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

A fluid network, fluid technology, applied in the field of monitoring and detection of fluid networks, modeling, and analysis, to solve problems such as infrastructure, water quality, or health that are not found and resolved

Active Publication Date: 2019-04-19

3M INNOVATIVE PROPERTIES CO

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AI-Extracted Technical Summary

Problems solved by technology

Such problems may not be identified and resolved until they have...

Method used

Embodiment 9 is the method according to any one of embodiments 1 to 8, wherein determining the sensor or infrastructure p...

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.

Application Domain

Geometric CADFluid-pressure actuator testing +8

Technology Topic

Real-time computingDistributed computing +1

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Examples

Experimental program(1)

Example Embodiment

[0098] Embodiment 1 is a method for optimally determining the placement of sensors or infrastructure in a fluid network. The method includes:

[0099] Create a model of the fluid network, wherein the model includes i) a plurality of directional connection nodes representing a fluid infrastructure provided in the fluid network and ii) one positioned at one or more selected locations in the fluid network Or multiple sensors;

[0100] Express the model as a matrix data structure associated with a processor, where the processor is set outside the fluid network;

[0101] Analyzing the matrix by the processor to evaluate whether each node of the model meets one or more locateability criteria, wherein analyzing the matrix includes interpreting and executing a plurality of instructions associated with the processor; and

[0102] The placement of the sensor or infrastructure in the fluid network is determined based on the result of analyzing the matrix.

[0103] Embodiment 2 is the method according to embodiment 1, wherein the model includes one or more directed acyclic graphs (DAG), and the matrix includes an accessible matrix.

[0104] Embodiment 3 is the method according to embodiment 1 or 2, wherein analyzing the matrix includes dynamic programming, which includes a bottom-up approach starting from the lowest level in the matrix.

[0105] Embodiment 4 is the method according to any one of embodiments 1 to 3, wherein analyzing whether each node of the model satisfies one or more localizable criteria includes evaluating whether there is a node set at the given node. At least two downstream sensors, the at least two sensors having corresponding paths that do not share any d partitions with respect to the given node.

[0106] Embodiment 5 is the method according to any one of embodiments 1 to 4, wherein determining the sensor or infrastructure placement includes providing a sensor to the given node when the given node does not meet the localizable criterion, and when the When a given node meets the locating standard, no sensor is provided to the given node.

[0107] Embodiment 6 is the method of any one of embodiments 1 to 5, wherein determining the sensor or infrastructure placement includes determining a minimum number of sensors to cover the complete fluid network.

[0108] Embodiment 7 is the method according to embodiment 6, wherein determining the sensor or infrastructure placement includes determining the complexity index of the fluid network as the ratio of the minimum number of sensors required to the number of nodes.

[0109] Embodiment 8 is the method according to any one of embodiments 1 to 7, wherein creating the model further includes grouping a plurality of adjacent nodes of the model into a node set.

[0110] Embodiment 9 is the method according to any one of embodiments 1 to 8, wherein determining the sensor or infrastructure placement includes adding one or more fluid paths between the nodes in the fluid network to reduce the number of sensors .

[0111] Implementation plan II :

[0112] Embodiment 1 is a method for detecting an abnormality of interest in a fluid network, the method including:

[0113] Providing one or more sensors arranged at one or more selected locations in the fluid network, wherein the sensors are configured to collect data from the fluid network at the corresponding locations;

[0114] Collecting data from the fluid network at the one or more locations through the one or more sensors;

[0115] Receive data from the sensor through the processor; and

[0116] The data is analyzed by the processor based on a model of the fluid network, where the model is represented as a directed graph associated with the processor, the directed graph includes a plurality of directional connection nodes, and one or more hypothetical nodes are Add between two adjacent nodes.

[0117] Embodiment 2 is the method according to embodiment 1, wherein the abnormality is related to pollution or infrastructure failure in the fluid network.

[0118] Embodiment 3 is the method according to embodiment 1 or 2, wherein analyzing the data further includes calculating the pollution level at one or more nodes in the detection area in the fluid network.

[0119] Embodiment 4 is the method according to embodiment 3, wherein calculating the pollution level at the plurality of nodes further includes determining the absorption probability matrix Q.

[0120] Embodiment 5 is the method according to embodiment 3 or 4, wherein analyzing the data further includes locating one or more pollution sources based on the calculated pollution level at the first node.

[0121] Embodiment 6 is the method according to embodiment 3, 4, or 5, wherein the detection area is determined based on one or more localizable criteria, and the localizable criteria includes evaluating whether there is a location set at the given node. At least two downstream sensors, the at least two sensors having corresponding paths that do not share any d partitions with respect to the given node.

[0122] Embodiment 7 is the method according to any one of embodiments 1 to 6, wherein the model is a harmonic model, and the pollution concentration level in the fluid network is expressed as a harmonic function.

[0123] Embodiment 8 is the method according to embodiment 7, wherein the pollution concentration level includes a chlorine level.

[0124] Embodiment 9 is the method according to any one of embodiments 1 to 8, wherein the directed graph further includes a second imaginary node connected to the one or more imaginary nodes.

[0125] Implementation List III :

[0126] Embodiment 1 is a method for determining the coverage of sensors in a fluid network. The method includes:

[0127] Create a model of the fluid network, wherein the model includes a plurality of directional connection nodes representing a fluid infrastructure provided in the fluid network and one or more sensors positioned at one or more selected locations in the fluid network ;

[0128] Express the model as a matrix data structure associated with a processor, where the processor is set outside the fluid network;

[0129] Analyzing the matrix by the processor to evaluate whether each node meets one or more locateability criteria, wherein analyzing the matrix includes interpreting and executing multiple instructions associated with the processor;

[0130] Assign each node to one of the positioning area, the detection area, and the safety area.

[0131] Embodiment 2 is the method according to embodiment 1, wherein the model is a graphical model including one or more directed acyclic graphs (DAG).

[0132] Embodiment 3 is the method according to embodiment 1 or 2, wherein analyzing whether each node meets one or more locateability criteria includes evaluating the path between a pair of nodes through the multiple instructions to determine whether the path passes through Through intermediate nodes.

[0133] Embodiment 4 is the method according to embodiment 3, wherein evaluating the path includes implementing an advanced Markov chain method through the plurality of instructions.

[0134] Embodiment 5 is the method according to any one of embodiments 1 to 4, wherein analyzing whether each node satisfies one or more locateability criteria includes evaluating whether there is downstream of a given node through the multiple instructions The at least two sensors of the at least two sensors have corresponding paths that do not share any d partitions with respect to the given node.

[0135] Embodiment 6 is the method according to any one of embodiments 1 to 5, wherein when a given node satisfies the location criterion, the given node is assigned to the location area, and when the given node does not meet the location area When the standard can be located, the given node is allocated to the detection area or the safety area.

[0136] Embodiment 7 is the method according to embodiment 6, wherein when the given node does not meet the localizable criterion, the given node is further evaluated to determine whether the sensor is located downstream of the given node, and when no sensor is located at When downstream, the given node is assigned to the safe area, otherwise the given node is assigned to the detection area.

[0137] Embodiment 8 is the method according to any one of embodiments 1 to 7, further comprising determining the minimum detectable concentration of the pollution level of each node.

[0138] Embodiment 9 is the method according to embodiment 8, wherein determining the minimum detectable concentration includes analyzing the sensitivity and absorption probability matrix of sensors distributed in the fluid network.

[0139] Implementation plan IV :

[0140] Embodiment 1 is a system including:

[0141] One or more sensors positioned at one or more selected locations in the fluid network, wherein the sensors are configured to collect data from the fluid network at the corresponding location; and

[0142] A processor provided outside the fluid network, wherein the processor is configured to receive data from the sensor and analyze the data based on a model of the fluid network, wherein the model includes representations of the fluid infrastructure provided in the fluid network A plurality of directional connection nodes and one or more sensors positioned at the one or more selected locations; and

[0143] A plurality of instructions associated with the processor, where the plurality of instructions are interpretable and executable by the processor to analyze the data and determine sensor placement in the fluid network.

[0144] Embodiment 2 is the system according to embodiment 1, wherein the fluid network includes a water network.

[0145] Embodiment 3 is the system according to embodiment 1 or 2, wherein the fluid infrastructure of the fluid network includes one or more water filters.

[0146] Embodiment 4 is the system according to embodiment 3, wherein the plurality of sensors includes one or more filter sensors provided with the water filter.

[0147] Embodiment 5 is the system according to any one of embodiments 1 to 4, wherein the data from the sensor is related to one or more parameters of disinfectant concentration, contaminant concentration, pressure or flow rate.

[0148] Embodiment 6 is the system according to any one of embodiments 1 to 5, wherein the data is related to a change or damage to the fluid network.

[0149] Embodiment 7 is the system according to any one of embodiments 1 to 6, further comprising a database associated with the processor, wherein the data from the sensor is stored in the database.

[0150] Embodiment 8 is the system according to embodiment 7, wherein the database further includes historical data related to the model of the fluid network.

[0151] Embodiment 9 is the system according to any one of embodiments 1 to 8, further including a display.

[0152] Embodiment 10 is the system according to any one of embodiments 1 to 9, wherein the model includes one or more directed acyclic graphs (DAG).

PUM

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