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Pothole detection method based on acceleration sensor and machine learning

An acceleration sensor, machine learning technology, applied in the direction of material inspection products, etc., to avoid the influence of subjective factors, high accuracy, and improve the detection accuracy.

Active Publication Date: 2020-02-21
CHONGQING UNIV
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Problems solved by technology

This detection method relies on user interaction, and requires users to reflect the pothole information on social software in a timely manner after discovering potholes. Certainty

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  • Pothole detection method based on acceleration sensor and machine learning
  • Pothole detection method based on acceleration sensor and machine learning
  • Pothole detection method based on acceleration sensor and machine learning

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Embodiment Construction

[0020] The present invention will be further described below in conjunction with the drawings and embodiments:

[0021] The hierarchical structure of the application environment of the present invention is as figure 1 As shown, the first layer is the perception layer, which is composed of an acceleration sensor module, a GPS module and a controller module. The acceleration sensor module is used for the collection of acceleration data when the car is running; the GPS module is used for the collection of position information when the car is running ; The controller module is implemented by the Arduino embedded development board, used for data interaction with the acceleration sensor module and the GPS module, and the obtained acceleration data and position information data are packaged and transmitted to the data storage module;

[0022] After the perception layer is the data storage module, the data storage module adopts Raspberry Pi; the data storage module is used to receive the da...

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Abstract

The invention provides a pavement pit detection method based on an acceleration sensor and machine learning. The method comprises the following steps that 1, a controller module acquires acceleration data collected by the acceleration sensor and positioning information data collected by a GPS module; 2, an embedded development board is used for sending the acquired acceleration sensor data and the GPS positioning information data to a Raspberry Pi; 3, the Raspberry Pi is used for storing the collected road information in an embedded database and transmit the data to a server during network connection; 4, the server receives the road information data and calculates a pit detection threshold value, and after the threshold value is used to detect pits, pit information data is transmitted to a map display module; and 5, the map display module marks the pits on a map. Accuracy of detection is improved, influence of subjective factors of men is also overcome, and reliability of detection is improved.

Description

Technical field [0001] The invention belongs to a pothole detection method in road surface detection technology, and specifically relates to a road pothole detection method based on acceleration sensors and machine learning. Background technique [0002] Traditional pothole detection technology (road detection technology) generally analyzes the images collected by a high-definition camera and judges whether there is a pothole on the road. At present, the use of image processing to detect potholes is due to the high price of cameras used, and the high cost of road pothole detection systems based on this is difficult to mass production. [0003] In response to this problem, recent pothole detection systems are based on cheap acceleration sensors to collect data and detect potholes by threshold. The basic method is to collect the vertical acceleration data of the car driving on the road and compare it with the threshold at low speed and high speed to determine whether the car has enc...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01N33/42
CPCG01N33/42
Inventor 刘铎任津廷张靖宇李阳梁靓
Owner CHONGQING UNIV
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