Automatic production line control method and system for electronic cigarette shell veneer pasting

Abstract

The embodiment of the invention provides an automatic production line control method and system for electronic cigarette shell veneer pasting, and relates to the technical field of automatic production line control, and the method comprises the steps that a calibration datum is established, and the calibration datum comprises independently-installed optical reference points; calculating the position of the camera relative to the world coordinate system according to the optical reference point; shooting a position image of the electronic cigarette shell; calculating the actual position of the electronic cigarette shell in the world coordinate system according to the position of the camera relative to the world coordinate system and the position image of the electronic cigarette shell; according to the actual position of the electronic cigarette shell and a preset ideal clamping position of the electronic cigarette shell, the posture deviation of the electronic cigarette shell is calculated; according to the posture deviation, adjusting a preset attaching movement track; and adaptively adjusting the applied local pressing pressure according to the posture deviation and the adjusted attachment motion track. According to the invention, the precision and quality of electronic cigarette shell veneer pasting can be improved.

Description

Technical Field

[0001] This application relates to the field of automated production line control technology, and in particular to a control method and system for an automated production line for electronic cigarette casing coating. Background Technology

[0002] In modern industrial production, automated production lines have become mainstream due to their high efficiency and consistency. However, even in highly automated environments, the physical components of equipment inevitably experience minor wear and deformation under prolonged, high-intensity continuous operation. These changes, especially those that are gradual and irregular, often exceed the capabilities of traditional static control and detection methods, leading to a series of difficult-to-detect quality problems and ultimately affecting the long-term reliability of the product. Take, for example, an automated production line for applying e-cigarette casings. Its core lies in a highly precise robotic arm system that strictly follows pre-set motion trajectory data to ensure that each piece of casing material is accurately placed in the designated position on the e-cigarette casing. However, with prolonged, high-intensity continuous operation of the automated production line, the positioning fixtures responsible for accurately holding the e-cigarette casings before application experience slight but persistent localized wear due to repeated contact with casings from different batches and with different surface treatment processes. This wear is not uniformly distributed but rather forms subtle deformations in certain specific areas, imperceptible to the naked eye, based on the actual contact patterns between the casing and the fixture. Due to the uneven deformation of the positioning fixture, each time the electronic cigarette casing is clamped, there will be a slight and irregular deviation between the actual position of the casing in three-dimensional space and the ideal position theoretically expected by the automated system. Summary of the Invention

[0003] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a control method and system for an automated production line for electronic cigarette casing application, aiming to improve the precision and quality of electronic cigarette casing application.

[0004] In a first aspect, embodiments of this application provide a control method for an automated production line for electronic cigarette casing coating, comprising: Establish a calibration reference, which includes an independently installed optical reference point; Calculate the camera's position relative to the world coordinate system based on the optical reference point; Take an image of the electronic cigarette casing's position; Based on the position of the camera relative to the world coordinate system and the position image of the electronic cigarette casing, calculate the actual position of the electronic cigarette casing in the world coordinate system; The posture deviation of the electronic cigarette shell is calculated based on the actual position of the electronic cigarette shell and the preset ideal clamping position of the electronic cigarette shell. Adjust the preset attachment motion trajectory based on the posture deviation; Based on the posture deviation and the adjusted attachment trajectory, the applied local pressing pressure is adaptively adjusted.

[0005] According to some embodiments of this application, the step of calculating the actual position of the electronic cigarette casing in the world coordinate system based on the position of the camera relative to the world coordinate system and the position image of the electronic cigarette casing includes: Analyze the optical characteristics of preset feature points in the position image of the electronic cigarette shell, the optical characteristics including the average brightness, contrast and grayscale histogram distribution skewness of the preset feature points; The optical properties of the preset feature points are compared with the preset reference optical properties to obtain the differences in optical properties; Based on the differences in optical properties, the image preprocessing parameters are adjusted, including gamma correction curves, local contrast enhancement parameters, or nonlinear brightness mapping functions. Based on the differences in optical properties, the parameters of the feature point recognition algorithm are adjusted. The feature point recognition algorithm parameters include edge detection threshold, gradient calculation method, matching tolerance or multi-scale feature descriptor. Based on the adjusted image preprocessing parameters and the adjusted feature point recognition algorithm parameters, the actual position of the electronic cigarette shell in the world coordinate system is calculated.

[0006] According to some embodiments of this application, the step of adaptively adjusting the applied local pressing pressure based on the posture deviation and the adjusted attachment motion trajectory includes: During the application of the local pressing pressure, the optical characteristics of the actual contact surface between the skin material and the electronic cigarette shell are obtained. The actual contact surface optical characteristics include microscopic reflectivity, gloss and surface texturing. By comparing the actual contact surface optical characteristics with the preset contact surface optical characteristics, the differences in the contact surface optical characteristics are obtained; The applied local pressing pressure is adaptively adjusted based on the posture deviation, the adjusted attachment trajectory, and the differences in the optical characteristics of the contact surface.

[0007] According to some embodiments of this application, the step of adaptively adjusting the applied local pressing pressure includes: Obtain microscopic spectral reflectance data of the contact surface between the adhesive backing layer of the skin material and the electronic cigarette shell; By comparing the microscopic spectral reflectance data with the preset ideal spectral reflectance characteristics, the differences in the microscopic properties of the skin material are obtained. Based on the posture deviation, the adjusted attachment trajectory, and the differences in the microstructure of the adhesive material, the applied local pressing pressure is adaptively adjusted.

[0008] According to some embodiments of this application, the step of adaptively adjusting the applied local pressing pressure includes: During the application of the local pressing pressure, transient micro-deformation data of the contact area between the skin material and the electronic cigarette shell are acquired. The transient micro-deformation data includes the local height change, deformation rate, and deformation recovery of the contact area. By comparing the transient microscopic deformation data with the preset ideal deformation response characteristics, the deformation response difference is obtained; Based on the difference in deformation response, the driving unit in the corresponding area of ​​the flexible pressing module is adjusted to adjust the applied local pressing pressure.

[0009] According to some embodiments of this application, the steps following the acquisition of transient micro-deformation data of the contact area between the adhesive material and the electronic cigarette shell include: Continuously monitor the transient micro-deformation data; By comparing current transient microdeformation data with historical transient microdeformation data, abnormal fluctuations or drifts in transient microdeformation data can be identified. The transient microscopic deformation data of the abnormal fluctuations or drifts are corrected in real time.

[0010] According to some embodiments of this application, the step of real-time correction of the transient microscopic deformation data of the abnormal fluctuations or drifts includes: Analyze the instantaneous rate of change and frequency components of the transient micro-deformation data of the abnormal fluctuations or drifts to identify the existence of non-periodic high-frequency fluctuations; By comparing the non-periodic high-frequency fluctuations with a preset deformation rate range, it can be determined whether the non-periodic high-frequency fluctuations originate from production environment noise or material damage. The non-periodic high-frequency fluctuations identified as production environment noise are subjected to dynamic filtering processing, wherein the dynamic filtering processing adaptively adjusts the filtering parameters according to the frequency and amplitude of the production environment noise; Real-time correction is performed on the filtered transient micro-deformation data.

[0011] According to some embodiments of this application, the step of distinguishing whether the non-periodic high-frequency fluctuations originate from production environment noise or material damage includes: Obtain the instantaneous rate of change and frequency components of the transient micro-deformation data of the abnormal fluctuations or drifts; The instantaneous rate of change and frequency components of the transient micro-deformation data of the abnormal fluctuation or drift are compared with a preset material damage feature map, which contains the instantaneous rate of change and frequency component characteristics of different types of material damage in the displacement sensor signal. When the instantaneous rate of change and frequency components of the transient micro-deformation data of the abnormal fluctuation or drift match the material damage feature spectrum, it is confirmed that the non-periodic high-frequency fluctuation originates from material damage. When the instantaneous rate of change and frequency components of the transient micro-deformation data of the abnormal fluctuation or drift do not match the material damage characteristic spectrum, it is confirmed that the non-periodic high-frequency fluctuation originates from production environment noise.

[0012] According to some embodiments of this application, the step of confirming that the non-periodic high-frequency fluctuation originates from material damage includes: When it is confirmed that the non-periodic high-frequency fluctuations originate from material damage, the non-periodic high-frequency fluctuations identified as material damage are marked with a damage severity level based on the instantaneous change rate and frequency component characteristics of the non-periodic high-frequency fluctuations of material damage, combined with a preset damage severity threshold. Based on the severity level of the damage, the subsequent quality inspection system will adjust the evaluation priority and processing procedures for defects.

[0013] Secondly, embodiments of this application provide an automated production line control system for electronic cigarette casing coating, comprising: A calibration reference establishment module is used to establish a calibration reference, which includes an independently installed optical reference point; The calculation module is used to calculate the position of the camera relative to the world coordinate system based on the optical reference point; The camera module is used to capture images of the electronic cigarette casing's position. The shell posture recognition module is used to calculate the actual position of the electronic cigarette shell in the world coordinate system based on the position of the camera relative to the world coordinate system and the position image of the electronic cigarette shell; The posture deviation recording module is used to calculate the posture deviation of the electronic cigarette shell based on the actual position of the electronic cigarette shell and the preset ideal clamping position of the electronic cigarette shell. The motion trajectory adjustment module is used to adjust the preset attachment motion trajectory according to the posture deviation; The pressing pressure adaptive adjustment module is used to adaptively adjust the applied local pressing pressure according to the posture deviation and the adjusted attachment motion trajectory.

[0014] The technical solution according to the embodiments of this application has at least the following beneficial effects: The automated production line control method for electronic cigarette casing bonding disclosed in this application overcomes the problem that traditional static spatial position conversion data cannot adaptively compensate for minor deviations caused by equipment wear by establishing a calibration benchmark and using optical reference points to accurately calculate the position of the camera relative to the world coordinate system. This method can capture position images of the electronic cigarette casing in real time and, combined with camera attitude information, accurately calculate the actual position of the electronic cigarette casing in the world coordinate system, thereby effectively identifying and quantifying irregular attitude deviations such as minor translations and tilts of the casing caused by wear of the positioning fixture. Based on the calculated attitude deviation, this application dynamically adjusts the preset bonding motion trajectory, so that the bonding path of the robotic arm can accurately adapt to the actual position and attitude of the casing, avoiding inconsistencies in the initial contact points caused by inaccurate paths. More importantly, this application further adaptively adjusts the applied local pressing pressure based on the attitude deviation and the adjusted bonding motion trajectory. This mechanism ensures uniform and sufficient contact between the adhesive layer and the e-cigarette shell throughout the entire application process. This application fundamentally solves the problems of positioning deviations and uneven application pressure in existing automated production lines caused by equipment wear and deformation by introducing technologies such as dynamic calibration, precise posture recognition, adaptive motion trajectory adjustment, and adaptive control of local pressing pressure. This method significantly improves the accuracy and quality of e-cigarette shell application, effectively avoiding minute defects that are difficult to detect by traditional testing systems, thereby enhancing the long-term reliability of the product.

[0015] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0016] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0017] Figure 1 A flowchart illustrating an automated production line control method for electronic cigarette casing coating according to an embodiment of this application; Figure 2 This is a schematic diagram of an automated production line control system for electronic cigarette casing application, provided as an embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical methods, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0019] It should be noted that the meaning of "multiple" (or "more than") in the description of the embodiments of this application refers to two or more, and "greater than," "less than," "exceeding," etc. are understood to exclude the number itself, while "above," "below," "within," etc. are understood to include the number itself. If "first," "second," etc. are used in the description, they are only for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated or the order of the technical features indicated.

[0020] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, the simultaneous existence of A and B, or the existence of B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: the existence of a alone, the existence of b alone, the existence of c alone, the simultaneous existence of a and b, the simultaneous existence of a and c, the simultaneous existence of b and c, or the simultaneous existence of a, b, and c, where a, b, and c can be single or multiple.

[0021] In the description of this application, unless otherwise expressly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0022] Based on the above, this application proposes a control method and system for an automated production line for electronic cigarette casing coating, aiming to improve the precision and quality of electronic cigarette casing coating.

[0023] The automated production line control method for electronic cigarette casing application provided in this application can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms; the software can be an application that implements the automated production line control method for electronic cigarette casing application, but is not limited to the above forms.

[0024] This application can be applied to numerous general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via communication networks. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices. It should be noted that in various specific embodiments of this invention, when processing is required based on data related to the characteristics of an object (e.g., user attributes or sets of attribute information), permission or consent from the corresponding object is obtained first, and the collection, use, and processing of this data comply with relevant laws and standards. Furthermore, when the embodiments of the present invention need to obtain the attribute information of an object, they will obtain the separate permission or separate consent of the corresponding object through pop-up windows or redirection to a confirmation page. After obtaining the separate permission or separate consent of the corresponding object, they will then obtain the relevant data of the object necessary for the embodiments of the present invention to operate normally.

[0025] See Figure 1 , Figure 1 This is a flowchart illustrating an automated production line control method for electronic cigarette casing bonding according to an embodiment of this application. The automated production line control method for electronic cigarette casing bonding provided in this embodiment includes, but is not limited to, steps S110 to S170, which will be described in detail below.

[0026] Step S110: Establish a calibration reference, which includes an independently installed optical reference point; Step S120: Calculate the position of the camera relative to the world coordinate system based on the optical reference point; Step S130: Take a positional image of the electronic cigarette casing; Step S140: Calculate the actual position of the electronic cigarette casing in the world coordinate system based on the position of the camera relative to the world coordinate system and the position image of the electronic cigarette casing. Step S150: Calculate the posture deviation of the electronic cigarette casing based on the actual position of the electronic cigarette casing and the preset ideal clamping position of the electronic cigarette casing; Step S160: Adjust the preset attachment motion trajectory according to the posture deviation; Step S170: Based on the posture deviation and the adjusted attachment motion trajectory, adaptively adjust the applied local pressing pressure.

[0027] It should be noted that "calibration datum" refers to a set of physical or virtual reference points used in an automated production line to establish a precise spatial reference. Its function is to provide a stable and reliable reference frame for subsequent measurements and positioning. "Optical reference points" refer to specific points in the calibration datum that possess unique optical properties, such as specific color, shape, or reflectivity, enabling the camera system to accurately identify and locate them. "World coordinate system" refers to a global, fixed three-dimensional coordinate system in which the positions of all equipment and workpieces can be described, ensuring data consistency between different sensors and actuators. "Attitude deviation" refers to the difference between the actual position and orientation of the e-cigarette casing and the preset ideal position and orientation, typically including translational and rotational deviations. "Preset attachment motion trajectory" refers to the pre-planned motion path and speed curve of the robotic arm during the attachment operation. "Local pressing pressure" refers to the pressure applied by the attachment head to the contact area between the attachment material and the e-cigarette casing during the attachment process, which can be finely adjusted as needed.

[0028] In one embodiment, a high-precision three-dimensional calibration plate can be installed at a fixed position on the production line. This calibration plate is engraved with multiple markers having specific geometric shapes and optical properties; these markers serve as independently installed optical reference points. Alternatively, a virtual, high-precision three-dimensional mesh can be created in the production line environment using a laser interferometer or a high-precision encoder, and specific intersections or feature points within the mesh can be defined as optical reference points. These optical reference points are independent of other moving parts on the production line, ensuring the stability of their position and the reliability of the reference. During production line startup or periodic maintenance, images of the optical reference points on the calibration benchmark are captured using a camera. Image processing algorithms are used to identify the pixel coordinates of these optical reference points in the camera images. Subsequently, using the known three-dimensional coordinates of the optical reference points in the world coordinate system, combined with camera intrinsic and extrinsic parameter calibration techniques (such as the Zhang Zhengyou calibration method), the precise position and orientation of the camera in the world coordinate system are calculated. Another approach is to integrate an inertial measurement unit (IMU) onto the camera. The IMU acquires the camera's attitude information in real time, and combined with the identification results of optical reference points, data fusion algorithms such as Kalman filtering are used to continuously optimize the accuracy of the camera's position calculation relative to the world coordinate system. Various imaging techniques can be employed when capturing the position image of the e-cigarette casing. A high-resolution industrial camera can be used to capture images of the e-cigarette casing from one or more preset angles after it has been clamped into position. To improve image quality, ring light sources or backlighting can be used to enhance the contrast of the casing's outline. Another method is to use structured light scanning technology, which projects light with a known pattern onto the surface of the e-cigarette casing and uses a camera to capture the deformed pattern, thereby obtaining the three-dimensional point cloud data of the casing.

[0029] In one embodiment, the actual position of the e-cigarette casing in the world coordinate system is calculated based on the camera's position relative to the world coordinate system and the position image of the e-cigarette casing. One implementation involves preprocessing the captured image of the e-cigarette casing's position, such as denoising and contrast enhancement. Then, image processing algorithms such as edge detection and feature point matching are used to identify key feature points or contours of the e-cigarette casing in the image. Combined with the previously calculated position and orientation of the camera in the world coordinate system, these image feature points or contours are mapped to the world coordinate system using perspective transformation or 3D reconstruction algorithms, thereby calculating the actual 3D position and orientation of the e-cigarette casing in the world coordinate system. Another approach is to use a deep learning model trained on a large number of labeled e-cigarette casing images, enabling the model to directly predict the precise position and orientation of the e-cigarette casing in the world coordinate system from the images. The calculated actual position and orientation of the e-cigarette casing in the world coordinate system are then compared one by one with pre-stored ideal clamping positions and orientations. By calculating the translation vectors and rotation matrices between the two, the translational deviations of the e-cigarette shell along the X, Y, and Z axes, as well as the rotational deviations around these axes, are obtained. Another approach is to define an error function that quantifies the difference between the actual and ideal positions, and to accurately calculate the posture deviations by minimizing this error function. Using the calculated posture deviations as input, a kinematic inverse model is used to adjust the robotic arm's trajectory in real time. For example, if there is a translational deviation in the X-axis direction of the e-cigarette shell, the robotic arm's attachment trajectory will be compensated accordingly in the X-axis direction. If there is a rotational deviation around the Z-axis, the end effector of the robotic arm will make corresponding angle adjustments during the attachment process. Another approach is to utilize a machine learning-based trajectory planning algorithm. This algorithm adaptively learns and optimizes the trajectory adjustment strategy based on historical posture deviation data and attachment results to achieve more precise attachment. The applied local pressure is adaptively adjusted based on the posture deviations and the adjusted attachment trajectory. Multiple miniature pressure sensors are integrated inside the attachment head, which can monitor the pressure distribution in the contact area between the attachment head and the adhesive material in real time. Based on the magnitude and direction of the posture deviation, and the adjusted motion trajectory, the system dynamically adjusts the drive units of different areas of the attachment head, such as miniature cylinders or piezoelectric actuators, to achieve precise control of local pressing pressure. For example, if the posture deviation makes the adhesive material more prone to air bubbles in a certain area, the system will increase the pressing pressure in that area; if there is a risk of over-pressing in a certain area, the system will appropriately reduce the pressure in that area. Another approach is to utilize a force feedback control system to dynamically adjust the pressing pressure by monitoring the contact force between the attachment head and the workpiece in real time and combining it with posture deviation information, ensuring a uniform and defect-free adhesion between the adhesive material and the e-cigarette shell.

[0030] It should be noted that the preset feature points can be specific geometric marks, textured areas, or edge features on the e-cigarette casing. Optical properties refer to the visual representation of these feature points in the image. For example, average brightness reflects local illumination intensity, contrast measures the distinguishability of a feature point from its surroundings, and the skewness of the grayscale histogram indicates the asymmetry of brightness distribution in the image. These parameters are used together to evaluate image quality and the recognizability of feature points. Specifically, the baseline optical properties are the optical parameters of feature points pre-acquired and stored under ideal or standard conditions. By comparing the optical properties of feature points in the currently captured image with these baseline properties, the deviation between the current image and the ideal state can be quantified, such as excessive or insufficient brightness, or insufficient contrast. The adjustment of image preprocessing parameters aims to optimize image quality, making it more suitable for subsequent feature point recognition. For example, when the image brightness is low, the gamma correction curve can be adjusted to improve overall brightness; when the contrast of a local area is insufficient, a local contrast enhancement algorithm (such as CLAHE) can be applied to highlight details; when the image has nonlinear brightness distortion, a nonlinear brightness mapping function can be used for correction. These adjustments are adaptively made based on differences in optical properties to ensure optimal recognition results under various environmental conditions. The parameter adjustments for the feature point recognition algorithm aim to improve the accuracy and robustness of feature point extraction. For example, when image noise is high, the edge detection threshold can be adjusted appropriately to reduce false detections; when feature point textures are complex, a more suitable gradient calculation method can be selected; the matching tolerance adjustment can adapt to minor changes in feature points under different viewpoints or deformations; the selection and parameter configuration of multi-scale feature descriptors (such as SIFT, SURF, or ORB) can address the performance of feature points at different scales. These adaptive parameter adjustments allow the feature point recognition algorithm to better adapt to changes in image quality. Therefore, after the aforementioned image preprocessing and feature point recognition algorithm parameter optimization, the preset feature points on the e-cigarette shell can be extracted more accurately, and combined with the camera's position information relative to the world coordinate system, the actual three-dimensional position and pose of the e-cigarette shell in the world coordinate system can be precisely calculated.

[0031] In one embodiment, it is assumed that the e-cigarette casing moves along a production line and is photographed by a camera. When the lighting fixtures on the production line age, causing a decrease in light intensity, or when batch differences in the e-cigarette casing cause slight changes in surface reflectivity, traditional fixed-parameter image processing methods may fail to accurately identify preset feature points on the casing, such as the edge of a USB interface or specific corner points of a brand logo. This application addresses this by first analyzing the average brightness, contrast, and grayscale histogram skewness of these preset feature points in the currently captured image. If the average brightness is found to be lower than a preset benchmark, and the grayscale histogram skewness is increased, it indicates that the overall image is dark and lacks contrast. In this case, the system automatically adjusts the image preprocessing parameters based on these optical characteristic differences, for example, increasing the gain of the gamma correction curve and enabling a local contrast enhancement algorithm. Simultaneously, the feature point recognition algorithm parameters are also adjusted, for example, lowering the edge detection threshold to capture weaker edge information, and possibly switching to a multi-scale feature descriptor that is more robust to changes in illumination. After these adaptive adjustments, even in environments with insufficient lighting or changes in material properties, the system can still accurately extract feature points on the e-cigarette shell and calculate the precise actual position of the e-cigarette shell in the world coordinate system based on these accurate feature points, thereby ensuring the accuracy of subsequent skin application operations.

[0032] It is important to note that during the bonding process of the skin material to the e-cigarette shell, the microscopic state of the contact surface between the two needs to be monitored in real time. The actual contact surface optical characteristics refer to the visual information reflecting the actual contact between the skin material and the e-cigarette shell, acquired through high-resolution optical sensors or dedicated imaging systems. Microscopic reflectivity can be understood as the intensity of reflection of incident light by different areas of the contact surface; its variation can indicate the local density of the material, surface smoothness, and potential adhesion defects, such as air bubbles or areas of incomplete contact. Gloss refers to the specularity of the light reflected from the contact surface; it is closely related to surface smoothness and material uniformity, and high gloss usually indicates good surface adhesion. Surface texturing describes the microstructure and pattern of the contact surface, revealing material flowability, bonding marks, or the presence of foreign objects. These optical characteristics are typically acquired using miniature cameras, spectrometers, or laser scanners positioned near the bonding module, with the aim of providing real-time, non-contact feedback on the quality of the contact surface. The process of comparing the actual contact surface optical characteristics with the preset contact surface optical characteristics to obtain the differences in contact surface optical characteristics involves comparing real-time acquired data such as microscopic reflectivity, gloss, and surface texture with the preset optical characteristics of an ideal or standard contact surface. The preset contact surface optical characteristics are usually obtained by measuring perfectly fitted samples or calculating through theoretical models, representing the optimal bonding state. The comparison process can employ image processing algorithms, pattern recognition techniques, or machine learning models. For example, it can quantify the deviation between the actual contact surface and the ideal state by calculating pixel-level brightness differences, texture similarity indices, or Euclidean distances of spectral features. Its purpose is to identify local defects, inhomogeneities, or potential adhesion problems on the contact surface. Adaptively adjusting the applied local pressing pressure based on posture deviations, the adjusted attachment trajectory, and the differences in contact surface optical characteristics means combining the global adjustment information provided by macroscopic posture deviations and the adjusted trajectory with the local fine-tuning adjustment information provided by microscopic differences in contact surface optical characteristics to jointly determine the final applied local pressing pressure. For example, if an orientation deviation indicates that the entire system needs to tilt in a certain direction, while optical characteristic differences show that the microscopic reflectivity of a certain local area is low, the system will take both factors into account and, based on the overall adjustment, apply additional or more precise pressure to that local area to compensate for insufficient microscopic contact. The aim is to achieve closed-loop control of the bonding process, ensuring a uniform and firm adhesion across the entire bonding surface.

[0033] In one embodiment, assuming an automated e-cigarette casing bonding production line, an e-cigarette casing is placed on a fixture, and a robotic arm carries the bonding material for bonding. First, the system calculates the camera's position relative to the world coordinate system based on an optical reference point and captures an image of the e-cigarette casing's position, thereby calculating the actual position of the e-cigarette casing in the world coordinate system. Subsequently, based on the actual position and the ideal clamping position, the system calculates the orientation deviation of the e-cigarette casing and adjusts the preset bonding trajectory accordingly. As the bonding material begins to contact the e-cigarette casing and applies local pressing pressure, a high-resolution microscopic optical sensor is deployed near the pressing module to continuously acquire real-time optical characteristic data of the contact surface between the bonding material and the e-cigarette casing, including microscopic reflectivity, gloss, and surface texture. For example, the sensor detects that in a certain edge area of ​​the e-cigarette casing, the microscopic reflectivity is lower than the preset ideal value, and the gloss exhibits slight non-uniformity, which may indicate the presence of tiny air bubbles or poor bonding in that area. The system immediately compares these actual contact surface optical characteristics with preset reference optical characteristics to calculate the differences in contact surface optical characteristics. Based on this difference, and combined with the previously calculated posture deviation and the adjusted attachment trajectory, the control system precisely adjusts the local pressing pressure of the flexible pressing module in that edge area. For example, it slightly increases the pressure in that area to promote air bubble removal and ensure a tighter fit. Through this real-time feedback and adaptive adjustment, the uniformity of the entire skin-applying process and the quality of the final product are ensured.

[0034] It should be noted that obtaining microscopic spectral reflectance data of the contact surface between the adhesive layer of the skin material and the e-cigarette shell refers to collecting the reflectance spectrum information of the adhesive layer at different wavelengths in the area where the skin material and the e-cigarette shell are about to make contact or initially make contact, using a high-precision spectral sensor or hyperspectral imaging system. This data can reveal the deep characteristics of the adhesive layer, such as its chemical composition, physical structure, thickness uniformity, and the presence of microscopic defects or contaminants. Its purpose is to obtain information on the internal or surface micro-state of the material that is difficult to detect with traditional visual inspection, providing data support for refined pressing. Specifically, the real-time acquired microscopic spectral reflectance data is compared with the spectral reflectance characteristics of the adhesive layer under ideal adhesion conditions, obtained beforehand through experiments or simulations. Ideal spectral reflectance characteristics are usually benchmark data established under standard environmental and ideal material conditions. By comparing, the deviation between the current adhesive layer and the ideal state can be quantified, such as abnormal reflectance at specific wavelengths, absorption peak shifts, or changes in the shape of the spectral curve. These differences directly reflect whether the microscopic properties of the adhesive layer meet the requirements. Its purpose is to identify and quantify potential problems with the adhesive layer, providing a basis for subsequent pressure adjustments. Based on the differences in posture deviation, adjusted attachment trajectory, and microscopic properties of the adhesive material, the adaptive adjustment of the applied local pressing pressure involves, specifically, considering both the macroscopic posture deviation of the e-cigarette shell and the adjustment of the attachment trajectory, further incorporating the differences in the adhesive layer characteristics obtained from microscopic spectral reflectance data, to dynamically adjust the local pressure applied by the pressing module in real time. For example, if the microscopic spectral data indicates that the adhesive layer is locally too thin or lacks sufficient activity, the system can correspondingly increase the pressing pressure in that area or extend the pressing time; conversely, if the adhesive layer is too active or too thick, the pressure may be appropriately reduced to avoid adhesive overflow or material damage.

[0035] In one embodiment, it is assumed that when applying a backing material to an electronic cigarette casing with a curved structure, the adhesive layer used is a pressure-sensitive polymer adhesive layer. During the application process, a pressing module integrating a miniature hyperspectral imaging sensor is used to apply local pressure. When the pressing module approaches or lightly touches the surface of the electronic cigarette casing, the sensor collects microscopic spectral reflectance data of the contact area between the adhesive layer and the casing in real time. For example, if the reflected intensity at a specific wavelength (such as the infrared region) is detected to be lower than a preset ideal value, this may indicate that the adhesive layer thickness in that area is too thin or that there are tiny gaps. Based on this microscopic characteristic difference, combined with known posture deviations and adjusted motion trajectories, the system immediately sends a command to the pressing module drive unit in that area, causing it to increase the pressing pressure locally by 0.5N and extend the pressing time by 0.1 seconds while maintaining the original motion trajectory. Conversely, if the spectral data indicates that the backing layer reflectance in a certain area is abnormally high, it may mean that the adhesive layer in that area is too thick or that there are contaminants. The system will then make corresponding fine adjustments, such as slightly reducing the pressure or adjusting the pressing angle, to ensure uniform application and avoid adhesive overflow. In this way, even when faced with minor differences between material batches or fluctuations in the production environment, the system can achieve precise adaptive control of local pressing pressure by real-time sensing and feedback of the microscopic spectral characteristics of the adhesive layer, thereby ensuring that each patch achieves the best adhesion effect.

[0036] It is important to note that during the application of localized pressing pressure, it is necessary to acquire transient microscopic deformation data of the contact area between the adhesive material and the e-cigarette shell in real time. Transient microscopic deformation data can be understood as information on the minute physical deformations occurring in the contact area within a very short time, specifically including local height changes, deformation rates, and deformation recovery. Local height changes refer to the vertical displacement of points on the contact surface, which can be acquired using high-precision measuring equipment such as laser displacement sensors, confocal microscopes, or optical interferometers. Deformation rate refers to the rate of change of local height over time, reflecting the speed of material deformation. Deformation recovery refers to the degree and speed at which the material returns to its original state after pressure is released or changed; this is crucial for assessing the material's elastic and plastic behavior. The purpose of acquiring this data is to provide real-time feedback on the microscopic dynamics of the bonding process. The acquired transient microscopic deformation data will be compared with preset ideal deformation response characteristics. Ideal deformation response characteristics are pre-established based on extensive experimental data, material mechanics models, or simulation analyses. They represent the expected deformation behavior pattern of the contact surface between the skin material and the e-cigarette shell under ideal adhesion conditions. For example, it may include the expected range of local height change, deformation rate curve, and deformation recovery time in different regions under a specific pressing pressure. By comparison, the deformation response difference can be obtained, which quantifies the deviation between the actual deformation and the ideal deformation. Based on the deformation response difference, the driving unit in the corresponding region of the flexible pressing module needs to be adjusted to adjust the applied local pressing pressure. The flexible pressing module is usually composed of multiple independent driving units, each capable of independently applying and adjusting local pressure. For example, these driving units can be miniature cylinders, piezoelectric actuator arrays, or electromagnetic actuators. When a deformation response difference in a certain region is detected to exceed a preset threshold, such as excessive local height change or excessively fast deformation rate, the system will send instructions to the corresponding driving unit according to the magnitude and direction of the difference, increasing or decreasing the local pressing pressure in that region in real time, thereby adjusting the actual deformation to the ideal state.

[0037] In one embodiment, it is assumed that the skin application operation is performed on a curved area of ​​the e-cigarette shell. During the pressing process, a micro-laser displacement sensor array integrated at the bottom of the flexible pressing module acquires real-time data on the local height changes, deformation rates, and deformation recovery at various points on the contact surface between the skin material and the e-cigarette shell, forming transient microscopic deformation data. For example, if the sensor detects that the local height change in a certain area is too small, it indicates insufficient pressure in that area, which may lead to air bubbles or incomplete adhesion. In this case, the system calculates the difference in deformation response and instructs the piezoelectric drive unit in the corresponding area of ​​the flexible pressing module to increase the local pressing pressure. Conversely, if the deformation rate in a certain area is too fast and the deformation recovery is poor, it may indicate that the material is overstretched or there is a risk of damage. The system will then reduce the local pressure in that area accordingly. Through this real-time, regional pressure adjustment, it is ensured that the skin material adheres optimally to the entire surface of the e-cigarette shell, especially in complex curved areas, thereby significantly improving the skin application quality and product appearance.

[0038] It should be noted that continuous monitoring of transient micro-deformation data refers to the uninterrupted acquisition and recording of transient micro-deformation data of the contact area between the skin material and the e-cigarette shell during the entire local pressing pressure application process. This can be achieved through a high-frequency sampling sensor array, such as a distributed micro laser displacement sensor or a piezoelectric thin film sensor, to ensure continuous tracking of deformation data over time. The purpose is to obtain complete and continuous information on the deformation process, providing a foundation for subsequent data analysis and anomaly identification. Identifying abnormal fluctuations or drifts in transient micro-deformation data can be understood as comparing and analyzing the current transient micro-deformation data acquired in real time with transient micro-deformation data from a previous period (e.g., the first N sampling points or a preset time window) to determine whether the current data significantly deviates from the normal trend. Statistical methods can be used, such as moving average, standard deviation analysis, Kalman filtering, or machine learning-based anomaly detection algorithms, such as isolated forests or local anomaly factors. The aim is to promptly identify and label unreliable data points that may be caused by noise, interference, or sensor malfunction. Real-time correction of transient micro-deformation data exhibiting abnormal fluctuations or drifts involves immediately taking measures to process the identified abnormal data and restore its accuracy and usability. For example, interpolation methods (such as linear interpolation and spline interpolation) can be used to fill missing or abnormal data points, or smoothing filters (such as moving average filtering and Gaussian filtering) can be used to eliminate high-frequency noise. In more complex scenarios, predictive models can be combined to predict normal values ​​based on historical data and current trends, and these predicted values ​​can replace abnormal values. The aim is to ensure that the deformation data used for subsequent compression pressure adjustments is accurate, reliable, and smooth, thereby avoiding misjudgments and improper operations caused by data anomalies.

[0039] In one embodiment, it is assumed that during the application of the e-cigarette casing, a flexible pressing module is applying local pressing pressure to the casing material. At this time, a high-precision micro-displacement sensor array integrated on the pressing module continuously collects transient micro-deformation data of the contact area between the casing material and the e-cigarette casing at a frequency of 1000 times per second. This data includes local height changes and deformation rates at various points on the contact surface. The system compares the currently collected deformation data with the data from the previous 50 sampling points in real time using a sliding window. For example, it calculates the deviation between the current data point and the average value within the sliding window and compares it with a preset threshold. If the deviation of a data point exceeds 3 standard deviations, it is marked as abnormal fluctuation data. Once abnormal fluctuation data is identified, the system immediately initiates a real-time correction mechanism. For example, if a transient high-frequency spike is detected, the system uses median filtering or wavelet denoising algorithms to smooth it and eliminate noise effects. If a sustained, unexpected drift is detected in the data over a short period, the system may use linear interpolation based on historical trends or Kalman filtering to estimate and replace the outlier. The transient micro-deformation data, after real-time correction, will serve as a more accurate and reliable input for subsequent comparison with preset ideal deformation response characteristics. Based on this, the driving units in the corresponding areas of the flexible pressing module will be precisely adjusted to achieve adaptive adjustment of local pressing pressure. For example, if the corrected data shows that the deformation rate of a certain area is lower than expected, the system will increase the pressing pressure in that area accordingly to ensure uniform adhesion.

[0040] It should be noted that analyzing the instantaneous rate of change and frequency components of transient micro-deformation data exhibiting abnormal fluctuations or drifts aims to gain a deeper understanding of the intrinsic characteristics of abnormal signals. The instantaneous rate of change reflects the degree and speed of abrupt changes in deformation, while the frequency components reveal the periodic or non-periodic characteristics of abnormal fluctuations. Through signal processing techniques such as Fourier transform and wavelet analysis, these features can be precisely extracted, thereby identifying non-periodic high-frequency fluctuations that do not conform to normal deformation patterns. These high-frequency fluctuations are often early manifestations of noise or localized damage. The purpose of comparing non-periodic high-frequency fluctuations with the preset deformation rate range of transient micro-deformation data is to establish a discrimination criterion to distinguish the specific source of abnormal fluctuations. The preset deformation rate range is determined based on extensive experimental data and accumulated experience, defining a reasonable rate range for material deformation under normal production conditions. When detected non-periodic high-frequency fluctuations exceed this range, and their characteristics do not match known noise patterns, they are more likely to indicate material damage. Conversely, if their characteristics highly match environmental noise patterns, they can be preliminarily identified as production environment noise. Dynamic filtering is applied to non-periodic high-frequency fluctuations identified as noise in the production environment. The aim is to effectively remove interference and restore the authenticity of the data. Unlike traditional static filtering, dynamic filtering adaptively adjusts filtering parameters, such as cutoff frequency and filter order, based on real-time changes in the noise's frequency and amplitude. This ensures that while removing noise, the effective information contained in the transient micro-deformation data is preserved to the maximum extent, avoiding over-filtering or under-filtering. For example, when a sudden increase in noise intensity is detected within a specific frequency range, the filter's gain or bandwidth can be adjusted in real time to more effectively suppress the noise.

[0041] In one embodiment, it is assumed that during the application of the e-cigarette casing, the displacement sensor of the flexible pressing module continuously monitors the transient micro-deformation data of the contact area between the casing material and the e-cigarette casing. When the system identifies abnormal fluctuations in the transient micro-deformation data by comparing it with historical data, such as a sudden high-frequency oscillation in the deformation signal in a certain local area, the control system immediately performs signal processing on the abnormal fluctuation data, for example, by analyzing its instantaneous rate of change and frequency components using short-time Fourier transform (STFT) or continuous wavelet transform (CWT). If the analysis results show that the high-frequency fluctuation has a low instantaneous rate of change, and its frequency components are mainly concentrated in a specific narrow band, while its amplitude fluctuates within a preset deformation rate range and matches the vibration frequency characteristics of known equipment in the production workshop, the system determines that the non-periodic high-frequency fluctuation originates from environmental noise. For this type of noise, the system activates an adaptive digital filter, such as a Kalman filter or an adaptive notch filter. The filter dynamically adjusts its filtering parameters (such as center frequency, bandwidth, or gain) based on the real-time detected noise frequency and amplitude to precisely suppress the noise component while preserving the effective information of the deformation data to the maximum extent. Conversely, if the analysis results show that the high-frequency fluctuation has an extremely high instantaneous rate of change, a wide frequency component distribution, and an amplitude that significantly exceeds the preset deformation rate range, and highly matches the preset characteristic spectrum of material tearing or wrinkling, the system will determine that the non-periodic high-frequency fluctuation originates from material damage. In this case, the system will not simply perform filtering but will immediately trigger an alarm and may adjust subsequent quality inspection procedures, such as increasing the frequency of visual inspection of the area or initiating additional non-destructive testing to further confirm the nature and severity of the damage.

[0042] It should be noted that the instantaneous rate of change refers to the speed at which the transient micro-deformation data changes numerically over a very short period of time, reflecting the severity of the deformation; the frequency component refers to the energy distribution of the transient micro-deformation data in different frequency bands, revealing the periodic or random characteristics of deformation fluctuations. These parameters can be obtained through signal processing methods such as difference operations, Fourier transforms, or wavelet analysis on the original transient micro-deformation data. The material damage feature map can be understood as a pre-established database or model that stores the typical instantaneous rate of change and frequency component characteristics of various known material damage types (e.g., scratches, cracks, delamination, bubbles, etc.) exhibited in displacement sensor signals. This map can be constructed through experiments, simulations, or historical data analysis, aiming to provide a reliable reference benchmark for damage identification. In practical applications, the comparison process can be implemented using pattern recognition, machine learning algorithms (such as support vector machines and neural networks), or rule-based expert systems. When the acquired instantaneous rate of change and frequency components are highly similar to a certain damage feature in the spectrum or fall within its preset matching threshold range, a match is considered to have occurred, thus confirming that the fluctuation originates from material damage. Conversely, if there is no match, the possibility of material damage is ruled out, and it is attributed to noise from the production environment.

[0043] In one embodiment, assuming that during the application of the electronic cigarette casing, a displacement sensor detects a non-periodic high-frequency fluctuation in transient micro-deformation data. The system first analyzes this data, calculating its instantaneous rate of change to, for example, 5 micrometers per millisecond, with its main frequency components concentrated in a narrow band between 500Hz and 1000Hz. Subsequently, the system compares these characteristics with a preset material damage feature map. This map may contain a "microcrack" feature entry, with an instantaneous rate of change ranging from 4 to 6 micrometers per millisecond and a frequency component of 450Hz to 1100Hz. Since the currently detected fluctuation characteristics highly match the "microcrack" feature entry, the system confirms that the non-periodic high-frequency fluctuation originates from material damage. Conversely, if the detected fluctuation has a lower instantaneous rate of change and its frequency components are distributed across a wider low-frequency band, such as 10Hz-50Hz, and there is no matching entry in the material damage map, the system determines that the fluctuation originates from environmental noise, such as equipment vibration. In this way, the production line can take different measures based on the true source of the fluctuation. For example, it can initiate defect marking and scrapping processes for material damage, while only data filtering may be performed for environmental noise, thus achieving smarter and more efficient production control.

[0044] It should be noted that "damage severity threshold" refers to a pre-set numerical limit used to quantify the severity of material damage. These thresholds can be determined based on historical data, material properties, product quality standards, or expert experience. For example, damage can be divided into minor, moderate, and severe levels, with corresponding instantaneous change rate and frequency component ranges set for each level. When the instantaneous change rate and frequency component characteristics of detected material damage fall within a certain preset range, it is marked as the corresponding damage severity level. "Damage severity level labeling" refers to the process of classifying and identifying identified material damage according to its severity. For example, it can be labeled as "minor damage," "moderate damage," or "severe damage," or a numerical rating system (e.g., 1-5). This labeling provides a quantitative basis for subsequent quality inspection and processing. In practical applications, a "quality inspection system" can be understood as a subsystem in an automated production line responsible for product quality inspection, which may include visual inspection equipment, X-ray inspection equipment, or other non-destructive testing equipment. "Defect assessment priority" refers to the priority order for processing defects of different severity levels within the quality inspection system. For example, severely damaged products may need to be rejected immediately or reworked, while slightly damaged products may be allowed to proceed to the next process or undergo partial repair. The "processing procedure" refers to the specific operational steps taken for defects of different severity levels. For instance, severe damage may trigger a line stop alarm and automatic rejection; moderate damage may trigger manual re-inspection and partial repair; and slight damage may simply be recorded and allowed to proceed.

[0045] See Figure 2 , Figure 2 This is a schematic diagram of an automated production line control system for electronic cigarette casing application, provided in one embodiment of this application. The automated production line control system 200 for electronic cigarette casing application includes: The calibration reference establishment module 210 is used to establish a calibration reference, which includes an independently installed optical reference point; Calculation module 220 is used to calculate the position of the camera relative to the world coordinate system based on the optical reference point; The imaging module 230 is used to capture images of the position of the electronic cigarette casing; The shell posture recognition module 240 is used to calculate the actual position of the electronic cigarette shell in the world coordinate system based on the position of the camera relative to the world coordinate system and the position image of the electronic cigarette shell. The posture deviation recording module 250 is used to calculate the posture deviation of the electronic cigarette shell based on the actual position of the electronic cigarette shell and the preset ideal clamping position of the electronic cigarette shell. The motion trajectory adjustment module 260 is used to adjust the preset attachment motion trajectory according to the posture deviation; The pressing pressure adaptive adjustment module 270 is used to adaptively adjust the applied local pressing pressure according to the posture deviation and the adjusted attachment motion trajectory.

[0046] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0047] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically include computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0048] The foregoing has provided a detailed description of the preferred embodiments of this application. However, this application is not limited to the above-described embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application. All such equivalent modifications or substitutions are included within the scope defined in this application.

Claims

1. A control method for an automated production line for electronic cigarette casing coating, characterized in that, include: Establish a calibration reference, which includes an independently installed optical reference point; Calculate the camera's position relative to the world coordinate system based on the optical reference point; Take an image of the electronic cigarette casing's position; Based on the position of the camera relative to the world coordinate system and the position image of the electronic cigarette casing, calculate the actual position of the electronic cigarette casing in the world coordinate system; The posture deviation of the electronic cigarette shell is calculated based on the actual position of the electronic cigarette shell and the preset ideal clamping position of the electronic cigarette shell. Adjust the preset attachment motion trajectory based on the posture deviation; Based on the posture deviation and the adjusted attachment trajectory, the applied local pressing pressure is adaptively adjusted.

2. The method according to claim 1, characterized in that, The step of calculating the actual position of the electronic cigarette casing in the world coordinate system based on the position of the camera relative to the world coordinate system and the position image of the electronic cigarette casing includes: Analyze the optical characteristics of preset feature points in the position image of the electronic cigarette shell, the optical characteristics including the average brightness, contrast and grayscale histogram distribution skewness of the preset feature points; The optical properties of the preset feature points are compared with the preset reference optical properties to obtain the differences in optical properties; Based on the differences in optical properties, the image preprocessing parameters are adjusted, including gamma correction curves, local contrast enhancement parameters, or nonlinear brightness mapping functions. Based on the differences in optical properties, the parameters of the feature point recognition algorithm are adjusted. The feature point recognition algorithm parameters include edge detection threshold, gradient calculation method, matching tolerance or multi-scale feature descriptor. Based on the adjusted image preprocessing parameters and the adjusted feature point recognition algorithm parameters, the actual position of the electronic cigarette shell in the world coordinate system is calculated.

3. The method according to claim 1, characterized in that, The step of adaptively adjusting the applied local pressing pressure based on the posture deviation and the adjusted attachment motion trajectory includes: During the application of the local pressing pressure, the optical characteristics of the actual contact surface between the skin material and the electronic cigarette shell are obtained. The actual contact surface optical characteristics include microscopic reflectivity, gloss and surface texturing. By comparing the actual contact surface optical characteristics with the preset contact surface optical characteristics, the differences in the contact surface optical characteristics are obtained; The applied local pressing pressure is adaptively adjusted based on the posture deviation, the adjusted attachment trajectory, and the differences in the optical characteristics of the contact surface.

4. The method according to claim 1, characterized in that, The step of adaptively adjusting the applied local pressing pressure includes: Obtain microscopic spectral reflectance data of the contact surface between the adhesive backing layer of the skin material and the electronic cigarette shell; By comparing the microscopic spectral reflectance data with the preset ideal spectral reflectance characteristics, the differences in the microscopic properties of the skin material are obtained. Based on the posture deviation, the adjusted attachment trajectory, and the differences in the microstructure of the adhesive material, the applied local pressing pressure is adaptively adjusted.

5. The method according to claim 1, characterized in that, The step of adaptively adjusting the applied local pressing pressure includes: During the application of the local pressing pressure, transient micro-deformation data of the contact area between the skin material and the electronic cigarette shell are acquired. The transient micro-deformation data includes the local height change, deformation rate, and deformation recovery of the contact area. By comparing the transient microscopic deformation data with the preset ideal deformation response characteristics, the deformation response difference is obtained; Based on the difference in deformation response, the driving unit in the corresponding area of ​​the flexible pressing module is adjusted to adjust the applied local pressing pressure.

6. The method according to claim 5, characterized in that, The steps following the acquisition of transient micro-deformation data of the contact area between the adhesive material and the electronic cigarette shell include: Continuously monitor the transient micro-deformation data; By comparing current transient microdeformation data with historical transient microdeformation data, abnormal fluctuations or drifts in transient microdeformation data can be identified. The transient microscopic deformation data of the abnormal fluctuations or drifts are corrected in real time.

7. The method according to claim 6, characterized in that, The step of real-time correction of the transient microscopic deformation data of the abnormal fluctuations or drifts includes: Analyze the instantaneous rate of change and frequency components of the transient micro-deformation data of the abnormal fluctuations or drifts to identify the existence of non-periodic high-frequency fluctuations; By comparing the non-periodic high-frequency fluctuations with a preset deformation rate range, it can be determined whether the non-periodic high-frequency fluctuations originate from production environment noise or material damage. The non-periodic high-frequency fluctuations identified as production environment noise are subjected to dynamic filtering processing, wherein the dynamic filtering processing adaptively adjusts the filtering parameters according to the frequency and amplitude of the production environment noise; Real-time correction is performed on the filtered transient micro-deformation data.

8. The method according to claim 7, characterized in that, The steps for distinguishing whether the non-periodic high-frequency fluctuations originate from production environment noise or material damage include: Obtain the instantaneous rate of change and frequency components of the transient micro-deformation data of the abnormal fluctuations or drifts; The instantaneous rate of change and frequency components of the transient micro-deformation data of the abnormal fluctuation or drift are compared with a preset material damage feature map, which contains the instantaneous rate of change and frequency component characteristics of different types of material damage in the displacement sensor signal. When the instantaneous rate of change and frequency components of the transient micro-deformation data of the abnormal fluctuation or drift match the material damage feature spectrum, it is confirmed that the non-periodic high-frequency fluctuation originates from material damage. When the instantaneous rate of change and frequency components of the transient micro-deformation data of the abnormal fluctuation or drift do not match the material damage characteristic spectrum, it is confirmed that the non-periodic high-frequency fluctuation originates from production environment noise.

9. The method according to claim 8, characterized in that, The steps following confirmation that the non-periodic high-frequency fluctuations originate from material damage include: When it is confirmed that the non-periodic high-frequency fluctuations originate from material damage, the non-periodic high-frequency fluctuations identified as material damage are marked with a damage severity level based on the instantaneous change rate and frequency component characteristics of the non-periodic high-frequency fluctuations of material damage, combined with a preset damage severity threshold. Based on the severity level of the damage, the subsequent quality inspection system will adjust the evaluation priority and processing procedures for defects.

10. A control system for an automated production line for electronic cigarette casing coating, characterized in that, include: A calibration reference establishment module is used to establish a calibration reference, which includes an independently installed optical reference point; The calculation module is used to calculate the position of the camera relative to the world coordinate system based on the optical reference point; The camera module is used to capture images of the electronic cigarette casing's position. The shell posture recognition module is used to calculate the actual position of the electronic cigarette shell in the world coordinate system based on the position of the camera relative to the world coordinate system and the position image of the electronic cigarette shell; The posture deviation recording module is used to calculate the posture deviation of the electronic cigarette shell based on the actual position of the electronic cigarette shell and the preset ideal clamping position of the electronic cigarette shell. The motion trajectory adjustment module is used to adjust the preset attachment motion trajectory according to the posture deviation; The pressing pressure adaptive adjustment module is used to adaptively adjust the applied local pressing pressure according to the posture deviation and the adjusted attachment motion trajectory.

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