Systems and methods for modeling, analyzing, detecting, and monitoring fluid networks

Patent metadata

Field	Value
Publication number	US-11250177-B2
Application number	US-201716328179-A
Country	US
Kind code	B2
Filing date	Jul 31, 2017
Priority date	Aug 31, 2016
Publication date	Feb 15, 2022
Grant date	Feb 15, 2022

Abstract

Systems and methods are provided for optimally determining sensor or infrastructure placement in a fluid network, for determining an anomaly of interest in the fluid network, and for determining sensor coverage in a fluid network, which are based on a model of the fluid network represented by a directed graph.

First claim

What is claimed is:

1. A method of determining sensor coverage in a fluid network, the method comprising:
creating a model of the fluid network, wherein the model comprises a plurality of directionally connected nodes representing fluid infrastructure disposed in the fluid network and one or more sensors at positioned one or more selected locations in the fluid network;
representing, via a processor, the model as a computer data structure comprising a matrix data structure, wherein the processor is disposed outside of the fluid network;
collecting sensor data comprising a contamination concentration or concentration change from one or more sensors disposed at one or more selected locations of the nodes in the fluid network;
analyzing, via the processor, the matrix data structure to evaluate whether each node of the fluid network satisfies one or more localizability criteria, wherein analyzing the matrix comprises interpreting and executing a plurality of instructions implemented by the processor;
assigning each node to one of a localization area, a detection area, and an out-of-reach area;
generating, via the processor, a harmonic function of the contamination concentration or concentration change;
modifying, via the processor, the matrix data structure to a harmonic diffusion model based on the harmonic function; and
calculating and outputting, via the processor, a contamination level at each of the nodes in the fluid network based on the harmonic diffusion model.

2. The method of claim 1 , wherein the model is a graphical model including one or more directed acyclic graphs (DAGs).

3. The method of claim 1 , wherein analyzing whether each node satisfies one or more localizability criteria comprises evaluating, via the plurality of instructions, paths between a pair of nodes to determine whether the paths pass through a medial node.

4. The method of claim 3 , wherein evaluating the path includes implementing, via the plurality of instructions, an advanced Markov chain method.

5. The method of claim 1 , wherein analyzing whether each node satisfies one or more localizability criteria includes for a given node, evaluating, via the plurality of instructions, whether there are at least two sensors located downstream of the given node which have the respective paths not sharing any d-separator with respect to the given node.

6. The method of claim 1 , wherein when a given node satisfies the localizability criteria, the given node is assigned to the localization area, and when the given node does not satisfy the localizability criteria, the given node is assigned to the detection area or the out-of-reach area.

7. The method of claim 6 , wherein when the given node does not satisfy the localizability criteria, the given node is further evaluated to determine whether a sensor is located downstream from the given node, when no sensors are located downstream, the given node is assigned to the out-of-reach area, otherwise the given node is assigned to the detection area.

8. The method of claim 1 further comprising determining a minimum detectable concentration of contamination level for each node.

9. The method of claim 8 , wherein determining the minimum detectable concentration comprises analyzing the sensitivity of sensors distributed in the fluid network and an absorption probability matrix.

10. A system, comprising:
one or more sensors positioned at one or more selected locations in a fluid network, wherein the sensors are configured to collect data comprising a contamination concentration or concentration change from the fluid network at the respective locations; and
a processor disposed outside of the fluid network, wherein the processor is configured to receive the data from the sensors, and analyze the data based on a model of the fluid network, wherein the model is represented as a computer data structure comprising a plurality of directionally connected nodes representing fluid infrastructure disposed in the fluid network and the one or more sensors positioned at the one or more selected locations,
wherein a plurality of instructions are interpretable and executable by the processor to analyze the data and determine sensor placement within the fluid network, and
wherein the processor is further configured to:
generate a harmonic function of the contamination concentration or concentration change;
modify the model to a harmonic diffusion model based on the harmonic function; and
calculate and output a contamination level at each of the nodes in the fluid network based on the harmonic diffusion model.

11. The system of claim 10 , wherein the fluid network includes a water network.

12. The system of claim 10 , wherein the fluid infrastructure of the fluid network includes one or more water filters.

13. The system of claim 12 , wherein the plurality of sensors includes one or more filter sensors provided with the water filters.

14. The system of claim 10 , wherein the data from the sensors are related to one or more parameters of a disinfectant concentration, a contaminant concentration, a pressure, or a flow rate.

15. The system of claim 10 , wherein the data are related to a change or damage to the fluid network.

16. The system of claim 10 further comprising a database associated with the processor, wherein the data from the sensors are stored in the database.

17. The system of claim 16 , wherein the database further includes historical data related to the model of the fluid network.

18. The system of claim 10 further comprising a display.

19. The system of claim 10 , wherein the model includes one or more directed acyclic graph (DAGs).

Assignees

• 3M Innovative Properties Co

Inventors

• Schumacher Jennifer F
• Taghaeeyan Saber
• Jesme Ronald D
• Bonifas Andrew P
• Amell Nicholas G
• Hable Brock A
• Golnari Golshan

Classifications

• G06Q50/06 Primary

  Energy or water supply · CPC title

• F15B19/007

  Simulation or modelling · CPC title

• G06F30/20

  Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30) · CPC title

• G01M3/2807

  for pipes (G01M3/2892, G01M3/30 take precedence) · CPC title

• E03B11/02

  for domestic or like local water supply · CPC title