Multi-level information fusion for spatiotemporal monitoring in water distribution networks

Aminravan, Farzad; Sadiq, Rehan; Hoorfar, Mina; Rodriguez, Manuel J.; Najjaran, Homayoun

doi:10.1016/j.eswa.2014.11.014

Cited by 11 publications

(5 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Multiple sensors obtain data that is uncertain, inaccurate or may even contain conflicting information [ 19 ], thus all the data gathered from different sensors must be fused. One of the most commonly used solutions to IF problems is the use of multi-agent architectures, especially because they can implement new algorithms for IF and manage high level information [ 20 , 21 , 22 ]. An automated reasoning system is implemented [ 23 ] to provide the system with the ability to make decisions based on new and past information obtained by a network of heterogeneous sensors.…”

Section: Related Workmentioning

confidence: 99%

GreenVMAS: Virtual Organization Based Platform for Heating Greenhouses Using Waste Energy from Power Plants

González‐Briones

Chamoso

Yoe

et al. 2018

Sensors

View full text Add to dashboard Cite

The gradual depletion of energy resources makes it necessary to optimize their use and to reuse them. Although great advances have already been made in optimizing energy generation processes, many of these processes generate energy that inevitably gets wasted. A clear example of this are nuclear, thermal and carbon power plants, which lose a large amount of energy that could otherwise be used for different purposes, such as heating greenhouses. The role of GreenVMAS is to maintain the required temperature level in greenhouses by using the waste energy generated by power plants. It incorporates a case-based reasoning system, virtual organizations and algorithms for data analysis and for efficient interaction with sensors and actuators. The system is context aware and scalable as it incorporates an artificial neural network, this means that it can operate correctly even if the number and characteristics of the greenhouses participating in the case study change. The architecture was evaluated empirically and the results show that the user’s energy bill is greatly reduced with the implemented system.

show abstract

Section: Related Workmentioning

confidence: 99%

GreenVMAS: Virtual Organization Based Platform for Heating Greenhouses Using Waste Energy from Power Plants

González‐Briones

Chamoso

Yoe

et al. 2018

Sensors

View full text Add to dashboard Cite

show abstract

“…The concentration is the result of the structure of water pipeline, and, in particular, of the number of independent water supply sources, the existence of retention capacity in the water supply network, water supply network spatial structure and variability of water demand in both daily and hourly cycle and it results directly from the hydraulics of system [22,26,32] and are defined through reliability and safety of system functioning [33,34].…”

Section: The Research Methodologymentioning

confidence: 99%

“…A well-known tool for the analysis of water supply network, both in terms of quantity and quality, is the EPANET software [25][26][27]. It is successfully used for qualitative analysis of disinfectants and naturally occurring in water compounds [5,6].…”

Section: Introductionmentioning

confidence: 99%

Simulation Model of Contamination Threat Assessment in Water Network Using the Epanet Software

Studziński

Pietrucha-Urbanik

2016

Ecological Chemistry and Engineering S

View full text Add to dashboard Cite

Abstract:The aim of this study is to assess the risk of failure of group water network in case of raw water contamination. The analysis was based on qualitative simulation performed in hydraulic water network model developed in the EPANET software. It was focused on the quantitative description of the consequences of chemically contaminated water. The methodology of risk assessment relies in determining the consequences of the supply water containing contamination threatening the health and lives of water consumers. The research methodology is as follows: development of a hydraulic model of the water pipeline and it's hydraulic verification, computer simulations of contamination propagation, calculating the dose delivered to the i-th section of the water supply system supplying water to Ni recipients and the mass of a substance that enters the body li. The simulation results indicate the spread of contamination that after 24 h covered most of the area supplied with water. The load delivered to the resident obtaining water from the i-th section of the water supply network, Li/Ni, was up to 18 g·d -1 , at least 15 g·d -1 was received by 34.9% of the population, 10-15 g·d -1 by 12.5% of the residents, 5-10 g·d -1 by 10.7% of the residents, 0-5 g·d -1 by 41.7% of the residents and uncontaminated water was delivered to only 13.3% of the consumers. The dose taken by the statistical consumer (calculated as for adults) l is up to 0.8 g for Li/Ni = 18 g·d -1 and is proportional to Li/Ni.

show abstract

“…First, the indicators at the bottom are combined, and then the mixed results are used as the input of the next layer. Hierarchical BRB can reduce the number of rules and avoid the explosion of combined rules [28,29].…”

Section: Introductionmentioning

confidence: 99%

Milling Fault Detection Method Based on Fault Tree Analysis and Hierarchical Belief Rule Base

Cheng¹,

Long²,

Wang³

et al. 2023

Computer Systems Science and Engineering

View full text Add to dashboard Cite

Expert knowledge is the key to modeling milling fault detection systems based on the belief rule base. The construction of an initial expert knowledge base seriously affects the accuracy and interpretability of the milling fault detection model. However, due to the complexity of the milling system structure and the uncertainty of the milling failure index, it is often impossible to construct model expert knowledge effectively. Therefore, a milling system fault detection method based on fault tree analysis and hierarchical BRB (FTBRB) is proposed. Firstly, the proposed method uses a fault tree and hierarchical BRB modeling. Through fault tree analysis (FTA), the logical correspondence between FTA and BRB is sorted out. This can effectively embed the FTA mechanism into the BRB expert knowledge base. The hierarchical BRB model is used to solve the problem of excessive indexes and avoid combinatorial explosion. Secondly, evidence reasoning (ER) is used to ensure the transparency of the model reasoning process. Thirdly, the projection covariance matrix adaptation evolutionary strategies (P-CMA-ES) is used to optimize the model. Finally, this paper verifies the validity model and the method's feasibility techniques for milling data sets.

show abstract

Multi-level information fusion for spatiotemporal monitoring in water distribution networks

Cited by 11 publications

References 49 publications

GreenVMAS: Virtual Organization Based Platform for Heating Greenhouses Using Waste Energy from Power Plants

GreenVMAS: Virtual Organization Based Platform for Heating Greenhouses Using Waste Energy from Power Plants

Simulation Model of Contamination Threat Assessment in Water Network Using the Epanet Software

Milling Fault Detection Method Based on Fault Tree Analysis and Hierarchical Belief Rule Base

Contact Info

Product

Resources

About