CN115700636A - Equipment inspection and report generation method, device, equipment and medium based on digital twin - Google Patents
Equipment inspection and report generation method, device, equipment and medium based on digital twin Download PDFInfo
- Publication number
- CN115700636A CN115700636A CN202211438649.2A CN202211438649A CN115700636A CN 115700636 A CN115700636 A CN 115700636A CN 202211438649 A CN202211438649 A CN 202211438649A CN 115700636 A CN115700636 A CN 115700636A
- Authority
- CN
- China
- Prior art keywords
- equipment
- parameters
- abnormal
- digital twin
- report
- 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
Images
Landscapes
- Testing And Monitoring For Control Systems (AREA)
Abstract
The application relates to a method, a device, equipment and a medium for equipment inspection and report generation based on digital twins, wherein the method comprises the following steps: acquiring current operating parameters of a plurality of devices and a digital twin model corresponding to each device; updating the parameters of each digital twin model based on the current operating parameters; judging whether equipment with running parameters which are not abnormal exists or not based on the current running parameters; if equipment with the running parameters which are not abnormal exists, simulating the running condition of the equipment with the running parameters which are not abnormal based on the digital twin model to obtain a prediction result; judging whether the equipment has abnormal operating parameters within preset time or not based on the prediction result; if so, acquiring the prediction time of the abnormal operation parameters of the equipment and the types of the abnormal operation parameters; and generating a routing inspection report based on the current operation parameters, the prediction time and the abnormal operation parameter type. The method and the device have the advantage that the potential problems can be found in time.
Description
Technical Field
The application relates to the technical field of equipment maintenance, in particular to a method, a device, equipment and a medium for equipment inspection and report generation based on digital twin.
Background
With the development of science and technology, the cross fusion trend is increasingly presented among disciplines, science and technology, and between natural science and human society and social science, and the science and technology deeply influences the national future fate and welfare of human life.
The technology is closely related to people's life, various production enterprises are no exception, the input quality can be ensured by polling equipment, and in the related technology, polling personnel are required to regularly poll the equipment and make a polling report through polling records.
Under normal conditions, only the current operation state of the equipment can be known through the inspection report, the equipment with the current problems can be found in time through the current operation state, but the equipment with the potential problems cannot be found, the preventive maintenance plan of the equipment management department for the equipment with the potential problems is influenced, and the condition of sudden failure of the equipment is caused.
Disclosure of Invention
In order to find out equipment with potential problems in time and reduce the sudden condition of equipment failure, the application provides an equipment inspection and report generation method, device, equipment and medium based on digital twin.
In a first aspect, the application provides a device inspection and report generation method based on digital twins, which adopts the following technical scheme:
a device inspection and report generation method based on digital twins comprises the following steps:
acquiring current operating parameters of a plurality of devices and a digital twin model for simulating the operating state corresponding to each device;
updating parameters of each of the digital twin models based on the current operating parameters;
judging whether equipment with running parameters which are not abnormal exists or not based on the current running parameters;
if equipment with the running parameters which are not abnormal exists, simulating the running condition of the equipment with the running parameters which are not abnormal based on the digital twin model to obtain a prediction result;
judging whether the equipment has abnormal operating parameters within preset time or not based on the prediction result;
if the equipment has abnormal operating parameters within the preset time, acquiring the predicted time and the abnormal operating parameter type of the equipment when the abnormal operating parameters occur;
and generating a patrol inspection report based on the current operation parameters, the prediction time and the abnormal operation parameter types.
By adopting the technical scheme, the future operation condition of the equipment with abnormal operation parameters is simulated through the digital twin model, and when the operation parameters of the equipment are abnormal within the preset time, the predicted time and the abnormal operation parameter types are written into the operation and maintenance inspection report, so that the equipment with potential problems can be conveniently and timely generated by a worker, the equipment with the potential problems can be early warned in advance, and the condition of sudden equipment failure can be reduced.
Optionally, the generating a polling report based on the current operation parameter, the predicted time, and the abnormal operation parameter type includes:
matching a polling report module based on the preset result;
acquiring video information of the digital twin model on the running condition of equipment with running parameters which are not abnormal;
processing the video information based on the polling report module to obtain a predicted video;
and generating the inspection report based on the matched inspection report module, the prediction video, the prediction time and the abnormal operation parameter type.
By adopting the technical scheme, the video, the prediction time and the abnormal operation parameter types are predicted, so that a user can know the possible conditions of equipment with abnormal operation parameters, and can process the conditions in time.
Optionally, before the simulating the operation condition of the device without the abnormal operation parameter based on the digital twin model, the method further includes:
acquiring a plurality of historical operation and maintenance inspection reports of equipment with abnormal operation parameters;
selecting at least one historical operation and maintenance inspection report from the plurality of historical operation and maintenance inspection reports, and taking the selected historical operation and maintenance inspection report as a comparison inspection report;
acquiring a first historical operating parameter in the comparison inspection report and a current operating parameter of the equipment;
calculating the time length from the generation time of the comparison inspection report to the current time;
acquiring a digital twin model corresponding to the equipment;
inputting the time length and the first historical operating parameter into the digital twin model for simulation to obtain a simulated operating parameter corresponding to the current time;
judging whether the simulation operation parameters are consistent with the current operation parameters;
if not, acquiring all second historical operating parameters in the historical operating parameter library;
and correcting the prediction parameters of the digital twin model based on the second historical operating parameters and the current operating parameters.
By adopting the technical scheme, whether the prediction parameters of the digital twin model are accurate or not is judged through the simulated operation parameters simulated by the digital twin model, and when the prediction parameters of the digital twin model are inaccurate, the prediction parameters of the digital twin model are corrected in time, so that the prediction accuracy of the digital twin model is improved.
Optionally, if there is a device with abnormal operating parameters, the method further includes:
the inspection report module is used for matching the abnormal operation parameters;
selecting a historical operation and maintenance inspection report adjacent to the current time from the historical operation and maintenance inspection reports;
acquiring a third history operation parameter in the selected history operation and maintenance inspection report;
inputting the third history operation parameter into the digital twin model, and simulating the operation process of equipment with abnormal operation parameters to obtain a simulated operation process;
generating an access flag to access the digital twin model;
associating the access mark with a digital twin model corresponding to equipment with abnormal operating parameters;
generating the patrol report based on the access flag and the current operating parameters.
By adopting the technical scheme, the digital twin model can be directly accessed through the access mark, so that a user can conveniently and intuitively know the condition of the equipment.
Optionally, after the generating the patrol inspection report based on the access flag and the current operating parameter, the method further includes:
acquiring a distribution diagram of equipment and an equipment image corresponding to the equipment with abnormal operation parameters;
marking the position of the equipment with abnormal operation parameters on the distribution diagram to obtain a marked distribution diagram;
marking a position corresponding to the abnormal operation parameter on the equipment image to obtain a marked image;
adding the label distribution map and the label image to the inspection report.
By adopting the technical scheme, the position of the abnormal equipment can be conveniently and quickly determined by maintenance personnel through the mark distribution map and the mark image, and the maintenance efficiency of the maintenance personnel is improved.
Optionally, after the generating the patrol report based on the access flag and the current operating parameter, the method further includes:
judging whether the equipment with abnormal operation parameters can operate or not;
if the equipment with the abnormal operating parameters can operate, acquiring basic information corresponding to all equipment with the abnormal operating parameters;
judging whether equipment of the same production line exists or not based on the basic information;
if yes, acquiring digital twin models of all equipment corresponding to the production line;
simulating the production process of the product based on the digital twin model to obtain the total production amount of the product;
acquiring the priority of equipment maintenance based on the total production amount;
adding the priority of equipment maintenance to the inspection report.
Optionally, the method further includes:
acquiring the maintenance times and the life cycle of each device;
giving different weights to the maintenance times and the life cycle;
calculating the health level of the equipment according to the weight of the maintenance times and the life cycle;
determining a period for each of the devices to generate a patrol report based on the health level.
In a second aspect, the present application provides a device for equipment inspection and report generation based on digital twins, which adopts the following technical solutions:
a device for equipment inspection and report generation based on digital twinning comprises:
the device comprises an acquisition module, a simulation module and a control module, wherein the acquisition module is used for acquiring the operating parameters of a plurality of devices and a digital twin model for simulating the operating state corresponding to each device;
an updating module for updating the parameters of each of the digital twin models based on the operating parameters;
the first judgment module is used for judging whether equipment with faults exists or not based on the operation parameters; if equipment which does not have faults exists, simulating the running condition of the equipment which does not have faults based on the digital twin model to obtain a prediction result;
the second judgment module is used for judging whether the equipment which does not have faults breaks down within the preset time or not based on the prediction result; if the equipment which does not have the fault breaks down within the preset time, acquiring the failure prediction time and the failure type of the equipment which does not break down;
and the generation module is used for generating a routing inspection report based on the operation parameters, the prediction time and the type of the fault.
By adopting the technical scheme, the future operation condition of the equipment with abnormal operation parameters is simulated through the digital twin model, and when the operation parameters of the equipment are abnormal within the preset time, the predicted time and the abnormal operation parameter types are written into the operation and maintenance inspection report, so that the equipment with potential problems can be conveniently and timely generated by a worker, the equipment with the potential problems can be early warned in advance, and the condition of sudden equipment failure can be reduced.
In a third aspect, the present application provides an electronic device, which adopts the following technical solutions:
an electronic device comprising a processor and a memory, the processor coupled with the memory;
the processor is configured to execute the computer program stored in the memory to cause the electronic device to perform the method according to any of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solutions:
a computer readable storage medium comprising a computer program or instructions which, when run on a computer, cause the computer to perform the method of any of the first aspects.
Drawings
Fig. 1 is a flow chart of a method for equipment inspection and report generation based on digital twins, which is embodied in the embodiment of the present application.
Fig. 2 is a block diagram of a device inspection and report generation apparatus 200 based on digital twinning according to an embodiment of the present application.
Fig. 3 is a block diagram of an electronic device 300 embodied in an embodiment of the present application.
Detailed Description
The present application is described in further detail below with reference to the attached drawings.
The present embodiment is only for explaining the present application, and it is not limited to the present application, and those skilled in the art can make modifications of the present embodiment without inventive contribution as needed after reading the present specification, but all of them are protected by patent law within the scope of the claims of the present application.
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In addition, the term "and/or" herein is only one kind of association relationship describing an associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter associated objects are in an "or" relationship, unless otherwise specified.
The embodiments of the present application will be described in further detail with reference to the drawings attached hereto.
The embodiment of the application provides a device inspection and report generation method based on a digital twin, which can be executed by an electronic device, wherein the electronic device can be a server or a terminal device, the server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, and a cloud server providing cloud computing service. The terminal device may be, but is not limited to, a smart phone, a tablet computer, a desktop computer, etc.
As shown in fig. 1, a method for generating a device patrol and report based on digital twin includes the following steps (steps S101 to S107):
step S101, obtaining current operation parameters of a plurality of devices and a digital twin model for simulating an operation state corresponding to each device;
step S102, updating the parameters of each digital twin model based on the current operation parameters;
in this embodiment, each device is installed with a detection device, wherein the detection device includes a plurality of sensors for detecting operating parameters of the device, wherein the types of the sensors include, but are not limited to, a vibration sensor, an ultrasonic sensor, a magnetic flux sensor, and a temperature sensor, the detection device further includes a microphone, which can be selected according to the operating attribute characteristics of the device, and the device may be a power plant device or a production device, which is not particularly limited.
Each device corresponds to a digital twin model, and the digital twin model can simulate the operation condition of the device according to the operation parameters of the device.
The method for constructing the digital twin model comprises the steps of constructing a virtual model corresponding to each device by using a 3D modeling tool according to the operation parameters of the device, and transmitting the operation parameters of the device to the virtual model in real time, so that the operation process of the device is simulated.
Step S103, judging whether equipment with abnormal operation parameters exists or not based on the current operation parameters; if yes, go to step S104;
in this embodiment, the electronic device refers to the acquired operation parameter as a current operation parameter, when the electronic device acquires the current operation parameter, the current operation parameter is compared with a parameter threshold, and when the current operation parameter exceeds the parameter threshold, a device corresponding to the current operation parameter exceeding the parameter threshold is referred to as a device with an abnormal operation parameter, otherwise, the device with an abnormal operation parameter is referred to as a device without an abnormal operation parameter.
It should be noted that each operating parameter of each device corresponds to a parameter threshold, and when the operating parameter exceeds the parameter threshold, the device may be damaged, which affects the normal operation of the device.
Step S104, simulating the operation condition of the equipment with the abnormal operation parameters based on the digital twin model to obtain a prediction result;
before simulating the operation condition of the equipment with the abnormal operation parameters, the simulation condition of the digital twin needs to be verified.
Specifically, the method comprises the following steps (step a-step i):
step a, obtaining a plurality of historical operation and maintenance patrol reports of equipment with abnormal operation parameters;
b, selecting at least one historical operation and maintenance inspection report from the plurality of historical operation and maintenance inspection reports, and taking the selected historical operation and maintenance inspection report as a comparison inspection report;
step c, acquiring and comparing a first historical operating parameter in the inspection report and a current operating parameter of the equipment;
in this embodiment, all the historical operation and maintenance inspection reports of each device are stored in the electronic device, the multiple historical operation and maintenance inspection reports are sorted based on the generation time of the historical operation and maintenance inspection reports, one historical operation and maintenance inspection report adjacent to the current time can be selected, and multiple historical operation and maintenance inspection reports can also be selected, which is not specifically limited.
In this embodiment, an example of selecting one of the historical operation and maintenance inspection reports is described.
For example, the current time is 12 days at 5 months in 2022, and the generation times corresponding to the historical operation and maintenance inspection reports are 8 days at 4 months in 2022, 20 days at 4 months in 2022 and 8 days at 5 months in 2022, respectively, so that the historical operation and maintenance inspection report at 8 days at 5 months in 2022 is selected.
Step d, calculating the time length of the time of the comparison inspection report from the current time;
in this embodiment, the generation time corresponding to the selected historical operation and maintenance inspection report is 2022 years, 5 months and 8 days, taking the current time being 2022 years, 5 months and 12 days as an example, and the time length is four days.
Step e, acquiring a digital twin model corresponding to the equipment;
step f, inputting the time length and the first historical operating parameter into a digital twin model for simulation to obtain a simulated operating parameter corresponding to the current time;
for example, the device a is a device whose operation parameters are not abnormal, at this time, the first historical operation parameter and the time length in the historical operation and maintenance inspection report corresponding to the device a are input into the digital twin model of the device a, and the digital twin model simulates the operation condition of the device a within the time length to obtain simulated operation parameters.
Step g, judging whether the simulation operation parameters are consistent with the current operation parameters; if not, entering step h;
step h, acquiring all second historical operating parameters in the historical operating parameter library;
and i, correcting the prediction parameters of the digital twin model based on the second historical operating parameters and the current operating parameters.
It should be noted that the electronic device can acquire the operation parameters of each device in real time, and store the operation parameters in the historical operation parameter library.
In this embodiment, when the simulated operation parameters are not consistent with the current operation parameters, all the second historical operation parameters in the historical operation parameter library are input into the trained neural network model, and the prediction parameters of the digital twin model are corrected, so that the simulated operation parameters simulated by the digital twin model are consistent, and the simulation of the future operation condition of the equipment by the digital twin model is more accurate.
And inputting the current operation parameters of the equipment of which the parameters are not abnormal into the corrected digital twin model, and simulating the future operation condition of the equipment to obtain the time when the operation parameters of the equipment are abnormal.
Step S105, judging whether the equipment has abnormal operation parameters within preset time or not based on the prediction result; if yes, go to step S106;
step S106, obtaining the prediction time of the abnormal operation parameters of the equipment and the types of the abnormal operation parameters;
and step S107, generating a routing inspection report based on the current operation parameters, the prediction time and the abnormal operation parameter type.
In this embodiment, the preset time is described by taking two days as an example, for example, when the operation parameter of the digital twin model simulation device is abnormal after three days, the operation parameter of the determination device is not abnormal within the preset time, and when the operation parameter of the digital twin model simulation device is abnormal after one day, the operation parameter of the determination device is abnormal within the preset time.
At the moment, the predicted time and the abnormal operation parameter type corresponding to the equipment with the abnormal operation parameters in the preset time are extracted.
It should be noted that, in this embodiment, the types of the devices include three types, namely an abnormal device, a device with a potential problem, and a normal device, where the abnormal device is a device in which at least one operation parameter of the device exceeds a parameter threshold, the device with the potential problem is a device in which an operation parameter exceeds a parameter threshold within a preset time, and the normal device is a device in which each operation parameter of the device is smaller than the parameter threshold within the preset time.
Wherein each device corresponds to a patrol reporting module.
In this embodiment, the generation of the polling report by the different types of devices will be described separately.
Equipment with potential problem
Specifically, the polling report module is matched based on a preset result; acquiring video information of the running condition of the digital twin model on equipment with running parameters which are not abnormal; processing the video information based on the polling report module to obtain a predicted video; and generating an inspection report based on the matched inspection report module, the prediction video, the prediction time and the abnormal operation parameter type.
In this embodiment, an inspection report template corresponding to a device with a potential problem is referred to as a first template, where the first template includes a current operation parameter display area and an operation parameter prediction area, where the operation parameter prediction area includes a prediction video, a prediction time, and an abnormal operation parameter type.
And acquiring video information, prediction time and abnormal operation parameter types through a digital twin model corresponding to the equipment. The video information is a recorded video in the simulation process of the digital twin model, the predicted video is a video obtained by cutting the recorded video according to the time requirement in the first template, for example, the recorded video is 10 minutes, the video display information of the operation parameter prediction area in the first template is 8 minutes, the recorded video is cut to obtain a video of 8 minutes, and the video of 8 minutes is used as the predicted video to be displayed in the first template.
(II) abnormality device
Specifically, the polling report module is matched with the abnormal running parameters; selecting a historical operation and maintenance inspection report adjacent to the current time from the historical operation and maintenance inspection reports; acquiring a third history operation parameter in the selected history operation and maintenance patrol inspection report; inputting the third history operation parameter into the digital twin model, and simulating the operation process of the equipment with abnormal operation parameters to obtain a simulated operation process; generating an access flag to access the digital twin model; associating the access mark with a digital twin model corresponding to the equipment with abnormal operating parameters; generating a patrol report based on the access flag and the current operating parameters.
In this embodiment, the patrol inspection report template corresponding to the abnormal device is referred to as a second template, and the second template includes a current parameter display area and a parameter abnormality analysis area, where the parameter abnormality analysis area includes a simulation process of an abnormal process of operating parameters of the device based on a digital twin model.
In this embodiment, the starting operation parameter in the simulation process of the digital twin model is a third history operation parameter of a historical operation and maintenance inspection report adjacent to the current time, the third history operation parameter is input into the digital twin model, the operation process of the device is modeled, and an access mark is generated in the parameter abnormality analysis area, where the access mark may be a button or a hyperlink, and is not specifically limited to this, so that the simulation process of the digital twin model can be viewed through the access mark, and the digital twin model can be enlarged and disassembled, and a user can conveniently and visually view the device with abnormal operation parameters.
The second template further comprises an equipment display area, wherein the content generated by the equipment display area is as follows:
specifically, a distribution diagram of the equipment and an equipment image corresponding to the equipment with abnormal operation parameters are obtained; marking the position of the equipment with abnormal operation parameters on the distribution diagram to obtain a marked distribution diagram; marking a position corresponding to the abnormal operation parameter on the equipment image to obtain a marked image; and adding the label distribution map and the label image to the patrol report.
In this embodiment, a distribution diagram of device distribution and a display diagram of each part of each device are stored in the electronic device, and when a current operating parameter of the device is abnormal, a position of the device is determined in the distribution diagram, and a marking manner of the position may be circled or another manner may be adopted, which is not specifically limited.
And analyzing the abnormal equipment to obtain the position of the abnormal operation parameter, and acquiring an equipment image of the corresponding position of the corresponding equipment, wherein the marking mode can be circle drawing, and other modes can also be adopted, and the method is not particularly limited.
And displaying the mark distribution map and the mark image in a device display area.
In this embodiment, the second template further includes a display area of the priority of maintenance, wherein the content of the display area of the priority of maintenance is generated as follows:
judging whether equipment with abnormal operation parameters can operate or not; if the equipment with the abnormal operation parameters can operate, acquiring basic information corresponding to all the equipment with the abnormal operation parameters; judging whether equipment of the same production line exists or not based on the basic information; if yes, acquiring digital twin models of all devices corresponding to the production line; simulating the production process of the product based on the digital twin model to obtain the total production amount of the product; determining the priority of equipment maintenance based on the total production; adding the priority of equipment maintenance to the patrol report.
In this embodiment, the electronic device summarizes the abnormal devices, and each device corresponds to a piece of basic information, which includes, but is not limited to, a unit number, a specialty, an area, and a production line to which the device belongs. The method comprises the steps of obtaining digital twin models corresponding to all devices in a production line corresponding to abnormal devices, inputting current operation parameters of each device in the production line into the digital twin models, simulating the future operation process of the devices, obtaining the total production quantity of the devices when the digital twin models can operate, calculating the production quantity difference value between the total production quantity and a standard quantity, judging whether the difference value is within a preset range, if so, determining the priority of device maintenance as a second priority, otherwise, determining the priority of device maintenance as a first priority, wherein the first priority is higher than the second priority, and preferentially maintaining the devices with the first priority.
(III) Normal Equipment
In this embodiment, the patrol report template corresponding to the normal device is referred to as a third template, and the second template includes the current parameter display area.
Wherein, every normal equipment all corresponds a health level, formulates the generating cycle of different operation and maintenance inspection reports through health level.
Specifically, the maintenance frequency, the importance level and the life cycle of each device are obtained; giving different weights to the maintenance times, the importance levels and the life cycles; calculating the health level of the equipment according to the maintenance times, the importance level and the weight of the life cycle; and determining the period for generating the operation and maintenance inspection report by each device based on the health level.
For example, the health level comprises a first level, a second level and a third level, and when the health level is at the first level, an operation and maintenance inspection report is generated once in three days; when the current level is at a second level, generating a primary operation and maintenance inspection report in five days; and when the monitoring system is at the third level, generating an operation and maintenance inspection report once in seven days.
The health grade is calculated as follows:
for example, dividing the life cycle, calculating the proportion of the rest life cycle of the equipment in the total life cycle, and weighing the weight value to be 30% when the proportion is in a first interval; the weight value is 20% when the proportion is in the second interval; the weight value is 10% when the ratio is in the third interval. A first interval [1/2,1], a second interval (3/1,1/2) and a first interval [0,3/1].
The weight of the maintenance times is 10% when the maintenance times are less than 5 times, 20% when the maintenance times are 5-10 times and 30% when the maintenance times are more than 10 times.
And summing the two weights, wherein when the weight value is less than or equal to 20%, the weight value is a first grade, 20% -00% of the weight value is a second grade, and 40% -60% of the weight value is a third grade.
Fig. 2 is a block diagram illustrating a structure of a device inspection and report generation apparatus 200 based on digital twins according to the present disclosure. As shown in fig. 2, the apparatus patrol inspection and report generation device 200 based on the digital twin mainly includes:
an obtaining module 201, configured to obtain operating parameters of a plurality of devices and a digital twin model for simulating an operating state corresponding to each device;
an updating module 202 for updating the parameters of each digital twin model based on the operating parameters;
a first judging module 203, configured to judge whether there is a failed device based on the operation parameter; if equipment which does not have faults exists, simulating the running condition of the equipment which does not have faults based on the digital twin model to obtain a prediction result;
a second judging module 204, configured to judge whether a device that does not fail will fail within a preset time based on the prediction result; if the equipment which does not have the fault breaks down within the preset time, acquiring the failure prediction time and the failure type of the equipment which does not break down;
a generation module 205 for generating a patrol report based on the operating parameters, the predicted time, and the type of fault
As an optional implementation manner of this embodiment, the generating module 205 includes:
the matching sub-module is used for matching the routing inspection reporting module based on a preset result;
the acquisition submodule is used for acquiring the video information of the running condition of the digital twin model on the equipment with the running parameters not abnormal;
the processing obtaining sub-module is used for processing the video information based on the patrol report module to obtain a prediction video;
a generation submodule for generating a patrol inspection report based on the matched patrol inspection report module, the prediction video, the prediction time and the abnormal operation parameter type
As an optional implementation manner of this embodiment, the device inspection and report generation apparatus 200 based on digital twin further includes:
the report acquisition module is used for acquiring a plurality of historical operation and maintenance patrol inspection reports of the equipment with the abnormal operation parameters before simulating the operation condition of the equipment with the abnormal operation parameters based on the digital twin model;
the selecting module is used for selecting at least one historical operation and maintenance inspection report from the plurality of historical operation and maintenance inspection reports, and taking the selected historical operation and maintenance inspection report as a comparison inspection report;
the parameter acquisition module is used for acquiring and comparing a first historical operating parameter in the routing inspection report and a current operating parameter of the equipment;
the first calculation module is used for calculating and comparing the time length from the generation time of the routing inspection report to the current time;
the model acquisition module is used for acquiring a digital twin model corresponding to the equipment;
the input simulation module is used for inputting the time length and the first historical operating parameter into the digital twin model for simulation to obtain a simulated operating parameter corresponding to the current time;
the parameter judging module is used for judging whether the simulation operation parameters are consistent with the current operation parameters; if not, acquiring all second historical operating parameters in the historical operating parameter library;
and the correction module is used for correcting the prediction parameters of the digital twin model based on the second historical operating parameters and the current operating parameters.
As an optional implementation manner of this embodiment, the device inspection and report generation apparatus 200 based on digital twin further includes:
the matching module is used for matching the routing inspection reporting module with the abnormal operation parameters if the equipment with the abnormal operation parameters exists;
the inspection report selecting module is used for selecting a historical operation and maintenance inspection report adjacent to the current time from the historical operation and maintenance inspection reports;
the operation parameter acquisition module is used for acquiring a third history operation parameter in the selected history operation and maintenance patrol inspection report;
the simulation obtaining module is used for inputting the third history running parameters into the digital twin model, simulating the running process of equipment with abnormal running parameters, and obtaining a simulated running process;
the mark generation module is used for generating an access mark for accessing the digital twin model;
the association module is used for associating the access mark with a digital twin model corresponding to the equipment with abnormal operating parameters;
and the report generating module is used for generating the patrol inspection report based on the access mark and the current operating parameter.
As an optional implementation manner of this embodiment, the device inspection and report generation apparatus 200 based on digital twin further includes:
the image acquisition module is used for acquiring a distribution map of the equipment and an equipment image corresponding to the equipment with abnormal operation parameters after generating a patrol report based on the access mark and the current operation parameters;
the first marking module is used for marking the position of the equipment with abnormal operation parameters on the distribution diagram to obtain a marking distribution diagram;
the second marking module is used for marking the position corresponding to the abnormal operation parameter on the equipment image to obtain a marked image;
and the first adding module is used for adding the mark distribution map and the mark image into the patrol report.
As an optional implementation manner of this embodiment, the device inspection and report generation apparatus 200 based on digital twin further includes:
the operation judgment module is used for judging whether equipment with abnormal operation parameters can operate or not after generating the inspection report based on the access mark and the current operation parameters; if the equipment with the abnormal operation parameters can operate, acquiring basic information corresponding to all the equipment with the abnormal operation parameters;
the equipment judgment module is used for judging whether equipment of the same production line exists or not based on the basic information; if yes, acquiring digital twin models of all equipment corresponding to the production line;
the production total quantity acquisition module is used for simulating the production process of the product based on the digital twin model to obtain the production total quantity of the product;
the first determining module is used for determining the priority of equipment maintenance based on the total production amount;
and adding the second adding module for adding the priority of equipment maintenance to the patrol report.
As an optional implementation manner of this embodiment, the device inspection and report generation apparatus 200 based on digital twin further includes:
the equipment information acquisition module is used for acquiring the maintenance times and the life cycle of each piece of equipment;
the giving module is used for giving different weights to the maintenance frequency and the life cycle;
the second calculation module is used for calculating the health level of the equipment according to the maintenance times and the weight of the life cycle;
and the second determining module is used for determining the period of generating the patrol inspection report by each device based on the health level.
The functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part. The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially or partially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing an electronic device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the digital twin-based device inspection and report generation method according to the embodiments of the present application.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system, the apparatus and the module described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
Fig. 3 is a block diagram of an electronic device 300 according to an embodiment of the present disclosure. As shown in fig. 3, electronic device 300 includes memory 301, processor 302, and communication bus 303; the memory 301 and the processor 302 are connected by a communication bus 303. The memory 301 has stored thereon a digital twin based device patrol and report generation method that can be loaded and executed by the processor 302 as provided in the above-described embodiments.
The memory 301 may be used to store instructions, programs, code sets or instruction sets. The memory 301 may include a storage program area and a storage data area, wherein the storage program area may store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing the digital twin-based device patrol and report generation method provided by the above-described embodiments, and the like; the storage data area may store data and the like involved in the digital twin-based device inspection and report generation method provided by the above-described embodiment.
The communication bus 303 may include a path that carries information between the aforementioned components. The communication bus 303 may be a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The communication bus 303 may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 3, but this does not indicate only one bus or one type of bus.
Embodiments of the present application provide a computer-readable storage medium storing a computer program that can be loaded by a processor and execute the digital twin-based device inspection and report generation method provided in the above embodiments.
In this embodiment, the computer readable storage medium may be a tangible device that retains and stores instructions for use by an instruction execution device. The computer readable storage medium may be, but is not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any combination of the foregoing. In particular, the computer readable storage medium may be a portable computer diskette, a hard disk, a U-disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a podium random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, an optical disk, a magnetic disk, a mechanical coding device, and any combination thereof.
The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
The foregoing description is only exemplary of the preferred embodiments of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the application referred to in the present application is not limited to the embodiments with a particular combination of the above-mentioned features, but also encompasses other embodiments with any combination of the above-mentioned features or their equivalents without departing from the spirit of the application. For example, the above features may be replaced with (but not limited to) features having similar functions as those described in this application.
Claims (10)
1. A device inspection and report generation method based on digital twins is characterized by comprising the following steps:
acquiring current operating parameters of a plurality of devices and a digital twin model for simulating the operating state corresponding to each device;
updating parameters of each of the digital twin models based on the current operating parameters;
judging whether equipment with running parameters which are not abnormal exists or not based on the current running parameters;
if equipment with the running parameters not abnormal exists, simulating the running condition of the equipment with the running parameters not abnormal based on the digital twin model to obtain a prediction result;
judging whether the equipment has abnormal operating parameters within preset time or not based on the prediction result;
if the equipment has abnormal operation parameters within the preset time, acquiring the predicted time and the abnormal operation parameter type of the equipment when the abnormal operation parameters occur;
and generating a routing inspection report based on the current operation parameter, the prediction time and the abnormal operation parameter type.
2. The method of claim 1, wherein generating a patrol report based on the current operating parameters, the predicted time, and the type of abnormal operating parameters comprises:
matching a polling report module based on the preset result;
acquiring video information of the digital twin model on the running condition of equipment with running parameters which are not abnormal;
processing the video information based on the polling report module to obtain a predicted video;
and generating the inspection report based on the matched inspection report module, the prediction video, the prediction time and the abnormal operation parameter type.
3. The method according to claim 1 or 2, wherein before the simulating the operation condition of the equipment with the operation parameters not abnormal based on the digital twin model, the method further comprises:
acquiring a plurality of historical operation and maintenance inspection reports of equipment with abnormal operation parameters;
selecting at least one historical operation and maintenance inspection report from the plurality of historical operation and maintenance inspection reports, and taking the selected historical operation and maintenance inspection report as a comparison inspection report;
acquiring a first historical operating parameter in the comparison inspection report and a current operating parameter of the equipment;
calculating the time length from the generation time of the comparison inspection report to the current time;
acquiring a digital twin model corresponding to the equipment;
inputting the time length and the first historical operating parameter into the digital twin model for simulation to obtain a simulated operating parameter corresponding to the current time;
judging whether the simulation operation parameters are consistent with the current operation parameters;
if not, acquiring all second historical operating parameters in the historical operating parameter library;
and correcting the prediction parameters of the digital twin model based on the second historical operating parameters and the current operating parameters.
4. The method of claim 1, wherein if there is a device with abnormal operating parameters, the method further comprises:
the inspection report module is used for matching the abnormal operation parameters;
selecting a historical operation and maintenance inspection report adjacent to the current time from the historical operation and maintenance inspection reports;
acquiring a third history operation parameter in the selected history operation and maintenance patrol inspection report;
inputting the third history operation parameter into the digital twin model, and simulating the operation process of equipment with abnormal operation parameters to obtain a simulated operation process;
generating an access flag to access the digital twin model;
associating the access mark with a digital twin model corresponding to equipment with abnormal operating parameters;
generating the patrol report based on the access flag and the current operating parameters.
5. The method of claim 4, further comprising, after the generating the patrol report based on the access flag and current operating parameters:
acquiring a distribution diagram of equipment and an equipment image corresponding to the equipment with abnormal operation parameters;
marking the position of the equipment with abnormal operation parameters on the distribution diagram to obtain a marked distribution diagram;
marking a position corresponding to the abnormal operation parameter on the equipment image to obtain a marked image;
adding the label distribution map and the label image to the inspection report.
6. The method of claim 4, further comprising, after the generating the patrol report based on the access flag and current operating parameters:
judging whether the equipment with the abnormal operation parameters can operate or not;
if the equipment with abnormal operating parameters can operate, acquiring basic information corresponding to all equipment with abnormal operating parameters;
judging whether equipment of the same production line exists or not based on the basic information;
if yes, acquiring digital twin models of all equipment corresponding to the production line;
simulating the production process of the product based on the digital twin model to obtain the total production amount of the product;
determining a priority for equipment maintenance based on the total production;
adding the priority of equipment maintenance to the inspection report.
7. The method of claim 1, further comprising:
acquiring the maintenance times and the life cycle of each device;
giving different weights to the maintenance times and the life cycle;
calculating the health level of the equipment according to the weight of the maintenance times and the life cycle;
determining a period for which each of the devices generates a patrol report based on the health level.
8. The utility model provides a device is patrolled and examined and report generation device based on digit twin, its characterized in that includes:
the device comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring the operating parameters of a plurality of devices and a digital twin model for simulating the operating state corresponding to each device;
an updating module for updating the parameters of each of the digital twin models based on the operating parameters;
the first judgment module is used for judging whether equipment with faults exists or not based on the operation parameters; if equipment which does not have faults exists, simulating the running condition of the equipment which does not have faults based on the digital twin model to obtain a prediction result;
the second judgment module is used for judging whether the equipment which does not have faults breaks down within the preset time or not based on the prediction result; if the equipment which does not have the fault breaks down within the preset time, acquiring the failure prediction time and the failure type of the equipment which does not break down;
and the generation module is used for generating a routing inspection report based on the operation parameters, the prediction time and the type of the fault.
9. An electronic device comprising a processor and a memory, the processor coupled with the memory;
the processor is configured to execute a computer program stored in the memory to cause the electronic device to perform the method of any of claims 1 to 7.
10. A computer-readable storage medium comprising a computer program or instructions which, when run on a computer, cause the computer to carry out the method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211438649.2A CN115700636A (en) | 2022-11-17 | 2022-11-17 | Equipment inspection and report generation method, device, equipment and medium based on digital twin |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211438649.2A CN115700636A (en) | 2022-11-17 | 2022-11-17 | Equipment inspection and report generation method, device, equipment and medium based on digital twin |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115700636A true CN115700636A (en) | 2023-02-07 |
Family
ID=85121183
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211438649.2A Pending CN115700636A (en) | 2022-11-17 | 2022-11-17 | Equipment inspection and report generation method, device, equipment and medium based on digital twin |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115700636A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115941453A (en) * | 2023-02-23 | 2023-04-07 | 浙江德塔森特数据技术有限公司 | Machine room alarm processing method and device based on digital twin, machine room and medium |
| CN115983901A (en) * | 2023-03-17 | 2023-04-18 | 山东捷瑞数字科技股份有限公司 | Equipment accessory demand prediction method, system and medium based on digital twin |
| CN116048124A (en) * | 2023-02-23 | 2023-05-02 | 北京思维实创科技有限公司 | Unmanned plane subway tunnel inspection method and device, computer equipment and storage medium |
| CN116956720A (en) * | 2023-07-19 | 2023-10-27 | 安徽斯维尔信息科技有限公司 | Industrial digital twin simulation operation and maintenance system |
-
2022
- 2022-11-17 CN CN202211438649.2A patent/CN115700636A/en active Pending
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115941453A (en) * | 2023-02-23 | 2023-04-07 | 浙江德塔森特数据技术有限公司 | Machine room alarm processing method and device based on digital twin, machine room and medium |
| CN116048124A (en) * | 2023-02-23 | 2023-05-02 | 北京思维实创科技有限公司 | Unmanned plane subway tunnel inspection method and device, computer equipment and storage medium |
| CN115941453B (en) * | 2023-02-23 | 2023-06-02 | 浙江德塔森特数据技术有限公司 | Machine room alarm processing method and device based on digital twin, machine room and medium |
| CN115983901A (en) * | 2023-03-17 | 2023-04-18 | 山东捷瑞数字科技股份有限公司 | Equipment accessory demand prediction method, system and medium based on digital twin |
| CN116956720A (en) * | 2023-07-19 | 2023-10-27 | 安徽斯维尔信息科技有限公司 | Industrial digital twin simulation operation and maintenance system |
| CN116956720B (en) * | 2023-07-19 | 2024-01-30 | 安徽斯维尔信息科技有限公司 | Industrial digital twin simulation operation and maintenance system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115700636A (en) | Equipment inspection and report generation method, device, equipment and medium based on digital twin | |
| CN109947088B (en) | Equipment fault early warning system based on model full life cycle management | |
| CN108375715B (en) | Power distribution network line fault risk day prediction method and system | |
| Wagner | A Bayesian network approach to assess and predict software quality using activity-based quality models | |
| CN106020154A (en) | Safe dynamic health assessment method and assessment system for ethylene production | |
| CN105868373B (en) | Method and device for processing key data of power business information system | |
| US11906112B2 (en) | Methods for safety management of compressors in smart gas pipeline network and internet of things systems thereof | |
| CN114266944B (en) | Rapid model training result checking system | |
| CN113099476B (en) | Network quality detection method, device, equipment and storage medium | |
| CN114879613A (en) | Industrial control system information security attack risk assessment method and system | |
| CN115689396A (en) | Pollutant discharge control method, device, equipment and medium | |
| CN114936801A (en) | Distribution network dispatching operation management method based on big data | |
| JP2009086896A (en) | Failure prediction system and failure prediction method for computer | |
| CN112580858A (en) | Equipment parameter prediction analysis method and system | |
| CN115409283A (en) | Equipment failure prediction method, equipment failure prediction device, equipment and storage medium | |
| CN112463530A (en) | Anomaly detection method and device for micro-service system, electronic equipment and storage medium | |
| CN117664281B (en) | Ultrasonic water meter fault detection and automatic calibration method and system based on Internet of Things | |
| CN114338348A (en) | Intelligent alarm method, device, equipment and readable storage medium | |
| CN113093670A (en) | Instrument control state monitoring method, system and monitoring platform | |
| CN112598319A (en) | Intelligent bridge operation and maintenance management method and system based on BIM, computer equipment and storage medium | |
| CN113792421B (en) | TPM equipment management data processing system and method based on digital twinning | |
| CN113608953B (en) | Test data generation method and device, electronic equipment and readable storage medium | |
| CN106485526A (en) | A kind of diagnostic method of data mining model and device | |
| CN115358336A (en) | Power utilization abnormity detection method and device and electronic equipment | |
| CN110688273B (en) | Classification model monitoring method and device, terminal and computer storage medium |
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 |