CN117273323A - Digital twinning-based power equipment management method and system - Google Patents
Digital twinning-based power equipment management method and system Download PDFInfo
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- G01R31/1263—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation
- G01R31/1272—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation of cable, line or wire insulation, e.g. using partial discharge measurements
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- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
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Abstract
The disclosure provides a digital twinning-based power equipment management method and a digital twinning-based power equipment management system, and relates to the technical field of power equipment management, wherein the method comprises the following steps: acquiring equipment composition structure and equipment operation data of target ultra-high voltage power equipment in a target area; constructing a target digital twin model; obtaining vibration intensity data; obtaining temperature distribution data; obtaining corona discharge data; obtaining a seed point set; the method comprises the steps of obtaining an abnormal identification point, managing an insulating layer of a target ultra-high voltage power device, solving the technical problems that in the prior art, the management monitoring dimension of the insulating layer of the ultra-high voltage power device is single, and further defect management accuracy and management efficiency of the insulating layer are poor, realizing defect identification of the insulating layer of the ultra-high voltage power device, improving the defect management efficiency of the insulating layer of the ultra-high voltage power device, and further guaranteeing the safe operation of the ultra-high voltage power device.
Description
Technical Field
The disclosure relates to the technical field of power equipment management, in particular to a power equipment management method and system based on digital twinning.
Background
With the development of technology, impact energy loads such as wind power and photovoltaic of a novel power system start to enter a power transmission and distribution system, the application of ultra-high voltage power equipment is greatly promoted in the construction of the novel power system, and the cost of carrying out on-site operation and maintenance management on the ultra-high voltage power equipment is high, so that the digital twin technology can be applied to the operation and maintenance management of the ultra-high voltage power equipment.
At present, the technical problems of poor accuracy and management efficiency of defect management of an insulating layer caused by single management monitoring dimension of the insulating layer of ultra-high voltage power equipment exist in the prior art.
Disclosure of Invention
The disclosure provides a digital twinning-based power equipment management method and system, which are used for solving the technical problems in the prior art that the accuracy and the management efficiency of defect management of an insulating layer are poor due to single management monitoring dimension of the insulating layer of ultra-high voltage power equipment.
According to a first aspect of the present disclosure, there is provided a digital twinning-based power equipment management method, comprising: acquiring equipment composition structure and equipment operation data of target ultra-high voltage power equipment in a target area; constructing a target digital twin model, wherein the target digital twin model is a digital simulation model obtained based on a digital twin technology according to the equipment composition structure and the equipment operation data; vibration intensity data are obtained, and vibration signals of the target ultra-high voltage power equipment are acquired through a vibration sensor; acquiring temperature distribution data, wherein the temperature distribution data are acquired by acquiring the temperature distribution data of the target ultra-high voltage power equipment through an infrared thermal imaging device; corona discharge data are obtained, and the corona discharge data are obtained by carrying out corona discharge monitoring on the target ultra-high voltage power equipment through an ultraviolet imaging device; according to the vibration intensity data, the temperature distribution data and the corona discharge data, seed points are automatically selected to obtain a seed point set; and identifying the target digital twin model according to the seed point set to obtain an abnormal identification point, and managing an insulating layer of the target ultra-high voltage power equipment according to the abnormal identification point.
According to a second aspect of the present disclosure, there is provided a digital twinning-based power device management system comprising: the device data acquisition module is used for acquiring device composition structures and device operation data of the target ultra-high voltage power devices in the target area; the digital twin model construction module is used for constructing a target digital twin model, and the target digital twin model is a digital simulation model obtained according to the equipment composition structure and the equipment operation data based on a digital twin technology; the vibration signal acquisition module is used for acquiring vibration intensity data, and the vibration intensity data is acquired by acquiring the vibration signal of the target ultra-high voltage power equipment through a vibration sensor; the temperature data acquisition module is used for acquiring temperature distribution data, and the temperature distribution data are acquired by acquiring the temperature distribution data of the target ultra-high voltage power equipment through an infrared thermal imaging device; the corona data acquisition module is used for acquiring corona discharge data, and the corona discharge data is acquired by carrying out corona discharge monitoring on the target ultrahigh voltage power equipment through an ultraviolet imaging device; the seed point selection module is used for automatically selecting seed points according to the vibration intensity data, the temperature distribution data and the corona discharge data to obtain a seed point set; and the insulating layer management module is used for identifying the target digital twin model according to the seed point set, obtaining an abnormal identification point and managing the insulating layer of the target ultra-high voltage power equipment according to the abnormal identification point.
According to one or more technical schemes adopted by the present disclosure, the following beneficial effects can be achieved:
1. the method comprises the steps of obtaining equipment composition structure and equipment operation data of target ultra-high voltage power equipment in a target area, constructing a target digital twin model, obtaining vibration intensity data, acquiring vibration signals of the target ultra-high voltage power equipment through a vibration sensor, obtaining temperature distribution data, obtaining corona discharge data, automatically selecting seed points according to the vibration intensity data, the temperature distribution data and the corona discharge data, obtaining a seed point set, identifying the target digital twin model according to the seed point set, obtaining an abnormal identification point, managing an insulating layer of the target ultra-high voltage power equipment according to the abnormal identification point, realizing defect identification of the insulating layer of the ultra-high voltage power equipment, facilitating timely processing of defects of the insulating layer, and achieving the technical effects of improving defect management efficiency of the insulating layer of the ultra-high voltage power equipment and guaranteeing safe operation of the ultra-high voltage power equipment.
2. Analyzing the vibration intensity data to obtain a first seed point, wherein the seed point is a part of the target extra-high voltage power equipment, the vibration intensity of which is greater than the preset vibration intensity, analyzing the temperature distribution data to obtain a second seed point, wherein the second seed point is a part of the target extra-high voltage power equipment, the temperature of which is greater than the preset temperature, analyzing the corona discharge data to obtain a third seed point, and the third seed point is a part of the target extra-high voltage power equipment, the corona intensity of which is greater than the preset corona intensity, wherein the first seed point, the second seed point and the third seed point form a seed point set, so that the seed point is screened, the follow-up key analysis management of the seed point is facilitated, and the technical effect of improving the management efficiency is achieved.
3. And carrying out vibration intensity grading identification on the target digital twin model according to the vibration ladder data to obtain a first grading identification point, carrying out temperature grading identification on the target digital twin model according to the ladder temperature data to obtain a second grading identification point, carrying out corona intensity grading identification on the target digital twin model according to the corona intensity ladder data to obtain a third grading identification point, carrying out grading identification on the seed points from three dimensions, providing support for defect identification of a subsequent insulating layer, and achieving the technical effects of improving defect identification efficiency of the insulating layer and further improving defect management efficiency of the insulating layer of the ultra-high voltage power equipment.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. The accompanying drawings, which are included to provide a further understanding of the invention, illustrate and explain the present invention, and together with the description serve to explain the principle of the invention, if not to limit the invention, and to enable others skilled in the art to make and use the invention without undue effort.
Fig. 1 is a schematic flow chart of a digital twin-based power equipment management method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a digital twin-based power device management system according to an embodiment of the present invention.
Reference numerals illustrate: the device comprises an equipment data acquisition module 11, a digital twin model construction module 12, a vibration signal acquisition module 13, a temperature data acquisition module 14, a corona data acquisition module 15, a seed point selection module 16 and an insulating layer management module 17.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, exemplary embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be apparent that the described embodiments are only some embodiments of the present invention and not all embodiments of the present invention, and it should be understood that the present invention is not limited by the example embodiments described herein.
The terminology used in the description is for the purpose of describing embodiments only and is not intended to be limiting of the invention. As used in this specification, the singular terms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. The terms "comprises" and/or "comprising," when used in this specification, specify the presence of steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other steps, operations, elements, components, and/or groups thereof.
Unless defined otherwise, all terms (including technical and scientific terms) used in this specification should have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms, such as those defined in commonly used dictionaries, should not be interpreted in an idealized or overly formal sense unless expressly so defined herein. Like numbers refer to like elements throughout.
It should be noted that, the user information (including, but not limited to, user equipment information, user personal information, etc.) and the data (including, but not limited to, data for presentation, analyzed data, etc.) related to the present invention are information and data authorized by the user or sufficiently authorized by each party.
Example 1
Fig. 1 is a diagram of a method for managing electric power equipment based on digital twinning according to an embodiment of the present application, where the method includes:
acquiring equipment composition structure and equipment operation data of target ultra-high voltage power equipment in a target area;
the target area refers to an area to be subjected to power equipment management, and the digital twinning-based power equipment management method is mainly used for managing an insulating layer of extra-high voltage power equipment (such as extra-high voltage converter transformer bushings, extra-high voltage wall bushings, converter valve towers, connecting hardware and other power equipment), so that the target area specifically refers to any area containing the extra-high voltage power equipment, and the target extra-high voltage power equipment is all the extra-high voltage power equipment in the target area, including equipment such as the extra-high voltage converter transformer bushings, the extra-high voltage wall bushings, the converter valve towers, the connecting hardware and the like. Based on the above, the device composition structure and the device operation data of the target extra-high voltage power device are acquired, the device composition structure refers to a physical composition structure of the target extra-high voltage power device, for example, an extra-high voltage converter transformer bushing is composed of a main insulation-capacitance core, an external insulation-upper porcelain part, a lower porcelain part, a connecting bushing, a conservator, a spring assembly, a base, a voltage equalizing ball, a measuring terminal, a connecting terminal, a rubber gasket, insulating oil and the like, the device composition structure comprises information of all parts, part shapes, sizes, connecting modes, connecting positions and the like which form the target extra-high voltage power device, and the device operation data refers to electrical parameters including voltage, current, resistance, power and the like which are generated when the target extra-high voltage power device operates in different modes. The equipment composition structure can be directly extracted and uploaded according to a use manual or a design drawing of the target ultra-high voltage power equipment, and the equipment operation data can be obtained according to historical operation data of the target ultra-high voltage power equipment, and the equipment operation data can be obtained through the historical operation data obtaining operation rules.
Constructing a target digital twin model, wherein the target digital twin model is a digital simulation model obtained based on a digital twin technology according to the equipment composition structure and the equipment operation data;
digital twinning is a virtual representation for modeling the state of a physical entity or system by fully utilizing data such as a physical model, sensor update, operation history and the like, integrating simulation processes of multiple disciplines, multiple physical quantities, multiple scales and multiple probabilities. In this embodiment, the target digital twin model is a digital simulation model that creates a high simulation for the target ultra-high voltage power equipment in a digital manner according to the equipment composition structure and the equipment operation data, and the target digital twin model can be obtained by inputting the equipment composition structure and the equipment operation data into the digital twin platform through a Siemens Digital Twin digital twin platform, for example. The construction of the digital twin model is a common technical means for a person skilled in the art and is not developed here.
Vibration intensity data are obtained, and vibration signals of the target ultra-high voltage power equipment are acquired through a vibration sensor;
The vibration sensors are paved at a plurality of positions of the target ultra-high voltage power equipment, the paving needs of the vibration sensors are uniform, the vibration sensors can be uniformly divided according to the size of the target ultra-high voltage power equipment, the vibration sensors are paved according to the dividing result, the model of the vibration sensors is not limited, and the vibration sensors can be selected according to actual conditions. And acquiring vibration signals of different parts of the target ultra-high voltage power equipment through paved vibration sensors, wherein the vibration signals comprise vibration intensities, and the vibration intensities of a plurality of parts are used as vibration intensity data.
Acquiring temperature distribution data, wherein the temperature distribution data are acquired by acquiring the temperature distribution data of the target ultra-high voltage power equipment through an infrared thermal imaging device;
the thermal infrared imaging is to image an object through a thermal infrared sensitive CCD, a temperature field on the surface of the object is reflected, the infrared thermal imaging device is an infrared thermal imager, and a user can select the existing infrared thermal imager to collect temperature data of all parts of the target ultra-high voltage power equipment according to actual conditions, so that temperature value groups of different parts are obtained to serve as temperature distribution data.
Corona discharge data are obtained, and the corona discharge data are obtained by carrying out corona discharge monitoring on the target ultra-high voltage power equipment through an ultraviolet imaging device;
In a preferred embodiment, further comprising:
the ultraviolet imaging device is used for collecting ultraviolet signals of the target ultra-high voltage power equipment to obtain ultraviolet signals; preprocessing the ultraviolet signal to obtain a target ultraviolet signal, wherein the preprocessing comprises filtering, enhancing and denoising; performing digital image conversion on the target ultraviolet signal to obtain a target ultraviolet image; and acquiring corona discharge data according to the target ultraviolet image, wherein the corona discharge data comprises corona intensity and corona position.
In a preferred embodiment, further comprising:
superposing the target ultraviolet image and a preset visible light image to obtain a superposed image; carrying out identification on the corona intensity and the corona position according to the superimposed image to obtain first corona discharge data; collecting operation environment information of the target ultra-high voltage power equipment, and carrying out corona influence analysis on the operation environment information to obtain a corona influence coefficient; and compensating and correcting the first corona discharge data through the corona influence coefficient to obtain the corona discharge data.
Corona discharge is a localized discharge phenomenon that occurs when the local voltage stress of a charged body exceeds a critical value, air is dissociated and the corona discharge phenomenon occurs. Particularly, in ultra-high voltage power equipment, corona, flashover or arc is often generated due to poor design, manufacturing, installation and maintenance, and electrons in the air continuously acquire and release energy during the discharge process, and ultraviolet rays are emitted when the electrons release energy (i.e., discharge). The ultraviolet imaging device (ultraviolet imager) can collect ultraviolet signals and perform digital image conversion on ultraviolet models, so that corona intensity of different parts can be identified, and the specific process is as follows:
The ultraviolet imaging device is used for acquiring ultraviolet signals of the target ultra-high voltage power equipment to obtain ultraviolet signals, the ultraviolet signals are preprocessed to obtain target ultraviolet signals, wherein the preprocessing comprises filtering, enhancing and denoising, the filtering, enhancing and denoising of the signals are common technical means for those skilled in the art, the filtering is not performed, the filtering can be performed through filtering algorithms such as median filtering and mean filtering, and the like, the preprocessing can be performed according to the actual situation, the preprocessing can be one or more of the filtering, enhancing and denoising, and the preprocessing can be realized through software platforms such as MATLAB, python, and the preprocessed ultraviolet signals are the target ultraviolet signals. Further, the target ultraviolet signal is subjected to digital image conversion, the ultraviolet wavelength range is 10nm-400nm, most of ultraviolet generated by high-voltage equipment discharge is 280nm-400nm, and the other part of ultraviolet generated by high-voltage equipment discharge is 230nm-280nm, at the moment, the digital image conversion is spectral imaging, so that a target ultraviolet image is obtained, the ultraviolet spectral imaging is a common technical means for a person skilled in the art, so that development is not performed, corona discharge data are obtained according to the target ultraviolet image, and the corona discharge data comprise corona intensity and corona position.
In the process of acquiring the corona discharge data according to the target ultraviolet image, the target ultraviolet image and a preset visible light image are overlapped, wherein the preset visible light image refers to a spectrum image of natural light when the target ultra-high voltage power equipment is subjected to corona discharge monitoring, the target ultraviolet image and the preset visible light image are overlapped to obtain an overlapped image, and further the corona intensity and the corona position are identified according to the overlapped image to obtain first corona discharge data.
In practical application, the number of ultraviolet signals detected in unit time is used as corona intensity, however, the number of ultraviolet signals is affected by a plurality of environmental conditions, such as humidity, temperature, air pressure, altitude and the like, the higher the air pressure and the temperature is, the higher the corona intensity is, therefore, the operation environment information of the target ultra-high voltage power equipment is collected, the operation environment information comprises environment temperature, humidity, air pressure and the like, the corona influence analysis is carried out on the operation environment information, the corona influence coefficient is obtained, specifically, the influence of different environmental conditions on the corona intensity can be extracted from massive internet big data based on a data mining technology, a corona influence database is obtained, such as the change degree of the corona intensity every 1 ℃ in temperature is obtained, the corona influence coefficient is obtained by comparing the collected operation environment information, the corona influence coefficient represents the change degree of the corona intensity, the first corona discharge data is compensated and corrected by the corona influence coefficient, namely the first corona discharge data is multiplied by the corona influence coefficient, and the result is the corona discharge data. Therefore, correction of corona discharge data is achieved, accuracy of basic data is improved, and management effect of target extra-high voltage power equipment is further improved.
According to the vibration intensity data, the temperature distribution data and the corona discharge data, seed points are automatically selected to obtain a seed point set;
in a preferred embodiment, further comprising:
analyzing the vibration intensity data to obtain a first seed point, wherein the seed point is a part with the vibration intensity greater than a preset vibration intensity on the target ultra-high voltage power equipment; analyzing the temperature distribution data to obtain a second seed point, wherein the second seed point is a part of the target ultra-high voltage power equipment, the temperature of which is greater than a preset temperature; analyzing the corona discharge data to obtain a third seed point, wherein the third seed point is a part with corona intensity greater than preset corona intensity on the target ultra-high voltage power equipment; the first seed point, the second seed point and the third seed point form the seed point set.
Analyzing the vibration intensity data to obtain a first seed point, wherein the seed point is a part of the target ultra-high voltage power equipment, the vibration intensity of the part is larger than the preset vibration intensity, the preset vibration intensity is set by a person skilled in the art, the vibration intensity of the insulating layer of the target ultra-high voltage power equipment, which is free of any stains, abrasion and the like, can be obtained through testing to serve as the preset vibration intensity, the vibration intensity data comprises vibration intensities of a plurality of different parts, the part of the vibration intensity, which is larger than the preset vibration intensity, is obtained to serve as the first seed point, and the first seed point generally refers to all parts of the vibration intensity, which are larger than the preset vibration intensity.
And analyzing the temperature distribution data to obtain a second seed point, wherein the second seed point is a part of the target extra-high voltage power equipment, the temperature is higher than a preset temperature, the temperature distribution data refer to temperatures of different parts of the target extra-high voltage power equipment, the preset temperature is set by a person skilled in the art, the highest temperature value of the insulating layer of the target extra-high voltage power equipment under the conditions of no stains, no abrasion and the like can be obtained through testing and is used as the preset temperature, and the part with the temperature higher than the preset temperature is obtained based on the preset temperature as the second seed point.
And analyzing the corona discharge data to obtain a third seed point, wherein the third seed point is a part of the target ultra-high voltage power equipment, the corona intensity of which is larger than the preset corona intensity, and similarly, the highest corona intensity of the insulating layer of the target ultra-high voltage power equipment, which is free of any stains, abrasion and the like, can be obtained through testing to serve as the preset corona intensity, and the third seed point generally refers to all parts of which the corona intensity is larger than the preset corona intensity. The first seed point, the second seed point and the third seed point form the seed point set. Therefore, the parts with high vibration, high temperature and high corona intensity are screened, the parts contained in the seed point set are possibly areas with defects such as stains, abrasion and the like on the insulating layer, and the parts can be focused on later, so that the management efficiency of the ultra-high voltage power equipment is improved.
And identifying the target digital twin model according to the seed point set to obtain an abnormal identification point, and managing an insulating layer of the target ultra-high voltage power equipment according to the abnormal identification point.
In a preferred embodiment, further comprising:
acquiring first vibration intensity distribution data of the first seed points, and carrying out step division on the first vibration intensity distribution data to obtain vibration step data; performing vibration intensity grading identification on the target digital twin model according to the vibration ladder data to obtain a first grading identification point; acquiring first temperature distribution data of the second seed points, and carrying out step division on the first temperature distribution data to acquire step temperature data; carrying out temperature grading identification on the target digital twin model according to the ladder temperature data to obtain a second grading identification point; acquiring first corona intensity distribution data of the third seed point, and carrying out step division on the first corona intensity distribution data to acquire corona intensity step data; and carrying out corona intensity grading identification on the target digital twin model according to the corona intensity ladder data to obtain a third grading identification point.
In a preferred embodiment, further comprising:
carrying out statistical analysis on the first grading identification point, the second grading identification point and the third grading identification point to obtain a first vibration level, a first temperature level and a first corona intensity level of the first identification point; weighting calculation is carried out on the first vibration level, the first temperature level and the first corona intensity level, and a first abnormal level of the first identification point is obtained; and comparing and analyzing the first abnormal grade based on a preset abnormal grade to obtain an abnormal identification point.
In a preferred embodiment, further comprising:
performing entity part matching on the target extra-high voltage power equipment according to the abnormal identification points to obtain a first entity part; acquiring a first entity high-definition image of the first entity part; preprocessing and amplifying the first entity high-definition image to obtain a first amplified image; performing defect identification according to the first amplified image to obtain a defect identification result; and repairing and managing the insulating layer of the target ultra-high voltage power equipment according to the defect identification result.
And marking the target digital twin model according to the seed point set to obtain an abnormal marking point, wherein the abnormal marking point is an abnormal part, and can be marked by a single symbol or color, and the insulating layer of the target ultra-high voltage power equipment is managed according to the abnormal marking point.
The specific process of identifying the target digital twin model according to the seed point set is as follows: the method comprises the steps of obtaining first vibration intensity distribution data of a first seed point, carrying out step division on the first vibration intensity distribution data to obtain vibration step data, in a simple way, the first seed point comprises a plurality of parts, the vibration intensity of each part is possibly different, the vibration intensities of the plurality of parts form the first vibration intensity distribution data, the first vibration intensity distribution data are arranged according to the sequence from large to small, then the first vibration intensity distribution data are equidistantly divided, a plurality of vibration intervals can be obtained, each vibration interval can comprise a plurality of parts with relatively similar vibration intensities, vibration intensity classification identification is carried out on the plurality of parts in the plurality of vibration intervals according to the interval range of the vibration interval, in a simple way, the plurality of parts in one vibration interval are identified by the same level, and the greater the vibration interval range is, the higher the identification level is, and the identified first seed point is the first classification identification point.
And similarly, acquiring first temperature distribution data of the second seed points, carrying out step division on the first temperature distribution data to obtain step temperature data, and carrying out temperature grading identification on the target digital twin model according to the step temperature data to obtain second grading identification points. And acquiring first corona intensity distribution data of the third seed point, carrying out step division on the first corona intensity distribution data to obtain corona intensity step data, and carrying out corona intensity grading identification on the target digital twin model according to the corona intensity step data to obtain a third grading identification point. It should be noted that, the first grading identification point, the second grading identification point, and the third grading identification point are grading identifications of vibration intensity, temperature, and corona intensity, respectively, and the first grading identification point, the second grading identification point, and the third grading identification point may include the same portion, that is, the same portion may have identification levels of vibration intensity, temperature, and corona intensity, and the identification levels of the three may be different, for example, the vibration intensity of a certain portion is level 1, and the temperature and corona intensity are level 3. Therefore, the multi-level identification of the seed points is realized, support is provided for the subsequent management of the insulation layers of the ultra-high voltage power equipment, and the management efficiency is improved.
And carrying out statistical analysis on the first grading identification point, the second grading identification point and the third grading identification point to obtain a first vibration level, a first temperature level and a first corona intensity level of the first identification point, wherein the first identification point generally refers to any one part to be identified, and any part may have the identification levels of vibration intensity, temperature and corona intensity, and if the first identification point does not have any one of the identification levels of vibration intensity, temperature and corona intensity, the identification level is marked as 0. Based on the above, the identification level of any part is acquired, a first vibration level, a first temperature level and a first corona intensity level are obtained, the first vibration level, the first temperature level and the first corona intensity level are weighted and calculated, specifically, the historical vibration intensity, the historical temperature and the historical corona intensity can be acquired through acquiring the historical insulating layer fault records of the same type of extra-high voltage power equipment, the historical vibration intensity, the historical temperature and the historical corona intensity are analyzed by using a coefficient of variation method, the weights corresponding to the first vibration level, the first temperature level and the first corona intensity level are obtained, then the weights corresponding to the first identification point are weighted and calculated, and the first abnormal level of the first identification point is obtained. And comparing and analyzing the first abnormal grade based on a preset abnormal grade to obtain an abnormal identification point, wherein the preset abnormal grade is set by a person skilled in the art and can be determined by combining historical experience, so that whether the first abnormal grade is larger than the preset abnormal grade is judged, and if so, the first abnormal grade is used as the abnormal identification point.
The method further comprises performing entity part matching on the target ultra-high voltage power equipment according to the abnormal identification point to obtain a first entity part, simply speaking, marking the abnormal identification point on a target digital twin model of the target ultra-high voltage power equipment, performing entity part matching on the target ultra-high voltage power equipment according to the identification part of the target digital twin model to obtain the first entity part, wherein the first entity part is the part corresponding to the abnormal identification point on the target ultra-high voltage power equipment in the actual situation, acquiring a first entity high-definition image of the first entity part through a high-definition camera, preprocessing the first entity high-definition image, amplifying the first entity high-definition image, wherein the preprocessing refers to noise reduction processing of the image, comprises median filtering, gaussian filtering and other methods, one or more of which can be selected for noise reduction processing by self, after the pretreatment is completed, amplifying the pretreated first solid high-definition image to obtain a first amplified image, carrying out defect identification according to the first amplified image, in short, carrying out important investigation on the part because the temperature, the vibration intensity and the corona intensity of an abnormal identification point are higher and the probability of defects of the insulating layer at the part is higher, specifically, acquiring different defect images of the insulating layer, such as images with stains, images with cracks and the like, constructing a defect image library by the prior art, then comparing the similarity of the first amplified image with the defect images in the defect image library, if the similarity is higher than a preset similarity, considering that the part has the same defects as the defect images, and the preset similarity can be set by itself, preferably, the defect identification result may be 75%, where the defect identification result is that whether the first entity part has a defect, and a defect type is present, and repair management is performed on the insulation layer of the target extra-high voltage power device according to the defect identification result, for example, the defect type is that a stain exists, decontamination treatment may be performed on the first entity part, and if a crack exists, repair may be performed on the crack. Therefore, the insulation layer management of the target ultra-high voltage power equipment is realized, the management efficiency is improved, and the safe operation of the target ultra-high voltage power equipment is ensured.
Based on the analysis, one or more technical schemes provided by the disclosure can achieve the following beneficial effects:
1. the method comprises the steps of obtaining equipment composition structure and equipment operation data of target ultra-high voltage power equipment in a target area, constructing a target digital twin model, obtaining vibration intensity data, acquiring vibration signals of the target ultra-high voltage power equipment through a vibration sensor, obtaining temperature distribution data, obtaining corona discharge data, automatically selecting seed points according to the vibration intensity data, the temperature distribution data and the corona discharge data, obtaining a seed point set, identifying the target digital twin model according to the seed point set, obtaining an abnormal identification point, managing an insulating layer of the target ultra-high voltage power equipment according to the abnormal identification point, realizing defect identification of the insulating layer of the ultra-high voltage power equipment, facilitating timely processing of defects of the insulating layer, and achieving the technical effects of improving defect management efficiency of the insulating layer of the ultra-high voltage power equipment and guaranteeing safe operation of the ultra-high voltage power equipment.
2. Analyzing the vibration intensity data to obtain a first seed point, wherein the seed point is a part of the target extra-high voltage power equipment, the vibration intensity of which is greater than the preset vibration intensity, analyzing the temperature distribution data to obtain a second seed point, wherein the second seed point is a part of the target extra-high voltage power equipment, the temperature of which is greater than the preset temperature, analyzing the corona discharge data to obtain a third seed point, and the third seed point is a part of the target extra-high voltage power equipment, the corona intensity of which is greater than the preset corona intensity, wherein the first seed point, the second seed point and the third seed point form a seed point set, so that the seed point is screened, the follow-up key analysis management of the seed point is facilitated, and the technical effect of improving the management efficiency is achieved.
3. And carrying out vibration intensity grading identification on the target digital twin model according to the vibration ladder data to obtain a first grading identification point, carrying out temperature grading identification on the target digital twin model according to the ladder temperature data to obtain a second grading identification point, carrying out corona intensity grading identification on the target digital twin model according to the corona intensity ladder data to obtain a third grading identification point, carrying out grading identification on the seed points from three dimensions, providing support for defect identification of a subsequent insulating layer, and achieving the technical effects of improving defect identification efficiency of the insulating layer and further improving defect management efficiency of the insulating layer of the ultra-high voltage power equipment.
Example two
Based on the same inventive concept as the digital twin-based power equipment management method in the foregoing embodiment, as shown in fig. 2, the present application further provides a digital twin-based power equipment management system, where the system includes:
the device data acquisition module 11 is used for acquiring device composition structures and device operation data of target ultra-high voltage power devices in a target area;
the digital twin model construction module 12 is used for constructing a target digital twin model, wherein the target digital twin model is a digital simulation model obtained according to the equipment composition structure and the equipment operation data based on a digital twin technology;
The vibration signal acquisition module 13 is used for acquiring vibration intensity data, and the vibration intensity data is acquired by acquiring the vibration signal of the target ultra-high voltage power equipment through a vibration sensor;
the temperature data acquisition module 14 is used for acquiring temperature distribution data, and the temperature distribution data are acquired by acquiring the temperature distribution data of the target ultra-high voltage power equipment through an infrared thermal imaging device;
the corona data acquisition module 15 is used for acquiring corona discharge data, and the corona discharge data are acquired by carrying out corona discharge monitoring on the target ultra-high voltage power equipment through an ultraviolet imaging device;
the seed point selection module 16, wherein the seed point selection module 16 is configured to automatically select seed points according to the vibration intensity data, the temperature distribution data, and the corona discharge data to obtain a seed point set;
the insulation layer management module 17, the insulation layer management module 17 is configured to identify the target digital twin model according to the seed point set, obtain an abnormal identification point, and manage an insulation layer of the target extra-high voltage power device according to the abnormal identification point.
Further, the corona data acquisition module 15 is further configured to:
the ultraviolet imaging device is used for collecting ultraviolet signals of the target ultra-high voltage power equipment to obtain ultraviolet signals;
preprocessing the ultraviolet signal to obtain a target ultraviolet signal, wherein the preprocessing comprises filtering, enhancing and denoising;
performing digital image conversion on the target ultraviolet signal to obtain a target ultraviolet image;
and acquiring corona discharge data according to the target ultraviolet image, wherein the corona discharge data comprises corona intensity and corona position.
Further, the corona data acquisition module 15 is further configured to:
superposing the target ultraviolet image and a preset visible light image to obtain a superposed image;
carrying out identification on the corona intensity and the corona position according to the superimposed image to obtain first corona discharge data;
collecting operation environment information of the target ultra-high voltage power equipment, and carrying out corona influence analysis on the operation environment information to obtain a corona influence coefficient;
and compensating and correcting the first corona discharge data through the corona influence coefficient to obtain the corona discharge data.
Further, the seed point selection module 16 is further configured to:
analyzing the vibration intensity data to obtain a first seed point, wherein the seed point is a part with the vibration intensity greater than a preset vibration intensity on the target ultra-high voltage power equipment;
analyzing the temperature distribution data to obtain a second seed point, wherein the second seed point is a part of the target ultra-high voltage power equipment, the temperature of which is greater than a preset temperature;
analyzing the corona discharge data to obtain a third seed point, wherein the third seed point is a part with corona intensity greater than preset corona intensity on the target ultra-high voltage power equipment;
the first seed point, the second seed point and the third seed point form the seed point set.
Further, the insulating layer management module 17 is further configured to:
acquiring first vibration intensity distribution data of the first seed points, and carrying out step division on the first vibration intensity distribution data to obtain vibration step data;
performing vibration intensity grading identification on the target digital twin model according to the vibration ladder data to obtain a first grading identification point;
acquiring first temperature distribution data of the second seed points, and carrying out step division on the first temperature distribution data to acquire step temperature data;
Carrying out temperature grading identification on the target digital twin model according to the ladder temperature data to obtain a second grading identification point;
acquiring first corona intensity distribution data of the third seed point, and carrying out step division on the first corona intensity distribution data to acquire corona intensity step data;
and carrying out corona intensity grading identification on the target digital twin model according to the corona intensity ladder data to obtain a third grading identification point.
Further, the insulating layer management module 17 is further configured to:
carrying out statistical analysis on the first grading identification point, the second grading identification point and the third grading identification point to obtain a first vibration level, a first temperature level and a first corona intensity level of the first identification point;
weighting calculation is carried out on the first vibration level, the first temperature level and the first corona intensity level, and a first abnormal level of the first identification point is obtained;
and comparing and analyzing the first abnormal grade based on a preset abnormal grade to obtain an abnormal identification point.
Further, the insulating layer management module 17 is further configured to:
performing entity part matching on the target extra-high voltage power equipment according to the abnormal identification points to obtain a first entity part;
Acquiring a first entity high-definition image of the first entity part;
preprocessing and amplifying the first entity high-definition image to obtain a first amplified image;
performing defect identification according to the first amplified image to obtain a defect identification result;
and repairing and managing the insulating layer of the target ultra-high voltage power equipment according to the defect identification result.
A specific example of a digital twin-based power device management method in the first embodiment is also applicable to a digital twin-based power device management system in the present embodiment, and a person skilled in the art can clearly know a digital twin-based power device management system in the present embodiment through the foregoing detailed description of a digital twin-based power device management method, so that the details thereof will not be described herein for brevity.
It should be understood that the various forms of flow shown above, reordered, added or deleted steps may be used, as long as the desired results of the disclosed embodiments are achieved, and are not limiting herein.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (8)
1. A digital twinning-based power device management method, the method comprising:
acquiring equipment composition structure and equipment operation data of target ultra-high voltage power equipment in a target area;
constructing a target digital twin model, wherein the target digital twin model is a digital simulation model obtained based on a digital twin technology according to the equipment composition structure and the equipment operation data;
vibration intensity data are obtained, and vibration signals of the target ultra-high voltage power equipment are acquired through a vibration sensor;
acquiring temperature distribution data, wherein the temperature distribution data are acquired by acquiring the temperature distribution data of the target ultra-high voltage power equipment through an infrared thermal imaging device;
corona discharge data are obtained, and the corona discharge data are obtained by carrying out corona discharge monitoring on the target ultra-high voltage power equipment through an ultraviolet imaging device;
according to the vibration intensity data, the temperature distribution data and the corona discharge data, seed points are automatically selected to obtain a seed point set;
and identifying the target digital twin model according to the seed point set to obtain an abnormal identification point, and managing an insulating layer of the target ultra-high voltage power equipment according to the abnormal identification point.
2. The method of claim 1, wherein the corona discharge monitoring of the target extra-high voltage power device by an ultraviolet imaging device to obtain corona discharge data comprises:
the ultraviolet imaging device is used for collecting ultraviolet signals of the target ultra-high voltage power equipment to obtain ultraviolet signals;
preprocessing the ultraviolet signal to obtain a target ultraviolet signal, wherein the preprocessing comprises filtering, enhancing and denoising;
performing digital image conversion on the target ultraviolet signal to obtain a target ultraviolet image;
and acquiring corona discharge data according to the target ultraviolet image, wherein the corona discharge data comprises corona intensity and corona position.
3. The method of claim 2, wherein said acquiring said corona discharge data from said target ultraviolet image comprises:
superposing the target ultraviolet image and a preset visible light image to obtain a superposed image;
carrying out identification on the corona intensity and the corona position according to the superimposed image to obtain first corona discharge data;
collecting operation environment information of the target ultra-high voltage power equipment, and carrying out corona influence analysis on the operation environment information to obtain a corona influence coefficient;
And compensating and correcting the first corona discharge data through the corona influence coefficient to obtain the corona discharge data.
4. The method of claim 1, wherein the automatically selecting seed points according to the vibration intensity data, the temperature distribution data, and the corona discharge data to obtain a set of seed points comprises:
analyzing the vibration intensity data to obtain a first seed point, wherein the seed point is a part with the vibration intensity greater than a preset vibration intensity on the target ultra-high voltage power equipment;
analyzing the temperature distribution data to obtain a second seed point, wherein the second seed point is a part of the target ultra-high voltage power equipment, the temperature of which is greater than a preset temperature;
analyzing the corona discharge data to obtain a third seed point, wherein the third seed point is a part with corona intensity greater than preset corona intensity on the target ultra-high voltage power equipment;
the first seed point, the second seed point and the third seed point form the seed point set.
5. The method of claim 4, wherein the identifying the target digital twin model from the set of seed points comprises:
Acquiring first vibration intensity distribution data of the first seed points, and carrying out step division on the first vibration intensity distribution data to obtain vibration step data;
performing vibration intensity grading identification on the target digital twin model according to the vibration ladder data to obtain a first grading identification point;
acquiring first temperature distribution data of the second seed points, and carrying out step division on the first temperature distribution data to acquire step temperature data;
carrying out temperature grading identification on the target digital twin model according to the ladder temperature data to obtain a second grading identification point;
acquiring first corona intensity distribution data of the third seed point, and carrying out step division on the first corona intensity distribution data to acquire corona intensity step data;
and carrying out corona intensity grading identification on the target digital twin model according to the corona intensity ladder data to obtain a third grading identification point.
6. The method as recited in claim 5, further comprising:
carrying out statistical analysis on the first grading identification point, the second grading identification point and the third grading identification point to obtain a first vibration level, a first temperature level and a first corona intensity level of the first identification point;
Weighting calculation is carried out on the first vibration level, the first temperature level and the first corona intensity level, and a first abnormal level of the first identification point is obtained;
and comparing and analyzing the first abnormal grade based on a preset abnormal grade to obtain an abnormal identification point.
7. The method of claim 6, wherein managing the insulation layer of the target extra-high voltage power device according to the anomaly identification point comprises:
performing entity part matching on the target extra-high voltage power equipment according to the abnormal identification points to obtain a first entity part;
acquiring a first entity high-definition image of the first entity part;
preprocessing and amplifying the first entity high-definition image to obtain a first amplified image;
performing defect identification according to the first amplified image to obtain a defect identification result;
and repairing and managing the insulating layer of the target ultra-high voltage power equipment according to the defect identification result.
8. A digital twinning-based power plant management system, characterized by the steps for performing any one of the digital twinning-based power plant management methods of claims 1 to 7, the system comprising:
The device data acquisition module is used for acquiring device composition structures and device operation data of the target ultra-high voltage power devices in the target area;
the digital twin model construction module is used for constructing a target digital twin model, and the target digital twin model is a digital simulation model obtained according to the equipment composition structure and the equipment operation data based on a digital twin technology;
the vibration signal acquisition module is used for acquiring vibration intensity data, and the vibration intensity data is acquired by acquiring the vibration signal of the target ultra-high voltage power equipment through a vibration sensor;
the temperature data acquisition module is used for acquiring temperature distribution data, and the temperature distribution data are acquired by acquiring the temperature distribution data of the target ultra-high voltage power equipment through an infrared thermal imaging device;
the corona data acquisition module is used for acquiring corona discharge data, and the corona discharge data is acquired by carrying out corona discharge monitoring on the target ultrahigh voltage power equipment through an ultraviolet imaging device;
The seed point selection module is used for automatically selecting seed points according to the vibration intensity data, the temperature distribution data and the corona discharge data to obtain a seed point set;
and the insulating layer management module is used for identifying the target digital twin model according to the seed point set, obtaining an abnormal identification point and managing the insulating layer of the target ultra-high voltage power equipment according to the abnormal identification point.
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