ultrasonic detection result record set and the sample ultrasonic airtightness evaluation record set respectively to obtain multiple ultrasonic airtightness evaluators, and the multiple ultrasonic airtightness evaluators have corresponding multiple airtightness evaluation accuracy rates; The multiple ultrasonic airtightness evaluators are sorted based on the multiple airtightness evaluation accuracies, the first M ultrasonic airtightness evaluators are output as the M confident ultrasonic airtightness evaluators, and the M confident ultrasonic airtightness evaluators are labeled according to the multiple airtightness evaluation accuracies to obtain the M airtightness evaluation confidences.

2. The method according to claim 1, characterized in that Based on the Q sub-reference bodies, the mold twin body is evaluated for dimensional characteristic air tightness to obtain Q dimensional characteristic air tightness values, including: Based on the Q sub-reference volumes, obtaining a first sub-reference volume; Performing registration and positioning on the mold twin based on the first sub-reference body to obtain a first comparison twin; Based on the actual mold size structure information, the actual mold size accuracy is obtained, and according to the actual mold size accuracy, a reference size evaluation operator is set, wherein the reference size evaluation operator is the actual mold size accuracy. , and W is a positive integer greater than 1; Based on the reference size evaluation operator, performing a size consistency evaluation on the first sub-reference body and the first comparison twin body to obtain a size consistency evaluation result; The size consistency evaluation results are averaged to obtain a first size characteristic air density, and the first size characteristic air density is added to the Q size characteristic air densities.

3. The method according to claim 1, characterized in that Get multiple ultrasonic airtightness evaluators, including: Based on the multiple preset learning channels, obtaining a first preset learning channel; Based on the first preset learning channel, supervised learning is performed on the sample mold ultrasonic detection result record set and the sample ultrasonic airtightness evaluation record set to obtain a first ultrasonic airtightness analyzer; Connecting to the mold detection data storage center to obtain an ultrasonic airtightness evaluation test set, and testing the first ultrasonic airtightness analyzer based on the ultrasonic airtightness evaluation test set to obtain a first ultrasonic airtightness analysis accuracy rate; Determining whether the first ultrasonic airtightness analysis accuracy is greater than a preset analysis accuracy; If the first ultrasonic airtightness analysis accuracy is greater than the preset analysis accuracy, the first ultrasonic airtightness analyzer is set as a first ultrasonic airtightness evaluator, the first ultrasonic airtightness analysis accuracy is identified as the first airtightness evaluation accuracy corresponding to the first ultrasonic airtightness evaluator, and the first ultrasonic airtightness evaluator is added to the multiple ultrasonic airtightness evaluators; If the first ultrasonic airtightness analysis accuracy is less than / equal to the preset analysis accuracy, incremental learning is performed on the first ultrasonic airtightness analyzer until the first ultrasonic airtightness evaluator is generated.

4. The method according to claim 1, characterized in that Construct a tracer detection evaluation function, including: The tracer detection evaluation function is constructed, and the tracer detection evaluation function is: ； ； ； in, Characterize the mold tracer air tightness coefficient, The credible tracer detection quantity, n is a positive integer, and n belongs to N, Characterize the nth tracer detection quantity, Tracer detection stability, α and β are the credible tracer weight and stable tracer weight respectively, and the sum of α and β is 1.

5. The method according to claim 1, characterized in that After generating the first mold air tightness test report, the method includes: Obtaining a mold airtightness constraint condition, wherein the mold airtightness constraint condition is that the mold size airtightness coefficient satisfies the mold size airtightness constraint interval, and the mold ultrasonic airtightness coefficient satisfies the mold ultrasonic airtightness constraint interval, and the mold tracing airtightness coefficient satisfies the mold tracing airtightness constraint interval; Determining whether the first mold air tightness test report meets the mold air tightness constraint condition; If the first mold air tightness detection report does not meet the mold air tightness constraint condition, a first air tightness warning signal is generated.

6. Aluminum foil lunch box stamping die air tightness detection system, characterized in that: Used to implement the method for detecting air tightness of an aluminum foil lunch box stamping die according to any one of claims 1 to 5, the system comprises: A first lunch box stamping die obtaining module, wherein the first lunch box stamping die obtaining module is used to obtain a first lunch box stamping die, and the first lunch box stamping die has a mold reference size structural feature corresponding to the mark; A mold size air tightness coefficient acquisition module, the mold size air tightness coefficient acquisition module is used to perform air tightness detection on the first lunch box stamping mold based on the mold reference size structure characteristics and according to the mold size air tightness detection algorithm to obtain the mold size air tightness coefficient; A mold ultrasonic detection result acquisition module, which is used to perform airtightness detection on the first lunch box stamping mold based on an ultrasonic detection terminal to obtain a mold ultrasonic detection result; A mold ultrasonic airtightness coefficient acquisition module, wherein the mold ultrasonic airtightness coefficient acquisition module is used to analyze the mold ultrasonic detection result based on a pre-constructed ultrasonic airtightness evaluation channel and an ultrasonic airtightness fusion function to obtain the mold ultrasonic airtightness coefficient; A tracer detection quantity acquisition module, the tracer detection quantity acquisition module is used to connect to a gas tracer detection terminal to perform N tracer air tightness tests on the first lunch box stamping die to obtain N tracer detection quantities, wherein N is a positive integer greater than 1, and the gas tracer detection terminal includes a multi-source gas supply device and a gas leakage detection device; A tracer detection evaluation function acquisition module, wherein the tracer detection evaluation function acquisition module is used to construct a tracer detection evaluation function; A mold tracer airtightness coefficient obtaining module, the mold tracer airtightness coefficient obtaining module is used to perform airtightness evaluation on the N tracer detection quantities based on the tracer detection evaluation function to obtain the mold tracer airtightness coefficient; The first mold air tightness detection report obtaining module is used to generate a first mold air tightness detection report based on the mold size air tightness coefficient, the mold ultrasonic air tightness coefficient and the mold tracing air tightness coefficient.

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