# US 2022/0171891 A1 · Automatic extraction of assets data from engineering data sources

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- Number: US 2022/0171891 A1
- Document ID: US20220171891A1
- Status: Published application
- Kind: A1
- Application number: 17/442,403
- Filed: 2020-03-24
- Published: 2022-06-02
- Earliest claimed: 2019-03-25
- Assignees: Schneider Electric Systems USA, Inc.
- Applicants: Schneider Electric Systems USA, Inc.
- Inventors: Bhaskar SINHA; Venkatesh JAGANNATH; Amitabha BHATTACHARYYA; Ashish PATIL; Sameer KONDEJKAR
- Web page: https://patentgrep.com/patent/US20220171891A1

## CPC

- G06F 30/12: characterised by design entry means specially adapted for CAD, e.g. graphical user interfaces [GUI] specially adapted for CAD
- G05B 17/02: electric
- G05B 19/0426: {Programming the control sequence}
- G05B 19/41885: {characterised by modeling, simulation of the manufacturing system}
- G05B 23/0221: {Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods}
- G05B 23/0243: {model based detection method, e.g. first-principles knowledge model}
- G05B 23/027: {Alarm generation, e.g. communication protocol; Forms of alarm}
- G05B 23/0272: {Presentation of monitored results, e.g. selection of status reports to be displayed; Filtering information to the user}
- G05B 23/0281: {Quantitative, e.g. mathematical distance; Clustering; Neural networks; Statistical analysis}
- G06F 30/27: using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
- G06N 5/022: Knowledge engineering; Knowledge acquisition
- G05B 2219/23008: Computer aided software engineering, program generation, case tools, CASE
- G05B 2219/23067: Control, human or man machine interface, interactive, HMI, MMI
- G05B 2219/23272: Natural language, use simple words like move, rotate
- G05B 2219/23278: Program by data flow
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G)
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS

## Abstract

Systems and methods for controlling industrial an industrial plant comprise: inputting an engineering diagram for a unit of the industrial plant, the engineering diagram including symbols representing assets of the industrial plant; extracting one or more assets from the engineering diagram using machine learning to recognize the one or more assets, the one or more assets including equipment, instruments, connectors, and lines, the lines relating the equipment, instruments, and connectors to one another; determining one or more relationships between the equipment, instruments, connectors, and lines to one another using machine learning to recognize the one or more relationships; and creating a flow graph from the equipment, instruments, connectors, and lines and the relationships between the equipment, instruments, connectors, and lines.

## Claims

### Claim 1

A control system for an industrial plant, comprising:
one or more processors; and
a storage unit communicatively coupled to the one or more processors and storing processor-executable instructions thereon that, when executed by the one or more processors, cause the control system to:
perform a process that inputs an engineering diagram for a unit of the industrial plant, the engineering diagram including symbols representing assets of the industrial plant;
perform a process that extracts one or more assets from the engineering diagram using machine learning to recognize the one or more assets, the one or more assets including equipment, instruments, connectors, and lines, the lines relating the equipment, instruments, and connectors to one another;
perform a process that determines one or more relationships between the equipment, instruments, connectors, and lines to one another using machine learning to recognize the one or more relationships; and
perform a process that creates a flow graph from the equipment, instruments, connectors, and lines and the relationships between the equipment, instruments, connectors, and lines.

### Claim 2 (depends on 1)

The control system of claim 1, wherein the process that extracts one or more assets from the engineering diagram includes a geometry-based extraction process and a machine learning-based classification process.

### Claim 3 (depends on 1)

The control system of claim 1, wherein the processor-executable instructions further cause the control system to perform a process that extracts one or more control loops from the engineering diagram based on one or more of the equipment, instruments, connectors, and lines.

### Claim 4 (depends on 1)

The control system of claim 1, wherein the processor-executable instructions further cause the control system to perform a process that extracts a unit identifier from the engineering diagram, wherein the unit identifier uniquely identifies a particular unit from among multiple units in the industrial plant.

### Claim 5 (depends on 1)

The control system of claim 1, wherein the processor-executable instructions further cause the control system to perform a process that extracts a drawing number and a revision number from the engineering diagram, the drawing number uniquely identifying the engineering diagram from among multiple engineering diagrams for the industrial plant and the revision number indicating a revision of the engineering diagram which is incremented whenever there are changes in the engineering diagram.

### Claim 6 (depends on 4)

The control system of claim 4, wherein the processor-executable instructions further cause the control system to perform a process that assigns a unique identifier to each equipment, instrument, connector, and line of the engineering diagram using the unit identifier from the engineering diagram.

### Claim 7 (depends on 1)

The control system of claim 1, wherein the process that determines one or more relationships between the equipment, instruments, connectors, and lines includes a process that generates a line-line graph, a process that generates an equipment-line graph, a process that generates a connector-line graph, and a process that generates an instrument-line graph.

### Claim 8 (depends on 1)

The control system of claim 1, wherein the processor-executable instructions further cause the control system to create the flow graph for the engineering diagram by performing a process that merges the line-line graph, the equipment-line graph, the connector-line graph, and the instrument-line graph with one another.

### Claim 9 (depends on 7)

The control system of claim 7, wherein the processor-executable instructions further cause the control system to perform a process that merges flow graphs from multiple engineering diagrams for the industrial plant to create a flow graph for the industrial plant.

### Claim 10 (depends on 1)

The control system of claim 1, wherein the processor-executable instructions further cause the control system to perform a process that displays the equipment, instruments, connectors and lines and the relationships between the equipment, instruments, connectors and lines in an asset hierarchy.

### Claim 11

A method of controlling an industrial plant, comprising:
inputting an engineering diagram for a unit of the industrial plant, the engineering diagram including symbols representing assets of the industrial plant;
extracting one or more assets from the engineering diagram using machine learning to recognize the one or more assets, the one or more assets including equipment, instruments, connectors, and lines, the lines relating the equipment, instruments, and connectors to one another;
determining one or more relationships between the equipment, instruments, connectors, and lines to one another using machine learning to recognize the one or more relationships; and
creating a flow graph from the equipment, instruments, connectors, and lines and the relationships between the equipment, instruments, connectors, and lines.

### Claim 12 (depends on 11)

The method of claim 11, wherein extracting one or more assets from the engineering diagram includes a performing geometry-based extraction process and a machine learning-based classification process.

### Claim 13 (depends on 11)

The method of claim 11, further comprising extracting one or more control loops from the engineering diagram based on one or more of the equipment, instruments, connectors, and lines.

### Claim 14 (depends on 11)

The method of claim 11, further comprising extracting a unit identifier from the engineering diagram, wherein the unit identifier uniquely identifies a particular unit from among multiple units in the industrial plant.

### Claim 15 (depends on 11)

The method of claim 11, further comprising extracting a drawing number and a revision number from the engineering diagram, the drawing number uniquely identifying the engineering diagram from among multiple engineering diagrams for the industrial plant and the revision number indicating a revision of the engineering diagram which is incremented whenever there are changes in the engineering diagram.

### Claim 16 (depends on 14)

The method of claim 14, further comprising assigning a unique identifier to each equipment, instrument, connector, and line of the engineering diagram using the unit identifier from the engineering diagram.

### Claim 17 (depends on 11)

The method of claim 11, wherein determining one or more relationships between the equipment, instruments, connectors, and lines includes generating a line-line graph, an equipment-line graph, a connector-line graph, and an instrument-line graph.

### Claim 18 (depends on 11)

The method of claim 11, wherein creating the flow graph for the engineering diagram includes merging the line-line graph, the equipment-line graph, the connector-line graph, and the instrument-line graph with one another.

### Claim 19 (depends on 17)

The method of claim 17, further comprising merging flow graphs from multiple engineering diagrams for the industrial plant to create a flow graph for the industrial plant.

### Claim 20 (depends on 11)

The method of claim 11, further comprising displaying the equipment, instruments, connectors and lines and the relationships between the equipment, instruments, connectors and lines in an asset hierarchy.

### Claim 21

(canceled)