Intelligent dynamic vibration packaging control method and system based on Internet of Things

Abstract

The invention provides an intelligent dynamic vibration packaging control method and system based on the Internet of Things, and relates to the technical field of packaging control, and the method comprises the steps: carrying out the initialization of an Internet of Things node and the construction of a packaging working condition digital twin; constructing a dynamic vibration feature vector through vibration state sensing; dynamically generating an edge control strategy based on the packaging working condition digital twin and the dynamic vibration feature vector; and dynamically adjusting and executing an edge control strategy to complete packaging control. According to the invention, the problem that a packaging control system cannot timely identify and respond to abnormal disturbances such as micro-amplitude vibration or structural resonance in a high-speed lamination process due to the lack of real-time sensing and dynamic adaptability to a packaging field state in the prior art can be solved; the technical problem that the packaging precision, the finished product yield and the equipment operation stability are further affected is solved, the technical target of dynamic packaging process regulation and control based on Internet of Things node collaborative perception is achieved, and the technical effect of improving the packaging control precision is achieved.

Description

Technical Field

[0001] This application relates to the field of packaging control technology, and in particular to an intelligent dynamic vibration packaging control method and system based on the Internet of Things. Background Technology

[0002] With the continuous development of intelligent manufacturing and high-precision packaging technologies, traditional mechanical or fixed-parameter packaging control methods are no longer sufficient to meet the response requirements of complex environmental disturbances. This is especially true in high-speed packaging scenarios with dynamic vibration disturbances, where the contradiction between system stability and control response speed becomes increasingly prominent. Currently, in industrial fields such as high-end display panels, precision components, and flexible packaging, the packaging process is extremely sensitive to vibration. Even minor vibration fluctuations can easily cause problems such as bonding misalignment, air bubble residue, and uneven pressure, directly affecting product yield and stability.

[0003] Currently, traditional packaging control largely relies on a single physical controller or preset rule parameters, lacking real-time perception and dynamic adaptation capabilities to the packaging environment. When faced with issues such as micro-vibrations caused by high-speed bonding or structural resonance caused by aging of equipment components, the system typically cannot adjust the control mode in a timely manner, leading to the accumulation of packaging errors. Furthermore, existing packaging equipment control strategies often rely on manual intervention and decision-making through a central server or human-machine interface, resulting in prolonged response times, high resource consumption, and a lack of edge intelligence processing capabilities, leading to overall sluggish system response and imprecise control.

[0004] In summary, existing technologies suffer from a lack of real-time perception and dynamic adaptation capabilities to the packaging environment. This results in the control system being unable to promptly identify and respond to abnormal disturbances such as micro-vibrations or structural resonances during the high-speed bonding process, further impacting packaging accuracy, product yield, and equipment operational stability. Summary of the Invention

[0005] The purpose of this application is to provide an intelligent dynamic vibration packaging control method and system based on the Internet of Things, in order to solve the technical problem in the prior art that the lack of real-time perception and dynamic adaptation capability of the packaging site state leads to the control system's inability to timely identify and respond to abnormal disturbances such as micro-vibration or structural resonance during the high-speed bonding process, which further affects the packaging accuracy, product yield and equipment operation stability.

[0006] In view of the above problems, this application provides an intelligent dynamic vibration packaging control method and system based on the Internet of Things.

[0007] In a first aspect, this application provides an intelligent dynamic vibration packaging control method based on the Internet of Things (IoT), implemented through an intelligent dynamic vibration packaging control system based on the IoT, including: initializing IoT nodes and constructing a digital twin of the packaging condition; constructing a dynamic vibration feature vector through vibration state perception; dynamically generating an edge control strategy based on the digital twin of the packaging condition and the dynamic vibration feature vector; and dynamically adjusting and executing the edge control strategy to complete the packaging control.

[0008] Preferably, the IoT-based intelligent dynamic vibration packaging control method further includes: deploying IoT nodes in the packaging device; collecting packaging object attribute information based on the IoT nodes; and generating a packaging working condition digital twin based on the packaging object attribute information at the edge node.

[0009] Preferably, the IoT-based intelligent dynamic vibration packaging control method further includes: the IoT node includes a vibration sensing node, an edge node, and a control execution node, and the vibration sensing node, the edge node, and the control execution node are connected through communication.

[0010] Preferably, the IoT-based intelligent dynamic vibration packaging control method further includes: collecting vibration data of the packaging device through the vibration sensing node and reporting it to the edge node; and performing data preprocessing of the vibration data through the edge node to construct the dynamic vibration feature vector.

[0011] Preferably, the IoT-based intelligent dynamic vibration packaging control method further includes: the edge control strategy being transmitted from the edge node to the control execution node; the intelligent control unit being driven by the control execution node; and vibration response compensation being performed according to a dual-channel feedback control mechanism and fed back to the intelligent control unit.

[0012] Preferably, the IoT-based intelligent dynamic vibration encapsulation control method further includes: receiving internal state feedback from the control execution node through a first channel; receiving external state feedback from the vibration sensing node through a second channel; and performing dynamic error calculation based on the edge control strategy, internal state feedback, and external state feedback to generate a vibration response compensation strategy.

[0013] Preferably, the IoT-based intelligent dynamic vibration packaging control method further includes: running an adaptive control algorithm based on the digital twin of the packaging condition and the dynamic vibration feature vector at the edge node; judging the over-limit trend and irregular disturbance according to the adaptive control algorithm, and selecting the optimal control mode in combination with the packaging type; and generating the edge control strategy by outputting the control command based on the optimal control mode through the edge node.

[0014] Preferably, the IoT-based intelligent dynamic vibration encapsulation control method further includes: uploading the dynamic vibration feature vector, edge control strategy, and execution response effect to a cloud node based on a preset collaboration period; constructing a vibration-control-response mapping through the cloud node; and optimizing the edge control strategy based on the vibration-control-response mapping if the decrease value of the execution response effect monitored by the cloud node exceeds a decrease threshold.

[0015] Preferably, the IoT-based intelligent dynamic vibration encapsulation control method further includes: detecting IoT node faults through a distributed fault perception mechanism; performing fault-tolerant detection of the distributed fault perception link based on data encryption permission verification; activating the local node perception mechanism based on the fault detection result and generating a fault log to push alarm nodes.

[0016] Secondly, this application also provides an IoT-based intelligent dynamic vibration packaging control system for executing the IoT-based intelligent dynamic vibration packaging control method as described in the first aspect, comprising: a twin construction module for initializing IoT nodes and constructing a digital twin of the packaging condition; a feature vector construction module for constructing a dynamic vibration feature vector through vibration state sensing; a control strategy generation module for dynamically generating an edge control strategy based on the digital twin of the packaging condition and the dynamic vibration feature vector; and a control strategy execution module for dynamically adjusting and executing the edge control strategy to complete the packaging control.

[0017] The technical solution provided in this application has at least the following technical effects or advantages: by achieving the technical goal of dynamic packaging process regulation based on IoT node collaborative sensing, edge intelligent analysis and adaptive vibration suppression control, the technical effect of improving the agility of the packaging process in response to complex disturbances, the accuracy of packaging control, and the reliability and self-optimization capability of system operation is achieved.

[0018] The above description is merely an overview of the technical solution of this application. To better understand the technical means of this application and to facilitate its implementation according to the description, and to make the above and other objects, features, and advantages of this application more apparent, specific embodiments of this application are described below. It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent through the following description. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the IoT-based intelligent dynamic vibration encapsulation control method of this application. Figure 2 This is a schematic diagram of the structure of the IoT-based intelligent dynamic vibration packaging control system of this application.

[0021] Figure labeling: Twin construction module 11, Feature vector construction module 12, Control strategy generation module 13, Control strategy execution module 14. Detailed Implementation

[0022] This application provides an IoT-based intelligent dynamic vibration packaging control method and system, solving the technical problem in existing technologies where the lack of real-time perception and dynamic adaptation to the packaging site conditions leads to the control system's inability to promptly identify and respond to abnormal disturbances such as micro-vibrations or structural resonances during high-speed bonding, further affecting packaging accuracy, product yield, and equipment operational stability. It achieves the technical goal of dynamic packaging process regulation based on IoT node collaborative perception, edge intelligent analysis, and adaptive vibration suppression control, thereby improving the packaging process's agility in responding to complex disturbances, the accuracy of packaging control, and the system's reliability and self-optimization capabilities.

[0023] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. It should be understood that this application is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. It should also be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all of them.

[0024] Example 1, please refer to the appendix. Figure 1 This application provides an intelligent dynamic vibration packaging control method based on the Internet of Things (IoT), which is applied to an intelligent dynamic vibration packaging control system based on the IoT, and specifically includes the following steps: S1: Perform IoT node initialization and encapsulation to construct a digital twin of the operating conditions.

[0025] Specifically, the initialization process involves configuring and starting up all IoT nodes deployed in the encapsulated device or environment. IoT nodes include vibration sensing nodes, edge computing nodes, and control execution nodes. Each type of node needs to be assigned a unique identification address, communication protocol parameters, sensor calibration data, and collaborative relationships with other nodes. The initialization process also includes zero-point calibration of sensors, setting signal amplification ratios, and configuring data sampling frequencies.

[0026] Next, after the IoT nodes are initialized and begin collecting data, a digital twin of the packaging process is constructed. By fusing and analyzing the real-time acquired attribute information of the packaged object, the status of the packaging equipment, and environmental conditions, a model corresponding to the actual packaging process is established in virtual space. The digital twin of the packaging process can reproduce the dynamic response of the packaged object under multi-dimensional factors such as transportation path, clamping process, and external vibration, and can also predict potential abnormal states, such as resonance, impact damage, or attitude deviation.

[0027] S2: Construct dynamic vibration feature vectors through vibration state perception.

[0028] Specifically, vibration sensing nodes (such as accelerometers, gyroscopes, and vibrometers) installed on the packaging device are used to continuously sense and record the vibration behavior of the packaging device, thereby forming a set of characteristic values ​​that can dynamically reflect its vibration state, including multiple dimensions such as vibration intensity, frequency, duration, and direction changes.

[0029] Next, the vibration data collected by the vibration sensing node and preprocessed by the edge node is further refined into a dynamic vibration feature vector, which includes peak acceleration, root mean square acceleration (representing the overall vibration energy), dominant frequency, spectral energy distribution, vibration duration, etc., with clear time labels and can be updated over time.

[0030] S3: Based on the digital twin of the packaging condition and the dynamic vibration feature vector, dynamically generate an edge control strategy.

[0031] Specifically, the target vibration threshold is determined based on the digital twin of the packaging conditions. A maximum permissible vibration intensity value is set based on the packaging device's tolerance and structural sensitivity; vibrations exceeding the target threshold are considered potentially damaging to the packaging device. Spectral limits are determined based on the digital twin of the packaging conditions because vibrations in certain frequency bands may resonate with the packaging device's natural frequencies, causing destructive amplification. Spectral analysis identifies frequency bands that are not permitted or need to be suppressed. Control strategy indices are determined based on the digital twin of the packaging conditions. Based on the digital twin simulation results and risk assessment, one or more suitable control mechanisms are selected from a pre-set control strategy library, including whether to activate the active vibration damping system, whether to switch the packaging rhythm, and whether to adjust the structural support force. Each control strategy corresponds to a strategy number, which is matched to the strategy index number based on the digital twin simulation results for rapid execution. The digital twin of the packaging conditions is used to predict the possible response under certain operations. The dynamic vibration feature vector is a set of key indicators collected and extracted in real time by vibration sensing nodes, including the intensity, frequency, directionality, and energy distribution of the current vibration. By combining the digital twin of the encapsulated operating conditions with dynamic vibration feature vectors, an edge control strategy can be dynamically generated to produce the most suitable control measures. The edge control strategy changes according to the real-time operating conditions.

[0032] S4: Dynamically adjust and execute the edge control strategy to complete the encapsulation control.

[0033] Specifically, the dynamic adjustment of the edge control strategy adjusts the current control method based on real-time changes in vibration data, thereby achieving stable control over the entire packaging process, including maintaining the target vibration level, adjusting the pressing speed, and controlling the jig movement, thus achieving the goal of energy saving and high efficiency.

[0034] Furthermore, this application also includes: deploying IoT nodes in the packaging device; collecting packaging object attribute information based on the IoT nodes; and generating a packaging condition digital twin based on the packaging object attribute information at the edge node.

[0035] Specifically, IoT nodes are deployed within the packaging device, which consists of electronic modules capable of sensing, communication, and computation. These IoT nodes have the ability to communicate with networks, collect data in real time, and perform preliminary processing.

[0036] Next, based on the IoT nodes collecting the attribute information of the objects to be packaged, the system performs state recognition and information acquisition for each object to be packaged. The attribute information of the packaged objects may include the object's type, size, mass, vibration resistance level, etc.

[0037] Next, IoT nodes include edge nodes, which are processing devices with local computing and modeling capabilities deployed close to the data source. The acquired packaged object attribute information is sent to the edge nodes, where a digital twin of the packaging process based on the packaged object attribute information is generated. This constructs a virtual model that matches the actual packaging process, enabling real-time simulation of variables (such as pressure, speed, and vibration) during packaging and predicting whether the packaging method is suitable for the packaging device.

[0038] Furthermore, this application also includes: the Internet of Things node includes a vibration sensing node, an edge node, and a control execution node, and the vibration sensing node, the edge node, and the control execution node are connected through communication.

[0039] Specifically, IoT nodes include vibration sensing nodes, which are intelligent sensing devices that monitor physical vibration information. Vibration sensing nodes integrate high-sensitivity accelerometers, gyroscopes, or MEMS components, and can collect parameters such as vibration intensity, direction, and frequency from the packaged equipment or object in real time, thereby providing basic data to determine whether there is excessive impact, equipment malfunction, or risk of damage to the object.

[0040] Meanwhile, IoT nodes also include edge nodes, which are computing devices deployed near the packaging site and possessing data processing and decision-making capabilities. Edge nodes can immediately analyze, model, and respond to data uploaded by vibration sensing nodes, avoiding time delays caused by remote communication.

[0041] In addition, IoT nodes also include control execution nodes, which are directly connected to or embedded in specific execution devices, such as active vibration damping systems, flexible grippers, and motor adjustment modules. The task of the control execution node is to accurately execute the corresponding actions after receiving control commands from the edge node, such as adjusting the clamping force of the packaging mechanism, changing the conveying speed, or activating vibration suppression devices.

[0042] Nodes with different functions are connected through communication to form a complete collaborative control network. The communication method can be a wired bus structure or a wireless transmission protocol, such as Wi-Fi, Bluetooth, or Zigbee. Through the interconnection mechanism, vibration data is transmitted from the vibration sensing node to the edge node for analysis, and then the edge node issues adjustment commands to the control execution node, forming a fast and efficient closed-loop response link.

[0043] Furthermore, this application also includes: collecting vibration data of the packaging device through the vibration sensing node and reporting it to the edge node; and performing data preprocessing of the vibration data through the edge node to construct the dynamic vibration feature vector.

[0044] Specifically, vibration data is collected from the packaging device through vibration sensing nodes. This involves real-time monitoring of vibration during device operation using vibration sensor nodes deployed on the packaging equipment or platform. Vibration sensing nodes equipped with accelerometers or inertial measurement units can capture information such as impact intensity, vibration frequency, duration, and directional changes, which can then be used to determine whether the packaging process is stable and whether there are abnormal impacts or continuous vibrations. Next, the vibration sensing nodes report the vibration data to edge nodes, i.e., via a local network (such as Wi-Fi, Zigbee, or Ethernet) to a nearby deployed edge computing device.

[0045] Subsequently, vibration data preprocessing is performed through edge nodes, including basic operations such as denoising, normalization, filtering, and time-window moving average to eliminate sensor errors and invalid interference, thereby improving data quality. Preprocessed vibration data is more stable and reliable, facilitating the extraction of representative feature variables. Finally, a dynamic vibration feature vector is constructed. Based on the preprocessed vibration data, several key indicators accurately representing the current vibration state are extracted and combined into a mathematical vector for subsequent analysis and decision-making. This vector includes parameters such as peak acceleration, root mean square acceleration, dominant frequency, and spectral energy density distribution, forming a dynamic sequence with time labels. Table 1 shows a partial record of the most recent construction of the dynamic vibration feature vector.

[0046] Table 1: Partial records of the most recent construction of dynamic vibration feature vectors Timestamp (milliseconds) <![CDATA[Peak acceleration (m / s 2 )]]> <![CDATA[Root mean square acceleration (m / s 2 )]]> Main frequency (Hz) Kurtosis (dimensionless) Skewness (dimensionless) Spectral energy concentration (%) Redundancy amplitude change rate (%) Simulation label: Disturbance type 1000 12.6 7.4 130 4.2 0.8 83.5 3.1 Small continuous disturbance 2000 15.2 8.1 135 5.3 1.1 86.9 3.6 intermittent shock disturbance 3000 10.4 6.7 120 3.9 -0.4 78.2 2.4 steady state 4000 18.9 9.8 140 6.5 1.8 89.4 4.2 Structural resonance 5000 11.7 7.2 125 4.0 0.3 80.7 2.9 Small continuous disturbance Furthermore, this application also includes: the edge control strategy is transmitted from the edge node to the control execution node; the intelligent control unit is driven by the control execution node; vibration response compensation is performed according to the dual-channel feedback control mechanism and fed back to the intelligent control unit.

[0047] Specifically, the control execution node is connected to the intelligent control unit. The intelligent control unit refers to a hardware component with adaptive capabilities, including adjusting the amplitude of vibration suppression components, adjusting the flexibility of the clamping fixture, and controlling the air pressure of the shock-absorbing base. The edge control strategy is transmitted from the edge node to the control execution node via a communication link. Upon receiving the edge control strategy, the control execution node drives the intelligent control unit, such as dynamically adjusting the damping coefficient or increasing the clamping contact surface to improve vibration suppression.

[0048] After initial adjustment, vibration response compensation is performed based on a dual-channel feedback control mechanism. The current control effect is evaluated in real time, and an optimized signal is returned to the intelligent control unit. The dual-channel feedback control mechanism simultaneously receives external physical feedback from the vibration sensing node and execution feedback from internal sensors in the control execution node. This continuously corrects the actions of the intelligent control unit, thereby achieving higher precision vibration control and more stable packaging quality.

[0049] Furthermore, this application also includes: receiving internal state feedback from the control execution node through a first channel; receiving external state feedback from the vibration sensing node through a second channel; and performing dynamic error calculation based on the edge control strategy, internal state feedback, and external state feedback to generate a vibration response compensation strategy.

[0050] Specifically, the internal status feedback of the control execution node is received through the first channel to obtain the internal operating data generated by the control execution node during the execution of the edge control strategy, including motor current, execution angle, clamping force, execution delay time, etc., which are used to reflect whether the control action is implemented as expected.

[0051] The second channel receives external status feedback from the vibration sensing node and receives actual vibration data of the environment or the surface of the packaging device collected by the vibration sensing node. This can more directly reflect the real response after physical operation, including vibration intensity, frequency, spindle displacement, or noise level.

[0052] Dynamic error calculation is performed based on edge control strategy, internal state feedback and external state feedback. The expected internal behavior is compared with the actual external response. The deviation between the current control strategy and the feedback information is analyzed, the degree of difference is quantified and its trend is judged, such as whether the error is increasing or converging. Then the control effectiveness is re-evaluated. If the dynamic error is found to be greater than the preset dynamic error threshold, a vibration response compensation strategy is generated.

[0053] Furthermore, this application also includes: running an adaptive control algorithm based on the digital twin of the packaging condition and the dynamic vibration feature vector at the edge node; judging the over-limit trend and irregular disturbance according to the adaptive control algorithm, and selecting the optimal control mode in combination with the packaging type; and generating the edge control strategy by outputting the control command based on the optimal control mode through the edge node.

[0054] Specifically, an adaptive control algorithm based on a digital twin of the packaging conditions and dynamic vibration feature vectors runs at the edge nodes. This algorithm is an intelligent control program that automatically adjusts parameters according to changes in the current packaging environment. The adaptive control algorithm does not rely on fixed logical rules but instead performs coordinated calculations based on the packaging condition information simulated in the digital twin and the dynamic vibration feature vectors constructed through vibration sensing. For example, the digital twin provides virtual model prediction capabilities (predicting the allowable vibration threshold range of the packaging material); while the dynamic vibration feature vectors provide actual sensed data (acceleration or frequency changes).

[0055] The adaptive control algorithm determines over-limit trends and irregular disturbances, analyzing whether existing vibration behavior is approaching or exceeding the set safety threshold or whether non-periodic sudden impacts or abnormal fluctuations have occurred. The optimal control mode is selected based on the packaging type; that is, when over-limit trends and irregular disturbances are identified, the most suitable control method is automatically selected by considering attributes such as the type, weight, and vibration resistance level of the packaged item.

[0056] By outputting control commands based on the optimal control mode through edge nodes, once the optimal control mode is determined, the edge node will immediately issue corresponding operation commands to the control execution node, which may involve adjusting the operating speed of the packaging equipment, activating the vibration damping mechanism, changing the clamping force, or resetting the motion trajectory, thereby generating an edge control strategy.

[0057] Furthermore, this application also includes: uploading the dynamic vibration feature vector, edge control strategy, and execution response effect to a cloud node based on a preset collaboration period; constructing a vibration-control-response mapping through the cloud node; and optimizing the edge control strategy based on the vibration-control-response mapping if the decrease value of the execution response effect monitored by the cloud node exceeds a decrease threshold.

[0058] Specifically, the preset collaboration period is a time interval or triggering condition pre-set by those skilled in the art based on actual conditions. For example, the preset collaboration period could be every 5 minutes, after each encapsulation cycle, or when triggered by a certain threshold. The cloud node is a cloud server. Based on the preset collaboration period, dynamic vibration feature vectors, edge control strategies, and execution response effects are uploaded to the cloud node. The cloud node performs data correlation analysis and model building on the received dynamic vibration feature vectors, edge control strategies, and execution response effects, constructing a vibration-control-response mapping. The vibration-control-response mapping is a multi-dimensional data mapping relationship that describes the response effects of different control strategies under specific vibration conditions. It can summarize the patterns and optimal configurations between control parameters and vibration response, thereby forming an intelligent model to guide edge control.

[0059] The cloud node continuously monitors and controls the execution response of the edge control strategy. If the decrease in the execution response exceeds a threshold, it indicates that the current edge control strategy is deteriorating. The edge control strategy is then optimized based on a vibration-control-response mapping until the optimized execution response reaches the level before the decrease. The threshold is a custom threshold set by those skilled in the art based on specific circumstances.

[0060] Furthermore, this application also includes: detecting IoT node faults through a distributed fault perception mechanism; performing fault-tolerant detection of the distributed fault perception link based on data encryption and permission verification; activating the local node perception mechanism based on the fault detection results and generating fault logs to push alarm nodes.

[0061] Specifically, a distributed fault perception mechanism is used for IoT node fault detection. This approach leverages multiple IoT nodes to collaboratively monitor for faults. Each node uses its own collected operational data and status information to jointly determine if a fault exists, such as sensor failure, communication interruption, or node disconnection. This distributed fault perception mechanism avoids detection blind spots caused by single-point failures, improving system reliability and the timeliness of fault detection.

[0062] Encryption protects communication data between nodes, preventing malicious attacks or data tampering. Access verification ensures only trusted nodes can access sensitive information, further preventing malicious attacks or data tampering. However, encrypted data may be lost during transmission due to inconsistencies in device interfaces or APIs across multiple nodes. Therefore, after IoT node fault detection, fault-tolerant detection is performed on the distributed fault-aware link that decrypts data based on encryption and access verification. This involves identifying and correcting data loss during encrypted transmission caused by inconsistencies in node device interfaces or APIs, resulting in an actual fault detection result indicating whether there are any misjudgments in the IoT node fault detection. The actual fault detection result includes both erroneous and error-free detection results. An erroneous detection result is the finding of a fault detection error after verification. If an erroneous detection result is obtained, the fault detection result is corrected. An error-free detection result is the finding of no fault detection error after verification.

[0063] If an error detection result is obtained, the local node perception mechanism is activated, and vibration data is collected and dynamic feature vectors are constructed using the local node until the IoT node recovers. A fault log is generated based on the error detection result and pushed to the alarm node for timely alerting and maintenance measures. The local node includes local vibration sensing nodes, local edge nodes, and local control execution nodes, serving as a backup node for the IoT node in case of failure.

[0064] In summary, the IoT-based intelligent dynamic vibration packaging control method provided in this application has the following technical effects: by achieving the technical goal of dynamic packaging process regulation based on IoT node collaborative sensing, edge intelligent analysis and adaptive vibration suppression control, it improves the agility of the packaging process in response to complex disturbances, the accuracy of packaging control, and the reliability and self-optimization capability of system operation.

[0065] Example 2: Based on the same inventive concept as the IoT-based intelligent dynamic vibration packaging control method in the foregoing examples, this application also provides an IoT-based intelligent dynamic vibration packaging control system. Please refer to the appendix. Figure 2 It includes: a twin construction module 11, used for initializing IoT nodes and constructing a digital twin of the encapsulation working condition; a feature vector construction module 12, used for constructing a dynamic vibration feature vector through vibration state perception; a control strategy generation module 13, used for dynamically generating an edge control strategy based on the digital twin of the encapsulation working condition and the dynamic vibration feature vector; and a control strategy execution module 14, used for dynamically adjusting and executing the edge control strategy to complete the encapsulation control.

[0066] Furthermore, the IoT-based intelligent dynamic vibration packaging control system is also used for: deploying IoT nodes in the packaging device; collecting packaging object attribute information based on the IoT nodes; and generating a packaging working condition digital twin based on the packaging object attribute information at the edge node.

[0067] Furthermore, the IoT-based intelligent dynamic vibration packaging control system is also used in that: the IoT node includes a vibration sensing node, an edge node, and a control execution node, and the vibration sensing node, the edge node, and the control execution node are connected through communication.

[0068] Furthermore, the IoT-based intelligent dynamic vibration packaging control system is also used to: collect vibration data of the packaging device through the vibration sensing node and report it to the edge node; and perform data preprocessing of the vibration data through the edge node to construct the dynamic vibration feature vector.

[0069] Furthermore, the IoT-based intelligent dynamic vibration packaging control system is also used for: transmitting the edge control strategy from the edge node to the control execution node; driving the intelligent control unit through the control execution node; and performing vibration response compensation according to the dual-channel feedback control mechanism and feeding it back to the intelligent control unit.

[0070] Furthermore, the IoT-based intelligent dynamic vibration packaging control system is also used to: receive internal state feedback from the control execution node through a first channel; receive external state feedback from the vibration sensing node through a second channel; and perform dynamic error calculation based on the edge control strategy, internal state feedback, and external state feedback to generate a vibration response compensation strategy.

[0071] Furthermore, the IoT-based intelligent dynamic vibration packaging control system is also used to: run an adaptive control algorithm based on the digital twin of the packaging condition and the dynamic vibration feature vector at the edge node; determine the over-limit trend and irregular disturbance according to the adaptive control algorithm, and select the optimal control mode in combination with the packaging type; and generate the edge control strategy by outputting the control command based on the optimal control mode through the edge node.

[0072] Furthermore, the IoT-based intelligent dynamic vibration packaging control system is also used to: upload the dynamic vibration feature vector, edge control strategy, and execution response effect to a cloud node based on a preset collaboration period; construct a vibration-control-response mapping through the cloud node; and optimize the edge control strategy based on the vibration-control-response mapping if the decrease value of the execution response effect monitored by the cloud node exceeds a decrease threshold.

[0073] Furthermore, the IoT-based intelligent dynamic vibration packaging control system is also used for: detecting IoT node faults through a distributed fault perception mechanism; performing fault-tolerant detection of the distributed fault perception link based on data encryption permission verification; activating the local node perception mechanism based on the fault detection result and generating fault logs to push alarm nodes.

[0074] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The IoT-based intelligent dynamic vibration packaging control method and specific examples in the aforementioned Embodiment 1 are also applicable to the IoT-based intelligent dynamic vibration packaging control system of this embodiment. Through the foregoing detailed description of the IoT-based intelligent dynamic vibration packaging control method, those skilled in the art can clearly understand the IoT-based intelligent dynamic vibration packaging control system of this embodiment. Therefore, for the sake of brevity, it will not be described in detail here.

[0075] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0076] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application also intends to include such modifications and variations.

Claims

1. A smart dynamic vibration packaging control method based on the Internet of Things, characterized in that, include: Perform IoT node initialization and encapsulation to construct a digital twin of the operating conditions; Constructing dynamic vibration feature vectors through vibration state perception; Based on the digital twin of the packaging condition and the dynamic vibration feature vector, an edge control strategy is dynamically generated; The edge control strategy is dynamically adjusted and executed to complete the encapsulation control.

2. The intelligent dynamic vibration packaging control method based on the Internet of Things as described in claim 1, characterized in that, The process includes initializing and encapsulating digital twins of IoT nodes, including: Deploying IoT nodes in packaging devices; Based on the IoT node, collect and encapsulate object attribute information; A digital twin of the encapsulation condition is generated at the edge node based on the attribute information of the encapsulated object.

3. The intelligent dynamic vibration packaging control method based on the Internet of Things as described in claim 2, characterized in that, The IoT node includes a vibration sensing node, an edge node, and a control execution node, which are connected via communication.

4. The intelligent dynamic vibration packaging control method based on the Internet of Things as described in claim 3, characterized in that, Dynamic vibration feature vectors are constructed through vibration state perception, including: Vibration data of the packaging device is collected by the vibration sensing node and reported to the edge node; The vibration data is preprocessed through the edge nodes to construct the dynamic vibration feature vector.

5. The intelligent dynamic vibration packaging control method based on the Internet of Things as described in claim 3, characterized in that, Dynamically adjusting the execution of the edge control strategy includes: The edge control strategy is transmitted from the edge node to the control execution node; The intelligent control unit is driven by the control execution node; Vibration response compensation is performed based on a dual-channel feedback control mechanism and fed back to the intelligent control unit.

6. The intelligent dynamic vibration packaging control method based on the Internet of Things as described in claim 5, characterized in that, Vibration response compensation is performed based on a dual-channel feedback control mechanism, including: The internal status feedback of the control execution node is received through the first channel; The external status feedback of the vibration sensing node is received through the second channel; Dynamic error calculation is performed based on the aforementioned edge control strategy, internal state feedback, and external state feedback to generate a vibration response compensation strategy.

7. The intelligent dynamic vibration packaging control method based on the Internet of Things as described in claim 2, characterized in that, Based on the digital twin of the packaging condition and the dynamic vibration feature vector, an edge control strategy is dynamically generated, including: An adaptive control algorithm based on the digital twin of the packaging condition and the dynamic vibration feature vector is run at the edge node; The adaptive control algorithm is used to determine over-limit trends and irregular disturbances, and the optimal control mode is selected based on the packaging type. The edge control strategy is generated by outputting control commands based on the optimal control mode through the edge nodes.

8. The intelligent dynamic vibration packaging control method based on the Internet of Things as described in claim 1, characterized in that, The dynamic adjustment and execution of the edge control strategy further includes: Based on a preset collaboration period, the dynamic vibration feature vector, edge control strategy, and execution response effect are uploaded to the cloud node; A vibration-control-response mapping is constructed using the cloud nodes; If the decrease in the execution response effect monitored by the cloud node exceeds the decrease threshold, edge control strategy optimization based on the vibration-control-response mapping is performed.

9. The intelligent dynamic vibration packaging control method based on the Internet of Things as described in claim 1, characterized in that, The dynamic adjustment and execution of the edge control strategy further includes: Fault detection of IoT nodes is achieved through a distributed fault perception mechanism. Fault-tolerant detection of distributed fault-aware links based on data encryption and permission verification; Based on the error detection results, the local node awareness mechanism is activated to generate fault logs and push them to alarm nodes.

10. An intelligent dynamic vibration packaging control system based on the Internet of Things, characterized in that, The steps for implementing the IoT-based intelligent dynamic vibration packaging control method according to any one of claims 1 to 9 include: The twin construction module is used for initializing IoT nodes and constructing digital twins for encapsulation conditions. The feature vector construction module is used to construct dynamic vibration feature vectors through vibration state perception. The control strategy generation module is used to dynamically generate an edge control strategy based on the digital twin of the packaging condition and the dynamic vibration feature vector. The control strategy execution module is used to dynamically adjust and execute the edge control strategy to complete the encapsulation control.

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