A flatness detection device and method suitable for low-speed and variable-speed measurement

Abstract

The invention discloses a flatness detecting device and method adapting to low-speed and variable-speed measurement. The device comprises a signal receiving unit, a signal converting unit, a data processing unit and a flatness output unit. The position offset errors produced by a large amount of accelerometer data second integral of a low-speed measurement interval are effectively decreased by selecting part of effective data, namely removing part of ultra-low-speed redundant data. In the low-speed measurement interval, the existing accumulative error influence of a carrier vehicle shaking distance in a follow-up normal measurement interval is calculated according to the shaking speed obtained based on integrated acceleration. The influence of the low-speed measurement interval on the follow-up normal measurement interval is greatly reduced by utilizing data self-adaptive segmentation of running vehicle acceleration, the data gap phenomenon caused by data segmentation processing is effectively eliminated by splicing segmented road surface longitudinal section outlines, accordingly a relative real outline of a road surface is effectively obtained, and further rapid and accurate flatness measurement at different speeds is achieved.

Description

technical field [0001] The invention belongs to the technical field of road surface smoothness evaluation, and relates to a road surface smoothness evaluation device and method, in particular to a flatness detection device and method suitable for low-speed and variable-speed measurement. Background technique [0002] Road surface roughness is an important indicator of road surface evaluation. It not only affects the driving comfort of drivers and passengers, but also is related to vehicle vibration, running speed, tire wear and vehicle operating costs. index of. The roughness of the road surface is also one of the performance indicators of the road surface. The AASHTO road test research in 1960 showed that about 95% of the service performance of the road surface comes from the smoothness of the road surface. The research of pavement long-term service performance (LTPP) shows that pavement roughness, especially initial pavement roughness will seriously affect the service lif...

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Problems solved by technology

[0006] The 3m ruler method is a traditional manual measurement method. This method has problems such as low measurement efficiency, great safety hazards, affecting traffic, and measurement results are interfered by human factors, and cannot achieve fast and accurate measurement of flatness;

[0010] Existing continuous flatness detectors are often composed of multiple modules such as measuring sensors (distance finders, accelerometers, encoders, GPS receivers, etc.), computers, controllers, and data collectors. There is a high degree of coupling between modules. , high overall system complexity, low integration, poor maintainability and reliability, etc., it is necessary to invent a flatness measurement system with low overall system complexity, high integration, strong maintainability and reliability; and this detection The method is only suitable for continuous detection at high speed and uniform speed; on the one hand, at non-uniform and low speed, the method of obtaining the vibration displacement of the detection vehicle through the direct two-integration of the accelerometer will produce a large error, resulting in the measurement of the road surface profile. There are obvious differences with the real contour of the road surface; on the other hand, in the low-speed measurement interval, due to the large error in the vibration velocity obtained by one integration of the accelerometer data, this vibration velocity error will have a cumulative impact on the vehicle-loaded vibration velocity in the subsequent normal measurement interval. There will be a large measurement error in the vibration distance obtained by one-time integration of the vibration speed, and the measurement results cannot meet the inspection requirements. As the traffic becomes increasingly busy and congested, non-uniform and low speeds will be common during the detection process. In order to better adapt to the actual traffic situation , it is necessary to solve the flatness measurement problem suitable for different speeds (non-uniform speed, low speed, high speed, uniform speed)

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