CN114781846A - Evaluation method and system for overhead transmission line defect identification training - Google Patents
Evaluation method and system for overhead transmission line defect identification training Download PDFInfo
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Abstract
The invention provides an evaluation method and system for overhead transmission line defect identification training, which comprises the following steps: acquiring images related to the overhead transmission line; classifying and standardizing the obtained images for naming; marking defects of the classified and normalized named images; gridding the unmarked image and the marked image according to the same requirement, carrying out subtraction operation on the unmarked image and the marked image to obtain a marked area in the marked image, and establishing a database comprising the center and the radius of the marked area; evaluating assessment data in training according to the database; according to the invention, through an image marking technology and the processing of related images, the standardization of a training database is improved, the standardized database is utilized to carry out targeted learning, training and daily training, the basic skill of overhead transmission line defect identification is mastered, the defect identification speed and accuracy are improved, a solid foundation is laid for checking work, the defect of the overhead transmission line is ensured not to be reported, and the false alarm is reduced.
Description
Technical Field
The invention belongs to the technical field of online training, and particularly relates to an evaluation method and system for overhead transmission line defect identification training.
Background
Under the big background of the novel electric power system who uses the new forms of energy as the main part founding, in order to improve overhead transmission line's stability and security, require transmission line operation and maintenance personnel, in the daily tour of circuit, daily testing process, in time discover the defect and the hidden danger that exist such as circuit body, affiliated facilities and passageway environment to in time take the forceful measure, develop the elimination of defect and hidden danger, thereby guarantee transmission line normal steady operation, ensure power supply. In recent years, helicopters and unmanned aerial vehicles are widely applied to the daily inspection process of power transmission lines, and the defects of all parts of the power transmission lines can be clearly reflected through close-distance fixed-point shooting of the helicopters and the unmanned aerial vehicles, so that the auxiliary inspection personnel can conveniently find the defects which are difficult to find on the ground. The large number of photos makes it difficult to identify the photos by human. The currently developed application defect identification cloud platform intelligently assists in identifying the inspection images of unmanned aerial vehicles and helicopters, but the overall discovery rate of the algorithm is about 60% at present. Therefore, under the current situation, because the image intelligent auxiliary identification still has a higher false alarm rate, especially a higher false alarm rate, and also needs to carry out a large amount of personnel checking work, which puts a high requirement on the defect identification personnel.
The inventor finds that the existing overhead transmission line defect identification training mode has the problems of low identification speed and low accuracy in addition to the great difficulty of identifying the huge number of photos completely through manual work, and easily causes the problems of missing report and false report of the overhead transmission line; meanwhile, the training mode aiming at the improvement of the defect identification skill of the power transmission line at present mainly takes the character description learning in the regulations as the main part, and the improvement training of the defect identification capability is strengthened in the mode of image display, but an image library is limited, the learning efficiency is poor, the learning process is complicated, and the learning effect cannot be checked.
Disclosure of Invention
The invention provides an evaluation method and system for overhead transmission line defect identification training, which aim to solve the problems and improve the standardization of a training database through an image marking technology and the processing of related images, utilizes the standardized database to carry out targeted learning, training and daily training, grasps the basic skill of overhead transmission line defect identification, improves the defect identification speed and accuracy, lays a solid foundation for checking work, ensures that the overhead transmission line defects are not reported in a missing way, reduces false reports, ensures the safe and stable operation of lines and improves the lean management level of the transmission lines.
In order to achieve the purpose, the invention is realized by the following technical scheme:
in a first aspect, the invention provides an evaluation method for overhead transmission line defect identification training, which comprises the following steps:
acquiring data to be checked in training;
evaluating the examination data in the training according to a preset database to obtain an evaluation result;
the establishment of the preset database comprises the following steps: acquiring images related to the overhead transmission line; classifying and standardizing the acquired images; marking defects of the classified and normalized named images; and gridding the unmarked image and the marked image according to the same requirement, carrying out subtraction operation on the unmarked image and the marked image to obtain a marked area in the marked image, and establishing a database comprising the center and the radius of the marked area.
Furthermore, the acquired images are classified, and the images comprise one or more of overhead transmission line foundations, towers, ground wires, various hardware fittings and grounding devices, auxiliary facilities and external hidden dangers.
Further, the principle of the standardized naming basis is that naming is performed according to defect positions, defect components, defect categories, defect degrees, defect remarks and defect grades.
Further, the unmarked image and the marked image respectively refer to an unmarked defect image and a marked defect image corresponding to the unmarked defect image.
In a second aspect, the present invention further provides a training system for identifying defects of an overhead transmission line, including:
the management platform at least comprises one or more of an examination object basic information data management module, an examination data management module, a test question image preprocessing module and an automatic paper marking module;
the examination platform at least comprises one or more of a simulation exercise module, an examination module and a self-learning module;
wherein the test data management module is configured to: acquiring data to be checked in training; evaluating the assessment data in the training according to a preset database to obtain an evaluation result; the establishment of the preset database comprises the following steps: acquiring images related to the overhead transmission line; classifying and standardizing the acquired images; carrying out defect marking on the classified and normalized named images; gridding the unmarked image and the marked image according to the same requirement, carrying out subtraction operation on the unmarked image and the marked image to obtain a marked area in the marked image, and establishing a database comprising the center and the radius of the marked area.
Further, the test subject basic information data management module is configured to: adding, editing, deleting and retrieving the basic information of the examination taking subjects, uploading the basic information of the examination taking subjects in batches, and retrieving the examination scores of the examination taking subjects;
the test data management module further configured to: adding, editing, deleting and retrieving test questions, adding, editing, deleting and retrieving test papers, and automatically identifying the position and the radius of a marked area by adopting a digital image processing algorithm on the marked image;
a question image preprocessing module configured to: classifying and standardizing and naming images related to the overhead transmission line;
an automatic scoring module configured to: the marks made when the examination subject answers can be recorded and compared with the correct answers for grading.
Further, the simulated exercise module is configured to: randomly drawing questions, and answering according to the browser page; after answering, automatically scoring, and feeding back correct answers and question analysis in real time;
the testing module configured to: setting questions according to the established examination paper rules, counting down the answering time when answering is started, automatically giving examination papers after timing is ended, automatically grading after giving the examination papers, and recording examination scores;
the self-learning module configured to: the method can perform comprehensive learning such as image preview, character learning, image marking, objective question answering and the like, and can perform targeted learning after searching and positioning according to defect types, defect names and the like.
In a third aspect, the present invention further provides an evaluation system for overhead transmission line defect identification training, including:
a data acquisition module configured to: acquiring data to be checked in training;
an evaluation module configured to: evaluating the examination data in the training according to a preset database to obtain an evaluation result;
the establishment of the preset database comprises the following steps: acquiring images related to the overhead transmission line; classifying and standardizing the obtained images for naming; carrying out defect marking on the classified and normalized named images; and gridding the unmarked image and the marked image according to the same requirement, carrying out subtraction operation on the unmarked image and the marked image to obtain a marked area in the marked image, and establishing a database comprising the center and the radius of the marked area.
In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of the evaluation method for overhead transmission line defect identification training according to the first aspect.
In a fifth aspect, the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the program to implement the steps of the evaluation method for overhead transmission line defect identification training described in the first aspect.
Compared with the prior art, the invention has the following beneficial effects:
1. on the basis of classifying and standardizing and naming images, through an image marking technology, meshing unmarked images and marked images according to the same requirement, carrying out subtraction operation on the unmarked images and the marked images to obtain marked areas in the marked images, storing the centers and the radiuses of the marked areas in a database, improving the standardization of the training database, developing targeted learning, training and daily training by using the standardized database, mastering the basic skills of defect identification of the overhead transmission line, improving the defect identification speed and accuracy, laying a solid foundation for checking work, ensuring that the defects of the overhead transmission line are not reported and reducing false alarms, thereby ensuring the safe and stable operation of the line and improving the lean management level of the transmission line;
2. by applying the simulation training system suitable for improving the defect identification capability of the operation and maintenance personnel of the power transmission line, the invention develops targeted training teaching, integrates self-learning, self-testing and examination into a whole, gets rid of the unicity and the dryness of content learning such as traditional books, teaching materials, regulations and the like, enhances the learning experience and the learning initiative of learners, reduces the working strength and the working pressure of teachers, greatly improves the training effect and the training quality and fills the blank of the existing similar training system; the system or the method specially used for the invention is applied to develop training teaching, relevant personnel can greatly improve the defect identification speed and accuracy, lay a solid foundation for checking work, ensure that the defects of the overhead transmission line are not reported in a missing way and are reported in few false reports, improve the lean management level of the transmission line, have very important significance for ensuring the safe, stable and reliable operation of the overhead transmission line and even a large power grid, and have obvious economic benefit and social benefit.
Drawings
The accompanying drawings, which form a part hereof, are included to provide a further understanding of the present embodiments, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the present embodiments and together with the description serve to explain the present embodiments without unduly limiting the present embodiments.
FIG. 1 is a flowchart of example 1 of the present invention;
FIG. 2 is a self-learning mode interface according to embodiment 2 of the present invention;
fig. 3 is an exercise and test mode interface of embodiment 2 of the present invention;
the specific implementation mode is as follows:
the invention is further described with reference to the following figures and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure herein. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
Example 1:
as shown in fig. 1, the embodiment provides an evaluation method for overhead transmission line defect identification training, including:
acquiring images related to the overhead transmission line;
classifying and standardizing the obtained images for naming;
carrying out defect marking on the classified and normalized named images; gridding the unmarked image and the marked image according to the same requirement, carrying out subtraction operation on the unmarked image and the marked image to obtain a marked area in the marked image, and establishing a database comprising the center and the radius of the marked area;
evaluating assessment data in training according to the database;
in the embodiment, the normalization of the image is realized by classifying and naming the image, and when the image is processed on the basis, the image classified according to name, defect and the like can be processed in a targeted manner, so that the processing speed of the image is increased, and the pertinence and accuracy of the image processing can be improved; on the basis of standardization, when a database for evaluation is established, the unmarked image and the marked image are gridded according to the same requirement, and the unmarked image and the marked image are subjected to subtraction operation to obtain a marked area in the marked image, so that the accuracy marking of the defect area is realized, the accuracy in evaluation and comparison is improved, and the probability of missing detection and false detection is reduced.
In the embodiment, when the images related to the overhead transmission line are acquired, screening work can be developed in a photo image library which is shot by depending on manual inspection, helicopter inspection work, unmanned aerial vehicle inspection work and the like in the power industry; the method comprises the following steps that a representative picture can be selected and added to a resource library for overhead transmission line defect identification training, wherein the resource library can comprise body defects such as foundations, towers, wires, ground wires (OPGW), insulators, hardware fittings, grounding devices and stay wires; the defects of accessory facilities such as line identification, safety signboards, various technical monitoring or special-purpose equipment (such as on-line monitoring, lightning protection, bird prevention devices and the like) and the like which are attached to the line body can be further included; and the external hidden troubles including building rooms against regulations, planting trees and bamboos, stacking, soil taking, various construction operations and the like in the line protection area.
The defects can comprise critical, serious and general defects, the number of the defects is not less than 200 (except for critical defects), and at least 200 non-defective pictures are required to be contained; the accurate recognition rate of the existing intelligent recognition system on pin defects is fully considered to be low, so that the proportion of the defect map is properly increased; the critical defect can be understood as that an object in which the detected defect is located is about to lose the original function and fail (such as the crack of a pin), and needs to be understood to carry out maintenance or replacement and other work; the serious defect can be understood as that the probability of failure of an object in which the detected defect is located is higher, and the detection frequency or strength needs to be increased; the general defect can be understood as that the defect occurs, but the defect does not have serious accidents such as failure in a short time.
In the embodiment, the principle of the standardized naming basis is that naming is carried out according to defect positions, defect components, defect types, defect degrees, defect remarks and defect grades; the method can label the defective pictures according to a unified standard, and uniformly name the defective pictures, and the standardized naming principle can be carried out according to the following steps of defect position, defect component, defect category, defect degree, defect remark and defect classification, wherein: the defect position refers to the position where the defect occurs, and the position requirement is accurately and clearly described; the defective part refers to a part where a defect occurs; the defect category refers to the content of defects occurring based on defective parts; the defect degree refers to the severity degree of the defect, and quantifiable is expressed by using quantitative data, such as the length, width, diameter, area, crack depth and the like of the defect occurrence area; the defect remark refers to important information of the defect which needs to be expressed additionally, such as information of defect reason, uncertain type and the like; the defect classification refers to final qualification of the defects according to defect classification standards, wherein the defect classification standards can be determined through defect degrees, or can be determined after weight values are taken according to the defect degrees and different defect positions and defect parts.
In this embodiment, the unmarked image and the marked image may respectively refer to an unmarked defect image and a marked defect image corresponding to the unmarked defect image; the defect marking can be realized by an image processing mode, the defect part is marked, and the defect area can also be marked by a manual/automatic marking mode; gridding is carried out according to the same requirement, and it can be understood that when an image is gridded, the middle points, the shapes, the sizes, the directions and the like of the cells in the grid are the same, and the unmarked image and the marked image are subjected to subtraction operation, first, the marked image and the unmarked image are respectively subjected to threshold operation, and a marked image in the image, such as an image in an oval circle in fig. 1, is extracted; the specific principle is as follows: as shown in fig. 1, the circle pattern may be marked as red or other colors, in the color RGB color model, the marked red (or other colors) has obvious difference from other colors not used by the mark, and according to this difference, the red mark pattern and the background image are distinguished and extracted according to color colors, and the pattern and the background are identified according to color values, which is called threshold operation; secondly, after threshold operation, the marked image and the unmarked image are respectively displayed as an image containing a red mark and an image not containing the red mark, and the background of the two images is basically removed; and finally, subtracting the gray values of the pixels at the corresponding positions from the two types of images, and forming an image only containing the mark pattern by the two types of images after the subtraction operation, so that the position of the mark pattern, including the center point and the radius, can be determined.
Example 2:
this embodiment provides an overhead transmission line defect identification training system, includes:
the management platform at least comprises one or more of an examination object basic information data management module, an examination data management module, a test question image preprocessing module and an automatic paper marking module;
the examination platform at least comprises one or more of a simulation exercise module, an examination module and a self-learning module;
wherein the test data management module is configured to: acquiring data to be checked in training; evaluating the examination data in the training according to a preset database to obtain an evaluation result; the establishment of the preset database comprises the following steps: acquiring images related to the overhead transmission line; classifying and standardizing the acquired images; marking defects of the classified and normalized named images; gridding the unmarked image and the marked image according to the same requirement, carrying out subtraction operation on the unmarked image and the marked image to obtain a marked area in the marked image, and establishing a database comprising the center and the radius of the marked area.
In the embodiment, the test object can be a student, the unmarked defect picture is subjected to grid splitting and is compared with the corresponding marked defect picture, the standardized naming is brought into a system selectable pull-down menu, and a defect identification system platform is set up; the system consists of 2 modules, namely an examination management platform and a student examination platform; the examination management platform mainly comprises a student data management function, an examination data management function, a test question picture preprocessing function, an automatic examination reading function and the like, and the student examination platform mainly comprises a simulation exercise function, a formal examination function, a self-learning function and the like.
In this embodiment, the examination subject basic information data management module is configured to: adding, editing, deleting and retrieving the basic information of examination taking subjects, uploading the basic information of the examination taking subjects in batch, retrieving examination scores of the examination taking subjects, retrieving according to students, retrieving examination papers and the like;
the test data management module further configured to: adding, editing, deleting and retrieving test questions, adding, editing, deleting and retrieving test papers, and automatically identifying the position and the radius of a marked area by adopting a digital image processing algorithm on the marked image; the image processing algorithm may be the subtraction operation of the foregoing;
a test question image preprocessing module configured to: classifying and standardizing and naming images related to the overhead transmission line;
an automatic scoring module configured to: the method can record marks made when examination taking objects answer, compare and score the marks with correct answers, compare and score the answer of a selection question related to a picture, and directly compare the answer with the pre-stored correct answers when comparing the selection questions.
In this embodiment, the simulation exercise module is configured to: random question extraction is carried out, students carry out answer operation on a WEB browser page, and after the students finish answering, the system can automatically score and feed back correct answers and question analysis in real time;
the testing module configured to: the method comprises the following steps that (1) questions can be set according to a set test paper rule, when students begin to answer the questions, the answering time is counted down, automatic paper delivery is finished after timing, after the paper delivery, a background automatically scores, and examination scores are recorded; a background input function is opened, so that the resource library is conveniently supplemented in the later period; the established test paper rule can be set to randomly select one type of test paper among several different types for examination, or randomly screen questions with certain data in a preset question bank to realize question grouping of the test paper.
The self-learning module configured to: the method can be used for comprehensively learning image preview, character learning, image marking, objective question answering and the like on a browser, and can be used for carrying out targeted learning after searching and positioning according to defect types, defect names and the like; in the module, the work of answering and detailed solving can be carried out on the defect type, the labeling area, the objective problem of the attention item and the like in the image.
In the embodiment, the background database of the system is sorted, the conventional common defect resource library of the overhead transmission line is sorted, representative and clear pictures are selected from a huge picture library, and the pictures cover the body facilities such as the foundation, the tower, the ground wire, various hardware fittings, grounding devices and the like of the overhead transmission line, the accessory facilities, external hidden dangers and the like, and various defects including critical, serious and general defects, and are marked on the basis of original pictures.
In the embodiment, in the development of the power transmission line defect identification training system, the defect identification training system has the functions of randomly composing a paper, automatically judging scores and the like, and has a learning mode and an examination mode.
In this embodiment, programming languages such as htmljavajavascript sql can be used to refer to the idea of "finding different" from the currently popular pictures, gridding the unmarked and marked pictures according to the same requirement, performing subtraction operation on the unmarked and marked pictures to obtain a marked area in the marked picture, and storing the center and radius of the marked area in a database, thereby comparing and determining the student answer results;
in the embodiment, the power transmission line defect identification training system is applied to carry out training teaching, and in order to meet the requirement of daily training teaching, the background input function of the power transmission line defect identification training system needs to be opened, so that the resource library is supplemented in the later period of convenience, the interface is improved, and the like.
The working method of the system is the same as the evaluation method for overhead transmission line defect identification training in embodiment 1, and details are not repeated here.
Example 3:
in a third aspect, the present embodiment provides an evaluation system for overhead transmission line defect identification training, including:
a data acquisition module configured to: acquiring data to be checked in training;
an evaluation module configured to: evaluating the assessment data in the training according to a preset database to obtain an evaluation result;
the establishment of the preset database comprises the following steps: acquiring images related to the overhead transmission line; classifying and standardizing the obtained images for naming; marking defects of the classified and normalized named images; gridding the unmarked image and the marked image according to the same requirement, carrying out subtraction operation on the unmarked image and the marked image to obtain a marked area in the marked image, and establishing a database comprising the center and the radius of the marked area.
The working method of the system is the same as the evaluation method for overhead transmission line defect identification training in embodiment 1, and details are not repeated here.
Example 4:
the present embodiment provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of the evaluation method for overhead transmission line defect identification training described in embodiment 1.
Example 5:
the embodiment provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and when the processor executes the program, the steps of the evaluation method for overhead transmission line defect identification training described in embodiment 1 are implemented.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and those skilled in the art can make various modifications and variations. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present embodiment shall be included in the protection scope of the present embodiment.
Claims (10)
1. An evaluation method for defect identification training of overhead transmission lines is characterized by comprising the following steps:
acquiring data to be checked in training;
evaluating the assessment data in the training according to a preset database to obtain an evaluation result;
the establishment of the preset database comprises the following steps: acquiring images related to the overhead transmission line; classifying and standardizing the obtained images for naming; carrying out defect marking on the classified and normalized named images; gridding the unmarked image and the marked image according to the same requirement, carrying out subtraction operation on the unmarked image and the marked image to obtain a marked area in the marked image, and establishing a database comprising the center and the radius of the marked area.
2. The evaluation method for the overhead transmission line defect identification training of claim 1, wherein the obtained images are classified, and the images comprise one or more of an overhead transmission line foundation, a tower, a ground wire, various hardware fittings, a grounding device, an accessory facility and external hidden dangers.
3. The evaluation method for overhead transmission line defect identification training as claimed in claim 1, wherein the principle of the standardized naming basis is naming according to defect location, defect components, defect category, defect degree, defect remark and defect classification.
4. The evaluation method for overhead transmission line defect identification training of claim 1, wherein the unmarked image and the marked image respectively refer to an unmarked defect image and a marked defect image corresponding to the unmarked defect image.
5. The utility model provides an overhead transmission line defect identification training system which characterized in that includes:
the management platform at least comprises one or more of an examination object basic information data management module, an examination data management module, a test question image preprocessing module and an automatic paper marking module;
the examination platform at least comprises one or more of a simulation exercise module, an examination module and a self-learning module;
wherein the test data management module is configured to: acquiring data to be checked in training; evaluating the assessment data in the training according to a preset database to obtain an evaluation result; the establishment of the preset database comprises the following steps: acquiring images related to the overhead transmission line; classifying and standardizing the acquired images; marking defects of the classified and normalized named images; and gridding the unmarked image and the marked image according to the same requirement, carrying out subtraction operation on the unmarked image and the marked image to obtain a marked area in the marked image, and establishing a database comprising the center and the radius of the marked area.
6. The overhead transmission line defect recognition training system of claim 5, wherein the test subject basic information data management module is configured to: adding, editing, deleting and retrieving the basic information of the examination taking subjects, uploading the basic information of the examination taking subjects in batches, and retrieving the examination scores of the examination taking subjects;
the test data management module further configured to: adding, editing, deleting and retrieving test questions, adding, editing, deleting and retrieving test papers, and automatically identifying the position and the radius of a marking area of the marked image by adopting a digital image processing algorithm;
a test question image preprocessing module configured to: classifying and standardizing images related to the overhead transmission line;
an automatic scoring module configured to: the marks made by the examination subjects during answering can be recorded and compared with the correct answers for grading.
7. The evaluation system for overhead transmission line defect recognition training as claimed in claim 5,
the simulated exercise module configured to: randomly drawing questions, and answering according to the browser page; after answering, automatically scoring, and feeding back correct answers and question analysis in real time;
the examination module configured to: setting up questions according to the established test paper rule, counting down the answering time when answering is started, automatically giving the paper after timing is ended, automatically grading after giving the paper, and recording the examination score;
the self-learning module configured to: the method can be used for comprehensively learning image preview, character learning, image marking, objective question answering and the like, and can be used for carrying out targeted learning after searching and positioning according to defect types, defect names and the like.
8. The utility model provides an overhead transmission line defect identification training system which characterized in that includes:
a data acquisition module configured to: acquiring data to be checked in training;
an evaluation module configured to: evaluating the examination data in the training according to a preset database to obtain an evaluation result;
the establishment of the preset database comprises the following steps: acquiring images related to the overhead transmission line; classifying and standardizing the acquired images; carrying out defect marking on the classified and normalized named images; and gridding the unmarked image and the marked image according to the same requirement, carrying out subtraction operation on the unmarked image and the marked image to obtain a marked area in the marked image, and establishing a database comprising the center and the radius of the marked area.
9. A computer-readable storage medium, on which a computer program is stored, wherein the program, when executed by a processor, performs the steps of the evaluation method for overhead transmission line defect recognition training according to any one of claims 1 to 4.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the method for evaluating overhead transmission line defect recognition training as claimed in any one of claims 1 to 4.
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