Application of GNSS-PPP on Dynamic Deformation Monitoring of Offshore Platforms

The real-time dynamic deformation monitoring of offshore platforms under environmental excitation is crucial to their safe operation.Although Global Navigation Satellite System-Precise Point Positioning(GNSS-PPP)has been considered for this purpose,its monitoring accuracy is relatively low.Moreover,the influence of background noise on the dynamic monitoring accuracy of GNSS-PPP remains unclear.Hence,it is imperative to further validate the feasibility of GNSS-PPP for deformation monitoring of offshore platforms.To address these concerns,vibration table tests with different amplitudes and frequencies are conducted.The results demonstrate that GNSS-PPP can effectively monitor horizontal vibration displacement as low as±30 mm,which is consistent with GNSS-RTK.Furthermore,the spectral characteristic of background noise in GNSS-PPP is similar to that of GNSS-RTK(Real Time Kinematic).Building on this observation,an improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)has been proposed to de-noise the data and enhance the dynamic monitoring accuracy of GNSS-PPP.Field monitoring application research is also undertaken,successfully extracting and analyzing the dynamic deformation of an offshore platform structure under environmental excitation using GNSS-PPP monitoring in conjunction with improved CEEMDAN de-noising.By comparing the de-noised dynamic deformation trajectories of the offshore platform during different periods,it is observed that the platform exhibits reversible alternating vibration responses under environmental excitation,with more pronounced displacement deformation in the direction of load action.The research results confirm the feasibility and potential of GNSS-PPP for dynamic deformation monitoring of offshore platforms.

Effects of Continuous Non-Invasive Blood Pressure Monitoring on Intraoperative Hemodynamics and Postoperative Myocardial Injury in Craniotomy:Comparison Between Groups Based on Self-Control and Propensity Score Matching

Objective:To explore the effect of continuous non-invasive blood pressure monitoring on intraoperative hemodynamics and postoperative myocardial injury in craniotomy.Methods:120 cases of elective craniotomy were divided into the self-control group(continuous non-invasive blood pressure monitoring and intermittent cuff non-invasive blood pressure monitoring,CNAP group)and propensity score matching group(only intermittent cuff non-invasive blood pressure measurement in previous craniotomy,PSM group);Goal-directed hemodynamic management in CNAP group included heart rate(HR),blood pressure(BP),stroke volume(SV),stroke variability(SVV),and systemic vascular resistance index(SVRI).The main index is to compare the troponin level within 72 hours after operation between the CNAP group and the PSM group;The secondary indicators are the comparison of the hemodynamic conditions between the CNAP group and the PSM at 10 specific time points.Results:The incidence of postoperative myocardial injury in the CNAP group was significantly lower than that in the PSM group(12%vs.30%,P=0.01);in the CNAP group hypotensive episodes(6 vs.3,P=0.01),positive balance of fluid therapy(700 vs.500 mL,P<0.001),more use of vasoactive drugs(29 vs.18,P=0.04),more stable hemodynamics medical status(P=0.03)were recorded.Conclusion:The hemodynamic management strategy based on continuous non-invasive blood pressure monitoring can reduce the incidence of myocardial injury after elective craniotomy and maintain a more stable hemodynamic state.

Comparing a non-invasive hemodynamic monitor with minimally invasive monitoring during major open abdominal surgery

As part of the enhanced recovery after surgery （ERAS） protocol, the goal-directed fluid management with hemodynamic monitoring can effectively guide perioperative fluid use and significantly improve the outcomes in highrisk patients undergoing major surgeries. Several minimally invasive and non-invasive monitoring devices are commercially available for clinical use. As part of an internal evaluation, we reported the results from three different hemodynamic monitoring devices used in a patient undergoing a major abdominal surgery.

Microseismic monitoring and forecasting of dynamic disasters in underground hydropower projects in southwest China:A review

The underground hydropower projects in Southwest China is characterized by large excavation sizes,high geostresses,complicated geological conditions and multiple construction processes.Various disasters such as collapses,large deformations,rockbursts are frequently encountered,resulting in serious casualties and huge economic losses.This review mainly presents some representative results on microseismic(MS)monitoring and forecasting for disasters in hydropower underground engineering.First,a set of new denoising,spectral analysis,and location methods were developed for better identification and location of MS signals.Then,the tempo-spatial characteristics of MS events were analyzed to understand the relationship between field construction and damages of surrounding rocks.Combined with field construction,geological data,numerical simulation and parametric analysis of MS sources,the focal mechanism of MS events was revealed.A damage constitutive model considering MS fracturing size was put forward and feedback analysis considering the MS damage of underground surrounding rocks was conducted.Next,an MS multi-parameter based risk assessment and early warning method for dynamic disasters were proposed.The technology for control of the damage and deformation of underground surrounding rocks was proposed for underground caverns.Finally,two typical underground powerhouses were selected as case studies.These achievements can provide significant references for prevention and control of dynamic disasters for underground engineering with similar complicated geological conditions.

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.

Seismic dynamic monitoring in CO_2 flooding based on characterization of frequency-dependent velocity factor

The phase velocity of seismic waves varies with the propagation frequency, and thus frequency-dependent phenomena appear when CO2 gas is injected into a reservoir. By dynamically considering these phenomena with reservoir conditions it is thus feasible to extract the frequency-dependent velocity factor with the aim of monitoring changes in the reservoir both before and after CO2 injection. In the paper, we derive a quantitative expression for the frequency-dependent factor based on the Robinson seismic convolution model. In addition, an inversion equation with a frequency-dependent velocity factor is constructed, and a procedure is implemented using the following four processing steps： decomposition of the spectrum by generalized S transform, wavelet extraction of cross-well seismic traces, spectrum equalization processing, and an extraction method for frequency-dependent velocity factor based on the damped least-square algorithm. An attenuation layered model is then established based on changes in the Q value of the viscoelastic medium, and spectra of migration profiles from forward modeling are obtained and analyzed. Frequency-dependent factors are extracted and compared, and the effectiveness of the method is then verified using a synthetic data. The frequency-dependent velocity factor is finally applied to target processing and oil displacement monitoring based on real seismic data obtained before and after CO2 injection in the G89 well block within Shengli oilfield. Profiles and slices of the frequency-dependent factor determine its ability to indicate differences in CO2 flooding, and the predicting results are highly consistent with those of practical investigations within the well block.

Comparative Analysis of ARIMA and LSTM Model-Based Anomaly Detection for Unannotated Structural Health Monitoring Data in an Immersed Tunnel

Structural Health Monitoring(SHM)systems have become a crucial tool for the operational management of long tunnels.For immersed tunnels exposed to both traffic loads and the effects of the marine environment,efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge.This study proposed amodel-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel.Firstly,a dynamic predictive model-based anomaly detectionmethod is proposed,which utilizes a rolling time window for modeling to achieve dynamic prediction.Leveraging the assumption of temporal data similarity,an interval prediction value deviation was employed to determine the abnormality of the data.Subsequently,dynamic predictive models were constructed based on the Autoregressive Integrated Moving Average(ARIMA)and Long Short-Term Memory(LSTM)models.The hyperparameters of these models were optimized and selected using monitoring data from the immersed tunnel,yielding viable static and dynamic predictive models.Finally,the models were applied within the same segment of SHM data,to validate the effectiveness of the anomaly detection approach based on dynamic predictive modeling.A detailed comparative analysis discusses the discrepancies in temporal anomaly detection between the ARIMA-and LSTM-based models.The results demonstrated that the dynamic predictive modelbased anomaly detection approach was effective for dealing with unannotated SHM data.In a comparison between ARIMA and LSTM,it was found that ARIMA demonstrated higher modeling efficiency,rendering it suitable for short-term predictions.In contrast,the LSTM model exhibited greater capacity to capture long-term performance trends and enhanced early warning capabilities,thereby resulting in superior overall performance.

Mechanism,prevention,and control of mining-induced dynamic disasters in underground metal mines in China:Challenges and solutions

Metal mineral resources play an indispensable role in the development of the national economy.Dynamic disasters in underground metal mines seriously threaten mining safety,which are major scientific and technological problems to be solved urgently.In this article,the occurrence status and grand challenges of some typical dynamic disasters involving roof falling,spalling,collapse,large deformation,rockburst,surface subsidence,and water inrush in metal mines in China are systematically presented,the characteristics of mining-induced dynamic disasters are analyzed,the examples of dynamic disasters occurring in some metal mines in China are summarized,the occurrence mechanism,monitoring and early warning methods,and prevention and control techniques of these disasters are highlighted,and some new opinions,suggestions,and solutions are proposed simultaneously.Moreover,some shortcomings in current disaster research are pointed out,and the direction of efforts to improve the prevention and control level of dynamic disasters in China’s metal mines in the future is prospected.The integration of forward-looking key innovative theories and technologies in the abovementioned aspects will greatly enhance the cognitive level of disaster prevention and mitigation in China’s metal mining industry and achieve a significant shift from passive disaster relief to active disaster prevention.

Improving autoencoder-based unsupervised damage detection in uncontrolled structural health monitoring under noisy conditions

Structural health monitoring is widely utilized in outdoor environments,especially under harsh conditions,which can introduce noise into the monitoring system.Therefore,designing an effective denoising strategy to enhance the performance of guided wave damage detection in noisy environments is crucial.This paper introduces a local temporal principal component analysis(PCA)reconstruction approach for denoising guided waves prior to implementing unsupervised damage detection,achieved through novel autoencoder-based reconstruction.Experimental results demonstrate that the proposed denoising method significantly enhances damage detection performance when guided waves are contaminated by noise,with SNR values ranging from 10 to-5 dB.Following the implementation of the proposed denoising approach,the AUC score can elevate from 0.65 to 0.96 when dealing with guided waves corrputed by noise at a level of-5 dB.Additionally,the paper provides guidance on selecting the appropriate number of components used in the denoising PCA reconstruction,aiding in the optimization of the damage detection in noisy conditions.

Time-Lapse Full-Waveform Inversion Using Cross-Correlation-Based Dynamic Time Warping

Offshore carbon capture, utilization, and storage(OCCUS) is regarded as a crucial technology for mitigating greenhouse gas emissions.Quantitative monitoring maps of sealed carbon dioxide are necessary in a comprehensive OCCUS project. A potential high-resolution method for the aforementioned purpose lies in the full-waveform inversion(FWI) of time-lapse seismic data. However, practical applications of FWI are severely restricted by the well-known cycle-skipping problem. A new time-lapse FWI method using cross-correlation-based dynamic time warping(CDTW) is proposed to detect changes in the subsurface property due to carbon dioxide(CO_(2)) injection and address the aforementioned issue. The proposed method, namely CDTW, which combines the advantages of cross-correlation and dynamic time warping, is employed in the automatic estimation of the discrepancy between the seismic signals simulated using the baseline/initial model and those acquired. The proposed FWI method can then back-project the estimated discrepancy to the subsurface space domain, thereby facilitating retrieval of the induced subsurface property change by taking the difference between the inverted baseline and monitor models. Numerical results on pairs of signals prove that CDTW can obtain reliable shifts under amplitude modulation and noise contamination conditions. The performance of CDTW substantially outperforms that of the conventional dynamic time warping method. The proposed time-lapse fullwaveform inversion(FWI) method is applied to the Frio-2 CO_(2) storage model. The baseline and monitor models are inverted from the corresponding time-lapse seismic data. The changes in velocity due to CO_(2) injection are reconstructed by the difference between the baseline and the monitor models.

Non-invasive biomarkers for monitoring the fibrogenic process in liver:A short survey

The clinical course ofchronic liver diseases is significantly dependent on the progression rate and the extent offibrosis, i.e. the non-structured replacement of necrotic parenchyma by extracellular matrix. Fibrogenesis, i.e. the development offibrosis can be regarded as an unlimited wound healing process, which is based on matrix (connective tissue) synthesis in activated hepatic stellate cells, fibroblasts (fibrocytes), hepatocytes and biliary epithelial cells, which are converted to matrix-producing (myo-)fibroblasts by a process defined as epithelial-mesenchymal transition. Blood (noninvasive) biomarkers offibrogenesis and fibrosis can be divided into class and class analytes. Class biomarkers are those single tests, which are based on the pathophysiology offibrosis, whereas class biomarkers aremostly multiparametric algorithms, which have been statistically evaluated with regard to the detection and activity ofongoing fibrosis. Currently available markers fulfil the criteria ofideal clinical-chemical tests only partially, but increased understanding ofthe complex pathogenesis offibrosis offers additional ways for pathophysiologically well based serum (plasma) biomarkers. They include TGF-β-driven marker proteins, bone marrow-derived cells (fibrocytes), and cytokines, which govern proand anti-fibrotic activities. Proteomic and glycomic approaches ofserum are under investigation to set up specific protein or carbohydrate profiles in patients with liver fibrosis. These and other novel parameters will supplement or eventually replaceliver biopsy/histology, high resolution imaging analysis, and elastography for the detection and monitoring of patients at risk ofdeveloping liver fibrosis.

Monitoring and analysis of nonlinear dynamic damage of transport roadway supported by composite hard rock materials in Linglong Gold Mine

The study concentrates mainly on the development of failure process incomposite rock mass. By use of acoustic emission (AE), convergence inspection, pressure monitoring,level measurement techniques and the modem signal analysis technology, as well as scan electronmicroscopy (SEM) experiment, various aspects of nonlinear dynamic damage of composite rock masssurrounding the transport roadway in Linglong gold mine are discussed. According to the monitoringresults, the stability of the rock mass can be synthetically evaluated, and the intrinsic relationbetween the damage and the characteristic parameters of acoustic emission can be determined. Thelocation of the damage of rock mass can also be detected based on the acoustic emission couplemonitoring signals. Finally, the key factors which influence the stability of the transport roadwaysupported by composite hard rock materials are found out.

Dynamic monitoring of menopause hormone therapy and defining the cut-off value of endometrial thickness during uterine bleeding

The aim of this study was to evaluate the effects of low-dose tibolone therapy on ovarian area, uterine volume and endometrial thickness, and define the cut-off value of endometrial thickness for curettage during uterine bleeding. We followed 619 postmenopausal women, aged 40-60 years, for two years. There were 301 subjects in the low-dose tibolone treatment group and 318 subjects in the control group. The ovarian area, uterine volume and endometrial thickness in all participants were measured by transvaginal ultrasound prior to, one and two years post enrollment, respectively. Endometrial specimens were collected from all subjects with abnormal uterine bleeding during the follow-up period. We found that the uterine volume in the treatment group was greater than that in the control group, and the difference was significant （P〈0.05）, but there were no significant differences in ovarian area and endometrial thickness between the two groups （P〉0.05）. When the cut-off value for endometrial thickness was 7.35 ram, the sensitivity and specificity were 100% and 79.07%, respectively, and 85.71% and 93.02% when 7.55 mm was set as the cut-offduring tibolone therapy. The results indicate that low-dose tibolone therapy may postpone uterine atrophy and the cut-off value of endometrial thickness may be appropriately adjusted for curettage.

Multi-parameter numerical simulation of dynamic monitoring of rock deformation in deep mining

The level of deformation development of surrounding rocks is a vital predictor to evaluate impending coal mine disasters and it is important to establish accurate measurements of the deformed status to ensure coal mine safety. Traditional deformation monitoring methods are mostly based on single parameter, in this paper, multiple approaches are integrated: firstly, both electric and elastic models are established,from which electric field distribution and seismic wave recording are calculated and finally, the resistivity profiles and source position information are determined using inversion methods, from which then the deformation and failure of mine floor are evaluated. According to the inversion results of both electric and seismic field signals, multiple-parameter dynamic monitoring of surrounding rock deformation in deep mine can be performed. The methodology is validated using numerical simulation results which shows that the multi-parameter dynamic monitoring methods have better results for surrounding rock deformation in deep mine monitoring than single parameter methods.

A Real-Time System for Monitoring Distant Dynamic Displacement of Structures

Based on digital image processing technique, a real-time system is developed to monitor and detect the dynamic displacement of engineering structures. By processing pictures with a self-programmed software, the real-time coordinate of an object in a certain coordinate system can be obtained, and further dynamic displacement data and curve of the object can also be achieved. That is, automatic gathering and real-time processing of data can be carried out by this system simultaneously. For this system, first, an untouched monitoring technique is adopted, which can monitor or detect objects several to hundreds of meters apart; second, it has flexible installation condition and good monitoring precision of sub-millimeter degree; third, it is fit for dynamic, quasi-dynamic and static monitoring of large engineering structures. Through several tests and applications in large bridges, good reliability and dominance of the system is proved.

DESIGN AND APPLICATION OF DYNAMIC MONITORING AND VISUALIZATION MANAGEMENT INFORMATION SYSTEM OF KARST LAND ROCKY DESERTIFICATION

In order to study the spatial-temporal change and environmental management of regional karst LUCC (land use and land cover change) and its causative environmental effect-rocky desertification by integrating qualitative analysis and quantitative analysis, and relying on RS, GIS and GPS (3S) techniques, karst land rocky derification dynamic monitoring and visualization management information system (KLRD.DMVM.IS) is framed, which includes design aim and structure model, function design, database design and model system design. The model system design gives priority to dynamic monitoring, drive force diagnosis, comprehensive evaluation and decision support of karst rocky desertification. From the viewpoint of model type, mathematic expression and its meaning, the dynamic monitoring models are concretely devised to reflect the spatial and temporal changing features and the trend of karst LUCC and rocky desertification. Taking Du'an Yao Autonomic County of Guangxi as an example, the KLRD.DMVM.IS is systematically analyzed in the application of the process and trend of karst LUCC and rocky desertification in Du'an County, and it provides the technical support for the study on karst land rocky desertification.

Monitoring of Land-Cover Dynamic Change in Lancangjiang River Cascaded Hydropower Area

The analysis of the 3 stages＇ （1988,1996,2000） variation of land-cover is performed according to Thematic Mapper （TM） and Enhancement Thematic Mapper（ETM） satellite image by combining ground GIS database with GPS field collected data in the area of Xiaowan-Dachaoshan Reservoirs of Lancangjiang River cascaded Hydropower Area. Consequently, the land-cover is divided into five subclasses, namely water, paddy field and wetland, bare dryland and sparse shrub, secondary forest and density forest. The result showed that the areas of bare land, upland and secondary forest decreased in 1988-1996, whereas from 1996 to 2000, water body and density forest keep invariability while the areas of paddy field and wetland, bare dryland and sparse scrub increasing and the area of secondary forest decrease; Features of reciprocal transformation between density forest and other type of land-cover had two points, i.e. secondary forest, bare dryland and sparse shrub converted to density forest; and density forest converted to secondary forest and paddy field and wetland. It reflects the dynamic variation of density forest; the area which slope less than 8° and greater than 15° shows bigger variation, however, less change in 8°-15°.

Studies on monitoring hemodynamics and oxygen dynamics of adult respiratory distress syndrome secondary to high altitude pulmonary edema

To study monitoring hemodynamics and oxygen dynamics of adult respiratory distress syndrome (ARDS) secondary to high altitude pulmonary edema (HAPE),we performed clinic and laboratory studies in 8 patients who preliminarily developed high altitude cerebral edema (HACE) and then ARDS occurred at an altitude of 4 500 m. After an initial emergency treatment on high mountains,all the patients were rapidly transported to a hospital at a lower altitude of 2 808 m. The right cardiac catheterizations were carried out within 5 h after hospitalized. The monitoring hemodynamics and oxygen dynamics were studied via a thermodilution Swan-Gaze catheter. The results showed that before treatments at the beginning of monitoring,there presented a significant pulmonary artery hypertension with a decreased cardiac function,and a lower oxygen metabolism in all the 8 patients. However,after some effective treatments,including mechanical ventilation and using dexamethasone,furosemide,etc,four days later the result of a repeated monitoring showed that their pulmonary artery pressure had been decreased with an improved cardiac function with all the oxygen metabolic indexes increased significantly. Our studies suggested that performing monitoring hemodynamics in patients with ARDS secondary to HAPE will define the clinical therapeutic measures which will benefit the outcome.

Remote sensing-based dynamic monitoring and environmental change of wetlands in southern Mongolian Plateau in 2000‒2018

The environmental change in the wetlands in the southern Mongolian Plateau has important impacts on the environment of North China and even the entire Northeast Asia,from which the global climate change can be understood on a large scale,especially the climate change in the Mongolian Plateau.This study extracted the information on the wetlands from three stages of remote sensing images(also referred to as RS images)of the study area,including Enhanced Thematic Mapper Plus(ETM+)images of 2000,TM images of 2010,and Landsat 8 Operational Land Imager(OLI)images of 2018.As indicated by the extraction results,the area of wetlands decreased from 796.90 km^(2) of 2000 to 666.24 km^(2) of 2018 at a rate of 7.26 km^(2)/a.The reduced area is 130.66 km^(2),which is about 16.4%reduction.And the patch number of wetlands decreased from 731 of 2000 to 316 of 2018 in the study area,approximately 56.8%reduction(415 patches),and the decrease in the area of the wetlands mainly occurred in the northwest endorheic region.In terms of wetland types,the change of the wetlands was dominated by the decrease of lacustrine wetlands,of which the area and patch number decreased by 106.2 km^(2) and 242,respectively.Furthermore,the area of the lacustrine wetlands decreased at the highest rate of 8.70 km^(2)/a in 2010‒2018.From the perspective of spatial distribution,the wetlands in the western part shrunk more notably than those in the eastern part as a whole in the study area.According to local meteorological data,the precipitation gently decreased and the temperature increased(about 1.7℃)from 1975-2018.Overall,the decrease in the area of the wetlands and the temperature rises in the study area were mainly driven by the Mongolian monsoon climate,reduction in precipitation,and human activities.

Proactive Spectrum Monitoring for Suspicious Wireless Powered Communications in Dynamic Spectrum Sharing Networks

This paper studies the proactive spec-trum monitoring with one half-duplex spectrum moni-tor(SM)to cope with the potential suspicious wireless powered communications(SWPC)in dynamic spec-trum sharing networks.The jamming-assisted spec-trum monitoring scheme via spectrum monitoring data(SMD)transmission is proposed to maximize the sum ergodic monitoring rate at SM.In SWPC,the suspi-cious communications of each data block occupy mul-tiple independent blocks,with a block dedicated to the wireless energy transfer by the energy-constrained suspicious nodes with locations in a same cluster(symmetric scene)or randomly distributed(asymmet-ric scene)and the remaining blocks used for the in-formation transmission from suspicious transmitters(STs)to suspicious destination(SD).For the sym-metric scene,with a given number of blocks for SMD transmission,namely the jamming operation,we first reveal that SM should transmit SMD signal(jam the SD)with tolerable maximum power in the given blocks.The perceived suspicious signal power at SM could be maximized,and thus so does the correspond-ing sum ergodic monitoring rate.Then,we further reveal one fundamental trade-off in deciding the op-timal number of given blocks for SMD transmission.For the asymmetric scene,a low-complexity greedy block selection scheme is proposed to guarantee the optimal performance.Simulation results show that the jamming-assisted spectrum monitoring schemes via SMD transmission achieve much better perfor-mance than conventional passive spectrum monitor-ing,since the proposed schemes can obtain more accu-rate and effective spectrum characteristic parameters,which provide basic support for fine-grained spectrum management and a solution for spectrum security in dynamic spectrum sharing network.