Icing thickness detection method for power transmission line icing image based on deep learning

Abstract

The invention discloses an icing thickness detection method for a power transmission line icing image based on deep learning, belongs to the field of digital image recognition, and aims at solving problems that the sensitivity and reliability of conventional tension monitoring are not high and improving the icing thickness monitoring accuracy and automation degree of a power transmission line. The method is used for the icing thickness monitoring and over-range warning for a system power transmission line, and comprises the steps: (1), collecting an icing image; (2), carrying out the preprocessing of an image, and building a data set; (3), building a convolution neural network; (4), carrying out the training and testing of a model; (5), extracting the icing thickness information, and transmitting the icing thickness information to a control center. The method introduces a digital image feature recognition method to the icing thickness detection of a power transmission and a tower, automatically extracts the thickness information through employing the icing shape features in the image, formulates a deicing plan for an operation and maintenance worker, and provides a new visual and intelligent solution for the safe and stable operation of a power system.

Description

technical field [0001] The invention belongs to the technical field of digital image recognition, and in particular relates to a method for detecting the state of ice coating thickness in an image based on a deep learning algorithm, which can be used for ice coating monitoring and overrun alarm of power transmission network equipment in a power system. Background technique [0002] The importance of the safe and stable operation of the power grid to the development of the national economy is self-evident. With the deepening of power grid interconnection and the gradual implementation of the power market, the operating environment of the power grid is also more complex, and higher requirements are put forward for the stability and reliability of the power grid. Require. my country has a vast territory, diverse climates, and complex terrain. The power grids all over the country are often damaged by various natural disasters. Most of our country often suffer from large-scale po...

AI Technical Summary

Problems solved by technology

[0005] (1) The sensor’s monitoring of icing is greatly affected by the working environment, and harsh weather conditions or electromagnetic field interference will reduce the measurement accuracy of the sensor;

[0006] (2) Camera monitoring judges the current icing status by shooting icing images of monitoring point towers or lines, but due to the lack of effective processing and utilization methods for icing images, reliable icing information cannot be obtained from them;

[0007] (3) The cost of manual inspection or helicopter inspection is high, the efficiency is low, and it is difficult to monitor the entire network;

[0008] (4) The system cannot detect hidden dangers of icing in time, resulting in the failure to issue an icing warning in time, coupled with the relative lag of deicing operations, the icing cannot be eliminated in time

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