Method for recognizing nest on power transmission line based on HOG features and machine learning

Abstract

The invention belongs to the field of power technology and computer vision, and aims at separating a normal image from an image with a nest, locating and finding a problem more quickly and meeting thedemands of the construction of an intelligent power grid. The invention discloses a method for recognizing a nest on a power transmission line based on HOG features and machine learning. The method comprises the following steps: 1, HOG feature extraction of a directional gradient histogram; 2, principal component analysis; 3, training of an SVM (support vector machine) classifier: 1) performing normalization; 2) extracting a feature vector of a training set obtained at a former step to form a training set of the classifier, and making a label file conforming to an SVM format; 3) finding the optimal parameters through testing; 4, the inputting of a test set image, classification through the trained classifier, and outputting of a final classification result. The method is mainly used in occasions of automatically recognizing the nest faults of the power equipment through images.

Description

technical field [0001] The invention belongs to the fields of electric power technology and computer vision, and relates to a method for identifying bird's nests of power transmission lines based on histogram of orientation gradient (HOG) features and machine learning. Specifically, it involves a bird's nest identification method for transmission lines based on HOG features and machine learning. Background technique [0002] Transmission lines play a very important role in the power system and are directly related to the electricity consumption of all walks of life in society. Large-scale power outages will bring immeasurable losses to the country's economic development. Therefore, the safe operation of transmission lines is one of the issues of great concern to the power sector. [0003] Bird activity often interferes with the normal operation of transmission lines. Its impact on transmission lines is mainly reflected in the following aspects: birds often build their nest...

AI Technical Summary

Problems solved by technology

[0005] However, this system requires long-term monitoring by staff, and is greatly affected by human factors. Long-term work will inevitably make it difficult for staff to concentrate for a long time, and work efficiency will decrease; in addition, if the subjective judgment of staff is used for these data , it is very easy to misjudge or miss the judgment, it is difficult to accurately find the potential safety hazards of power transmission equipment, and it greatly increases the maintenance cost, which cannot meet the needs of smart grid construction

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