379 results about "Material flow" patented technology

The invention relates to the technical field of control or regulation systems, and discloses a cooperative control method for a photovoltaic intelligent manufacturing equipment production line, and the method comprises the steps: a control unit collects the stock and change rate of materials in a physical cache region in real time; establishing and mapping the physical cache region into a virtual viscoelastic dynamic model with non-Newtonian fluid characteristics; calculating a virtual elastic restoring force enabling the stock to return to a balance point and a virtual viscous damping force preventing the stock state from changing based on the model; wherein an asymmetric anisotropic damping generation strategy is executed, and a damping coefficient is dynamically split according to a material flowing trend; and finally, superposing the virtual adjustment correction after vector synthesis to the basic transmission speed to generate a dynamic speed instruction, and by constructing a virtual dynamic field with rheological characteristics and an asymmetric damping mechanism, the problem of nonlinear cascade oscillation in discrete logistics transmission is solved, and differential self-adaptive suppression of accumulation and evacuation risks is realized.

The invention discloses an L-shaped conveyor belt path dynamic planning and congestion prediction system, which relates to the technical field of automatic control, and constructs a conveying path node diagram by collecting material weight, speed and spacing information of each node on a conveying path, and calculates a congestion index of each path section; the method comprises the following steps: combining a light-mass material jumping sensitivity model, identifying a high-risk node and marking the high-risk node as a congestion prediction area, constructing a dynamic optimization model based on path risk distribution and a material flow direction, generating and evaluating a plurality of path adjustment strategies, executing an optimal strategy according to priority, and realizing path speed adjustment, standby path switching and feeding rhythm control; through a feedback mechanism, a strategy effect is evaluated in real time, a path state is updated, operation data is synchronized to a historical database, a learnable conveying operation file is formed, the stability and the intelligent response capability of a conveying system can be effectively improved, and the method is suitable for high-speed sorting and automatic packaging scenes.

The invention discloses an injection molding equipment anomaly detection method based on a graph neural network, and the method comprises the following steps: collecting multi-dimensional monitoring data in the operation process of injection molding equipment, and carrying out the normalization, denoising and missing value filling, and obtaining structured monitoring sequence data; dividing the injection molding production process into a plurality of process stages based on timestamps and process stage labels in the structured monitoring sequence data, and constructing a corresponding stage sub-graph set; based on the stage sub-graph set, the energy transfer path, the material flow path and the historical abnormal propagation path, constructing a nested graph structure; inputting the nested graph structure into an improved dynamic graph convolutional network for feature extraction to obtain a time-aware graph embedding representation; and performing anomaly detection on the time perception type graph embedded representation to generate an anomaly detection result of the injection molding equipment. According to the method, nested graph structure modeling and the dynamic graph convolutional network are adopted, and high-precision detection and rapid positioning of the abnormal state of the injection molding equipment are achieved.

The invention relates to the technical field of soil remediation, in particular to a soil remediation formula optimization method based on solid waste raw material charcoal improvement, which comprises the following steps: acquiring a coal gangue powder material flow and a sludge material flow, respectively performing component detection on a soil sample set, the coal gangue powder material flow and the sludge material flow to obtain a component content report, performing multi-factor combination on the plurality of biochar, the plurality of microbiota and the plurality of enrichment plants to obtain a plurality of first initial raw material combinations; and constructing a plurality of unit soil remediation experiment groups based on the component content report, the plurality of first initial raw material combinations, the soil sample set, the coal gangue powder material flow and the sludge material flow, and performing a soil remediation experiment on the plurality of unit soil remediation experiment groups based on a preset test pause condition to obtain an optimal scheme. According to the invention, the formula optimization of targeted soil remediation can be realized by utilizing the charcoal, the coal gangue and the municipal sludge.

The invention discloses a material level intelligent sensing and early warning system in the silo unloading process, and relates to the technical field of silo material level intelligent sensing. The method comprises the following steps: a data acquisition module used for acquiring a multi-modal data stream; the model construction module is used for constructing a normal unloading model based on the multi-modal data flow and a preset physical mechanism constraint; the state judgment module is used for extracting a current feature vector from the multi-modal data stream; comparing the current feature vector with a feature distribution range in a multi-dimensional feature space determined by a normal unloading model, and judging a current material flow state; according to the invention, material flow abnormal symptoms can be captured in time, early warning of the blocking risk is realized, the production rhythm is prevented from being disturbed by material flow interruption, the potential safety hazard caused by manual entering into the silo for troubleshooting is reduced, the grain loss and equipment damage risks caused by long-term retention and mildew of materials are reduced, and the storage safety and the operation stability of a grain storage system are guaranteed.

The embodiment of the invention provides an intelligent monitoring method and system based on multi-source heterogeneous data fusion. The intelligent monitoring method based on multi-source heterogeneous data fusion comprises the steps that production data sets in different production scenes are collected and stored in a classified mode; mining association features of equipment operation behavior records and material circulation track information through semantic association analysis, and extracting influence features of production environment perception data in combination with environmental factor mapping to obtain multi-source qualitative features; generating a node relation chain according to the business process association relation, and configuring a matching algorithm of qualitative scene features; screening feature subsets conforming to association rules, and combining and associating the feature subsets to obtain a scene feature combination; creating a scene exception reasoning model by using the scene feature combination and performing exception feature evolution analysis to obtain an exception reasoning result; and the abnormal propagation path is traced, the root cause node is positioned, and the abnormal monitoring label is generated, so that the accuracy of abnormal root cause positioning and the scene adaptability are improved.

The invention discloses an automatic monitoring method for an industrial solid waste treatment process, and the method comprises the steps: synchronously collecting a temperature distribution matrix, a gas concentration spectrogram, a kiln body vibration spectrum and a material rheological image in the solid waste treatment process, constructing a multi-source heterogeneous data set, and carrying out the time-space alignment preprocessing; based on a preset solid waste component feature code, calling a process parameter reference value, and performing self-adaptive correction in combination with the material rheological image features to generate a personalized reference set; fusing the multi-modal monitoring data to generate a solid waste reaction process three-dimensional state model, extracting core feature parameters, comparing the core feature parameters with a personalized reference set, and screening abnormal features; inputting the abnormal features into a pre-trained abnormal diagnosis model, and when an abnormal probability value exceeds a preset threshold value, triggering early warning and generating an abnormal identifier; according to the method and the system, intelligent monitoring and regulation of the industrial solid waste treatment process are realized, and the stability, the safety and the treatment efficiency of the treatment process are comprehensively improved.

The embodiment of the invention discloses a spectrum-based substance mixing degree detection method and device. The intelligent generated data processing method comprises the following steps: acquiring first hyperspectral data of a to-be-modeled material in a stirring process state and final-state hyperspectral data of the to-be-modeled material in a uniform stirring state; establishing a final state spectrum difference curve, an intra-group spectrum difference curve and a large particulate matter distribution curve; determining a multi-dimensional mixing degree judgment index according to the final-state spectrum difference curve, the intra-group spectrum difference curve and the large particulate matter distribution curve; when it is detected that the to-be-detected material flows into the detection pipeline and is located in the to-be-detected area, starting a hyperspectral acquisition device to acquire a plurality of second hyperspectral data of the to-be-detected material; when it is detected that the multiple second hyperspectral data meet the preset validity condition, the multi-dimensional mixing degree judgment index and the preset batch qualification condition, it is judged that the to-be-detected material reaches the uniform mixing state. According to the embodiment of the invention, accurate detection of the substance mixing uniformity is realized.

The invention discloses a material tracking system for battery production, and particularly relates to the technical field of production data traceability, a process topology constraint model is constructed based on a production process, and a material flow expected path is generated; collecting behaviors of the materials in each station to form a material circulation time sequence track; matching the time sequence track with the process topology constraint model to generate a process legality state; controlling association establishment of process data and material identifiers according to a process legality state, and isolating and re-checking data which do not meet constraints; a source identifier is introduced into the process data and is bound with the process legality state, and finally a material production resume record is generated; according to the invention, through process topology constraint and behavior time sequence matching, accurate tracking of material circulation in a dynamic production scene is realized; abnormal path data is prevented from entering associative storage through legality judgment and associative gating; through source identification and resume integration, the traceability and the rechecking reliability capability of the material production process are improved.

The invention discloses a material granularity monitoring method, device and equipment and a storage medium, and relates to the technical field of granularity monitoring, and the method comprises the following steps: obtaining material flow data and an original material vibration signal, and filtering the original material vibration signal to obtain a pure material vibration signal; extracting multi-dimensional vibration characteristic signals of the pure material vibration signal in a time domain dimension, a frequency domain dimension and a nonlinear dimension; inputting the multi-dimensional vibration characteristic signal and the pure material vibration signal into a granularity inversion system for deduction to obtain an initial material granularity proportion; and calculating based on the initial material granularity proportion, the pure material vibration signal and the material flow data to obtain a compensation coefficient, and calibrating the initial material granularity proportion based on the compensation coefficient to determine the target material granularity proportion. The system can adapt to severe industrial environments with high dust and the like, hardware cost and maintenance difficulty are reduced, the whole process from signal processing to granularity calibration is automatic, the response speed is high, and the precision is high.

The invention discloses a multi-process energy consumption dynamic optimization control system for a precious metal processing production line, and relates to the technical field of precious metal processing, and the system comprises a data collection module which is used for collecting energy consumption data, process parameters and material flow data of equipment in real time; the optimization decision module comprises an energy consumption modeling unit and a dynamic optimization unit; the energy consumption modeling unit is used for establishing an energy consumption digital twin model for key equipment on a production line; the dynamic optimization unit is used for receiving and calculating a current optimal process parameter set value and an optimization instruction for adjusting the operation power and rhythm of equipment; and the driving execution module is used for realizing collaborative energy consumption optimization control of multiple processes. The method has the advantages that accurate energy consumption perception is achieved by constructing the energy consumption digital twinborn model, meanwhile, order merging is intelligently decided based on the material flow state and the order delivery time, and double optimization of overall energy efficiency improvement of the production line and comprehensive energy consumption cost is achieved.

The utility model relates to the technical field of material detection, in particular to a material flowing state detection device. The device comprises a chute, an impeller and a rotating speed detection structure, wherein a channel for materials to flow through from top to bottom is formed in the chute; the impeller is rotationally connected into the chute, and blades on one side of the impeller can make contact with materials in the material flowing process; the rotating speed detection structure is connected to the impeller and used for detecting the rotating state of the impeller in real time. Materials can push the impeller to rotate while flowing; the rotating speed detection structure can detect the rotating state of the impeller in real time to obtain the rotating speed of the impeller; a worker judges whether materials exist in the chute or not and judges the flowing state of the materials by observing the detection result of the rotating speed detection structure. The detection device can stably and reliably work for a long time, does not need to be maintained frequently, and is not easily interfered by sundries, and the detection result can accurately reflect the flowing state of the material, so that the smoothness of the production process can be improved, and accidents are avoided.

The invention relates to the technical field of valves, in particular to a high-temperature material flow adjusting device and a control method thereof.The high-temperature material flow adjusting device comprises a device body, a spring hanging bracket fixed to the device body, a water inlet and return system, a control system, a monitoring device and a connecting pipe fixed to a discharging port of the device body. By means of the curved surface fitting design of the valve head and the valve seat, linear adjustment of the high-temperature material flow is achieved, the defects that small opening is sensitive and large opening is slow are thoroughly overcome, the micro-adjustment requirement is accurately met, material level and temperature signals are collected in real time through a monitoring device, closed-loop control is constructed through a PLC control system, and the control precision of the high-temperature material flow is greatly improved. The electric actuating mechanism is automatically driven to adjust the position of the valve rod, manual intervention is not needed, manual judgment errors are avoided, potential safety hazards of operation in a high-temperature scene are eliminated, flow control accuracy and stability are greatly improved, and the problem that a traditional control loop is unstable is solved.

The invention relates to the technical field of intelligent manufacturing and industrial internet of things, in particular to an intelligent real-time production line regulation and control system and method based on digital twinning, and the system comprises a state sensing and collection module which is used for obtaining the real-time operation parameters of production equipment, material flow state information and environment disturbance characteristics of a production line; the digital twin modeling module is used for fusing multi-source data, constructing accurate mapping of a production line physical entity and a virtual model through a twin model driven by dynamic data, and predicting a performance degradation trend and a disturbance propagation path of production line equipment in real time; the intelligent decision-making module is used for generating a production line real-time scheduling strategy through a distributed collaborative reinforcement learning algorithm and outputting a production line regulation and control instruction set; and the real-time regulation and control feedback module executes production line regulation and control actions through a multi-target dynamic balance algorithm and automatically generates a production line production optimization report with equipment health degree compensation. Therefore, the problems of static model construction, lagging of a decision mechanism, lack of regulation and control feedback and the like in the prior art are solved.

The invention discloses a three-dimensional visual material dynamic management scheduling system for power station storage, and relates to the technical field of material dynamic management. The system comprises a material circulation data management module, an approval path performance analysis module, a material perfectness rate statistics and early warning module, a demand response and influence calculation module and a three-dimensional visual display module. The material circulation data management module constructs a whole-process database; the examination and approval path efficiency analysis module reveals the relationship between examination and approval time consumption and emergency degree and the path efficiency difference; the material perfectness rate statistics and early warning module forms correlation between the circulation frequency and the perfectness rate and sets an early warning threshold value; the demand response and influence calculation module calculates an aging value and provides an optimization suggestion; and the three-dimensional visual display module integrates and displays the key information to form a dynamic visual management interface, so that efficient, accurate and intelligent management and scheduling of the warehouse materials of the power station are realized.

The invention relates to the technical field of blister thermoforming, and discloses a high-precision controllable thermoforming method of a blister machine, which comprises the following steps: extracting a feature recognition material type, and calculating to obtain a thermal diffusion coefficient; a temperature field is collected in real time, temperature distribution at the next moment is predicted, a fuzzy rule base is established to dynamically adjust PID parameters, a falling risk coefficient is calculated based on the actually measured temperature, and whether airflow compensation is started or not is judged; a mold cavity structure is constructed, and a vacuum degree curve is set in stages; material flow monitoring is conducted on the material, and the vacuum degree is corrected through fuzzy control; analyzing to obtain a coordinate deviation, and executing dynamic compensation; performing real-time correction according to the coordinate deviation, establishing an inter-station coupling coefficient matrix through multi-station cooperative control, and performing temperature compensation; and constructing a multi-dimensional quality evaluation model, performing analysis to obtain a comprehensive quality index, judging whether to trigger a key parameter optimization process or not based on the comprehensive quality index, and performing real-time feedback optimization.

The invention provides a sewage plant water-energy-drug collaborative optimization method and system, and the method comprises the steps: obtaining the data of a technological process and a material transfer relationship of a sewage plant, constructing a graph network structure model with a technological unit as a node and material flow as an edge, and carrying out the preprocessing, thereby obtaining dynamic coupling graph structure data; a dynamic coupling graph neural network model containing a node feature coding layer, a time sequence coding module, a space message passing layer and an attention mechanism layer is constructed based on the data, and a prediction model capable of representing the dynamic coupling relation of the process unit is obtained through historical data training; then, a multi-objective optimization function which takes the lowest ton water treatment cost as an objective and covers water quality standard reaching, energy consumption and medicament dosage constraints is constructed; and in combination with the prediction model and the optimization function, the optimal operation parameters are solved through an optimization algorithm, and a whole-plant collaborative optimization decision scheme is generated. According to the invention, the dynamic coupling GNN prediction model and the virtual element multi-domain parallel optimization technology are integrated, and intelligent operation management of the sewage treatment plant is realized.

The invention relates to the technical field of production line scheduling, in particular to a production line resource scheduling control method and system, and the method comprises the steps: connecting end equipment of each production line through a parallel pipeline and a controllable valve to form a shared equipment resource pool, and obtaining the operation data information of each production line when a production request is received, the operation data information comprises the material flow and the equipment load rate of the end equipment, performing calculation based on the material flow and a preset target yield to obtain a demand calculation result, and dynamically scheduling the end equipment in the shared equipment resource pool based on the equipment load rate and the demand calculation result. According to the technical scheme of the invention, by constructing the'shared equipment resource pool ', the barrier that the resources of the traditional production lines are isolated is broken, and the elastic allocation and sharing of the resources across the production lines are realized, so that the resource utilization rate of the end equipment is improved, and the comprehensive output efficiency of the whole production system is improved.

The invention relates to the technical field of remote management, in particular to a medical SPD intelligent cabinet remote management method and system, and the method comprises the following steps: screening abnormal points based on the operation data of an intelligent cabinet, extracting a deviation amplitude, searching an inventory trend, screening a boundary point set, judging a flow trend, positioning a scheduling axis sequence, and marking a key monitoring position; and acquiring response time delay to judge interference matching, and generating an automatic material dispatching response unit. According to the method, through combined comparison of the switching frequency, the temperature and humidity fluctuation and the inventory change rate, state abnormal point and inventory boundary features are extracted, a material flow center is accurately identified, a flow direction inflection point is actively identified and pre-judged, and meanwhile, by means of linkage judgment of response time delay and operation displacement, path interference is dynamically identified and a response path is automatically bound; the dynamic perception, path adaptation and remote response efficiency in the scheduling process is improved, the judgment precision and intelligent response capability of the intelligent cabinet to abnormity are enhanced, and the effectiveness of material monitoring and remote management is improved.

The invention belongs to the technical field of conveyor intelligent speed regulation control, and particularly discloses and provides a conveyor intelligent speed regulation control method based on sensor data, which comprises the following steps: collecting the current speed, load, material flow and running state data of a conveyor in real time; carrying out load trend analysis in combination with historical operation data, and predicting a future load change curve; the running health condition of the equipment is judged according to the state parameters of the key components, a first smooth speed instruction is generated based on a load curve and the current speed if the equipment is healthy, a safe speed threshold value is determined and a second smooth speed instruction is generated if the equipment is not healthy, and finally a driving motor is controlled to execute speed regulation; according to the method, the load change curve of the future set time period is predicted through the material flow data and the historical operation data which are collected in real time, and the smooth speed instruction is generated through the S curve planning algorithm based on the prediction result, so that the look-ahead and smooth regulation and control of the speed are realized.

System, product or method for facilitating manufacturing in a factory, comprising receiving a P&ID diagram of equipment elements and control modules in the factory and / or using a hardware processor to identify, and to provide an output indication of, material flow routes that connect at least some of the equipment elements and / or control modules including, e.g. for each route, an ordered sequence of equipment elements and / or control modules from a source to a destination and a direction.

The utility model discloses a blanking hopper of an automatic packaging machine, the blanking hopper is respectively connected with a finished product bin and a material temporary storage hopper, the blanking hopper is provided with an inclined material slope, an abutting vibration motor is arranged outside the material slope, and a drawing flow baffle is arranged at the bottom of the material temporary storage hopper. Through structural improvement, a transition hopper, a linear vibrating screen and other components are removed and replaced with the discharging hopper with the inclined material slope and the vibrating motor, and normal sliding of materials is guaranteed with gravity as a main part and exciting force as an auxiliary part; a special material baffle is arranged at the bottom and used for controlling the discharging speed, and the packaging efficiency can be improved; a direct material conveying part of the whole set of equipment is not provided with built-in electric equipment, so that potential safety hazards such as heating are avoided; the motor and the vibration motor are controlled to start and stop synchronously at the baffle plate, so that auxiliary vibration is carried out only under the condition that the materials flow, and the materials precipitated in a static state are prevented from being compacted by vibration; the whole structure is simplified, and the interior is convenient to clean and maintain.

The invention provides an intelligent management and control system and method for a food processing production line, and the method comprises the steps: activating an equipment control algorithm to carry out the parameter adjustment of putting equipment if a difference characteristic vector exceeds a preset threshold range, determining the adjusted putting rate and volume parameters, and enabling the parameters to be optimized based on the equipment performance and material flow characteristics; according to the precision conformity mark, a formula proportion model of various raw materials is updated through a feedback mechanism, an updated formula proportion coefficient is determined, and the coefficient is used for adjusting the proportion relation between the raw materials to maintain formula balance; according to the stable fusion data set, a putting execution instruction sequence is generated, the instruction sequence comprises an action sequence and parameter configuration, and the instruction sequence is output to an actuator to achieve raw material putting control consistent in formula.

This invention discloses a feeding speed control system and method based on the material level of a metering tube, applied to a yarn-making line. The yarn-making line includes a metering tube, an electronic scale, and multiple belts. Material flows sequentially from the first belt, the second belt, the third belt, and the metering tube to the weighing device. The feeding speed control system includes a control module and multiple photoelectric detection modules. The metering tube is divided into multiple material zones for characterizing the amount of material inside. The multiple photoelectric detection modules are all located inside the metering tube, and the number of photoelectric detection modules is the same as the number of material zones. Each photoelectric detection module is set to correspond to each material zone and is used to detect the material in the corresponding material zone. The control module is electrically connected to the multiple photoelectric detection modules and is used to control the feeding speed of the first belt, the second belt, and the third belt respectively according to the material information detected by the multiple photoelectric detection modules. This allows for real-time adjustment of the feeding speed of each belt, ensuring that the material flow rate in subsequent processes is quantitatively controllable.

The present application relates to a method and system for collaborative management of multiple devices in an agricultural microbial preparation production line, which method comprises calculating a device health score based on operating state information, combining the device health score with a biological risk index to generate a task release score, generating a production task instruction when the task release score meets a preset release threshold, constructing a collaborative interlocking matrix between multiple types of process equipment and material handling equipment based on the production task instruction, distributing control execution instructions to the multiple types of process equipment and material handling equipment, obtaining device feedback state information and material flow information respectively, performing consistency verification on the device feedback state information and the material flow information to obtain a consistency verification result, generating a revision audit chain corresponding to the control event information when manually modified, and generating a disposal control instruction when the operating state information or the control event information triggers a preset abnormal threshold. The present application has the effect of improving production safety.

The utility model belongs to the technical field of material transportation, and discloses an adjusting device. The adjusting device comprises a rotating plate, a connecting mechanism and an adjusting part, the rotating plate can move in the material flow direction and can rotate in the discharging scraper-trough conveyer, and the rotating plate is used for blocking materials in the discharging scraper-trough conveyer so as to change the material falling position of the materials; the connecting mechanism comprises a first connecting block, a second connecting block and a locking piece, a sliding groove extending in the length direction of the rotating plate is formed in the rotating plate, the first connecting block is slidably connected to the sliding groove, the second connecting block is slidably connected to the discharging scraper-trough conveyer in the first direction, and the locking piece can fix the second connecting block and the discharging scraper-trough conveyer; the adjusting piece is connected to the second connecting block and can push the rotating plate to enable the rotating plate to rotate. According to the adjusting device, the rotating plate can slide in the material flow direction of materials, the rotating plate does not need to be disassembled and assembled when a shielding part is replaced, operation steps are reduced, and the material conveying efficiency is improved.

The present application relates to a kind of blast furnace distribution chute minimum distribution circle number quantification method and application.Firstly, the maximum material passing area is calculated by using the collision point of the material falling from the center throat pipe to the chute receiving bottom, the maximum material flow volume flow allowed by the initial velocity and the maximum material passing area after material flow collision is calculated, and then the shortest distribution time of ore group and coke group is calculated, finally, the minimum distribution circle number of each group is calculated according to the chute rotating speed.When the original distribution circle number is greater than or equal to the minimum distribution circle number, there is no risk of material overflow, and the distribution matrix does not need to be adjusted;When the original distribution circle number is less than the minimum distribution circle number, there is a risk of material overflow, and the distribution matrix needs to be adjusted to make the total distribution circle number exceed the minimum distribution circle number.The present application can accurately grasp the material flow velocity and distribution law, realize the precise control of distribution parameters, ensure the stable material falling point, uniform material surface and reasonable airflow distribution, and support the efficient and stable operation of blast furnace.

The embodiment of the invention discloses a construction method of a multi-source organic solid waste whole-process substance flow and energy flow metabolic network diagram and a related device. A basic theoretical analysis and research framework is set up; constructing an urban typical organic solid waste material flow model according to the basic theoretical analysis and research framework; and according to the urban typical organic solid waste material flow model, constructing a Yifen city typical organic solid waste metabolic network. It can be seen that the embodiment of the invention is beneficial for solving the following problems: 1, composition and characteristics of the organic solid waste can be better understood by establishing a substance flow and energy flow metabolic network diagram, so that a more efficient and more economical treatment process is designed; 2, through the metabolic network diagram, the influence of the organic solid waste treatment process on the environment can be better known, so that measures are taken to reduce the influence of the organic solid waste on the environment.

The invention discloses an environment-friendly chemical product sales prediction method based on big data, and relates to the technical field of supply chain prediction, and the method comprises the steps: recognizing an environment-friendly replacement intention triggering behavior in the environment strategy information of a supply chain participant, and associating the supply chain participant according to a material flow direction, thereby forming a cross-enterprise environment intention chain; comparing an action sequence in the cross-enterprise environment intention chain with a usual action sequence before historical environmental protection substitution of a supply chain participant, positioning a substitution trigger point, and generating a substitution trigger time sequence according to time; and performing feasibility matching on the sales volume window and the corresponding logistics execution capability information to generate an execution-level sales prediction table. According to the method, the environment-friendly substitution intention triggering behavior in the supply chain participation main body environment strategy information is identified, and the cross-enterprise environment intention chain is constructed along the material flow direction, so that a real causal chain required to be generated in the supply chain is effectively described.

The invention discloses a two-stage separation disc structure for a vacuum system for enhancing moisture vaporization, and relates to the technical field of water vapor separation, the two-stage separation disc structure comprises a storage tank and a first assembly mounted on the storage tank; a baffle plate on the outer ring of a first-stage separation disc adopts an inclined annular design with high inside and low outside, so that most vaporific materials thrown out in the rotating process can be intercepted, the intercepted materials flow back to the surfaces of the separation discs along inclined plate surfaces, the retention time of the materials in a vacuum area is prolonged, and the loss rate of the materials along with water vapor loss is reduced; meanwhile, the two sets of double-plunger pumps precisely convey the materials to the inner disc centers of the first-stage separation disc and the second-stage separation disc from the upper end and the lower end of the storage tank correspondingly, agglomeration waste in the material conveying process is avoided, and the raw material utilization rate is further increased; from the perspective of cost, the reduction of material loss directly reduces the raw material purchase cost, the efficient vaporization effect shortens the single dehydration period, the equipment productivity utilization rate is indirectly improved, and the production cost of a unit product is reduced.