Intelligent bridge detection system based on unmanned aerial vehicle

Abstract

The invention discloses an intelligent bridge detection system based on an unmanned aerial vehicle. The intelligent bridge detection system comprises an unmanned aerial vehicle body and a ground station control center, wherein the unmanned aerial vehicle body is provided with an image data acquisition apparatus, a flight control module, an automatic navigation module, an ultrasonic distance measurement module, a GPS module and a wireless transmission module, the ground station control center comprises a central control module, a route simulation processing module, a human-machine interaction module, an image analysis and processing module, a display module, a storage module and a wireless transmission module, the flight control module is respectively electrically connected with the image data acquisition apparatus, the automatic navigation module, the ultrasonic distance measurement module, the GPS module and the wireless transmission module, and the central control module is respectively electrically connected with the route simulation processing module, the human-machine interaction module, the image analysis and processing module, the display module, the storage module and the wireless transmission module. By adopting the intelligent bridge detection system, the detection precision is high, and the road traffic is not influenced.

Description

technical field [0001] The invention relates to the technical field of drones, in particular to an intelligent bridge detection system based on drones. Background technique [0002] In recent years, with the development of expressways, a large number of bridges have also risen. In order to ensure road safety and people's lives, bridges need to be inspected and maintained on a regular basis, and unsafe or abnormal phenomena of bridges should be detected early. On the one hand, the traditional bridge inspection is to manually contact the bridge structure with the help of escalators or bridge operating platform vehicles, and then use crack observers, tape measures, cameras and other tools to manually search, measure, and record the surface diseases of the structure. Form an electronic record report; on the other hand, manual observation of the bridge structure through a telescope, and then a rough description of the disease, can not take images, low efficiency, high difficulty...

AI Technical Summary

Problems solved by technology

On the one hand, the traditional bridge inspection is to manually contact the bridge structure with the help of escalators or bridge operating platform vehicles, and then use crack observers, tape measures, cameras and other tools to manually search, measure, and record the surface diseases of the structure. Form an electronic record report; on the other hand, manual observation of the bridge structure through a telescope, and then a rough description of the disease, can not take images, low efficiency, high difficulty, high risk factor, and low detection accuracy

[0003] Application No. 201610934918.2 discloses an intelligent video detection system for bridge diseases, including a horizontal bar. The two ends of the horizontal bar are respectively equipped with a bridge disease detection device and an environmental monitoring device under the bridge. The bridge disease detection device includes an electric cloud installed on the horizontal bar. An image acquisition device is fixed above the electric platform, and the environmental monitoring device under the bridge includes a monitoring bracket fixed on a horizontal bar, and a rotatable monitoring head is hinged on the monitoring bracket; this scheme can greatly reduce manual inspection and traditional inspection methods. The labor intensity and reduce the cost of detection, improve the intelligent level of bridge detection, however, it is only applicable to the situation where the staff operate the instrument on the bridge surface for detection, the external environment under the bridge cannot be observed, and the specific location of the disease cannot be accurately located

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