scholarly journals Underground Microseismic Event Monitoring and Localization within Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2830
Author(s):  
Sili Wang ◽  
Mark P. Panning ◽  
Steven D. Vance ◽  
Wenzhan Song
Keyword(s):  
Sensor Networks ◽  
Real Time ◽  
Information Needs ◽  
Localization Algorithm ◽  
Distributed Sensors ◽  
Distributed Sensor ◽  
Microseismic Events ◽  
The Stability ◽  
Stability And Accuracy

Locating underground microseismic events is important for monitoring subsurface activity and understanding the planetary subsurface evolution. Due to bandwidth limitations, especially in applications involving planetarily-distributed sensor networks, networks should be designed to perform the localization algorithm in-situ, so that only the source location information needs to be sent out, not the raw data. In this paper, we propose a decentralized Gaussian beam time-reverse imaging (GB-TRI) algorithm that can be incorporated to the distributed sensors to detect and locate underground microseismic events with reduced usage of computational resources and communication bandwidth of the network. After the in-situ distributed computation, the final real-time location result is generated and delivered. We used a real-time simulation platform to test the performance of the system. We also evaluated the stability and accuracy of our proposed GB-TRI localization algorithm using extensive experiments and tests.

In Situ Study of Barrier Layers Using Spectroscopic Ellipsometry and Mass Spectroscopy of Recoiled Ions

2000 ◽  
Vol 619 ◽  
Author(s):  
Y. Gao ◽  
A.H. Mueller ◽  
E.A. Irene ◽  
O. Auciello ◽  
A.R. Krauss ◽  
...  
Keyword(s):  
Real Time ◽  
Mass Spectroscopy ◽  
Spectroscopic Ellipsometry ◽  
Nitrogen Concentration ◽  
Random Access ◽  
Copper Interconnects ◽  
Access Memory ◽  
Barrier Layers ◽  
The Stability

ABSTRACTAn in situ study of barrier layers using spectroscopic ellipsometry (SE) and Time-of-Flight (ToF) mass spectroscopy of recoiled ions (MSRI) is presented. First the formation of copper silicides has been observed by real-time SE and in situ MSRI in annealed Cu/Si samples. Second TaSiN films as barrier layers for copper interconnects were investigated. Failure of the TaSiN layers in Cu/TaSiN/Si samples was detected by real-time SE during annealing and confirmed by in situ MSRI. The effect of nitrogen concentration on TaSiN film performance as a barrier was also examined. The stability of both TiN and TaSiN films as barriers for electrodes for dynamic random access memory (DRAM) devices has been studied. It is shown that a combination of in situ SE and MSRI can be used to monitor the evolution of barrier layers and detect the failure of barriers in real-time.

In Situ and Real-Time Atomic Force Microscopy Studies of the Stability of Oligothiophene Langmuir–Blodgett Monolayers in Liquid

2014 ◽  
Vol 118 (11) ◽  
pp. 5789-5795 ◽  
Author(s):  
Nai-Ning Yin ◽  
Alexander Buyanin ◽  
Shawn L. Riechers ◽  
Olivia P. Lee ◽  
Jean M. J. Fréchet ◽  
...  
Keyword(s):  
Atomic Force Microscopy ◽  
Real Time ◽  
Force Microscopy ◽  
Langmuir Blodgett ◽  
Atomic Force ◽  
The Stability

scholarly journals Performance statistics of a real-time Pacific Ocean weather sensor network

2021 ◽  
Author(s):  
IA Houghton ◽  
PB Smit ◽  
D Clark ◽  
C Dunning ◽  
A Fisher ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Pacific Ocean ◽  
Real Time ◽  
Sensor Network ◽  
Open Ocean ◽  
Distributed Sensor Networks ◽  
Data Set ◽  
Distributed Sensor ◽  
Distributed Sensor Network ◽  
Wind Currents

AbstractA distributed sensor network of over one hundred free-drifting, real-time marine weather sensors was deployed in the Pacific Ocean beginning in early 2019. The Spotter buoys used in the network represent a next generation ocean weather sensor designed to measure surface waves, wind, currents, and sea surface temperature. Large distributed sensor networks like these provide much needed long-dwell sensing capabilities in open ocean regions. Despite the demand for better weather forecasts and climate data in our oceans, direct in situ measurements of marine surface weather (waves, winds, currents) remain exceedingly sparse in the open oceans. Due to the large expanse of our oceans, distributed paradigms are necessary to create sufficient data density at global scale, similar to advances in sensing on land and in space. Here we discuss initial findings from this long-dwell open ocean distributed sensor network. Through triple-collocation analysis, we determine errors in collocated satellite-derived observations and model estimates. The correlation analysis shows that the Spotter network provides wave height data with lower errors than both satellites and models. The wave spectrum was also further used to infer wind speed. Buoy drift dynamics are similar to established drogued drifters, particularly when accounting for windage. We find a windage correction factor for the Spotter buoy of approximately 1%, which is in agreement with theoretical estimates. Altogether, we present a completely new open ocean weather data set and characterize the data quality against other observations and models to demonstrate the broad value for ocean monitoring and forecasting that can be achieved using large-scale distributed sensor networks in our oceans.

Stability and Accuracy Analysis of Real-Time Hybrid Simulation (RTHS) with Incomplete Boundary Conditions and Actuator Delay

2020 ◽  
Vol 20 (11) ◽  
pp. 2050122
Author(s):  
Yu Tang ◽  
Hui Qin
Keyword(s):  
Boundary Conditions ◽  
Real Time ◽  
Degrees Of Freedom ◽  
Hybrid Simulation ◽  
Dynamic Responses ◽  
Discrete Control ◽  
Integration Algorithm ◽  
Two Factors ◽  
The Stability ◽  
Stability And Accuracy

The main purpose of this paper is to examine the effects of incomplete boundary conditions and actuator delay on the dynamic responses of seismically excited civil structures. A set of constraint equations representing the reserved interface degrees-of-freedom (DOFs) and the delay are introduced to form a mechanical model of real-time hybrid simulation (RTHS) (referred to as RTHS-I&A) for a multi-degree-of-freedom (MDOF) system based on dynamic substructure method (DSM). Then, the RTHS-I&A system is modeled by a discrete closed-loop transfer function based on discrete control theory, using a selected integration algorithm, and the stability of the system is investigated by examining the poles of the function. Three typical cases with different structural properties are utilized to investigate the effects of incomplete boundary conditions and actuator delay. The results show that both incomplete boundary conditions and actuator delay greatly affect the dynamic responses of structures, and the combination of the two factors will amplify their influence especially on the nodes at the interface. The numerical model of RTHS-I&A proposed in this paper is quite useful for evaluating the responses of structures with different interface conditions and loading schemes that are preliminarily designed before a physical testing is conducted, and provides guidance for future relevant researches.

Interval Density Analysis From a Distributed Absolute Pressure Array

2021 ◽  
Author(s):  
Richard Hewlett ◽  
Stephen Pink ◽  
Jaideva Goswami ◽  
Daniel Debrosse ◽  
Charles Wright
Keyword(s):  
Real Time ◽  
Sensor Array ◽  
Sensor Nodes ◽  
Absolute Pressure ◽  
Fluid Density ◽  
Pressure Data ◽  
Distributed Sensors ◽  
Distributed Sensor ◽  
Density Analysis ◽  
Insight Into

Abstract The objective of this paper is to evaluate the effectiveness of a distributed pressure sensor array along the drillstring in identifying and quantifying fluid influx into the wellbore. As part of a real-time wired drillpipe (WDP) network, distributed sensors can be spaced along the network at varying intervals. In the fall of 2020, a test well was drilled where such a WDP network was utilized, involving 11 discrete sensor packages. These distributed sensors consisted of absolute annular and internal pressure transducers. From these distributed sensors, analysis of various intervals was examined for fluid effects including density analysis. This paper summarizes the findings of the tests and analyses. The WDP network (Craig, et al. 2013) is the underlying technology that allows for the distributed sensor array and the real-time processing of measured data. Each discrete sensor package is a node on the network. The industry-leading telemetry bandwidth of the WDP network allows for many sensor nodes. The test well drilled in the fall of 2020 gave an opportunity to place 11 sensor nodes along the drillstring. The real-time absolute pressure data collected from these nodes was analyzed for various intervals, calculating differential pressure between pressure sensor nodes and further calculating interval fluid density. The results of the distributed absolute pressure data provided many interesting observations. The effectiveness of the interval density for quick-look monitoring was greatly enhanced from the more traditional view of the raw pressure data alone. The effects of sensor spacing and sensitivity were easily observed. Tracking variations in fluid density as it transitions through the wellbore can provide insight into fluid mixing, fluid velocity, and transmission time. Transmission time through the various intervals can further provide insight into wellbore conditions. The slope and peak of interval fluid transitions help understand volumetric and specific density details of fluid transitions from events such as drilling mud pills and influx materials. This novel dataset showcases the power of a real-time distributed sensor array. Multiple intervals of interest can be examined, leading to a new level of wellbore understanding. Information concerning the wellbore fluid can aid in real-time decision making to optimize the wellbore and associated operations, while providing a new level of risk avoidance and safety factor.

Hierarchically Organized Bayesian Networks for Distributed Sensor Networks

2002 ◽  
Author(s):  
Torsten Licht ◽  
Abhijit Deshmukh
Keyword(s):  
Sensor Networks ◽  
Bayesian Networks ◽  
Large Scale ◽  
Security Assessment ◽  
Prior Beliefs ◽  
Distributed Sensor Networks ◽  
Distributed Sensors ◽  
New Formalism ◽  
Distributed Sensor ◽  
Or Groups

As sensor hardware becomes more sophisticated, smaller in size and increasingly affordable, use of large scale sensor networks is bound to become a reality in several application domains, such as vehicle condition monitoring, environmental sensing and security assessment. The ability to incorporate communication and decision capabilities in individual or groups of sensors, opens new opportunities for distributed sensor networks to monitor complex engineering systems. In such large scale sensor networks, the ability to integrate observations or inferences made by distributed sensors into a single hypothesis about the state of the system is critical. This paper addresses the sensor integration issue in hierarchically organized sensor networks. We propose a multi-agent architecture for distributed sensor networks. We present a new formalism to represent causal relations and prior beliefs of hierarchies of sensors, called Hierarchically Organized Bayesian Networks (HOBN), which is a semantic extension of Multiply Sectioned Bayesian Networks (MSBN). This formalism allows a sensor to reason about the integrity of a sensed signal or the integrity of neighboring sensors. Furthermore, we can also evaluate the consistency of local observations with respect to the knowledge of the system gathered up to that point.

Analysis of Barge Adjustment in Large-Scale Structures Ro-Ro Ship Process

2011 ◽  
Vol 255-260 ◽  
pp. 4110-4114
Author(s):  
Meng Gong ◽  
Qing Zhang ◽  
Ming Liu
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Computer Control ◽  
Large Scale Structures ◽  
Key Factor ◽  
The Common ◽  
Scale Structures ◽  
The Stability ◽  
Stability And Accuracy ◽  
Specific Project

It is the key factor that the barge adjustment of large-scale structures’ ro-ro ship when the structure moves onto the barge. Generally, the common method on-site shipment is manual measurement which is a waste of time and labor power, at the same time, Barge adjustment is inaccurate and can not fundamentally solve the problem of the stability and real-time adjustment of the barge. In this paper, these questions are discussed based on the auto barge adjustment centralized in the computer, sensor and other technologies. In the process of ro-ro ship, the automatic computer control has been analyzed which makes the barge adjustment more timely, accurate and ensures real-time stability and accuracy of barge adjustment. Depending on the specific project case, it proves the feasibility and effectiveness of this method.

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