Road surface roughness detection system and method based on multi-sensor

Abstract

The invention discloses a road surface smoothness detection system and method based on multi-sensors, which includes a rigid detection beam, three displacement sensors, a gyroscope, a GPS, and a rotary encoder. At the front end, three displacement sensors are arranged on the rigid detection beam at intervals along the direction of the vehicle body to obtain the smoothness of the local road surface; the gyroscope is used to obtain the attitude and azimuth of the detection beam during the driving of the car; the rotary encoder is used to obtain the mileage; GPS is used to obtain the longitude, latitude and altitude of the car. The invention uses the non-inertial longitudinal section detection theory of the small-step reference transfer principle to realize the small-wavelength detection of the longitudinal section under the condition of variable speed and slow speed, and at the same time uses the data fusion method of GPS elevation and gyroscope elevation to realize road surface The precise detection of the large wavelength of the longitudinal section, combined with the small wavelength of the longitudinal section, realizes the accurate detection of the full wavelength of the road surface.

Description

technical field [0001] The invention belongs to the technical field of roads and bridges, and relates to a detection system and method for road surface roughness parameters, in particular to a detection system and method based on multi-sensor data fusion. Background technique [0002] (1) Existing road surface roughness detection technology [0003] Pavement roughness is an important index in pavement construction acceptance and pavement condition evaluation, which reflects the longitudinal unevenness of pavement and driving comfort. The main content of road surface roughness detection and evaluation is to calculate the international roughness index (IRI) according to the unevenness of the road surface longitudinal section detected, and determine the driving quality of the road according to the size of the IRI. [0004] At present, the road surface roughness testing equipment mainly includes a level, a three-meter ruler, a continuous flatness meter, a vehicle-mounted bump a...

AI Technical Summary

Problems solved by technology

The disadvantage is manual operation, low detection efficiency, generally only used for calibration work

The disadvantage of this equipment is that it is time-consuming and labor-intensive, and the test results are affected by human factors.

The disadvantage of this instrument is that it is greatly affected by road bumps and the repeatability is not ideal

Its disadvantage is that the instrument needs to be calibrated frequently, and the calibration work is a time-consuming and laborious work

The disadvantage is that the detection speed is slow, there are certain requirements for the tested road surface, and the price is expensive

Due to the limitation of the frequency response range of the accelerometer, in order to reduce the measurement error, the driving detection speed must be increased, but the detection speed of the vehicle is affected by many factors in the actual detection process, especially the municipal road conditions, when there is a red light at the intersection, you must stop

Therefore, this detection technology cannot detect low-speed and variable-speed driving.

[0012] 7. The non-inertial reference road surface roughness detection method and technology researched and developed by Chang'an University can realize slow and variable speed detection, but the detection beam installed with the laser displacement sensor is long (generally greater than 3 meters), and the system must be installed in the On vehicles with longer wheelbases

Due to the limitations of the current instrument hardware and sensor performance and detection accuracy, it is difficult to cover all road wavelengths with only a single sensor, so it is impossible to achieve full-band detection of the road profile. In addition, for changes in driving speed, special occasions and road sections The existing methods are not well satisfied with the detection of slow speed and stop at any time, as well as the stop of urban roads and forks.

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