Numerical simulation of dynamic surface deformation based on DInSAR monitoring

Differential interferometric synthetic aperture radar （DInSAR） technology is a new method to monitor the dynamic surface subsidence. It can monitor the large scope of dynamic deformation process of surface subsidence basin and better reflect the surface subsidence form in different stages. But under the influence of factors such as noise and other factors, the tilt and horizontal deformation curves regularity calculated by DInSAR data are poorer and the actual deviation is larger. The tilt and horizontal deformations are the important indices for the safety of surface objects protection. Numerical simulation method was used to study the dynamic deformation of LW32 of West Cliff colliery in Australia based on the DInSAR monitoring data. The result indicates that the subsidence curves of two methods fit well and the correlation coefficient is more than 95%. The other deformations calculated by numerical simulation results are close to the theory form. Therefore, considering the influence, the surface and its subsidiary structures and buildings due to mining, the numerical simulation method based on the DInSAR data can reveal the distribution rules of the surface dynamic deformation values and supply the shortcomings of DInSAR technology. The research shows that the method has good applicability and can provide reference for similar situation.

Optical Surface Monitoring系统跟踪运动靶区的位置精度和剂量精度验证

目的:评估Optical Surface Monitoring System(OSMS)测量靶区运动的几何精度和使用OSMS跟踪运动靶区放疗时的剂量精度。方法:①分别使用OSMS与锥形束CT监测腹部模体的位置,通过移动治疗床使模体产生位移和旋转,对比二者对模体位置的测量结果;②用呼吸运动平台搭载MatriXX二维电离室阵列,测量不同跟踪阈值时模体内相对剂量,分别与计划剂量分布对比,分析不同跟踪阈值时计划验证的gamma通过率。结果:OSMS和锥形束CT系统对模体平移和旋转预设偏移的测量结果差异很小,使用OSMS门控技术时OSMS的阈值越小gamma通过率越高,相对剂量分布与计划剂量的一致性也越好。结论:OSMS系统对模体表面位置监测精度高,可以应用到实际放射治疗的辅助摆位。使用OSMS门控技术跟踪运动靶区可以提高靶区的剂量精度,而且对患者不附加任何电离辐射,适合应用于分次间的辅助摆位和分次内的靶区跟踪。

Structural Surface Crack Monitoring Method Based on Electrical Potential Technique and Modern Surface Technology

Crack monitoring plays a great role in modern structural health monitoring, however, most of the conventional crack inspections have disadvantages in terms of the accuracy, expense, reliability, durability and level of instrumentation required. Thus, development of a simple and reliable crack inspection technique that allows continuous monitoring has been desired. In this paper, electrical potential technique and modern surface technology are employed together to develop a new structural surface crack monitoring method. A special crack monitoring coating sensor based on electrical potential technique was deposited on the hot spot of the structure by modern surface technology. The sensor consists of three layers： the isolated layer, the sensing layer and the protective layer. The isolated layer is prepared by anodic oxidation technology, the sensing layer is made of ion plated copper, and the protective layer is made of silicone. The thickness of each layer is at micrometer magnitude. The electrical conductivity of the sensor is very stable, and the fatigue performance of the specimen with or without coating sensor is nearly unchanged. The crack monitoring experiment result shows that there are two sudden rises of the coating sensor electrical potential values, corresponding to different stages of the crack initiation and propagation. Since the width of the surface coating sensor is only 0.5 mm, this crack monitoring sensor can detect the propagation of cracks less than 0.5 mm long. The method proposed takes the simplicity of electrical potential technique and can monitor surface crack of nearly all kinds of structures precisely. The results of this paper may form the basis of a new crack monitoring system.

Application of micro-seismic monitoring technology in mining engineering

Micro-seismic phenomena, occurring when rock masses are subjected to forces and failures, allow the determination of their unstable states and failure zones by analyzing micro-seismic signals. We first present the principles of micro-seismic monitoring and location, as well as an underground explosion-proof micro-seismic monitoring system. Given a practical engineering application, we describe the application of micro-seismic monitoring technology in determining the height of a "two-zone" overburden, i.e., a caving zone and a fracture zone, the width of a coal-pillar section and the depth of failure of a floor. The workfaces monitored accomplished safe and highly efficient mining based on our micro-seismic monitoring results and provide direct proof of the reliability and validity of micro-seismic monitoring technology.

Determining areas in an inclined coal seam floor prone to water-inrush by micro-seismic monitoring

The failure depth of the coal seam floor is one important consideration that must be kept in mind when mining is carried out above a confined aquifer.Determining the floor failure depth is the essential precondition for predicting the water-resisting ability of the floor.We have used a high-precision microseismic monitoring technique to overcome the limited amount of data available from field measurements. The failure depth of a coal seam floor,especially an inclined coal seam floor,may be more accurately estimated by monitoring the continuous,dynamic failure of the floor.The monitoring results indicate the failure depth of the coal seam floor near the workface conveyance roadway（the lower crossheading） is deeper and that the failure range is wider here compared to the coal seam floor near the return airway（the upper crossheading）.The results of micro-seismic monitoring show that the dangerous area for water-inrush from the coal seam floor may be identified.This provides an important field measurement that helps ensure safe and highly efficient mining of the inclined coal seam above the confined aquifer at the Taoyuan Coal Mine.

Contribution of the BDS to availability and reliability improvement:A case study of dam surface displacement monitoring in China

The GPS-only system is limited in dam surface monitoring because of its low availability and reliability due to the visible satellites are not enough. This dilemma is expected to be solved through incorporating the China’s BeiDou System(BDS). This contribution will quantitatively analyse the availability and reliability improvements from DBS in different shielding situations of dams. The analysis is conducted through simulating a dam obstruction with different size, azimuth and distance to receiver. The similar experiments are simulated in the area across China in order to explore these contributions in different locations. Quantitative analysis results derive conclusions:(1) In most areas, the availability improved from 50% of GPS-only to 95% of BDS + GPS when most of the GEO/IGSO satellites are not blocked, and to70% even when most of GEO/IGSO satellites are blocked.(2) The average MDBs can be reduced by half when most of the GEO/IGSO satellites are not blocked, and by 10% even when most of GEO/IGSO satellites are blocked.

Research on the Fault Monitoring System in Free-form Surface CNC Machining Based on Wavelet Analysis

Carrying out experiments and researches on tool bre ak age and undercut of work-piece of free-form surface by using wavelet analysis, both the fault features can be extracted in a special frequency segment of wave let decompose. According to the feature of transient fault, the author proposes for the first time the automatic determination technology of the threshold by us e of the adaptive filter characteristic of wavelet transform. Based on profound researches on steady fault feature, this dissertation makes an effective token o f steady fault feature by using wavelet energy method, and proposes the new idea to identify cut-in case and cut-out case, thereby successfully gives an uniqu e description quantitatively on the characterization of the variation of fault a nd cutting condition in the monitoring system.

Remote Monitoring of Surfaces Wetted for Dust Control on the Dry Owens Lakebed, California

Extensive dust control on the dry Owens Lake mainly uses constructed basins that are flooded with shallow depths of fresh water. This dust control is mandated by law as a minimum percent of the area of each individual wetting basin. Wetted surfaces are evaluated for area and degree of wetness using the shortwave infrared (SWIR) band of Landsat TM, or similar earth observation satellite sensor. The SWIR region appropriate for these measurements lies within the electromagnetic spectrum between about 1.5 and 1.8 μm wavelengths. A threshold value for Landsat TM5 band 5 reflectance of 0.19 was found to conform with surfaces having a threshold for adequate wetting at a nascent point where rapid drying would occur following loss of capillary connection with groundwater. This threshold is robust and requires no atmospheric correction for the effects of aerosol scatter and attenuation as long as the features on the image appear clear. Monthly monitoring of surface wetting has proven accurate, verifiable and repeatable using these methods. This threshold can be calibrated for any Earth observation satellite that records the appropriate SWIR region. The monitoring program is expected to provide major input for the final phase of the dust control program that will have a focus to conserve water and resources.

A speckle noise suppression method based on surface waves investigation and monitoring data

The internal energy distribution of waves can be described using ocean-wave spectra.In many ways,obtaining wave spectra on a global scale is critical.Surface waves investigation and monitoring onboard the Chinese-French oceanography satellite is the first space-borne instrument for detecting wave spectra specially,which was launched on October 29,2018.It can avoid the shortage of synthetic aperture radar detection results while still having some problems,especially with the effects of speckle noise.In this study,a method to suppress the speckle noise is proposed.First,the empirical formula for background speckle noise is established.Second,many spatio-temporal representative fluctuation spectra are classified and averaged.Third,rational transfer function filtering is used to obtain speckle noise close to the along-track direction.Finally,a signal-to-noise ratio threshold is used to suppress the abnormal speckle noise.This method solves the problems existing in previous denoising methods,such as excessive denoising in the along-track direction and the inability of some abnormal noises to be denoised in the two-dimensional directional wave spectra.

On-Line Life Monitoring Technique for Tube Bundles of Boiler High-Temperature Heating Surface

High-temperature heating surface such as superheater and reheater of large-sized utility boiler all experiences a relatively severe working conditions. The failure of boiler tubes will directly impact the safe and economic operation of boiler. An on-line life monitoring model of high-temperature heating surface was set up according to the well-known L-M formula of the creep damages. The tube wall metal temperature and working stress was measured by on-line monitoring, and with this model, the real-time calculation of the life expenditure of the heating surface tube bundles were realized. Based on the technique the on-line life monitoring and management system of high-temperature heating surface was developed for a 300 MW utility boiler. An effective device was thus suggested for the implementation of the safe operation and the condition-based maintenance of utility boilers.

GF-3 InSAR Achieves Sub-centimeter Level Surface Subsidence Monitoring

The GF-3 satellite was launched on August 10,2016 from the Taiyuan Satellite Launch Center and was put into operation at the end of January,2017.It has acquired nearly 100 thousand C-band multi-polarization ocean and land SAR images,providing data support for many departments covering resource survey,typhoon early warning,disaster assessment,crop yield estimation and polar investigation.Recently,the team led by ZHANG Qingjun from

Fiber optic monitoring of an anti-slide pile in a retrogressive landslide

Anti-slide piles are one of the most important reinforcement structures against landslides,and evalu-ating the working conditions is of great significance for landslide mitigation.The widely adopted analytical methods of pile internal forces include cantilever beam method and elastic foundation beam method.However,due to many assumptions involved in calculation,the analytical models cannot be fully applicable to complex site situations,e.g.landslides with multi-sliding surfaces and pile-soil interface separation as discussed herein.In view of this,the combination of distributed fiber optic sensing(DFOS)and strain-internal force conversion methods was proposed to evaluate the working conditions of an anti-sliding pile in a typical retrogressive landslide in the Three Gorges reservoir area,China.Brillouin optical time domain reflectometry(BOTDR)was utilized to monitor the strain distri-bution along the pile.Next,by analyzing the relative deformation between the pile and its adjacent inclinometer,the pile-soil interface separation was profiled.Finally,the internal forces of the anti-slide pile were derived based on the strain-internal force conversion method.According to the ratio of calculated internal forces to the design values,the working conditions of the anti-slide pile could be evaluated.The results demonstrated that the proposed method could reveal the deformation pattern of the anti-slide pile system,and can quantitatively evaluate its working conditions.

Surface Defect Detection and Evaluation Method of Large Wind Turbine Blades Based on an Improved Deeplabv3+Deep Learning Model

The accumulation of defects on wind turbine blade surfaces can lead to irreversible damage,impacting the aero-dynamic performance of the blades.To address the challenge of detecting and quantifying surface defects on wind turbine blades,a blade surface defect detection and quantification method based on an improved Deeplabv3+deep learning model is proposed.Firstly,an improved method for wind turbine blade surface defect detection,utilizing Mobilenetv2 as the backbone feature extraction network,is proposed based on an original Deeplabv3+deep learning model to address the issue of limited robustness.Secondly,through integrating the concept of pre-trained weights from transfer learning and implementing a freeze training strategy,significant improvements have been made to enhance both the training speed and model training accuracy of this deep learning model.Finally,based on segmented blade surface defect images,a method for quantifying blade defects is proposed.This method combines image stitching algorithms to achieve overall quantification and risk assessment of the entire blade.Test results show that the improved Deeplabv3+deep learning model reduces training time by approximately 43.03%compared to the original model,while achieving mAP and MIoU values of 96.87%and 96.93%,respectively.Moreover,it demonstrates robustness in detecting different surface defects on blades across different back-grounds.The application of a blade surface defect quantification method enables the precise quantification of dif-ferent defects and facilitates the assessment of risk levels associated with defect measurements across the entire blade.This method enables non-contact,long-distance,high-precision detection and quantification of surface defects on the blades,providing a reference for assessing surface defects on wind turbine blades.

Advances in Monitorinq Methods of Downward Surface Net Radiation

Downward surface net radiation,the net energy of the earth's surface obtained through shortwave and longwave radiation process,is the main driving force for material and energy cycle in the whole earth system.In this study,the main research results of monitoring methods of downward surface net radiation at home and abroad in recent decades have been summarized,and main remote sensing radiation products produced according to various sensors have been introduced.Moreover,the monitoring methods of downward shortwave and long-wave radiation have been discussed,and their principles,advantages and disadvantages have been analyzed to provide scientific references for further study of downward surface solar net radiation in future.

Extracting Impervious Surface and Its Change Information Using Satellite Remote Sensing Data

Impervious surface is one of the important parameters of valley water circular simulation,scientific estimation for which has significant and practical value for the urban water quantity and process simulation,diffuse pollution estimating and the forecast of climate changes.The objective of this research is to get the information of impervious surface and its dynamic change.Through the computer-assisted field method,the technologies of decision tree and data mining were applied to withdraw the impervious surface information in research region by the Landsat TM data in 1988,1994 and 2002.The results suggested that the accuracy of impervious surface information extraction in the study area arrived above 94.4% in 2002 image.On this basis,the mixed method was used to extract the location and the types of the impervious surface change.The overall accuracy of monitoring reached 89%,which meets the demand of the hydrological models.

Monitoring and Analysis on Impact of Gezhouba Hydroproject on Downstream River Course

Gezhouba hydroproject was impounded and put into operation in 1981. In order to analyse the impact on the downstream river course, Jingjiang Hydrologic and Water Resources Survey Bureau of Changjiang Water Resources Commission has conducted prototype observation on the Yichang-Chenglingji river stretch. On basis of the observed data, the change in river regime and scour-sedimentation evolution and water surface profile below the dam are analysed systematically. The results show that the scouring of downstream river course mainly stretches from Yichang to Ouchikou, mainly occurring in 1980～1987; the scourring mainly takes place in the river channel and the water surface profile drops significantly in dry season,but not quite in high flood season.

Real-Time Spreading Thickness Monitoring of High-core Rockfill Dam Based on K-nearest Neighbor Algorithm

During the storehouse surface rolling construction of a core rockfilldam, the spreading thickness of dam face is an important factor that affects the construction quality of the dam storehouse' rolling surface and the overallquality of the entire dam. Currently, the method used to monitor and controlspreading thickness during the dam construction process is artificialsampling check after spreading, which makes it difficult to monitor the entire dam storehouse surface. In this paper, we present an in-depth study based on real-time monitoring and controltheory of storehouse surface rolling construction and obtain the rolling compaction thickness by analyzing the construction track of the rolling machine. Comparatively, the traditionalmethod can only analyze the rolling thickness of the dam storehouse surface after it has been compacted and cannot determine the thickness of the dam storehouse surface in realtime. To solve these problems, our system monitors the construction progress of the leveling machine and employs a real-time spreading thickness monitoring modelbased on the K-nearest neighbor algorithm. Taking the LHK core rockfilldam in Southwest China as an example, we performed real-time monitoring for the spreading thickness and conducted real-time interactive queries regarding the spreading thickness. This approach provides a new method for controlling the spreading thickness of the core rockfilldam storehouse surface.

Use of SAR interferometry for monitoring illegal mining activities: A case study at Xishimen Iron Ore Mine

The development and application of the ''digital mine'' concept in China depends heavily upon the use of remote sensing data as well as domestic expertise and awareness. Illegal mining of mineral resources has been a serious long term problem frustrating the Xishimen Iron Ore Mine management. This mine is located in Wu'an county in Hebei province, China. Illegal activities have led to enormous economic losses by interfering with the normal operation of the Xishimen mine and have ruined the surrounding environ- ment and the stability of the Mahe riverbed the crosses the mined area. This paper is based on field recon- naissance taken over many years around the mine area. The ground survey data are integrated with Differential Synthetic Aperture Radar Interferometry (D-InSAR) results from ALOS/PALSAR data to pin- point mining locations. By investigating the relationship between the resulting interferometric deforma- tion pattern and the mining schedule, which is known a priori, areas affected by illegal mining activities are identified. To some extent these areas indicate the location of the illegal site. The results clearly dem- onstrate D-InSAR's ability to cost-effectively monitor illegal mining activities.

Embedded System Development for Detection of Railway Track Surface Deformation Using Contour Feature Algorithm

Derailment of trains is not unusual all around the world,especially in developing countries,due to unidentified track or rolling stock faults that cause massive casualties each year.For this purpose,a proper condition monitoring system is essential to avoid accidents and heavy losses.Generally,the detection and classification of railway track surface faults in real-time requires massive computational processing and memory resources and is prone to a noisy environment.Therefore,in this paper,we present the development of a novel embedded system prototype for condition monitoring of railway track.The proposed prototype system works in real-time by acquiring railway track surface images and performing two tasks a)detect deformation(i.e.,faults)like squats,shelling,and spalling using the contour feature algorithm and b)the vibration signature on that faulty spot by synchronizing acceleration and image data.A new illumination scheme is also proposed to avoid the sunlight reflection that badly affects the image acquisition process.The contour detection algorithm is applied here to detect the uneven shapes and discontinuities in the geometrical structure of the railway track surface,which ultimately detects unhealthy regions.It works by converting Red,Green,and Blue(RGB)images into binary images,which distinguishes the unhealthy regions by making them white color while the healthy regions in black color.We have used the multiprocessing technique to overcome the massive processing and memory issues.This embedded system is developed on Raspberry Pi by interfacing a vision camera,an accelerometer,a proximity sensor,and a Global Positioning System(GPS)sensors(i.e.,multi-sensors).The developed embedded system prototype is tested in real-time onsite by installing it on a Railway Inspection Trolley(RIT),which runs at an average speed of 15 km/h.The functional verification of the proposed system is done successfully by detecting and recording the various railway track surface faults.An unhealthy frame’s onsite detection processing time was recorded at approximately 25.6ms.The proposed system can synchronize the acceleration data on specific railway track deformation.The proposed novel embedded system may be beneficial for detecting faults to overcome the conventional manual railway track condition monitoring,which is still being practiced in various developing or underdeveloped countries.