Accurate Spectral Estimation Technique Based on Decimated Linear Predictor for Leak Detection in Waterworks
Clicks: 114
ID: 268885
2021
Article Quality & Performance Metrics
Overall Quality
Improving Quality
0.0
/100
Combines engagement data with AI-assessed academic quality
Reader Engagement
Emerging Content
30.0
/100
113 views
1 readers
Trending
AI Quality Assessment
Not analyzed
Abstract
Rural pipelines dedicated to water distribution, that is, waterworks, are essential for agriculture, notably plantations and greenhouse cultivation. Water is a primary resource for agriculture, and its optimized management is a key aspect. Saving water dispersion is not only an economic problem but also an environmental one. Spectral estimation of leakage is based on processing signals captured from sensors and/or transducers generally mounted on pipelines. There are different techniques capable of processing signals and displaying the actual position of leaks. Not all algorithms are suitable for all signals. That means, for pipelines located underground, for example, external vibrations affect the spectral response quality; then, depending on external vibrations/noises and flow velocity within pipeline, one should choose a suitable algorithm that fits better with the expected results in terms of leak position on the pipeline and expected time for localizing the leak. This paper presents findings related to the application of a decimated linear prediction (DLP) algorithm for agriculture and rural environments. In a certain manner, the application also detects the hydrodynamics of the water transportation. A general statement on the issue, DLP illustration, a real application and results are also included.
Abstract Quality Issue:
This abstract appears to be incomplete or contains metadata (193 words).
Try re-searching for a better abstract.
| Reference Key |
lay-ekuakille2021sensorsaccurate
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Aimé Lay-Ekuakille;Vito Telesca;Paolo Visconti;Nicola Ivan Giannoccaro;Lay-Ekuakille, Aimé;Telesca, Vito;Visconti, Paolo;Giannoccaro, Nicola Ivan; |
| Journal | sensors |
| Year | 2021 |
| DOI |
10.3390/s21062185
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.