Automatic remote monitoring and diagnostics system

• US 8,126,679 B2
• Filed: 03/17/2010
• Issued: 02/28/2012
• Est. Priority Date: 10/27/2005
• Status: Active Grant

• Current Assignee: GE Infrastructure Technology, LLC (General Electric Company)
• Original Assignee: General Electric Company
• Inventors: Jammu, Vinay Bhaskar, Graichen, Catherine Mary, Smolenski, Arnim, Morjaria, Mahesh Amritlal, De, Soumen, Bureau, Aurélie
• Primary Examiner(s): Khuu, Cindy H
• Application Number:
  US12/726,166
• Publication Number:
  US 20100235142A1
• Time in Patent Office: 713 Days
• Field of Search: 702/183
• US Class Current: 702/183
• CPC Class Codes: G05B 2219/33303 Expert system for diagnostic, monitoring use of tree and probability
• CPC Class Codes: G05B 23/0248 Causal models, e.g. fault tree; digraphs; qualitative physics
• CPC Class Codes: G05B 23/0278 Qualitative, e.g. if-then rules; Fuzzy logic; Lookup tables; Symptomatic search; FMEA

Abstract

A Monitoring and Diagnostics System is provided, which includes a monitoring unit and a monitored unit remotely located from the monitoring unit. The System also includes communication means between the monitoring unit and the monitored unit. The monitored unit includes data acquisition means for providing fault data of the monitored unit and the communication means are adapted to communicate the fault data from the monitored unit to the monitoring unit. The monitoring unit includes a rules engine having a set of expert rules for analyzing the information contained in the fault data and being adapted to deduce diagnostics information from the rules and from the information. In addition, a communication method for communicating between a first Programmable Logic Controller and a second Programmable Logic Controller or a central unit is provided, in which a description file is provided.

Claims

1. A Monitoring and Diagnostics System, comprising:

a monitored unit comprising a wind turbine including at least one sensor configured to measure fault data of said monitored unit;

a network; and

a monitoring unit coupled to said monitored unit via said network, said monitoring unit configured to receive the fault data via said network, said monitoring unit comprising a reasoning engine comprising a diagnostics knowledge, said reasoning engine configured to;

analyze the fault data and deduce diagnostics information from said diagnostics knowledge and based on the fault data;

provide suggestions for possible next steps to be undertaken based on the diagnostics information; and

determine and initiate a course of action to be taken on said monitored unit based on the information contained in the fault data.

2. A Monitoring and Diagnostics System according to claim 1 wherein the reasoning engine comprises at least one of the following elements:

Bayesian belief networks, causality engines, rules engines, causal trees, decision trees, classification trees, simulation engines, neural networks, and database comparisons.

3. A Monitoring and Diagnostics System according to claim 1 wherein said diagnostics knowledge comprises at least one of the following elements:

Bayesian graphs, procedures, sets of expert rules, causal or decision tree databases, and other databases.

4. A Monitoring and Diagnostics System according to claim 1 wherein said reasoning engine is adapted to analyze a cross-relation between a plurality of faults contained in the fault data.

5. A Monitoring and Diagnostics System according to claim 1 wherein said monitored unit further comprises a central unit configured to control said monitored unit.

6. A Monitoring and Diagnostics System according to claim 1, further comprising a database configured to store the fault data and the diagnostics information.

7. A Monitoring and Diagnostics System according to claim 1 wherein said reasoning engine is configured to update said diagnostics knowledge.

8. A Monitoring and Diagnostics System according to claim 1 wherein said monitored unit comprises a plurality of monitored units.

9. A Monitoring and Diagnostics System according to claim 1, further comprising an optional service database configured to store the initiated course of action and whether the course of action was successfully performed.

10. A Monitoring and Diagnostics System according to claim 1 wherein said monitoring unit is remotely located from said monitored unit.

11. A Monitoring and Diagnostics System according to claim 1 wherein one possible course of action to be taken is an automatic reset of the wind turbine.

12. A Monitoring and Diagnostics System according to claim 1 wherein the fault data is selectable by at least one of fault, fault type, monitored unit, and a cluster of monitored units.

13. A method for monitoring a unit using a Monitoring and Diagnostics System, said method comprising:

coupling a monitoring unit to a monitored unit via a network, the monitored unit comprising a wind turbine, the monitoring unit including a reasoning engine, the reasoning engine including a processor and diagnostics knowledge;

receiving, by the monitoring unit, fault data from the monitored unit via the network;

analyzing information contained in the fault data using the processor;

determining, by the reasoning engine, diagnostics information from the information using the diagnostics knowledge;

providing, by the reasoning engine, suggestions for possible next steps to be undertaken based on the diagnostics information; and

determining and initiating, by the reasoning engine, a course of action to be taken on the monitored unit based on the information contained in the fault data.

14. A monitoring unit, comprising:

a communication interface configured to receive fault data from a remotely located wind turbine via a communication means; and

a reasoning engine configured to;

analyze the fault data;

determine a remedial action to be taken on the wind turbine based on the information contained in the fault data; and

initiate the remedial action.

15. A monitoring unit according to claim 14 further comprising a parsing means configured to analyze the fault data and generate fault data values based on the fault data, said reasoning engine configured to analyze the fault data values.

16. A monitoring unit according to claim 14 wherein said reasoning engine is further configured to generate at least one suggested next step to be undertaken for the wind turbine based on the fault data.