Quality detection method, device and equipment for electronic cigarette

Abstract

The invention provides an electronic cigarette quality detection method, device and equipment, and the method comprises the steps: carrying out the component detection of an electronic cigarette based on a smoke component analyzer, and forming a smoke component parameter set; collecting electrical parameters of the electronic cigarette to form an electrical parameter set; measuring physical characteristic parameters, and constructing a physical parameter set; performing dimension reduction analysis on the smoke component parameter set, the electrical parameter set and the physical parameter set based on a principal component analysis method, extracting corresponding key feature parameters, and allocating weights for the key feature parameters based on an analytic hierarchy process; inputting each key feature parameter with the distributed weight into a pre-trained quality evaluation model, and outputting a quality grade score of the electronic cigarette; and for the qualified electronic cigarette with the quality grade score higher than a threshold value, generating an encrypted two-dimensional code containing all key feature parameters and the quality grade score, and associatively storing the encrypted two-dimensional code in a block chain tracing system. According to the invention, product quality evaluation is carried out on the whole, and product quality tracing is carried out.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a quality detection method, device and equipment for electronic cigarettes. Background Art

[0002] Traditional e-cigarette quality testing methods have many limitations. Traditional e-cigarette quality testing usually only conducts quality testing in a single dimension, such as judging the quality of e-cigarettes based on the smoke composition of e-cigarettes, or only conducting quality testing based on the electrical parameters of e-cigarettes. Without effectively correlating multiple aspects of data such as smoke composition, electrical properties, and physical properties, it is difficult to judge product quality from a holistic perspective.

[0003] Furthermore, in the existing quality inspection process, there is no product quality traceability, and the root cause of the problem cannot be accurately located, which brings great difficulties to subsequent quality improvement and problem troubleshooting, and it is difficult to meet the requirements for traceability management of the product throughout its life cycle. Summary of the invention

[0004] The main purpose of the present invention is to provide an electronic cigarette quality inspection method, device and equipment, aiming to overcome the defects of being unable to associate smoke composition, electrical and physical property data for comprehensive quality inspection and the lack of product quality traceability.

[0005] To achieve the above object, the present invention provides a method for detecting the quality of an electronic cigarette, comprising the following steps: The smoke generated by the electronic cigarette is tested based on the smoke component analyzer to form a smoke component parameter set; the electrical parameters of the electronic cigarette are collected to form an electrical parameter set; the physical characteristic parameters of the electronic cigarette are measured to construct a physical parameter set; Based on the principal component analysis method, the dimensionality reduction analysis is performed on the smoke component parameter set, the electrical parameter set and the physical parameter set, the corresponding key characteristic parameters are extracted, and a weight is assigned to each key characteristic parameter based on the hierarchical analysis method; Inputting each of the key characteristic parameters with assigned weights into a pre-trained quality assessment model, and outputting a quality grade score of the electronic cigarette; For qualified e-cigarettes with a quality grade score higher than the threshold, an encrypted QR code containing all its key characteristic parameters and quality grade score is generated, and the encrypted QR code is associated with the corresponding e-cigarette product information and stored in the blockchain traceability system.

[0006] Furthermore, after outputting the quality grade score of the electronic cigarette, the method further includes: Determine the electronic cigarettes whose quality grade score is lower than the threshold as unqualified products, and perform defect analysis on the smoke component parameter set, electrical parameter set and physical parameter set; Store defect analysis results in the blockchain traceability system.

[0007] Furthermore, the step of assigning weights to each key feature parameter based on the hierarchical analysis method includes: The smoke component parameter set, electrical parameter set, and physical property parameter set are used as the criterion layer, and the key characteristic parameters under each parameter set are used as the indicator layer; Based on data mining, the influence of each parameter set on the quality of the electronic cigarette is analyzed to determine the relative importance between the elements of the criterion layer and the relative importance of the elements of the indicator layer relative to the criterion layer, and generate a judgment matrix; Solving the maximum eigenvalue of the judgment matrix and obtaining its corresponding eigenvector; performing normalization operation on the eigenvector to obtain the initial weight vector of each indicator layer relative to the criterion layer; Calculating the consistency ratio of the judgment matrix, and judging whether the consistency ratio meets the requirement; If the consistency ratio meets the requirement, the current initial weight vector is confirmed, and weights are assigned to each key feature parameter.

[0008] Further, after determining whether the consistency ratio meets the requirement, it also includes: If not, the element values ​​of the judgment matrix are automatically adjusted, and the weight vectors of each indicator layer relative to the criterion layer are recalculated until the consistency ratio meets the requirement.

[0009] Furthermore, an encrypted QR code containing all its key characteristic parameters and quality grade scores is generated, including: Generate an encryption key based on the smoke composition parameter set, the electrical parameter set, and the physical parameter set; Encrypting the key characteristic parameters and the quality grade score based on the encryption key to obtain encrypted data; The encrypted data is added to the QR code to generate the encrypted QR code.

[0010] Further, based on the smoke component parameter set, the electrical parameter set and the physical parameter set, an encryption key is generated, including: Extracting multiple key values ​​from the smoke component parameter set, electrical parameter set, and physical parameter set; recombining and arranging each key value to form a data string; Based on the length of the data string, selecting a corresponding base point on a preset elliptic curve domain; Based on the preset elliptic curve domain and base point, each key value in the data string is used as a scalar to perform a scalar multiplication operation to generate a plurality of elliptic curve points; The coordinate values ​​of each elliptic curve point are converted into a code string; Generate a pseudo-random noise sequence, perform a bitwise XOR operation on the pseudo-random noise sequence and the encoding string, and generate the encryption key.

[0011] Further, based on the smoke component parameter set, the electrical parameter set and the physical parameter set, an encryption key is generated, including: Encoding the smoke component parameter set, the electrical parameter set, and the physical parameter set to obtain encoded data; Add the characters in the coded data to the data table one by one in order to generate a coded data table; Extracting values ​​from the smoke component parameter set to generate a first curve; based on the first curve, deforming the coded data table to obtain a deformed data table; Extracting values ​​from the electrical parameter set to generate a second curve; extracting values ​​from the physical parameter set to generate a third curve; The second curve and the third curve are superimposed on the deformation data table, and the cells in the deformation data table whose positional relationships with the second curve and the third curve meet the preset conditions are used as target cells. The characters in the target cells are combined in sequence to obtain the encryption key.

[0012] The present invention also provides an electronic cigarette quality detection device, comprising: The collection unit is used to detect the components of the smoke generated by the electronic cigarette based on the smoke component analyzer to form a smoke component parameter set; collect the electrical parameters of the electronic cigarette to form an electrical parameter set; measure the physical characteristic parameters of the electronic cigarette to construct a physical parameter set; An extraction unit, used for performing dimensionality reduction analysis on the smoke component parameter set, the electrical parameter set and the physical parameter set respectively based on the principal component analysis method, extracting corresponding key characteristic parameters, and assigning weights to each key characteristic parameter based on the hierarchical analysis method; An evaluation unit, used for inputting each of the key characteristic parameters with assigned weights into a pre-trained quality evaluation model, and outputting a quality grade score of the electronic cigarette; The storage unit is used to generate an encrypted QR code containing all key characteristic parameters and quality grade scores of qualified electronic cigarettes with quality grade scores higher than a threshold, and associate the encrypted QR code with the corresponding electronic cigarette product information and store it in the blockchain traceability system.

[0013] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods when executing the computer program.

[0014] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned methods are implemented.

[0015] The quality detection method, device and equipment of the electronic cigarette provided by the present invention include: based on the smoke component analyzer, the smoke generated by the electronic cigarette is detected to form a smoke component parameter set; the electrical parameters of the electronic cigarette are collected to form an electrical parameter set; the physical characteristic parameters of the electronic cigarette are measured to construct a physical parameter set; based on the principal component analysis method, the smoke component parameter set, the electrical parameter set and the physical parameter set are respectively subjected to dimensionality reduction analysis, the corresponding key characteristic parameters are extracted, and weights are assigned to each key characteristic parameter based on the hierarchical analysis method; each of the key characteristic parameters with assigned weights is input into a pre-trained quality assessment model, and the quality grade score of the electronic cigarette is output; for qualified electronic cigarettes with a quality grade score higher than a threshold, an encrypted two-dimensional code containing all its key characteristic parameters and quality grade scores is generated, and the encrypted two-dimensional code is associated with the corresponding electronic cigarette product information and stored in a blockchain traceability system. In the present invention, the quality detection of the electronic cigarette is carried out by combining the smoke component parameter set, the electrical parameter set and the physical parameter set, and the product quality is evaluated from the overall perspective; at the same time, an encrypted two-dimensional code containing all its key characteristic parameters and quality grade scores is generated, and the product quality of the product after quality detection is effectively traced. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a schematic diagram of the steps of a quality detection method for an electronic cigarette in one embodiment of the present invention; Figure 2 is a structural block diagram of a quality detection device for an electronic cigarette in one embodiment of the present invention; Figure 3 It is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0017] The implementation, functional features and advantages of the present invention will be further described in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] Reference Figure 1 In one embodiment of the present invention, a method for detecting the quality of an electronic cigarette is provided, comprising the following steps: Step S1, detecting the components of the smoke generated by the electronic cigarette based on the smoke component analyzer to form a smoke component parameter set; collecting the electrical parameters of the electronic cigarette to form an electrical parameter set; measuring the physical characteristic parameters of the electronic cigarette to construct a physical parameter set; Step S2, performing dimensionality reduction analysis on the smoke component parameter set, the electrical parameter set, and the physical parameter set based on the principal component analysis method, extracting corresponding key characteristic parameters, and assigning weights to each key characteristic parameter based on the hierarchical analysis method; Step S3, inputting each of the key feature parameters with assigned weights into a pre-trained quality assessment model, and outputting a quality grade score of the electronic cigarette; Step S4, for qualified electronic cigarettes with quality grade scores higher than the threshold, generate an encrypted QR code containing all its key characteristic parameters and quality grade scores, and associate the encrypted QR code with the corresponding electronic cigarette product information and store it in the blockchain traceability system.

[0020] In this embodiment, as described in step S1 above, the smoke component analyzer uses spectral analysis, chromatographic separation and other technologies to accurately identify and quantify various chemical components in the smoke. For example, the exact content of nicotine can be accurately determined, and its accuracy can reach the milligram level or even the microgram level to ensure compliance with different management standards; for common solvents such as propylene glycol and glycerol, their ratio can be accurately analyzed, which is not only related to the taste and amount of smoke, but also closely related to the safety of electronic cigarettes, because improper ratios may cause the smoke to be too irritating or produce harmful cracking products. At the same time, a variety of potentially harmful components such as aldehydes and ketones, such as formaldehyde, acetaldehyde, acetone, etc., are strictly tested. Therefore, it is very important to accurately grasp its content, and all these detected data are summarized to form a smoke component parameter set.

[0021] Through professional electrical measuring instruments, such as high-precision oscilloscopes and multimeters, multiple electrical parameters of electronic cigarettes in working state are monitored in real time. Voltage stability is one of the key indicators. Unstable voltage may cause abnormal temperature fluctuations of the heating wire, which will affect the smoke generation effect on the one hand, accelerate the aging of the heating wire on the other hand, and even cause the risk of short circuit. The measurement of current intensity can reflect the power consumption of the electronic cigarette, and the battery life can be calculated in combination with the battery capacity. If the current increases abnormally, there is a risk of leakage in the circuit. In addition, it also includes the precise measurement of resistance value. The change of resistance can reflect the material uniformity and working state of the heating wire. For example, local oxidation of the heating wire will cause the resistance to increase, which will affect the heating efficiency and smoke quality. These electrical parameters are integrated into an electrical parameter set.

[0022] The testing work is carried out using high-precision three-dimensional measuring instruments, material hardness testers and other equipment. From the perspective of appearance size, the length, diameter, thickness and other parameters of the electronic cigarette shell are accurately measured to ensure that it meets the requirements of ergonomic design. At the same time, the tolerance is controlled within a very small range to prevent poor assembly or affect the user's grip comfort due to dimensional deviation; material property testing covers the hardness, wear resistance and corrosion resistance of the shell material. For example, for a shell made of aluminum alloy, it is necessary to test whether its hardness meets the standard to resist daily scratches, as well as its corrosion resistance under environmental factors such as sweat and air, to prevent the shell from rusting and fading, affecting the appearance and product life; for internal parts, the assembly gap of each component is carefully measured. Minor improper assembly may cause looseness, friction noise or even functional failure. For example, the connection gap between the atomizer core and the battery assembly is unreasonable, resulting in poor contact and affecting the atomization effect. These physical property parameters are combined to construct a physical property parameter set.

[0023] As described in step S2 above, principal component analysis (PCA) is a mathematical tool that can project a high-dimensional data space into a low-dimensional subspace while retaining the main information characteristics of the data to the greatest extent. Taking the smoke component parameter set as an example, there is a certain correlation between many chemical component data. PCA transforms these related variables into a few unrelated principal components through linear transformation, and each principal component is a linear combination of the original variables. For example, when detecting a variety of aldehyde substances, it is found that the content change trends of some aldehydes are highly similar. PCA can extract a principal component that comprehensively reflects the overall situation of aldehydes, thereby reducing the data dimension and avoiding redundant information from interfering with subsequent analysis. The same is true for the electrical and physical property parameter sets. The most representative key characteristic parameters are extracted respectively. These key characteristic parameters carry the core information of each parameter set and are the key basis for judging the quality of electronic cigarettes.

[0024] The above-mentioned analytic hierarchy process (AHP) constructs a hierarchical structure, taking the comprehensive evaluation of e-cigarette quality as the target layer, the smoke composition, electrical properties, and physical property parameter sets as the criterion layer, and the key characteristic parameters under each parameter set as the indicator layer. For each element in the criterion layer and the indicator layer, the relative importance of the quality of the e-cigarette is compared and scored in pairs, and the relative importance is quantified using the 1-9 scale method to construct a judgment matrix. For example, based on a large amount of experimental data and market feedback, it is believed that the smoke composition has a significant impact on human health and is more critical in quality assessment than electrical parameters, so a higher relative score is given. Then, the characteristic root method is used with the help of professional statistical software to calculate the maximum characteristic root and corresponding eigenvector of the judgment matrix, and the eigenvector is normalized to obtain the initial weight vector of each indicator layer relative to the criterion layer. Then, the rationality of the weight distribution is ensured through consistency test, and finally the comprehensive weight of each key characteristic parameter relative to the target layer is determined, so that the subsequent quality assessment model can run accurately according to the true importance of each parameter.

[0025] As described in step S3 above, the pre-trained quality assessment model is constructed based on a deep learning framework, such as a multi-layer neural network structure. In the model training stage, a large amount of electronic cigarette sample data covering different brands, models, and production batches is collected. The above samples are accompanied by accurate quality grade annotations, which are determined by professional laboratories in combination with complex processes such as human inhalation experiments and comprehensive physical and chemical performance tests. The key characteristic parameters (with weights) of the sample are used as input, and the quality grade is used as the output label. Through repeated iterative training, the model continuously adjusts the internal neuron connection weights and learns the characteristic patterns of electronic cigarettes with different quality levels. When faced with the input of the key characteristic parameters of the electronic cigarette to be tested, the model performs complex nonlinear operations based on the learned patterns, comprehensively considers the weights and interrelationships of each parameter, and finally outputs a continuous quality grade score, which intuitively reflects the comprehensive quality level of the electronic cigarette in terms of composition, electrical properties, physical properties, etc., for example, 0-100 points. The higher the score, the better the quality, providing a quantitative basis for subsequent quality judgment.

[0026] As described in step S4 above, first, all the key characteristic parameters of the electronic cigarette (including the final data after dimension reduction and weighted processing of smoke composition, electrical properties, physical properties, etc.) and the quality grade score are integrated, and the hash function is used to hash these data and map them to a hash value of fixed length to ensure the uniqueness and integrity of the data and prevent data tampering. Then, the hashed data is encrypted using an encryption algorithm to generate an encrypted ciphertext, and based on this ciphertext combined with the QR code generation rules, an encrypted QR code with a complex pattern is generated. This QR code not only carries rich quality information of the electronic cigarette, but also, due to the encryption process, outsiders cannot easily obtain the content, effectively protecting the privacy of product quality data, while providing a reliable data carrier for subsequent traceability and verification.

[0027] The above-mentioned blockchain traceability system uses its distributed ledger technology, and each node saves a complete or partial copy of the ledger to ensure that the data cannot be tampered with and is highly reliable. The encrypted QR code is associated with the production batch number, production date, production equipment number, raw material supplier information and other product information of the e-cigarette, and then uploaded to the blockchain network after being packaged in a specific data structure. When it is necessary to trace the source of product quality, whether it is consumers or enterprises themselves, they only need to scan the encrypted QR code on the e-cigarette and trigger the data query command through the smart contract on the blockchain. Detailed information on the entire process from raw material procurement, production and processing to quality inspection can be quickly and accurately obtained, realizing the full life cycle traceability of product quality information, greatly improving the transparency and efficiency of quality control.

[0028] In one embodiment, after outputting the quality grade score of the electronic cigarette, the method further includes: Determine the electronic cigarettes whose quality grade score is lower than the threshold as unqualified products, and perform defect analysis on the smoke component parameter set, electrical parameter set and physical parameter set; Store defect analysis results in the blockchain traceability system.

[0029] In this embodiment, when the quality grade score of the electronic cigarette is lower than a preset threshold, it is directly classified as a substandard product based on clear and quantitative standards.

[0030] For smoke composition, we conduct an in-depth comparison between the standard composition range of qualified products and the actual test data of unqualified products. We focus on whether the nicotine content deviates from the reasonable range; analyze whether the ratio of propylene glycol and glycerol is unbalanced, and closely monitor whether harmful components such as aldehydes and ketones exceed the standard. We use chemical data analysis software and combine it with big data statistical models to accurately locate the factors that lead to unqualified smoke composition, such as excessive impurities in raw materials, poor temperature control during the atomization process, or improper use of flavor additives, etc., to provide key information for subsequent improvements in production processes.

[0031] Check the voltage stability of the e-cigarette. Unstable voltage performance indicates defects in the circuit design, such as capacitor leakage and poor performance of the voltage stabilizing chip. This not only affects the atomization effect, but may also cause battery overheating due to excessive voltage, or low voltage resulting in less smoke. By monitoring the current fluctuation curve, determine whether there are abnormal current spikes or troughs. Abnormal current may mean that there are short circuits or circuit breaks in the circuit, or that the load capacity of the electronic components does not match. Analyze the gap between the battery life and the nominal value. If the battery life is significantly lower than expected, it may be that the battery capacity is falsely marked, the battery ages too quickly, or the power management chip consumes too much energy. These problems require accurate diagnosis to optimize electrical performance and ensure product safety and reliability.

[0032] For the appearance dimensions, compare the standard tolerances of the design drawings to check whether there are dimensional deviations caused by mold wear and rough processing technology. Too large or too small dimensions may affect the tightness of the product assembly, causing parts to loosen or fall off, and even affecting the user's grip. Evaluate the material properties of the shell. For example, if the hardness does not meet the standard, the product is prone to scratches and wear during daily use, affecting the appearance and product life; if the material has poor corrosion resistance, the shell is prone to rust and fade after contact with sweat, humid air and other environments. For internal assembly gaps, use high-precision image measurement equipment to review. Too large gaps may cause friction and collision of parts to produce noise, and even affect the normal operation of key functional components such as atomizer cores and heating wires. Through careful analysis, find out the potential root causes of problems in the physical structure.

[0033] Finally, through the consensus mechanism between blockchain nodes, the data block is uploaded and stored in the blockchain network, ensuring that each node has a complete or partial copy, ensuring the data is tamper-proof and traceable.

[0034] In one embodiment, the step of assigning weights to the key feature parameters based on the hierarchical analysis method includes: The smoke component parameter set, electrical parameter set, and physical property parameter set are used as the criterion layer, and the key characteristic parameters under each parameter set are used as the indicator layer; Based on data mining, the influence of each parameter set on the quality of the electronic cigarette is analyzed to determine the relative importance between the elements of the criterion layer and the relative importance of the elements of the indicator layer relative to the criterion layer, and generate a judgment matrix; Solving the maximum eigenvalue of the judgment matrix and obtaining its corresponding eigenvector; performing normalization operation on the eigenvector to obtain the initial weight vector of each indicator layer relative to the criterion layer; Calculating the consistency ratio of the judgment matrix, and judging whether the consistency ratio meets the requirement; If the consistency ratio meets the requirement, the current initial weight vector is confirmed and weights are assigned to each key feature parameter. If not, the element values ​​of the judgment matrix are automatically adjusted and the weight vectors of each indicator layer relative to the criterion layer are recalculated until the consistency ratio meets the requirement.

[0035] In this embodiment, the smoke component parameter set, electrical parameter set, and physical property parameter set are used as the criterion layer, and the key characteristic parameters under each parameter set are used as the indicator layer. This step is the basic framework for constructing the hierarchical analysis model. Through such stratification, the logical context of the quality assessment of electronic cigarettes is clearly sorted out. The criterion layer divides the key areas that affect the quality of electronic cigarettes from a large category, and the many key characteristic parameters covered in each area are presented in detail in the indicator layer. For example, the smoke component parameter set includes key characteristic parameters such as nicotine content, harmful aldehyde content, and atomizer ratio; the key characteristic parameters under the electrical parameter set, such as voltage stability, battery life, and charging efficiency, determine the power supply performance of the electronic cigarette; the key characteristic parameters covered by the physical property parameter set, such as the hardness of the shell material, the assembly accuracy of the components, and the tolerance of the product appearance dimensions, affect the durability and assembly quality of the product. This hierarchical structure provides an orderly framework for the subsequent precise quantification of the importance of each parameter.

[0036] Based on data mining, the influence of each parameter set on the quality of e-cigarettes is analyzed to determine the relative importance of the elements in the criterion layer and the relative importance of the elements in the indicator layer relative to the criterion layer, and generate a judgment matrix. Data mining technology uses algorithms such as association analysis and cluster analysis to deeply explore the rules behind the data. For the criterion layer, from a macro perspective, for example, by analyzing a large number of health complaint cases caused by smoke composition problems, safety accident reports caused by electrical failures, and user negative reviews due to poor physical properties, combined with product recall data, after-sales repair frequency and other information, the relative importance of the three criterion layer elements of smoke composition, electrical properties, and physical properties in the overall quality is quantified. At the indicator layer, with the help of data mining, for the smoke component parameter set, the market acceptance of products with different nicotine content and the impact of different harmful aldehyde contents on the changes in health indicators of long-term users are compared to accurately determine the importance ranking of each key characteristic parameter relative to the criterion layer to which it belongs. Based on these in-depth analysis results, the 1-9 scaling method is used to construct a judgment matrix to numerically quantify the relative importance of each element, providing the original data basis for subsequent weight calculations.

[0037] Solve the maximum eigenvalue of the judgment matrix and obtain its corresponding eigenvector; normalize the eigenvector to obtain the initial weight vector of each indicator layer relative to the criterion layer. Solving the maximum eigenvalue and the corresponding eigenvector is one of the core mathematical operation steps of the hierarchical analysis method. Use mathematical software or algorithm library to input the constructed judgment matrix, and obtain its maximum eigenvalue and corresponding eigenvector through iterative calculation. Each component of the eigenvector represents a relative weight tendency of the corresponding indicator layer element under the criterion layer to which it belongs, but the values ​​of each component are not normalized at this time, and the sum is not necessarily 1. Perform normalization operation, that is, divide each component of the eigenvector by the sum of all components, so that each component is readjusted to a proportion form, and obtain the initial weight vector of each indicator layer relative to the criterion layer, which preliminarily shows the weight distribution of each key characteristic parameter under the criterion to which it belongs, and prepares for subsequent consistency test and final weight determination.

[0038] Calculate the consistency ratio of the judgment matrix and determine whether the consistency ratio meets the requirements. The above consistency ratio is a key indicator to measure the rationality of the judgment matrix. In the process of constructing the judgment matrix, due to the use of the 1-9 scale method based on experience and data analysis to compare and score two by two, there is a certain degree of subjectivity or data error accumulation, resulting in internal logical inconsistency in the judgment matrix. The consistency ratio is calculated by a specific formula. The formula generally involves calculating the consistency index (CI), CI = (λmax- n) / (n - 1), where λmax is the maximum characteristic root, n is the order of the judgment matrix, and then combined with the average random consistency index (RI) table to obtain the corresponding RI value, and finally calculate the consistency ratio (CR) = CI / RI. If CR < 0.1, the judgment matrix passes the consistency test, which means that the constructed judgment matrix is ​​logically reasonable enough, and the relative importance of each element is relatively reliable. The next step of the weight confirmation process can be entered; if CR ≥ 0.1, it indicates that there is a more obvious inconsistency problem in the judgment matrix and it needs to be readjusted.

[0039] If the consistency ratio meets the requirements, the current initial weight vector is confirmed, and weights are assigned to each key feature parameter. If not, the element values ​​of the judgment matrix are automatically adjusted, and the weight vectors of each indicator layer relative to the criterion layer are recalculated until the consistency ratio meets the requirements. When the judgment matrix fails the consistency test, it needs to be retrospectively corrected. There are many common automatic adjustment strategies, such as based on data sensitivity analysis, finding out the elements that have a greater impact on consistency, re-evaluating the combination of data mining and expert experience, and adjusting their relative importance scores; or using an optimization algorithm, with the goal of minimizing the consistency ratio, making small iterative adjustments to the elements of the judgment matrix, and recalculating the characteristic roots, eigenvectors and consistency ratios after each adjustment until the requirement of CR < 0.1 is met. Once the standard is met, the weight vectors of each key feature parameter determined are scientific and reasonable, and can accurately reflect the true importance of each parameter in the quality assessment of e-cigarettes, which is convenient for subsequent analysis of the weight-based quality assessment model to ensure the accuracy and reliability of e-cigarette quality detection.

[0040] In one embodiment, an encrypted QR code containing all key feature parameters and quality ratings is generated, including: Generate an encryption key based on the smoke composition parameter set, the electrical parameter set, and the physical parameter set; Encrypting the key characteristic parameters and the quality grade score based on the encryption key to obtain encrypted data; The encrypted data is added to the QR code to generate the encrypted QR code.

[0041] In this embodiment, encryption keys are generated based on the smoke component parameter set, electrical parameter set, and physical property parameter set, making full use of the comprehensive quality characteristic information of the electronic cigarette itself to ensure data security. These parameter sets are processed by specific algorithms, such as using a hash function to first perform hash operations on the data in each parameter set, extracting hash values ​​with a fixed length and representing the data characteristics, and then splicing or further computing these hash values ​​according to predetermined rules, such as using a key generation algorithm (such as a key derivation function based on the elliptic curve cryptography system), using the spliced ​​data as input, and generating a high-strength encryption key. The encryption key generated in this way is closely bound to the core quality attributes of the electronic cigarette, which not only provides a basis for subsequent encryption, but also greatly increases the difficulty of the key being cracked, because if an attacker wants to obtain the key, he needs to understand the precise information of the electronic cigarette in terms of composition, electrical properties, and physics at the same time, which increases the difficulty of deciphering.

[0042] After obtaining the encryption key, use symmetric encryption or asymmetric encryption algorithms to protect key information. If a symmetric encryption algorithm (such as the Advanced Encryption Standard AES) is used, the encryption key is used for both the encryption and decryption processes. The key feature parameters (the most representative data after the previous dimension reduction and weighting processing, such as the key harmful comprehensive indicators extracted from the smoke component parameter set, the core power stability parameters in the electrical parameter set, and the key assembly precision parameters in the physical property parameter set) and the quality grade score are used as plain text input. Through the cooperation of the encryption algorithm and the encryption key, the plain text is transformed bit by bit to generate encrypted data in ciphertext form. This encryption method has a fast operation speed and is suitable for fast processing of a large amount of electronic cigarette product data. If an asymmetric encryption algorithm (such as RSA) is used, the public key in the encryption key is used to encrypt the data, and only the corresponding private key can be decrypted, which further improves security, especially when data transmission and storage involve an external insecure network environment, which can effectively prevent key data from being stolen and tampered with, ensuring that even if the encrypted QR code is accidentally leaked, others cannot easily interpret the electronic cigarette quality information therein, and maintain the confidentiality and integrity of product quality data.

[0043] Add the encrypted data to the QR code to generate the encrypted QR code. QR code is a convenient and widely used information carrier. First, according to the length, type and expected application scenario of the encrypted data (such as consumer scanning code query, etc.), select the appropriate QR code standard (such as QR code, Data Matrix code, etc.) and version to ensure that the QR code has sufficient capacity to carry the encrypted data. Then, through a special QR code generation software or algorithm module, the encrypted data is converted into a graphic pattern of the QR code according to specific coding rules, that is, the encrypted information is integrated into the black and white module arrangement of the QR code. The generated encrypted QR code looks the same as an ordinary QR code, but the encrypted key characteristic parameters and quality grade scores of the electronic cigarette are hidden inside. Only through the supporting decryption program (the decryption end with the corresponding encryption key, such as the quality traceability system of the production enterprise and the special inspection software of the management department) can the information be accurately restored, which is convenient for the identification and management of the product in the circulation process, and provides a reliable and safe technical means for the quality traceability and authenticity identification of electronic cigarettes.

[0044] In one embodiment, generating an encryption key based on the smoke component parameter set, the electrical parameter set, and the physical parameter set includes: Extracting multiple key values ​​from the smoke component parameter set, electrical parameter set, and physical parameter set; recombining and arranging each key value to form a data string; Based on the length of the data string, selecting a corresponding base point on a preset elliptic curve domain; Based on the preset elliptic curve domain and base point, each key value in the data string is used as a scalar to perform a scalar multiplication operation to generate a plurality of elliptic curve points; The coordinate values ​​of each elliptic curve point are converted into a code string; Generate a pseudo-random noise sequence, perform a bitwise XOR operation on the pseudo-random noise sequence and the encoding string, and generate the encryption key.

[0045] In this embodiment, multiple key values ​​are extracted from the smoke component parameter set, the electrical parameter set, and the physical parameter set, which is the basic step for generating encryption keys. For the smoke component parameter set, core data such as the specific content value of nicotine, the concentration limit value of specific harmful aldehydes, and the precise proportion of key atomizer components are selected. These values ​​directly reflect the key quality attributes such as the potential impact of electronic cigarette smoke on human health and the smoke generation effect. In the electrical parameter set, key values ​​such as the rated voltage of the battery, the standard value of the current under stable working conditions, and the extreme value of the power fluctuation range are extracted. They are related to the stability of the power supply and the safety of use of the electronic cigarette. As for the physical parameter set, the standard value of the thickness of the key parts of the shell, the reasonable range value of the assembly gap of the core components, and the specific indicators of the material hardness are selected. These values ​​reflect the reliability and durability of the physical structure of the electronic cigarette. The key values ​​extracted from different parameter sets are recombined and arranged according to predetermined rules to form a complete data string. This rule can be based on the specific quality assessment logic of the electronic cigarette, industry standard specifications, or an effective sequence verified by a large number of experiments. For example, the key values ​​of each parameter set are first arranged in the order of smoke composition, electrical properties, and physical properties. Within each parameter set, the order is further refined based on the degree of component hazard, the importance of electrical performance, the criticality of physical structure, etc. This makes the formed data string unique and holistic, integrates the key quality information scattered in different parameter sets, and makes it the basic input for subsequent encryption operations such as elliptic curve operations. At the same time, the generated encryption key is deeply bound to the comprehensive quality characteristics of the electronic cigarette, which enhances the pertinence and security of the key.

[0046] In cryptographic applications, the elliptic curve domain is a specific mathematical environment that is determined in advance, and is usually defined based on the elliptic curve equation on a finite field, such as the finite field and equation form corresponding to the common secp256k1 curve. This preset elliptic curve domain has good mathematical properties, and its discrete logarithm problem is computationally difficult. It is difficult for an attacker to reversely generate the relevant parameters of the point through a known elliptic curve point, thus providing a high-intensity security guarantee for encryption. It is the basic framework of the entire elliptic curve encryption operation. Different application scenarios and security requirements will use different elliptic curve domain standards. In the encryption application related to the quality inspection of electronic cigarettes, the selected elliptic curve domain is comprehensively considered, which can not only meet the security requirements of data encryption, but also adapt to the subsequent coordination with other encryption steps and the entire quality inspection system.

[0047] The corresponding base point is selected according to the length of the data string formed previously. This step reflects the further deepening of the correlation between encryption key generation and e-cigarette quality data. As a unique identification feature, the length of the data string can guide the selection of a suitable base point. Data strings of different lengths correspond to different base point selections, which makes the selection of the base point not a fixed and predictable pattern, increasing the complexity and randomness of the entire encryption process. The base point plays a key starting role in elliptic curve encryption. Subsequent scalar multiplication operations are all based on this selected base point. The base point is dynamically selected according to the length of the data string, so that the generated encryption key can better integrate the data characteristics related to the quality of e-cigarettes. In addition, each e-cigarette product will eventually select a different base point due to its own unique set of quality parameters, thereby generating differentiated and personalized encryption keys, effectively resisting cracking attempts against general encryption modes. The above base point selection method can be customized in advance.

[0048] Based on the preset elliptic curve domain and the selected base point, each key value in the data string is used as a scalar for scalar multiplication to generate multiple elliptic curve points. Elliptic curve scalar multiplication is not a simple numerical multiplication, but is implemented according to the mathematical rules of the elliptic curve. Specifically, on the finite field defined by the elliptic curve, the multiplication effect is simulated by addition and doubling operations. For example, for the selected base point G and a key value k (scalar), when calculating kG, first convert k to binary form, and then process each bit from high to low. If the current bit is 1, the current point is doubled (that is, the point itself is added by the addition rule of the elliptic curve) and added to the previous result; if the current bit is 0, only the corresponding point movement operation is performed, and no addition operation is performed. Through this bit-by-bit processing method, a new point P = kG on the elliptic curve is finally obtained. Repeating this process and treating each key value in the data string as a scalar for operation will generate multiple different elliptic curve points. These elliptic curve points carry key information based on the quality parameters of the e-cigarette, and due to the complexity and irreversibility of elliptic curve operations, the security of encryption is greatly improved.

[0049] The coordinate values ​​of the elliptic curve points generated above contain encrypted information that incorporates the key values ​​of the quality of electronic cigarettes after complex calculations, and they become the core elements for the subsequent construction of encryption keys. Each elliptic curve point is generated based on a unique quality parameter (key value) on a specific elliptic curve domain, and its coordinate value is highly random and unpredictable. It is difficult to restore the original key value from the outside through observation or simple analysis, which further ensures the confidentiality and security of the encryption key. At the same time, it also makes the encryption key closely linked to the specific quality status of the electronic cigarette, providing a reliable encryption foundation for subsequent quality traceability, data verification and other links, ensuring that only authorized parties who have mastered the correct decryption method and the corresponding relationship between relevant quality parameters can interpret the encrypted information.

[0050] The coordinate values ​​of each elliptic curve point are converted into a code string. This step is mainly to represent the coordinate values ​​of the elliptic curve point in a form that is more suitable for subsequent encryption operations and data storage and transmission. The coordinates of elliptic curve points are usually numerical values ​​on a specific finite field, with complex mathematical representations and large data lengths. Direct use is not conducive to subsequent fusion operations with other encryption elements (such as pseudo-random noise sequences), nor is it conducive to storage and transmission in carriers such as QR codes. Through code conversion, such as using common encoding methods such as hexadecimal encoding and Base64 encoding, the coordinate values ​​are converted into a unified format, more compact and easy-to-process binary data sequence to form a code string.

[0051] The coded string carries the encryption elements containing the key information of the e-cigarette quality after elliptic curve operation. It is an important intermediate product for constructing the final encryption key. As the basic data for subsequent XOR operation with pseudo-random noise sequence, its accuracy and integrity are crucial to generating high-quality and high-security encryption keys.

[0052] The purpose of generating a pseudo-random noise sequence is to further increase the complexity and unpredictability of the encryption key. This pseudo-random noise sequence is usually generated with the help of a specific algorithm, such as a cryptographically secure pseudo-random number generator (CSPRNG). Its seed value can be associated with other identification information of the e-cigarette (such as product serial number, production batch number, etc.) to ensure that the pseudo-random noise sequence generated by each e-cigarette product is unique. The pseudo-random noise sequence appears to be random like a true random number, but is actually generated by a certain algorithm. However, the complexity of its generation algorithm and its sensitivity to the seed value make it difficult for the outside to predict its specific value, thereby introducing additional random factors into the encryption process and strengthening the security of the encryption key.

[0053] The generated pseudo-random noise sequence is subjected to a bitwise XOR operation with the coding string to generate an encryption key. XOR operation is a simple but effective encryption method, which is reversible, that is, the same operation can be decrypted by performing the XOR operation again, but without knowing the pseudo-random noise sequence, it is extremely difficult to reverse the coding string from the encryption key (and then obtain the original key information of the e-cigarette quality). Through this bitwise XOR operation, the quality encryption information based on elliptic curve operation contained in the coding string is combined with the randomness of the pseudo-random noise sequence. The encryption key finally generated combines the dual characteristics of the e-cigarette quality characteristics and random noise, has extremely high confidentiality and anti-cracking capabilities, and can effectively protect the key data involved in the e-cigarette quality detection process.

[0054] In one embodiment, generating an encryption key based on the smoke component parameter set, the electrical parameter set, and the physical parameter set includes: Encoding the smoke component parameter set, the electrical parameter set, and the physical parameter set to obtain encoded data; Add the characters in the coded data to the data table one by one in order to generate a coded data table; Extracting values ​​from the smoke component parameter set to generate a first curve; based on the first curve, deforming the coded data table to obtain a deformed data table; Extracting values ​​from the electrical parameter set to generate a second curve; extracting values ​​from the physical parameter set to generate a third curve; The second curve and the third curve are superimposed on the deformation data table, and the cells in the deformation data table whose positional relationships with the second curve and the third curve meet the preset conditions are used as target cells. The characters in the target cells are combined in sequence to obtain the encryption key.

[0055] In this embodiment, the smoke component parameter set, electrical parameter set and physical parameter set are encoded in order to uniformly convert these different types of parameter information with their own complex formats and meanings into a form that is more convenient for subsequent processing and operation. For example, the smoke component parameter set may contain data such as the names and contents of various chemical components, some of which are presented in numerical form, and some are specific identification symbols of chemical substances; the electrical parameter set involves values ​​of different units and accuracy requirements such as voltage, current, and resistance; and the physical parameter set covers various types of data such as size and hardness. Through the encoding operation, a unified encoding rule is adopted to convert these data into standardized encoded data, so that they can be subsequently integrated, calculated, and processed under the same logical framework.

[0056] Adding the encoded characters to the data table one by one in sequence is the process of presenting the linear encoded data in a two-dimensional structure. The data table can be regarded as a storage structure in the form of a matrix, for example, organizing data in rows and columns. Filling the encoded characters into it in order forms a coded data table. By converting the one-dimensional encoded data into a two-dimensional data table, the positional relationship between the data can be better utilized to mine and incorporate more encryption logic, so that the encryption key generation process can fully combine the information of each parameter set of the e-cigarette, and increase the complexity and unpredictability of the encryption process, because each character position in the data table is associated with the original parameter set information, and it is difficult for attackers to directly infer the layout of the original data in this two-dimensional structure from the final encryption key.

[0057] Extracting values ​​from the smoke component parameter set to generate the first curve is a step of representing the smoke component-related data in a visual curve form that can be used for subsequent calculations. For example, the content of different chemical components can be used as the vertical coordinate, and the order of detection of these components or the order of their importance in the electronic cigarette smoke can be used as the horizontal coordinate. A continuous curve can be drawn through a suitable curve fitting algorithm (such as polynomial fitting, spline interpolation, etc.). This curve contains the key numerical characteristics and relationships of the smoke component parameter set. Due to the differences in the smoke components of different electronic cigarette products, the shape and trend of the generated first curve will be different, making this curve a unique identifier representing the characteristics of the electronic cigarette smoke components.

[0058] Using the generated first curve to deform the coded data table is a key operation to integrate the characteristic information of the smoke components into the entire data table structure. There are many specific deformation methods, such as determining the degree of deformation such as stretching, compression, and torsion of each row or column in the data table based on the slope change and curvature of the curve. For example, if the slope of the curve is large in a certain interval, it means that the corresponding part of the smoke component changes dramatically, then the row or column at the corresponding position in the data table can be stretched to a large extent to change the relative position and arrangement order of the characters in the data table. Through such a deformation operation, the originally regular coded data table carries the changing characteristics of the smoke components, and the generated deformed data table is no longer a simple sequential arrangement structure, but a special data organization form that integrates the smoke component information, which further increases the difficulty of extracting the encryption key from the deformed data table in the future, and also makes the encryption key closely related to the smoke component, an important quality parameter of the electronic cigarette.

[0059] Similarly, extracting values ​​from the electrical parameter set to generate the second curve is to curve the data related to the electrical performance of the electronic cigarette. For example, the voltage value is used as the ordinate and different working states or time series are used as the abscissa to draw a curve. This curve can intuitively reflect the electrical characteristics of the electronic cigarette, such as voltage stability, fluctuations, etc. The idea of ​​generating the third curve for the physical parameter set is similar. For example, the size values ​​of different parts of the shell are used as the ordinate and the curve is drawn with the order of the parts as the abscissa to reflect the characteristics of the physical structure of the product. These two curves carry key information on the electrical and physical characteristics of the electronic cigarette. Like the first curve, they each serve as a unique identifier to reflect the characteristics of the electronic cigarette in different quality dimensions, and provide basic data for subsequent operations such as superimposing on the deformation data table, so that the information on electrical and physical characteristics can also be integrated into the generation process of the encryption key, so that the encryption key can comprehensively reflect the multi-faceted quality characteristics of the electronic cigarette.

[0060] Superimposing the second curve and the third curve into the deformation data table is a key step to further integrate the electrical and physical characteristics of the electronic cigarette into the deformation data table that has integrated the smoke composition information. The superposition method can be carried out according to the preset rules, such as applying a certain operation (such as addition, multiplication or more complex custom operation) to the cells at the corresponding positions in the deformation data table according to the corresponding coordinate positions. After the superposition is completed, the target cells are screened out according to the preset conditions. These preset conditions can be based on the numerical changes in the cells after the curve superposition to meet a specific threshold, or the position relationship with the intersection of the curves. For example, it is set that only when the sum of the distance values ​​between the cell position and the corresponding second curve and third curve is greater than a certain set value, and the cell is in a specific row and column area after the previous deformation operation, it is determined as the target cell. Through such strict screening conditions related to each parameter curve, the cells that comprehensively reflect the key information of the smoke composition, electrical properties, and physical properties of the electronic cigarette are accurately located, so that the encryption key generated in the end can be closely related to the overall quality of the product.

[0061] Finally, the characters in the target cells are combined in sequence to obtain the encryption key. The above characters carry the encrypted information of various quality parameters of electronic cigarettes after multiple rounds of complex operations such as fusion, deformation, and superposition. The order and combination method are unique and depend on the processing of parameter sets in the previous steps and the corresponding rule settings. Since the encryption key generation process deeply combines the multiple quality characteristics of electronic cigarettes such as smoke composition, electrical properties, and physical properties, and has undergone complex deformation and screening operations, it is difficult for external attackers to crack this encryption key through conventional means to obtain the original electronic cigarette quality parameter information, thereby providing high-intensity security for subsequent data encryption using the encryption key, ensuring the confidentiality and integrity of electronic cigarette quality data in storage, transmission, and traceability.

[0062] In one embodiment, generating an encryption key based on the smoke component parameter set, the electrical parameter set, and the physical parameter set includes: For the smoke component parameter set, the frequency and proportion of each component are counted and converted into a frequency distribution vector; for the electrical parameter set, the root mean square value and power spectrum density of voltage and current are calculated to form an electrical characteristic sequence; for the physical parameter set, the standard deviation of the shell size and the quantitative grade of the material hardness are extracted to form a physical characteristic index; Perform weighted summation of the frequency distribution vector, electrical characteristic sequence, and physical characteristic index to obtain a comprehensive characteristic vector; The three coordinate axes are set to correspond to the three major types of characteristics: smoke, electrical properties, and physical properties. The element values ​​in the comprehensive feature vector are mapped to the three-dimensional space, and a parameter-related surface is generated through the surface fitting algorithm.

[0063] On the parameter-related surface, the differential geometry method is used to calculate the main curvature lines of the surface, and one of them is selected as the encrypted contour line; The encrypted contour line is discretized to obtain a sequence of coordinate points, the coordinate value of each coordinate point is encoded and converted, and the encoded coordinate point sequence is embedded in the grid space, and multiple rounds of encryption operations are performed to generate the final encryption key.

[0064] In this embodiment, the frequency and proportion of each component are counted in order to extract representative and general information from the complex smoke component data. The smoke component parameter set of electronic cigarettes includes a variety of chemical components, such as nicotine, propylene glycol, glycerol, various flavors, potentially harmful aldehydes and other substances. By counting their respective frequencies of occurrence, that is, the proportion of the number of times these components are detected in multiple tests to the total number of detections, and the proportion (that is, the mass or volume proportion of the component in the entire smoke component), the general composition characteristics of the smoke components can be intuitively displayed. By arranging these frequency and proportion data and converting them into frequency distribution vectors, the information of the smoke components is quantified in the form of a mathematical vector, and each dimension of this vector corresponds to the relevant frequency and proportion information of a component.

[0065] Calculating the root mean square value of voltage and current and the power spectrum density to form an electrical characteristic sequence is a process of deeply quantifying the performance of electronic cigarettes from an electrical perspective. The root mean square value (RMS) is often used to measure the effective value of electrical quantities such as voltage and current. It can reflect the average energy level of these electrical quantities over a period of time, which is critical for evaluating the stable power supply of electronic cigarettes when they are working. The characteristic quantities obtained by calculation are sequentially organized into an electrical characteristic sequence, so that the key information about the electrical performance of electronic cigarettes contained in the electrical parameter set can be presented in an orderly and quantitative manner.

[0066] Extracting the standard deviation of the shell size and the quantitative grade of the material hardness to form physical characteristic indicators is a quantitative description of the electronic cigarette from the aspects of physical structure and material characteristics. By forming such physical characteristic indicators, the key information in the physical parameter set is extracted, providing indispensable physical characteristic data support for the subsequent construction of encryption keys that can comprehensively reflect the overall quality of the product. In addition, due to different material selection and manufacturing processes, the physical characteristic indicators of different products are also unique.

[0067] The purpose of weighted summation of the frequency distribution vector, electrical characteristic sequence, and physical characteristic index obtained above is to integrate information from different dimensions (smoke composition, electrical properties, and physical properties) that are closely related to the quality of e-cigarettes, and form a characteristic vector that can comprehensively reflect the overall quality of the product. The weighting coefficient here is determined based on the importance of each parameter to the quality of e-cigarettes, and the judgment of this importance is usually based on a large amount of experimental data, market feedback, and quality standards and professional experience in the industry.

[0068] The three coordinate axes are set to correspond to the three major characteristics of smoke, electrical properties, and physics, and the element values ​​in the comprehensive feature vector are mapped to three-dimensional space. This step is to present the abstract comprehensive feature vector in a visual and geometric way, so as to facilitate intuitive observation and exploration of the intrinsic relationship between different parameters. Through this mapping, the comprehensive feature vector of each electronic cigarette product corresponds to a point set in three-dimensional space, and these point sets show certain distribution patterns and morphological characteristics due to the integration of quality characteristics of different dimensions. Then, a surface fitting algorithm (such as radial basis function fitting, etc.) is used to generate a parameter-related surface, which can smoothly pass through or approximate these point sets, thereby integrating the scattered quality characteristics represented by vectors into a continuous geometric surface. The geometric properties of the surface, such as shape, undulation, and curvature, contain rich information. For example, the steepness of the surface in the direction of the smoke characteristic axis may reflect the sensitivity of the change in smoke composition to the overall quality. The concave and convex areas of the surface may correspond to the good and bad areas of product quality under different parameter combinations. It becomes the key carrier for subsequent more complex encryption operations. Moreover, since different products have different comprehensive feature vectors, the generated parameter-associated surface is unique.

[0069] On the parameter-related surface, the differential geometry method is used to calculate the principal curvature lines of the surface. This is to use the in-depth research results of the geometric properties of the surface in higher mathematics to explore the more representative and characteristic geometric elements on the surface. The principal curvature line reflects the bending changes of the surface in different directions. It is an important manifestation of the intrinsic geometric structure of the surface. Each principal curvature line contains the local and overall geometric information of the surface in the corresponding direction. One of them is selected as the encrypted contour line because this line inherits the multi-faceted quality characteristic information of the electronic cigarette carried by the parameter-related surface, and is presented in a relatively concise but highly condensed curve form. Its direction in three-dimensional space, curvature changes and other characteristics are closely related to the smoke, electrical properties and physical characteristics of the product. For example, a sudden change in curvature in a certain section corresponds to a special correlation between the proportion of key components in the smoke and the voltage stability in the electrical parameters. This unique geometric information makes the encrypted contour line the core element for the subsequent generation of encryption keys. Different products have different parameter association surfaces, and the selected encrypted contour lines will also vary greatly, greatly increasing the unpredictability and security of the encryption key, providing basic data rich in product quality codes for subsequent encryption operations.

[0070] Discretizing the encrypted contour to obtain a sequence of coordinate points is a necessary step to convert a continuous geometric curve into a digital form that can be easily processed and calculated by a computer. By sampling the points on the encrypted contour according to certain intervals or rules, it is represented as a series of discrete coordinate points. Each coordinate point contains the coordinate value of the corresponding position in the three-dimensional space. These coordinate values ​​carry the quality characteristic information of the electronic cigarette previously integrated into the encrypted contour. The coordinate values ​​of each coordinate point are encoded and converted (such as using Gray code encoding, etc.). On the one hand, it is to enhance the anti-interference ability of the data. Gray code encoding has the characteristic that only one bit of adjacent code values ​​changes. During the data transmission or storage process, even if individual bit errors occur, the impact on data interpretation can be minimized; on the other hand, the sequence of coordinate points after encoding conversion is more suitable for subsequent embedding in a specific mathematical space (such as grid space) for encryption operations, so that it can follow the rules and requirements of the corresponding encryption algorithm and prepare for the generation of secure and reliable encryption keys.

[0071] Embedding the encoded coordinate point sequence into the grid point space is a key step in encrypting using the lattice cryptography, a modern cryptography technology with high security. The lattice is a special mathematical structure with good mathematical properties. For example, difficult problems on the lattice (such as the shortest vector problem, the nearest vector problem, etc.) are computationally difficult, which provides a strong security guarantee for encryption. After embedding the encoded coordinate point sequence into the grid point space, through multiple rounds of encryption operations based on the lattice cryptography algorithm, such as linear transformation and modular operations on the lattice, the information in the coordinate point sequence is repeatedly confused and diffused, so that the original electronic cigarette quality feature information contained in the original coordinate point sequence is highly encrypted, and it is difficult for external attackers to reverse the original information from the encrypted results. After multiple rounds of such complex encryption operations, the encryption key finally generated fully combines the comprehensive parameter information of the electronic cigarette, and with the high-intensity encryption characteristics of the lattice cryptography technology, it provides a solid security foundation for the subsequent encryption protection of the electronic cigarette quality data (such as key feature parameters, quality grade scores, etc.), ensuring that these data can resist various potential security threats in the storage, transmission and quality traceability, and ensure the confidentiality and integrity of the information.

[0072] Reference Figure 2 In one embodiment of the present invention, there is also provided an electronic cigarette quality detection device, comprising: The collection unit is used to detect the components of the smoke generated by the electronic cigarette based on the smoke component analyzer to form a smoke component parameter set; collect the electrical parameters of the electronic cigarette to form an electrical parameter set; measure the physical characteristic parameters of the electronic cigarette to construct a physical parameter set; An extraction unit, used for performing dimensionality reduction analysis on the smoke component parameter set, the electrical parameter set and the physical parameter set respectively based on the principal component analysis method, extracting corresponding key characteristic parameters, and assigning weights to each key characteristic parameter based on the hierarchical analysis method; An evaluation unit, used for inputting each of the key characteristic parameters with assigned weights into a pre-trained quality evaluation model, and outputting a quality grade score of the electronic cigarette; The storage unit is used to generate an encrypted QR code containing all key characteristic parameters and quality grade scores of qualified electronic cigarettes with quality grade scores higher than a threshold, and associate the encrypted QR code with the corresponding electronic cigarette product information and store it in the blockchain traceability system.

[0073] In this embodiment, for the specific implementation of each unit in the above device embodiment, please refer to the above method embodiment, which will not be repeated here.

[0074] Reference Figure 3 In an embodiment of the present invention, a computer device is also provided. The computer device may be a server, and its internal structure may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a display screen, an input device, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above method is implemented.

[0075] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0076] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented. It can be understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0077] In summary, the quality detection method, device and equipment of the electronic cigarette provided in the embodiment of the present invention include: based on the smoke component analyzer, the smoke generated by the electronic cigarette is detected to form a smoke component parameter set; the electrical parameters of the electronic cigarette are collected to form an electrical parameter set; the physical characteristic parameters of the electronic cigarette are measured to construct a physical parameter set; based on the principal component analysis method, the smoke component parameter set, the electrical parameter set and the physical parameter set are respectively subjected to dimensionality reduction analysis, the corresponding key feature parameters are extracted, and weights are assigned to each key feature parameter based on the hierarchical analysis method; each of the key feature parameters with assigned weights is input into a pre-trained quality assessment model, and the quality grade score of the electronic cigarette is output; for qualified electronic cigarettes with a quality grade score higher than a threshold, an encrypted two-dimensional code containing all its key feature parameters and quality grade scores is generated, and the encrypted two-dimensional code is associated with the corresponding electronic cigarette product information and stored in the blockchain traceability system. In the present invention, the quality detection of the electronic cigarette is carried out by combining the smoke component parameter set, the electrical parameter set and the physical parameter set, and the product quality is evaluated from the overall perspective; at the same time, an encrypted two-dimensional code containing all its key feature parameters and quality grade scores is generated, and the product quality of the product after quality detection is effectively traced.

[0078] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided by the present invention and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM.

[0079] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0080] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for detecting the quality of an electronic cigarette, characterized in that: The following steps are involved: The smoke generated by the electronic cigarette is tested based on the smoke component analyzer to form a smoke component parameter set; the electrical parameters of the electronic cigarette are collected to form an electrical parameter set; the physical characteristic parameters of the electronic cigarette are measured to construct a physical parameter set; Based on the principal component analysis method, the dimensionality reduction analysis is performed on the smoke component parameter set, the electrical parameter set and the physical parameter set, the corresponding key characteristic parameters are extracted, and a weight is assigned to each key characteristic parameter based on the hierarchical analysis method; Inputting each of the key characteristic parameters with assigned weights into a pre-trained quality assessment model, and outputting a quality grade score of the electronic cigarette; For qualified e-cigarettes with a quality grade score higher than the threshold, an encrypted QR code containing all its key characteristic parameters and quality grade score is generated, and the encrypted QR code is associated with the corresponding e-cigarette product information and stored in the blockchain traceability system.

2. The quality detection method of electronic cigarette according to claim 1, characterized in that: After outputting the quality grade score of the electronic cigarette, it also includes: Determine the electronic cigarettes whose quality grade score is lower than the threshold as unqualified products, and perform defect analysis on the smoke component parameter set, electrical parameter set and physical parameter set; Store defect analysis results in the blockchain traceability system.

3. The quality detection method of electronic cigarette according to claim 1, characterized in that: The method of assigning weights to each key feature parameter based on the hierarchical analysis method includes: The smoke component parameter set, electrical parameter set, and physical property parameter set are used as the criterion layer, and the key characteristic parameters under each parameter set are used as the indicator layer; Based on data mining, the influence of each parameter set on the quality of the electronic cigarette is analyzed to determine the relative importance between the elements of the criterion layer and the relative importance of the elements of the indicator layer relative to the criterion layer, and generate a judgment matrix; Solving the maximum eigenvalue of the judgment matrix and obtaining its corresponding eigenvector; performing normalization operation on the eigenvector to obtain the initial weight vector of each indicator layer relative to the criterion layer; Calculating the consistency ratio of the judgment matrix, and judging whether the consistency ratio meets the requirement; If the consistency ratio meets the requirement, the current initial weight vector is confirmed, and weights are assigned to each key feature parameter.

4. The electronic cigarette quality detection method according to claim 3, characterized in that: After determining whether the consistency ratio meets the requirement, the following steps are further included: If not, the element values ​​of the judgment matrix are automatically adjusted, and the weight vectors of each indicator layer relative to the criterion layer are recalculated until the consistency ratio meets the requirement.

5. The electronic cigarette quality detection method according to claim 1, characterized in that: Generate an encrypted QR code containing all its key characteristic parameters and quality rating, including: Generate an encryption key based on the smoke composition parameter set, the electrical parameter set, and the physical parameter set; Encrypting the key characteristic parameters and the quality grade score based on the encryption key to obtain encrypted data; The encrypted data is added to the QR code to generate the encrypted QR code.

6. The electronic cigarette quality detection method according to claim 5, characterized in that: Based on the smoke component parameter set, the electrical parameter set and the physical parameter set, an encryption key is generated, including: Extracting multiple key values ​​from the smoke component parameter set, electrical parameter set, and physical parameter set; recombining and arranging each key value to form a data string; Based on the length of the data string, selecting a corresponding base point on a preset elliptic curve domain; Based on the preset elliptic curve domain and base point, each key value in the data string is used as a scalar to perform a scalar multiplication operation to generate a plurality of elliptic curve points; The coordinate values ​​of each elliptic curve point are converted into a code string; Generate a pseudo-random noise sequence, perform a bitwise XOR operation on the pseudo-random noise sequence and the encoding string, and generate the encryption key.

7. The electronic cigarette quality detection method according to claim 5, characterized in that: Based on the smoke component parameter set, the electrical parameter set and the physical parameter set, an encryption key is generated, including: Encoding the smoke component parameter set, the electrical parameter set, and the physical parameter set to obtain encoded data; Add the characters in the coded data to the data table one by one in order to generate a coded data table; Extracting values ​​from the smoke component parameter set to generate a first curve; based on the first curve, deforming the coded data table to obtain a deformed data table; Extracting values ​​from the electrical parameter set to generate a second curve; extracting values ​​from the physical parameter set to generate a third curve; The second curve and the third curve are superimposed on the deformation data table, and the cells in the deformation data table whose positional relationships with the second curve and the third curve meet the preset conditions are used as target cells. The characters in the target cells are combined in sequence to obtain the encryption key.

8. An electronic cigarette quality detection device, characterized in that: include: The collection unit is used to detect the components of the smoke generated by the electronic cigarette based on the smoke component analyzer to form a smoke component parameter set; collect the electrical parameters of the electronic cigarette to form an electrical parameter set; Measure the physical characteristic parameters of the electronic cigarette and construct a physical parameter set; An extraction unit, used for performing dimensionality reduction analysis on the smoke component parameter set, the electrical parameter set and the physical parameter set respectively based on the principal component analysis method, extracting corresponding key characteristic parameters, and assigning weights to each key characteristic parameter based on the hierarchical analysis method; An evaluation unit, used for inputting each of the key characteristic parameters with assigned weights into a pre-trained quality evaluation model, and outputting a quality grade score of the electronic cigarette; The storage unit is used to generate an encrypted QR code containing all key characteristic parameters and quality grade scores of qualified electronic cigarettes with quality grade scores higher than a threshold, and associate the encrypted QR code with the corresponding electronic cigarette product information and store it in the blockchain traceability system.

9. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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