Monitoring and stability analysis of roadbed & high slope prior to highway construction.

Monitoring in highway projects is significant for the safety, efficiency and quality of construction. This paper proposes a detailed method for monitoring soft-soil roadbed and high-slope, and the layered settlement gauge and total station are employed to carry out experimental monitoring. The law and stability of soft-soil roadbed settlement and deformation under high-slope are further analyzed. The results show that the cumulative values of roadbed settlement and slope platform deformation in general both increase with the increase of monitoring time. However, near 180 days, an abnormal settlement phenomenon was monitored on both sides of the highway with a maximum value of 9.44 mm. This phenomenon was captured at gauge #1, #3, and #4 on observation stake 3, and exact oppositely, it was also observed at gauge #2 on observation stake 4. Moreover, unusual deformations of the high-slope platforms occurred over a period of 10 to 30 days, and these unusual settlements and deformations are indicative of the highway's instability. Therefore, the monitoring on soft-soil roadbed settlement and high-slope deformation can provide reference for highway construction.

Wavelet denoising of fiber optic monitoring signals in permafrost regions.

To address the noise issue in fiber optic monitoring signals in frozen soil areas, this study employs wavelet denoising techniques to process the fiber optic signals. Since existing parameter choices for wavelets are typically based on conventional environments, selecting suitable parameters for frozen soil regions becomes crucial. In this work, an index library is constructed based on commonly used wavelet basis functions in civil engineering. An optimal wavelet basis function is objectively selected through specific criteria. Considering the characteristic of small root mean square error in fiber optic signals in frozen soil areas, a multi-index fusion approach is applied to determine the optimal decomposition level. Field observations validate that denoised signals, with parameters set appropriately, can more accurately identify locations where settlement occurs.