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Method for extracting road surface characteristic parameters based on modern time series of vertical dynamic load

A technology of time series and characteristic parameters, applied in measurement devices, instruments, etc., can solve the problems of rough detection and high cost, and achieve the effect of improving detection level, low cost and good real-time performance.

Inactive Publication Date: 2012-10-10
JIANGSU UNIV OF SCI & TECH
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Problems solved by technology

[0004] In order to overcome the shortcomings of the existing road surface measuring instruments, which are either relatively rough or costly, the present invention proposes a method for extracting road surface characteristic parameters based on the modern time series of vertical dynamic loads, using the wheel force sensor measurement system to obtain relevant measurement parameters

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  • Method for extracting road surface characteristic parameters based on modern time series of vertical dynamic load
  • Method for extracting road surface characteristic parameters based on modern time series of vertical dynamic load
  • Method for extracting road surface characteristic parameters based on modern time series of vertical dynamic load

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[0028] A Method for Extracting Pavement Characteristic Parameters Based on Modern Time Series of Vertical Dynamic Loads. The wheel force sensor is used to directly measure the road load spectrum. By building a road data acquisition system based on the wheel force sensor as the core, the sensor is installed on the test prototype vehicle, and the load spectrum data of various road surfaces are collected in the actual vehicle test. After signal preprocessing such as removing the mean value and removing trend items, AR time series modeling is carried out on the signal, combined with the adaptive Kalman filter algorithm, noise is removed to obtain the real road load spectrum, and effective road recognition is extracted by fuzzy clustering method index. It can be applied to pavement classification, pavement quality inspection and pavement simulation test. It is characterized by:

[0029] Step 1: Install WFT on the test prototype vehicle, conduct real vehicle experiments on various...

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Abstract

The invention discloses a method for extracting road surface characteristic parameters based on modern time series of vertical dynamic load. Firstly, a road spectrum signal is collected by a wheel force sensor; the signal is pretreated; an auto-regressive (AR) model is established; self-adaptive Kalman filtering is performed by a state-space model to further extract more real parameters; finally, the parameters are selected and confirmed by fuzzy clustering analysis to obtain the result to judge the road identification information. The method has the beneficial effects of high automation degree, good instantaneity, accurate measurement, low cost and positive influence on improving measurement level of road quality and construction of high-quality road and reducing domestic and overseas difference.

Description

technical field [0001] The invention belongs to the field of road surface feature recognition, and in particular relates to a method for extracting road surface feature recognition parameters based on modern time series analysis of wheel vertical dynamic loads. Background technique [0002] With the continuous improvement of the quality of highway construction in our country and the improvement of the high-grade highway network, how to test and evaluate the quality of the road surface is a very important topic at present. Among the evaluation indicators of many inspection items on the pavement, the flatness accounts for 15% to 20% of the total score of the evaluation items, and is one of the most important indicators in the quality inspection of the pavement. In the "Highway Engineering Quality Inspection and Evaluation Standard" (JTJ071-94), which was implemented on October 1, 1994, my country put forward clear requirements for the flatness index. Under the conditions of s...

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Application Information

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IPC IPC(8): G01B21/30
Inventor 刘庆华张为公张建林国余李忠国夏鹏飞钱强董晓马
Owner JIANGSU UNIV OF SCI & TECH
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