公开(公告)号：US20190331513A1

公开(公告)日：2019-10-31

申请号：US16310375

申请日：2017-06-14

Applicant: Hifi Engineering Inc.

Inventor： Seyed Ehsan Jalilian ,  Dongliang Huang ,  Henry Leung ,  King Fai Ma

IPC: G01F1/66 ,  G01M3/28 ,  G06N3/08

Abstract: There is provided a method of estimating flowrate in a pipeline based on acoustic behaviour of the pipe. First acoustic data is measured from the pipeline. A flowrate of the fluid in the pipeline is then estimated. The estimation is based on the first acoustic data and based on a correlation established between second acoustic data and corresponding flowrate data from an experimental pipeline. The correlation is established by a machine learning process (which may include the use of an artificial neural network, such as an autoencoder). The second acoustic data and corresponding flowrate data are used as inputs to the machine learning process.

公开(公告)号：US20240377235A1

公开(公告)日：2024-11-14

申请号：US18783079

申请日：2024-07-24

Applicant: Hifi Engineering Inc.

Inventor： Seyed Ehsan Jalilian ,  Dongliang Huang ,  Henry Leung ,  King Fai Ma

IPC: G01F1/66 ,  G01M3/28 ,  G06N3/0455 ,  G06N3/08 ,  G06N20/00

Abstract: There is provided a method of estimating flowrate in a pipeline based on acoustic behaviour of the pipe. First acoustic data is measured from the pipeline. A flowrate of the fluid in the pipeline is then estimated. The estimation is based on the first acoustic data and based on a correlation established between second acoustic data and corresponding flowrate data from an experimental pipeline. The correlation is established by a machine learning process (which may include the use of an artificial neural network, such as an autoencoder). The second acoustic data and corresponding flowrate data are used as inputs to the machine learning process.

公开(公告)号：US12078518B2

公开(公告)日：2024-09-03

申请号：US16310375

申请日：2017-06-14

Applicant: Hifi Engineering Inc.

Inventor： Seyed Ehsan Jalilian ,  Dongliang Huang ,  Henry Leung ,  King Fai Ma

IPC: G01F1/66 ,  G01M3/28 ,  G06N3/0455 ,  G06N3/08 ,  G06N20/00

CPC classification number: G01F1/666 ,  G01F1/662 ,  G01M3/2807 ,  G06N3/08 ,  G06N20/00 ,  G06N3/0455

Abstract: There is provided a method of estimating flowrate in a pipeline based on acoustic behaviour of the pipe. First acoustic data is measured from the pipeline. A flowrate of the fluid in the pipeline is then estimated. The estimation is based on the first acoustic data and based on a correlation established between second acoustic data and corresponding flowrate data from an experimental pipeline. The correlation is established by a machine learning process (which may include the use of an artificial neural network, such as an autoencoder). The second acoustic data and corresponding flowrate data are used as inputs to the machine learning process.