With a structure’s foundation and supporting ground generally being critical to its design and construction, understanding how soil behaves under various stress and drainage conditions is imperative. It is well known that certain characteristics and behaviors of soils with fines are highly dependent on water content and liquid limit is one of the important soil index properties to define such characteristics. However, conventional liquid limit measurement techniques can be easily affected by the proficiency of the operator, potentially leading to disastrous consequences. The dynamic properties of soils are required in numerous applications, and current testing techniques frequently call for specialized lab equipment, which is often pricy and delicate to test conditions. To address these concerns and advance the state of the art, this study explores a novel method to determine the liquid limit of cohesive soil by employing video-based vibration analysis which may precisely measure and identify the status of a soil’s water content. In this research, the modal characteristics of cohesive soil columns are extracted from videos by phase-based motion estimation. By utilizing the proposed method that analyzes the optical flow in every pixel of the series of frames that effectively represents the motion of corresponding points of the soil specimen, the vibration characteristics of the entire soil specimen could be assessed in a non-contact and non-destructive manner. The experimental investigation results compared with the liquid limit determined by the conventional method verify that the proposed method reliably and straightforwardly identifies the liquid limit of clay. It is envisioned that the proposed approach could be applied to measuring liquid limit of soil in practical field, entertaining its simple implementation that only requires a digital camera or even a smartphone without the need for special equipment or techniques that may be subject to the proficiency of the operator.
Among various signal processing approaches, stochastic resonance (SR) has been widely employed for weak signal detection and mechanical fault diagnosis. Various advancements have been focused on identifying useful information from the frequency domain by optimizing parameters in a post-processing environment to activate SR. Yet, these methods often require detailed information about the original signal a priori, which is challenging from measurements that are already overwhelmed by noise. Furthermore, classical bistable SR has often been employed for weak signal detection, which exhibits an inherent signal distortion due to output saturation that reduces the signal recovery performance. To address these concerns and advance the state of the art, we propose a novel signal denoising method that exploits unsaturated SR in a parallel array of piecewise continuous bistable systems. The original noise-contaminated signal is adaptively scaled by an optimal gain value that is determined from a non-dimensional model based on the attendant noise level, which is one of the few parameters that can be reliably identified from practical noise-contaminated signals. As a result, the proposed approach can operate without any post-processing optimization and parameter selection. Numerical investigations are performed with a simulated acoustic emission signal (amplitude modulated sine pulse) with various amplitudes and attendant noise levels to illustrate the operation principle and the effectiveness of the proposed approach. The results exemplify the promising potential of implementing the proposed approach for enhancing online signal denoising in practice.
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