15 results about "Process flow diagram" patented technology

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 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.

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.

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.

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 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 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 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.

The application is suitable for the technical field of sewage treatment monitoring, and particularly relates to a sewage treatment real-time monitoring method and system.The method comprises the following steps: delimiting a real-time monitoring range of sewage treatment, finding a discharge source device, selecting an influence point, collecting video data by using a video monitoring device pre-installed at the discharge source device, and intercepting a state snapshot containing the influence point; drawing a process flow diagram of sewage treatment, setting sewage characteristics of each influence point, and creating disposal rules corresponding to the sewage characteristics one by one.The application can offset and compensate the pollutant concentration by comparing the pollutant concentration with the expected concentration, improve the accuracy of monitoring data, reduce the treatment risk, and ensure the effluent water quality, so as to accurately control the dosing process through early prediction and fine monitoring, ensure the stability of the effluent water quality, and improve the sewage treatment efficiency and sustainable management level.

The invention provides a data processing method and device based on a process flow diagram, and relates to the technical field of industrial automation design, and the method comprises the steps: obtaining a to-be-recognized process flow diagram; according to the expression form of the instrument symbols on the process flow diagram, the process flow diagram is identified, N instrument symbols and instrument information associated with each instrument symbol are obtained, the instrument information at least comprises instrument coordinates, instrument position numbers and subsidiary information, the expression form of the instrument symbol is any one of a circle, an arc, a line segment and a block; aiming at each instrument symbol in the N instrument symbols, generating a horizontal search zone and a vertical search zone by taking the instrument coordinate as a center, and screening out target information corresponding to the instrument symbol from the affiliated information according to the horizontal search zone and the vertical search zone; and generating a target information table corresponding to the process flow diagram according to the instrument coordinates, the instrument position numbers and the target information corresponding to the N instrument symbols.

This invention discloses a digital and intelligent dual-mode early warning method, device, server, and storage medium for petrochemical production, belonging to the field of early warning. It constructs a knowledge graph based on the process flow diagram and uses a graph embedding algorithm to encode the network topology relationships of measurement points into low-dimensional dense vectors. Simultaneously, the inherent attributes of the measurement points are encoded into category embedding vectors, and the two are combined to form a static feature set. During online operation, the dynamically acquired feature vectors are used as queries, and the static feature set is used as keys and values. After linear transformation through a learnable weight matrix, attention weights are calculated, and the value vectors are weighted and summed to obtain a context vector. Finally, the context vector, dynamic features, and static features are fused to generate a comprehensive feature vector, which is input into the early warning model to output the final early warning result. This provides the model with richer and more accurate input features, thereby improving the prediction accuracy and robustness of the early warning model.

The invention discloses a process flow diagram generation method, a related device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the conversion based on a character string sequence describing a target process, and obtaining an initial flow diagram; constructing a target constraint based on property parameters of a flow chart target in the initial flow chart; obtaining a candidate action set based on the target constraint; selecting at least one candidate action as a target action based on the selection probability of each candidate action predicted by the state parameters of the initial flow chart; and executing the target action based on the initial flow chart to obtain a process flow chart of the target process. According to the scheme, the engineering availability of mapping from symbolic expression to the process flow diagram can be improved.

The invention discloses an environmental impact assessment method for a carbon capture technology after combustion of a coal-fired power plant, and particularly relates to a low-carbon energy technology, comprising the following steps: S1, system boundary characterization: on the basis of physical layout and process flow diagrams of the coal-fired power plant and a carbon capture system, determining a system boundary; an evaluation object is divided into five key function units including power generation, carbon capture, pollutant cooperative control, waste treatment and resource consumption, an independent data anchor point is established for each unit by introducing a virtual grid coding technology, a digital mapping model is constructed, and a structured space framework is provided; according to the method, a five-dimensional index system of power generation, carbon capture, pollutant cooperative control, waste treatment and resource consumption is constructed, and a nonlinear coupling model among the influence coefficients of all dimensions is established, so that the environmental influence of the carbon capture system is comprehensively evaluated, the limitation of traditional single carbon emission reduction evaluation is broken through, and the evaluation efficiency is improved. And evaluation conversion from single environmental benefit to comprehensive environmental performance is achieved.

The application discloses an AI intelligent agent-based intelligent management and control method and system for a crude oil unit, relates to the field of petroleum chemical industry, and comprises the following steps: constructing a high-fidelity digital twin virtual model by using a process flow diagram, a pipeline instrument flow diagram and historical operation data of the crude oil unit, defining and initializing micro intelligent agents according to a process control loop division principle; performing offline parallel training on the micro intelligent agents in the high-fidelity digital twin virtual model, collecting time series data, using a causal discovery algorithm, constructing a causal correlation graph of the crude oil unit, and calculating the dynamic correlation strength between the behavior data of the micro intelligent agents. Through the decision guidance of the intelligent agent grouping based on the dynamic correlation strength and the causal contribution calculation, the application realizes the deep coupling of the global optimization target and the local control, and overcomes the problem of insufficient long-term self-adaptive ability caused by the lack of causal reasoning in the traditional method.