Intelligent vibration control method and system for automatic separation of stacked parts

Abstract

The invention discloses an intelligent vibration control method and system for automatic separation of stacked parts, and relates to the technical field of logistics separation control, and the method comprises the steps: carrying out the multi-parameter control decision of a vibration separation device according to the stacked part state feature data and the stacked part basic feature data of stacked logistics parts; obtaining a vibration separation first strategy; carrying out error separation suppression optimization analysis to obtain a vibration optimization first analysis result; carrying out flexible buffer compensation analysis to obtain a vibration optimization second analysis result; performing stack adhesion control enhanced analysis to obtain a vibration optimization third analysis result; and carrying out global tuning to obtain a vibration separation second strategy and carrying out separation tracking control. The technical problems that in the prior art, complex logistics piece characteristics are difficult to adapt, mistaken separation is prone to occurring, stacking piece adhesion cannot be effectively treated, and the stacking piece separation efficiency and accuracy are poor are solved, and the technical effect of improving the logistics stacking piece separation efficiency and accuracy is achieved.

Description

Technical Field

[0001] This application relates to the technical field of logistics separation control, specifically to an intelligent vibration control method and system for automatic separation of stacked parts. Background Technology

[0002] With the rapid development of the modern logistics industry, automated sorting systems have become the core for improving logistics efficiency and reducing operating costs. Among them, the automatic separation of stacked logistics items is a key link in the automated sorting process, directly affecting the overall performance and operational efficiency of the logistics system. However, it exposes many limitations when dealing with complex and diverse logistics items. On the one hand, logistics items are diverse in type, with significant differences in material, shape, weight, and stacking state. For example, logistics items made of different materials, such as paper boxes, plastic boxes, and metal parts, have different response characteristics during vibration. Regular-shaped and irregular-shaped logistics items also present vastly different separation difficulties. Traditional vibration separation cannot accurately control these differences, easily leading to low separation efficiency or even damage to logistics items. On the other hand, in actual logistics operations, stacked items may exhibit complex phenomena such as adhesion and adsorption. Especially in humid environments or when there is static electricity on the surface of the logistics items, the problem of stacked item adhesion is more prominent. Existing methods are difficult to effectively overcome interference factors, resulting in incomplete separation of stacked items and affecting the accuracy and smoothness of subsequent sorting operations.

[0003] Therefore, current technologies suffer from several technical problems, including difficulty in adapting to the characteristics of complex logistics components, susceptibility to accidental separation, and inability to effectively handle the adhesion of stacked components, resulting in poor efficiency and accuracy in separating stacked components. Summary of the Invention

[0004] This application provides an intelligent vibration control method and system for automatic separation of stacked parts, which solves the technical problems in the prior art, such as difficulty in adapting to the characteristics of complex logistics parts, easy occurrence of misseparation, inability to effectively handle the adhesion of stacked parts, resulting in poor efficiency and accuracy of stacked part separation, and achieves the technical effect of improving the efficiency and accuracy of logistics stacked part separation.

[0005] This application provides an intelligent vibration control method for automatic separation of stacked components. The method includes: making multi-parameter control decisions on a vibration separation device based on stacked component state characteristic data and stacked component basic characteristic data to obtain a vibration separation decision set; performing multilateral joint optimization on the vibration separation decision set based on the separation expectation bilateral elements to obtain a first vibration separation strategy; performing erroneous separation suppression optimization analysis on the first vibration separation strategy to obtain a first vibration optimization analysis result; performing flexible buffer compensation analysis on the first vibration separation strategy to obtain a second vibration optimization analysis result; performing stacked component adhesion control enhancement analysis on the first vibration separation strategy to obtain a third vibration optimization analysis result; performing global optimization on the first vibration separation strategy based on the first, second, and third vibration optimization analysis results to obtain a second vibration separation strategy; and combining the vibration separation device to perform separation tracking control on the stacked components.

[0006] In a possible implementation, the intelligent vibration control method for automatic separation of stacked components further performs the following processing: constructing a misseparation prediction model based on a set of stacked component misseparation event records; predicting misseparation of the stacked components based on the stacked component state feature data, the stacked component basic feature data, and the vibration separation first strategy, thereby obtaining predicted misseparation events; identifying the association between the predicted misseparation events and the vibration separation first strategy, thereby obtaining misseparation-related control data; identifying the association between the stacked component state feature data and the stacked component basic feature data, thereby obtaining misseparation-related stacked component features; and performing optimized feature analysis on the misseparation-related control data based on the predicted misseparation events and the misseparation-related stacked component features, thereby generating the vibration optimization first analysis result.

[0007] In a possible implementation, the intelligent vibration control method for automatic separation of stacked components further performs the following processing: simulates vibration separation of the stacked components according to the first vibration separation strategy to obtain a vibration separation simulation dataset; evaluates the damage of the stacked components according to the vibration separation simulation dataset to obtain separation damage evaluation results for each component; filters the separation damage evaluation results for each component to obtain separation damage evaluation clusters that do not meet the separation damage evaluation constraints; and uses the separation damage evaluation constraints as a buffer compensation target, performs buffer compensation feature analysis on the first vibration separation strategy according to the separation damage evaluation clusters to generate the second vibration optimization analysis result.

[0008] In a possible implementation, the intelligent vibration control method for automatic separation of stacked components further performs the following processing: obtaining stacked component adhesion characteristic data and stacked component environmental characteristic data; based on the stacked component environmental characteristic data, performing separation influence analysis on the stacked component according to the stacked component adhesion characteristic data, and obtaining adhesion separation influence analysis results; performing weakening analysis on the first vibration separation strategy according to the adhesion separation influence analysis results, and obtaining adhesion influence control weakening characteristics; performing control enhancement analysis on the first vibration separation strategy according to the adhesion influence control weakening characteristics, and generating the vibration optimization third analysis result.

[0009] In a possible implementation, the intelligent vibration control method for automatic separation of stacked components further performs the following processing: performing overlap detection on the first, second, and third vibration optimization analysis results to obtain a vibration optimization overlap detection result; performing conflict detection on the first, second, and third vibration optimization analysis results to obtain a vibration optimization conflict detection result; globally fusing the first, second, and third vibration optimization analysis results based on the vibration optimization overlap detection result and the vibration optimization conflict detection result to obtain a vibration optimization fourth analysis result; and optimizing the first vibration separation strategy based on the fourth vibration optimization analysis result to generate the second vibration separation strategy.

[0010] In a possible implementation, the intelligent vibration control method for automatic separation of stacked components further performs the following processing: obtaining vibration control multi-element of the vibration separation device, the vibration control multi-element including vibration frequency, vibration amplitude, vibration direction, and vibration duration; using the stacked component state feature data and the stacked component basic feature data as vibration control retrieval constraints, and combining the vibration control multi-element to perform vibration control scheme retrieval, obtaining a retrieved vibration control scheme set; performing trigger feature parsing based on the retrieved vibration control scheme set to construct a multi-factor constraint domain for vibration control; and performing multi-parameter control decisions based on the multi-factor constraint domain for vibration control to generate the vibration separation decision set.

[0011] In a possible implementation, the intelligent vibration control method for automatic separation of stacked components further performs the following processing: setting separation expectation bilateral constraints based on the separation expectation bilateral elements, wherein the separation expectation bilateral elements include separation rate and separation efficiency; performing bilateral constraint optimization on the vibration separation decision set based on the separation expectation bilateral constraints to obtain a vibration separation optimization set; performing weight allocation based on the separation expectation bilateral elements to construct a separation fitness function, and performing separation fitness maximization optimization on the vibration separation optimization set based on the separation fitness function to generate the first vibration separation strategy.

[0012] In a possible implementation, the intelligent vibration control method for automatic separation of stacked components further performs the following processing: extracting a first vibration separation decision based on the vibration separation decision set; performing vibration separation prediction on the stacked components based on the first vibration separation decision to obtain a first decision separation prediction result, wherein the first decision separation prediction result includes a first prediction separation rate and a first prediction separation efficiency; if the first decision separation prediction result satisfies the separation expectation bilateral constraint, adding the first vibration separation decision to the vibration separation optimization set; if the first decision separation prediction result does not satisfy the separation expectation bilateral constraint, eliminating the first vibration separation decision.

[0013] In a possible implementation, the intelligent vibration control method for automatic separation of stacked components further performs the following processing: obtaining stacked component state feature elements and stacked component basic feature elements, wherein the stacked component state feature elements include stacked shape structure, stacked center of gravity distribution, stacked contact features, and stacked tightness, and the stacked component basic feature elements include single-component mass, single-component size, single-component material, and single-component attributes; performing feature acquisition on the stacked material based on the stacked component state feature elements to obtain the stacked component state feature data; and performing feature acquisition on the stacked material based on the stacked component basic feature elements to obtain the stacked component basic feature data.

[0014] This application also provides an intelligent vibration control system for automatic separation of stacked components. The system includes: a multi-parameter control decision module, used to make multi-parameter control decisions on the vibration separation device based on the stacked component state characteristic data and the stacked component basic characteristic data, to obtain a vibration separation decision set; a multilateral joint optimization module, used to perform multilateral joint optimization on the vibration separation decision set based on the separation expectation bilateral elements, to obtain a first vibration separation strategy; a first analysis result acquisition module, used to perform erroneous separation suppression optimization analysis on the first vibration separation strategy, to obtain a first vibration optimization analysis result; a second analysis result acquisition module, used to perform flexible buffer compensation analysis on the first vibration separation strategy, to obtain a second vibration optimization analysis result; a third analysis result acquisition module, used to perform stacked component adhesion control enhancement analysis on the first vibration separation strategy, to obtain a third vibration optimization analysis result; and a separation tracking control module, used to perform global optimization of the first vibration separation strategy based on the first vibration optimization analysis result, the second vibration optimization analysis result, and the third vibration optimization analysis result, to obtain a second vibration separation strategy, and to perform separation tracking control on the stacked components in conjunction with the vibration separation device.

[0015] The proposed intelligent vibration control method and system for automatic separation of stacked components utilizes multi-parameter control decisions based on the stacked component state characteristic data and basic characteristic data of the stacked components. This process yields: a first vibration separation strategy; a first vibration optimization result through error separation suppression optimization analysis; a second vibration optimization result through flexible buffer compensation analysis; a third vibration optimization result through enhanced stacked component adhesion control analysis; and finally, global optimization to obtain a second vibration separation strategy and implement separation tracking control. This addresses the technical problems in existing technologies, such as difficulty adapting to complex component characteristics, susceptibility to error separation, and inability to effectively handle stacked component adhesion, resulting in poor separation efficiency and accuracy. Ultimately, it achieves the technical effect of improving the efficiency and accuracy of stacked component separation. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings of the embodiments of this disclosure will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0017] Figure 1 This is a schematic flowchart of an intelligent vibration control method for automatic separation of stacked components provided in an embodiment of this application.

[0018] Figure 2 This is a schematic diagram of the intelligent vibration control system for automatic separation of stacked components provided in an embodiment of this application.

[0019] Figure labeling: Multi-parameter control decision module 10, Multilateral joint optimization module 20, First analytical result acquisition module 30, Second analytical result acquisition module 40, Third analytical result acquisition module 50, Separate tracking control module 60. Detailed Implementation

[0020] The above description is merely an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below.

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description of this application will be provided in conjunction with the accompanying drawings. The described embodiments should not be considered as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] In the following description, references to "some embodiments" describe a subset of all possible embodiments. However, it is understood that "some embodiments" can be the same or different subsets of all possible embodiments and can be combined with each other without conflict. The terms "first" and "second" are used merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only.

[0023] This application provides an intelligent vibration control method for automatic separation of stacked components, such as... Figure 1 As shown, the method includes: Step S100: Based on the stacked state characteristic data and basic characteristic data of the stacked logistics components, the vibration separation device is subjected to multi-parameter control decision-making to obtain a vibration separation decision set.

[0024] Preferably, the stacked item status characteristic data mainly describes the current real-time status of the stacked logistics items. For example, the tilt angle of the stacked items; if the stacked items are tilted, it is necessary to consider how to adjust the vibration direction and force during vibration separation to avoid the logistics items slipping or being damaged. Different degrees of compactness of the stacked items require different vibration intensity and frequency. Understanding the center of gravity position of the stacked items helps to determine the appropriate vibration application point and improve the separation effect. The stacked item basic characteristic data includes the inherent attribute information of the logistics items themselves, such as the material of the logistics items. Different materials (such as paper, plastic, and metal) have different mechanical responses during vibration. Paper may be more fragile and require gentler vibration parameters. The shape of the logistics items; regular and irregular shaped logistics items have different stability and separation difficulty during vibration. The weight of the logistics items; heavier logistics items require more vibration energy to achieve separation.

[0025] Preferably, multiple control parameters of the vibration separation device are determined, including vibration frequency, vibration amplitude, and vibration direction. Different combinations produce different vibration effects. Then, through analysis of a large amount of experimental data, a mapping relationship is established between the stacked component state characteristic data, the stacked component basic characteristic data, and the control parameters of the vibration separation device. For example, when the stacked components are highly compact and the material is heavy, it is necessary to increase the vibration frequency and vibration amplitude. Based on the mapping relationship, corresponding decision rules are formulated. For example, if the tilt angle of the stacked components exceeds a threshold, the vibration direction is adjusted first to bring it to equilibrium; if the friction between the stacked components is large, the vibration frequency and amplitude are appropriately increased. Finally, based on different data combinations and decision rules, multiple possible vibration separation control schemes are generated, each scheme corresponding to specific vibration parameter settings, thereby generating a vibration separation decision set.

[0026] Furthermore, step S100 also includes step S110, obtaining stacked component state feature elements and stacked component basic feature elements. The stacked component state feature elements include stacked shape structure, stacked center of gravity distribution, stacked contact features, and stacked tightness. The stacked component basic feature elements include single component mass, single component size, single component material, and single component attributes. Step S120, performing feature acquisition on the stacked material based on the stacked component state feature elements to obtain the stacked component state feature data. Step S130, performing feature acquisition on the stacked material based on the stacked component basic feature elements to obtain the stacked component basic feature data.

[0027] Preferably, the stacked component state characteristic elements are composed of stack shape structure, stack center of gravity distribution, stack contact characteristics, and stack density. Stack shape structure refers to the overall shape and structure of the stacked components, such as a neat rectangular stack, an irregular stack, or a multi-layered staggered stack. Stack center of gravity distribution describes the position of the overall center of gravity of the stacked components; stacks with a higher center of gravity may be more prone to tilting or overturning during vibration. Stack contact characteristics include the contact conditions between stacked components, such as the size of the contact area and the flatness of the contact surface, affecting the friction and adhesion between the stacked components. Stack density indicates the degree of mutual compression between the stacked components; a denser stack requires greater vibration energy to achieve separation. Based on the stacked component state characteristic elements, various sensing and detection devices (such as 3D scanners, weighing instruments, pressure sensors, etc.) are used to collect actual features of the stacked components, obtaining stacked component state characteristic data that reflects the current state of the stacked components.

[0028] Preferably, the basic feature elements of the stacked logistics components are composed of individual component mass, individual component size, individual component material, and individual component attributes. Individual component mass refers to the weight of each individual logistics component; individual component size includes the length, width, and height of the logistics component, affecting its arrangement in the stack and its movement space during vibration; individual component material includes paper, plastic, metal, glass, etc., and different materials have different physical properties, such as elasticity, hardness, and coefficient of friction; individual component attributes include special properties, such as whether it is fragile, whether it has static electricity, and whether it is liquid packaging. Similarly, based on the basic feature elements of the stacked logistics components, feature acquisition is performed on individual logistics components in the stack, including measuring the individual component mass using high-precision weighing equipment; measuring the individual component size data using calipers, measuring tapes, etc.; determining the individual component material using material analysis instruments (such as spectrometers, hardness testers, etc.); and reviewing and recording the labels and instructions of the logistics components to obtain individual component attribute information; thus, the basic feature data of the stacked logistics components is obtained, which is used to represent the basic attributes of individual logistics components.

[0029] Further, step S100 also includes step S140, obtaining the vibration control multi-element of the vibration separation device, wherein the vibration control multi-element includes vibration frequency, vibration amplitude, vibration direction, and vibration duration; step S150, using the stacked component state feature data and the stacked component basic feature data as vibration control retrieval constraints, and combining the vibration control multi-element to perform vibration control scheme retrieval, thereby obtaining a retrieval vibration control scheme set; step S160, performing trigger feature parsing based on the retrieval vibration control scheme set to construct a vibration control multi-factor constraint domain; step S170, performing multi-parameter control decisions based on the vibration control multi-factor constraint domain to generate the vibration separation decision set.

[0030] Preferably, the adjustable parameters of the vibration separation device are obtained, namely, the vibration control multi-element, including vibration frequency (the number of vibrations per unit time), vibration amplitude (the intensity of vibration, the larger the amplitude), vibration direction (the direction of application of the vibration force), and vibration duration (the duration of vibration). Then, the stacked component state characteristic data (such as the tilt angle, tightness, and center of gravity position of the stacked components) and the stacked component basic characteristic data (such as the material, shape, and weight of the logistics component) are used as search constraints to limit the vibration control scheme to adapt to the specific characteristics and current state of the logistics component. Considering various possible combinations of multiple elements such as vibration frequency, amplitude, direction, and duration, multiple different vibration control schemes are retrieved to form a search vibration control scheme set.

[0031] Preferably, each scheme in the retrieved vibration control scheme set is analyzed to extract key triggering features related to vibration control. These may include the response characteristics of the material at specific frequencies and amplitudes, the impact of vibration in different directions on the separation of stacked parts, and the relationship between vibration duration and separation effect. Then, based on the analysis results of the triggering features, the value range and interrelationships of each vibration control element are determined, forming a multi-dimensional constraint domain for vibration control. For example, based on the material and shape of the material, the vibration frequency must be within a certain range to avoid damage to the material. At the same time, the vibration amplitude and direction are also limited by the state of the stacked parts and the basic characteristics. When vibrating in a specific direction, the amplitude cannot exceed a certain value, otherwise the material will slip. Finally, within the multi-dimensional constraint domain of vibration control, the stacked part state characteristic data, the stacked part basic characteristic data, and the actual separation requirements are comprehensively considered to optimize multiple parameters such as vibration frequency, amplitude, direction, and duration. The impact of different parameters on the separation effect, the safety of the material, and the operating efficiency of the equipment is balanced, thereby generating a set of superior vibration control schemes, forming a vibration separation decision set. Each scheme can achieve efficient and safe automatic separation of stacked parts while meeting various constraints.

[0032] Step S200: Perform multilateral joint optimization on the vibration separation decision set based on the bilateral elements of the separation expectation to obtain the first vibration separation strategy.

[0033] Step S200 further includes step S210, setting separation expectation bilateral constraints based on the separation expectation bilateral elements, wherein the separation expectation bilateral elements include separation rate and separation efficiency; step S220, performing bilateral constraint optimization on the vibration separation decision set based on the separation expectation bilateral constraints to obtain a vibration separation optimization set; step S230, assigning weights based on the separation expectation bilateral elements, constructing a separation fitness function, and performing separation fitness maximization optimization on the vibration separation optimization set based on the separation fitness function to generate the vibration separation first strategy.

[0034] Preferably, the separation expectation bilateral elements include separation rate and separation efficiency. The separation rate refers to the proportion of successfully separated items to the total number of items, while the separation efficiency refers to the number of items separated per unit time. Based on the separation rate and efficiency, separation expectation bilateral constraints are set to reflect the expectations for the vibration separation device in terms of separation effect and speed. For example, the separation rate might be set to be above 98%, and the separation efficiency to be 600 items per hour. Then, the separation expectation bilateral constraints are applied to the vibration separation decision set for bilateral constraint optimization. This involves evaluating each vibration separation scheme in the decision set to determine if it meets the separation expectation bilateral constraints. Multiple schemes that meet the bilateral constraints are then selected from the decision set, forming a vibration separation optimization set containing multiple feasible schemes that meet the standards in terms of both separation rate and separation efficiency.

[0035] Preferably, different weight values ​​are assigned to the separation rate and separation efficiency based on actual needs and the importance attached to them. For example, the separation rate weight is 0.6 and the separation efficiency weight is 0.4. Then, a separation fitness function is constructed based on the assigned weights to comprehensively evaluate the merits of each vibration separation scheme in the vibration separation optimization set. The separation fitness function may be: Separation Fitness = Separation Rate Weight × Separation Rate + Separation Efficiency Weight × Separation Efficiency (converting the separation efficiency to a proportion of the same order of magnitude as the separation rate). The separation rate and separation efficiency of each scheme are combined and calculated according to the preset weights to obtain the separation fitness value. For example, if a scheme has a separation rate of 90% and a separation efficiency of 400 logistics pieces per hour, its fitness is 0.6 × 0.9 + 0.4 × (400 / 600) ≈ 0.74. For each scheme in the vibration separation optimization set, its separation fitness value is calculated, and the scheme with the largest separation fitness value is determined. This scheme, which comprehensively considers the separation rate and separation efficiency, is the optimal vibration control strategy and is used as the first vibration separation strategy for the separation control of stacked logistics pieces to achieve the optimal vibration separation effect.

[0036] Furthermore, step S220 also includes step S221, extracting a first vibration separation decision based on the vibration separation decision set; step S222, performing vibration separation prediction on the stacked material based on the first vibration separation decision to obtain a first decision separation prediction result, the first decision separation prediction result including a first prediction separation rate and a first prediction separation efficiency; step S223, if the first decision separation prediction result satisfies the separation expectation bilateral constraint, adding the first vibration separation decision to the vibration separation optimization set; step S224, if the first decision separation prediction result does not satisfy the separation expectation bilateral constraint, eliminating the first vibration separation decision.

[0037] Preferably, a vibration control scheme is randomly selected from the vibration separation decision set as the first vibration separation decision. Based on the first vibration separation decision, the separation process of the stacked logistics components is simulated and predicted. Specifically, the stacked logistics components' stack state characteristic data (such as stack shape structure, stack center of gravity distribution, stack contact characteristics, and stack tightness) and stack basic characteristic data (such as single component mass, single component size, single component material, and single component attributes) are comprehensively considered. Combined with the vibration parameters (vibration frequency, amplitude, direction, and duration) in the first vibration separation decision, the separation situation of the stacked logistics components is predicted to obtain the first decision separation prediction result. This mainly includes the first predicted separation rate, which is the proportion of the logistics components that can be successfully separated under this decision to the total number of logistics components; and the first predicted separation efficiency, which is the predicted number of logistics components that can be separated per unit time.

[0038] Preferably, the separation prediction result of the first decision is compared with the separation expectation bilateral constraint. If both the first predicted separation rate and the first predicted separation efficiency meet the separation expectation bilateral constraint, it means that the first vibration separation decision can theoretically achieve the expected separation effect, and the first decision is added to the vibration separation optimization set. If the first predicted separation rate or the first predicted separation efficiency does not meet the separation expectation bilateral constraint, it means that the first vibration separation decision cannot achieve the expected separation target, and the decision is eliminated from consideration and no longer considered as a feasible vibration control scheme.

[0039] Step S300: Perform error separation suppression optimization analysis on the first vibration separation strategy to obtain the first analysis result of vibration optimization.

[0040] Step S300 further includes step S310, constructing a misseparation prediction model based on the stacked component misseparation event record set; step S320, predicting misseparation of the stacked components based on the stacked component state feature data, the stacked component basic feature data, and the vibration separation first strategy, according to the misseparation prediction model, to obtain predicted misseparation events; step S330, performing association identification on the vibration separation first strategy based on the predicted misseparation events, to obtain misseparation association control data; step S340, performing association identification on the stacked component state feature data and the stacked component basic feature data based on the predicted misseparation events, to obtain misseparation association stacked component features; step S350, performing optimized feature analysis on the misseparation association control data based on the predicted misseparation events and the misseparation association stacked component features, to generate the vibration optimization first analysis result.

[0041] Preferably, the stacked component misseparation event record set is a detailed record of all historical stacked component misseparation events. It contains various information at the time of each misseparation event, such as the stacked component state characteristics data (e.g., stack shape structure, center of gravity distribution, etc.), the basic characteristics data of the stacked components (single component mass, material, etc.), the vibration separation strategy adopted, and the specific circumstances of the misseparation (which components were misseparated, the form of misseparation, etc.). A model is built using machine learning (e.g., decision trees, neural networks, etc.), and trained using the data from the stacked component misseparation event record set to obtain a misseparation prediction model. This model learns the correlation between stacked component characteristics data, vibration separation strategy, and misseparation events. Then, the current stacked component state characteristics data, the basic characteristics data of the stacked components, and the determined first vibration separation strategy are used as inputs to provide to the misseparation prediction model. The model predicts whether the current stacked components will be misseparated, i.e., predicts the misseparation event, which may include whether misseparation will occur, which components may be misseparated, and the probability of misseparation.

[0042] Preferably, for predicting erroneous separation events, an in-depth analysis is conducted to determine which parameters or operations in the first vibration separation strategy are related to the occurrence of erroneous separation. Control parameters and operational information associated with erroneous separation are extracted from the first vibration separation strategy to form erroneous separation-related control data. For example, if erroneous separation is predicted to occur at the current vibration frequency and amplitude, the vibration frequency and amplitude are the control parameters associated with erroneous separation. Similarly, for predicting erroneous separation events, the analysis is conducted to determine which features in the stacked component state characteristic data and stacked component basic characteristic data are related to the occurrence of erroneous separation. Features associated with erroneous separation are extracted from the stacked component state characteristic data and stacked component basic characteristic data to form erroneous separation-related stacked component features. For example, if it is predicted that logistics components with irregular shapes and high centers of gravity are prone to erroneous separation, the shape and center of gravity distribution of the logistics components are the stacked component features associated with erroneous separation.

[0043] Preferably, the predicted misseparation events, the features of the stacked components associated with misseparation, and the control data associated with misseparation are combined for optimized feature analysis. Specifically, it considers how the characteristics of the logistics component interact with the vibration separation strategy to cause misseparation. For example, for a logistics component with a high center of gravity and an irregular shape, the current vibration direction and intensity may be inappropriate. Then, based on the results of the comprehensive analysis, the control data associated with misseparation is optimized and adjusted, such as adjusting the vibration direction, reducing the vibration amplitude, or changing the vibration frequency. Finally, the first analysis result of vibration optimization is generated, thereby optimizing the vibration separation strategy to improve the accuracy and reliability of stacked component separation.

[0044] Step S400: Perform flexible buffer compensation analysis on the first vibration separation strategy to obtain the second analysis result of vibration optimization.

[0045] Step S400 further includes step S410, performing simulated vibration separation on the stacked material components according to the first vibration separation strategy to obtain a vibration separation simulation dataset; step S420, performing damage evaluation on the stacked material components according to the vibration separation simulation dataset to obtain separation damage evaluation results for each material component; step S430, filtering the separation damage evaluation results for each material component to obtain separation damage evaluation clusters that do not meet the separation damage evaluation constraints; and step S440, using the separation damage evaluation constraints as a buffer compensation target, performing buffer compensation feature analysis on the first vibration separation strategy according to the separation damage evaluation clusters to generate the second vibration optimization analysis result.

[0046] Preferably, according to the first vibration separation strategy, virtual vibration separation is performed on the stacked logistics components. Various relevant data during the simulated vibration separation process are recorded, such as the displacement, velocity, and acceleration changes of each logistics component during vibration, the collision situation between logistics components, and the separation time and sequence, forming a vibration separation simulation dataset that reflects the separation process and state changes of the stacked logistics components under the current vibration separation strategy. Then, damage evaluation is performed using the data in the vibration separation simulation dataset to assess the potential damage to each logistics component during the simulated separation process. This may consider the material properties, stress conditions, number and intensity of collisions, or the degree of deformation of the logistics components to determine the damage situation. Consequently, for each logistics component, a corresponding separation damage evaluation result is generated, which may include the degree of damage and damage classification, such as "no damage," "minor damage," or "severe damage," to clarify the damage status of each logistics component during the simulated vibration separation process.

[0047] Preferably, based on the quality requirements, usage needs, and customer requirements of the logistics components, evaluation constraints regarding separation damage are set. For example, it is stipulated that the maximum allowable damage level for a certain type of logistics component during separation is minor damage, and severe damage is not allowed. Then, the separation damage evaluation results of each logistics component are compared with the set separation damage evaluation constraints. The damage evaluation results of logistics components that do not meet the constraints are filtered out to form a separation damage evaluation cluster. The damage evaluation results contained therein represent logistics components that may have unacceptable damage under the current vibration separation strategy. Finally, with the set separation damage evaluation constraints as the goal, that is, to make the separation damage of logistics components meet the constraints, the first vibration separation strategy is analyzed based on the separation damage evaluation cluster to identify factors that may lead to unacceptable damage to logistics components. Based on the analysis results, the first vibration separation strategy is optimized and adjusted, such as reducing vibration amplitude, increasing buffer time, or changing vibration frequency, etc. Finally, a second vibration optimization analysis result is generated, which can reduce the damage of logistics components during the actual vibration separation process.

[0048] Step S500: Perform enhanced analysis on the stacked component adhesion control of the first vibration separation strategy to obtain the third analysis result of vibration optimization.

[0049] Step S500 further includes step S510, obtaining stacked component adhesion feature data and stacked component environmental feature data of the stacked material; step S520, based on the stacked component environmental feature data, performing separation influence analysis on the stacked material according to the stacked component adhesion feature data, and obtaining adhesion separation influence analysis results; step S530, performing weakening analysis on the vibration separation first strategy according to the adhesion separation influence analysis results, and obtaining adhesion influence control weakening features; step S540, performing control enhancement analysis on the vibration separation first strategy according to the adhesion influence control weakening features, and generating the vibration optimization third analysis result.

[0050] Preferably, data is collected from the stacked logistics components to obtain data on the adhesion characteristics and environmental characteristics of the stacked components. The adhesion characteristics refer to various information related to the adhesion between the logistics components, such as the location, area, and strength of the adhesion, to understand the specific adhesion status. The environmental characteristics refer to information about the environment in which the logistics components are located, such as ambient temperature, humidity, and air pressure, which may affect the adhesion status and subsequent separation process. By comprehensively considering both the environmental and adhesion characteristics, the separation impact analysis of the stacked logistics components is performed. For example, higher humidity may cause logistics components made of certain materials to adhere more tightly, and specific adhesion locations and strengths also affect the ease of separation. This analysis yields a comprehensive assessment result regarding the impact of adhesion on separation, i.e., the adhesion-separation impact analysis result, indicating what difficulties the separation process may encounter under the current environmental and adhesion conditions, and which factors have a significant impact on separation.

[0051] Preferably, the first vibration separation strategy is weakened based on the analysis results of adhesion separation effects. This includes analyzing the parts of the strategy that may be ineffective due to adhesion, i.e., identifying the strategy features that cannot effectively achieve separation or cause problems when faced with adhesion of materials and the current environmental conditions. For example, if the vibration frequency in the original strategy cannot effectively break the adhesion due to high adhesion strength, this vibration frequency may be a weakening feature in controlling adhesion effects. Control enhancement analysis is then performed on the weakening feature in controlling adhesion effects, i.e., improving and optimizing the first vibration separation strategy. For example, if the vibration frequency is a weakening feature, the adjustment range of the vibration frequency is considered, or a mechanism is designed to automatically adjust the vibration frequency according to the adhesion strength to enhance the strategy's control over adhesion. Finally, a third vibration optimization analysis result is generated, which can better address the adhesion problem of stacked materials and improve the separation effect.

[0052] Step S600: Based on the first analysis result of vibration optimization, the second analysis result of vibration optimization, and the third analysis result of vibration optimization, the first vibration separation strategy is globally optimized to obtain the second vibration separation strategy, and the stacked material is separated and tracked for control by the vibration separation device.

[0053] Step S600 further includes step S610, performing overlap detection on the first, second, and third vibration optimization analysis results to obtain a vibration optimization overlap detection result; step S620, performing conflict detection on the first, second, and third vibration optimization analysis results to obtain a vibration optimization conflict detection result; step S630, globally fusing the first, second, and third vibration optimization analysis results based on the vibration optimization overlap detection result and the vibration optimization conflict detection result to obtain a vibration optimization fourth analysis result; and step S640, optimizing the first vibration separation strategy based on the fourth vibration optimization analysis result to generate the second vibration separation strategy.

[0054] Preferably, overlap detection is performed on the first, second, and third analysis results of vibration optimization, that is, analyzing whether there are identical or similar parts in the three analysis results, so as to clarify the commonalities between the analysis results from different angles and record the overlapping content; conflict detection is performed on the first, second, and third analysis results of vibration optimization, that is, checking whether there are contradictory or conflicting parts among the three analysis results. For example, the first analysis result of vibration optimization may require increasing the vibration amplitude to improve the separation rate, while the second analysis result of vibration optimization, considering the damage problem of the material, may require reducing the vibration amplitude to avoid damage. There is a conflict in the direction of vibration amplitude adjustment. Then, the cause of the conflict and its impact on the vibration separation strategy are obtained, and the content of the conflict, the parameters involved, and the possible degree of impact are recorded in detail.

[0055] Preferably, based on the overlap detection results and conflict detection results, the first, second, and third vibration optimization analysis results are globally fused. Specifically, based on the overlap detection results, optimization measures that can be uniformly adopted are determined, and based on the conflict detection results, the rationality and importance of each analysis result are analyzed. Then, the three analysis results are integrated into a more comprehensive and reasonable fourth vibration optimization analysis result, which includes optimization suggestions and adjustment directions for the first vibration separation strategy, combining the advantages of each analysis result and avoiding conflicts and contradictions. Finally, the first vibration separation strategy is optimized based on the fourth vibration optimization analysis result, such as changing the vibration direction, adjusting the vibration frequency and amplitude, thereby generating a new vibration separation strategy, namely the second vibration separation strategy, which can better achieve automatic separation of stacked material components, improving the efficiency, accuracy, and safety of separation.

[0056] Preferably, during the separation of stacked material components using a vibration separation device, the separation process is monitored and optimized in real time by monitoring equipment to ensure that the separation effect achieves the expected goal. Specifically, sensors are used to acquire the status information of the stacked material components in real time, such as the position, orientation, vibration amplitude, and degree of separation of the material components. The operating status of the vibration separation device itself is monitored, including the working parameters of the vibration source (such as vibration frequency and vibration direction) and the working status of each component of the device (whether there is abnormal wear, loosening, etc.). The monitored material component status information and device operating status information are then fed back to the control system, and corresponding control measures are taken to adjust the operating parameters of the vibration separation device to optimize the material component separation process. For example, when the material components are severely adhered and difficult to separate, the vibration frequency or amplitude is automatically increased to enhance the vibration effect and promote the separation of the material components. If the material components are separated excessively, which may lead to damage, the vibration intensity in that area is reduced. At the same time, the running time and vibration direction of the vibration separation device are adjusted to achieve the best separation effect, thereby improving the separation efficiency and quality of the stacked material components and reducing damage to the material components.

[0057] In the above text, refer to Figure 1 A smart vibration control method for automatic separation of stacked components according to an embodiment of the present invention is described in detail. Next, reference will be made to... Figure 2 An intelligent vibration control system for automatic separation of stacked components according to an embodiment of the present invention is described.

[0058] The intelligent vibration control system for automatic separation of stacked parts according to embodiments of the present invention addresses the technical problems in the prior art, such as difficulty in adapting to the characteristics of complex logistics components, susceptibility to erroneous separation, and inability to effectively handle the adhesion of stacked parts, resulting in poor separation efficiency and accuracy. It achieves the technical effect of improving the separation efficiency and accuracy of stacked logistics components. Figure 2As shown, the intelligent vibration control system for automatic separation of stacked components includes: a multi-parameter control decision module 10, a multilateral joint optimization module 20, a first analytical result acquisition module 30, a second analytical result acquisition module 40, a third analytical result acquisition module 50, and a separation tracking control module 60.

[0059] The multi-parameter control decision module 10 is used to make multi-parameter control decisions on the vibration separation device based on the stacked state characteristic data and basic characteristic data of the stacked material, and obtain a vibration separation decision set; the multilateral joint optimization module 20 is used to perform multilateral joint optimization on the vibration separation decision set based on the separation expectation bilateral elements, and obtain a first vibration separation strategy; the first analysis result acquisition module 30 is used to perform erroneous separation suppression optimization analysis on the first vibration separation strategy, and obtain a first vibration optimization analysis result; the second analysis result acquisition module 40 is used to perform flexible buffer compensation analysis on the first vibration separation strategy, and obtain a second vibration optimization analysis result; the third analysis result acquisition module 50 is used to perform stacked adhesion control enhancement analysis on the first vibration separation strategy, and obtain a third vibration optimization analysis result; the separation tracking control module 60 is used to perform global optimization on the first vibration separation strategy based on the first vibration optimization analysis result, the second vibration optimization analysis result, and the third vibration optimization analysis result, and obtain a second vibration separation strategy, and combine the vibration separation device to perform separation tracking control on the stacked material.

[0060] The specific configuration of the first analysis result acquisition module 30 will be described in detail below. The first analysis result acquisition module 30 further includes: constructing a misseparation prediction model based on the stacked component misseparation event record set; predicting misseparation of the stacked components based on the stacked component state feature data, the stacked component basic feature data, and the vibration separation first strategy, and obtaining predicted misseparation events; performing association identification on the vibration separation first strategy based on the predicted misseparation events to obtain misseparation association control data; performing association identification on the stacked component state feature data and the stacked component basic feature data based on the predicted misseparation events to obtain misseparation association stacked component features; and performing optimized feature analysis on the misseparation association control data based on the predicted misseparation events and the misseparation association stacked component features to generate the vibration optimization first analysis result.

[0061] The specific configuration of the second analysis result acquisition module 40 will be described in detail below. The second analysis result acquisition module 40 further includes: performing simulated vibration separation on the stacked material components according to the first vibration separation strategy to obtain a vibration separation simulation dataset; performing damage evaluation on the stacked material components according to the vibration separation simulation dataset to obtain separation damage evaluation results for each material component; filtering the separation damage evaluation results for each material component to obtain separation damage evaluation clusters that do not meet the separation damage evaluation constraints; using the separation damage evaluation constraints as a buffer compensation target, performing buffer compensation feature analysis on the first vibration separation strategy according to the separation damage evaluation clusters to generate the second vibration optimization analysis result.

[0062] The specific configuration of the third analysis result acquisition module 50 will be described in detail below. The third analysis result acquisition module 50 further includes: acquiring stacked component adhesion characteristic data and stacked component environmental characteristic data of the stacked material; based on the stacked component environmental characteristic data, performing separation influence analysis on the stacked material according to the stacked component adhesion characteristic data to obtain adhesion separation influence analysis results; performing weakening analysis on the vibration separation first strategy according to the adhesion separation influence analysis results to obtain adhesion influence control weakening features; and performing control enhancement analysis on the vibration separation first strategy according to the adhesion influence control weakening features to generate the vibration optimization third analysis result.

[0063] The specific configuration of the separation tracking control module 60 will be described in detail below. The separation tracking control module 60 further includes: performing overlap detection on the first, second, and third vibration optimization analysis results to obtain a vibration optimization overlap detection result; performing conflict detection on the first, second, and third vibration optimization analysis results to obtain a vibration optimization conflict detection result; globally fusing the first, second, and third vibration optimization analysis results based on the vibration optimization overlap detection result and the vibration optimization conflict detection result to obtain a vibration optimization fourth analysis result; and optimizing the first vibration separation strategy based on the fourth vibration optimization analysis result to generate the second vibration separation strategy.

[0064] The specific configuration of the multi-parameter control decision module 10 will be described in detail below. The multi-parameter control decision module 10 further includes: obtaining vibration control multi-elements of the vibration separation device, the vibration control multi-elements including vibration frequency, vibration amplitude, vibration direction, and vibration duration; using the stacked component state feature data and the stacked component basic feature data as vibration control retrieval constraints, and combining the vibration control multi-elements to perform vibration control scheme retrieval, obtaining a retrieved vibration control scheme set; performing trigger feature parsing based on the retrieved vibration control scheme set to construct a multi-dimensional constraint domain for vibration control; and performing multi-parameter control decisions based on the multi-dimensional constraint domain for vibration control to generate the vibration separation decision set.

[0065] The specific configuration of the multilateral joint optimization module 20 will be described in detail below. The multilateral joint optimization module 20 further includes: setting bilateral constraints for separation expectation based on the bilateral elements of the separation expectation, wherein the bilateral elements of the separation expectation include separation rate and separation efficiency; performing bilateral constraint optimization on the vibration separation decision set based on the bilateral constraints of the separation expectation to obtain a vibration separation optimization set; assigning weights based on the bilateral elements of the separation expectation to construct a separation fitness function, and performing separation fitness maximization optimization on the vibration separation optimization set based on the separation fitness function to generate the first vibration separation strategy.

[0066] The specific configuration of the multilateral joint optimization module 20 will be described in detail below. The multilateral joint optimization module 20 further includes: extracting a first vibration separation decision based on the vibration separation decision set; performing vibration separation prediction on the stacked material components based on the first vibration separation decision to obtain a first decision separation prediction result, wherein the first decision separation prediction result includes a first prediction separation rate and a first prediction separation efficiency; if the first decision separation prediction result satisfies the separation expectation bilateral constraint, adding the first vibration separation decision to the vibration separation optimization set; if the first decision separation prediction result does not satisfy the separation expectation bilateral constraint, eliminating the first vibration separation decision.

[0067] The specific configuration of the multi-parameter control decision module 10 will be described in detail below. The multi-parameter control decision module 10 further includes: obtaining stacked component state feature elements and stacked component basic feature elements; the stacked component state feature elements include stacked shape structure, stacked center of gravity distribution, stacked contact features, and stacked density; the stacked component basic feature elements include single-component mass, single-component size, single-component material, and single-component attributes; performing feature acquisition on the stacked material based on the stacked component state feature elements to obtain the stacked component state feature data; and performing feature acquisition on the stacked material based on the stacked component basic feature elements to obtain the stacked component basic feature data.

[0068] The intelligent vibration control system for automatic separation of stacked components provided in the embodiments of the present invention can execute the intelligent vibration control method for automatic separation of stacked components provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0069] Although this application makes various references to certain modules in the system according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0070] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for intelligent vibration control for automatic separation of stacks, characterized by, The method comprises: According to the stack state feature data and the stack basic feature data of the stacked logistics pieces, a multi-parameter control decision is made for the vibration separation device to obtain a vibration separation decision set; According to the separated expected double-sided elements, a multi-edge joint optimization is performed on the vibration separation decision set to obtain a vibration separation first strategy; An error separation suppression optimization analysis is performed on the vibration separation first strategy to obtain a vibration optimization first analysis result; A flexible buffer compensation analysis is performed on the vibration separation first strategy to obtain a vibration optimization second analysis result; A stack adhesion control enhancement analysis is performed on the vibration separation first strategy to obtain a vibration optimization third analysis result; According to the vibration optimization first analysis result, the vibration optimization second analysis result, and the vibration optimization third analysis result, a global tuning is performed on the vibration separation first strategy to obtain a vibration separation second strategy, and the vibration separation device is combined to perform separation tracking control on the stacked logistics pieces.

2. The intelligent vibration control method for automatic separation of a stack as claimed in claim 1, wherein, The error separation suppression optimization analysis on the vibration separation first strategy to obtain the vibration optimization first analysis result comprises: According to the stack error separation event record set, an error separation prediction model is constructed; Based on the stack state feature data, the stack basic feature data, and the vibration separation first strategy, an error separation prediction is performed on the stacked logistics pieces according to the error separation prediction model to obtain a predicted error separation event; According to the predicted error separation event, an associated identification is performed on the vibration separation first strategy to obtain error separation associated control data; According to the predicted error separation event, an associated identification is performed on the stack state feature data and the stack basic feature data to obtain error separation associated stack features; Based on the predicted error separation event and the error separation associated stack features, an optimization feature analysis is performed on the error separation associated control data to generate the vibration optimization first analysis result.

3. The intelligent vibration control method for automatic separation of a stack as claimed in claim 1, wherein, The flexible buffer compensation analysis on the vibration separation first strategy to obtain the vibration optimization second analysis result comprises: According to the vibration separation first strategy, a simulation vibration separation is performed on the stacked logistics pieces to obtain a vibration separation simulation data set; According to the vibration separation simulation data set, a damage evaluation is performed on the stacked logistics pieces to obtain a separation damage evaluation result of each logistics piece; The separation damage evaluation results of each logistics piece are screened to obtain a separation damage evaluation cluster that does not meet the separation damage evaluation constraint; Taking the separation damage evaluation constraint as the buffer compensation target, a buffer compensation feature analysis is performed on the vibration separation first strategy according to the separation damage evaluation cluster to generate the vibration optimization second analysis result.

4. The intelligent vibration control method for automatic separation of a stack of claim 1, wherein, The stack adhesion control enhancement analysis on the vibration separation first strategy to obtain the vibration optimization third analysis result comprises: Obtaining stack adhesion feature data and stack environment feature data of the stacked logistics pieces; Based on the stack environment feature data, a separation influence analysis is performed on the stacked logistics pieces according to the stack adhesion feature data to obtain an adhesion separation influence analysis result; According to the adhesion separation influence analysis result, a weakening analysis is performed on the vibration separation first strategy to obtain an adhesion influence control weakening feature; According to the adhesion influence control weakening feature, control enhancement analysis is performed on the vibration separation first strategy to generate a vibration optimization third analysis result.

5. The intelligent vibration control method for automatic separation of a stack of claim 1, wherein, According to the vibration optimization first analysis result, the vibration optimization second analysis result, and the vibration optimization third analysis result, global optimization is performed on the vibration separation first strategy to obtain a vibration separation second strategy, including: Overlapping detection is performed on the vibration optimization first analysis result, the vibration optimization second analysis result, and the vibration optimization third analysis result to obtain a vibration optimization overlapping detection result; Conflict detection is performed on the vibration optimization first analysis result, the vibration optimization second analysis result, and the vibration optimization third analysis result to obtain a vibration optimization conflict detection result; According to the vibration optimization overlapping detection result and the vibration optimization conflict detection result, global fusion is performed on the vibration optimization first analysis result, the vibration optimization second analysis result, and the vibration optimization third analysis result to obtain a vibration optimization fourth analysis result; According to the vibration optimization fourth analysis result, the vibration separation first strategy is optimized to generate the vibration separation second strategy.

6. The intelligent vibration control method for automatic separation of a stack of claim 1, wherein, According to the stack flow piece stack state feature data and the stack base feature data, multi-parameter control decision is performed on the vibration separation device to obtain a vibration separation decision set, including: A vibration control multi-element of the vibration separation device is obtained, including a vibration frequency, a vibration amplitude, a vibration direction, and a vibration duration; With the stack state feature data and the stack base feature data as vibration control retrieval constraints, vibration control scheme retrieval is performed in combination with the vibration control multi-element to obtain a retrieval vibration control scheme set; Trigger feature analysis is performed according to the retrieval vibration control scheme set to construct a vibration control multi-element constraint domain; Multi-parameter control decision is performed according to the vibration control multi-element constraint domain to generate the vibration separation decision set.

7. The intelligent vibration control method for automatic separation of a stack of claim 1, wherein, According to the separation expected double-sided element, multi-edge joint optimization is performed on the vibration separation decision set to obtain a vibration separation first strategy, including: According to the separation expected double-sided element, a separation expected double-sided constraint is set, including a separation rate and a separation efficiency; According to the separation expected double-sided constraint, double-sided constraint optimization is performed on the vibration separation decision set to obtain a vibration separation optimization set; According to the separation expected double-sided element, a separation fitness function is constructed, and separation fitness maximization optimization is performed on the vibration separation optimization set according to the separation fitness function to generate the vibration separation first strategy.

8. The intelligent vibration control method for automatic separation of a stack of claim 7, wherein, According to the separation expected double-sided constraint, double-sided constraint optimization is performed on the vibration separation decision set to obtain a vibration separation optimization set, including: According to the vibration separation decision set, a vibration separation first decision is extracted; According to the vibration separation first decision, vibration separation prediction is performed on the stacked flow piece to obtain a first decision separation prediction result, including a first predicted separation rate and a first predicted separation efficiency; if the first decision separation prediction result satisfies the separation expectation double-sided constraint, adding the vibration separation first decision to the vibration separation optimization set; if the first decision separation prediction result does not satisfy the separation expectation double-sided constraint, eliminating the vibration separation first decision.

9. The intelligent vibration control method for automatic separation of a stack of claim 1, wherein, The method comprises: obtaining stack state characteristic elements and stack basic characteristic elements, the stack state characteristic elements comprising stack shape structure, stack barycenter distribution, stack contact characteristic and stack compactness, and the stack basic characteristic elements comprising single piece mass, single piece size, single piece material and single piece attribute; characteristic collection is carried out on the stacked logistics piece according to the stack state characteristic elements, and the stack state characteristic data is obtained; characteristic collection is carried out on the stacked logistics piece according to the stack basic characteristic elements, and the stack basic characteristic data is obtained.

10. An intelligent vibration control system for automatic separation of stacks, characterized by, The system is used to implement the intelligent vibration control method for stack automatic separation according to any one of claims 1 to 9, and the system comprises: a multi-parameter control decision module for making multi-parameter control decisions on the vibration separation device according to the stack state characteristic data and the stack basic characteristic data of the stacked logistics piece, and obtaining a vibration separation decision set; a multi-edge joint optimization module for making multi-edge joint optimization on the vibration separation decision set according to the separation expectation double-sided elements, and obtaining a vibration separation first strategy; a first analysis result obtaining module for making error separation suppression optimization analysis on the vibration separation first strategy, and obtaining a vibration optimization first analysis result; a second analysis result obtaining module for making flexible buffer compensation analysis on the vibration separation first strategy, and obtaining a vibration optimization second analysis result; a third analysis result obtaining module for making stack adhesion control enhancement analysis on the vibration separation first strategy, and obtaining a vibration optimization third analysis result; a separation tracking control module for making global optimization on the vibration separation first strategy according to the vibration optimization first analysis result, the vibration optimization second analysis result and the vibration optimization third analysis result, and obtaining a vibration separation second strategy, and combining the vibration separation device to perform separation tracking control on the stacked logistics piece.

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