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In filling engineering, the mechanical properties of geomaterials are the most important mechanical indicators. With the improvement of the measurement technology, the falling ball test (FBT) method has been gradually popularized and applied to the testing of geomaterials mechanical properties. In order to verify the testing accuracy of the FBT method, experimental results of the deformation modulus tested for the homogeneous fine-grained materials and the layered structures using the FBT method are compared with the K 30 plate load test, which is the earliest and the most widely used in-situ test method. And some conclusions are drawn in this present paper.

Through theoretical research and actual road condition analysis, this paper establishes the simulation calculation model and the spectrum analysis model. Through the spectrum inversion, the stable road surface state is obtained, and the conversion relationship between the reconstruction depth of the spectral reproduction method and the structural depth of the volume displacement method is obtained. Through the conversion relationship of a typical single spectrum, the relationship between SMTD and TD is obtained under each type of standard waveform. Actually, in the process of sand paving, due to the presence of the exposed part, the SMTD and TD in the actual road surface are not positively correlated, thereby correcting the relationship between SMTD and TD. The acquired road surface data is modeled by MATLAB, and the analog waveform is made according to the actual waveform, and the reduced order decomposition is performed to determine the range of a. The intercept b value is determined by comparing the experimental spectra before and after sanding. This paper solves the problem that the detection mechanism needs to perform statistical correlation test in accordance with the requirements of JTG-E60 regulations to meet the requirements of pavement assessment.

Surface evenness affects vehicle safety, service life, and passenger comfort. The road surface with poor flatness will produce resistance to the vehicle driving, making the vehicle vibrate and bump, hindering the safety of the vehicle driving, and will also cause local water accumulation, speed up the road damage and so on. In order to make the vehicle safe, passengers feel comfortable, road life growth, road flatness detection is particularly important.In order to make the vehicle safe to travel, passengers feel comfortable, the road service life growth, and the detection of road surface evenness is particularly important. In order to overcome the shortcomings of the existing algorithms for pavement evenness, this paper has put forward a new fast algorithm that can be applied to the continuous vialog, and according to the elevation value obtains the evenness standard deviation σ. The results show that the algorithm is high reliability, which provides a reference for the upgrade of instruments and equipment, and makes up for the shortcomings that the continuous vialog cannot be tested quickly.