The SQVT-SVMD-PE Denoising Method for Vibration Signals and Its Application

Abnormal environmental conditions or sensor anomalies in deformation monitoring scenarios of ancient buildings pose serious challenges to deformation monitoring. To eliminate or mitigate these impacts and improve denoising accuracy and reliability, this paper proposes a joint denoising model of Sample Quantile Value Testing (SQVT), Successive Variational Mode Decomposition (SVMD), and Permutation Entropy (PE) for deformation monitoring. Specifically, the SQVT model detects multiple outliers. Second, SVMD is introduced to effectively obtain intrinsic mode functions (IMFs). Additionally, PE is performed to remove high-noise components for enhanced accuracy. Finally, simulations and field experiments are used to validate the effectiveness of the proposed model and provide valuable insights for denoising in deformation monitoring.