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Distribution network concrete pole falling and breaking accident prediction method based on machine vision

A technology of machine vision and accident prediction, applied in neural learning methods, instruments, computer components, etc., can solve problems such as the inability to predict electric pole down accidents, save manpower and material resources, solve safety and complexity, and facilitate inquiries Effect

Active Publication Date: 2021-03-23
STATE GRID HENAN ELECTRIC POWER ELECTRIC POWER SCI RES INST +2
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Problems solved by technology

This method uses the deep learning target detection method to realize the identification and fault detection of the transmission tower during the inspection process, but it cannot predict the accident of the power pole falling

Method used

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  • Distribution network concrete pole falling and breaking accident prediction method based on machine vision

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Embodiment 1

[0030] Such as figure 1 As shown, this embodiment provides a machine vision-based method for predicting accidents of broken concrete poles in distribution networks, which includes the following steps:

[0031] S1: Get the GPS data of the electric pole: rely on the GPS locator to obtain the specific position coordinates of the electric pole to be tested;

[0032] S2: Electric pole number: Refers to the number of electric poles to be detected according to the position obtained by the GPS locator, so as to facilitate the correspondence between the accident electric pole and the number;

[0033] S3: Inspection path planning: relying on the scheduled inspection UAV, set the UAV inspection route according to the prepared pole serial number position; The position of the pole is recorded as the waypoint and the direction of the drone is set, and then the drone is controlled to fly to the starting point and start inspection according to the recorded waypoint;

[0034] S4: UAV image a...

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Abstract

The invention provides a distribution network concrete pole falling and breaking accident prediction method based on machine vision, and belongs to the technical field of power transmission system distribution network safe operation and maintenance, and the method comprises the following steps: S1, obtaining pole GPS data; S2, numbering the electric poles; S3, planning an inspection path; S4, performing unmanned aerial vehicle image acquisition; S5, preprocessing the image; S6, performing weight assignment; S7, calculating a rod falling and breaking probability and predicting an accident; S8,providing a coping measure; and S9, establishing a distribution network pole database. According to the method, the distribution network line is checked regularly through the navigation tour inspection unmanned aerial vehicle, the in-service operation state parameter characteristics such as the position, the appearance, the surrounding environment, the burial depth and the loop form of the concrete electric pole are extracted, the service time and the local meteorological data are combined, the electric pole falling and breaking accident is predicted, and response measures are taken to improvethe safety reliability of distribution network operation.

Description

technical field [0001] The invention relates to the technical field of safe operation and maintenance of a distribution network of a power transmission system, in particular to a machine vision-based prediction method for an accident of a broken concrete pole in a distribution network. Background technique [0002] The distribution network is the last section connecting the transmission network and various users. In the distribution network, concrete poles are mostly used. Ensuring the normal and stable operation of the poles is of great significance to production and life. Therefore, regular inspections of the poles are required. . At present, in the process of pole condition exploration, the common method is mainly based on manual on-site inspection. Manual inspection has the disadvantages of low efficiency, high labor intensity, and high risk factor. This makes inspection tasks extremely difficult. [0003] The patent document with the publication number CN110929646A di...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/13G06V20/41G06N3/045G06F18/25G06F18/214
Inventor 徐恒博王磊彭磊孙芊戚建军罗松涛唐欣牛荣泽李宗峰
Owner STATE GRID HENAN ELECTRIC POWER ELECTRIC POWER SCI RES INST
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