A wild edible mushroom frozen slice processing production line cooperative control method and system

Abstract

The application discloses a kind of wild edible mushroom frozen section processing production line collaborative control method and system, it is related to food processing automation control technical field, comprising: according to the material conveying relationship between each processing equipment in production line constructs processing flow network, establishes processing node load relationship, determines the load distribution of processing node, and establishes processing flow load field;According to the load imbalance area of processing flow load field, the processing flow of processing flow network is reconstructed, and the collaborative pheromone field is established according to the reconstructed processing flow network, and the collaborative priority of each processing node is determined based on the collaborative pheromone field;According to the collaborative priority of each processing node and the collaborative pheromone field, processing flow collaborative potential field is generated, and the processing flow in processing flow network is driven to migrate according to processing flow collaborative potential field, and dynamic equilibrium state is formed Processing flow;The application is reconstructed dynamically by processing flow and guided by collaborative potential field, and the problem of production line load imbalance and insufficient collaborative control ability is solved.

Description

Technical Field

[0001] This invention relates to the field of automated control technology in food processing, and more specifically, to a collaborative control method and system for a frozen sliced ​​wild edible fungus processing production line. Background Technology

[0002] As the food processing industry moves towards automation and intelligence, frozen slicing production lines for wild edible fungi are increasingly adopting continuous processing equipment to improve processing efficiency and product quality. Existing frozen slicing processes for wild edible fungi typically include multiple processing steps such as cleaning, pretreatment, freezing, slicing, conveying, and packaging. These processing devices form a continuous processing flow through material conveying relationships. However, due to the significant morphological variations, substantial changes in moisture content, and susceptibility to environmental influences in wild edible fungi raw materials, issues such as variations in material conveying speed, fluctuations in equipment load, and mismatches in processing capacity at local processing nodes can easily arise during actual processing.

[0003] The above-disclosed embodiments have at least the following technical problems:

[0004] Traditional frozen sliced ​​wild edible fungi processing production lines often use fixed processing procedures, making it difficult to identify load imbalances and their spread in a timely manner. They are unable to dynamically adjust the processing procedures and tasks according to load changes, which can easily lead to material backlog, uneven equipment utilization, and reduced production line efficiency.

[0005] To address the above problems, this invention proposes a solution. Summary of the Invention

[0006] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a collaborative control method and system for a wild edible fungus frozen slice processing production line. By dynamically reconstructing the processing flow and guiding the collaborative potential field, the method solves the problems of production line load imbalance and insufficient collaborative control capability.

[0007] To achieve the above objectives, the present invention provides the following embodiments:

[0008] A collaborative control method for a wild edible mushroom frozen slice processing production line includes: constructing a processing flow network based on the material conveying relationship between each processing device in the production line; establishing the load relationship of each processing node in the processing flow network based on the operating status of each processing node in the processing flow network; determining the load distribution of the processing nodes; and establishing a processing flow load field; identifying load imbalance areas based on the processing flow load field; reconstructing the processing flow network based on the load imbalance areas; establishing a collaborative pheromone field based on the reconstructed processing flow network; determining the collaborative priority of each processing node based on the collaborative pheromone field; generating a processing flow collaborative potential field based on the collaborative priority of each processing node and the collaborative pheromone field; driving the migration of processing flows in the processing flow network based on the processing flow collaborative potential field to form a dynamic equilibrium state of the processing flow; and controlling the operation of the wild edible mushroom frozen slice processing production line based on the dynamic equilibrium state of the processing flow.

[0009] In a preferred embodiment, the process of constructing a processing flow network based on the material conveying relationship between processing equipment in the production line, establishing the load relationship of processing nodes based on the operating status of each processing node in the processing flow network, determining the load distribution of processing nodes, and establishing a processing flow load field are specifically as follows: The connection structure between processing nodes is established based on the material conveying path between processing equipment in the production line; the processing flow influence domain is divided based on the processing influence range of each processing node, and a processing flow network is constructed; the competitive response state of each processing node in adjacent processing flow influence domains is analyzed based on the operating status of each processing node, competitive response characteristics are extracted, and competitive response units are divided; the activation direction of the competitive response is identified based on each competitive response unit, and a processing flow competitive response map is constructed; the competitive advantage region of the processing flow is identified based on the processing flow competitive response map, and load coordination units are divided based on the competitive advantage region of the processing flow; the coordination evolution state between each load coordination unit is identified based on the distribution characteristics of each load coordination unit in the processing flow network, and a load coordination state is formed; the load influence domain of each load coordination unit is determined based on the load coordination state, and a processing flow load field is established.

[0010] In a preferred embodiment, the step of establishing a connection structure between processing nodes based on the material conveying path between processing equipment in the production line, dividing the processing flow influence domain based on the processing influence range of each processing node, and constructing a processing flow network is as follows: Extracting the material input and output ends of each processing equipment based on the material conveying path between processing equipment in the production line, and establishing a connection structure between processing nodes; analyzing the flow direction of materials between processing nodes based on the connection structure, extracting the upstream and downstream processing nodes of each processing node, and forming a processing flow transmission chain based on the flow association between processing nodes; analyzing the processing influence range of each processing node on adjacent processing nodes based on the processing flow transmission chain, identifying the direct influence area and extended influence area of ​​each processing node, and dividing the processing flow influence domain. The process involves: identifying the common processing nodes between adjacent processing flow influence domains and defining them as influence connection nodes; analyzing the continuous flow direction of materials between adjacent processing flow influence domains based on these connection nodes, identifying the influence transmission path extending from one processing flow influence domain to another; extracting processing nodes continuously involved in the transmission of processing influence based on these transmission paths, and forming influence transmission regions based on these nodes; connecting the corresponding processing flow influence domains to form processing flow influence channels; analyzing the transmission characteristics between processing flow influence domains based on the processing flow influence domains and channels, and establishing a processing flow influence topology; identifying the influence levels between processing flow influence domains based on the processing flow influence topology, and constructing a processing flow network based on each influence level.

[0011] In a preferred embodiment, the step of identifying the competitive advantage region of the processing flow based on the competitive response map and dividing the load coordination unit according to the competitive advantage region is as follows: Extract each competitive response activation chain from the competitive response map and identify the convergence position between each competitive response activation chain to form a competitive response convergence center; using each competitive response convergence center as the starting node, trace the continuously activated competitive response units level by level along the competitive response activation chain to form a competitive response propagation chain; analyze the continuous propagation direction of the competitive response in the processing flow network based on the competitive response propagation chain, identify the competitive response expansion front, and form a competitive response expansion band; analyze the sustained range of the competitive response based on the competitive response expansion band to identify the competitive advantage coverage area; identify the continuous coordination state of the competitive response between processing nodes based on the competitive advantage coverage area to form a competitive coordination cluster; analyze the synchronous evolution state of the competitive response between processing nodes based on the competitive coordination cluster to identify the competitive response synchronous evolution chain; divide the set of processing nodes with consistent competitive responses based on the competitive response synchronous evolution chain to form a load coordination unit.

[0012] In a preferred embodiment, the steps of identifying load imbalance regions based on the processing flow load field, reconstructing the processing flow network based on the load imbalance regions, establishing a cooperative pheromone field based on the reconstructed processing flow network, and determining the cooperative priority of each processing node based on the cooperative pheromone field are as follows: Identifying convergence centers where loads continuously converge and diffusion centers where loads continuously diffuse based on the processing flow load field, and determining load imbalance regions based on the load mismatch areas formed between the convergence centers and diffusion centers; identifying processing flow transfer units adjacent to the load imbalance regions based on the load imbalance regions, and sequentially associating them according to the connection order between each processing flow transfer unit to form a load imbalance propagation chain; identifying alternative transfer segments based on the load imbalance propagation chain, and assigning each alternative transfer segment to the appropriate alternative transfer segment. The segments are connected sequentially to form a processing flow continuation path; the processing flow connection mode between processing nodes in the processing flow network is adjusted according to the processing flow continuation path to form a reconstructed processing flow network; the intersection position between each processing flow continuation path is identified according to the reconstructed processing flow network, and processing flow collaborative response units are divided according to each intersection position; the extended segment of continuous collaborative transmission of processing flow is identified according to the processing flow collaborative response unit, and a collaborative extension chain is formed according to the continuation order between each extended segment; the corresponding collaborative coverage area is determined according to each collaborative extension chain, and a collaborative pheromone field is established according to the spatial distribution of the collaborative coverage area; the collaborative core position of each processing node is identified according to the collaborative pheromone field, and the collaborative priority is determined according to the continuation level between each processing node and the collaborative core position.

[0013] In a preferred embodiment, the step of identifying the convergence center of continuous load convergence and the diffusion center of continuous load diffusion based on the processing flow load field, and determining the load imbalance region based on the load mismatch region formed between the convergence center and the diffusion center, specifically includes: extracting the continuous load distribution contour between each load influence domain based on the processing flow load field, and identifying the extension direction of the continuous load distribution based on each continuous load distribution contour; identifying the load convergence center and the load diffusion center based on the extension direction of each continuous load distribution; determining the continuous load convergence direction based on the load convergence center, determining the continuous load diffusion direction based on the load diffusion center, and identifying the load balance boundary line formed between the continuous load convergence direction and the continuous load diffusion direction; extracting the continuously distributed load influence domains on both sides of the load balance boundary line to form a load evolution zone; identifying the position where the continuous load evolution changes from synchronous to asynchronous based on the load evolution zone on both sides of the boundary line to form a load decoupling zone; dividing the continuous load mismatch region based on the extension range of the load decoupling zone to the adjacent load influence domain, and determining the continuous load mismatch region as the load mismatch region; and continuously merging the load mismatch regions based on the connectivity distribution in the processing flow network to form the load imbalance region.

[0014] In a preferred embodiment, the step of identifying the collaborative core position of each processing node based on the collaborative pheromone field and determining the collaborative priority based on the continuity level between each processing node and the collaborative core position is as follows: Extracting the region where collaborative pheromones continuously converge based on the collaborative pheromone field and identifying the collaborative core position; tracing the processing nodes layer by layer outward along the continuous connection direction in the collaborative pheromone field, with the collaborative core position as the center, and identifying processing node segments; identifying the continuous connection positions between the processing nodes and the collaborative core position based on the processing node segments, and dividing the collaborative connection layers where the processing nodes are located according to the continuous connection positions; analyzing the proximity of the processing nodes to the collaborative core position based on the collaborative connection layers to determine the continuity level corresponding to each processing node; and determining the collaborative priority of each processing node based on the continuity level of the processing node and the continuous collaborative distribution state in the collaborative pheromone coverage area where the processing node is located.

[0015] In a preferred embodiment, the process of generating a processing flow collaborative potential field based on the collaborative priority of each processing node and the collaborative pheromone field, driving the migration of processing flows in the processing flow network based on the processing flow collaborative potential field to form a dynamic equilibrium state of the processing flow, and controlling the operation of the wild edible fungus frozen slice processing production line based on the dynamic equilibrium state of the processing flow, specifically includes: identifying processing nodes with continuously converging collaborative priorities based on the collaborative priorities of each processing node, and forming a collaborative guidance zone based on the continuously converging collaborative priorities of each processing node; extracting the continuous connection relationship between adjacent collaborative guidance zones based on the collaborative guidance zones, identifying the transmission direction of the processing flow continuously moving towards the collaborative guidance zone, and forming a collaborative potential line; analyzing the continuous expansion range of the collaborative effect in the collaborative pheromone field based on the collaborative potential line, identifying the continuous area jointly covered by each collaborative potential line, and establishing a processing flow collaborative potential field; and so on. The starting area of ​​the processing flow migration is identified based on the collaborative potential field of the processing flow. The processing flow is then continuously traced along the collaborative potential line from the starting area to identify the target segment of the continuous migration, thus forming a processing flow migration path. Based on the migration path, the material flow sequence and processing task allocation relationship between processing nodes in the processing flow network are adjusted to form a processing flow migration state. The location of continuously closed migration loops between processing flow migration paths is identified based on the processing flow migration state, and the convergence state of the processing flow migration within each closed migration loop is analyzed to form a dynamic equilibrium region. Based on the dynamic equilibrium region, the continuous collaborative flow state between adjacent dynamic equilibrium regions is analyzed to form a dynamic equilibrium state of the processing flow. Based on the dynamic equilibrium state of the processing flow, the processing sequence, material conveying sequence, and processing cycle time of each processing equipment are controlled to control the operation of the wild edible mushroom frozen slice processing production line.

[0016] In a preferred embodiment, the step of analyzing the continuous extension range of synergistic effects in the synergistic pheromone field based on synergistic potential lines, identifying the continuous region commonly covered by each synergistic potential line, and establishing a processing flow synergistic potential field specifically involves: identifying the location where two or more synergistic potential lines converge continuously based on the extension direction of the synergistic potential lines in the synergistic pheromone field, and determining this location as the synergistic convergence point; continuously tracing adjacent processing nodes along the synergistic potential lines based on the synergistic convergence point, identifying processing node segments where synergistic effects remain continuously concentrated, and determining each processing node segment as a synergistic potential ridge; analyzing the continuous connection relationship between synergistic potential ridges based on the synergistic potential ridges, identifying combinations of synergistic potential ridges that continuously maintain synergistic effects, and determining each... The combination of cooperative potential ridges is determined as a cooperative potential ridge cluster; the positions of continuous connection between cooperative potential ridges are identified based on the cooperative potential ridge cluster, and the continuously connected processing nodes are traced along each continuous connection position to form a cooperative potential ridge connection band; the continuous transmission direction of cooperative action between processing nodes is analyzed based on the cooperative potential ridge connection band, the connection channel is identified, and cooperative potential corridors are divided according to the connection channel; the coverage range of continuous expansion of cooperative action is identified based on the cooperative potential corridor, and a cooperative potential field skeleton is formed according to the continuous connection relationship between each cooperative potential corridor; the coverage range of processing nodes where cooperative action is continuously maintained is identified based on the cooperative potential field skeleton, and the cooperative potential field skeleton is continuously expanded in combination with the cooperative pheromone field to form a processing flow cooperative potential field.

[0017] A system for collaborative control of a wild edible mushroom frozen slice processing production line includes a load module, a reconfiguration module, and a control module, with connections between the modules. The load module constructs a processing flow network based on the material conveying relationships between processing equipment in the production line, establishes the load relationships of processing nodes based on the operating status of each processing node in the processing flow network, determines the load distribution of processing nodes, and establishes a processing flow load field. The reconfiguration module identifies load imbalance areas based on the processing flow load field, reconfigures the processing flow network based on these areas, establishes a collaborative pheromone field based on the reconfigured processing flow network, and determines the collaborative priority of each processing node based on the collaborative pheromone field. The control module generates a processing flow collaborative potential field based on the collaborative priority of each processing node and the collaborative pheromone field, drives the migration of processing flows in the processing flow network based on the collaborative potential field to form a dynamic equilibrium state of the processing flow, and controls the operation of the wild edible mushroom frozen slice processing production line based on the dynamic equilibrium state of the processing flow.

[0018] The technical effects and advantages of the collaborative control method and system for a frozen slicing production line of wild edible fungi of this invention are as follows:

[0019] 1. This invention constructs a processing flow competition response map to continuously analyze the competition response relationships, competitive advantage regions, and competitive coordination states among processing nodes, forming load coordination units. This allows the system to identify the overall coordination relationships among multiple processing nodes, rather than simply comparing the processing capabilities of individual devices. When abnormal changes occur in local processing nodes, the diffusion trend of load among processing nodes can be continuously tracked by combining the competition response propagation chain, competitive advantage coverage area, and competition response synchronous evolution chain. This timely identification of changes in load coordination relationships provides a reliable basis for subsequent processing flow reconstruction, thereby reducing the overall processing efficiency decline of the production line caused by local device abnormalities and improving the stability of production line operation.

[0020] 2. This invention establishes a collaborative pheromone field to continuously express the collaborative relationships between processing nodes in the processing flow network. Based on the core location, successive layers, and successive levels of collaboration, the collaborative priority of processing nodes is determined. This allows production line control to no longer rely on a fixed control sequence, but rather dynamically adjust the importance of each processing node according to the current collaborative state of the processing flow. This prioritizes key processing nodes in processing flow scheduling, further enhancing the overall collaborative performance of the processing flow. The collaborative pheromone field accurately reflects the continuous collaborative relationships between processing nodes, improving the real-time performance of collaborative control and ensuring a consistently reasonable distribution of the processing flow. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating a collaborative control method for a frozen sliced ​​wild edible fungus processing production line according to the present invention.

[0022] Figure 2 This is a schematic diagram of the system structure of a collaborative control method for a frozen sliced ​​processing production line of wild edible fungi according to the present invention. Detailed Implementation

[0023] The embodiments of the present invention 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 the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0024] Example 1, Figure 1 The present invention discloses a collaborative control method for a wild edible mushroom frozen slicing processing production line, comprising:

[0025] S1. Construct a processing flow network based on the material conveying relationship between each processing equipment in the production line. Establish the load relationship of each processing node based on the operating status of each processing node in the processing flow network. Determine the load distribution of the processing nodes and establish a processing flow load field.

[0026] In this embodiment, a processing flow network is constructed based on the material conveying relationship between each processing device in the production line. The load relationship of each processing node in the processing flow network is established based on the operating status of each processing node, the load distribution of the processing nodes is determined, and a processing flow load field is established, as follows:

[0027] Establish the connection structure between processing nodes based on the material conveying path between each processing equipment in the production line, divide the processing flow influence domain based on the processing influence range of each processing node, and construct the processing flow network based on each processing flow influence domain.

[0028] The competitive response status of a processing node in adjacent processing flow influence domains is analyzed based on its operating status. Competitive response characteristics of the processing nodes are extracted, and competitive response units are divided based on these characteristics. Specifically, based on the operating status of the processing node and the processing flow influence domain where the processing node is located, the processing flow influence domains adjacent to the current processing node are identified. Based on the processing flow flow direction between the current processing node and adjacent processing flow influence domains, the flow changes of the processing flow between adjacent processing flow influence domains are analyzed to form the competitive response status of the processing node. Based on the competitive response status, the direction of competitive response change and the continuity of competitive response change between adjacent processing flow influence domains are extracted to form competitive response characteristics. Processing nodes with consistent competitive response change directions and continuous competitive response changes are aggregated to form competitive response units.

[0029] The activation direction of the competitive response is identified based on the competitive response unit, and a processing flow competitive response map is constructed based on the activation direction of the competitive response unit. Specifically, based on the distribution position of the competitive response unit in the processing flow influence domain, target competitive response units adjacent to the current competitive response unit are extracted. Based on the changing trend of the competitive response characteristics between the current competitive response unit and the target competitive response unit, the expansion direction of the competitive response from the current competitive response unit to the target competitive response unit is identified, and this expansion direction is determined as the activation direction of the competitive response. The activation connection relationship between the competitive response units is established based on the activation direction of the competitive response unit. The processing flow competitive response map is constructed based on the competitive response unit and the activation connection relationship.

[0030] Identify the competitive advantage region of the processing flow based on the competitive response map, and divide the load coordination unit according to the competitive advantage region of the processing flow;

[0031] Based on the distribution characteristics of load coordination units in the processing flow network, the cooperative evolution state between load coordination units is identified, and a load coordination state is formed based on the cooperative evolution state. The cooperative evolution state is used to characterize the changes in the cooperative effect between adjacent load coordination units during the processing flow transmission process, such as maintenance, enhancement, weakening, or transfer. The load coordination state is used to characterize the overall cooperative distribution of the processing flow among multiple load coordination units and the spatial organization of the cooperative effect. Specifically, based on the distribution position of the load coordination units in the processing flow network, target load coordination units adjacent to the current load coordination unit are extracted. Based on the processing flow influence channel between the current load coordination unit and the target load coordination unit, the continuity direction of load coordination between adjacent load coordination units is identified, forming a cooperative continuity chain. Based on the cooperative continuity chain, the continuous migration state of load coordination in the processing flow network is analyzed, and the migration stage of load coordination from one load coordination unit to another is identified. Based on the migration stage, a cooperative evolution state is formed. Based on the cooperative evolution states with continuous migration relationships, a correlation is formed to form a load coordination state.

[0032] The load influence domain of the load coordination unit is determined based on the load coordination state, and the processing flow load field is established based on the spatial distribution of the load influence domain. Specifically, the coordination connection range between load coordination units is extracted based on the load coordination state, and the coordination coverage area of ​​the load coordination unit in the processing flow network is identified. Based on the coordination coverage area, the continuous transmission direction of the processing flow along the processing flow network is analyzed, and the coverage boundary that the load coordination effect can be continuously maintained is identified. Based on the coverage boundary, the load influence domain of the load coordination unit is determined. Based on the adjacent distribution of the load influence domain in the processing flow network, the continuous connection area between the load influence domains is identified. Based on the load influence domain and the continuous connection area, a processing flow load field covering the entire processing flow network is constructed.

[0033] In this embodiment, a connection structure between processing nodes is established based on the material conveying path between processing equipment in the production line. The processing flow influence domain is divided based on the processing influence range of the processing nodes, and a processing flow network is constructed based on the processing flow influence domain, as detailed below:

[0034] Based on the material conveying path between processing equipment in the production line, extract the material input end and material output end of the processing equipment, and establish the connection structure between processing nodes based on the conveying correspondence between the material input end and the material output end;

[0035] Based on the connection structure between processing nodes, the flow direction of materials between processing nodes is analyzed, the upstream and downstream processing nodes are extracted, and a processing flow transmission chain is formed based on the flow association between processing nodes.

[0036] Based on the processing flow transmission chain analysis, the processing influence range of the processing node on the adjacent processing node is analyzed, the direct influence area and extended influence area of ​​the processing node are identified, and the processing flow influence domain is divided according to the direct influence area and extended influence area.

[0037] Based on the influence domain of the processing flow, extract the processing nodes that are commonly associated between adjacent processing flow influence domains, and determine the commonly associated processing nodes as influence connection nodes;

[0038] Based on the analysis of the connection nodes, the continuous flow direction of materials between adjacent processing flow influence domains is analyzed, and the influence transmission path of processing influence extending from one processing flow influence domain to another is identified.

[0039] Extract the processing nodes that continuously participate in the transmission of processing effects based on the transmission path, and form the transmission area based on the processing nodes that continuously participate in the transmission of processing effects;

[0040] Based on the influence transmission area, the corresponding processing flow influence domain is connected to form a processing flow influence channel;

[0041] Based on the analysis of the transmission characteristics between the processing flow influence domains and the processing flow influence channels, a processing flow influence topology is established. Specifically, this involves: extracting the corresponding connected processing flow influence domains based on the processing flow influence channels to form influence connection units between processing flow influence domains; analyzing the continuous transmission direction of processing influence between processing flow influence domains based on the influence connection units to form a processing flow influence connection sequence; identifying processing flow influence domains that are continuously connected from beginning to end based on the processing flow influence connection sequence and forming a processing flow influence main chain; and associating the remaining processing flow influence connection sequences based on the processing flow influence main chain to form a processing flow influence topology.

[0042] Based on the topology of the processing flow influence, the influence hierarchy between the processing flow influence domains is identified, and a processing flow network is constructed based on the influence hierarchy. Specifically, the influence connection direction between the processing flow influence domains is extracted based on the processing flow influence topology, and a continuous influence chain is formed according to the influence connection direction. The arrangement position of the processing flow influence domain in the continuous influence chain is identified based on the continuous influence chain, and the influence hierarchy of the processing flow influence domain is determined based on the arrangement position. The processing flow transmission direction between adjacent influence levels is analyzed based on the influence hierarchy, and a hierarchical connection relationship is established. Based on the processing flow influence domain and the hierarchical connection relationship, the processing nodes in the processing flow network are hierarchically mapped to form a processing flow network with influence hierarchy.

[0043] The process involves analyzing the material flow direction between processing nodes based on the connection structure between them, extracting the upstream and downstream processing nodes, and forming a processing flow chain based on the flow association between the processing nodes, as detailed below:

[0044] The material input path and material output path of the processing node are obtained based on the connection structure between the processing nodes, and the material flow direction of the processing node is determined based on the material input path and material output path.

[0045] Extract adjacent processing nodes connected to the current processing node based on the material input path and material output path of the processing node;

[0046] Based on the material flow direction, analyze the continuous flow path between adjacent processing nodes and the current processing node, and identify the dominant flow path and branch flow paths in the continuous flow path. Specifically, based on the material flow direction, starting from the processing node, trace step by step along the continuously connected processing nodes to form multiple continuous flow paths. Based on the continuity of the continuous flow path between processing nodes, identify the continuous flow path that is connected end to end without any interruption nodes. The continuous flow path with the longest continuous distance is determined as the dominant flow path, and the continuous flow path that is connected to the dominant flow path but does not continuously extend to the terminal processing node is determined as the branch flow path.

[0047] The upstream and downstream processing nodes of the current processing node are determined based on the dominant flow path, and the processing nodes of the branch flow paths are determined as associated processing nodes. Specifically, the order of processing nodes in the dominant flow path is extracted based on the dominant flow path. Taking the current processing node as the base node, the processing node that is located before the current processing node and is directly connected to the current processing node in the order is determined as the upstream processing node of the current processing node. The processing node that is located after the current processing node and is directly connected to the current processing node in the order is determined as the downstream processing node of the current processing node.

[0048] The backbone path of the processing flow is determined based on the upstream and downstream processing nodes. Associated processing nodes connected to the backbone path are then sequentially incorporated into it to form extended processing flow paths. Specifically, the process involves: connecting processing nodes sequentially according to the connection order between upstream and downstream processing nodes to form the backbone path; analyzing the connection positions between associated processing nodes and the backbone path to determine the access points where they continuously connect to the backbone path along the material flow direction; and identifying the first node to continuously connect to the backbone path as the backbone connection node. Using the backbone connection node as the connection base, the process extends step-by-step along the continuous connection direction between associated processing nodes to form associated extension branches. Based on the connection positions between the associated extension branches and the backbone path, the associated extension branches are connected to the corresponding backbone paths. The resulting extended processing flow path is then formed based on the connected backbone path and associated extension branches.

[0049] The processing flow convergence node and processing flow extension node are identified based on the processing flow extension path, and the processing flow transfer unit is divided based on the processing flow convergence node and processing flow extension node. Specifically, the continuous convergence position and continuous divergence position of the processing flow are identified based on the processing flow extension path, and the processing flow convergence node and processing flow extension node are determined respectively. The processing flow conversion boundary is extracted based on the connection position between the processing flow convergence node and the processing flow extension node. The processing flow transfer unit is divided based on the continuous processing area enclosed by the processing flow conversion boundary. The processing flow conversion boundary is the boundary position of the processing node when the processing flow changes from a convergence state to an extension state or from an extension state to a convergence state during the transfer process.

[0050] The processing flow transfer units are continuously associated according to their connection sequence to form a processing flow transfer chain.

[0051] The process involves analyzing the impact range of a processing node on adjacent processing nodes based on the processing flow transmission chain, identifying the direct and extended impact areas of the processing nodes, and dividing the processing flow influence domain according to the direct and extended impact areas, as detailed below:

[0052] Extract the preceding and following processing nodes of the processing node based on the processing flow chain, and determine the starting node of the processing influence based on the connection order between the preceding and following processing nodes and the current processing node;

[0053] Centered on the starting node of the processing impact, the continuously connected processing nodes are traced level by level along the processing flow transmission chain. The first layer of processing nodes directly connected to the starting node of the processing impact is identified, and a directly affected area is formed based on the starting node of the processing impact and the first layer of processing nodes.

[0054] Starting from the first-level processing node, continue to trace the continuously connected processing nodes along the processing flow chain, identify the processing nodes of the second and subsequent levels, and form an extended influence area based on the processing nodes of the second and subsequent levels.

[0055] Based on the continuous coverage status of the directly affected area and the extended affected area, the continuous extension boundary of the processing influence is identified, and processing influence boundary units are formed based on the continuous extension boundary.

[0056] Based on the analysis of the continuous connection status between adjacent processing influence boundary units, the continuous coverage area of ​​processing influence is identified, and a processing influence fusion area is formed based on the continuous coverage area of ​​processing influence.

[0057] Based on the coverage of the processing influence fusion area, the processing influence fusion area to which the processing node belongs is determined, and the processing flow influence domain is formed according to the regional affiliation of the processing node.

[0058] In this embodiment, the competitive advantage region of the processing flow is identified based on the processing flow competitive response map, and the load coordination unit is divided according to the competitive advantage region of the processing flow, as detailed below:

[0059] The competitive response activation chain is extracted based on the competitive response map of the processing flow, and the convergence position between the competitive response activation chains is identified to form a competitive response convergence center. Specifically, the activation connection relationship between competitive response units is extracted based on the competitive response map of the processing flow. Taking the competitive response unit as the starting competitive response unit, the continuously connected competitive response units are traced along the activation connection relationship to form a competitive response extension path. The connection segment where the competitive response is continuously maintained is identified based on the competitive response extension path, and the connection segment where the competitive response is continuously maintained is determined as the competitive response activation chain.

[0060] Starting from the competition response convergence center, the continuously activated competition response units are traced level by level along the competition response activation chain to form a competition response propagation chain;

[0061] Based on the analysis of the competitive response propagation chain, the continuous propagation direction of the competitive response in the processing flow network is analyzed, the competitive response extension front is identified, and a competitive response extension band is formed based on the competitive response extension front. Specifically, the competitive response propagation wavefront is formed by analyzing the continuous propagation direction of the competitive response in the processing flow network based on the competitive response propagation chain. Based on the competitive response propagation wavefront, the processing nodes that synchronously expand the competitive response are identified to form the competitive response propagation band. The competitive response propagation band is then continuously spliced ​​together to form the competitive response extension band.

[0062] Based on the analysis of the competitive response extension band, the range of sustained competitive response is identified, and stable coverage areas where the competitive response is continuously maintained without interruption are identified, and these stable coverage areas are determined as competitive advantage coverage areas.

[0063] Based on the competitive advantage coverage area, the continuous collaborative state of competitive responses among processing nodes is identified to form a competitive collaborative cluster. Specifically, this involves: extracting processing nodes participating in the competitive response based on the competitive advantage coverage area and establishing competitive response associations between processing nodes; analyzing the continuous transmission state of competitive responses among processing nodes based on the competitive response associations; identifying processing node combinations that maintain continuous consistency in competitive responses; analyzing the consistent direction of competitive response changes based on the processing node combinations to form a competitive response synchronization group; and continuously associating the competitive response synchronization groups to form a competitive collaborative cluster.

[0064] Based on the analysis of competitive and cooperative clusters, the synchronous evolution state of the competitive response among processing nodes is analyzed, and the synchronous evolution chain of the competitive response is identified. Specifically, the processing nodes participating in competitive cooperation are extracted based on the competitive and cooperative clusters, and cooperative connections between processing nodes are established based on the connection relationships in the processing flow network. Based on the cooperative connections, the continuous transmission state of the competitive response among processing nodes is analyzed, and continuous processing nodes whose competitive responses change synchronously are identified and formed into synchronous evolution units. Based on the synchronous evolution units, the continuous expansion direction of the competitive response along the processing flow network is analyzed, and the forward and backward transmission order between synchronous evolution units is identified. Based on the forward and backward transmission order of synchronous evolution units, continuous association is performed to form a synchronous evolution chain of the competitive response.

[0065] Based on the synchronous evolution chain of the competition response, a set of processing nodes that maintain consistent competition response is divided to form a load coordination unit.

[0066] S2, Identify the load imbalance region based on the processing flow load field, reconstruct the processing flow network based on the load imbalance region, establish a cooperative pheromone field based on the reconstructed processing flow network, and determine the cooperative priority of each processing node based on the cooperative pheromone field.

[0067] In this embodiment, load imbalance regions are identified based on the processing flow load field. The processing flow network is then reconstructed based on these load imbalance regions. A cooperative pheromone field is established based on the reconstructed processing flow network, and the cooperative priority of each processing node is determined based on this field. Specifically, the following steps are taken:

[0068] Based on the processing flow load field, identify the convergence center where the load continuously converges and the diffusion center where the load continuously diffuses, and determine the load imbalance area based on the load mismatch area formed between the convergence center and the diffusion center.

[0069] Identify the processing flow transfer units adjacent to the load imbalance region based on the load imbalance region, and associate them sequentially according to the connection order between the processing flow transfer units to form a load imbalance propagation chain;

[0070] Based on the load imbalance propagation chain, alternative transmission segments connected to the beginning and end of the load imbalance propagation chain in the processing flow network are identified, and these alternative transmission segments are sequentially connected to form a processing flow continuation path. Specifically, the starting and ending nodes of the propagation chain are extracted according to the load imbalance propagation chain, and these nodes are used as processing flow continuation boundaries. Based on these boundaries, processing flow transmission units that are continuously connected to the processing flow boundaries but not included in the load imbalance propagation chain are identified, and these units are determined as candidate alternative transmission segments. Based on the analysis of the continuous connection positions between the candidate alternative transmission segments and adjacent candidate alternative transmission segments, alternative transmission segments that continuously connect the starting and ending nodes are identified. Based on the connection order between the alternative transmission segments, the alternative transmission segments are sequentially associated to form a processing flow continuation path.

[0071] Adjust the connection method between processing nodes in the processing flow network according to the processing flow continuation path to form a reconstructed processing flow network;

[0072] Based on the reconstructed processing flow network, the intersection points between each processing flow successive path are identified, and processing flow collaborative response units are divided according to the intersection points. Specifically, the continuous successive segments between each processing flow successive path are extracted based on the reconstructed processing flow network, and the locations where each processing flow successive path continuously converges are identified. Based on the continuous convergence locations, adjacent processing nodes are traced along the processing flow successive paths to identify the continuous successive range commonly covered by each processing flow successive path, forming a processing flow collaborative coverage area. Based on each processing flow collaborative coverage area, the continuity maintenance status of each processing flow successive path within the common coverage area is analyzed, and the locations where processing flow succession changes from single-path transmission to multi-path collaborative transmission are identified, forming a collaborative response interface. Based on each collaborative response interface, a set of processing nodes that continuously maintain the collaborative successive state is divided, and each set of processing nodes is determined as a processing flow collaborative response unit.

[0073] Based on the processing flow collaborative response unit, the extended segments of the continuous collaborative transmission of the processing flow are identified, and a collaborative extension chain is formed according to the succession sequence between each extended segment. Specifically, the processing nodes that are continuously connected to adjacent processing flow collaborative response units are identified based on the processing flow collaborative response unit, and the processing nodes that undertake the continuous succession of adjacent processing flow collaborative response units are determined as collaborative relay nodes. Based on each collaborative relay node, the continuous succession status between adjacent processing flow collaborative response units is analyzed, and the processing node segments that maintain continuous collaborative response are identified. Each processing node segment is determined as a collaborative relay segment. Based on each collaborative relay segment, the direction in which the collaborative relay extends continuously from one processing flow collaborative response unit to another is identified, forming a collaborative extension direction. Based on the collaborative extension direction, each collaborative relay segment is sequentially associated according to the succession sequence of each collaborative relay segment to form a collaborative extension chain.

[0074] The corresponding collaborative coverage area is determined based on each collaborative extension chain, and a collaborative pheromone field is established based on the spatial distribution of each collaborative coverage area.

[0075] The collaborative core position of each processing node is identified based on the collaborative pheromone field, and the collaborative priority is determined based on the successive hierarchy between each processing node and the collaborative core position.

[0076] In this embodiment, the convergence center where the load continuously converges and the diffusion center where the load continuously diffuses are identified based on the processing flow load field, and the load imbalance region is determined based on the load mismatch area formed between the convergence center and the diffusion center, as detailed below:

[0077] The continuous load distribution contours between each load influence domain are extracted based on the processing flow load field, and the extension direction of the continuous load distribution is identified based on each continuous load distribution contour.

[0078] Based on the direction of continuous distribution of each load, identify the location where multiple loads converge to the same area and determine this location as the load convergence center;

[0079] Based on the direction of continuous distribution of each load, identify the location where the load is continuously dispersed from the same area to multiple areas, and determine this location as the load diffusion center;

[0080] The continuous convergence direction of the load is determined based on the load convergence center, the continuous diffusion direction of the load is determined based on the load diffusion center, and the load balance boundary line formed between the continuous convergence direction and the continuous diffusion direction of the load is identified.

[0081] Based on each load balance boundary line, the load influence domains continuously distributed on both sides of the boundary line are extracted to form load evolution zones;

[0082] Identify the location where the continuous load evolution changes from synchronous to asynchronous based on the load evolution zones on both sides of the dividing line, thus forming a load decoupling zone;

[0083] The continuous load mismatch region is divided according to the extension range of each load decoupling band to the influence domain of adjacent loads, and each continuous load mismatch region is determined as the load mismatch area.

[0084] Based on the connectivity distribution of each load mismatch region in the processing flow network, they are continuously merged to form load imbalance regions.

[0085] The process of determining the continuous load convergence direction based on the load convergence center, determining the continuous load diffusion direction based on the load diffusion center, and identifying the load balance boundary line formed between the continuous load convergence direction and the continuous load diffusion direction is as follows:

[0086] Based on the extension direction of the continuous load distribution along each load convergence center, the influence domain of adjacent loads is traced to form a continuous load convergence trajectory.

[0087] Based on the extension direction of the continuous load distribution along each load diffusion center, the influence domain of adjacent loads is traced to form a continuous load diffusion trajectory;

[0088] Identify the location where the continuous convergence of loads terminates based on the continuous convergence trajectory of each load, and form the load convergence front.

[0089] Identify the location where the continuous diffusion of the load terminates based on the continuous diffusion trajectory of each load, and form the load diffusion front.

[0090] Based on the continuous connection points between the load convergence front and the load diffusion front, load balancing boundary units are formed;

[0091] The load balancing boundary lines are formed by continuously associating the load balancing boundary units according to their connection sequence.

[0092] In this embodiment, the connection method between processing nodes in the processing flow network is adjusted according to the processing flow continuation path to form a reconstructed processing flow network, as follows:

[0093] The system identifies processing nodes that continuously undertake processing flow succession based on the processing flow succession path, and divides the processing flow succession layer based on each processing node that continuously undertakes processing flow succession. Specifically, the system extracts the arrangement order of each processing node in the processing flow succession path based on each processing flow succession path, identifies the continuous succession segment between each processing node, analyzes the continuous undertaking status of adjacent processing nodes for processing flow succession based on each continuous succession segment, identifies the set of processing nodes that maintain consistent processing flow succession, identifies the location where processing flow succession changes based on each set of processing nodes, and determines this location as the processing flow succession switching point. The system divides the processing flow succession layer based on the processing nodes that are continuously covered between adjacent processing flow succession switching points.

[0094] Interlayer transition zones are formed based on the continuous connection positions between adjacent processing flow transition layers, and processing flow migration units are divided based on the interlayer transition zones;

[0095] The migration connection direction is identified based on the continuous connection position between the processing flow migration units, and a processing flow migration chain is formed according to the connection sequence of each processing flow migration unit;

[0096] Identify continuously covered processing node segments based on each processing flow continuation chain, and divide the processing flow continuation domain according to the continuous coverage range between each processing node segment;

[0097] The processing flow transmission order between processing nodes in the processing flow network is reorganized based on the processing flow migration domain, and a reconstructed processing flow network is formed.

[0098] The process flow transmission order between processing nodes in the processing flow network is reorganized according to the processing flow migration domain to form a reconstructed processing flow network, as detailed below:

[0099] Extract continuously covered processing nodes from the processing flow continuation domain, and form a processing node continuation sequence according to the continuation order between processing flow continuation domains;

[0100] Identify the connection positions between adjacent processing nodes based on the processing node connection sequence, and establish the processing node connection topology based on each connection position;

[0101] Based on the topology analysis of processing nodes, the continuous connection directions between each processing node are analyzed to form a group of processing node connection paths.

[0102] Remap the material transfer path between processing nodes according to the processing node succession path group, and disconnect the processing node corresponding to the load imbalance propagation chain.

[0103] A new connection structure is established between processing nodes based on the remapped material transfer path, forming a reconstructed processing flow network.

[0104] In this embodiment, the corresponding cooperative coverage area is determined according to each cooperative extension chain, and a cooperative pheromone field is established according to the spatial distribution of each cooperative coverage area, as follows:

[0105] Extract continuously connected cooperative relay segments from the cooperative extension chain, and sequentially associate each cooperative relay segment according to the cooperative extension direction to form a cooperative pheromone transmission sequence;

[0106] The location of the first aggregation of copherions is identified based on the copherion delivery sequence, and this location is determined as the copherion deposition node;

[0107] Starting from the copheromone deposition node, adjacent processing nodes are continuously traced to both sides along the copheromone transmission sequence to identify the range of continuous copheromone expansion and form a copheromone expansion band.

[0108] Based on the co-pheromone extension bands, identify the positions where consecutive co-pheromone extension bands overlap, and determine the positions where consecutive overlaps are co-pheromone fusion nodes;

[0109] Based on the continuous outward tracking of adjacent co-pheromone extension bands from the co-pheromone fusion node, the continuous area covered by multiple co-pheromone extension bands is identified, forming a co-pheromone fusion zone;

[0110] Based on the analysis of the cophery pheromone fusion region, the continuous extension range of cophery pheromone between processing nodes is analyzed to identify the stable boundary for cophery pheromone to maintain continuous coverage.

[0111] Identify the coverage area where the co-pheromone maintains a continuous distribution based on the stable boundary, and form a co-pheromone distribution domain based on each coverage area;

[0112] A co-pheromone association network is established based on the spatial adjacency and continuous connection relationships between co-pheromone coverage areas. Specifically, this involves: identifying the boundary positions where adjacent co-pheromone coverage areas contact each other, extracting the boundary segments of continuous co-pheromone distribution based on each boundary position, identifying the transition range from one co-pheromone coverage area to another based on the boundary segments of continuous co-pheromone distribution, defining the transition range as the co-pheromone transition zone, analyzing the continuous connection state between the two co-pheromone coverage areas based on the co-pheromone transition zone, identifying the combination of coverage areas that maintain continuous co-transmission, defining each combination of coverage areas as a co-coupling unit, identifying the continuous association direction between co-pheromone coverage areas based on each co-coupling unit, and connecting each co-coupling unit sequentially according to the continuous association direction to form a co-pheromone association network.

[0113] Construct a co-pheromone field based on the co-pheromone coverage area and the co-pheromone association network.

[0114] The construction of the co-pheromone field based on the co-pheromone coverage domain and the co-pheromone association network is as follows:

[0115] Based on the co-pheromone association network, the interrelated co-pheromone coverage regions are extracted, and a set of co-pheromone coverage regions is formed according to the association relationship.

[0116] The outer boundaries of each co-pheromone coverage area are extracted based on the co-pheromone coverage area set, and the boundary segments set relative to each other between adjacent co-pheromone coverage areas are identified according to the co-pheromone association network.

[0117] Based on the analysis of the relative boundary segments, the continuous correspondence between the boundary segments is analyzed, and the boundary pairing areas that continuously maintain the corresponding boundary segments are identified.

[0118] Based on the continuous tracking of adjacent processing nodes along the co-pheromone association network in the boundary pairing area, the coverage area of ​​continuous connection between the boundary pairing areas is identified, forming a co-pheromone fusion zone;

[0119] Based on the analysis of the fusion band of co-pheromones, the distribution range of continuous fusion between adjacent co-pheromones coverage areas is identified, and stable regions where co-pheromones maintain continuous distribution are identified, and these stable regions are determined as co-pheromones transition surfaces.

[0120] The continuous connection range between multiple co-pheromone coverage areas is identified based on the co-pheromone transition surface, and the continuously connected co-pheromone coverage areas are merged to form a co-pheromone action layer.

[0121] Identify the continuous range between adjacent copherolactone action layers based on the copherolactone action layer, and determine the copherolactone field connection region based on the continuous range.

[0122] Identify the termination position of the continuous distribution of copheric pheromones based on the connection region of the copheric pheromone field, and connect the termination positions of each continuous distribution to form the continuous propagation boundary of the copheric pheromone field;

[0123] A cooperative pheromone field covering the entire reconstructed processing flow network is established based on the cooperative pheromone action layer and each continuous propagation boundary.

[0124] In this embodiment, the collaborative core position of each processing node is identified based on the collaborative pheromone field, and the collaborative priority is determined based on the successive hierarchy between each processing node and the collaborative core position, as follows:

[0125] Based on the copheromone field, the region where copheromone continuously converges is extracted, and the location where copheromone continuously converges from the surrounding area to the center is identified. The location where copheromone continuously converges is determined as the copheromone core location.

[0126] Centered on the collaborative core location, the processing nodes are traced outward layer by layer along the continuous connection direction in the collaborative pheromone field to identify the processing node segments that are continuously passed between each processing node and the corresponding collaborative core location.

[0127] Identify the continuous connection positions between the processing node and the collaborative core position based on the processing node segment, and divide the collaborative connection layers where the processing node is located in order according to the continuous connection positions.

[0128] Based on the analysis of the proximity between processing nodes and the core location of the collaborative succession layer, the succession level corresponding to each processing node is determined.

[0129] Based on the succession level of the processing nodes and the continuous collaborative distribution status in the collaborative pheromone coverage area where the processing nodes are located, the collaborative priority of each processing node is determined.

[0130] S3 generates a processing flow collaborative potential field based on the collaborative priority and collaborative pheromone field of each processing node, drives the migration of processing flows in the processing flow network based on the processing flow collaborative potential field, forms a dynamic equilibrium state of processing flows, and controls the operation of the wild edible fungus frozen slice processing production line based on the dynamic equilibrium state of processing flows.

[0131] In this embodiment, a collaborative potential field for the processing flow is generated based on the collaborative priority and collaborative pheromone field of each processing node. The processing flow migration in the processing flow network is driven by the collaborative potential field to form a dynamic equilibrium state of the processing flow. The operation of the wild edible fungus frozen slice processing production line is controlled based on the dynamic equilibrium state of the processing flow, as follows:

[0132] Based on the collaborative priority of each processing node, processing nodes with continuously converging collaborative priorities are identified, and a collaborative guidance zone is formed based on these nodes. Specifically, based on the connection relationship between processing nodes in the processing flow network, the continuous change of collaborative priorities of adjacent processing nodes is analyzed along the processing flow transmission direction to identify processing nodes with continuously converging collaborative priorities. Based on the continuous distribution range of these nodes in the processing flow network, a collaborative guidance zone is defined.

[0133] Based on the extraction of the continuous connection relationship between adjacent collaborative guidance zones, the transmission direction of the continuous flow of processing towards the collaborative guidance zone is identified, and a collaborative potential line is formed.

[0134] Based on the analysis of the synergistic potential lines, the continuous extension range of the synergistic effect in the synergistic pheromone field is analyzed, the continuous region covered by each synergistic potential line is identified, and the synergistic potential field of the processing flow is established based on the continuous region.

[0135] The location where the processing flow continuously deviates from the cooperative potential line is identified based on the cooperative potential field of the processing flow, and this location is determined as the starting area of ​​the processing flow migration. The processing flow refers to the continuous processing path formed by the sequential transfer of materials between processing nodes according to the connection relationship between each processing node in the processing flow network.

[0136] Based on the continuous tracking of the processing flow continuation direction along the cooperative potential line from the starting area of ​​the processing flow migration, the target segment of the continuous migration of the processing flow is identified, and the processing flow migration path is formed based on the starting area and the target segment.

[0137] Adjust the material flow sequence and processing task allocation relationship between each processing node in the processing flow network according to the processing flow migration path to form the processing flow migration state;

[0138] Based on the processing flow migration status, identify the locations where continuous closed migration loops are formed between processing flow migration paths, and analyze the convergence status of processing flow migration within each closed migration loop to form a dynamic equilibrium region;

[0139] Based on the dynamic equilibrium zone analysis, the continuous collaborative flow state between adjacent dynamic equilibrium zones is analyzed to form a dynamic equilibrium state of the processing flow. Specifically, this involves: identifying the processing flow exchange segments between adjacent dynamic equilibrium zones based on the connection relationship between each dynamic equilibrium zone, forming dynamic equilibrium connection units; analyzing the continuous flow direction of the processing flow between adjacent dynamic equilibrium zones based on the dynamic equilibrium connection units, identifying the collaborative flow segments where the processing flow maintains continuous circulation; identifying the set of processing nodes where the processing flow maintains continuous circulation based on the collaborative flow segments, forming dynamic equilibrium circulation units; analyzing the continuous connection relationship between adjacent dynamic equilibrium circulation units, identifying the coverage area where the processing flow maintains stable circulation, forming a dynamic equilibrium coverage area; and analyzing the continuous equilibrium maintenance state of the processing flow in the entire processing flow network based on the dynamic equilibrium coverage area, thus forming a dynamic equilibrium state of the processing flow.

[0140] The operation of the wild edible mushroom frozen slice processing production line is controlled by adjusting the processing sequence, material conveying sequence, and processing rhythm of each processing equipment based on the dynamic equilibrium state of the processing flow. Specifically, this involves: identifying the processing relationships between processing nodes that maintain continuous and balanced flow based on the dynamic equilibrium state of the processing flow, forming a processing coordination control unit based on these relationships; analyzing the continuous processing sequence between processing nodes based on the processing coordination control unit, identifying the processing execution order of processing nodes, and forming a processing execution sequence; analyzing the continuous flow of materials between adjacent processing nodes based on the processing execution sequence, identifying the continuous conveying order of materials entering processing nodes, and forming a material conveying sequence; analyzing the continuous connection relationship between processing nodes based on the processing execution sequence and the material conveying sequence, identifying the processing waiting sections where processing nodes maintain continuous processing, and forming a processing rhythm sequence; generating production line coordination control instructions based on the processing execution sequence, each material conveying sequence, and each processing rhythm sequence, and sending these instructions to the corresponding processing equipment to control the operation of the wild edible mushroom frozen slice processing production line.

[0141] In this embodiment, the continuous extension range of the synergistic effect in the synergistic pheromone field is analyzed based on the synergistic potential lines, the continuous region covered by each synergistic potential line is identified, and a processing flow synergistic potential field is established based on the continuous region, as follows:

[0142] Based on the extension direction of the cooperative potential line in the cooperative pheromone field, identify the location where two or more cooperative potential lines converge continuously, and determine the location as the cooperative potential convergence point.

[0143] Based on the continuous tracking of adjacent processing nodes along the collaborative potential line from the collaborative potential point, the processing node segments where the collaborative effect is maintained in a continuous and concentrated manner are identified, and each processing node segment is determined as a collaborative potential ridge.

[0144] Based on the analysis of the continuous connection between the synergistic potential ridges, the combination of synergistic potential ridges that maintain continuous synergistic effect is identified, and each combination of synergistic potential ridges is determined as a cluster of synergistic potential ridges.

[0145] The location of continuous connection between the synergistic potential ridges is identified based on the synergistic potential ridge cluster, and the continuous connection processing nodes are traced along each continuous connection location to form a synergistic potential ridge connection band;

[0146] Based on the analysis of the synergistic potential ridge connecting bands, the continuous transmission direction of synergistic effect between processing nodes is analyzed, the connection channels that maintain continuous synergistic transmission between multiple synergistic potential ridge clusters are identified, and the synergistic potential corridors are divided according to the connection channels.

[0147] The coverage of the continuous expansion of the synergistic effect is identified based on the synergistic potential corridors, and the framework of the synergistic potential field is formed according to the continuous connection relationship between each synergistic potential corridor.

[0148] Based on the collaborative potential field skeleton, the coverage area of ​​the processing nodes that maintain continuous collaborative interaction is identified, and the collaborative potential field skeleton is continuously expanded in combination with the collaborative pheromone field to form a processing flow collaborative potential field.

[0149] In this embodiment, the locations where continuous closed migration loops are formed between processing flow migration paths are identified based on the processing flow migration status, and the convergence status of processing flow migration within each closed migration loop is analyzed to form a dynamic equilibrium region, as detailed below:

[0150] Extract the continuous connection relationship between each processing flow migration path based on the processing flow migration status, identify the positions where cyclic connections are formed between processing flow migration paths, and determine the positions of each cyclic connection as migration intersection nodes;

[0151] Starting from the migration junction node, the processing flow migration path is continuously traced along the processing flow migration direction, and continuous migration paths that return to the corresponding migration junction node are identified, forming a closed migration loop.

[0152] Identify migration path segments that maintain a continuous migration direction based on closed migration loops, and connect each migration path segment sequentially according to the migration direction to form a migration loop segment;

[0153] Based on the analysis of the continuous connection between adjacent migration cycle segments, the positions where the migration direction is continuously consistent and there is no migration bifurcation are identified, and the corresponding regions are determined as migration stability loops.

[0154] Based on the analysis of the migration stabilization loop, the cyclical maintenance state of the processing flow migration within the migration stabilization loop is analyzed, the location where the processing flow migration continuously accumulates inward is identified, and this location is determined as the migration convergence kernel;

[0155] Based on the continuous tracking of processing nodes outward along the migration stability loop by each migration convergence kernel, the coverage area of ​​the stable migration loop of the processing flow is identified, and a migration stability coverage area is formed.

[0156] Based on the analysis of each migration-stable coverage area, the continuous connection relationship between adjacent migration-stable coverage areas is analyzed, the positions where migration-stable coverage areas continuously maintain a closed loop are identified, and the coverage area that continuously maintains a closed loop is determined as the dynamic equilibrium area.

[0157] Example 2, Figure 2 The present invention provides a system for a collaborative control method of a frozen slicing production line for wild edible fungi, comprising a load module, a reconfiguration module, and a control module, with connections between the modules;

[0158] The load module is used to construct a processing flow network based on the material conveying relationship between each processing device in the production line, establish the load relationship of each processing node based on the operating status of each processing node, determine the load distribution of the processing nodes, and establish a processing flow load field.

[0159] The reconstruction module is used to identify load imbalance regions based on the processing flow load field, reconstruct the processing flow network based on the load imbalance regions, establish a cooperative pheromone field based on the reconstructed processing flow network, and determine the cooperative priority of each processing node based on the cooperative pheromone field.

[0160] The control module is used to generate a processing flow collaborative potential field based on the collaborative priority and collaborative pheromone field of each processing node, drive the migration of processing flows in the processing flow network according to the processing flow collaborative potential field, form a dynamic equilibrium state of processing flows, and control the operation of the wild edible fungus frozen slice processing production line based on the dynamic equilibrium state of processing flows.

[0161] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0162] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the implementation. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0163] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0164] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0165] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A collaborative control method for a wild edible mushroom frozen slicing processing production line, characterized in that, include: A processing flow network is constructed based on the material conveying relationship between each processing equipment in the production line. The load relationship of each processing node in the processing flow network is established based on the operating status of each processing node. The load distribution of the processing nodes is determined, and a processing flow load field is established. The load imbalance region is identified based on the processing flow load field. The processing flow network is reconstructed based on the load imbalance region. A cooperative pheromone field is established based on the reconstructed processing flow network. The cooperative priority of each processing node is determined based on the cooperative pheromone field. Based on the collaborative priority and collaborative pheromone field of each processing node, a collaborative potential field for the processing flow is generated. The processing flow migration in the processing flow network is driven by the collaborative potential field of the processing flow to form a dynamic equilibrium state of the processing flow. The operation of the wild edible fungus frozen slice processing production line is controlled based on the dynamic equilibrium state of the processing flow.

2. The collaborative control method for a wild edible fungus frozen slicing processing production line according to claim 1, characterized in that, The process flow network is constructed based on the material conveying relationship between each processing device in the production line. The load relationship of each processing node in the processing flow network is established based on the operating status of each processing node, the load distribution of the processing nodes is determined, and a processing flow load field is established, as detailed below: Establish the connection structure between processing nodes based on the material conveying path between each processing equipment in the production line, divide the processing flow influence domain based on the processing influence range of each processing node, and construct the processing flow network. Based on the operational status of each processing node, analyze the competitive response status of each processing node in the adjacent processing flow influence domain, extract competitive response characteristics, and divide the competitive response units. The activation direction of the competitive response is identified based on each competitive response unit, and a competitive response map of the processing flow is constructed. Identify the competitive advantage region of the processing flow based on the competitive response map, and divide the load coordination unit according to the competitive advantage region of the processing flow; Based on the distribution characteristics of each load coordination unit in the processing flow network, the cooperative evolution state between each load coordination unit is identified, and a load coordination state is formed; The load influence domain of each load coordination unit is determined based on the load coordination state, and the processing flow load field is established.

3. The collaborative control method for a wild edible mushroom frozen slice processing production line according to claim 2, characterized in that, The connection structure between processing nodes is established based on the material conveying path between each processing device in the production line. The processing flow influence domain is divided based on the processing influence range of each processing node, and a processing flow network is constructed, as follows: Based on the material conveying path between each processing device in the production line, extract the material input and output ends of each processing device, and establish the connection structure between processing nodes; Based on the connection structure between processing nodes, the flow direction of materials between each processing node is analyzed, the upstream and downstream processing nodes of each processing node are extracted, and a processing flow transmission chain is formed based on the flow association between each processing node. Based on the processing flow transmission chain analysis, the processing influence range of each processing node on adjacent processing nodes is analyzed, the direct influence area and extended influence area of ​​each processing node are identified, and the processing flow influence domain is divided. Based on the influence domain of the processing flow, extract the processing nodes that are commonly associated between adjacent influence domains of the processing flow and identify them as influence connection nodes; Based on the analysis of the connection nodes, the continuous flow direction of materials between adjacent processing flow influence domains is analyzed, and the influence transmission path of processing influence extending from one processing flow influence domain to another is identified. Extract the processing nodes that continuously participate in the transmission of processing effects based on the transmission path, and form the transmission area based on each processing node that continuously participates in the transmission of processing effects; Based on the influence transmission area, the corresponding processing flow influence domain is connected to form a processing flow influence channel; Based on the analysis of the influence domain and influence channel of the processing flow, the transmission characteristics between the influence domains of the processing flow are analyzed, and the topology of the processing flow influence is established. Based on the topology of the processing flow influence, the influence levels between the processing flow influence domains are identified, and a processing flow network is constructed based on each influence level.

4. The collaborative control method for a wild edible mushroom frozen slicing processing production line according to claim 2, characterized in that, The process of identifying the competitive advantage region of the processing flow based on the competitive response map and dividing the load coordination unit according to the competitive advantage region is as follows: Extract each competitive response activation chain from the competitive response map of the processing flow, and identify the convergence position between each competitive response activation chain to form a competitive response convergence center; Starting from each competitive response convergence center, the continuously activated competitive response units are traced level by level along the competitive response activation chain to form a competitive response propagation chain; Based on the analysis of the competitive response propagation chain, the continuous propagation direction of the competitive response in the processing flow network is identified, the competitive response extension front is identified, and a competitive response extension band is formed; Analyze the sustained range of the competitive response based on the competitive response extension band to identify the area of ​​competitive advantage coverage; Based on the competitive advantage coverage area, identify the continuous collaborative state of competitive responses among processing nodes to form a competitive collaborative cluster; Based on the analysis of competitive cooperative clusters, the synchronous evolution state of competitive response among processing nodes is analyzed to identify the synchronous evolution chain of competitive response; Based on the synchronous evolution chain of the competition response, a set of processing nodes that maintain consistent competition response is divided to form a load coordination unit.

5. The collaborative control method for a wild edible mushroom frozen slice processing production line according to claim 1, characterized in that, The process involves identifying load imbalance regions based on the processing flow load field, reconstructing the processing flow network based on these regions, establishing a cooperative pheromone field based on the reconstructed processing flow network, and determining the cooperative priority of each processing node based on the cooperative pheromone field. The specific steps are as follows: Based on the processing flow load field, identify the convergence center where the load continuously converges and the diffusion center where the load continuously diffuses, and determine the load imbalance area based on the load mismatch area formed between the convergence center and the diffusion center. Identify the processing flow transfer units adjacent to the load imbalance region based on the load imbalance region, and associate them sequentially according to the connection order between each processing flow transfer unit to form a load imbalance propagation chain; Identify alternative transmission segments based on the load imbalance propagation chain, and connect each alternative transmission segment in sequence to form a processing flow continuation path; Adjust the connection method between processing nodes in the processing flow network according to the processing flow continuation path to form a reconstructed processing flow network; Based on the reconstructed processing flow network, the intersection points between each processing flow succession path are identified, and processing flow collaborative response units are divided according to each intersection point; The processing flow collaborative response unit identifies the extended segments of the continuous collaborative transmission of the processing flow and forms a collaborative extension chain according to the successive sequence between each extended segment; The corresponding collaborative coverage area is determined based on each collaborative extension chain, and a collaborative pheromone field is established based on the spatial distribution of the collaborative coverage area. The collaborative core position of each processing node is identified based on the collaborative pheromone field, and the collaborative priority is determined based on the successive hierarchy between each processing node and the collaborative core position.

6. The collaborative control method for a wild edible mushroom frozen slice processing production line according to claim 5, characterized in that, The process involves identifying the convergence center of continuous load convergence and the diffusion center of continuous load diffusion based on the processing flow load field, and determining the load imbalance region based on the load mismatch area formed between the convergence center and the diffusion center, as detailed below: The continuous load distribution contours between each load influence domain are extracted based on the processing flow load field, and the extension direction of the continuous load distribution is identified based on each continuous load distribution contour. Identify load convergence centers and load diffusion centers based on the direction of continuous load distribution. The continuous convergence direction of the load is determined based on the load convergence center, the continuous diffusion direction of the load is determined based on the load diffusion center, and the load balance boundary line formed between the continuous convergence direction and the continuous diffusion direction of the load is identified. Based on the load balance boundary line, the load influence domains continuously distributed on both sides of the boundary line are extracted to form the load evolution zone; Identify the location where the continuous load evolution changes from synchronous to asynchronous based on the load evolution zones on both sides of the dividing line, thus forming a load decoupling zone; The continuous load mismatch region is divided according to the extent of the load decoupling band extending into the influence domain of adjacent loads, and the continuous load mismatch region is defined as the load mismatch area. Based on the connectivity distribution of the load mismatch region in the processing flow network, continuous merging is performed to form a load imbalance region.

7. The collaborative control method for a wild edible fungus frozen slice processing production line according to claim 5, characterized in that, The process involves identifying the collaborative core location of each processing node based on the collaborative pheromone field, and determining the collaborative priority based on the hierarchical connection between each processing node and the collaborative core location, as detailed below: Based on the cophery pheromone field, the region where cophery pheromones continuously converge is extracted, and the location of the cophery core is identified; Centered on the core location of the collaboration, the processing nodes are traced outward layer by layer along the continuous connection direction in the collaboration pheromone field to identify the processing node segments. Identify the continuous connection positions between the processing node and the collaborative core position based on the processing node segment, and divide the collaborative connection layers where the processing node is located in order according to the continuous connection positions. Based on the analysis of the proximity between processing nodes and the core location of the collaborative succession layer, the succession level corresponding to each processing node is determined. Based on the succession level of the processing nodes and the continuous collaborative distribution status in the collaborative pheromone coverage area where the processing nodes are located, the collaborative priority of each processing node is determined.

8. The collaborative control method for a wild edible mushroom frozen slice processing production line according to claim 1, characterized in that, The process involves generating a collaborative potential field for the processing flow based on the collaborative priority and collaborative pheromone field of each processing node, driving the migration of processing flows in the processing flow network based on the collaborative potential field, forming a dynamic equilibrium state of the processing flow, and controlling the operation of the wild edible fungus frozen slice processing production line based on the dynamic equilibrium state of the processing flow, as detailed below: Based on the coordination priority of each processing node, identify processing nodes with continuously converging coordination priorities, and form a coordination guidance area based on the processing nodes with continuously converging coordination priorities. Based on the extraction of the continuous connection relationship between adjacent collaborative guidance zones, the transmission direction of the continuous flow of processing towards the collaborative guidance zone is identified, and a collaborative potential line is formed. Based on the analysis of the synergistic potential lines, the continuous extension range of the synergistic effect in the synergistic pheromone field is analyzed, the continuous region covered by each synergistic potential line is identified, and the synergistic potential field of the processing flow is established. The starting area of ​​the processing flow migration is identified based on the cooperative potential field of the processing flow, and the direction of processing flow continuation is continuously tracked along the cooperative potential line based on the starting area of ​​the processing flow migration to identify the target segment of the continuous migration of the processing flow and form the processing flow migration path. Adjust the material flow sequence and processing task allocation relationship between each processing node in the processing flow network according to the processing flow migration path to form the processing flow migration state; Based on the processing flow migration status, identify the locations where continuous closed migration loops are formed between processing flow migration paths, and analyze the convergence status of processing flow migration within each closed migration loop to form a dynamic equilibrium region; Based on the dynamic equilibrium zone analysis, the continuous and coordinated flow state between adjacent dynamic equilibrium zones is formed to establish a dynamic equilibrium state of the processing flow. The operation of the wild edible mushroom frozen slice processing production line is controlled by adjusting the processing sequence, material conveying sequence, and processing rhythm of each processing equipment based on the dynamic equilibrium state of the processing flow.

9. The collaborative control method for a wild edible mushroom frozen slice processing production line according to claim 8, characterized in that, The process involves analyzing the continuous extension range of synergistic effects in the synergistic pheromone field based on synergistic potential lines, identifying the continuous region commonly covered by each synergistic potential line, and establishing a processing flow synergistic potential field, as detailed below: Based on the extension direction of the cooperative potential line in the cooperative pheromone field, identify the location where two or more cooperative potential lines converge continuously, and determine the location as the cooperative potential convergence point. Based on the continuous tracking of adjacent processing nodes along the collaborative potential line from the collaborative potential point, the processing node segments where the collaborative effect is maintained in a continuous and concentrated manner are identified, and each processing node segment is determined as a collaborative potential ridge. Based on the analysis of the continuous connection between the synergistic potential ridges, the combination of synergistic potential ridges that maintain continuous synergistic effect is identified, and each combination of synergistic potential ridges is determined as a cluster of synergistic potential ridges. The location of continuous connection between the synergistic potential ridges is identified based on the synergistic potential ridge cluster, and the continuous connection processing nodes are traced along each continuous connection location to form a synergistic potential ridge connection band; Based on the analysis of the synergistic potential ridge connecting zone, the continuous transmission direction of the synergistic effect between processing nodes is analyzed, the connecting channels are identified, and the synergistic potential corridors are divided according to the connecting channels. The coverage of the continuous expansion of the synergistic effect is identified based on the synergistic potential corridors, and the framework of the synergistic potential field is formed according to the continuous connection relationship between each synergistic potential corridor. Based on the collaborative potential field skeleton, the coverage area of ​​the processing nodes that maintain continuous collaborative interaction is identified, and the collaborative potential field skeleton is continuously expanded in combination with the collaborative pheromone field to form a processing flow collaborative potential field.

10. A system using the collaborative control method for a wild edible fungus frozen slicing processing production line as described in any one of claims 1-9, characterized in that, It includes a load module, a reconfiguration module, and a control module, and the modules are interconnected. The load module is used to construct a processing flow network based on the material conveying relationship between each processing device in the production line, establish the load relationship of each processing node based on the operating status of each processing node in the processing flow network, determine the load distribution of the processing nodes, and establish a processing flow load field. The reconstruction module is used to identify load imbalance regions based on the processing flow load field, reconstruct the processing flow network based on the load imbalance regions, establish a cooperative pheromone field based on the reconstructed processing flow network, and determine the cooperative priority of each processing node based on the cooperative pheromone field. The control module is used to generate a processing flow collaborative potential field based on the collaborative priority and collaborative pheromone field of each processing node, drive the migration of processing flows in the processing flow network according to the processing flow collaborative potential field, form a dynamic equilibrium state of processing flows, and control the operation of the wild edible fungus frozen slice processing production line based on the dynamic equilibrium state of processing flows.

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