MONITORING SYSTEM AND METHOD

• US 20080015816A1
• Filed: 09/28/2007
• Published: 01/17/2008
• Est. Priority Date: 09/30/2004
• Status: Active Grant

• Current Assignee: BL Technologies Inc. (Ashland Global Holdings, Inc.)
• Original Assignee: General Electric Company
• Inventors: Mahajanam, Rama, Babu, Ravi, Vora, Nishith, Jammu, Vinay
• Granted Patent: US 8,046,191 B2
• Time in Patent Office: Days
• US Class Current: 702/182
• CPC Class Codes: 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

Abstract

A system includes an analysis module and/or a prediction module. The analysis module receives data from a heat transfer device, and can compute a performance indicator indicative of an incipient anomaly condition of the heat transfer device based upon the received data, and/or can compute a normalized efficiency of the heat transfer device. The normalized efficiency represents a corrected efficiency that isolates effects of a process parameter on performance of the heat transfer device. The data represents a measurable process parameter or a change in a measurable process parameter in the heat transfer device. The prediction module receives the data and computes a performance indicator to predict performance degradation of the heat transfer device over time based upon the received data. Associated methods are provided.

Claims

1. A system, comprising:

an analysis module operable to receive data from a heat transfer device, and

to compute a performance indicator indicative of an incipient anomaly condition of the heat transfer device based upon the received data, or

to compute a normalized efficiency of the heat transfer device, wherein the normalized efficiency represents a corrected efficiency that isolates effects of one or more process parameters on performance of the heat transfer device;

wherein the data represents a measurable process parameter or a change in a measurable process parameter in the heat transfer device.

2. The system as defined in claim 1, wherein the system can isolate effects of one or more process parameters related to performance of the heat transfer device.

3. The system as defined in claim 1, wherein the system can provide incipient detection of an anomaly condition in a heat transfer device.

4. The system as defined in claim 1, further comprising an efficiency correction unit comprising:

at least one base load filter operable to remove effects of a varying load on the heat transfer device, wherein the varying load is configured to utilize an output from the heat transfer device to produce useful work;

at least one efficiency calculator operable to compute an initial efficiency of the heat transfer device, wherein the initial efficiency differs the normalized efficiency; and

at least one efficiency normalization unit operable to apply a normalization model to the data to compute the normalized efficiency for the heat transfer device based on the initial efficiency.

5. The system as defined in claim 4, wherein the efficiency correction unit comprises one or more stability filters operable to validate whether the data is sufficiently stable for application of the normalization model.

6. The system as defined in claim 4, wherein the efficiency calculator unit computes the initial efficiency based on an output-loss algorithm.

7. The system as defined in claim 1, wherein the measurable process parameter includes a pressure inside the heat transfer device, a temperature inside the heat transfer device, a mass flow rate of the fuel into the heat transfer device, a mass flow rate of air into the heat transfer device, a mass flow output of gas from the heat transfer device, a higher heating value of the fuel, or a higher heating value of the steam.

8. The system as defined in claim 1, further comprising a maintenance unit operable to introduce an anomaly reduction medium based on the normalized efficiency to at least one of the heat transfer device, a fuel for the heat transfer device, and a heat circulation medium in the heat transfer device.

9. The system as defined in claim 6, wherein the anomaly reduction medium provided via the maintenance unit to the heat transfer device includes at least one of deposit conditioning additives, combustion catalysts, or reflectivity modifiers.

10. The system as defined in claim 1, wherein the anomaly condition includes a fouling effect, a slagging effect, or a corrosive effect.

11. The system as defined in claim 1, further comprising a data logging unit capable of collecting data from the heat transfer device, wherein the data represents at least one measurable process parameter or changes in the measurable process parameter.

12. The system as defined in claim 1, further comprising a trend detection module in communication with the analysis module, and the trend detection module can detect the incipient anomaly condition in the heat transfer device based upon the performance indicator.

13. The system as defined in claim 12, wherein the incipient anomaly condition in the heat transfer device includes one or more of a fouling effect, a slagging effect, or a corrosive effect.

14. A system, comprising:

a prediction module operable to receive data from the heat transfer device and to compute a performance indicator to predict performance degradation of the heat transfer device over time based upon the received data, wherein the data represents a measurable process parameter or a change in a measurable process parameter in the heat transfer device, and thereby to predict a performance degradation over time of a heat transfer device.

15. The system as defined in claim 14, further comprising a trend detection module configured to detect the incipient anomaly condition in the heat transfer device based upon the a performance indicator.

16. The system as defined in claim 14, wherein the prediction module further predicts a time to failure of the heat transfer device based on the a performance indicator.

17. The system as defined in claim 14, wherein the measurable process parameter includes a pressure inside the heat transfer device, a temperature inside the heat transfer device, a mass flow rate of the fuel into the heat transfer device, a mass flow rate of air into the heat transfer device, a mass flow output of gas from the heat transfer device via a data logging unit, a higher heating value of the fuel, or a higher heating value of the steam.

18. The system as defined in claim 14, wherein the performance indicator is a mass flow rate of a fuel, a mass flow rate of a gas, an efficiency factor, an effectiveness factor, a gas pressure difference, an air pressure difference, or a temperature difference.

19. The system as defined in claim 14, wherein the anomaly condition in the heat transfer device includes a fouling effect, a slagging effect, or a corrosive effect.

20. A method, comprising:

diagnosing via a knowledge based network at least one probable cause of performance degradation of the heat transfer device based on at least one symptom indicating a change in performance of the heat transfer device;

analyzing via the knowledge based network the at least one probable cause of performance degradation in the heat transfer device to estimate a time to failure of the heat transfer device; and

validating via the knowledge based network the at least one probable cause based on at least a previous occurrence of the change in performance of the heat transfer device.

21. The method as defined in claim 20, comprising determining a detectability and an isolation capability for the probable cause of occurrence of the performance change based upon a cause and effect network.

22. The method as defined in claim 20, further comprising monitoring the at least one symptom at a plurality of locations on the heat transfer device.

23. A method, comprising:

obtaining data representing one or more measurable process parameters or a change in the one or more measurable process parameters of the heat transfer device;

calculating an initial efficiency of the heat transfer device based on the at least one or more measurable process parameters; and

applying a normalization model to the data to determine a normalized efficiency of the heat transfer device, wherein the normalized efficiency represents a corrected efficiency, different from the initial efficiency, that isolates the effects of the one or more process parameters of the heat transfer device.

24. The method as defined in claim 23, comprising mixing the anomaly reduction medium with a fuel for injection into the heat transfer device via the maintenance unit, or mixing the anomaly reduction medium to a liquid medium inside the heat transfer device.

25. A method, comprising:

providing data representing a measurable process parameter or a change in a measurable process parameter in a heat transfer device to an analysis module to compute a performance indicator or to an efficiency correction unit to calculate an initial efficiency;

detecting an anomaly condition in the heat transfer device via a trend detection module based upon the a performance indicator;

generating one or more prediction models based on an anomaly condition, and the prediction model provides one or more probable causes of failure;

detecting incipient failure of the heat transfer device via the one or more prediction models; and

providing an anomaly reduction medium to the heat transfer device based on the initial efficiency or on the incipient failure detection to reduce the effects of at least one of the anomaly conditions and thereby to defeat the failure mode.