Monitoring slope deformation using a 3-D laser image scanning system: a case study

An ILRIS-36D 3-D laser image scanning system was used to monitor the Anjialing strip mine slope on Pingshuo in Shanxi province. The basic working principles, performance indexes, features and data collection and processing methods are illus-trated. The point cloud results are analyzed in detail. The rescale range analysis method was used to analyze the deformation char-acteristics of the slope. The results show that the trend of slope displacement is stable and that the degree of landslide danger is low. This work indicates that 3-D laser image scanning can supply multi-parameter, high precision real time data over long distances. These data can be used to study the distortion of the slope quickly and accurately.

ACQUIREMENT AND COMPUTER PROCESSING OF 3-D SURFACE SHAPE DATA

The laser scanning and CCD image-transmitting measurement method and principle on acquiring 3-D curved surface shape data are discussed. Computer processing technique of 3-D curved surface shape(be called“ 3 - D surface shape”for short) data is analysed. This technique in- cludes these concrete methods and principles such as data smoothing, fitting, reconstructing ,elimi- nating and so on. The example and result about computer processing of 3- D surface shape data are given .

Epitaxial synthesis and electronic properties of monolayer Pd2Se3

Two-dimensional(2D)materials received large amount of studies because of the enormous potential in basic science and industrial applications.Monolayer Pd2Se3 is a fascinating 2D material that was predicted to possess excellent thermoelectric,electronic,transport,and optical properties.However,the fabrication of large-scale and high-quality monolayer Pd2Se3 is still challenging.Here,we report the synthesis of large-scale and high-quality monolayer Pd2Se3 on graphene-SiC(0001)by a two-step epitaxial growth.The atomic structure of Pd2Se3 was investigated by scanning tunneling microscope(STM)and confirmed by non-contact atomic force microscope(nc-AFM).Two subgroups of Se atoms have been identified by nc-AFM image in agreement with the theoretically predicted atomic structure.Scanning tunneling spectroscopy(STS)reveals a bandgap of 1.2 eV,suggesting that monolayer Pd2Se3 can be a candidate for photoelectronic applications.The atomic structure and defect levels of a single Se vacancy were also investigated.The spatial distribution of STS near the Se vacancy reveals a highly anisotropic electronic behavior.The two-step epitaxial synthesis and characterization of Pd2Se3 provide a promising platform for future investigations and applications.

Enhanced Constructability Using 4D Plus Modelling in Brownfield Sites

In the oil and gas industry, operations in greenfield sites are straightforward. However, there are increased risks, such as damage to existing facilities, unknown site conditions, and other complexities in brownfield sites. In addition to these physical risks, task scheduling is also complex, as vessels need to be replaced during a turnaround. To mitigate the risks of site conditions and realize a truncated schedule for Saudi Aramco’s operations, 3D laser scanning was combined with 3D modeling, clash detection, and time. This integrated approach minimized the shutdown period, which resulted in cost savings, heightened safety, and enhanced stakeholder communications.

法如国际贸易（上海）有限公司

FARO拓展多功能产品线一推出3-D激光扫描头 FARO Laser Scan Arm三维激光扫描测量臂在工业界首次实现期七轴测量臂与激光扫描头的完美结合，在同一坐标系下实现接触式测量和非接触式快速扫描测量。

Classified denoising method for laser point cloud data of stored grain bulk surface based on discrete wavelet threshold

Surfaces of stored grain bulk are often reconstructed from organized point sets with noise by 3-D laser scanner in an online measuring system.As a result,denoising is an essential procedure in processing point cloud data for more accurate surface reconstruction and grain volume calculation.A classified denoising method was presented in this research for noise removal from point cloud data of the grain bulk surface.Based on the distribution characteristics of cloud point data,the noisy points were divided into three types:The first and second types of the noisy points were either sparse points or small point cloud data deviating and suspending from the main point cloud data,which could be deleted directly by a grid method;the third type of the noisy points was mixed with the main body of point cloud data,which were most difficult to distinguish.The point cloud data with those noisy points were projected into a horizontal plane.An image denoising method,discrete wavelet threshold(DWT)method,was applied to delete the third type of the noisy points.Three kinds of denoising methods including average filtering method,median filtering method and DWT method were applied respectively and compared for denoising the point cloud data.Experimental results show that the proposed method remains the most of the details and obtains the lowest average value of RMSE(Root Mean Square Error,0.219)as well as the lowest relative error of grain volume(0.086%)compared with the other two methods.Furthermore,the proposed denoising method could not only achieve the aim of removing noisy points,but also improve self-adaptive ability according to the characteristics of point cloud data of grain bulk surface.The results from this research also indicate that the proposed method is effective for denoising noisy points and provides more accurate data for calculating grain volume.