49 results about "Process flow diagram" patented technology

The embodiment of the invention provides a mining factory aided design method and system, and the method can obtain design demand data input based on a browser page canvas, and builds a target process model according to the design demand data. Wherein the target process model comprises a general model and a special model. And calculating process flow data based on the target process model, executing equipment type selection calculation according to the process flow data, generating a calculation logic diagram, and mapping the calculation logic diagram into a process flow diagram. According to the method, process modeling and process calculation can be quickly carried out, and a special model conforming to the industrial computer theory is supported to be built, so that modeling and calculation are simpler and more efficient. Meanwhile, a calculation result and a model can be conveniently applied, equipment type selection calculation and process flow diagram output are carried out, unification of models and data in all links is achieved, and the design efficiency of a mining factory is improved.

The invention is suitable for the technical field of agent adding, and particularly relates to a water treatment agent adding method and system.The method comprises the steps that a technological process diagram of a sewage treatment pond is drawn, a water inlet and a water outlet are found out, online monitoring equipment arranged at the water inlet and the water outlet in advance is used for collecting technological indexes of sewage, and the technological indexes of the sewage are obtained; a water inlet index and a water outlet index are defined; the two ends of the backflow pipeline are located at a water inlet and a water outlet respectively, the deployment mode of verification equipment and an intermediate storage tank in the backflow pipeline is set, the verification equipment is used for reading the concentration parameter of backflow liquid in the intermediate storage tank, the concentration parameter is defined as a verification index, the backflow ratio is set, and the verification result is obtained. And creating a multi-level verification mechanism. By collecting real-time sensing data, predictive accurate dosing can be realized, the use efficiency of the medicament can be optimized, a data basis is provided for advanced adjustment of a dosing system, and the stability of effluent quality is greatly improved.

The invention discloses a complex electronic equipment manufacturing process model simulation verification and optimization method. The method comprises the following steps: acquiring a process flow diagram in a manufacturing process model; performing chart conversion, resource library analysis and process flow diagram analysis on image-text data in the obtained process flow diagram, and taking data obtained by the chart conversion, the resource library analysis and the process flow diagram analysis as an input file of manufacturing process model simulation; carrying out operational analysis on the input file, and giving out warning and error information prompts; and modifying the manufacturing process model on the basis of a set rule and a production operation historical data optimization method until no error occurs in simulation. According to the method, the workload of repeatedly modifying the manufacturing process model can be reduced, the matching property of the manufacturing process model and the actual business is improved, and the predictability of the production process is improved, so that the optimization of the product process route, the controllable process quality and the achievable delivery plan are ensured.

The invention discloses a foreign matter detection visual identification system for display panel production, and relates to the technical field of display production, and the system comprises a monitoring area division module which divides a display panel into a plurality of monitoring sub-areas based on a display panel structure diagram and a process flow diagram, each monitoring sub-area is endowed with a unique area number, and the area number of each monitoring sub-area is stored; the label comprises a region coordinate range, a structure label and a process stage label; and the identification detection module is used for carrying out image detection on each monitoring sub-region, acquiring a local image feature set, carrying out enhancement processing on the local image feature set, and outputting a group of standardized structure enhanced image identification data. According to the invention, a multi-dimensional process parameter sequence modeling mechanism is introduced into the mapping module, and depth time sequence prediction models such as a long-short-term memory network and the like are integrated, so that the possibility of occurrence of foreign matter defects in the future can be predicted based on parameter variation trends such as temperature, pressure and exposure power of each monitoring sub-region in different process stages.

The invention belongs to the field of production management, and discloses a method and a system for intelligently arranging mixed styles on a sewing assembly line, and the method comprises the steps: combining the working procedures of various styles into operation elements according to the similarity detection and mixed style process analysis of single style process analysis data before the mixed arrangement production of various styles; generating a mixed intelligent process flow diagram containing an operation element table based on the operation elements; calculating order values of the operation elements according to the wiring setting parameters in combination with the mixed intelligent process flow diagram, generating an operation element sequence table, and combining the operation elements according to a preset rule to obtain an optimal arrangement scheme of the operation elements; and calculating the commissioning sequence of the mixed arrangement of the styles, and cyclically commissioning in the mixed assembly line according to the commissioning sequence. According to the method, small and medium-sized clothing factories are not subjected to high equipment investment, and for quick-return small bills with multiple styles, small quantity and tight delivery time, the small bills are changed into large bills, so that continuous and efficient output is realized.

The invention discloses an intelligent supervision and management method and system for factory production, and relates to the technical field of production management, and the method comprises the steps: constructing a time difference chain based on an operation behavior, and extracting a fluctuation feature element through a sliding window; performing frequency domain transformation on the fluctuation characteristic elements to obtain a rhythm fluctuation spectrum; calculating a dynamic time warping distance between the rhythm fluctuation spectrum and a historical rhythm reference spectrum to obtain a spectrum deviation descriptor; mapping the spectral deviation descriptors into a standard semantic process flow diagram in a nested manner to form a rhythm process nested diagram; node-level index semantic vectors are extracted from the rhythm process nested graph based on a graph embedding algorithm, multi-dimensional semantic alignment detection is executed, and alignment residual measurement is output; and aggregating the alignment residual measurement, generating a structured dislocation score list, and constructing an abnormal behavior scene graph based on a score threshold. According to the method, the rhythm fluctuation spectrum is generated and semantic nested mapping is carried out, so that the abnormity and semantic dislocation in the production supervision process are identified.

The process calculation method of the water treatment process comprises the following steps of: 1, making a water treatment process flow diagram for simulating a real water treatment process flow on a picture; a step 2 in which the flow rate of each liquid flow is temporarily determined on the water treatment process flow diagram so that the water revenue and expenditure for each unit icon are not contradictory; a step (3) in which any one of the flow rates of the liquid flow determined in step (2) is changed and determined to an arbitrary value; a step 4 for calculating and specifying, on the basis of the specified flow rate of the liquid flow, the flow rate of all the liquid flow that must be calculated; a step (5) for selecting one cell icon connected to one or more of the liquid flows for which the flow rate has been determined and to one or more of the liquid flows for which the flow rate has not been determined, and calculating and determining the flow rate of all the liquid flows for which the flow rate has not been determined and which are connected to the selected cell icon in accordance with the priority set for each cell icon; and a step (6) in which steps (4-5) are repeated until the flow rate of all the liquid flows is determined.

The invention relates to the field of natural gas unmanned stations, discloses a natural gas unmanned station reliability quantitative evaluation method, device, equipment and medium, and can determine a plurality of key equipment types in a natural gas unmanned station and the number of equipment corresponding to each key equipment type according to a process flow diagram of the natural gas unmanned station. Generating a fault tree model based on the plurality of key device types and the corresponding device number; wherein the fault tree model comprises a station failure top event, a middle event group and a bottom event group which are connected through a logic gate. And determining a plurality of event states of a bottom event group in the fault tree model and corresponding event state probability distribution. And constructing a plurality of bottom event state groups based on a plurality of event states and event state probability distributions of the bottom event groups. And determining the reliability of the natural gas unmanned station according to the plurality of bottom event state groups, the station failure top event in the fault tree model, the intermediate event group and the logic gate, thereby effectively realizing quantitative evaluation of the reliability of the natural gas unmanned station.

The invention discloses a method for converting a water treatment process flow diagram into a graph model, which comprises the following steps of: 1, identifying a graph and a character identifier in a water treatment process flow diagram to be converted by using an image and text identification algorithm; 2, extracting engineering project information, a technological process topological relation, technological unit information and technological unit part information in the water treatment technological process diagram; 3, dividing nodes of the graph model into three layers of mother nodes, child nodes and grandchild nodes which are connected with a topological relation step by step; 4, obtaining engineering project information; 5, converting into a child node and child node connection relationship in the graph model; step 6, acquiring information of each process unit in the process flow diagram; 7, converting the flow data and inlet and outlet water quality data of each process unit into attributes of a node connection relationship; and step 8, acquiring part information of each process unit. The method has the beneficial effect that the conversion rate of the water treatment process flow diagram to the digital diagram model can be improved.

The invention relates to a model training method and a parameter prediction method and device based on a flow chart. The method comprises the steps of obtaining key configuration data of a current process in a process flow chart; a flow chart data set is generated according to the key configuration data, the flow chart data set serves as a training sample, and the flow chart data set comprises flow convergence state information; and constructing a network model based on a variational auto-encoder of any condition, training the network model by using the training sample, and constructing a flow chart network model adaptive to the process flow chart. Performing missing value prediction on the key configuration data by using the flow chart network model, and performing parameter adjustment on the key configuration data according to the predicted missing value; and inputting the adjusted configuration data into the process flow diagram to carry out convergence prediction. Therefore, the problem of non-convergence of the optimized chemical process flow diagram is solved, the convergence probability of the flow diagram is improved, and meanwhile, the simulation stability and efficiency are improved.

An automation device (1) for executing a process flow, the automation device (1) having at least one function module (3) for executing process steps (9a, 9b) of the process flow, wherein the function module (3) has at least one object interface (4a, 4b) and module data (7); the automation device (1) having a transport device (5) for transferring an object (2a, 2b) to the object interface (4a, 4b) and / or for receiving the object (2a, 2b) from the object interface (4a, 4b); the automation device (1) having a control device (6) for controlling the function module (3) based on a process flow diagram (8); characterized in that the control device (6) is configured to parameterize the process flow diagram (8) based on the module data (7).

The embodiments of the present application belong to the technical field of digitalization of nuclear power plants. Provided are a method and apparatus for converting a process flow diagram of a nuclear power plant, and an electronic device and a storage medium. The method comprises: acquiring a plurality of original process flow diagrams in different flow diagram formats; on the basis of the flow diagram formats, performing graphic symbol information recognition on the original process flow diagrams, so as to obtain item graphic symbol data, wherein the item graphic symbol data comprises a plurality of pieces of graphic symbol information and a corresponding graphic symbol image of each piece of graphic symbol information, and each piece of graphic symbol information is used for representing a type of item; on the basis of each piece of graphic symbol information in the item graphic symbol data, performing attribute information matching, so as to obtain item attribute information corresponding to each item; and on the basis of the graphic symbol image corresponding to each piece of graphic symbol information and the corresponding item attribute information, constructing a target process flow diagram having a unified flow diagram format. The embodiments of the present application enable complete conversion of drawing data from different development platforms while retaining complete attribute information and corresponding associated information.

The invention discloses an optimization method for slow loading of a process flow diagram of a ship system. The method specifically comprises the following steps: S1, reading and caching the process flow diagram; carrying out cache management on the read process flow diagram; s2, managing the cached process flow diagram, and selecting a specific process flow diagram by reading and displaying the cached process flow diagram; s3, selecting a specific process flow diagram, and carrying out initialization loading on the selected process flow diagram; and completing loading and updating of the process flow diagram. Through system loading, flow chart cache management and interface container loading, the method is used for solving the problem of slow display of the flow chart of the propagation system, and the method comprises the steps of loading the flow chart in advance, increasing the loading speed of the flow chart, increasing the data refreshing speed, increasing the efficiency of opening the flow chart interface, avoiding jamming of a plurality of flow charts, and improving the display efficiency of the flow chart. Content disorder of a flow chart interface is avoided.

The present invention is entitled "Method for Analyzing the Impact of Operator Actions in an Industrial Plant". The present invention relates to the field of processing systems, in particular, processing systems for industrial plants. The present invention discloses a method for determining the interdependencies between multiple elements in an industrial processing system. The method comprises the following steps: providing a process flow diagram PFD of the topology of the processing system; converting the PFD into a directed graph, wherein each of the multiple elements is converted into a node, and each relationship between the multiple elements is converted into a directed edge; selecting a node from the multiple nodes as a starting node; and constructing a subgraph, wherein the subgraph consists of all nodes forward connected from the starting node, thereby showing at least one interdependency between the multiple elements in the subgraph.

The invention is suitable for the technical field of sewage treatment monitoring, and particularly relates to a real-time monitoring method and system for sewage treatment, and the method comprises the steps: delimiting a real-time monitoring range of sewage treatment, searching emission source equipment, selecting an influence point location, collecting video data through video monitoring equipment which is installed at the emission source equipment in advance, and transmitting the video data to a server; intercepting a state snapshot containing an influence point location; and drawing a process flow diagram of sewage treatment, setting sewage characteristics of each influence point location, and creating treatment rules in one-to-one correspondence with the sewage characteristics. By comparing the pollutant concentration with the expected concentration, deviation and compensation can be carried out on the pollutant concentration, the accuracy of monitoring data is improved, the treatment risk is reduced, and the effluent quality is ensured, so that the dosing process is accurately controlled through advanced prediction and refined monitoring, the effluent quality is ensured to be stable, and the economic benefit is improved. The sewage treatment efficiency and the sustainable management level are improved.

The application provides a kind of oiling path planning method and device, and a kind of computer readable storage medium.The planning method includes the following steps: according to the process flow diagram of crude oil tank farm, directed graph model is established, and the attribute data and state data of process equipment and / or pipeline in the crude oil tank farm are saved to corresponding node and / or corresponding link;Adjacency list is established to store the attribute data, state data, index information of the pointing node of each node and link information connected to the pointing node;Obtain at least one subtask starting node information, termination node information and ideal pump flow data;According to multiple optimization objectives, the directed graph model and the adjacency list, the objective function of the multi-objective optimization problem is established, and the feasibility constraint conditions of path search and path combination are set;And based on the feasibility constraint condition, multi-objective evolution operation is carried out to determine at least one non-dominated path planning scheme.

A method for using generative artificial intelligence (AI) to produce a framework for a simulation workflow includes receiving a process flow diagram for equipment at a facility. The method also includes receiving first data related to the equipment from one or more sensors. The method also includes determining parameters for the equipment based upon the process flow diagram and the first data. The method also includes receiving second data from the one or more sensors. The method also includes calibrating a subset of models based upon the parameters, the first data, and the second data to produce calibrated models. The method also includes performing a facility simulation using the calibrated models based upon the second data to produce an output.

The invention discloses an AI intelligent agent-based atmospheric and vacuum distillation unit intelligent management and control method and system, and relates to the field of petrochemical engineering, and the method comprises the steps: building a high-fidelity digital twin virtual model through a process flow diagram, a pipeline instrument flow diagram and historical operation data of an atmospheric and vacuum distillation unit, and carrying out the division of a process control loop according to a process control loop division principle; defining and initializing a micro agent; the method comprises the following steps: performing off-line parallel training on a micro-agent in a high-fidelity digital twin virtual model, collecting time sequence data, constructing a causal association map of an atmospheric and vacuum distillation unit by using a causal discovery algorithm, and calculating dynamic association strength among behavior data of the micro-agent. Through decision guidance of agent grouping based on dynamic association strength and causal contribution degree calculation, deep coupling of a global optimization target and local control is realized, and the problem of insufficient long-term adaptive ability caused by lack of causal reasoning in a traditional method is overcome.

A process flow diagram reconstruction method, device, medium and product, the process flow diagram reconstruction method comprising: using a first flow diagram processing model to identify the types and positions of all devices in a to-be-reconstructed process flow diagram to obtain the type information and position information of all devices, identifying the positions of all the device names in the to-be-reconstructed process flow diagram by using a second flow diagram processing model to obtain the position information of all the device names, and obtaining all the device names according to the obtained position information of all the device names and a character recognition tool, creating corresponding equipment on a configuration interface in a graphical mode according to the obtained type information and position information of all the equipment, and adding the obtained equipment names to the created equipment according to the obtained position information of all the equipment names so as to obtain a reconstructed process flow diagram, therefore, a large amount of labor cost and time cost are saved.

This invention relates to the field of chemical dosing technology, and particularly to a method and system for adding water treatment chemicals. The method includes: drawing a process flow diagram of a wastewater treatment tank; locating the inlet and outlet; using online monitoring equipment pre-deployed at the inlet and outlet to collect wastewater process parameters, defining them as influent and effluent parameters; marking the return pipeline in the process flow diagram, wherein the two ends of the return pipeline are located at the inlet and outlet respectively; setting the deployment method of calibration equipment and intermediate storage tank in the return pipeline; using the calibration equipment to read the concentration parameters of the return liquid in the intermediate storage tank, defining them as calibration parameters; setting the return ratio; and creating a multi-level verification mechanism. This invention, by collecting real-time sensor data, enables predictive and precise chemical dosing, optimizes chemical usage efficiency, provides a data basis for advance adjustments to the dosing system, and significantly improves the stability of effluent water quality.

The invention provides a ship block construction lean dispatching method, which comprises the following steps: S1, dividing a construction process into a plurality of working steps according to a process flow diagram of ship block construction, and calculating the unit time of each working step; s2, obtaining the actual object amount required during ship block construction; s3, calculating the standard operation time required by the segmented construction, and calculating the correction operation time of the segmented construction in combination with the standard operation time and the broadening factor; s4, forming an hour-level process flow diagram of ship block construction; and S5, performing personnel balance deduction to form a personnel configuration table, and generating an hour-level dispatching table of ship block construction according to the personnel configuration table and the hour-level process flow diagram. According to the technical scheme, the hour-level process flow diagram of ship block construction can be formed, the hour-level dispatching table of ship block construction is finally generated in combination with personnel balanced deduction, personnel can be helped to cope with a complex and changeable production environment, and it is ensured that the ship block construction process is smoothly completed.

The invention belongs to the technical field of simulation modeling, and particularly relates to an automatic simulation modeling method based on a process flow diagram. Calibrating a simulation modeling range on the process flow diagram; determining the boundary and the boundary type of the simulation modeling range; extracting equipment information, pipeline information and boundary information in the process flow diagram; obtaining a one-dimensional graphical numerical calculation model through four-step translation according to a mapping relation between process flow diagram equipment and a graphical model, a node division standard, a pipeline connection standard and a boundary division standard; graphical model component coding is carried out, the model components are automatically coded according to the simulation modeling coding standard, and each model component has a unique code; and evaluating the quality of the graphical model of the process system by adopting a simulation model comprehensive evaluation method. According to the method, the modeling information is directly extracted from the process flow diagram, the defects that manual modeling is low in efficiency and high in error rate are overcome, the simulation modeling efficiency of complex process system engineering can be effectively improved, and the production cost is reduced.

Systems and methods for generating industrial process flow diagrams using generative AI and image recognition are described herein. In certain embodiments, a system includes memory devices that stores a cognitive services model trained to determine whether image data represents process information; and a generative model trained to generate process diagram information from the image data. The system also includes processors that receive the image data; and execute the cognitive services model to determine whether the image data contains information associated with a process. When the cognitive services model determines that the image data contains the information associated with the process, the processors are also execute the generative model using the image data to generate the process diagram information. Further, the processors provide the process diagram information to a diagram visualization program, wherein the diagram visualization program generates a diagram from the process diagram information.

The embodiment of the invention provides a process flow diagram generation method and device, equipment and a storage medium, and relates to the technical field of processes. The method comprises the following steps: acquiring an initial process flow diagram file; performing analysis and vectorization processing on the initial process flow diagram file to obtain a process flow diagram file based on a vector diagram format; the process flow diagram file based on the vector diagram format is subjected to standardization processing, a standardized process flow diagram file is obtained, and elements in the standardized process flow diagram file are standardized elements. By adopting the technical scheme provided by the embodiment of the invention, the generation efficiency of the process diagram can be improved.

The application discloses a foreign matter detection visual identification system for display panel production and relates to the technical field of display production, and comprises a monitoring area division module, a recognition detection module and the like, wherein the monitoring area division module divides a display panel into a plurality of monitoring sub-areas based on a display panel structure diagram and a process flow diagram, each monitoring sub-area is given a unique area number, and each monitoring sub-area contains an area coordinate range, a structure label and a process stage label; the recognition detection module performs image detection on each monitoring sub-area, acquires a local image feature set and performs enhancement processing on the local image feature set, and outputs a group of standardized structure enhancement image recognition data. Through the introduction of a multi-dimensional process parameter sequence modeling mechanism in the mapping module and the integration of a deep time sequence prediction model such as a long short-term memory network, the application can predict the possibility of future foreign matter defects based on the temperature, pressure, exposure power and other parameter change trends of each monitoring sub-area at different process stages.

The invention provides a method and system for converting a process flow diagram picture into an EBPFD model file, and the method for converting the process flow diagram picture into the EBPFD model file comprises the steps: carrying out the extraction processing of elements, characters and connecting lines in the process flow diagram picture, building the connection with an EBPFD model, and converting the process flow diagram picture into the EBPFD model. Therefore, the efficiency and quality of conversion from the process flow diagram to the EBPFD model file are improved.

The embodiment of the invention discloses a process fault detection method, device and equipment, a medium and a program product, and relates to the technical field of industrial process fault detection. The method comprises the following steps: constructing digraph structure data according to a process flow diagram, and obtaining state time sequence data in real time; inputting the state data into a feature extraction model to obtain dynamic time sequence features; constructing state time sequence features according to the dynamic time sequence features and embedded vectors containing learnable parameters; determining a target attention coefficient and a classification input feature between each target node and other target nodes in the directed graph structure data; and inputting the classification input features into a classifier to determine a process fault type, and determining a root cause node causing the process fault from the target nodes according to fluctuation data of the target attention coefficient relative to the stable attention coefficient. According to the scheme, the influence degree of the node on the process fault can be explicitly displayed, so that the technical process and the process fault reason are transparent.

The invention belongs to the field of abnormal working condition prediction and early warning, and discloses an abnormal working condition prediction method, which comprises the following steps: firstly, according to a process flow diagram and process parameters, establishing a process flow steady-state model, adding a controller, establishing a dynamic mechanism model, simulating a fractionating tower tray overtemperature working condition, and obtaining historical data and dynamic simulation data of a fractionating device production process; secondly, screening characteristic variables through a Pearson correlation coefficient, and reducing the data dimension; and utilizing a GA-BP neural network to deeply learn a potential relationship between variables so as to predict a change trend of process key parameters. And finally, comparing the predicted value of the process parameter with a preset alarm limit value, and selectively executing an alarm operation corresponding to the chemical device with the process parameter.

The invention relates to the technical field of process file templates, and provides a process file template creation method, which comprises the following steps of: 1, creating three blank basic worksheets; step 2, creating nine blank process file worktables; the blank process file worksheet comprises an unfilled envelope, a catalog, a product and process special characteristic list, a process flow chart, a control plan, a machining card, a special inspection record, a self-inspection record and a tool list blank worksheet; 3, creating five user-defined windows for quickly inputting information and outputting process files; 4, creating a process file in the custom tab and a custom tool of the process file; and 5, checking the template. According to the method, the input time for filling tedious files can be shortened for process engineers, the repeated input process is saved, the information in the basic worksheet is automatically extracted and filled into the process file worksheet, simple errors caused by wrong writing of the process engineers are avoided, and the efficiency and accuracy of process design are improved.

The present application relates to the field of municipal design, in order to improve the drawing efficiency of process flow diagram, provide a kind of sewage treatment plant process flow diagram creation method based on Revit, comprising: step 1, on the basis of existing plant Revit three-dimensional model, create the section of each process unit;Step 2, create process flow chart in Revit software, and adjust the position of the section of each process unit according to process flow order;Step 3, define different types of detail drawing line and draw process flow line with it;Step 4, add annotation information and export two-dimensional drawing. The above steps improve the drawing efficiency of process flow diagram.