Research on Transmission Line Tower Tilting and Foundation State Monitoring Technology Based onMulti-Sensor Cooperative Detection and Correction

The transmission line tower will be affected by bad weather and artificial subsidence caused by the foundation and other factors in the power transmission.The tower’s tilt and severe deformation will cause the building to collapse.Many small changes caused the tower’s collapse,but the early staff often could not intuitively notice the changes in the tower’s state.In the current tower online monitoring system,terminal equipment often needs to replace batteries frequently due to premature exhaustion of power.According to the need for real-time measurement of power line tower,this research designed a real-time monitoring device monitoring the transmission tower attitude tilting and foundation state based on the inertial sensor,the acceleration of 3 axis inertial sensor and angular velocity raw data to pole average filtering pre-processing,and then through the complementary filtering algorithm for comprehensive calculation of tilt angle,the system meets the demand for inclined online monitoring of power line poles and towers regarding measurement accuracy,with low cost and power consumption.The optimization multi-sensor cooperative detection and correction measured tilt angle result relative accuracy can reach 1.03%,which has specific promotion and application value since the system has the advantages of unattended and efficient calculation.

Research on information technology of state monitoring and fault prediction for mechatronics system

The safety and reliability of mechatronics systems,particularly the high-end,large and key mechatronics equipment in service,can strongly influence on production efficiency,personnel safety,resources and environment.Based on the demands of development of modern industries and technologies such as international industry 4.0,Made-in-China 2025 and Internet + and so on,this paper started from revealing the regularity of evolution of running state of equipment and the methods of signal processing of low signal noise ratio,proposed the key information technology of state monitoring and earlyfault-warning for equipment,put forward the typical technical line and major technical content,introduced the application of the technology to realize modern predictive maintenance of equipment and introduced the development of relevant safety monitoring instruments.The technology will play an important role in ensuring the safety of equipment in service,preventing accidents and realizing scientific maintenance.

Real-time State Monitoring During Switching Mode Transitions in High Power Three-level Inverters

大功率多电平逆变器近年来在实际工业生产中得到越来越广泛的应用。多电平逆变器由于结构复杂,采用元器件较多,因此在设计和实验中,实现各个工作状态下运行参数的同步监测和分析较为困难。本文针对大功率三电平逆变器,实现开关动态特性的在线测试,在此基础上,进一步研究三电平逆变器在开关状态变化时理论与实际负载运行工况下电路拓扑的转换变化规律。通过全电路电气参数和元器件状态的实时监测,发现在三电平逆变器非正常运行状态下开关转换时额外电应力,同时,深入研究在实际工况运行条件非正常状态下该额外电应力出现的机理和原因,为三电平逆变器的故障诊断提供了参考,对于设计高可靠性的多电平逆变器系统有一定的理论和现实意义。

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.

Contactless Raman Spectroscopy-Based Monitoring of Physical States of Silyl-Modified Polymers during Cross-Linking

Cross-linking of silyl-modified polymers occurs at the alkoxysilane groups attached to the ends of polymer chains by hydrolysis and polycondensation mechanisms in the presence of moisture. During these reactions, three different physical states can be identified (viscous, skin effect and cross-linked state). Knowledge of the evolution of these states at each reaction time is essential to determine the open time for the adhe-sive industry and is generally obtained by a manual method. Automation of this moni-toring could avoid operator error and could be used for very long cross linking reac-tions or to screen a large number of catalysts. Thus, a contactless micro process tech-nology was developed to correlate these physical states with an optical technology, Raman spectroscopy, by monitoring the decrease in intensity of the Si-OCH3 groups during chemical reactions. This online characterization method can also be used to compare the efficiencies of several catalysts for the cross-linking of silyl-modified polymers, using a minimum amount of chemical materials.

Comprehensive early warning of rock burst utilizing microseismic multi-parameter indices

Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powerful tool for the early warning of rock burst. In this study, an MS multi-parameter index system was established and the critical values of each index were estimated based on the normalized multi-information warning model of coal-rock dynamic failure. This index system includes bursting strain energy(BSE) index, time-space-magnitude independent information(TSMII) indices and timespace-magnitude compound information(TSMCI) indices. On the basis of this multi-parameter index system, a comprehensive analysis was conducted via introducing the R-value scoring method to calculate the weights of each index. To calibrate the multi-parameter index system and the associated comprehensive analysis, the weights of each index were first confirmed using historical MS data occurred in LW402102 of Hujiahe Coal Mine(China) over a period of four months. This calibrated comprehensive analysis of MS multi-parameter index system was then applied to pre-warn the occurrence of a subsequent rock burst incident in LW 402103. The results demonstrate that this multi-parameter index system combined with the comprehensive analysis are capable of quantitatively pre-warning rock burst risk.

Multimodal process monitoring based on transition-constrained Gaussian mixture model

Reliable process monitoring is important for ensuring process safety and product quality.A production process is generally characterized bymultiple operation modes,and monitoring thesemultimodal processes is challenging.Most multimodal monitoring methods rely on the assumption that the modes are independent of each other,which may not be appropriate for practical application.This study proposes a transition-constrained Gaussian mixture model method for efficient multimodal process monitoring.This technique can reduce falsely and frequently occurring mode transitions by considering the time series information in the mode identification of historical and online data.This process enables the identified modes to reflect the stability of actual working conditions,improve mode identification accuracy,and enhance monitoring reliability in cases of mode overlap.Case studies on a numerical simulation example and simulation of the penicillin fermentation process are provided to verify the effectiveness of the proposed approach inmultimodal process monitoring with mode overlap.

Method of Phase Diagrams for the Analysis of Seism-Acoustical Spatial-Time Monitoring Data in Oil Wells

Experimental and theoretical studies of the mechanisms of vibration stimulation of oil recovery in watered fields lead to the conclusion that resonance oscillations develop in fractured-block formations. These oscillations, caused by weak but long-lasting and frequency-stable influences, create the conditions for ultrasonic wave’s generation in the layers, which are capable of destroying thickened oil membranes in reservoir cracks. For fractured-porous reservoirs in the process of exploitation by the method of water high-pressure oil displacement, the possibility of intensifying ultrasonic vibrations can have an important technological significance. Even a very weak ultrasound can destroy, over a long period of time, the viscous oil membranes formed in the cracks between the blocks, which can be the reason for lowering the permeability of the layers and increasing the oil recovery. To describe these effects, it is necessary to consider the wave process in a hierarchically blocky environment and theoretically simulate the mechanism of the appearance of self-oscillations under the action of relaxation shear stresses. For the analysis of seism acoustic response in time on fixed intervals along the borehole an algorithm of phase diagrams of the state of many-phase medium is suggested.

The Impact of the FreeStyle LibreTM Flash Glucose Monitoring System on Glycemic Control in Patients with Diabetes;Observational Multicenter 15-Months Study

Objectives: The study was to determine the impact of using the FreeStyle LibreTM flash glucose monitoring system on glycemic control and the rate of events due to diabetes in people with diabetes from different types and age groups. Methods: a retrospective cohort chart review study was carried out at three centers in the Taif region in the Kingdom of Saudi Arabia: The study was approved by an accredited centralized institutional review board. Paper or electronic medical records were included for individuals of any age with diabetes (type 1, type 2, gestational diabetes) managed with diet, insulin therapy, or/and oral antihyperglycemic medication and/or non-insulin injection therapy. The primary outcome measure was the laboratory HbA1c level as well as reduction. Secondary outcome measures were frequency of severe hypoglycemia, admission to hospital or ER visit related to diabetes complications, and severe hyperglycemia (DKA or HHS). Results: Data was analyzed from 1695 patients. The average HbA1c before using the flash glucose monitoring system was 9.60% ± 1.44% and 3 months HbA1c after using the FreeStyle LibreTM flash glucose monitoring system was 8.70% + 1.45% for a difference of -0.90% ([95% CI -0.92: -0.88];p 65 years, (p-values Conclusion: The benefits of using the FreeStyle LibreTM flash glucose monitoring system are self-evident in reducing HbA1c and events due to hyperglycemia or hypoglycemia.

Outlier Detection and Forecasting for Bridge Health Monitoring Based on Time Series Intervention Analysis

The method of time series analysis,applied by establishing appropriate mathematical models for bridge health monitoring data and making forecasts of structural future behavior,stands out as a novel and viable research direction for bridge state assessment.However,outliers inevitably exist in the monitoring data due to various interventions,which reduce the precision of model fitting and affect the forecasting results.Therefore,the identification of outliers is crucial for the accurate interpretation of the monitoring data.In this study,a time series model combined with outlier information for bridge health monitoring is established using intervention analysis theory,and the forecasting of the structural responses is carried out.There are three techniques that we focus on:(1)the modeling of seasonal autoregressive integrated moving average(SARIMA)model;(2)the methodology for outlier identification and amendment under the circumstances that the occurrence time and type of outliers are known and unknown;(3)forecasting of the model with outlier effects.The method was tested with a case study using monitoring data on a real bridge.The establishment of the original SARIMA model without considering outliers is first discussed,including the stationarity,order determination,parameter estimation and diagnostic checking of the model.Then the time-by-time iterative procedure for outlier detection,which is implemented by appropriate test statistics of the residuals,is performed.The SARIMA-outlier model is subsequently built.Finally,a comparative analysis of the forecasting performance between the original model and SARIMA-outlier model is carried out.The results demonstrate that proper time series models are effective in mining the characteristic law of bridge monitoring data.When the influence of outliers is taken into account,the fitted precision of the model is significantly improved and the accuracy and the reliability of the forecast are strengthened.

Dynamic Control System of Automatic Monitoring Equipment for Waste Gas Pollution Source

In order to improve the quality of automatic monitoring data of pollution sources and apply the automatic monitoring data to verify the environmental tax,Shandong Province took the lead in adopting the Internet of Things technology and drawing on the successful experience of air automatic monitoring stations and surface water automatic monitoring stations in management,and developed a dynamic management and control system for automatic monitoring equipment of pollution sources to improve and strengthen the quality audit of automatic monitoring data,further improve the quality of automatic monitoring data and better provide a basis for environmental management and decision making.The system realizes the simultaneous monitoring of monitoring data,running state and parameters of the automatic monitoring equipment,eliminates the phenomenon of falsification by modifying equipment parameters,and judges the validity of the collected data by acquiring the working state of the equipment remotely and randomly.After the actual operation test of the Department of Ecological Environment of Shandong Province,the system is proved to have the characteristics of practicality,real time and high efficiency,and be able to make up for low frequency and narrow coverage of manual inspection,with good application prospect in the field of environment and pollution source monitoring.

Assessment of the Trophic Status by Monitoring of Reservoir’s Water Quality

Continuous long-term monitoring of aquatic systems is important for understanding their complete evolution in order to monitor changes in the trophic status and water quality. The continuous monitoring during a period of 20 years, by sampling once a month at two locations, the water quality of reservoir “Grliste”, which is used for the water supplying town Zajecar (Eastern Serbia), is observed and developmental stages in the life of the reservoir were determinated. It should be noted that the obtained results were used also in the purpose of finding a cause of cyanobacteria bloom, as a consequence of algal production. Limiting factors of algal production usually were nitrogen and phosphorus, however, in this study, obtained results of subtraction between trophic state index, calculated through total chlorophyll a (TSIChl-a) and trophic state index, calculated through total phosphorus (TSITP), indicated that limiting factor of algal production was light. On the basis of the concentrations of dissolved oxygen (DO), total phosphorus (TP) and chlorophyll a (Chl-a) in the surface and in the bottom, it was concluded that the reservoir passed through four development phases during the examined period. Results of long-term monitoring showed that in the first years after the formation of the reservoir, the highest trophicity was detected (hypereutrophic status), but later the reservoir mostly maintained eutrophic status.

Fuzzy reasoning model using fuzzy Petri Nets for the monitoring of robotic assembly

This paper presented a fuzzy Petri net model to deal with the monitoring of robotic assembly. Based on the fuzzy Petri net model, an efficient composite reasoning mode was proposed to perform fuzzy reasoning automatically. It can determine whether there exists an antecedent-consequence relationship between two contact states. Furthermore, various types of sensor signals can be converted to the same form of real values between zero and one, and the contradiction among large number, high degree of truth and importance of input conditions can be resolved very well by introducing the weight factors and priorities for sensor signals. Finally, a peg-in-the-hole example was given to illustrate the reasonability and feasibility of the proposed model.

基于数实结合的测控装备健康监测系统设计与实现

针对测控业务领域装备种类多、型号杂、布站分散、技术保障人力不足、远程技术协助手段落后等实际问题,结合测控装备自身特点和运维保障规律,提出了采用数字技术构建功能级数字测控装备,并利用数字装备和实体装备间物联网络使数实装备状态数据一致,实现基于数实结合的测控装备健康监测,实现装备状态数实同步,并可利用数实同步有效的评估装备状态、进行故障诊断和健康趋势预估,实现了运维保障数字化。

基于神经网络的液压机状态监测系统研究

神经网络是一种类似于人类神经系统的人工智能模型,利用神经网络可以对传统的监测数据进行组合和筛选,以提高故障检测的准确度。为提升液压机状态监测系统的故障评估性能,利用基于神经网络的机器学习方法的优势,提出一种设备状态监测解决新方案。对大量数据进行神经网络模型训练及特征提取,从而实现对液压机监测系统故障的准确识别。

刮板输送机技术发展历程(四)——智能化成套装备

采煤工作面机器人群包括智能刮板输送机,它不仅要自适高效输送煤流而且要引导智能采煤机沿着工作面截割煤炭、牵引智能液压支架安全支护岩层顶板,因此刮板输送机智能性直接影响采煤机组智能性。认为,断链监测与保护技术、链张力实时感控技术、煤流量在线监测技术和机身自动调直技术是智能刮板输送机的关键感控要素,目前这些技术已达到成熟应用,为刮板输送机无人化运行提供了重要保障。自2010年起,我国刮板输送机智能化技术创新加速,研发成功超大功率、超长运距智能刮板输送机,以此构建了超级智采工作面。指出,未来刮板输送机永磁电机智能驱动、智能力感刮板链、全耐磨整体成型中部槽、数字孪生控制系统将成为新一代高级智能刮板输送机的发展方向,进而推进煤矿智采工作面进入高级智能化层次。

组合式有源传感器状态监测与容错控制研究

针对传统传感器状态监测方法准确性不高的问题,提出一种组合式有源传感器状态监测与容错控制方法。该方法分为2个部分:前一部分进行传感器状态监测,包括状态信号去噪处理、小波包能量熵特征提取以及利用参数优化后的概率神经网络识别传感器健康状态3个步骤;后一部分设计容错控制模型,以状态监测结果为参考,切换控制策略,实现容错控制。实验结果表明:与其他3种传统方法相比,在该方法控制下容错控制误差在±1 r/min,波动较小,控制效果更优。