Study Of Pavement Properties Based On Wavelet Analysis

Road surface is one of the indispensible parts in automobile travelling. The quality of road surface has direct impact on driving safety, comfort, dynamic property and economical efficiency. The characteristic parameters, such as road adhesion coefficient and road roughness, provide a way to evaluate road surface. In addition, the acquisition of these parameters has put great application value on the analysis of automobile road tests, road condition detection and the time cycle of road maintenance.As is known to all, automobile travels through the interaction force between wheels and road surface. Therefore, the road surface characteristic parameters could be obtained from real-time measurement of wheel force signals, the acquisition of the accurate data of which calls for denoising process since they have been exposed to various noises inevitably. The final characteristic parameters are to be extracted from the denoised wheel force signals, for the effect of denoising process directly influences the whole work. The main contents of the study are based on the above procedures. They are as follows:(1) The author gives an overall elaboration of wavelet analysis theory, which provides a method to denoise wheel force signals, as well as its advantages on processing signals.(2) To fulfill the requirements of the experiment, the paper has adopted Six-axis Wheel Force Transducer to collect several groups of bituminous road surface signals of "still to acceleration to brake". The paper has also adopted Six-axis Wheel Force Transducer to collect several groups of bituminous road and bad stone road signals of uniform motion in a straight line.(3) The denoising process is completed by analyzing the source and characteristics of the noises through wavelet analysis. The result of denoising shows that the noises has been erased whereas the vital information has been kept, thus providing the reliable analyzing data for the subsequent study on road surface features. The author collects the peak-value road adhesion coefficient of bituminous road surface during braking by analyzing the signals from denoised tyre longitudinal force and normal reaction. The result is in accord with that in automobile theory. The result show that based on the wheel force signal is used to extract the maximum coefficient has better accuracy, thus providing the reliable analyzing data for the subsequent study on road surface features.(4) The analysis on the construct and features of normal dynamic load signals provides support to collect road roughness information by using normal dynamic load. The author has collected the wheel force signals of two different road surface by Six-axis Wheel Force Transducer; the signals are denoised through spectral subtraction and wavelet analysis according to the features of normal dynamic load signals; and as a last procedure, the parameters such as mean value, variance, total variance, zero-crossing rate, four-layer detail coefficient and the fourth-layer approximation coefficient are acquired from the denoised normal dynamic load signals. The differences between the two surfaces emerge after a comparison of the above parameters, which provides further data to recognize road roughness through wheel force.The results show that the pavement properties are studied by using real-time wheel force for vehicle road test is a valid and reliable test method.