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Wind turbine generator maintenance work quality examination auxiliary method and system

A work quality, wind turbine technology, applied in relational databases, computer parts, structured data retrieval, etc., can solve problems such as inability to compare a large number of pictures in a short time, labor and time cost, low accuracy, etc. Facilitate intuitive analysis, reduce manual confirmation, and achieve high accuracy

Pending Publication Date: 2021-04-02
GUANGDONG MINGYANG WIND POWER IND GRP CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In the process of operation and maintenance, with the increase in the amount of image collection, there is a certain misjudgment rate for the quality of key point maintenance through manual judgment
Regarding whether the pictures are reused, it is impossible to compare a large number of pictures in a short time through manual judgment
Manual judgment has disadvantages such as time-consuming and low accuracy
If you want to comprehensively analyze the on-site work situation, you need to spend a lot of manpower and time costs. At present, you can only use the method of random inspection

Method used

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  • Wind turbine generator maintenance work quality examination auxiliary method and system
  • Wind turbine generator maintenance work quality examination auxiliary method and system
  • Wind turbine generator maintenance work quality examination auxiliary method and system

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Experimental program
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Embodiment 1

[0055] This embodiment discloses an auxiliary method for reviewing the quality of wind turbine maintenance work. The method is to synchronize the acquisition of picture data information and work order data, and take all pictures in a work order as an analysis unit, and input each picture In the image recognition and classification model that has been trained, the model gives the classification category and confidence probability. At the same time, each picture is mapped to md5 information, and the picture name and mapping information are saved to the database for repeated comparisons. Finally, according to the regular inspection According to the requirements of the specification, the quality of the maintenance work order is judged whether it is qualified or not, and the results are visualized.

[0056] Such as figure 1 As shown, the above-mentioned wind turbine overhaul work quality review auxiliary method in this embodiment includes the following steps:

[0057] 1) Image dat...

Embodiment 2

[0072] This embodiment discloses an auxiliary system for reviewing the quality of wind turbine maintenance work. The system uses deep learning image recognition technology to identify key points of maintenance, and uses encryption function mapping to identify reused pictures, such as Figure 4 As shown, the system is divided into a background data processing and analysis module and a front-end interface display and operation module, of which:

[0073] The background data processing analysis module includes the following functional units:

[0074] In order to reduce the impact of the system on network bandwidth, the timing task unit starts its analysis program at 4:00 every morning, and completes the tasks of image data synchronization, work order data synchronization, image data analysis, and work order quality judgment in sequence; of course, the program also The execution cycle can be set.

[0075] The data synchronization unit adopts the incremental update method to synchr...

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Abstract

The invention discloses a wind turbine generator maintenance work quality review auxiliary method and system. The method comprises the steps: taking all pictures in a work order as an analysis unit through the obtaining synchronization of picture data information and work order data, inputting each picture into a trained image recognition and classification model, and carrying out the recognitionand classification of all pictures in the work order; providing classification categories and confidence probabilities by a model, simultaneously performing md5 information mapping on each picture, storing picture names and mapping information into a database so as to repeatedly compare, finally judging whether the quality of the overhaul work order is qualified or not according to regular inspection specification requirements, and visualizing a result. According to the invention, the pictures collected in the daily maintenance process can be automatically classified, the work orders corresponding to the pictures can be automatically missed and analyzed, and the condition of repeatedly using the pictures can be automatically recognized. A report is automatically formed for the analysis result statistics, visual analysis is facilitated, and effective supervision is formed for key point pictures of work order missing detection (missing transmission) and the site where the pictures are repeatedly used.

Description

technical field [0001] The invention relates to the technical field of wind power generation operation and maintenance, in particular to an auxiliary method and system for reviewing the quality of wind turbine maintenance work. Background technique [0002] The operation and maintenance cost of wind farms is one of the largest cost components of wind farms, usually accounting for up to 25% of the total life cycle costs. Wind farm operators are under great pressure to improve the efficiency and quality of operation and maintenance work, so as to Reduce operation and maintenance costs. The operating environment of wind turbines is relatively harsh. Regular inspections can keep the equipment in the best condition and prolong the service life of wind turbines. At present, in the process of operation and maintenance, the on-site operation and maintenance personnel will take photos of the key points of maintenance. On the one hand, it is used to control the risk items of the unit...

Claims

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Application Information

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IPC IPC(8): G06Q10/00G06Q10/06G06K9/00G06K9/62G06F16/28
CPCG06Q10/20G06Q10/06395G06F16/284G06V20/20G06F18/2414G06F18/2415Y04S10/50
Inventor 孙启涛刘元波刘贞贞鲁纳纳
Owner GUANGDONG MINGYANG WIND POWER IND GRP CO LTD
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