A Novel Sensor System for Measuring Wheel Loads of Vehicles on Highways
With the development of the highway transportation and business trade, vehicle Weigh-In-Motion (WIM) technology has become a key technology for measuring traffic loads. In this paper a novel WIM system based on monitoring of pavement strain responses in rigid pavement was investigated. In this WIM system multiple low cost, light weight, small volume and high accuracy embedded concrete strain sensors were used as WIM sensors to measure rigid pavement strain responses. In order to verify the feasibility of the method, a system prototype based on multiple sensors was designed and deployed on a relatively busy freeway. Field calibration and tests were performed with known two-axle truck wheel loads and the measurement errors were calculated based on the static weights measured with a static weighbridge. This enables the weights of other vehicles to be calculated from the calibration constant. Calibration and test results for individual sensors or three-sensor fusions are both provided. Repeatability, sources of error, and weight accuracy are discussed. Successful results showed that the proposed method was feasible and proven to have a high accuracy. Furthermore, a sample mean approach using multiple fused individual sensors could provide better performance compared to individual sensors.
Wavelet domain analysis for identification of vehicle axles from bridge measurements
Bridge weigh-in-motion (B-WIM) is a process by which the axle and gross vehicle weights of vehicles travelling at highway speeds can be determined from instrumented bridges. The traditional method of attaching strain transducers to the soffit of the bridge and placing axle detectors on the road surface has been replaced here by using additional transducers underneath the bridge for axle detection and nothing-on-the-road (NOR). This paper presents a wavelet based analysis of strain signals and shows the efficacy of using wavelets in pattern recognition of these signals. The transformed signals are used to identify axle passage and hence the vehicle velocity and the axle spacing. In addition to numerically generated strains, signals acquired from such a NOR instrumentation of a bridge in Slovenia have been analysed by the method of wavelet transformation to extract axle position information that was not readily detectable using existing methods.
THE ARTIFICIAL GENERATION OF ROAD SURFACE TOPOGRAPHY BY THE INVERSE FFT METHOD
Techniques are presented for the digital simulation of the height profiles of a number of correlated parallel tracks and of an entire two-dimensional random road surface. It is shown that the profiles of a number of correlated tracks may be generated by using the one-dimensional discrete Fourier transform, but, in order to generate a fully isotropic surface, it is necessary to use two-dimensional Fourier transform methods and these are discussed in detail. A sample two-dimensional isotropic road surface is generated from an experimentally determined one-dimensional spectral density and its one-dimensional statistics are compared with those of the original displacement data. For the covering abstract of the conference see TRIS 395019. (Author/TRRL)