Baseline correction for near-fault ground motion recordings of the 2008 Wenchuan Ms8.0 earthquake

In this study, both records of a digital accelerometer and a seismograph at a far-field station for the 2008 Ms8.0 Wenchuan earthquake were analyzed, and a pulsive noise model for acceleration record was found. By comparing with the result of a rotary-table tilt test, we concluded that the noises in the acceleration records were caused by ground tilt as a result of rotational ground motion. We analyzed the key noises that may cause baseline offset, and proposed a baseline-correction scheme for preserving the long-period ground motion in accordance with specific pulse positions. We then applied this correction method to some near-field strongmotion acceleration records. The result shows that this method can obtain near-field ground displacements, including permanent displacements, in agreement with GPS data, and that this method is more stable than other methods.

Spectral baseline estimation using penalized least squares with weights derived from the Bayesian method

The penalized least squares(PLS)method with appropriate weights has proved to be a successful baseline estimation method for various spectral analyses.It can extract the baseline from the spectrum while retaining the signal peaks in the presence of random noise.The algorithm is implemented by iterating over the weights of the data points.In this study,we propose a new approach for assigning weights based on the Bayesian rule.The proposed method provides a self-consistent weighting formula and performs well,particularly for baselines with different curvature components.This method was applied to analyze Schottky spectra obtained in 86Kr projectile fragmentation measurements in the experimental Cooler Storage Ring(CSRe)at Lanzhou.It provides an accurate and reliable storage lifetime with a smaller error bar than existing PLS methods.It is also a universal baseline-subtraction algorithm that can be used for spectrum-related experiments,such as precision nuclear mass and lifetime measurements in storage rings.

Improved Baseline Correction Method Based on Polynomial Fitting for Raman Spectroscopy

Raman spectrum, as a kind of scattering spectrum, has been widely used in many fields because it can characterize the special properties of materials. However, Raman signal is so weak that the noise distorts the real signals seriously. Polynomial fitting has been proved to be the most convenient and simplest method for baseline correction. It is hard to choose the order of polynomial because it may be so high that Runge phenomenon appears or so low that inaccuracy fitting happens. This paper proposes an improved approach for baseline correction, namely the piecewise polynomial fitting （PPF）. The spectral data are segmented, and then the proper orders are fitted, respectively. The iterative optimization method is used to eliminate discontinuities between piecewise points. The experimental results demonstrate that this approach improves the fitting accuracy.