Estado del arte en detección de fugas y propuesta de máquina de soporte vectorial para el análisis de estanqueidad en envases

This document presents an experimental study that supports probabilistic decisions based on neural networks to detect the presence of leaks in pipeline transport systems, since such leaks can cause serious consequences. In addition to the economic losses presented by the lost product, process stoppage and repair of the damage, there can be insurmountable environmental and social losses such as the death of human beings. The probabilistic model correlates measurements of inlet and outlet pressures and flow to the state of leakage. The study and experimentation presented in this work are based on information acquired by simulating the behavior of the fluid in a pilot tube installed in the Fluid Mechanics laboratory of the Universidad Francisco de Paula Santander, Seccional Ocaña. Finally, experimental tests were carried out to obtain the data of the physical variables of the flow sensors at the entrance and exit, with these data a multilayer neural network of perception was trained. The results obtained from the test equipment, with intentionally caused leaks, showed that the structure of the multilayer Perceptron neural network was capable of detecting leaks in the pilot tubes. With the accomplishment of this work it was found that the neural network presents favorable results at the time of detecting the leak compared with other methods of detection since this one presents immunity to the noise, a parallel structure and, consequently, capacities of fast processing and classification.

show abstract

Diagnosis of horizontal pipe leaks using neural networks

Camperos

Blanco

2019

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Estado del arte en detección de fugas y propuesta de máquina de soporte vectorial para el análisis de estanqueidad en envases

Cited by 1 publication

References 12 publications

Diagnosis of horizontal pipe leaks using neural networks

Diagnosis of horizontal pipe leaks using neural networks

Contact Info

Product

Resources

About