System and method for asset fleet monitoring and predictive diagnostics using analytics for large and varied data sources

Patent metadata

Field	Value
Publication number	US-10503145-B2
Application number	US-201514871205-A
Country	US
Kind code	B2
Filing date	Sep 30, 2015
Priority date	Mar 25, 2015
Publication date	Dec 10, 2019
Grant date	Dec 10, 2019

Abstract

A method includes receiving information associated with operation of multiple pieces of industrial equipment at multiple sites. The multiple pieces of industrial equipment are of a same or similar type, and the information represents different types of data including operational data associated with the multiple pieces of industrial equipment and text-based data associated with the multiple pieces of industrial equipment. The method also includes analyzing the information to identify correlations in the information associated with one or more conditions involving the pieces of industrial equipment. The method further includes, based on the analyzing, generating one or more monitoring rules or routines to be used to identify the one or more conditions. The multiple pieces of industrial equipment could include machines with rotating components, machines with heat transfer equipment, or general process equipment.

First claim

What is claimed is:

1. A method for rule based monitoring of industrial equipment, the method comprising:
receiving information associated with the operation of multiple pieces of industrial equipment at one or more sites, the multiple pieces of industrial equipment being of a same or similar type, the information comprising different types of data including operational data associated with the multiple pieces of industrial equipment and text-based data associated with the multiple pieces of industrial equipment;
analyzing the information to identify normal behavior characteristics and abnormal behavior characteristics involving the pieces of industrial equipment, wherein the analysis of the information comprises:
clustering the information to identify normal or abnormal behavioral characteristics of the industrial equipment;
analyzing the information to identify faults and their potential causes, the probabilities of faults occurring, and the remaining lifetime of industrial equipment experiencing those faults;
performing text mining in order to identify root causes and corrective actions for the faults and to catalogue behavioral characteristics; and

generating one or more monitoring rules or routines based on the normal behavior characteristics and abnormal behavior characteristics;
deploying the generated one or more monitoring rules or routines to a monitoring system;
detecting by the monitoring system one or more conditions involving the pieces of industrial equipment violating the generated one or more monitoring rules or routines; and
transmitting a notification by the monitoring system, upon detecting a condition of the one or more conditions that indicates the abnormal behavior characteristics involving the pieces of industrial equipment, to a user device associated with the industrial equipment.

2. The method of claim 1 , further comprising:
receiving additional information comprising at least one of: (i) more information associated with the operation of the pieces of industrial equipment and (ii) information associated with operation of additional pieces of industrial equipment; and
generating one or more new or updated monitoring rules or routines using the additional information.

3. The method of claim 1 , wherein analyzing the information comprises performing statistical modeling augmented with at least one of: one or more physical first principles models and one or more semi-empirical models.

4. The method of claim 1 , wherein the multiple pieces of industrial equipment comprise at least one of: machines with rotating components, machines with heat transfer equipment, and general process equipment.

5. The method of claim 1 , wherein:
the operational data comprises real-time or time-stamped instrumentation data associated with the multiple pieces of industrial equipment; and
the text-based data comprises maintenance information associated with the multiple pieces of industrial equipment.

6. The method of claim 1 , wherein the information associated with the operation of the pieces of industrial equipment comprises information associated with historical operations of the pieces of industrial equipment.

7. The method of claim 1 , wherein the one or more conditions involving the pieces of industrial equipment comprise one or more faults with the pieces of industrial equipment.

8. An apparatus system comprising:
at least one interface configured to:
receive information associated with operation of multiple pieces of industrial equipment at one or more sites, the multiple pieces of industrial equipment being of a same or similar type, the information comprising different types of data including operational data associated with the multiple pieces of industrial equipment and text-based data associated with the multiple pieces of industrial equipment; and
at least one processing device configured to:
analyze the information to identify normal behavioral characteristics and abnormal behavioral characteristics correlations in the information associated with one or more conditions involving the pieces of industrial equipment wherein the analysis of the information comprises:
clustering the information to identify the normal behavioral characteristics and the abnormal behavioral characteristics of the pieces of industrial equipment;
processing the clustered information using machine learning to identify at least one of possible causes of the abnormal behavioral characteristics of the pieces of industrial equipment, and probabilities of a probability that the abnormal behavioral characteristics exist, and determining a life span of the pieces of industrial equipment with the abnormal behavioral characteristics;
performing text mining to identify root causes and solutions for the abnormal behavioral characteristics and catalogue the abnormal behavioral characteristics of the pieces of industrial equipment; and
based on the analysis, generate one or more monitoring rules or routines to be used to identify the one or more conditions based on the normal behavioral characteristics and abnormal behavioral characteristics;
deploy the generated one or more monitoring rules or routines to a monitoring system;
detect by the monitoring system one or more conditions involving the pieces of industrial equipment violating the generated one or more monitoring rules or routines; and
transmit a notification by the monitoring system, upon detecting a condition of the one or more conditions that indicates the abnormal behavioral characteristics involving the pieces of industrial equipment, to a user device associated with the industrial equipment.

9. The apparatus of claim 8 , wherein:
the at least one interface is further configured to receive additional information comprising at least one of: (i) more information associated with the operation of the pieces of industrial equipment and (ii) information associated with operation of additional pieces of industrial equipment; and
the at least one processing device is further configured to generate one or more new or updated monitoring rules or routines using the additional information.

10. The apparatus of claim 8 , wherein the at least one processing device is configured to analyze the information by performing statistical modeling augmented with at least one of: one or more physical first principles models and one or more semi-empirical models.

11. The apparatus of claim 8 , wherein:
the operational data comprises real-time or time-stamped instrumentation data associated with the multiple pieces of industrial equipment; and
the text-based data comprises maintenance information associated with the multiple pieces of industrial equipment.

12. The apparatus of claim 8 , wherein the one or more conditions involving the pieces of industrial equipment comprise at least one of:
one or more user-defined conditions involving the pieces of industrial equipment; and
one or more faults with the pieces of industrial equipment.

13. A non-transitory computer readable medium containing computer readable program code that when executed causes at least one processing device to:
obtain information associated with operation of multiple pieces of industrial equipment at one or more sites, the multiple pieces of industrial equipment being of a same or similar type, the information comprising different types of data including operational data associated with the multiple pieces of industrial equipment and text-based data associated with the multiple pieces of industrial equipment;
analyze the information to identify correlations in the information associated with one or more conditions of normal behavioral ch

Assignees

• Honeywell Int Inc

Inventors

• Germann David J
• Stewart Gregory E
• Light Marc
• Mylaraswamy Dinkar

Classifications

• G05B2219/34427

  Diagnostic, monitoring incorporated in controller · CPC title

• G05B23/0216

  Human interface functionality, e.g. monitoring system providing help to the user in the selection of tests or in its configuration · CPC title

• G05B19/4065 Primary

  Monitoring tool breakage, life or condition · CPC title

• B23K11/00

  Resistance welding; Severing by resistance heating · CPC title

• G05B23/0243 Primary

  model based detection method, e.g. first-principles knowledge model · CPC title