Multiple Kalman filters model with shaping filter GPS real-time deformation analysis

In order to detect the deformation in real-time of the GPS time series and improve its reliability, the multiple Kalman filters model with shaping filter was proposed. Two problems were solved: firstly, because the GPS real-time deformation series with a high sampling rate contain coloured noise, the multiple Kalman filter model requires the white noise, and the multiple Kalman filters model is augmented by a shaping filter in order to reduce the colored noise; secondly, the multiple Kalman filters model with shaping filter can detect the deformation epoch in real-time and improve the quality of GPS measurements for the real-time deformation applications. Based on the comparisons of the applications in different GPS time series with different models, the advantages of the proposed model were illustrated. The proposed model can reduce the colored noise, detect the smaller changes, and improve the precision of the detected deformation epoch.

Principle and realization method of tunnel deformation detection based on image recognition and data transmission technology

To detect the deformation of the tunnel structure based on image sensor networks is the advanced study and application of spatial sensor technology. For the vertical settlement of metro tunnel caused by internal and external stress after its long period operation, the overall scheme and measuring principle of tunnel deformation detection system is in- troduced. The image data acquisition and processing of detection target are achieved by the cooperative work of image sensor, ARM embedded system. RS485 communication achieves the data transmission between ARM memory and host computer. The database system in station platform analyses the detection data and obtains the deformation state of tunnel inner wall, which makes it possible to early-warn the tunnel deformation and take preventive measures in time.

Methodology for Road Defect Detection and Administration Based on Mobile Mapping Data

A detailed inspection of roads requires highly detailed spatial data with sufficient precision to deliver an accurate geometry and to describe road defects visually.This paper presents a novel method for the detection of road defects.The input data for road defect detection included point clouds and orthomosaics gathered by mobile mapping technology.The defects were categorized in three major groups with the following geometric primitives:points,lines and polygons.The method suggests the detection of point objects from matched point clouds,panoramic images and ortho photos.Defects were mapped as point,line or polygon geometries,directly derived from orthomosaics and panoramic images.Besides the geometric position of road defects,all objects were assigned to a variety of attributes:defect type,surface material,center-of-gravity,area,length,corresponding image of the defect and degree of damage.A spatial dataset comprising defect values with a matching data type was created to perform the attribute analysis quickly and correctly.The final product is a spatial vector data set,consisting of points,lines and polygons,which contains attributes with further information and geometry.This paper demonstrates that mobile mapping suits a large-scale feature extraction of road infrastructure defects.By its simplicity and flexibility,the presented methodology allows it to be easily adapted to extract further feature types with their attributes.This makes the proposed approach a vital tool for data extraction settings with multiple mobile mapping data analysts,e.g.,offline crowdsourcing.

Single-Shot 360-Degree Cranial Deformity Detection System Using Digital Image Correlation

In this paper,a single-shot 360-degree cranial deformity detection system using digital image correlation(DIC)is presented to quickly obtain and detect accurate 3D data of infants’cra-nium.By introducing plane mirrors into a stereo 3D DIC measurement system,a multi-view 3D imaging model is established to convert 3D data from real and virtual perspectives into 360-degree 3D data of the tested infant cranium,achieving single-shot and panoramic 3D measurement.Exper-imental results showed that the performance and measurement accuracy of the proposed system can meet the requirements for cranial deformity detection,which provides a fast,accurate,and low-cost solution medically.

Potential loess landslide deformation monitoring using L-band SAR interferometry

Multi-temporal InSAR technique can implement continuous earth surface deformation detection with long time scale and wide geographical coverage.In this paper,we first employ the Small Baseline Subset method to survey potential landslides in Guide County,Qinghai Province,which is identified as a loess landslide prone area for geological and climate conditions.Two anomalous deformation regions are detected by L-band Phased Array and L-band Synthetic Aperture Radar stacks.Then,qualitative and quantitative evaluations of the measuring points are given for understanding the distribution regularity of deformation.Finally,preliminary correlation between the time-series deformation and triggering factors is analyzed to explore the driving mechanism for landslide movement.The results demonstrate that L-band SAR has high potential in landslide monitoring applications and can be used as the basis for landslide recognizing,precursory information extracting,and early warning.

Ability to detect and locate gross errors on DEM matching algorithm

Digital elevation model(DEM)matching techniques have been extended to DEM deformation detection by substituting a robust estimator for the least squares estimator,in which terrain changes are treated as gross errors.However,all existing methods only emphasise their deformation detecting ability,and neglect another important aspect:only when the gross error can be detected and located,can this system be useful.This paper employs the gross error judgement matrix as a tool to make an in-depth analysis of this problem.The theoretical analyses and experimental results show that observations in the DEM matching algorithm in real applications have the ability to detect and locate gross errors.Therefore,treating the terrain changes as gross errors is theoretically feasible,allowing real DEM deformations to be detected by employing a surface matching technique.