DATA ACQUISITION SYSTEM FOR CONDITION-BASED MAINTENANCE

• US 20120065901A1
• Filed: 11/21/2011
• Published: 03/15/2012
• Est. Priority Date: 11/16/2009
• Status: Active Grant

• Current Assignee: Simmonds Precision Products, Inc. (Raytheon Technologies Corporation d/b/a RTX)
• Original Assignee: NRG System Inc
• Inventors: Bechhoefer, Eric R., Taylor, John T.
• Granted Patent: US 8,442,778 B2
• Time in Patent Office: Days
• US Class Current: 702/34
• CPC Class Codes: F03D 17/00 Monitoring or testing of wind motors, e.g. diagnostics testing during commissioning of wind motors F03D13/30
• CPC Class Codes: F03D 7/047 characterised by the controller architecture, e.g. multiple processors or data communications
• CPC Class Codes: F05B 2240/96 as part of a wind turbine farm
• CPC Class Codes: F05B 2270/326 Rotor angle
• CPC Class Codes: F05B 2270/332 Maximum loads or fatigue criteria
• CPC Class Codes: F05B 2270/803 Sampling thereof
• CPC Class Codes: G01M 13/00 Testing of machine parts
• CPC Class Codes: G05B 23/0283 Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL] preventive maintenance, i.e. planning maintenance according to the available resources without monitoring the system G06Q10/06
• CPC Class Codes: Y02E 10/72 Wind turbines with rotation axis in wind direction
• CPC Class Codes: Y02P 80/20 using renewable energy

Abstract

Generally, a system and method consistent with the present disclosure may provide a relatively low cost, relatively robust data acquisition and analysis system useful for condition-based maintenance. The system may be useful for condition-based maintenance in industrial applications, e.g., of equipment and/or machinery. The industrial monitoring system may be used, for example, to monitor a condition of rotating machinery, e.g., a wind turbine. The system and method may include data analysis that may be useful for anticipating a need for maintenance, repair and/or replacement of one or more components.

Claims

1. A method of determining an estimate of a remaining useful life of a monitored component of a wind turbine, the method comprising:

detecting a parameter associated with a condition of the monitored component of the wind turbine using a sensor coupled to the monitored component of the wind turbine and providing sensor output data to a module based at least in part on the parameter;

generating module output data based at least in part on the sensor output data;

providing the module output data to a server, and

estimating the remaining useful life of the monitored component of the wind turbine based at least in part on a representation of the condition of the monitored component of the wind turbine.

2. The method according to claim 1, further comprising analyzing the sensor output data to generate the representation of the condition of the monitored component of the wind turbine.

3. The method according to claim 2, wherein the analyzing is performed by the module.

4. The method according to claim 2, wherein the analyzing comprises performing a transform to determine a frequency spectrum based on the sensor output data, the frequency spectrum associated with the condition of the wind turbine.

5. The method according to claim 4 further comprising determining statistics based, at least in part, on the frequency spectrum, wherein the statistics are associated with the condition of the monitored component of the wind turbine.

6. The method according to claim 2, wherein the analyzing comprises determining a vector of average sensor output data for a time period corresponding to a revolution of a component of the wind turbine.

7. The method according to claim 6, further comprising determining statistics, based, at least in part, on the vector of average sensor output data.

8. The method according to claim 2, further comprising determining a condition indicator, wherein the condition indicator corresponds to a probability distribution of the detected parameter for a sample of components of known good wind turbines.

9. The method according to claim 8, further comprising determining a health indicator based, at least in part, on at least one condition indicator, wherein the health indicator represents a current condition of the monitored component.

10. The method according to claim 9, further comprising scaling the health indicator so that a threshold indicating no longer good corresponds to a common reference of health indicators of other monitored components of the wind turbine.

11. A data acquisition system comprising:

a plurality of sensors, each sensor configured to detect a plurality of parameters associated with a condition of a respective component of a wind turbine and to proved processed sensor data based at least in part on those parameters;

a plurality of modules, each module coupled to at least one sensor and configured to research the sensor data from at least one sensor and to generate module output data based at least in part of the received sensor data;

a data bus configured to couple the plurality of modules to a server to provide the current component health and an estimate of the remaining useful life of a selected component of the wind turbine to a user based at least in part on a representation of the condition of the selected component of the wind turbine.

12. The data acquisition system according to claim 11, wherein one sensor is a tachometer configured to detect a rotational speed of a component of the wind turbine and at least one sensor is an accelerometer configured to detect vibration.

13. The data acquisition system according to claim 11, wherein the selected component of the wind turbine is a shaft, a bearing or a gear.

14. The data acquisition system according to claim 11, wherein the data bus is a daisy chain and each module is connected to at most two other modules.

15. The data acquisition system according to claim 11, wherein the data bus is configured to carry power from the local data concentrator to the modules.

16. The data acquisition system according to claim 11, wherein at least one of the plurality of modules comprises a controller configured to perform floating point calculations in hardware.

17. The data acquisition system according to claim 11, wherein the researching comprises performing a transform to determine a frequency spectrum based on received sensor data, the frequency spectrum associated with the condition of the wind turbine.