CN113763320A - Cable accessory lead sealing construction defect detection method and system - Google Patents
Cable accessory lead sealing construction defect detection method and system Download PDFInfo
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- 230000007547 defect Effects 0.000 title claims abstract description 150
- 238000010276 construction Methods 0.000 title claims abstract description 55
- 238000007789 sealing Methods 0.000 title claims abstract description 47
- 238000001514 detection method Methods 0.000 title abstract description 19
- 238000000034 method Methods 0.000 claims abstract description 31
- 230000008439 repair process Effects 0.000 claims abstract description 27
- 238000012549 training Methods 0.000 claims description 21
- 230000015654 memory Effects 0.000 claims description 8
- 230000008569 process Effects 0.000 claims description 7
- 238000010586 diagram Methods 0.000 description 10
- 238000004590 computer program Methods 0.000 description 7
- 230000006870 function Effects 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 238000004519 manufacturing process Methods 0.000 description 2
- 229910052751 metal Inorganic materials 0.000 description 2
- 239000002184 metal Substances 0.000 description 2
- 229910052782 aluminium Inorganic materials 0.000 description 1
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
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Abstract
The invention discloses a method for detecting the defect of lead sealing construction of a cable accessory, which comprises the steps of collecting a real defect data sample of the lead sealing construction of the cable accessory; inputting the real defect data sample into a pre-trained repairing network to repair the real defect data sample; and extracting the characteristics of the real defect data sample and the repaired real defect data sample, performing characteristic matching, and taking the characteristic difference as a defect. Corresponding systems, storage media, and computing devices are also disclosed. The method adopts the repair network to repair the real defect data sample, adopts the characteristic matching mode to obtain the defect, and has high efficiency and comprehensive detection compared with the traditional manual detection.
Description
Technical Field
The invention relates to a method and a system for detecting defects of lead sealing construction of cable accessories, and belongs to the technical field of defect detection.
Background
In the cable manufacturing process, the lead sealing plays an important role in sealing and waterproofing various terminals and middle connections of the metal sheath or aluminum sheath cable, so that the metal outer sheath of the cable can be connected with other electrical equipment to form a good grounding system. In particular, in the construction of various joints of high-voltage cables, a skilled lead sealing technique is required, and therefore, defects thereof need to be detected in the lead sealing construction process. At present, the defect detection of lead sealing construction of cable accessories generally depends on manual work, so that the efficiency is low, and partial defects cannot be detected.
Disclosure of Invention
The invention provides a method and a system for detecting the defects of lead sealing construction of cable accessories, which solve the problems of low manual detection efficiency and incomplete detection.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
a method for detecting defects of lead sealing construction of cable accessories comprises the following steps:
acquiring a real defect data sample of the lead sealing construction of the cable accessory;
inputting the real defect data sample into a pre-trained repairing network to repair the real defect data sample;
and extracting the characteristics of the real defect data sample and the repaired real defect data sample, performing characteristic matching, and taking the characteristic difference as a defect.
The process of training the repair network is as follows:
collecting a lead sealing construction sample of the cable accessory;
carrying out defect construction on the cable accessory lead sealing construction sample to produce a defect sample;
training by adopting a defect sample to generate a confrontation type network, and taking a generator in the trained confrontation type network as a repair network; the generator in the countermeasure network is used for repairing the defect sample, and the discriminator in the countermeasure network is used for discriminating the defect sample repaired by the generator.
Extracting the characteristics of the real defect data sample and the repaired real defect data sample, carrying out characteristic matching, and taking the characteristic difference as a defect, wherein the specific process comprises the following steps: and extracting SIFT characteristics of the real defect data sample and the repaired real defect data sample, carrying out SIFT characteristic matching based on the similarity, and taking the SIFT characteristic difference as a defect.
The SIFT features include global SIFT features and local SIFT features.
A cable accessory lead sealing construction defect detection system comprises:
a real sample acquisition module: acquiring a real defect data sample of the lead sealing construction of the cable accessory;
a repair module: inputting the real defect data sample into a pre-trained repairing network to repair the real defect data sample;
a defect acquisition module: and extracting the characteristics of the real defect data sample and the repaired real defect data sample, performing characteristic matching, and taking the characteristic difference as a defect.
Still include the network training module, the network training module includes:
an acquisition module: collecting a lead sealing construction sample of the cable accessory;
a defect sample construction module: carrying out defect construction on the cable accessory lead sealing construction sample to produce a defect sample;
a training module: training by adopting a defect sample to generate a confrontation type network, and taking a generator in the trained confrontation type network as a repair network; the generator in the countermeasure network is used for repairing the defect sample, and the discriminator in the countermeasure network is used for discriminating the defect sample repaired by the generator.
A defect acquisition module: and extracting SIFT characteristics of the real defect data sample and the repaired real defect data sample, carrying out SIFT characteristic matching based on the similarity, and taking the SIFT characteristic difference as a defect.
The SIFT features include global SIFT features and local SIFT features.
A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform a cable accessory lead sealing construction defect detection method.
A computing device comprising one or more processors, one or more memories, and one or more programs stored in the one or more memories and configured to be executed by the one or more processors, the one or more programs including instructions for performing a cable accessory lead sealing construction defect detection method.
The invention achieves the following beneficial effects: the method adopts the repair network to repair the real defect data sample, adopts the characteristic matching mode to obtain the defect, and has high efficiency and comprehensive detection compared with the traditional manual detection.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic diagram of generation of a competing network training;
FIG. 3 is a schematic diagram of the method of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
As shown in fig. 1, a method for detecting defects in lead sealing construction of cable accessories comprises the following steps:
step 1, collecting a real defect data sample of the lead sealing construction of the cable accessory;
the real defect data sample is a sample collected in the construction process, the sample only knows the existence of defects but does not know the specific positions and the number of the defects, and the sample is an image;
step 2, inputting the real defect data sample into a pre-trained repairing network to repair the real defect data sample;
and 3, extracting the characteristics of the real defect data sample and the repaired real defect data sample, performing characteristic matching, and taking the characteristic difference as a defect.
According to the method, the real defect data sample is repaired by adopting the repairing network, the defect is obtained by adopting the characteristic matching mode, and compared with the traditional manual detection, the method is high in efficiency and comprehensive in detection.
As shown in fig. 2, the repair network is a pre-trained network, and is directly used in actual repair, the repair network specifically uses a generator in a generation countermeasure network, and the specific training process is as follows:
11) collecting a lead sealing construction sample of the cable accessory;
the collected sample is not required to be manually calibrated, and the sample is an image, namely the sample does not need to contain defect characteristics, so that the data collection cost is saved, and meanwhile, the omission problem caused by manual calibration is avoided;
12) carrying out defect construction on the cable accessory lead sealing construction sample to produce a defect sample;
using random defect modulesf(X~||X) Automatically implementing defect structure on the collected sample, wherein the defect of the structure is random defect, mainly typical defect in some lead sealing constructionForming a defect sample;
13) training by adopting a defect sample to generate a confrontation type network, and taking a generator in the trained confrontation type network as a repair network; the generator in the countermeasure network is generated to repair the defect sample, and the discriminator in the countermeasure network is generated to discriminate the defect sample repaired by the generator;
taking the defect sample produced in the step 12) as input, training an unsupervised network, namely generating a reactance network, wherein the network consists of a generator G and a discriminator D, the generator is used for repairing the defect sample to obtain a repaired image Y, the discriminator identifies the repaired image Y, if the confidence coefficient C output by the discriminator is lower than a set threshold value T, the robustness of the generator is insufficient, and the sample needs to be sent to the generator again for iterative training.
As shown in FIG. 3, the trained generator is used as the repair network, so that the real defect data sample can be correctedxRepairing to obtain repaired imageyExtracting real defect data samplesxAnd the repaired imageyThe SIFT features comprise global SIFT features and local SIFT features, SIFT feature matching is carried out based on feature similarity, and accordingly SIFT feature differences can be obtained, the differences are judged to be defects, namely real defect data samples are obtainedxThe defect of (2).
The method is a cable accessory lead sealing construction defect detection method based on unsupervised learning, and training does not need collection and manual calibration of defect samples, so that the omission problem caused by manual calibration is avoided; meanwhile, SIFT features are extracted, robustness is provided for local and global features of the defect image, and the real-time requirement is met; the method can realize end-to-end and full-automatic detection of the lead sealing construction defects of the cable accessories and improve the safety of cable application.
The software system corresponding to the method, namely the system for detecting the lead sealing construction defects of the cable accessories, comprises the following steps:
the network training module comprises:
an acquisition module: collecting a lead sealing construction sample of the cable accessory;
a defect sample construction module: carrying out defect construction on the cable accessory lead sealing construction sample to produce a defect sample;
a training module: training by adopting a defect sample to generate a confrontation type network, and taking a generator in the trained confrontation type network as a repair network; the generator in the countermeasure network is used for repairing the defect sample, and the discriminator in the countermeasure network is used for discriminating the defect sample repaired by the generator.
A real sample acquisition module: and acquiring a real defect data sample of the lead sealing construction of the cable accessory.
A repair module: and inputting the real defect data sample into a pre-trained repairing network to repair the real defect data sample.
A defect acquisition module: extracting SIFT characteristics of the real defect data sample and the repaired real defect data sample, carrying out SIFT characteristic matching based on the similarity, and taking the SIFT characteristic difference as a defect; wherein the SIFT features comprise global SIFT features and local SIFT features.
A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform a cable accessory lead sealing construction defect detection method.
A computing device comprising one or more processors, one or more memories, and one or more programs stored in the one or more memories and configured to be executed by the one or more processors, the one or more programs including instructions for performing a cable accessory lead sealing construction defect detection method.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The present invention is not limited to the above embodiments, and any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are included in the scope of the claims of the present invention which are filed as the application.
Claims (10)
1. A method for detecting defects of lead sealing construction of cable accessories is characterized by comprising the following steps:
acquiring a real defect data sample of the lead sealing construction of the cable accessory;
inputting the real defect data sample into a pre-trained repairing network to repair the real defect data sample;
and extracting the characteristics of the real defect data sample and the repaired real defect data sample, performing characteristic matching, and taking the characteristic difference as a defect.
2. The method for detecting the defects of the lead sealing construction of the cable accessories, as claimed in claim 1, wherein the process of training the repair network is as follows:
collecting a lead sealing construction sample of the cable accessory;
carrying out defect construction on the cable accessory lead sealing construction sample to produce a defect sample;
training by adopting a defect sample to generate a confrontation type network, and taking a generator in the trained confrontation type network as a repair network; the generator in the countermeasure network is used for repairing the defect sample, and the discriminator in the countermeasure network is used for discriminating the defect sample repaired by the generator.
3. The method for detecting the defects in the lead sealing construction of the cable accessories, according to claim 1, is characterized in that the characteristics of the real defect data sample and the repaired real defect data sample are extracted, characteristic matching is performed, and the difference of the characteristics is taken as the defects, and the method comprises the following specific steps:
and extracting SIFT characteristics of the real defect data sample and the repaired real defect data sample, carrying out SIFT characteristic matching based on the similarity, and taking the SIFT characteristic difference as a defect.
4. The method for detecting the defects of the lead sealing construction of the cable accessories, according to claim 3, wherein the SIFT features comprise global SIFT features and local SIFT features.
5. The utility model provides a cable accessories seals plumbous construction defect detecting system which characterized in that includes:
a real sample acquisition module: acquiring a real defect data sample of the lead sealing construction of the cable accessory;
a repair module: inputting the real defect data sample into a pre-trained repairing network to repair the real defect data sample;
a defect acquisition module: and extracting the characteristics of the real defect data sample and the repaired real defect data sample, performing characteristic matching, and taking the characteristic difference as a defect.
6. The system for detecting the defects of the lead sealing construction of the cable accessories as claimed in claim 5, further comprising a network training module, wherein the network training module comprises:
an acquisition module: collecting a lead sealing construction sample of the cable accessory;
a defect sample construction module: carrying out defect construction on the cable accessory lead sealing construction sample to produce a defect sample;
a training module: training by adopting a defect sample to generate a confrontation type network, and taking a generator in the trained confrontation type network as a repair network; the generator in the countermeasure network is used for repairing the defect sample, and the discriminator in the countermeasure network is used for discriminating the defect sample repaired by the generator.
7. The system for detecting the defects of the lead sealing construction of the cable accessories as claimed in claim 5, wherein the defect acquisition module is used for: and extracting SIFT characteristics of the real defect data sample and the repaired real defect data sample, carrying out SIFT characteristic matching based on the similarity, and taking the SIFT characteristic difference as a defect.
8. The system for detecting the defects of the lead sealing construction of the cable accessories as claimed in claim 7, wherein the SIFT features comprise global SIFT features and local SIFT features.
9. A computer readable storage medium storing one or more programs, characterized in that: the one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any of the methods of claims 1-4.
10. A computing device, comprising:
one or more processors, one or more memories, and one or more programs stored in the one or more memories and configured to be executed by the one or more processors, the one or more programs including instructions for performing any of the methods of claims 1-4.
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