scholarly journals Non Asymptotic Real Time Adaptation to Background Noise in Multichannel C OTDR Monitoring Systems

2015 ◽  
Author(s):  
ANDREY V ◽  
DMITRY V
Keyword(s):  
Real Time ◽  
Background Noise ◽  
Monitoring Systems

Potential Urban Rainfall Prediction Measurement System

1984 ◽  
Vol 16 (8-9) ◽  
pp. 349-362 ◽  
Author(s):  
John L Vogel
Keyword(s):  
Real Time ◽  
The United States ◽  
Monitoring Systems ◽  
Climatic Region ◽  
Convective Storm ◽  
Rainfall Prediction ◽  
Water Quality Regulations ◽  
General Data ◽  
Real Time Information ◽  
Time Information

Continued growth of urban regions and more stringent water quality regulations have resulted in an increased need for more real-time information about past, present, and future patterns and intensities of precipitation. Detailed, real-time information about precipitation can be obtained using radar and raingages for monitoring and prediction of precipitation amounts. The philosophy and the requirements for the development of real-time radar prediction-monitoring systems are described for climatic region similar to the Midwest of the united States. General data analysis and interpretation techniques associated with rainfall from convective storm systems are presented.

scholarly journals Machine Learning Solutions for Bridge Scour Forecast Based on Monitoring Data

2021 ◽  
pp. 036119812110126
Author(s):  
Negin Yousefpour ◽  
Steve Downie ◽  
Steve Walker ◽  
Nathan Perkins ◽  
Hristo Dikanski
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Monitoring Data ◽  
Sensor Data ◽  
Monitoring Systems ◽  
Bridge Scour ◽  
Scour Monitoring ◽  
Novel Approach ◽  
Bayesian Inference Method ◽  
Water Level Variations

Bridge scour is a challenge throughout the U.S.A. and other countries. Despite the scale of the issue, there is still a substantial lack of robust methods for scour prediction to support reliable, risk-based management and decision making. Throughout the past decade, the use of real-time scour monitoring systems has gained increasing interest among state departments of transportation across the U.S.A. This paper introduces three distinct methodologies for scour prediction using advanced artificial intelligence (AI)/machine learning (ML) techniques based on real-time scour monitoring data. Scour monitoring data included the riverbed and river stage elevation time series at bridge piers gathered from various sources. Deep learning algorithms showed promising in prediction of bed elevation and water level variations as early as a week in advance. Ensemble neural networks proved successful in the predicting the maximum upcoming scour depth, using the observed sensor data at the onset of a scour episode, and based on bridge pier, flow and riverbed characteristics. In addition, two of the common empirical scour models were calibrated based on the observed sensor data using the Bayesian inference method, showing significant improvement in prediction accuracy. Overall, this paper introduces a novel approach for scour risk management by integrating emerging AI/ML algorithms with real-time monitoring systems for early scour forecast.

scholarly journals Groundwater Monitoring Systems to Understand Sea Water Intrusion Dynamics in the Mediterranean: The Neretva Valley and the Southern Venice Coastal Aquifers Case Studies

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 561
Author(s):  
Ivan Lovrinović ◽  
Alessandro Bergamasco ◽  
Veljko Srzić ◽  
Chiara Cavallina ◽  
Danko Holjević ◽  
...  
Keyword(s):  
Real Time ◽  
Coastal Aquifers ◽  
Sea Water ◽  
Quantitative Information ◽  
Water Dynamics ◽  
Monitoring Systems ◽  
Driving Mechanism ◽  
Sea Water Intrusion ◽  
Water Intrusion ◽  
Aquifer Systems

Sea water intrusion (SWI) has been widely recognized as a global problem, significantly influencing coastal aquifers, mostly through reduced water quality and agricultural production indicators. In this paper, we present the outcomes of the implementation of two independent real-time monitoring systems, planned and installed to get insights on groundwater dynamics within the adjacent coastal aquifer systems, one located in the Neretva Valley, southeastern Croatia, the other located south of the Venice lagoon, northeastern Italy. Both systems are presented with technical details and the capacity to observe, store, and transmit (Neretva site) observed values in real-time. Analysis of time series reveals the significant influence of the sea level oscillations onto the observed groundwater electrical conductivity (EC) and piezometric head values, while precipitation rate is detected as a driving mechanism for groundwater parameters in shallow geological units. The installed monitoring systems are shown to be of great importance to provide qualitative and quantitative information on the processes influencing groundwater and surface water dynamics within two coastal systems.

Compressor Computerized Performance Monitoring System CPMS

2021 ◽  
Author(s):  
Vadim Goryachikh ◽  
Fahad Alghamdi ◽  
Abdulrahman Takrouni
Keyword(s):  
Natural Gas ◽  
Real Time ◽  
Monitoring System ◽  
Performance Monitoring ◽  
Compressibility Factor ◽  
Background Information ◽  
Monitoring Systems ◽  
Turbo Expander ◽  
Time Calculation ◽  
Performance Deterioration

Abstract Background information Natural gas liquid (NGL) production facilities, typically, utilize turbo-expander-brake compressor (TE) to generate cold for C2+ separation from the natural gas by isentropic expansion of feed stream and use energy absorbed by expansion to compress residue gas. Experience shows that during operational phase TE can exposed to operation outside of design window that may lead to machine integrity loss and consequent impact on production. At the same time, there is a lack of performance indicators that help operator to monitor operating window of the machine and proactively identify performance deterioration. For instance, TE brake compressor side is always equipped with anti-surge protection system, including surge deviation alarms and trip. However, there is often gap in monitoring deviation from stonewall region. At the same time, in some of the designs (2×50% machines) likelihood of running brake compressor in stonewall is high during one machine trip or train start-up, turndown operating modes. Also, typical compressor performance monitoring systems does not have enough dynamic parameters that may indicate machine process process performance deterioration proactively (real-time calculation of actual polytrophic efficiency, absorbed power etc.) and help operator to take action before catastrophic failure occurs. In addition, typical compressor monitoring systems are based on assumed composition and fixed compressibility factor and do not reflect actual compositions variations that may affect machine performance monitoring. To overcome issues highlighted above, Hawiyah NGL (HNGL) team has developed computerized monitoring and advisory system to monitor the performance of turbo-expander-brake compressor, proactively, identify potentially unsafe conditions or performance deterioration and advice operators on taking necessary actions to avoid unscheduled deferment of production. Computerized performance monitoring system has been implemented in HNGL DCS (Yokogawa) and utilized by control room operators on day-to-day basis. Real-time calculation, analysis and outputs produced by performance monitoring system allow operator to understand how current operating condition are far from danger zone. Proactive deviation alarms and guide messages produce by the system in case of deviation help operators to control machine from entering unsafe region. Actual polytrophic efficiency, adsorbed power calculations provide machine condition status and allow identifying long-term performance deterioration trends.

On Real-Time Performance Evaluation of Volcano-Monitoring Systems With Wireless Sensor Networks

2015 ◽  
Vol 15 (6) ◽  
pp. 3514-3523 ◽  
Author(s):  
Roman Lara ◽  
Diego Benitez ◽  
Antonio Caamano ◽  
Marco Zennaro ◽  
Jose Luis Rojo-Alvarez
Keyword(s):  
Wireless Sensor Networks ◽  
Performance Evaluation ◽  
Sensor Networks ◽  
Real Time ◽  
Volcano Monitoring ◽  
Wireless Sensor ◽  
Monitoring Systems ◽  
Time Performance

A Highly Reliable Online Monitoring and Real-Time Alarm System for the Insulation Condition of Power Transformers

2014 ◽  
Vol 971-973 ◽  
pp. 1045-1050
Author(s):  
Wen Xing Sun ◽  
Zhao Hui Li ◽  
Shi Jie Cheng
Keyword(s):  
Electric Power ◽  
Real Time ◽  
Condition Monitoring ◽  
Online Monitoring ◽  
Hydropower Plant ◽  
Power Transformers ◽  
Monitoring Systems ◽  
Alarm System ◽  
Condition Monitoring Systems ◽  
Insulation Condition

Many successful applications for the online monitoring of the insulation condition for electric power transformers have been reported over last thirty years. However, false or unsolved alarms have been quite frequently generated by those condition monitoring systems. Failures and some occasionally catastrophic accidents involving transformers have still occurred. A highly reliable insulation condition online monitoring and real-time alarm system has been developed, to help resolve these problems. An electric power transformer has strongly linked mechanical, electrical, magnetic, chemical and thermal characteristics, and is also directly linked to circuit breakers and generators. Team Intelligence (TI) was employed to integrate all the monitoring modules of the various different aspects of the transformer into one unique system. This system could also be integrate with the condition monitoring systems of various linked facilities, such as the monitoring systems of the turbine and the generator in a Optimal Maintenance Information System for Hydropower Plant (HOMIS). Highly reliable monitoring and real-time alarms of transformer insulation condition could be achieved, due to highly coordinated and rapid response features. This system has been deployed in several hydropower plants. The industrial application examples are demonstrated.

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