CN117438115A - Intelligent monitoring twin system and method for nuclear power plant main pipeline machining operation process - Google Patents
Intelligent monitoring twin system and method for nuclear power plant main pipeline machining operation process Download PDFInfo
- Publication number
- CN117438115A CN117438115A CN202311332132.XA CN202311332132A CN117438115A CN 117438115 A CN117438115 A CN 117438115A CN 202311332132 A CN202311332132 A CN 202311332132A CN 117438115 A CN117438115 A CN 117438115A
- Authority
- CN
- China
- Prior art keywords
- machine
- cutting machine
- beveling
- main pipeline
- beveling machine
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 92
- 238000000034 method Methods 0.000 title claims abstract description 65
- 230000008569 process Effects 0.000 title claims abstract description 52
- 238000003754 machining Methods 0.000 title claims description 20
- 238000005520 cutting process Methods 0.000 claims abstract description 175
- 238000012545 processing Methods 0.000 claims abstract description 34
- 230000001360 synchronised effect Effects 0.000 claims abstract description 11
- 230000000007 visual effect Effects 0.000 claims abstract description 8
- 238000004891 communication Methods 0.000 claims description 7
- 238000013507 mapping Methods 0.000 claims description 7
- 238000012806 monitoring device Methods 0.000 claims description 5
- 238000011156 evaluation Methods 0.000 description 9
- 238000003698 laser cutting Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 230000003993 interaction Effects 0.000 description 3
- 238000005299 abrasion Methods 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000003062 neural network model Methods 0.000 description 2
- 230000005855 radiation Effects 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 238000012800 visualization Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000000903 blocking effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 239000003758 nuclear fuel Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G21—NUCLEAR PHYSICS; NUCLEAR ENGINEERING
- G21C—NUCLEAR REACTORS
- G21C17/00—Monitoring; Testing ; Maintaining
- G21C17/017—Inspection or maintenance of pipe-lines or tubes in nuclear installations
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
- B23K26/00—Working by laser beam, e.g. welding, cutting or boring
- B23K26/70—Auxiliary operations or equipment
- B23K26/702—Auxiliary equipment
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Computation (AREA)
- General Physics & Mathematics (AREA)
- Plasma & Fusion (AREA)
- Computer Hardware Design (AREA)
- Optics & Photonics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Computational Mathematics (AREA)
- Mechanical Engineering (AREA)
- High Energy & Nuclear Physics (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Monitoring And Testing Of Nuclear Reactors (AREA)
Abstract
The invention discloses an intelligent monitoring twin system and a method for a nuclear power plant main pipeline processing operation process, wherein the intelligent monitoring twin system comprises a cutting machine or/and beveling machine equipment entity, monitoring equipment, a cutting machine or/and beveling machine virtual model and a control platform, and synchronous visual display of the cutting machine or/and the beveling machine and corresponding virtual models is realized according to the operation data of the cutting machine or/and the beveling machine and the data acquired by the monitoring equipment; and simultaneously, the data acquired by the monitoring equipment are transmitted back to the corresponding virtual model, and the virtual model performs evolution iteration on the state of the cutting machine or/and the beveling machine based on the transmitted data and is displayed on the control platform. The invention can realize the omnibearing state monitoring in the running process of the equipment and improve the safety and reliability of the running process of the equipment.
Description
Technical Field
The invention belongs to the technical field of intelligent monitoring, relates to intelligent monitoring of electromechanical equipment, and particularly relates to an intelligent monitoring twin system and method for a main pipeline machining operation process of a nuclear power plant.
Background
In pressurized water reactor nuclear power plants, the heat transfer tubes of the Steam Generator (SG) occupy a majority of the total area of the pressure boundary of the primary loop system. A pressurized water reactor nuclear power plant steam generator belongs to a large heat exchange container, and heat energy generated by nuclear fuel is used for pushing a steam turbine to generate electricity and apply work through steam. As large-scale expensive equipment for connecting the first loop and the second loop, the problems of corrosion, mechanical damage, abrasion, fatigue and the like of the heat transfer pipe are often accompanied in the operation process. The operational capacity of the steam generator is related to the safety and economic benefits of the nuclear power plant. And thus maintain its integrity, is extremely important to ensure the safety of the nuclear power plant. However, with the increase of the service life, the steam generator needs to consider engineering links such as maintenance, replacement, retirement and the like. In the replacement engineering, in order to replace the main body part of the steam generator reaching the expected service life, the connecting parts thereof are cut. The cutting of the primary loop pipeline is an important link in the whole replacement engineering, and links such as radiation protection, free end pipeline fixation, debris collection and treatment, cutting monitoring, pipeline blocking and the like in the cutting process need to be comprehensively considered. In order to further improve the digital monitoring level of the nuclear power plant in the replacement process of the in-service steam generator, improve the efficiency and quality of the completion of the replacement engineering of the steam generator, a digital twin technology is introduced, and a digital twin monitoring system with informatization and intellectualization is constructed mainly in the cutting and beveling processes of a loop pipeline.
Patent application CN202211068985.2 discloses a laser cutting synchronous simulation method based on digital twin of a laser cutting machine, which mainly describes how to synchronously simulate the machining process of the laser cutting machine from the angles of a virtual laser cutting machine and a laser cutting machine in a real physical environment, and cannot monitor the equipment and the machining operation process from the monitoring angle in the operation process of the machining equipment, and cannot evaluate and analyze the current operation progress of the equipment.
Disclosure of Invention
The invention aims to provide an intelligent monitoring twin system and method for a main pipeline machining operation process of a nuclear power plant, aiming at the technical situation that effective monitoring is difficult to realize in the main pipeline cutting and opening adding process of the nuclear power plant at present, so that the contact between personnel and nuclear radiation in the main pipeline cutting and groove machining operation process of the nuclear power plant is reduced, the monitoring intensity of equipment in the remote operation process is improved, and the safety of equipment and workpieces in the remote operation process is improved.
The invention provides an intelligent monitoring twin system for a nuclear power plant main pipeline processing operation process, which comprises the following components:
the cutting machine or/and beveling machine equipment entity is arranged on the main pipeline and is used for cutting or/and beveling the main pipeline;
the monitoring equipment is used for monitoring the cutting machine or/and the beveling machine; the monitoring equipment comprises more than two vibration monitors which are arranged along the circumferential direction of the main pipeline, a temperature detector which is arranged on the circumferential direction of the main pipeline, a first camera which is used for collecting image information for the cutting machine, and a second camera which is used for collecting image information for the beveling machine;
the virtual model of the cutting machine or/and the beveling machine is based on a three-dimensional model constructed by the cutting machine or/and the beveling machine; the virtual model of the cutting machine or/and the beveling machine is in communication connection with the corresponding cutting machine or/and the beveling machine and is used for synchronously mapping based on the operation data from the cutting machine or/and the beveling machine;
the control platform is in communication connection with the cutting machine/beveling machine, the monitoring equipment and the corresponding virtual model, and the synchronous visual display of the cutting machine/beveling machine and the corresponding virtual model is realized according to the operation data of the cutting machine/beveling machine and the data acquired by the monitoring equipment; and simultaneously, the data acquired by the monitoring equipment are transmitted back to the corresponding virtual model, and the virtual model performs evolution iteration on the state of the cutting machine or/and the beveling machine based on the transmitted data and is displayed on the control platform.
Above-mentioned nuclear power plant trunk line processing operation in-process intelligent monitoring twin system, monitoring facilities still includes the third camera that is used for monitoring the trunk line, and the third camera shooting scope covers cutting machine, beveling machine and takes the pipeline of cutting and processing. The first cameras are arranged symmetrically along the circumferential direction of the main pipeline, and the shooting range of the first cameras covers the cutting machine; the second cameras are arranged symmetrically along the circumferential direction of the main pipeline, and the shooting range of the second cameras covers the beveling machine.
According to the intelligent monitoring twin system for the nuclear power plant main pipeline processing operation process, the cutting machine or/and beveling machine virtual model also predicts the cutting machine or/and beveling machine operation data at the next moment and feeds the cutting machine or/and beveling machine operation data back to corresponding equipment entities. When the running data of the cutting machine or/and the beveling machine reaches an alarm level, the equipment entity autonomously alarms or informs workers to view in the field in other modes.
The intelligent monitoring twin system for the main pipeline processing operation process of the nuclear power plant comprises a virtual model of the cutting machine or/and the beveling machine, wherein for the cutting machine, the operation data comprise main shaft data of an axis where a cutting tool is located, tool parameter data (such as a tool length, a cutting rate and the like), servo motor control signals, feed data (radial feed data), alarm signal data (such as limit alarms of the main shaft and two shafts of a radial feed shaft, servo motor fault alarms and the like) and the like; for the beveling machine, the operation data comprise spindle data of an axis where the beveling tool is located, tool parameter data (such as tool length, cutting rate and the like), servo motor control signals, feed data (axial feed data and radial feed data), alarm signal data (such as limit alarm of three axes of a spindle, a radial feed shaft and an axial feed shaft, servo motor fault alarm and the like) and the like.
The intelligent monitoring twin system for the nuclear power plant main pipeline processing operation process comprises a cutting machine or/and beveling machine state, a main pipeline processing area thermal state, a cutter state and the like. The assembly state of the cutting machine or the beveling machine and the main pipeline can be measured according to the vibration monitors, and the current assembly error between the cutting machine or the beveling machine and the main pipeline is represented by the measured data deviation of each vibration monitor; the thermal state of the main pipeline processing area can be obtained through a thermometer; the cutter state can be obtained by acquiring images through a first camera or a second camera; the tool state includes a tool wear state and a tool life; the tool state may be obtained by inputting images acquired by one or a second camera into a trained neural network model (e.g., GA-BP, GRU, DE-BP, etc.). Along with the processing process, the evolution process of the state of the cutting machine or/and the beveling machine can be obtained.
The control platform can evaluate the state of the cutting machine or/and the beveling machine according to the evolution result of the state of the cutting machine or/and the beveling machine, and can correspondingly reflect the state of the cutting machine or/and the beveling machine according to the evaluation result. For example, when the assembly accuracy of the cutting machine or the beveling machine and the main pipeline deviates from a set threshold value, or the temperature of the main pipeline is too high, or the cutter is seriously worn, or the service life of the cutter reaches an upper limit, a corresponding fault early warning can be sent out, and the fault early warning is processed by staff. The control platform can also feed back the evaluation result to the equipment entity, and the equipment entity directly alarms or informs workers to view on site through other modes.
The invention also provides an intelligent monitoring method for the processing operation process of the main pipeline of the nuclear power plant, which is carried out by using the intelligent monitoring system for the processing operation process of the main pipeline of the nuclear power plant according to the following steps:
s1, the cutting machine or/and beveling machine equipment entity sends operation data to a corresponding virtual model and a control platform; the monitoring equipment sends the acquired data to the control platform;
s2, synchronously mapping the virtual model of the cutting machine or/and the beveling machine based on operation data from the cutting machine or/and the beveling machine, and sending the virtual model and the synchronous data to a control platform for display;
s3, the control platform displays the received acquired data of the cutting machine or/and beveling machine equipment entity, the corresponding virtual model and the monitoring equipment in real time; and the control platform simultaneously transmits the monitoring equipment acquisition data to the corresponding virtual model.
And S4, the virtual model of the cutting machine or/and the beveling machine performs evolution iteration on the state of the cutting machine or/and the beveling machine according to the data acquired by the monitoring equipment, and the evolution iteration result is sent to the control platform for display.
In the step S2, the virtual model of the cutting machine or/and the beveling machine predicts the running data of the cutting machine or/and the beveling machine at the next moment and feeds the running data back to the corresponding equipment entity. When the state of the cutting machine or/and the beveling machine reaches an alarm level, the equipment entity autonomously alarms or informs workers to view on site in other modes, so that real-time interaction between the cutting machine or/and the beveling machine equipment entity and the corresponding virtual model is realized.
The intelligent monitoring method for the processing operation process of the main pipeline of the nuclear power plant further comprises the step S5, wherein the control platform evaluates the state of the cutting machine or/and the beveling machine according to the evolution result of the state of the cutting machine or/and the beveling machine. The control platform can also feed back the evaluation result to the equipment entity, and the equipment entity directly alarms or informs workers to view on site through other modes.
Compared with the prior art, the invention has the following beneficial effects:
1) The intelligent monitoring system for the main pipeline cutting and beveling operation process of the nuclear power plant can realize omnibearing state monitoring in the equipment operation process and improve the safety and reliability of the equipment operation process.
2) Aiming at the digital twin virtual model constructed on the industrial site, the invention provides an implementation thought for carrying out virtual model evolution iteration by utilizing the on-site multi-source physical data, and the depicting similarity of the virtual model to the physical entity is greatly improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of an intelligent monitoring twin system framework for a main pipeline processing operation process of a nuclear power plant according to embodiment 1 of the present invention.
Fig. 2 shows a main pipeline cutting and beveling environment of a nuclear power plant according to embodiment 1 of the present invention, where (a) corresponds to a cutting machine and (b) corresponds to a beveling machine; in the figure, 1-main pipeline, 11-pipeline to be cut, 12-pipeline to be processed, 2-cutting machine, 3-support, 31-first fixing seat, 32-second fixing seat, 33-telescopic support rod, 4-beveling machine, 5-vibration monitor, 6-thermoscope, 7-first camera, 8-second camera and 9-third camera.
Fig. 3 is a block diagram of an intelligent monitoring twin system on-site deployment relationship in the process of the main pipeline processing operation of the nuclear power plant according to embodiment 1 of the present invention.
Fig. 4 is a flowchart of virtual model evolution iteration in embodiment 2 of the present invention.
Detailed description of the preferred embodiments
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
The intelligent monitoring twin system for the main pipeline processing operation process of the nuclear power plant provided by the embodiment, as shown in fig. 1, comprises a cutting machine or/and beveling machine equipment entity, monitoring equipment, a cutting machine or/and beveling machine virtual model and a control platform.
Cutting machine and/or beveling machine equipment entity
And the cutting machine and beveling machine equipment entity is arranged on the main pipeline and used for cutting and beveling the main pipeline.
The main pipeline cutting operation environment of the nuclear power plant according to the present embodiment is as shown in fig. 2 (a), the cutting machine 2 is mounted on the main pipeline 1 through the bracket 3, and the cutting machine 2 is located at the pipeline 11 to be cut. The bracket 3 includes a first fixing seat 31 and a second fixing seat 32 which are circumferentially arranged along the main pipe, and a telescopic support rod 33 which is fixed between the first fixing seat 31 and the second fixing seat 32. By adjusting the telescopic support rod 33, the first fixing base 31 and the second fixing base 32 can be coaxially assembled with the main pipe 1, respectively. The working environment of the beveling machine 4 is shown in fig. 2 (b), and the installation mode is similar to that of a cutting machine, wherein the beveling machine 4 is positioned at a pipeline 12 to be processed, and the detailed explanation is omitted.
The cutting machine 2 and the beveling machine 4 used in this embodiment are conventional apparatuses as disclosed in the art, and the present invention is not limited to any particular type of cutting machine or beveling machine. The cutting machine 2 and the beveling machine are respectively in communication connection with the virtual model and the control platform through respective PLC controllers, and operation data are transmitted to the virtual model and the control platform in real time. For the cutting machine, the operation data comprise main shaft data of an axis where the cutting tool is located, tool parameter data (such as tool length, cutting speed and the like), servo motor control signals, feed data (radial feed data), alarm signal data (such as limit alarm of the main shaft and two shafts of a radial feed shaft, servo motor fault alarm and the like) and the like; for the beveling machine, the operation data comprise spindle data of an axis where a beveling tool is located, tool parameter data (such as a tool length, a cutting rate and the like), servo motor control signals, feed data (axial feed data and radial feed data), alarm signal data (such as limit alarm of a spindle, a radial feed shaft, three axes of the axial feed shaft, servo motor fault alarm and the like) and the like. The operation data of the cutting machine and the beveling machine can be calculated by the motor data sensed by the motor driver of the corresponding servo motor.
Here, the roles of the cutting machine and the beveling machine equipment entity mainly include: 1) providing three-dimensional parameters for the construction of the virtual model, 2) generating interaction between twin data generated by the operation of the equipment and the virtual model, and 3) monitoring and data acquisition of the operation of the equipment entity by the field monitoring equipment, and providing feedback data for the iterative evolution of the virtual model.
(II) monitoring device
And the monitoring equipment is used for carrying out multi-source physical data real-time monitoring and acquisition on the cutting machine and the beveling machine. The monitoring device comprises a vibration monitor 5, a thermo detector 6, a first camera 7 and a second camera 8.
The vibration monitor 5 is used for measuring vibration data generated in the working process of the cutting machine or the beveling machine. The vibration monitor 5 quantity is more than two, installs in first fixing base side along trunk line circumference.
The thermometer 6 is used for measuring the ambient temperature around the cutting machine or the beveling machine during operation. The thermometer 6 is mounted on the first fixing base 31 and faces the belt cutting pipe 11.
The first camera 7 is used for monitoring the cutting machine and collecting related images; the second camera 8 is used for monitoring the beveling machine and collecting related images. The number of the first cameras 7 and the second cameras 8 is 2, the first cameras 7 or the second cameras 8 are symmetrically arranged on the first fixing seat, and the shooting range of the first cameras or the second cameras covers the cutting machine or the beveling machine.
The monitoring device further comprises a third camera 9 monitoring the main pipe. And the shooting range of the third camera covers a cutting machine, a beveling machine and a pipeline with cutting and beveling.
The monitoring device transmits the acquired data to the control platform in real time.
(III) virtual model of cutting machine and beveling machine
Based on the physical parameters of the cutting machine and the beveling machine and the parameters of the main pipeline, a corresponding three-dimensional model is built through CAD software and the like, and the three-dimensional model comprises the main pipeline and the virtual model of the cutting machine and the beveling machine which are arranged on the main pipeline.
The main pipe parameters include main pipe geometry and dimensions. The physical parameters of the cutting machine and the beveling machine include basic parameters of each of the parts constituting the cutting machine or the beveling machine (such as model numbers, sizes, etc. of each of the parts), and the fitting relationship (i.e., positional relationship) between each of the parts. And determining a basic motion model of each part according to the assembly relation among the parts, for example, constructing a basic motion model of the rotating ring structure in the cutting machine relative to the static ring structure which rotates around the axial direction.
Finally, the constructed virtual model of the three-dimensional cutting machine and the beveling machine is imported into a three-dimensional engine, and each part is associated with corresponding physical parameters (such as coordinates and the like). And configuring related physical parameters and other components for the original three-dimensional model according to the actual motion rules of the physical entity, and simultaneously establishing a synchronous data interface connected with the physical entity for the components and variable parameters to be synchronized.
The virtual models of the cutting machine and the beveling machine are in communication connection with the corresponding cutting machine and the beveling machine, and are used for synchronously mapping based on operation data from the cutting machine and the beveling machine, synchronizing the actions of the virtual models and simulating the machining process of the cutting machine. The virtual model of the cutting machine or/and the beveling machine also predicts the running data of the cutting machine and the beveling machine at the next moment and feeds the running data back to the corresponding equipment entity. When the state of the cutting machine or/and the beveling machine reaches an alarm level, the equipment entity autonomously alarms or informs workers to view in the field in other modes. The virtual model can predict the operation data of the cutting machine and the beveling machine at the next moment through the conventional LSTM model, and then the prediction result is fed back to the cutting machine and the beveling machine to perform early warning on the cutting machine and the beveling machine, so that real-time interaction between the cutting machine and the beveling machine equipment entity and the corresponding virtual model is realized.
Thus, the virtual model is presented in a three-dimensional visualization form, and the presented effects include not only the geometric model and the motion model of the equipment entity, but also the synchronized mapping of the twinning data from the equipment entity, and the iteration of the acquisition and evolution model from the on-site monitoring data.
(IV) control platform
The control platform is in communication connection with the cutting machine/beveling machine, the monitoring equipment and the corresponding virtual models, and synchronous visual display of the cutting machine, the beveling machine and the corresponding virtual models is realized according to the operation data of the cutting machine and the beveling machine and the data acquired by the monitoring equipment, for example, a first camera picture (picture 1), a second camera picture (picture 2), a third camera picture (picture 3), a cutting machine virtual model interface and a beveling machine virtual model interface.
And simultaneously, the data acquired by the monitoring equipment are transmitted back to the corresponding virtual model, and the virtual model performs evolution iteration on the states of the cutting machine and the beveling machine based on the transmitted data and is displayed on the control platform. The states of the cutting machine and the beveling machine comprise an assembly state of the cutting machine or the beveling machine and the main pipeline, a thermal state of a main pipeline processing area, a cutter state and the like. The assembly state of the cutting machine or the beveling machine and the main pipeline can be measured according to the vibration monitors, and the current assembly error between the cutting machine or the beveling machine and the main pipeline is represented by the measured data deviation of each vibration monitor. The thermal state of the processing area of the main pipeline can be obtained through a thermometer so as to evolve the environmental state of the processing area. The cutter state can be obtained by acquiring images through the first camera or the second camera; the tool state includes tool wear state and tool life; the tool state may be obtained by inputting images acquired by one camera or a second camera into a trained neural network model (e.g., GA-BP, GRU, DE-BP, etc.). Along with the processing process, the evolution process of the states of the cutting machine and the beveling machine can be obtained, the states are mapped to corresponding positions of the virtual model, and the virtual model is transmitted to a control platform for visual display. The virtual model of the cutting machine or/and the beveling machine also predicts the operation data of the cutting machine or/and the beveling machine at the next moment and feeds the operation data back to the corresponding equipment entity. When the state of the cutting machine or/and the beveling machine reaches an alarm level, the equipment entity autonomously alarms or informs workers to view in the field in other modes.
The control platform can evaluate the states of the cutting machine and the beveling machine according to the evolution results of the states of the cutting machine and the beveling machine, and can correspondingly reflect the states of the cutting machine and the beveling machine according to the evaluation results. For example: (1) Judging whether the measured data deviation of each vibration monitor is in an error range, if so, indicating that the assembly precision between the cutting machine or the beveling machine and the main pipeline meets the requirement; if the assembly accuracy exceeds the error range, the assembly accuracy between the cutting machine or the beveling machine and the main pipeline is not in accordance with the requirement, and the machining process is required to be stopped for adjustment; (2) When the temperature of the main pipeline exceeds a set threshold value, stopping the processing process; (3) When the wear state or the service life of the tool meets the set standard, the machining process is stopped and the tool is replaced. Therefore, corresponding fault early warning can be sent out according to the evaluation result, and the fault early warning can be processed by staff.
Thus, the functions of the control platform include: 1) providing a visual interface for a user, wherein the visual interface is used for displaying parameters such as the running state of equipment, 2) loading multiple paths of video pictures and other multi-source data from the scene, 3) running a virtual model of the equipment and undertaking evolution calculation work of the model. The control platform can also feed back the evaluation result to the equipment entity, and the equipment entity directly alarms or informs workers to view on site through other modes.
A block diagram of the deployment relationship of the intelligent monitoring twin system at the operation site in the embodiment is shown in fig. 3. The two areas are divided into a working site and a remote control room from the position relation. The relevant monitoring equipment on the operation site is deployed around the cutting machine, the beveling machine and the pipeline to be processed according to the corresponding position relation, the data collected by all the monitoring equipment are directly connected with the local control box, and all the data are connected with a control platform in a remote monitoring room through a wired network. In the monitoring room, the virtual models of the cutting machine and the beveling machine and related multi-source data are displayed in a centralized three-dimensional visual mode in the remote control platform, and monitoring personnel only need to monitor and evaluate various parameters and state data of the remote control platform after the equipment operates and make corresponding reflection.
Example 2
The embodiment provides an intelligent monitoring system for a main pipeline processing operation process of a nuclear power plant, which is provided by the embodiment 1, for intelligent monitoring of the main pipeline processing operation process of the nuclear power plant, and comprises the following steps:
s1, transmitting operation data to a corresponding virtual model and a corresponding control platform by a cutting machine and beveling machine equipment entity; the monitoring equipment sends the acquired data to the control platform;
along with the starting of the equipment, all the multi-source data collected on site are returned and summarized to the remote centralized processing.
And S2, synchronously mapping the virtual models of the cutting machine and the beveling machine based on operation data from the cutting machine and the beveling machine, and sending the virtual models and the synchronous data to a control platform for display.
As shown in fig. 4, the virtual model is based on a motion chain and related configuration parameters which are constructed by a basic motion model and conform to the motion rule of the equipment entity, and then a data synchronization visualization model is established between data signals including spindle data, tool data, feed data, servo motor control signals, alarm signals and the like and the equipment entity according to the operation data transmitted by the cutting machine or the beveling machine.
In the step, the virtual model of the cutting machine or/and the beveling machine also predicts the running data of the cutting machine or/and the beveling machine at the next moment and feeds the running data back to the corresponding equipment entity. When the state of the cutting machine or/and the beveling machine reaches an alarm level, the equipment entity autonomously alarms or informs workers to view in the field in other modes.
S3, the control platform displays the received data acquired by the cutting machine and beveling machine equipment entities, the corresponding virtual model and the monitoring equipment in real time; and the control platform simultaneously transmits the monitoring equipment acquisition data to the corresponding virtual model.
And S4, the virtual models of the cutting machine and the beveling machine conduct evolution iteration on the states of the cutting machine and the beveling machine according to the data acquired by the monitoring equipment, and the evolution iteration results are sent to the control platform for display.
Because the cutting and groove machining operation process belongs to the field of machining operation, the process has structural damage links of parts to be machined, and therefore the traditional static data synchronization model cannot meet the monitoring function requirement of the operation process. Thus, the embodiment has important significance in dynamically correcting the current stage model by utilizing the on-site multi-source sensing data. The correction process mainly focuses on the three links of evolving equipment and pipeline assembly precision by using vibration data, evolving cutting and processing area states by using temperature data and evolving cutter abrasion states and service lives by using cutter images to obtain states of a cutting machine or a beveling machine. The virtual model after evolution is completed reflects various physical parameters and states of equipment entities in real time, and provides service data support for links such as operation monitoring, progress management, fault early warning, processing simulation, remote monitoring, operation process playback and the like, so that the digital twin function in the system is played to the greatest extent.
Along with the continuous evolution of the virtual model and the accumulation of data history data, the data and the model presented in the remote control platform are more close to the real-time state of the equipment entity, so that a complete intelligent monitoring twin system is formed.
And S5, the control platform evaluates the states of the cutting machine and the beveling machine according to the evolution results of the states of the cutting machine and the beveling machine, and can also correspondingly reflect according to the evaluation results.
For example: (1) Judging whether the measured data deviation of each vibration monitor is in an error range, if so, indicating that the assembly precision between the cutting machine or the beveling machine and the main pipeline meets the requirement; if the assembly accuracy exceeds the error range, the assembly accuracy between the cutting machine or the beveling machine and the main pipeline is not in accordance with the requirement, and the machining process is required to be stopped for adjustment;
(2) When the temperature of the main pipeline exceeds a set threshold value, stopping the processing process;
(3) When the wear state or the service life of the tool meets the set standard, the machining process is stopped and the tool is replaced. Therefore, corresponding fault early warning can be sent out according to the evaluation result, and the fault early warning can be processed by staff.
The control platform can also feed back the evaluation result to the equipment entity, and the equipment entity directly alarms or informs workers to view on site through other modes.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. An intelligent monitoring twin system for a nuclear power plant main pipeline machining operation process, which is characterized by comprising:
the cutting machine or/and beveling machine equipment entity is arranged on the main pipeline and is used for cutting or/and beveling the main pipeline;
the monitoring equipment is used for monitoring the cutting machine or/and the beveling machine; the monitoring equipment comprises more than two vibration monitors which are arranged along the circumferential direction of the main pipeline, a temperature detector which is arranged on the circumferential direction of the main pipeline, a first camera which is used for collecting image information for the cutting machine, and a second camera which is used for collecting image information for the beveling machine;
the virtual model of the cutting machine or/and the beveling machine is based on a three-dimensional model constructed by the cutting machine or/and the beveling machine; the virtual model of the cutting machine or/and the beveling machine is in communication connection with the corresponding cutting machine or/and the beveling machine and is used for synchronously mapping based on the operation data from the cutting machine or/and the beveling machine;
the control platform is in communication connection with the cutting machine/beveling machine, the monitoring equipment and the corresponding virtual model, and the synchronous visual display of the cutting machine/beveling machine and the corresponding virtual model is realized according to the operation data of the cutting machine/beveling machine and the data acquired by the monitoring equipment; and simultaneously, the data acquired by the monitoring equipment are transmitted back to the corresponding virtual model, and the virtual model performs evolution iteration on the state of the cutting machine or/and the beveling machine based on the transmitted data and is displayed on the control platform.
2. The intelligent monitoring twinning system for a nuclear power plant main pipeline machining process according to claim 1, wherein the monitoring device further comprises a third camera for monitoring the main pipeline; the first cameras are arranged symmetrically along the circumferential direction of the main pipeline, and the shooting range of the first cameras covers the cutting machine; the second cameras are arranged symmetrically along the circumferential direction of the main pipeline, and the shooting range of the second cameras covers the beveling machine.
3. The intelligent monitoring twin system for the main pipeline processing operation process of the nuclear power plant according to claim 1, wherein the virtual model of the cutting machine or/and the beveling machine predicts the operation data of the cutting machine or/and the beveling machine at the next moment and feeds the operation data back to the cutting machine or/and the beveling machine.
4. The intelligent monitoring twin system for the main pipeline machining operation process of the nuclear power plant according to claim 1, wherein the states of the cutting machine and/or the beveling machine comprise an assembly state of the cutting machine or the beveling machine and the main pipeline, a thermal state of a main pipeline machining area, a cutter state and the like; the assembly state of the cutting machine or the beveling machine and the main pipeline is measured according to each vibration monitor, and the current assembly error between the cutting machine or the beveling machine and the main pipeline is represented by the measured data deviation of each vibration monitor; the thermal state of the main pipeline processing area is obtained through a thermometer; the cutter state is obtained by acquiring images through the first camera or the second camera.
5. The intelligent monitoring twinning system for a nuclear power plant main pipeline machining operation process of claim 4, wherein the tool condition includes a tool wear condition and a tool life.
6. The intelligent monitoring twin system for a main pipeline processing operation process of a nuclear power plant according to claim 1, wherein the control platform evaluates states of the cutting machine or/and the beveling machine according to evolution results of states of the cutting machine or/and the beveling machine.
7. An intelligent monitoring method for a main pipeline processing operation process of a nuclear power plant, characterized in that an intelligent monitoring twin system for a main pipeline processing operation process of a nuclear power plant according to any one of claims 1 to 6 is used, and the method comprises the following steps:
s1, the cutting machine or/and beveling machine equipment entity sends operation data to a corresponding virtual model and a control platform; the monitoring equipment sends the acquired data to the control platform;
s2, synchronously mapping the virtual model of the cutting machine or/and the beveling machine based on operation data from the cutting machine or/and the beveling machine, and sending the virtual model and the synchronous data to a control platform for display;
s3, the control platform displays the received acquired data of the cutting machine or/and beveling machine equipment entity, the corresponding virtual model and the monitoring equipment in real time; and the control platform simultaneously transmits the monitoring equipment acquisition data to the corresponding virtual model.
And S4, the virtual model of the cutting machine or/and the beveling machine performs evolution iteration on the state of the cutting machine or/and the beveling machine according to the data acquired by the monitoring equipment, and the evolution iteration result is sent to the control platform for display.
8. The intelligent monitoring method for the main pipeline processing operation process of a nuclear power plant according to claim 7, wherein in step S2, the virtual model of the cutting machine or/and the beveling machine predicts the operation data of the cutting machine or/and the beveling machine at the next moment and feeds back the operation data to the cutting machine or/and the beveling machine.
9. The intelligent monitoring method for the main pipeline processing operation process of the nuclear power plant according to claim 7, further comprising the step of S5, wherein the control platform evaluates the state of the cutting machine or/and the beveling machine according to the evolution result of the state of the cutting machine or/and the beveling machine.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2023109704216 | 2023-08-02 | ||
| CN202310970421 | 2023-08-02 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117438115A true CN117438115A (en) | 2024-01-23 |
Family
ID=89550777
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311332132.XA Pending CN117438115A (en) | 2023-08-02 | 2023-10-13 | Intelligent monitoring twin system and method for nuclear power plant main pipeline machining operation process |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117438115A (en) |
-
2023
- 2023-10-13 CN CN202311332132.XA patent/CN117438115A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Kiangala et al. | Initiating predictive maintenance for a conveyor motor in a bottling plant using industry 4.0 concepts | |
| AU2019201086B2 (en) | Method and system for condition monitoring of a group of plants | |
| US20210201593A1 (en) | Systems and methods for presenting an augmented reality | |
| CN107730017A (en) | Intelligent metallurgical equipment operational diagnostics system | |
| US20160282843A1 (en) | Systems and methods for enhancing monitoring of an industrial automation system | |
| CN101539763A (en) | Wind field monitoring system | |
| Alatorre et al. | Teleoperated, in situ repair of an aeroengine: Overcoming the internet latency hurdle | |
| CN111322206B (en) | Intelligent operation and maintenance system and method for large mechanical part of wind turbine generator | |
| CN115865992B (en) | Intelligent water conservancy online monitoring system | |
| CN114595875A (en) | State evaluation method and system based on transformer sensing information and digital twins | |
| CN115329559A (en) | Digital twinning method and system for welding robot workstation | |
| CN114326517B (en) | Remote management method and system based on virtual reality | |
| CN117438115A (en) | Intelligent monitoring twin system and method for nuclear power plant main pipeline machining operation process | |
| KR101855679B1 (en) | Remote real monitoring and prediction system of auto-machine tool | |
| CN110907038A (en) | Power equipment infrared thermal imaging monitoring system based on artificial intelligence | |
| CN111259562B (en) | Dynamic virtual system for analyzing, controlling and controlling failure area of heating surface of boiler | |
| JP6573504B2 (en) | Work support system and work support method for work device | |
| CN115390534A (en) | Permanent magnetic ferrite full-life cycle management system and method based on digital twinning | |
| CN114006475A (en) | Power plant digital medium-voltage switch equipment intelligent management system | |
| CN113313816B (en) | Visualization method for overhaul state of heating surface in operation and maintenance of boiler | |
| CN113064420A (en) | Management platform and management method for intelligent inspection robot of urban comprehensive pipe gallery | |
| Jharko et al. | Intelligent Support Systems for NPP Operators: Dynamic Modeling and Operational Diagnostics | |
| Niculescu et al. | Data Recorder System for Maintenance to Rotary Blade Machines–“HolderPPS” | |
| Kirkpatrick | Digital Twins in Advanced Manufacturing to Enhance Manufacturing Efficiency | |
| Huang et al. | Robotic replacement system for thermocouple components in the nuclear power plant |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |