The ultrasonic phased array total focusing method (TFM) has the advantages of high imaging signal-to-noise ratio (SNR) and high defect resolution, but the problem of large amount data capturing and processing limits its practical industrial applications. To reduce the imaging calculation demand of the total focusing method, a half-matrix focusing method (HFM) is proposed based on the acoustic reciprocity. The method simplifies the calculation process of full-matrix data capturing (FMC) and total focus imaging. The experimental results show that the signal obtained by the linear array transceiver sensor is highly consistent, and the imaging resolution and signal-to-noise ratio of the half-matrix focusing method are slightly lower than those of full-matrix focusing method and higher than those of the B-scan imaging. However, compared with TFM, data acquisition and computational efficiency using the HFM have been improved significantly.
From a conventional viewpoint, seismic‐prospecting background noise is usually regarded as the product of a stationary and Gaussian stochastic process. In this paper, we use statistical methods to investigate the properties of the land‐seismic‐prospecting background noise on stationarity, Gaussianity, power spectral density, and spatial correlation. We use and analyse the passive noise records collected by receiver arrays at different typical geological environments (desert, steppe, and mountainous regions). Differences exist in the statistical properties of the background noise from different geological environments, but we still find some common characteristics. It is shown that the background noise is not strictly stationary and has different stationary properties over different timescales. Most of the noise records appear to be a Gaussian process when examined over a period of about 20 s but are found to be non‐Gaussian when examined over shorter periods of about 1 s. The background noise is a kind of colored noise, and its energy mainly concentrates in the low‐frequency bands. We also find that the spatial correlation of the background noise is weak. The results of this paper provide a scientific understanding about the properties of seismic‐prospecting background noise.
In the denoising of seismic prospecting, background noise is often assumed to be stationary and Gaussian. However, this is not always appropriate for real seismic data. We used statistical tests to assess the stationarity and Gaussianity of land seismic data. The data we used for the analyses were passive noise records collected with receiver arrays in different land environments, e.g., deserts, steppes, and mountains. The results showed that the background noise was not strictly stationary, but locally stationary. The noise could be treated as a stationary series only in short time periods, whereas the stationarity became poor with increasing the time length of the noise records. By analyzing the behavior of noise data, we determined that the nonstationary noise always had more energy in the high-frequency band, which varied with the acquisition environments. The wind strength and the complexity of the environmental conditions also impacted the noise stationarity. Moreover, we found that noise in complex environments has a higher degree of Gaussianity than noise in simpler environment. Most of the noise records appeared to be a Gaussian process when examined over a period longer than 20 s, but they were found to be non-Gaussian when examined over shorter time periods of the order of 1 s.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.