A HybridManufacturing ProcessMonitoringMethod Using Stacked Gated Recurrent Unit and Random Forest

This study proposed a new real-time manufacturing process monitoring method to monitor and detect process shifts in manufacturing operations.Since real-time production process monitoring is critical in today’s smart manufacturing.The more robust the monitoring model,the more reliable a process is to be under control.In the past,many researchers have developed real-time monitoring methods to detect process shifts early.However,thesemethods have limitations in detecting process shifts as quickly as possible and handling various data volumes and varieties.In this paper,a robust monitoring model combining Gated Recurrent Unit(GRU)and Random Forest(RF)with Real-Time Contrast(RTC)called GRU-RF-RTC was proposed to detect process shifts rapidly.The effectiveness of the proposed GRU-RF-RTC model is first evaluated using multivariate normal and nonnormal distribution datasets.Then,to prove the applicability of the proposed model in a realmanufacturing setting,the model was evaluated using real-world normal and non-normal problems.The results demonstrate that the proposed GRU-RF-RTC outperforms other methods in detecting process shifts quickly with the lowest average out-of-control run length(ARL1)in all synthesis and real-world problems under normal and non-normal cases.The experiment results on real-world problems highlight the significance of the proposed GRU-RF-RTC model in modern manufacturing process monitoring applications.The result reveals that the proposed method improves the shift detection capability by 42.14%in normal and 43.64%in gamma distribution problems.

Pros and cons of continuous glucose monitoring in the intensive care unit

Diabetes mellitus affects people worldwide,and management of its acute complications or treatment-related adverse events is particularly important in critically ill patients.Previous reports have confirmed that hyperglycemia can increase the risk of mortality in patients cared in the intensive care unit(ICU).In addition,severe and multiple hypoglycemia increases the risk of mortality when using insulin or intensive antidiabetic therapy.The innovation of continuous glucose monitoring(CGM)may help to alert medical caregivers with regard to the development of hyperglycemia and hypoglycemia,which may decrease the potential complications in patients in the ICU.The major limitation of CGM is the measurement of interstitial glucose levels rather than real-time blood glucose levels;thus,there will be a delay in the treatment of hyperglycemia and hypoglycemia in patients.Recently,the European Union approved a state-of-art artificial intelligence directed loop system coordinated by CGM and a continuous insulin pump for diabetes control,which may provide a practical way to prevent acute adverse glycemic events related to antidiabetic therapy in critically ill patients.In this mini-review paper,we describe the application of CGM to patients in the ICU and summarize the pros and cons of CGM.

基于Unity3D的油田抽油机三维可视化监控系统设计

针对抽油机监测形式单一、三维可视化程度低和联动性差的缺陷,引入信息―物理实时映射思想,开发了油田抽油机三维可视化监控系统。设计了抽油机数字空间,搭建虚实交互层设计架构;搭建三维可视化系统数据组成及关系框架;结合逆运动学,构建数学模型,基于五维模型和Unity 3D平台设计抽油机三维可视化系统总体架构;以游梁式抽油机为对象进行实验验证,实现了实时动态监测、虚实混合控制、运动轨迹追踪和在线预警等服务功能。为三维可视化监控在石油机械领域的落地应用和数字孪生系统的开发提供借鉴。

Assessment of Monitor Units and Gamma Pass Rate for 6 MV and Flattening Filter Free (FFF) Beams in Volumetric Modulated Arc Therapy (VMAT)

Background: In linear accelerators, the treatment field’s uniform intensity is achieved by including a flattening filter in the beam. However, to produce more conformal dose distributions, contemporary radiotherapy practice now frequently uses fluence and aperture modifying techniques, such as volumetric modulated arc therapy. In these circumstances, the flattening filter in the beam manufacturing process is no longer required. It is therefore necessary to compare the monitor units of 6 MV and flattening filter free plans and how it influences the gamma pass rates to determine which is best for treating cervical cancer with pelvic lymph node metastasis. Methods: VMAT plans for fifteen patients with cervical cancer with pathological pelvic lymph node metastasis were included in this study. Each patient had two VMAT plans using conventional 6 MV beam with flattening filter and one with flattening filter free beam (FFF). The VMAT plans were made using two arcs, and then recalculated to give the planned dose distribution to the detectors in a Delta4 phantom. The VMAT plans were irradiated on the Delta4 phantom using an Elekta linear accelerator (6 MV). Results: The mean monitor unit for the 6 MV plans was 506.3 MU and a standard deviation of 48.6 while that of the FFF plans had a mean MU of 701.5 with a standard deviation of 87.6. The total monitor units (MUs) for the FFF plans were significantly greater than the 6 MV plans (p = 6.1 × 10-5). Conclusion: Flattening filter free (FFF) plans require more numbers of monitor units in comparison to conventional 6 MV filtered beams for external radiation of cervical cancer with pelvic lymph nodes involvement.

Adaptive Signal Enhancement Unit for EEG Analysis in Remote Patient Care Monitoring Systems

In this paper we propose an efcient process of physiological artifact elimination methodology from brain waves(BW),which are also commonly known as electroencephalogram(EEG)signal.In a clinical environment during the acquisition of BW several artifacts contaminates the actual BW component.This leads to inaccurate and ambiguous diagnosis.As the statistical nature of the EEG signal is more non-stationery,adaptive ltering is the more promising method for the process of artifact elimination.In clinical conditions,the conventional adaptive techniques require many numbers of computational operations and leads to data samples overlapping and instability of the algorithm used.This causes delay in diagnosis and decision making.To overcome this problem in our work we propose to set a threshold value to diminish the problem of round off error.The resultant adaptive algorithm based on this strategy is Non-linear Least mean square(NL2MS)algorithm.Again,to improve this algorithm in terms of ltering capability we perform data normalization,using this algorithm several hybrid versions are developed to improve ltering and reduce computational operations.Using the method,a new signal enhancement unit(SEU)is realized and performance of various hybrid versions of algorithms examined using real EEG signals recorded from the subject.The ability of the proposed schemes is measured in terms of convergence,enhancement and multiplications required.Among various SEUs,the MCN2L 2MS algorithm achieves 14.6734,12.8732,10.9257,15.7790 dB during the artifact removal of RA,EMG,CSA and EBA components with only two multiplications.Hence,this algorithm seems to be better candidate for artifact elimination.

Research on Network-based Integrated Condition Monitoring Unit for Rotating Machinery

In this paper, a network-based monitoring unit for condition monitoring andfault diagnosis of rotating machinery is designed and implemented. With the technology of DSP(Digital signal processing) , TCP/IP, and simultaneous acquisition, a mechanism of multi-process andinter-process communication, the integrating problem of signal acquisition, the data dynamicmanagement and network-based configuration in the embedded condition monitoring system is solved. Itoffers the input function of monitoring information for network-based condition monitoring and afault diagnosis system.

ZIZ-2 Vibration monitoring and diagnosing system for turbine generator units

ZJZ-2 system has the following functions: (1) Real-time on-line sampling and FFT analysis (32 channel); (2) Data aquisition, analysis and storage during start-up and shut-down; (3) Alarming, emergency recognition and fault retrieval; (4) Data aquisition, analysis and storage during daily operation; (5) Recall of historic data; (6) Output of routine reports and tables; (7) Analysis of vibration behaviour: Bode plot, polar plot, spectrum, cascade, waveform, shaft orbit, trend, etc;

Effects of Beam Startup Characteristics on Dose Delivery Accuracy at Low Monitor Units in Step-and-Shoot Intensity Modulated Radiation Therapy

Intensity modulated radiation therapy (IMRT) is a highly accurate technique that is usually implemented in either dynamic or step-and-shoot fashion with many segments each having low monitor units (MUs). The present study evaluated the effects of beam startup characteristics on the dose delivery accuracy for each segment at low MUs for step-and-shoot IMRT with an Elekta Precise accelerator at the highest dose rates. We used a two-dimensional semi-conductor detector for the dose measurements. The field size of each segment was assumed to be 20 ×20 cm2 and each segment was set to deliver 1 - 10 MUs. Our results show a variation in dose delivery accuracy between segments for the same IMRT beam, which can be attributed to the beam startup characteristics. This variability is attributed to the changes in the transient changes in the temperatures of the electron gun filament and the magnetron. That is, the transient increase in the temperature of the filament leads to increasing doses with time and that of the magnetron leads to decreasing doses with time during the first few MUs.

Decentralized and overall condition monitoring system for large-scale mobile and complex equipment

It is an urgent project to realize online and overall condition monitoring and timely fault diagnosis for large-scale mobile and complex equipment. Moreover, most of the existing large-scale complex equipment has quite insufficient accessibility of examination, although it still has quite a long service life. The decentralized and overall condition monitoring, as a new concept, is proposed from the point of view of the whole system. A set of complex equipment is divided into several parts in terms of concrete equipment. Every part is processed via one detecting unit, and the main detecting unit is connected with other units. The management work and communications with the remote monitoring center have been taken on by it. Consequently, the difficulty of realizing a condition monitoring system and the complexity of processing information is reduced greatly. Furthermore, excellent maintainability of the condition monitoring system is obtained because of the modularization design. Through an application example, the design and realization of the decentralized and overall condition monitoring system is introduced specifically. Some advanced technologies, such as, micro control unit （MCU）, advanced RISC machines （ARM）, and control area network （CAN）, have been adopted in the system. The system＇s applicability for the existing large-scale mobile and complex equipment is tested.

Beam Characteristics at Low Dose Monitor Unit Settings for Vero4DRT

The stability of delivery of low monitor unit (MU) setting is important especially for step-and-shoot intensity-modulated radiotherapy (IMRT), because the nature of the technique is inherent to repeat beam on/off according to the number of the segments. This study evaluates the dose linearity and profile flatness/symmetry under low MU settings for Vero4DRT, a new linear-accelerator based irradiation system that currently implements step-and-shoot IMRT. To evaluate the dose linearity and flatness/symmetry, the point doses and beam profiles were measured as functions of MU and dose rates. The accuracy of dose delivery depended on the dose rate. Under all dose rates, the dose was linear within 1% above 5 MU and within 2% above 3 MU. The beam symmetry was degraded in-line compared with crossline, although both profiles were symmetric within 2% at all dose settings. The profile flatness was also within 2% above 5 MU at any dose rate and showed no significant variation among the low MU settings. To ensure stable beam delivery without increasing the treatment time of Vero4DRT, we recommend a delivery of 5 MU per segment at a dose rate of 500 MU/min.

Advancement in Wide Area Monitoring Protection and Control Using PMU’s Model in MATLAB/SIMULINK

A big step forward to improve power system monitoring and performance, continued load growth without a corresponding increase in transmission resources has resulted in reduced operational margins for many power systems worldwide and has led to operation of power systems closer to their stability limits and to power exchange in new patterns. These issues, as well as the on-going worldwide trend towards deregulation of the entire industry on the one hand and the increased need for accurate and better network monitoring on the other hand, force power utilities exposed to this pressure to demand new solutions for wide area monitoring, protection and control. Wide-area monitoring, protection, and control require communicating the specific-node information to a remote station but all information should be time synchronized so that to neutralize the time difference between information. It gives a complete simultaneous snap shot of the power system. The conventional system is not able to satisfy the time-synchronized requirement of power system. Phasor Measurement Unit (PMU) is enabler of time-synchronized measurement, it communicate the synchronized local information to remote station.

What,why and how to monitor blood glucose in critically ill patients

Critically ill patients are prone to high glycemic variations irrespective of their diabetes status.This mandates frequent blood glucose(BG)monitoring and regulation of insulin therapy.Even though the most commonly employed capillary BG monitoring is convenient and rapid,it is inaccurate and prone to high bias,overestimating BG levels in critically ill patients.The targets for BG levels have also varied in the past few years ranging from tight glucose control to a more liberal approach.Each of these has its own fallacies,while tight control increases risk of hypoglycemia,liberal BG targets make the patients prone to hyperglycemia.Moreover,the recent evidence suggests that BG indices,such as glycemic variability and time in target range,may also affect patient outcomes.In this review,we highlight the nuances associated with BG monitoring,including the various indices required to be monitored,BG targets and recent advances in BG monitoring in critically ill patients.

Online Fault Detection Configuration on Equipment Side of a Variable-Air-Volume Air Handling Unit

With the development of the technology of the Internet of Things,more and more operational data can be collected from air conditioning systems.Unfortunately,the most of existing air conditioning controllers mainly provide controlling functions more than storing,processing or computing the measured data.This study develops an online fault detection configuration on the equipment side of air conditioning systems to realize these functions.Modbus communication is served to collect real-time operational data.The calculating programs are embedded to identify whether the measured signals exceed their limits or not,and to detect if sensor reading is frozen and other faults in relation to the operational performance are generated or not.The online fault detection configuration is tested on an actual variable-air-volume(VAV)air handling unit(AHU).The results show that the time ratio of fault detection exceeds 95.00%,which means that the configuration exhibits an acceptable fault detection effect.

Nonlinear Statistical Process Monitoring Based on Control Charts with Memory Effect and Kernel Independent Component Analysis

A novel nonlinear combination process monitoring method was proposed based on techniques with memory effect (multivariate exponentially weighted moving average (MEWMA)) and kernel independent component analysis (KICA). The method was developed for dealing with nonlinear issues and detecting small or moderate drifts in one or more process variables with autocorrelation. MEWMA charts use additional information from the past history of the process for keeping the memory effect of the process behavior trend. KICA is a recently developed statistical technique for revealing hidden, nonlinear statistically independent factors that underlie sets of measurements and it is a two-phase algorithm: whitened kernel principal component analysis (KPCA) plus independent component analysis (ICA). The application to the fluid catalytic cracking unit (FCCU) simulated process indicates that the proposed combined method based on MEWMA and KICA can effectively capture the nonlinear relationship and detect small drifts in process variables. Its performance significantly outperforms monitoring method based on ICA, MEWMA-ICA and KICA, especially for long-term performance deterioration.

基于声纹监测技术的大型泵站机组振动特性研究

声音和振动是反映旋转机械设备运行状态信息的直接载体,根据声纹监测的原理,通过对数据进行采集、预处理、提取特征值,采用卷积神经网络深度学习识别模型,建立大型泵站机组运行状态声纹样本库和模型库,构建泵站机组振动状态的声纹监测系统,实现大型泵站机组运行状态的实时监测。

基于数字孪生的工业机器人建模及监测方法

针对工业机器人数据不透明、监测存在死角等问题,通过对实体工业机器人分析和研究,构建数字孪生机器人监测系统。首先从几何、物理、逻辑3个维度完成虚拟机器人的建模;其次基于开放平台通信联合架构(open platform communications united architecture,OPC UA),实现机器人的数据采集和通信,设计用户显示界面,达到数据实时可视化的效果;最后,通过机器人仿真实验得出机器人末端执行器X、Y、Z坐标的相对位置误差分别为0.48%、0.32%、0.27%,通过数字孪生机器人监测同步实验验证机器人关节角度误差最大值为0.31°。实验结果表明:该方法能够实现数字孪生工业机器人的运动数据监测,减少工业机器人在生产过程中发生意外和故障的风险,为智能工业机器人的发展提供思路和方向。

星载激光雷达视轴监测系统设计

提出了一种针对星载激光雷达在轨高精度光轴监测与标定需求的多光轴监测方法,该方法基于主动激光光源。通过使用785 nm的激光,分束后分别照射到星敏感器的基准棱镜和接收望远镜的取光棱镜,反射信号被聚焦至监视相机的焦平面,实现了对接收光轴及星敏光轴的精确监测。此外,监视相机还同步采集发射激光的部分能量,用于测量监测发射光轴。文中详细描述了光学系统的设计流程及关键组件的优化方案,并通过地面真空环境试验及在轨监测数据进行了验证。设计结果表明,各监视通道的成像质量达到了衍射极限,收发光轴的设计精度分别为0.09μrad和2.28μrad,关键组件取光棱镜的温控精度达到了±0.2℃。地面的真空热光试验结果进一步验证了该方案的高精度光轴监视能力,收发光轴的监测精度均优于3μrad。最后通过分析激光雷达入轨后的测量数据,确认了视轴监测系统的工作稳定性,成功实现了在轨的高精度光轴监视。该研究成果为星载激光雷达提供了一种有效的在轨高精度光轴监测与标定解决方案。

基于门控循环单元网络的钻井井漏智能监测方法

井漏是钻井过程中常见的钻井风险,若对该风险发现、处理不及时,极易导致井塌事故,轻则延长施工周期,重则危害现场人员人身安全。为了提高油气井钻井过程中井漏风险识别的准确性,降低风险识别对人为经验的依赖,结合钻井参数的非线性以及长时依赖特征,提出了一种基于门控循环单元(Gated Recurrent Unit,GRU)网络的井漏风险智能识别方法。该模型以池体积、出口流量和立管压力作为监测参数构建GRU网络,能够提取监测参数的时间序列特征,以实现对井漏风险的准确识别。利用现场实测钻井数据对模型进行了实验测试,结果表明,该方法对井漏风险的识别准确率达到了90.1%,优于长短期记忆网络的识别结果。