Digital twinning-based electromechanical equipment visual simulation system

Abstract

The invention relates to the technical field of electromechanical equipment data visualization, in particular to an electromechanical equipment visualization simulation system based on digital twinning, which comprises an initial node mapping module, a state active extraction module, a state active extraction module, a state active extraction module and a state active extraction module, a jump interval identification module obtains a mapping table according to traffic trajectory turning classification, a graph domain expansion scheduling module positions graph boundaries to obtain a rendering set, and a device evolution graph set output module arranges layered graphs in sequence to form a continuous evolution sequence and obtain a simulation result. According to the method, contour and direction correlation analysis is introduced, measuring point space-time positions are uniformly arranged, a continuous track corresponding relation is established, change concentration sections are identified to strengthen abnormity and turning depiction, track jump and graph boundary cooperative scheduling is combined, key change areas are orderly presented, and a continuous image sequence based on an evolution relation is constructed. And the state evolution readability, continuity and positioning precision are effectively improved.

Description

Technical Field

[0001] This invention relates to the field of electromechanical equipment data visualization technology, and in particular to an electromechanical equipment visualization simulation system based on digital twins. Background Technology

[0002] The field of electromechanical equipment data visualization technology encompasses the acquisition, processing, and graphical display of data generated during the real-time operation of electromechanical equipment. The core of this technology involves the real-time acquisition, structured processing, and graphical modeling of the large amounts of dynamic data generated during equipment operation, forming an interactive and perceptible visualization interface. This primarily includes multi-dimensional classification of operational data, dynamic analysis of time-series data, real-time correlation of spatial parameters, and intuitive presentation of equipment status through a graphics engine. The field adopts a data-driven approach, mapping real-time operational data to graphical models and continuously updating them to achieve a dynamic and visual presentation of equipment operating status. This transforms data from abstract forms into intuitive images, thereby improving the efficiency and responsiveness in understanding equipment operating status. Among them, the digital twin-based electromechanical equipment visualization simulation system refers to the construction of a digital model that is consistent with the actual electromechanical equipment structure, function and operation behavior, and the dynamic mapping and visual modeling of the real-time operation data of the equipment. The main technical issues it addresses include using sensor components to collect key data of the equipment in real time during operation, such as parameters such as temperature, pressure, speed and current. The collected data is transmitted to the computing platform through a data interface protocol. In the platform, the data is restructured and simulated according to physical laws and operating logic. The data results are synchronously mapped into dynamic model shape changes in three-dimensional space using graphical modeling methods. The data is then rendered and displayed through a visualization graphics engine, so that the digital model can be continuously updated and displayed as the actual data changes. By combining digital modeling, physical simulation and graphics rendering methods in a real-time data-driven manner, a data visualization simulation system that can sustainably reflect the equipment operation process is constructed. Existing technologies focus on the overall mapping of real-time data to digital models, typically using a unified timeline to drive graphical updates. In scenarios with long operating paths or complex distribution of measurement points, it is difficult to distinguish the order of data from different locations and correlate them into segments. When the operating status changes frequently in a local area, the graphical display mainly reflects the overall parameter fluctuations, lacking clear identification of the areas where changes are concentrated. This can easily lead to unclear spatial positioning of critical states. For example, when the local operating conditions of the equipment change abruptly, it is difficult to quickly correlate the relevant areas in the graph with the source of the change, thus affecting the efficiency of judging and handling operational details. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of existing technologies and propose a digital twin-based visualization simulation system for electromechanical equipment. To achieve the above objectives, the present invention adopts the following technical solution: a digital twin-based visual simulation system for electromechanical equipment, the system comprising: The initial node mapping module acquires the changes in the external contour of the equipment and determines the direction of operation. It collects the positions of temperature measurement points, voltage sampling points and flow sensing points, maps each measurement point to the operating section of the electromechanical equipment, calibrates them in sequence, and forms a set of edge measurement point sorting results. The active state extraction module, based on the arrangement order of each measuring point in the edge measuring point sorting result set and the relationship with the running section, identifies the change direction of each measuring point in segments, analyzes the continuous and switching characteristics within the same section, distinguishes and marks the running sections where changes occur in a concentrated manner, and forms a set of regions where measuring point changes are concentrated. The jump interval identification module, based on the concentrated operation section identifier of the concentrated area of ​​the measurement point change, selects the corresponding flow sensing point number and obtains the trajectory change sequence, identifies the trajectory direction, determines the jump operation section at the change turning point, and forms a jump number classification mapping table. The image domain expansion scheduling module, based on the jump operation segment position and flow sensing point number in the jump number classification mapping table, locates the corresponding outline graphic position of the jump operation segment, extracts the expanded view graphic boundary and determines the coverage position, includes it in the rendering scheduling range and divides it sequentially to obtain the image rendering scheduling boundary set. As a further embodiment of the present invention, the edge measurement point sorting result set includes measurement point sequence number, operating section positioning label, and measurement point type identification information; the measurement point change concentration area set includes change trend clustering section identifier, continuous change pattern characteristics, and measurement point association label within the section; the jump number classification mapping table includes jump section number, flow sensing point association number, and classification index identifier; and the image rendering scheduling boundary set includes graphic boundary position parameters, rendering section division label, and map domain mapping sequence number. As a further embodiment of the present invention, the initial node mapping module includes a contour direction recognition submodule, a measurement point segment assignment submodule, and a measurement point sequence calibration submodule; The contour direction recognition submodule acquires information on the external contour changes during the operation of electromechanical equipment, monitors the trend of contour edge shape changes in the equipment under continuous operation, performs direction recognition based on the extension sequence of contour changes on the running path, determines the running direction for the electromechanical equipment to be deployed under operation, and generates a running deployment direction identifier. The measuring point section attribution submodule, based on the operation deployment direction identifier, collects the location distribution information of temperature measuring points, voltage sampling points and flow sensing points distributed in the operating area of ​​electromechanical equipment, and makes section division judgment according to the relative position order of each measuring point on the operating path, and assigns different types of measuring points to specific operating sections, generating a measuring point section correspondence table. The measurement point sequence calibration submodule, based on the measurement point segment correspondence table, sequentially calibrates the appearance order of measurement points along the running unfolding direction within each running segment, organizes the arrangement relationship of different types of measurement points in the running trajectory, establishes a clear position correspondence relationship in the running unfolding view, and obtains the edge line measurement point sorting result set. As a further embodiment of the present invention, the active state extraction module includes a change direction recognition submodule, a continuous feature extraction submodule, and a concentrated behavior segment recognition submodule; The change direction recognition submodule, based on the edge measurement point sorting result set, calls the arrangement order of the measurement points in the running section, and performs segmented recognition of the change direction of temperature measurement points, voltage sampling points and flow sensing points in the continuous running process. It judges the direction based on the change trend of the measurement points at each time node and generates a sequence of measurement point change directions. The continuous feature extraction submodule compares the changing directions of the measuring points in each operating segment according to the sequence of changing directions of the measuring points, identifies the continuous state of the direction in the continuous segment and the position where the direction changes, filters the distribution segments of measuring points with direction switching, and obtains the set of changing direction switching positions. The concentrated behavior section identification submodule calls the set of change direction switching locations to identify the distribution between adjacent operating sections, classifies and statistically analyzes the frequency of direction switching phenomena, selects the operating section number corresponding to the concentrated change area based on the density of distribution, and establishes a set of concentrated change areas for measuring points. As a further embodiment of the present invention, the jump interval identification module includes a sensing point extraction submodule, a trajectory turning point identification submodule, and a jump segment classification submodule; The sensing point extraction submodule, based on the clearly defined operating section identifier of the concentrated area set of measurement point changes, selects the flow sensing point number in the corresponding operating section, collects the position record sequence of each sensing point in the continuous operation process, organizes the position data of each sensing point in the order of operating time, and establishes a set of sensing point trajectory sequences. The trajectory turning identification submodule identifies the direction of trajectory change of each flow sensing point during continuous operation based on the set of sensing point trajectory sequences, filters the locations where the trajectory direction changes abruptly, determines the operating segment number to which the turning position belongs, obtains the range of operating positions where the trajectory turning occurs, and obtains the set of trajectory turning segments. The jump segment classification submodule calls the set of trajectory turning segments, combines the sensing point number information in each turning segment, establishes an attribution correspondence between the running segment that exhibits jump behavior and the corresponding flow sensing point, integrates the number information and segment location according to the attribution relationship, and generates a jump number classification mapping table. As a further embodiment of the present invention, the map domain expansion scheduling module includes a map position positioning submodule, a boundary range extraction submodule, and a rendering segment division submodule; The graphic location positioning submodule, based on the relationship between the jump operation segment position marked in the jump number classification mapping table and the corresponding flow sensing point number, obtains the contour graphic identification information corresponding to each segment in the operation unfolded map domain, detects the graphic position matching result of the jump operation segment in the map domain, and obtains the index corresponding to the contour position. The boundary range extraction submodule extracts the contour boundary annotations corresponding to each jump running segment in the unfolded map domain according to the contour position index, identifies the start and end positions of the boundary coverage in the running unfolding direction, confirms the graphic range of the contour segment associated with the jump behavior, and establishes a set of graphic coverage boundaries. The rendering segment division submodule calls the graphic coverage boundary set, groups the graphic boundaries sequentially according to the running unfolding direction, performs scheduling partitioning based on the connection order of the contour graphics covered by each group of boundaries, extracts the corresponding contour segments and assigns them to the rendering layout range, and generates an image rendering scheduling boundary set. As a further aspect of the present invention, the system further includes: The equipment evolution atlas output module extracts the associated graphic fragments of temperature measurement points, voltage sampling points and flow sensing points within the rendering scheduling boundary range based on the rendering scheduling boundary range in the image rendering scheduling boundary set. The fragments are then arranged hierarchically according to the direction of electromechanical equipment operation and the type of measurement points to obtain the electromechanical equipment simulation results. The simulation results of the electromechanical equipment include a set of graphic fragment sequences, a hierarchical structure of measurement point types, and information on the order of evolution. As a further aspect of the present invention, the device evolution atlas output module includes a graphic fragment extraction submodule, a fragment order arrangement submodule, and an evolution atlas generation submodule; The graphic fragment extraction submodule extracts the associated graphic information of temperature measurement points, voltage sampling points and flow sensing points within the corresponding boundary range based on the determined rendering scheduling boundary range in the image rendering scheduling boundary set. It identifies the corresponding graphic position of each measurement point in the outline unfolded view, organizes them into a set of graphic units that can be called independently, and obtains a set of graphic fragments of measurement points. The segment sequence arrangement submodule, based on the set of measurement point graphic segments, determines the sequence of graphic segments of different measurement point types according to the direction of operation of the electromechanical equipment, divides the graphic segments within the same operating contour level into hierarchical divisions according to the measurement point type, and arranges the corresponding graphic segments in sequence according to the direction of operation to obtain the graphic segment arrangement sequence. The evolution atlas generation submodule calls the graphic fragment arrangement sequence, combines and associates the continuously arranged graphic fragments, maintains the consistency of the running contour hierarchy, integrates the graphic content arranged along the unfolding direction, forms a continuously unfolded graphic output result, and generates the electromechanical equipment simulation result. As a further aspect of the present invention, the process of extracting the associated graphical information of temperature measuring points, voltage sampling points, and flow sensing points within the corresponding boundary range specifically involves: For each rendering scheduling boundary range in the image rendering scheduling boundary set, the corresponding graphic boundary range is cropped. Boundary constraints and element deduplication are performed on the cropped graphic content. The graphic information associated with temperature measurement points, voltage sampling points and flow sensing points are merged into the corresponding cropping results. The process of identifying the corresponding graphic position of each measuring point in the unfolded contour view is as follows: A measurement point location index is established based on the relative positional relationship between graphic markers and contour line segments, and the measurement point location index is written into the independently callable set of graphic units to form the set of measurement point graphic segments. As a further aspect of the present invention, the process of arranging the corresponding graphic segments sequentially according to the unfolding direction specifically includes: The measurement point location indexes are sorted by directional projection according to the operating direction of the electromechanical equipment. Within the same operating contour level, the graphic segments corresponding to temperature measurement points, voltage sampling points, and flow sensing points are formed into continuous sequences. These continuous sequences are then combined and associated in a fixed hierarchical order to obtain the continuously unfolded graphic output result. Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, by introducing correlation analysis between the running contour and the unfolding direction, the spatial position and temporal sequence of multiple types of measuring points in the running path are uniformly arranged, so that the changes of measuring points can form a clear correspondence in the continuous trajectory. Furthermore, the concentrated distribution of the change direction is segmented to enhance the ability to depict local anomalies and turning behaviors. At the same time, by combining the coordinated scheduling of trajectory jump positions and graphic boundaries, the key change areas are presented in an orderly manner in the unfolded view. Then, in the graphic output stage, a continuous image sequence based on the change evolution relationship is constructed, so that the state evolution during the running process has stronger readability, coherence and positioning accuracy. Attached Figure Description Figure 1 This is a system flowchart of the present invention; Figure 2 This is a flowchart illustrating the acquisition process of the initial node mapping module in this invention. Figure 3 This is a flowchart illustrating the acquisition process of the active status extraction module of the present invention. Figure 4 This is a flowchart illustrating the acquisition process of the jump interval identification module of the present invention. Figure 5 This is a flowchart illustrating the acquisition process of the graph domain expansion scheduling module of the present invention. Figure 6 This is a flowchart illustrating the acquisition process of the device evolution atlas output module of the present invention. Detailed Implementation The technical solution of the present invention will now be described with reference to the accompanying drawings. In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one. In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same. To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments. Please see Figure 1 This invention provides a technical solution: a digital twin-based visual simulation system for electromechanical equipment, the system comprising: The initial node mapping module acquires information on the external contour changes of electromechanical equipment during operation, clarifies the operating direction of the electromechanical equipment for deployment in the operating state, collects the location distribution information of temperature measuring points, voltage sampling points, and flow sensing points distributed in the operating area of ​​the electromechanical equipment, and assigns each measuring point to a specific operating section according to the spatial distribution of the temperature measuring points, voltage sampling points, and flow sensing points on the equipment's operating path. The module also performs sequential labeling according to the order in which each measuring point appears along the operating trajectory, so that various measuring points form a clear positional correspondence in the operating deployment view, and obtains the edge line measuring point sorting result set. The active status extraction module, based on the order of measurement points in the edge measurement point sorting result set and the correspondence with the operating section, identifies the changing direction of temperature measurement points, voltage sampling points, and flow sensing points during the continuous operation of electromechanical equipment. Within the same operating section, it compares and analyzes the continuity and switching characteristics of the changing direction of each measurement point. Based on the distribution characteristics of repeated changing directions in adjacent operating sections, it distinguishes and processes operating sections where the changing behavior is concentrated, and clarifies the operating section identifier corresponding to each concentrated area of ​​change, forming a set of concentrated measurement point changing areas. The jump interval identification module, based on the clearly defined operating section identifiers of the concentrated area set of measurement point changes, selects the corresponding flow sensing point number in each operating section, obtains the trajectory change sequence of the flow sensing point during the operation of the electromechanical equipment, identifies the trajectory change direction of the flow sensing point along the operating sequence, determines the corresponding operating section at the position of change and identifies the operating section as the jump operating section, and classifies it according to the correspondence between the jump operating section position and the flow sensing point number to form a jump number classification mapping table; The image domain expansion scheduling module, based on the relationship between the position of the jump operation segment and the corresponding flow sensing point number in the jump number classification mapping table, locates the graphic position of the electromechanical equipment outline segment corresponding to the jump operation segment in the operation expansion image domain, extracts the graphic boundary range of the outline segment in the expansion view, determines the coverage position of the graphic boundary in the operation expansion direction, includes the graphic range corresponding to the outline segment that has jump behavior into the rendering scheduling range, and divides the graphic boundary range in order according to the operation expansion direction to obtain the image rendering scheduling boundary set; The equipment evolution atlas output module extracts the corresponding graphic fragments associated with temperature measurement points, voltage sampling points, and flow sensing points within the defined rendering scheduling boundary range in the image rendering scheduling boundary set. The graphic fragments of different measurement point types are arranged sequentially according to the direction of equipment operation. Within the same operating contour level, the graphic fragments are hierarchically divided according to measurement point type and arranged sequentially along the direction of equipment operation. This allows different changing characteristics during equipment operation to form a continuous evolution sequence in the unfolded graphics, thus obtaining the simulation results of the equipment. The edge measurement point sorting result set includes measurement point sequence number, operating section location label, and measurement point type identification information. The measurement point change concentration area set includes change trend cluster section identifier, continuous change pattern characteristics, and measurement point association label within the section. The jump number classification mapping table includes jump section number, flow sensing point association number, and classification index identifier. The image rendering scheduling boundary set includes graphic boundary position parameters, rendering section division label, and map domain mapping sequence number. The electromechanical equipment simulation results include graphic segment sequence set, measurement point type hierarchical structure, and evolution order arrangement information. Please see Figure 2 The initial node mapping module includes a contour direction recognition submodule, a measurement point segment assignment submodule, and a measurement point sequence calibration submodule. The contour direction recognition submodule acquires information on the external contour changes during the operation of electromechanical equipment, monitors the trend of contour edge shape changes in the equipment under continuous operation, performs direction recognition based on the extension sequence of contour changes on the running path, determines the running direction for the electromechanical equipment to be deployed under operation, and generates a running deployment direction identifier. To acquire information on the external contour changes of electromechanical equipment during operation, a high-precision industrial-grade 3D laser scanner (such as the Faro Focus series) or structured light camera is used to collect point cloud data of the equipment's surface in real time. A 3D mesh model of the equipment is then established in a digital twin simulation environment. The coordinate data of each vertex constituting the external contour of the model is read, and a sampling frequency of 50 frames per second is set to capture minute deformations. The current frame is then obtained. Set of vertex coordinates at time Compared to the previous frame Set of vertex coordinates at time The coordinate unit is millimeters (mm). The coordinate difference is calculated for vertices with the same index in the set to obtain the instantaneous displacement vector of each vertex. The micro-motion filtering threshold was set to 0.5 mm to screen out mold lengths. Displacement vectors greater than 0.5 mm are used as effective deformation data, and the effective displacement vectors are statistically analyzed on the three-dimensional coordinate axes. , , The sum of the projected components on, if on The sum of the projection components along the positive axis is greater than negative axis direction, and shaft and If the sum of the two-way projection components of the axis is 1.5 times, then the main deformation trend of the contour is determined to be along... Extending along the positive axis, the origin is selected from the preset geometric center point in the digital twin model of the electromechanical equipment, and the axis extends along the defined direction. A virtual ray is constructed along the positive axis as the baseline for the running path. Taking a large rotating electric motor as an example, its rotor profile deforms under the action of thermal expansion and centrifugal force. Calculations show that the apex of its profile mainly extends towards the rear end of the axial direction. In the negative axis direction, the unit vector determined by this direction is used as the reference vector. All effective displacement vectors are traversed, and the cosine value of the angle between each vector and the reference vector is calculated. Random deformation points with a cosine value less than 0.8 are eliminated, and contour change points that are in the same direction as the reference vector are retained. The change points are arranged in ascending order according to the magnitude of their projected coordinate values ​​on the reference line. The point with the smallest projected coordinate is defined as the unfolding start end, and the point with the largest projected coordinate is defined as the unfolding end end. The start end and the end end are connected to form a vector line segment with a clear direction, generating an unfolding direction identifier. The measurement point section assignment submodule collects the location distribution information of temperature measurement points, voltage sampling points and flow sensing points distributed in the operating area of ​​electromechanical equipment based on the operation direction identifier. It then divides the measurement points into sections according to their relative positions on the operating path, assigns different types of measurement points to specific operating sections, and generates a measurement point section correspondence table. Based on the direction of deployment, virtual entity objects of temperature measurement points (data from patch PT100 temperature sensor), voltage sampling points (data from Hall voltage sensor), and flow sensing points (data from ultrasonic flow meter) are loaded into the digital twin mapping space, and the three-dimensional coordinate values ​​of each measurement point object in the world coordinate system of the twin scene are read. The unit is millimeters. The vector line segment corresponding to the running unfolding direction marker generated in the previous steps is used to obtain the total length of that line segment. For example, for a conveyor with a total length of 2000 mm, the total length of its running path The setting is 2000 mm, and the granularity benchmark for segment division is set to 100 mm. This is achieved through calculation. (Rounding up) Divide the entire running path into 20 consecutive numerical intervals, that is... For each acquired measurement point coordinate, calculate its perpendicular projection point on the vector segment of the running unfolding direction, and solve for the Euclidean distance between the projection point and the starting point of the running path. For example, a certain temperature measuring point The projection distance on the path is 450 mm from the starting point, at a certain voltage sampling point. The projection distance is 455 mm, at a certain flow sensing point. The projected distance is 1205 mm. The calculated distance value... Compare with each numerical range to determine millimeters and Millimeters all fell in This section, namely the 5th operating segment, and millimeters fall In this interval, namely the 13th operating segment, for measuring points whose distance value is exactly equal to the interval boundary value, such as measuring points with a distance of 500 mm, they are uniformly assigned to the next adjacent segment, namely the 6th segment, according to the "left closed, right open" principle. The above calculation and comparison operations are completed by traversing all measuring points. A key-value pair index is established between the unique identification code (ID) of the measuring point and the segment number it falls into, for example, {Section_05:[T1,V1],Section_13:[F1]}. It is checked whether each segment contains measuring points of the preset type. If there is no measuring point data in a certain segment, it is marked as an empty set. Finally, all non-empty segments and the list of measuring points contained therein are structurally integrated to generate a measuring point segment correspondence table. The measurement point sequence calibration submodule, based on the measurement point segment correspondence table, calibrates the measurement points in each running segment in the order of their appearance along the running unfolding direction, organizes the arrangement relationship of different types of measurement points in the running trajectory, establishes a clear position correspondence in the running unfolding view, and obtains the edge line measurement point sorting result set; Based on the correspondence table of measurement point sections, extract a list of all measurement point objects contained in each non-empty operation section. Taking the 5th operation section as an example, this section contains temperature measurement points. (Projection distance 450 mm), voltage sampling point (Projection distance 455 mm) and newly added temperature measuring points (Projection distance 420 mm) The projected distance values ​​of these measuring points on the running path are read as sorting weights. Pairwise comparisons are performed on the measuring points within the same section. and ,because Therefore Ranked Previously, compared and ,because Therefore Ranked Previously, through multiple rounds of numerical comparison and location exchange, the absolute physical order of the measuring points within this section was established as follows: For different types of measuring points, specific type priority coefficients are assigned, with temperature set to 1, voltage to 2, and flow rate to 3. When the absolute value of the difference between the projected distance values ​​of two measuring points is less than 1 mm, i.e. If the two are determined to be physically overlapping, then a secondary sort is performed based on the type priority coefficient, with smaller coefficients ranked higher. For example, if... and If the distance between the temperature measuring points is 450 mm, then... Arranged at voltage sampling points Previously, after sorting within a single segment, the sorted measurement point sequences within each segment were sequentially concatenated according to the segment numbers in ascending order (e.g., segment 1, segment 2... segment 20) to construct a global measurement point linked list that runs through the entire equipment operating path. Each measurement point in the linked list was assigned a global sequence number starting from 1 and incrementing, for example... Marked as Seq_001, Marked as Seq_002, Marked as Seq_003, and so on until all measuring points along the 2000 mm long path are covered. The global sequence number, physical coordinates, segment to which they belong, and type attributes of each measuring point are encapsulated into a unified data structure to obtain the sorted result set of edge line measuring points. Please see Figure 3 The active state extraction module includes a change direction recognition submodule, a continuous feature extraction submodule, and a concentrated behavior segment recognition submodule; The change direction recognition submodule, based on the edge line measurement point sorting result set, calls the arrangement order of the measurement points in the running section, and performs segmented recognition of the change direction of temperature measurement points, voltage sampling points and flow sensing points in the continuous operation process. It judges the direction based on the change trend of the measurement points at each time node and generates a sequence of measurement point change directions. Based on the edge measurement point sorting result set, the digital twin simulation engine extracts each sorted measurement point object and obtains its associated historical operation data stream from the field PLC via OPCUA or MQTT protocol. For each measurement point, the data sequence of the 10 sampling points preceding the current simulation frame is extracted. For example, for the temperature measurement point numbered Seq_005 in the sorting result set, its temperature reading sequence within the last 10 seconds is extracted. (Unit: degrees Celsius) Calculate the first difference for each pair of adjacent data points in the sequence. Statistical sequence positive difference value quantity negative difference quantity ,like If the local change trend of the measuring point within the current time window is determined to be "increasing", the direction value is marked as "increasing". ,like If it is, it is determined to be "descending", and the direction value is marked as "descending". If neither of these values ​​reaches 8, the condition is classified as "stable" or "fluctuating," and the direction value is marked as [value missing]. Similarly, the above calculation is performed on all measuring points (including temperature, voltage, and flow rate) in the sorting result set. This process iterates through all measuring points along the entire operating path, arranging the calculated direction marker values ​​for each measuring point according to their order in the sorting result set. For the three measuring points located in the 5th operating segment... If the calculated direction values ​​are respectively Then the local directional subsequence corresponding to this segment is After all measurement points have been processed, these local direction markers are sequentially spliced ​​together to form an integer array with the same length as the edge measurement point sorting result set. Each element in the array corresponds to the dynamic change state of the measurement point in the physical space at the current moment, generating a sequence of measurement point change directions. The continuous feature extraction submodule compares the changing directions of the measuring points in each operating segment according to the sequence of changing directions of the measuring points, identifies the continuous state of the direction in the continuous segment and the position where the direction changes, filters the distribution segments of measuring points with direction switching, and obtains the set of changing direction switching positions. Based on the sequence of changes in the measuring point direction, traverse each element in the sequence and its adjacent elements on the running path, setting a sliding window size of 3, that is, taking the direction values ​​of three consecutive measuring points each time. Compare the three values ​​in the window to see if they are completely identical. If the small segment is determined to be in a "continuously rising" state, the switching point is not recorded. If the value in the window changes abruptly, for example, if the sequence segment is... Index detected and There exists a... arrive The value range transition is used to identify the location as a direction reversal point, and the global index number of the measurement point where the jump occurs is recorded. Using this as the starting point for switching, continue sliding the window backward; if the subsequent sequence changes... If this confirms that the inverted state has stabilized, then the index... and its associated physical coordinates Store in a temporary buffer. For each operating segment, count the number of all direction switching points contained within it. Taking the 13th operating segment as an example, if the flow value detected in the flow sensing point sequence within this segment changes from "stable" (… ) turned into "surge" ( ), and the voltage sampling point data changed from "stable" ( ) turned into "decline" ( If two direction switching events occur within the segment, the original numbers of these two switching points in the edge measurement point sorting result set are extracted, such as Seq_105 and Seq_106. Combined with their respective segment IDs, a structured record is constructed containing the coordinates of the switching point, the state value before the switch, the state value after the switch, and the associated measurement point ID. Records with a state value change magnitude greater than or equal to (i.e., from...) are then selected. Change , or from Change Wait, exclude Change The distribution segment of the measurement points (invalid cases) is used to obtain the set of positions for changing direction. The concentrated behavior section identification submodule calls the change direction switching location set to identify the distribution between adjacent operating sections, classifies and statistically analyzes the frequency of direction switching phenomena, selects the operating section number corresponding to the concentrated change area based on the density of distribution, and establishes a set of concentrated change areas for measuring points. Call the change direction switching position set, read all the switching point records stored in it, extract the running segment number to which each switching point belongs, and create a counter array with a length equal to the total number of running segments (e.g., 20 segments). The initial values ​​are all 0. Iterate through each record in the location set. If a certain switching point belongs to the first record, it will be considered as the first record. If there are multiple sections, then execute... After completing the traversal, the frequency distribution of direction switching in each segment is obtained, for example... The frequency of segment 4 is 5, and the frequency of segment 13 is 8. Calculate the non-zero mean of the entire counter array. and standard deviation Set a dense detection threshold Assuming the calculation yields ,but Set the counter array values ​​greater than The segments were identified as high-frequency switching zones, namely segments 4 and 13. For these selected high-frequency segments, their spatial adjacency was checked. If the sum of the frequencies of segments 4 and 5 (assuming segment 5 has a frequency of 2, which is not exceeding the threshold but is adjacent to the high-frequency zone) is greater than the threshold calculated separately, then... Then, the 4th and 5th sections are merged and regarded as an extended change concentration area. For the 13th section, if the frequency of its adjacent sections is 0, it is marked as an isolated change concentration area. A unique area identifier (Area_ID) is assigned to each determined concentration area. For example, Area_A corresponds to the 4th and 5th sections, and Area_B corresponds to the 13th section. A mapping index is established between these area identifiers and the corresponding physical operation section numbers (Section_04, Section_05, Section_13) to establish a set of measurement point change concentration areas. Please see Figure 4 The jump interval identification module includes a sensor point extraction submodule, a trajectory turning identification submodule, and a jump segment classification submodule; The sensor point extraction submodule, based on the clearly defined operating section identifier of the concentrated area set of measurement point changes, selects the flow sensor point number in the corresponding operating section, collects the position record sequence of each sensor point in the continuous operation process, organizes the position data of each sensor point in the order of operation time, and establishes a sensor point trajectory sequence set. Based on the clearly defined operating segment identifiers of the concentrated area set of measurement point changes, a structured query is performed in the digital twin database, using the segment ID of each segment in the concentrated area set as the search key. For example, Area_A corresponds to Section_04 and Section_05. From the measurement point segment correspondence table, all device object numbers marked as "flow sensing points" within these two segments are extracted. Assuming a set of sensing point numbers is extracted... For each number in the set, it connects to the corresponding digital twin virtual entity and reads its historical displacement data log for the most recent complete operating cycle (data sourced from the built-in MEMS inertial measurement unit (IMU) or visual tracking system). The data sampling frequency is 100Hz. Each record in the log is parsed to extract the timestamp. with three-dimensional spatial coordinates The tuples are used to perform time-series processing on the extracted raw location data, arranging them in ascending order of timestamps. For example, for sensing points... , sort out the sequence ,in Set the time step for the total number of samples. For 0.01 seconds, check the sequence for time breaks. If any are found... Then, a linear interpolation algorithm is used to fill in the missing intermediate coordinate points to ensure the continuity of the trajectory. For each sensing point, a complete and continuous spatiotemporal trajectory linked list is generated, for example... Corresponding to Trajectory_04a, For Trajectory_05a, all processed trajectory lists and their corresponding sensor point numbers are encapsulated to establish a sensor point trajectory sequence set. The trajectory turning recognition submodule identifies the direction of trajectory change of each flow sensing point during continuous operation based on the trajectory sequence set of sensing points, filters the locations where the trajectory direction changes abruptly, determines the operating segment number to which the turning position belongs, obtains the range of operating positions where the trajectory turning occurs, and obtains the set of trajectory turning segments. Based on the set of sensor point trajectory sequences, the coordinate point data of each trajectory linked list is read one by one, and the trajectory direction vector is defined. For the current point Point to the next point The unit vector, i.e. Calculate the angle between two adjacent direction vectors. Set the threshold for angle mutation Given a radius of 30 degrees (approximately 0.52 radians), traverse the entire trajectory and calculate the value of each node. Value, if a certain point is detected For example, at time If the angle is calculated to be 45 degrees, then this point is determined to be a point of abrupt change in trajectory direction, and the timestamp of this abrupt change point is recorded. and their corresponding spatial coordinates , the coordinates Project the image backwards onto the baseline of the running path established in the previous steps, and calculate the projection distance. Using this projected distance, the corresponding operating segment number can be found in the measurement point segment correspondence table. For example, the projected distance... Millimeters, falling Within the interval, the turning point is determined to belong to the 5th operating segment (Section_05). For multiple consecutive abrupt changes occurring at the same sensing point within a short period of time (e.g., within 0.5 seconds), the one that occurs is selected. The point with the largest value is used as the representative point for this jump behavior to eliminate jitter noise. The abrupt change judgment results of all sensing points are statistically analyzed. If no abrupt change point is detected within a certain operating segment, it is marked as a "stable segment" and skipped. If it contains at least one valid abrupt change point, it is marked as a "jump segment," and the corresponding abrupt change coordinate range is set as follows: to By associating the segment ID with the segment ID, we obtain a set of trajectory turning segments. The jump segment classification submodule calls the trajectory turning segment set, combines the sensor point number information in each turning segment, establishes the attribution correspondence between the running segment that exhibits jump behavior and the corresponding flow sensor point, integrates the number information and segment location according to the attribution relationship, and generates a jump number classification mapping table. The system retrieves the set of trajectory turning segments, reads the ID of each transition segment and its corresponding abrupt change coordinate range, iterates through the set, and extracts the flow sensing point numbers associated with each transition segment. For example, for the transition segment Section_05, the system queries to find the sensing points where the trajectory turning occurs. Construct an empty hash map table, using the running section ID as the key and a list containing sensor point numbers and mutation type descriptions as values. Fill the extracted information into the table, in the format {Section_05:[{Sensor_ID:F5a,Jump_Type:"Angle_45_Deg"}]}. If multiple sensor points within the same section experience jumps, for example, within Section_04... and If both transitions occur, their information is appended to the list corresponding to that section, forming {Section_04:[{Sensor_ID:F4a...},{Sensor_ID:F4b...}]}. For entries already existing in the mapping table, they are internally sorted according to the alphabetical order of the sensor point numbers to ensure data structure consistency. Simultaneously, the range of transition coordinates recorded in each entry is... (like This is stored as an additional attribute for subsequent visualization and positioning. Finally, the integrity of the mapping table is checked, empty key-value pairs without any sensor point data are removed, all non-empty entries are integrated, and a jump number classification mapping table is generated. Please see Figure 5 The map domain expansion scheduling module includes a map location positioning submodule, a boundary range extraction submodule, and a rendering segment division submodule; The graphic location positioning submodule obtains the outline graphic identification information corresponding to each segment in the operation unfolded map domain based on the relationship between the jump operation segment position marked in the jump number classification mapping table and the corresponding flow sensing point number, detects the graphic position matching result of the jump operation segment in the map domain, and obtains the outline position corresponding index. Based on the relationship between the jump operation segment locations marked in the jump number classification mapping table and the corresponding flow sensing point numbers, the two-dimensional panoramic unfolded layer of the electromechanical equipment is loaded in the visualization rendering engine of the digital twin system. The metadata of all predefined graphic elements in this layer is read. The metadata includes the vector graphic ID (Graphic_ID) corresponding to each operation segment and its pixel coordinate range on the canvas. Each record in the mapping table is traversed to extract the jump segment number, for example, Section_05. Using this number as the index key, the matching graphic object is retrieved from the layer metadata. Assuming the search result shows that Section_05 corresponds to the vector polygon object Poly_05, the bounding box attribute of Poly_05 is read to obtain its top-left corner coordinates. and the coordinates of the bottom right corner The unit is pixels (px), for example to For the flow sensing points within the same segment recorded in the mapping table Calculate its relative position in the graphic coordinate system and call the coordinate transformation matrix. , sensor point physical coordinates Mapped to pixel coordinates in the graph domain The formula is Verify the calculated pixel coordinates Does it fall within the bounding box of Poly_05? If it does... and If the graphic position is successfully matched, the graphic ID, pixel boundary range, and the pixel coordinates of the included sensing points are encapsulated into a position index object, namely {Section_ID:Section_05,Graphic_ID:Poly_05,Bounds:[400,150,500,350]; Sensor_Pix:[450,200]} If the calculated pixel coordinates exceed the bounding box, the nearest neighbor matching algorithm is executed to classify them into the nearest bounding box and mark them as "overflow correction". The above retrieval, transformation and verification process is performed on all transition segments in the mapping table, and all generated position index objects are stored in a hash table structure to obtain the index corresponding to the contour position. The boundary range extraction submodule extracts the contour boundary annotations corresponding to each jump running segment in the unfolded map domain based on the corresponding index of the contour position, identifies the start and end positions of the boundary coverage in the running unfolding direction, confirms the graphic range of the contour segment associated with the jump behavior, and establishes a set of graphic coverage boundaries. Based on the index corresponding to the contour position, traverse each index object stored in the hash table and extract the pixel boundary range attribute (Bounds). Taking object Poly_05 as an example, its boundary range is... , Define the direction of the run and unfold in the corresponding area of ​​the graph. On the positive axis, identify the shape in Coverage start point on axis and the finish line To fully demonstrate the jump behavior, the coverage area is dynamically expanded by setting an expansion factor. (That is, extend the graphic width forward and backward by 20%), calculate the expanded display area. ; in Similarly for Boundary confirmation is performed along the axis to ensure that the height range covers the pixel coordinates of all relevant sensor points. If a certain jump behavior involves multiple consecutive segments (such as Section_04 and Section_05), the union of the boundaries of these segment graphics is calculated, i.e., the minimum of all relevant graphics is taken. and maximum Construct a merged rectangular bounding box, and generate a specific set of rectangular clipping box parameters for each independent transition event or continuous transition region. ,For example These clipping box parameters are bound to the corresponding transition event IDs, marked as the highlighted areas to be rendered, and a set of graphic coverage boundaries is established. The rendering segment division submodule calls the graphic coverage boundary set, groups the graphic boundaries sequentially according to the running unfolding direction, performs scheduling partitioning based on the connection order of the contour graphics covered by each group of boundaries, extracts the corresponding contour segments and assigns them to the rendering layout range, and generates the image rendering scheduling boundary set. Call the graphic coverage boundary set, read all the rectangular clipping box parameters contained therein, and then, based on each clipping box... Center point coordinates in the axial direction Center point coordinates in the axial direction Sort in ascending order, for example, if there are three cropping frames. The sorted order is as follows Check for overlap or insufficient spacing between adjacent cropping frames, and set a minimum spacing threshold. Pixels, calculate the number of adjacent cropping boxes and Spacing between ,like Then, the two clipping boxes will be merged into a larger rendering group, and the boundary parameters of the merged group will be updated. like To maintain their independence, each sorted and merged boundary group is defined as an independent rendering unit. Each unit is assigned a rendering priority, the priority value of which is determined by the number of transition points contained in the unit. The more transition points, the higher the priority. For example, a unit with 5 transition points is set to High priority, and a unit with 1 transition point is set to Normal priority. The original contour graphic fragment data corresponding to each rendering unit is extracted in sequence, including vertex arrays, texture coordinates and shader parameters. This data is packaged into the rendering queue, along with its target layout coordinates on the final output canvas, to generate an image rendering scheduling boundary set. Please see Figure 6 The equipment evolution atlas output module includes a graphic fragment extraction submodule, a fragment order arrangement submodule, and an evolution atlas generation submodule; The graphic fragment extraction submodule extracts the associated graphic information of temperature measurement points, voltage sampling points and flow sensing points within the corresponding boundary range based on the determined rendering scheduling boundary range in the image rendering scheduling boundary set. It identifies the corresponding graphic position of each measurement point in the contour unfolded view, organizes them into a set of graphic units that can be called independently, and obtains a set of graphic fragments of measurement points. The process of extracting the associated graphical information of temperature measurement points, voltage sampling points, and flow sensing points within the corresponding boundary range is as follows: For each rendering scheduling boundary range in the image rendering scheduling boundary set, the corresponding graphic boundary range is cropped. Boundary constraints and feature deduplication are performed on the cropped graphic content. The graphic information associated with temperature measurement points, voltage sampling points and flow sensing points are merged into the corresponding cropping results. The process of identifying the corresponding graphic position of each measuring point in the unfolded contour view is as follows: The measurement point location index is established based on the relative positional relationship between the graphic markers and the contour line segments, and the measurement point location index is written into a set of independently callable graphic units to form a set of measurement point graphic segments. Based on the defined rendering scheduling boundary ranges in the image rendering scheduling boundary set, GPU graphics clipping instructions (such as glScissor or Stencil Test) are invoked in the 3D scene of the digital twin, for each defined bounding box parameter. A 3D view frustum clipping space is constructed, and all types of measurement point data objects and their bound visual assets are extracted within this space. For temperature measurement points, a preset heatmap texture map is loaded, and the thermal gradient color data within the bounding box is extracted. For voltage sampling points, the corresponding waveform curve vector path is extracted, and the curve segment within the boundary is extracted. For flow sensing points, the current frame state data of their particle flow effect is extracted, and the set of particle coordinates within the boundary is extracted. Boundary constraint detection is performed to determine whether the extracted graphic elements overflow the clipping box. If a certain particle coordinate... satisfy or Remove it from the rendering list to prevent clipping. For static icons that may overlap in the same location, remove duplicates. Calculate the Euclidean distance between the center points of each icon; if the distance is less than 5 pixels, keep the highest-level icon and delete redundant copies. Iterate through each retained graphic element and calculate its local coordinates relative to the top-left corner of its bounding box. For example, the local coordinates of a certain temperature map are Calculate the perpendicular distance from the point to the nearest contour edge. ,like For each pixel, record the ID of the edge it is attached to, construct an index object containing {Local_Pos:(u,v),Edge_Ref:ID,Type:"Temp"}, encapsulate all processed graphics data packets and their position indices into independent renderable units, such as Unit_05_Temp, Unit_05_Volt, etc., and obtain a set of measurement point graphics fragments. The segment sequence arrangement submodule, based on the set of measurement point graphic segments and the direction of operation of electromechanical equipment, judges the order of graphic segments of different measurement point types, divides the graphic segments within the same operating contour level into hierarchical divisions according to measurement point type, and arranges the corresponding graphic segments in sequence according to the direction of operation to obtain the graphic segment arrangement sequence. The process of arranging the corresponding graphic segments in order of their unfolding direction is as follows: The measurement point location index is sorted by directional projection according to the direction of operation of the electromechanical equipment. Within the same operating contour level, the graphic segments corresponding to the temperature measurement point, voltage sampling point and flow sensing point are formed into continuous sequences. The continuous sequences are combined and associated in a fixed hierarchical order to obtain the continuously unfolded graphic output result. Based on the set of measurement point graphic fragments, a multi-level linear rendering queue is created, defining three parallel rendering layer channels: Layer_1 (bottom layer / temperature field), Layer_2 (middle layer / fluid field), and Layer_3 (top layer / electrical characteristics). The type attribute of each graphic unit in the fragment set is read, and it is distributed to the corresponding layer channel according to its type. For example, Unit_05_Temp is placed in Layer_1, and flow-related graphic units are placed in Layer_2. Within each layer, a secondary sort is performed based on the direction projection sort value in the measurement point location index associated with the graphic unit. The center point of each unit is then read. Axis coordinates, if Layer_2 has three flow segments ; Then according to Adjust the rendering order to ensure visual continuity, and check the edge connection of adjacent graphic fragments within the same level. If there is a color difference between the right boundary texture of the previous fragment and the left boundary texture of the next fragment... (CIELAB color difference formula), calling the texture blending algorithm, a 10-pixel-wide alpha gradient transition band is generated at the seam to smooth the visual discontinuity. After completing the internal sorting and fusion of each layer, it is arranged according to Layer_1. Layer_2 Layer_3 sequentially overlays and combines the data streams from the three channels. For regions where all three layers have pixel outputs at the same location, a weighted blending mode is used. The final pixel color is calculated to ensure that the underlying heatmap is not completely obscured by the upper layer, and a sequence of graphic fragments containing hierarchical relationships and temporal logic is generated. The evolution atlas generation submodule calls the graphic fragment arrangement sequence, combines and associates the continuously arranged graphic fragments, maintains the consistency of the running contour hierarchy, integrates the graphic content arranged along the unfolding direction, forms the continuously unfolded graphic output result, and generates the electromechanical equipment simulation result. Call the image fragment arrangement sequence, initialize a high-resolution frame buffer, and set the resolution to [resolution value missing]. The system reads each combined composite graphic node in the sequence, rasterizes it according to its absolute coordinates in the panoramic field, and writes it to the corresponding position in the frame buffer. For long-span graphics that span multiple rendering scheduling boundaries (such as the outline of a conveyor belt running through the entire equipment), the system uses the Bezier curve interpolation algorithm to connect the segment points, generating smooth continuous contour lines to fill the small gaps that may be generated by segmented rendering. The system loads the global illumination model, sets virtual light sources according to the equipment operating environment, and calculates the reflection and refraction effects of light on the graphic surfaces of each measuring point. In particular, for the particle flow effect of the flow sensing point, the system applies a dynamic blur filter to enhance its sense of flow. Finally, the synthesized static frame data is pushed into the video encoder in timeline order, or directly output to the digital twin monitoring screen in the form of a texture stream to generate a complete visualization view containing dynamic thermal changes, fluid trajectory jumps, and electrical waveform evolution, thus obtaining the simulation results of the electromechanical equipment. The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A visualization simulation system for electromechanical equipment based on digital twins, characterized in that, The system includes: The initial node mapping module acquires the changes in the external contour of the equipment and determines the direction of operation. It collects the positions of temperature measurement points, voltage sampling points and flow sensing points, maps each measurement point to the operating section of the electromechanical equipment, calibrates them in sequence, and forms a set of edge measurement point sorting results. The active state extraction module, based on the arrangement order of each measuring point in the edge measuring point sorting result set and the relationship with the running section, identifies the change direction of each measuring point in segments, analyzes the continuous and switching characteristics within the same section, distinguishes and marks the running sections where changes occur in a concentrated manner, and forms a set of regions where measuring point changes are concentrated. The jump interval identification module, based on the concentrated operation section identifier of the concentrated area of ​​the measurement point change, selects the corresponding flow sensing point number and obtains the trajectory change sequence, identifies the trajectory direction, determines the jump operation section at the change turning point, and forms a jump number classification mapping table. The image domain expansion scheduling module, based on the jump operation segment position and flow sensing point number in the jump number classification mapping table, locates the corresponding outline graphic position of the jump operation segment, extracts the expanded view graphic boundary and determines the coverage position, includes it in the rendering scheduling range and divides it sequentially to obtain the image rendering scheduling boundary set.

2. The electromechanical equipment visualization simulation system based on digital twins according to claim 1, characterized in that: The edge measurement point sorting result set includes measurement point sequence number, operating section positioning label, and measurement point type identification information. The measurement point change concentration area set includes change trend clustering section identifier, continuous change pattern characteristics, and measurement point association label within the section. The jump number classification mapping table includes jump section number, flow sensing point association number, and classification index identifier. The image rendering scheduling boundary set includes graphic boundary position parameters, rendering section division label, and map domain mapping sequence number.

3. The electromechanical equipment visualization simulation system based on digital twins according to claim 1, characterized in that: The initial node mapping module includes a contour direction recognition submodule, a measurement point segment assignment submodule, and a measurement point sequence calibration submodule. The contour direction recognition submodule acquires information on the external contour changes during the operation of electromechanical equipment, monitors the trend of contour edge shape changes in the equipment under continuous operation, performs direction recognition based on the extension sequence of contour changes on the running path, determines the running direction for the electromechanical equipment to be deployed under operation, and generates a running deployment direction identifier. The measuring point section attribution submodule, based on the operation deployment direction identifier, collects the location distribution information of temperature measuring points, voltage sampling points and flow sensing points distributed in the operating area of ​​electromechanical equipment, and makes section division judgment according to the relative position order of each measuring point on the operating path, and assigns different types of measuring points to specific operating sections, generating a measuring point section correspondence table. The measurement point sequence calibration submodule, based on the measurement point segment correspondence table, sequentially calibrates the appearance order of measurement points along the running unfolding direction within each running segment, organizes the arrangement relationship of different types of measurement points in the running trajectory, establishes a clear position correspondence relationship in the running unfolding view, and obtains the edge line measurement point sorting result set.

4. The electromechanical equipment visualization simulation system based on digital twins according to claim 1, characterized in that: The active state extraction module includes a change direction recognition submodule, a continuous feature extraction submodule, and a concentrated behavior segment recognition submodule; The change direction recognition submodule, based on the edge measurement point sorting result set, calls the arrangement order of the measurement points in the running section, and performs segmented recognition of the change direction of temperature measurement points, voltage sampling points and flow sensing points in the continuous running process. It judges the direction based on the change trend of the measurement points at each time node and generates a sequence of measurement point change directions. The continuous feature extraction submodule compares the changing directions of the measuring points in each operating segment according to the sequence of changing directions of the measuring points, identifies the continuous state of the direction in the continuous segment and the position where the direction changes, filters the distribution segments of measuring points with direction switching, and obtains the set of changing direction switching positions. The concentrated behavior section identification submodule calls the set of change direction switching locations to identify the distribution between adjacent operating sections, classifies and statistically analyzes the frequency of direction switching phenomena, selects the operating section number corresponding to the concentrated change area based on the density of distribution, and establishes a set of concentrated change areas for measuring points.

5. The electromechanical equipment visualization simulation system based on digital twins according to claim 1, characterized in that: The jump interval identification module includes a sensor point extraction submodule, a trajectory turning identification submodule, and a jump segment classification submodule; The sensing point extraction submodule, based on the clearly defined operating section identifier of the concentrated area set of measurement point changes, selects the flow sensing point number in the corresponding operating section, collects the position record sequence of each sensing point in the continuous operation process, organizes the position data of each sensing point in the order of operating time, and establishes a set of sensing point trajectory sequences. The trajectory turning identification submodule identifies the direction of trajectory change of each flow sensing point during continuous operation based on the set of sensing point trajectory sequences, filters the locations where the trajectory direction changes abruptly, determines the operating segment number to which the turning position belongs, obtains the range of operating positions where the trajectory turning occurs, and obtains the set of trajectory turning segments. The jump segment classification submodule calls the set of trajectory turning segments, combines the sensing point number information in each turning segment, establishes an attribution correspondence between the running segment that exhibits jump behavior and the corresponding flow sensing point, integrates the number information and segment location according to the attribution relationship, and generates a jump number classification mapping table.

6. The electromechanical equipment visualization simulation system based on digital twins according to claim 1, characterized in that: The map domain expansion and scheduling module includes a map location positioning submodule, a boundary range extraction submodule, and a rendering segment division submodule; The graphic location positioning submodule, based on the relationship between the jump operation segment position marked in the jump number classification mapping table and the corresponding flow sensing point number, obtains the contour graphic identification information corresponding to each segment in the operation unfolded map domain, detects the graphic position matching result of the jump operation segment in the map domain, and obtains the index corresponding to the contour position. The boundary range extraction submodule extracts the contour boundary annotations corresponding to each jump running segment in the unfolded map domain according to the contour position index, identifies the start and end positions of the boundary coverage in the running unfolding direction, confirms the graphic range of the contour segment associated with the jump behavior, and establishes a set of graphic coverage boundaries. The rendering segment division submodule calls the graphic coverage boundary set, groups the graphic boundaries sequentially according to the running unfolding direction, performs scheduling partitioning based on the connection order of the contour graphics covered by each group of boundaries, extracts the corresponding contour segments and assigns them to the rendering layout range, and generates an image rendering scheduling boundary set.

7. The electromechanical equipment visualization simulation system based on digital twins according to claim 1, characterized in that: The system also includes: The equipment evolution atlas output module extracts the associated graphic fragments of temperature measurement points, voltage sampling points and flow sensing points within the rendering scheduling boundary range based on the rendering scheduling boundary range in the image rendering scheduling boundary set. The fragments are then arranged hierarchically according to the direction of electromechanical equipment operation and the type of measurement points to obtain the electromechanical equipment simulation results. The simulation results of the electromechanical equipment include a set of graphic fragment sequences, a hierarchical structure of measurement point types, and information on the order of evolution.

8. The electromechanical equipment visualization simulation system based on digital twins according to claim 7, characterized in that: The device evolution atlas output module includes a graphic fragment extraction submodule, a fragment order arrangement submodule, and an evolution atlas generation submodule; The graphic fragment extraction submodule extracts the associated graphic information of temperature measurement points, voltage sampling points and flow sensing points within the corresponding boundary range based on the determined rendering scheduling boundary range in the image rendering scheduling boundary set. It identifies the corresponding graphic position of each measurement point in the outline unfolded view, organizes them into a set of graphic units that can be called independently, and obtains a set of graphic fragments of measurement points. The segment sequence arrangement submodule, based on the set of measurement point graphic segments, determines the sequence of graphic segments of different measurement point types according to the direction of operation of the electromechanical equipment, divides the graphic segments within the same operating contour level into hierarchical divisions according to the measurement point type, and arranges the corresponding graphic segments in sequence according to the direction of operation to obtain the graphic segment arrangement sequence. The evolution atlas generation submodule calls the graphic fragment arrangement sequence, combines and associates the continuously arranged graphic fragments, maintains the consistency of the running contour hierarchy, integrates the graphic content arranged along the unfolding direction, forms a continuously unfolded graphic output result, and generates the electromechanical equipment simulation result.

9. The electromechanical equipment visualization simulation system based on digital twins according to claim 8, characterized in that: The process of extracting the associated graphical information of temperature measuring points, voltage sampling points, and flow sensing points within the corresponding boundary range is as follows: For each rendering scheduling boundary range in the image rendering scheduling boundary set, the corresponding graphic boundary range is cropped. Boundary constraints and element deduplication are performed on the cropped graphic content. The graphic information associated with temperature measurement points, voltage sampling points and flow sensing points are merged into the corresponding cropping results. The process of identifying the corresponding graphic position of each measuring point in the unfolded contour view is as follows: A measurement point location index is established based on the relative positional relationship between graphic markers and contour line segments, and the measurement point location index is written into the independently callable set of graphic units to form the set of measurement point graphic segments.

10. The electromechanical equipment visualization simulation system based on digital twins according to claim 8, characterized in that: The process of arranging the corresponding graphic segments sequentially according to the unfolding direction is as follows: The measurement point location index is sorted by directional projection according to the direction of operation of the electromechanical equipment. Within the same operating contour level, the graphic segments corresponding to the temperature measurement point, voltage sampling point and flow sensing point are formed into continuous sequences. The continuous sequences are combined and associated in a fixed hierarchical order to obtain the continuously unfolded graphic output result.

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