WO2014098802A1 - Limit based threshold estimation for prognostics and health management - Google Patents

Limit based threshold estimation for prognostics and health management Download PDF

Info

Publication number
WO2014098802A1
WO2014098802A1 PCT/US2012/070287 US2012070287W WO2014098802A1 WO 2014098802 A1 WO2014098802 A1 WO 2014098802A1 US 2012070287 W US2012070287 W US 2012070287W WO 2014098802 A1 WO2014098802 A1 WO 2014098802A1
Authority
WO
WIPO (PCT)
Prior art keywords
operational parameter
determined
action
modified
action index
Prior art date
Application number
PCT/US2012/070287
Other languages
French (fr)
Inventor
Sitaram Ramaswamy
Mothivel MUMMUDI
Original Assignee
United Technologies Corporation
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by United Technologies Corporation filed Critical United Technologies Corporation
Priority to EP12890240.0A priority Critical patent/EP2954580B1/en
Priority to CN201280077631.2A priority patent/CN104854747B/en
Priority to JP2015549324A priority patent/JP6197047B2/en
Priority to KR1020157018979A priority patent/KR101978018B1/en
Priority to PCT/US2012/070287 priority patent/WO2014098802A1/en
Priority to US14/651,181 priority patent/US10126209B2/en
Publication of WO2014098802A1 publication Critical patent/WO2014098802A1/en

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01MTESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M99/00Subject matter not provided for in other groups of this subclass
    • G01M99/008Subject matter not provided for in other groups of this subclass by doing functionality tests
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00Testing or monitoring of control systems or parts thereof
    • G05B23/02Electric testing or monitoring
    • G05B23/0205Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0224Process history based detection method, e.g. whereby history implies the availability of large amounts of data
    • G05B23/0227Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions
    • G05B23/0235Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions based on a comparison with predetermined threshold or range, e.g. "classical methods", carried out during normal operation; threshold adaptation or choice; when or how to compare with the threshold
    • HELECTRICITY
    • H01ELECTRIC ELEMENTS
    • H01MPROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00Fuel cells; Manufacture thereof
    • H01M8/04Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298Processes for controlling fuel cells or fuel cell systems
    • HELECTRICITY
    • H01ELECTRIC ELEMENTS
    • H01MPROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00Fuel cells; Manufacture thereof
    • H01M8/04Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298Processes for controlling fuel cells or fuel cell systems
    • H01M8/04305Modeling, demonstration models of fuel cells, e.g. for training purposes
    • HELECTRICITY
    • H01ELECTRIC ELEMENTS
    • H01MPROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00Fuel cells; Manufacture thereof
    • H01M8/04Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298Processes for controlling fuel cells or fuel cell systems
    • H01M8/04992Processes for controlling fuel cells or fuel cell systems characterised by the implementation of mathematical or computational algorithms, e.g. feedback control loops, fuzzy logic, neural networks or artificial intelligence
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00Program-control systems
    • G05B2219/20Pc systems
    • G05B2219/26Pc applications
    • G05B2219/2668Fuel cells
    • HELECTRICITY
    • H01ELECTRIC ELEMENTS
    • H01MPROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00Fuel cells; Manufacture thereof
    • H01M8/04Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298Processes for controlling fuel cells or fuel cell systems
    • H01M8/04313Processes for controlling fuel cells or fuel cell systems characterised by the detection or assessment of variables; characterised by the detection or assessment of failure or abnormal function
    • H01M8/0432Temperature; Ambient temperature
    • HELECTRICITY
    • H01ELECTRIC ELEMENTS
    • H01MPROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00Fuel cells; Manufacture thereof
    • H01M8/04Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298Processes for controlling fuel cells or fuel cell systems
    • H01M8/04313Processes for controlling fuel cells or fuel cell systems characterised by the detection or assessment of variables; characterised by the detection or assessment of failure or abnormal function
    • H01M8/04537Electric variables
    • H01M8/04544Voltage
    • HELECTRICITY
    • H01ELECTRIC ELEMENTS
    • H01MPROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00Fuel cells; Manufacture thereof
    • H01M8/04Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298Processes for controlling fuel cells or fuel cell systems
    • H01M8/04313Processes for controlling fuel cells or fuel cell systems characterised by the detection or assessment of variables; characterised by the detection or assessment of failure or abnormal function
    • H01M8/04537Electric variables
    • H01M8/04574Current
    • HELECTRICITY
    • H01ELECTRIC ELEMENTS
    • H01MPROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00Fuel cells; Manufacture thereof
    • H01M8/04Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298Processes for controlling fuel cells or fuel cell systems
    • H01M8/04694Processes for controlling fuel cells or fuel cell systems characterised by variables to be controlled
    • H01M8/04955Shut-off or shut-down of fuel cells
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/30Hydrogen technology
    • Y02E60/50Fuel cells

Definitions

  • a method of monitoring the operation of a device includes determining a plurality of operational parameters that are indicative of an operation condition of the device. A difference between each operational parameter and a corresponding limit on that parameter is determined. Each limit indicates a value of the corresponding operational parameter that corresponds to an undesirable operation condition of the device. An action index is determined based on at least a smallest one of the determined differences. A determination is made whether the action index is within a range corresponding to desirable operation of the device.
  • a system for monitoring device operation includes a plurality of detectors that provide respective indications of operational parameters that are indicative of an operation condition of the device.
  • the system includes a processor that is configured to determine a difference between each operational parameter and a corresponding limit on that parameter. Each of the limits indicates a value of the corresponding operational parameter that corresponds to an undesirable operation condition of the device.
  • the processor is configured to determine an action index based on at least a smallest one of the determined differences.
  • the processor is configured to determine whether the action index is within a range corresponding to desirable operation of the device.
  • Figure 1 schematically illustrates a system for monitoring operation of an example device.
  • Figure 2 is a flowchart diagram summarizing an example approach.
  • Figure 3 graphically illustrates a relationship between an action index and the shutdown limits related to the action index.
  • FIG. 1 schematically illustrates a system 20 for monitoring operation of a device 30.
  • the device 30 comprises a fuel cell power plant. Selected portions of an example fuel cell power plant are illustrated for discussion purposes.
  • a cell stack assembly (CSA) 32 contains a plurality of fuel cells that generate electrical power in a known manner.
  • a source of fuel 34 supplies the CSA 32.
  • a coolant assembly 36 selectively provides coolant for controlling a temperature of the CSA in a known manner.
  • the system 20 for monitoring operation of the device 30 includes a plurality of sensors or detectors that are situated for detecting a plurality of operational parameters that provide an indication regarding the operation condition of the device 30.
  • a temperature sensor 40 provides an indication of a temperature of exhaust from the CSA 32.
  • Another detector 42 provides an indication of a voltage or temperature within the CSA 32.
  • Another detector 44 provides an indication regarding the content or amount of fuel provided by the fuel supply system 34 to the CSA 32.
  • Another detector 46 provides information regarding the coolant system 36 such as information regarding a temperature of the coolant or a concentration of a particular component within the coolant.
  • Another detector 48 provides an indication of coolant temperature exiting the CSA 32.
  • a processor 50 collects information from the detectors 40-48 for monitoring the operating condition of the device 30. Based on determinations made by the processor 50, an output is provided to a user through a user interface 52.
  • the output may be a visible or audible alarm or some indication that there is reason to adjust or shutdown operation of the device 30.
  • the output provided by the user interface 52 may be customized to meet the needs of a particular situation.
  • Figure 2 includes a flowchart diagram 60 that summarizes an example approach for monitoring an operating condition of the device 30 in Figure 1.
  • a plurality of operational parameters are determined. This occurs by gathering information from the detectors 40-48 and processing them within the processor 50 to place the detector information into a usable form.
  • a determination is made regarding the distance between each operational parameter and a corresponding limit. In one example, the distance is determined as the Euclidean distance between the operational parameter value indicated by the corresponding detector and a limit that is determined for that particular parameter. In the case of a fuel cell as the example device 30, there are limits on temperature of various components within the device 30.
  • Acceptable limits on temperature are determined based on known information regarding acceptable operation parameters to ensure proper operation of the device 30 and to facilitate achieving a desired lifetime for the device. Given a particular device 30, the particular limits on the operational parameters at issue will either be known or can be determined to meet the needs of a particular situation.
  • One way in which the disclosed example departs from previous PHM techniques is that the difference or distance between an operational parameter and a limit on that parameter is determined instead of determining how much an observed operation parameter differs from a base line or expected value for that parameter.
  • taking into account the distance or difference between the operational parameters and their corresponding limits allows for obtaining an early warning of a condition that may lead to a desire or need to shutdown operation of the device 30.
  • Obtaining an early warning allows for being more proactive in addressing a condition of a device 30 before having to shut it down, for example.
  • Another feature of taking the approach of the disclosed example is that it allows for being more lenient in setting thresholds that place limits on operational parameters.
  • the processor 50 determines which of those distances is the smallest. In other words, the processor 50 identifies which of the operational parameters is closest to the limit on that parameter.
  • an action index is determined based at least on the smallest one of the determined distances.
  • the action index comprises a shutdown index.
  • the action index provides information regarding taking action to shut down the device.
  • action indices such as a coolant replacement index, a recharge index, a fuel adjustment index, among many others.
  • a shutdown index is used for an example for discussion purposes.
  • the action index is determined based upon modified observation values.
  • Each of the observed operation parameters is modified by combining the observed operational parameter value and a weighted Euclidean distance between that value and the corresponding limit.
  • the Euclidean distance for each operational parameter is multiplied by a weight and then combined with the observed parameter value.
  • the weighted Euclidean distance is added to the observed operational parameter value to obtain the modified value.
  • Determining the smallest of the distances between the operational parameters and their corresponding limits is useful for setting the weighting of the distances for purposes of obtaining modified operational parameter values.
  • the smallest distance is weighted the most significantly. That way, when the modified operational parameter values are used for determining the action index, the one that is closest to its corresponding limit has the most significant impact on the action index.
  • the Euclidean distance that is the smallest of the determined distances receives a weight of approximately one and all other Euclidean distances are weighted with a factor of zero.
  • the action index is computed in one example using the following relationship
  • (x SD - x) is a vector matrix of distances between the modified observation values and the corresponding limits on those values
  • P is a principle component vector matrix containing the normal or expected operation values for each operational parameter
  • is a diagonal matrix of principle component Eigen values
  • P T is a transpose of the principle component vector matrix
  • (x SD - x) T is a transpose of the vector matrix of the distances between the modified operational parameter values and the corresponding limits on those operation parameters.
  • the matrix multiplication operation enabled by the P ⁇ P T term in the equation serves to project the "x" vector onto the principal component subspace. It appropriately rotates and rescales the "x" vector in order to calculate a appropriately scaled action index consistent with the selection of the P principle components. In the absence of such scaling, the risk of multiple false alarms is significantly higher.
  • an appropriate lower limit is placed on the action index. For example, if the index has a value less than 0.1, that is an indication that some action should be taken based upon the current operating condition of the device 30.
  • the action index is a shutdown index
  • the action index has a value that is less than 0.1
  • the user interface 52 provides an indication indicating that the device 30 should be shutdown in one example.
  • the processor 50 automatically shuts down the device 30 and the user interface 52 provides an indication that shutdown has occurred.
  • the user interface 52 may also provide information regarding the operational parameter value, the action index value or a combination of them and any other information that would be useful to an individual for troubleshooting operation of the device 30, for example.
  • FIG. 3 schematically shows the upper and lower limit of the action index value.
  • the dashed line 70 indicates the higher action index limit (HAIL) and the solid line 72 indicates the lower action index limit (LAIL).
  • a plurality of index values based on system performance are shown at 74. As long as the action index calculated is outside of the HAIL and LAIL limits, the system is judged as being in control. The actual values of the HAIL and LAIL are determined based on the balance between risk and false alarms associated with the system. Additionally, an escalating alert strategy might be employed depending on how closely the actual action index comes to HAIL and LAIL limits. Note that in this case, the action index value of 0 signifies arrival at the shutdown limit.

Landscapes

  • Engineering & Computer Science (AREA)
  • Electrochemistry (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • General Chemical & Material Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Manufacturing & Machinery (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Chemical & Material Sciences (AREA)
  • Automation & Control Theory (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Fuzzy Systems (AREA)
  • Artificial Intelligence (AREA)
  • Computing Systems (AREA)
  • Evolutionary Computation (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Testing And Monitoring For Control Systems (AREA)
  • Fuel Cell (AREA)
  • Alarm Systems (AREA)

Abstract

According to an embodiment, a method of monitoring the operation of a device includes determining a plurality of operational parameters that are indicative of an operation condition of the device. A difference between each operational parameter and a corresponding limit on that parameter is determined. Each limit indicates a value of the corresponding operational parameter that corresponds to an undesirable operation condition of the device. An action index is determined based on at least a smallest one of the determined differences. A determination is made whether the action index is within a range corresponding to desirable operation of the device.

Description

LIMIT BASED THRESHOLD ESTIMATION FOR
PROGNOSTICS AND HEALTH MANAGEMENT
BACKGROUND
[oooi] A variety of complex device are in widespread use today. Many of those devices have various operating parameters that indicate whether the device is functioning properly or if there may be a problem with the operation of the device. For example, fuel cell systems have specified threshold limits for certain performance variables. For example, there are temperature limits for various portions of a fuel cell system during acceptable operating conditions. There are also limits on output voltage or current for many fuel cell systems.
[0002] Significant study has been devoted to prognostics and health management (PHM) and principle component analysis (PCA) for detecting when a device is operating under conditions that depart from an expected or desired operating state. One limitation on such approaches is that the analysis is done with respect to the normal or baseline operation of the device instead of basing the analysis on threshold limits on the operating parameters.
SUMMARY
[0003] According to an embodiment, a method of monitoring the operation of a device includes determining a plurality of operational parameters that are indicative of an operation condition of the device. A difference between each operational parameter and a corresponding limit on that parameter is determined. Each limit indicates a value of the corresponding operational parameter that corresponds to an undesirable operation condition of the device. An action index is determined based on at least a smallest one of the determined differences. A determination is made whether the action index is within a range corresponding to desirable operation of the device.
[000 ] According to an embodiment, a system for monitoring device operation includes a plurality of detectors that provide respective indications of operational parameters that are indicative of an operation condition of the device. The system includes a processor that is configured to determine a difference between each operational parameter and a corresponding limit on that parameter. Each of the limits indicates a value of the corresponding operational parameter that corresponds to an undesirable operation condition of the device. The processor is configured to determine an action index based on at least a smallest one of the determined differences. The processor is configured to determine whether the action index is within a range corresponding to desirable operation of the device.
[0005] The various features and advantages of a disclosed example embodiment will become apparent to those skilled in the art from the following detailed description. The drawings that accompany the detailed description can be briefly described as follows. BRIEF DESCRIPTION OF THE DRAWINGS
[0006] Figure 1 schematically illustrates a system for monitoring operation of an example device.
[0007] Figure 2 is a flowchart diagram summarizing an example approach.
[0008] Figure 3 graphically illustrates a relationship between an action index and the shutdown limits related to the action index.
DETAILED DESCRIPTION
[0009] Figure 1 schematically illustrates a system 20 for monitoring operation of a device 30. The disclosed system and method of this description is not necessarily limited to any particular device 30. In the illustrated example, the device 30 comprises a fuel cell power plant. Selected portions of an example fuel cell power plant are illustrated for discussion purposes. A cell stack assembly (CSA) 32 contains a plurality of fuel cells that generate electrical power in a known manner. A source of fuel 34 supplies the CSA 32. A coolant assembly 36 selectively provides coolant for controlling a temperature of the CSA in a known manner.
[oooio] The system 20 for monitoring operation of the device 30 includes a plurality of sensors or detectors that are situated for detecting a plurality of operational parameters that provide an indication regarding the operation condition of the device 30. In the illustrated example, a temperature sensor 40 provides an indication of a temperature of exhaust from the CSA 32. Another detector 42 provides an indication of a voltage or temperature within the CSA 32. Another detector 44 provides an indication regarding the content or amount of fuel provided by the fuel supply system 34 to the CSA 32. Another detector 46 provides information regarding the coolant system 36 such as information regarding a temperature of the coolant or a concentration of a particular component within the coolant. Another detector 48 provides an indication of coolant temperature exiting the CSA 32.
[oooii] Given this description, those skilled in the art who are dealing with a particular device of interest will be able to configure a set of detectors to provide the necessary operational parameter information for monitoring the operating condition of the device with which they are dealing. The illustrated detectors are provided for discussion purposes. The disclosed example embodiment is not necessarily limited to any particular device or any particular arrangement of detectors.
[00012] A processor 50 collects information from the detectors 40-48 for monitoring the operating condition of the device 30. Based on determinations made by the processor 50, an output is provided to a user through a user interface 52. The output may be a visible or audible alarm or some indication that there is reason to adjust or shutdown operation of the device 30. Depending on the particular device and the conditions that are being monitored, the output provided by the user interface 52 may be customized to meet the needs of a particular situation.
[00013] Figure 2 includes a flowchart diagram 60 that summarizes an example approach for monitoring an operating condition of the device 30 in Figure 1. At 62, a plurality of operational parameters are determined. This occurs by gathering information from the detectors 40-48 and processing them within the processor 50 to place the detector information into a usable form. At 64, a determination is made regarding the distance between each operational parameter and a corresponding limit. In one example, the distance is determined as the Euclidean distance between the operational parameter value indicated by the corresponding detector and a limit that is determined for that particular parameter. In the case of a fuel cell as the example device 30, there are limits on temperature of various components within the device 30. Acceptable limits on temperature are determined based on known information regarding acceptable operation parameters to ensure proper operation of the device 30 and to facilitate achieving a desired lifetime for the device. Given a particular device 30, the particular limits on the operational parameters at issue will either be known or can be determined to meet the needs of a particular situation.
[0001 ] One way in which the disclosed example departs from previous PHM techniques is that the difference or distance between an operational parameter and a limit on that parameter is determined instead of determining how much an observed operation parameter differs from a base line or expected value for that parameter. With the disclosed example, taking into account the distance or difference between the operational parameters and their corresponding limits allows for obtaining an early warning of a condition that may lead to a desire or need to shutdown operation of the device 30. Obtaining an early warning allows for being more proactive in addressing a condition of a device 30 before having to shut it down, for example. Another feature of taking the approach of the disclosed example is that it allows for being more lenient in setting thresholds that place limits on operational parameters. For situations in which a device would be shut down when a limit on a particular parameter is met, those limits must be strictly set to avoid catastrophic failure of the device. Taking the approach of the disclosed example and obtaining an early warning of an operational parameter approaching a limit on that parameter provides more leeway in setting a threshold as it becomes possible to address an operating condition of the device before an absolute threshold on that particular is met.
[00015] Once the distance between each operational parameter and its corresponding limit has been determined, the processor 50 determines which of those distances is the smallest. In other words, the processor 50 identifies which of the operational parameters is closest to the limit on that parameter.
[00016] At 66, an action index is determined based at least on the smallest one of the determined distances. In one example, the action index comprises a shutdown index. For a situation in which device operation is monitored for purposes of shutting down the device to avoid failure, the action index provides information regarding taking action to shut down the device. There are other possible action indices such as a coolant replacement index, a recharge index, a fuel adjustment index, among many others. A shutdown index is used for an example for discussion purposes.
[00017] In one example, the action index is determined based upon modified observation values. Each of the observed operation parameters is modified by combining the observed operational parameter value and a weighted Euclidean distance between that value and the corresponding limit. In other words, the Euclidean distance for each operational parameter is multiplied by a weight and then combined with the observed parameter value. In one example, the weighted Euclidean distance is added to the observed operational parameter value to obtain the modified value.
[00018] Determining the smallest of the distances between the operational parameters and their corresponding limits is useful for setting the weighting of the distances for purposes of obtaining modified operational parameter values. In one example, the smallest distance is weighted the most significantly. That way, when the modified operational parameter values are used for determining the action index, the one that is closest to its corresponding limit has the most significant impact on the action index.
[00019] In one example, the Euclidean distance that is the smallest of the determined distances receives a weight of approximately one and all other Euclidean distances are weighted with a factor of zero.
[00020] The action index is computed in one example using the following relationship
action index = (xSD - x) P λ PT (xSD - x)T
[00021] wherein (xSD - x) is a vector matrix of distances between the modified observation values and the corresponding limits on those values; P is a principle component vector matrix containing the normal or expected operation values for each operational parameter; λ is a diagonal matrix of principle component Eigen values; PT is a transpose of the principle component vector matrix; and (xSD - x)T is a transpose of the vector matrix of the distances between the modified operational parameter values and the corresponding limits on those operation parameters. Further definition of the meaning of P and the topic of principal component analysis approaches can be found in Fault detection and diagnosis in industrial systems, ISBN 1-85233-327-8.
[00022] The matrix multiplication operation enabled by the P λ PT term in the equation serves to project the "x" vector onto the principal component subspace. It appropriately rotates and rescales the "x" vector in order to calculate a appropriately scaled action index consistent with the selection of the P principle components. In the absence of such scaling, the risk of multiple false alarms is significantly higher.
[00023] In Figure 2, at 68 a determination is made whether the action index is within an acceptable range. In one example, an appropriate lower limit is placed on the action index. For example, if the index has a value less than 0.1, that is an indication that some action should be taken based upon the current operating condition of the device 30. In an example where the action index is a shutdown index, when the action index has a value that is less than 0.1, that is an indication that the device 30 should be shutdown. The user interface 52 provides an indication indicating that the device 30 should be shutdown in one example. In another example, the processor 50 automatically shuts down the device 30 and the user interface 52 provides an indication that shutdown has occurred. The user interface 52 may also provide information regarding the operational parameter value, the action index value or a combination of them and any other information that would be useful to an individual for troubleshooting operation of the device 30, for example.
[0002 ] Figure 3 schematically shows the upper and lower limit of the action index value. The dashed line 70 indicates the higher action index limit (HAIL) and the solid line 72 indicates the lower action index limit (LAIL). A plurality of index values based on system performance are shown at 74. As long as the action index calculated is outside of the HAIL and LAIL limits, the system is judged as being in control. The actual values of the HAIL and LAIL are determined based on the balance between risk and false alarms associated with the system. Additionally, an escalating alert strategy might be employed depending on how closely the actual action index comes to HAIL and LAIL limits. Note that in this case, the action index value of 0 signifies arrival at the shutdown limit.
[00025] The preceding description is exemplary rather than limiting in nature.
Variations and modifications to the disclosed examples may become apparent to those skilled in the art that do not necessarily depart from the essence of this invention. The scope of legal protection given to this invention can only be determined by studying the following claims.

Claims

CLAIMS We claim:
1. A method of monitoring the operation of a device, comprising the steps of:
(A) determining a plurality of operational parameters that are indicative of an operation condition of the device;
(B) determining a difference between each determined operational parameter and a corresponding limit on the operational parameter, each limit indicating a value of the corresponding operational parameter that corresponds to an undesirable operation condition of the device;
(C) determining an action index based on at least a smallest one of the determined differences; and
(D) determining whether the action index is within a range corresponding to desirable operation of the device.
2. The method of claim 1, wherein step (B) comprises
determining a Euclidean distance of each determined operational parameter from the corresponding limit; and
wherein the determined Euclidean distance is the determined difference.
3. The method of claim 2, comprising determining the Euclidean distance squared for each determined operational parameter.
4. The method of claim 2, wherein step (C) comprises
establishing a modified operational parameter for at least the operational parameter having the smallest determined difference by adding a weighted version of the determined distance for the operational parameter to the determined operational parameter;
determining a modified difference between the established modified operational parameter and the corresponding limit.
5. The method of claim 4, wherein step (C) comprises
determining a modified difference for each of the determined operational parameters; and
establishing a matrix of the modified differences.
6. The method of claim 5, wherein step (C) comprises
determining the action index by multiplying
the matrix of the modified difference by
a principal component vector matrix by
a diagonal matrix of principal component Eigen values by
a transpose of the principal component vector matrix by
a transpose of the matrix of the modified differences,
wherein the principal component vector matrix includes predetermined operational parameter values corresponding to desirable operation of the device.
7. The method of claim 6, wherein the action index comprises a shutdown index indicative of a need to take action to shutdown operation of the device.
8. The method of claim 6, wherein
step (D) comprises establishing a lower limit on an acceptable value for the action index and
the method comprises providing an indication that action should be taken when the action index has a value less than the lower limit.
9. The method of claim 1, wherein
step (D) comprises establishing a lower limit on an acceptable value for the action index and
the method comprises providing an indication that action should be taken when the action index has a value less than the lower limit.
10. A system for monitoring device operation, comprising:
a plurality of detectors that provide respective indications of operational parameters that are indicative of an operation condition of the device; and
a processor configured to
determine a difference between each determined operational parameter and a corresponding limit on the operational parameter, each limit indicating a value of the corresponding operational parameter that corresponds to an undesirable operation condition of the device;
determine an action index based on at least a smallest one of the determined differences; and
determine whether the action index is within a range corresponding to desirable operation of the device.
11. The system of claim 10, wherein the processor is configured to determine a Euclidean distance of each determined operational parameter from the corresponding limit and wherein the determined Euclidean distance is the determined difference.
12. The system of claim 11, wherein the processor is configured to determine the Euclidean distance squared for each determined operational parameter.
13. The system of claim 11, wherein the processor is configured to
establish a modified operational parameter for at least the operational parameter having the smallest determined difference by adding a weighted version of the determined distance for the operational parameter to the determined operational parameter; and
determine a modified difference between the established modified operational parameter and the corresponding limit.
14. The system of claim 13, wherein the processor is configured to
determine a modified difference for each of the determined operational parameters; and
establish a matrix of the modified differences.
15. The system of claim 14, wherein the processor is configured to determine the action index by multiplying
the matrix of the modified difference by
a principal component vector matrix by
a diagonal matrix of principal component Eigen values by
a transpose of the principal component vector matrix by
a transpose of the matrix of the modified differences,
wherein the principal component vector matrix includes predetermined operational parameter values corresponding to desirable operation of the device.
16. The system of claim 15, wherein the action index comprises a shutdown index indicative of a need to take action to shutdown operation of the device.
17. The system of claim 16, wherein the processor is
provided with a lower limit on an acceptable value for the action index; and configured to provide an indication that action should be taken when the action index has a value less than the lower limit.
18. The system of claim 17, comprising a user interface that provides information corresponding to the processor indication, the information being provided in at least one of an audible or visible format.
19. The system of claim 10, wherein the processor is
provided with a lower limit on an acceptable value for the action index; and configured to provide an indication that action should be taken when the action index has a value less than the lower limit.
PCT/US2012/070287 2012-12-18 2012-12-18 Limit based threshold estimation for prognostics and health management WO2014098802A1 (en)

Priority Applications (6)

Application Number Priority Date Filing Date Title
EP12890240.0A EP2954580B1 (en) 2012-12-18 2012-12-18 Limit based threshold estimation for prognostics and health management
CN201280077631.2A CN104854747B (en) 2012-12-18 2012-12-18 For omen and the threshold estimation based on the limit of health control
JP2015549324A JP6197047B2 (en) 2012-12-18 2012-12-18 Threshold estimation based on constraints for prediction and health management
KR1020157018979A KR101978018B1 (en) 2012-12-18 2012-12-18 Limit based threshold estimation for prognostics and health management
PCT/US2012/070287 WO2014098802A1 (en) 2012-12-18 2012-12-18 Limit based threshold estimation for prognostics and health management
US14/651,181 US10126209B2 (en) 2012-12-18 2012-12-18 Limit based threshold estimation for prognostics and health management

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/US2012/070287 WO2014098802A1 (en) 2012-12-18 2012-12-18 Limit based threshold estimation for prognostics and health management

Publications (1)

Publication Number Publication Date
WO2014098802A1 true WO2014098802A1 (en) 2014-06-26

Family

ID=50978918

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2012/070287 WO2014098802A1 (en) 2012-12-18 2012-12-18 Limit based threshold estimation for prognostics and health management

Country Status (6)

Country Link
US (1) US10126209B2 (en)
EP (1) EP2954580B1 (en)
JP (1) JP6197047B2 (en)
KR (1) KR101978018B1 (en)
CN (1) CN104854747B (en)
WO (1) WO2014098802A1 (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016059203A1 (en) * 2014-10-17 2016-04-21 Stiftelsen Sintef Control of an electrochemical device with integrated diagnostics, prognostics and lifetime management

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105278526B (en) * 2015-11-19 2017-12-01 东北大学 A kind of industrial process fault separating method based on regularization framework

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020020623A1 (en) * 2000-07-20 2002-02-21 Speranza A. John Electrochemical cell system output control method and apparatus
US20020037445A1 (en) * 2000-09-25 2002-03-28 Martin Keller Method for operating a fuel cell battery
US7008708B2 (en) * 2000-01-03 2006-03-07 Idatech, Llc System and method for early detection of contaminants in a fuel processing system
US20100015474A1 (en) * 2008-07-18 2010-01-21 Rebecca Dinan Adaptive Technique and Apparatus to Detect an Unhealthy Condition of a Fuel Cell System
US20110153035A1 (en) 2009-12-22 2011-06-23 Caterpillar Inc. Sensor Failure Detection System And Method
EP1473789B1 (en) * 2003-04-08 2011-08-17 Asia Pacific Fuel Cell Technologies, Ltd. Device and method for controlling fuel cell system

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH08339203A (en) * 1995-06-14 1996-12-24 Omron Corp Manipulated variable generating device and method therefor
US6993407B2 (en) * 2003-10-02 2006-01-31 Taiwan Semiconductor Manufacturing Company Method and system for analyzing semiconductor fabrication
JP4375208B2 (en) * 2004-11-17 2009-12-02 日産自動車株式会社 Fuel cell output limiting device
JP4752258B2 (en) * 2004-12-08 2011-08-17 日産自動車株式会社 Fuel cell system
JP2007087856A (en) * 2005-09-26 2007-04-05 Nissan Motor Co Ltd Fuel cell system
CN201362352Y (en) * 2008-05-22 2009-12-16 上海海事大学 Fault-tolerant control device of unmanned underwater robot sensor
JP5048625B2 (en) * 2008-10-09 2012-10-17 株式会社日立製作所 Anomaly detection method and system

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7008708B2 (en) * 2000-01-03 2006-03-07 Idatech, Llc System and method for early detection of contaminants in a fuel processing system
US20020020623A1 (en) * 2000-07-20 2002-02-21 Speranza A. John Electrochemical cell system output control method and apparatus
US20020037445A1 (en) * 2000-09-25 2002-03-28 Martin Keller Method for operating a fuel cell battery
EP1473789B1 (en) * 2003-04-08 2011-08-17 Asia Pacific Fuel Cell Technologies, Ltd. Device and method for controlling fuel cell system
US20100015474A1 (en) * 2008-07-18 2010-01-21 Rebecca Dinan Adaptive Technique and Apparatus to Detect an Unhealthy Condition of a Fuel Cell System
US20110153035A1 (en) 2009-12-22 2011-06-23 Caterpillar Inc. Sensor Failure Detection System And Method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP2954580A4 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016059203A1 (en) * 2014-10-17 2016-04-21 Stiftelsen Sintef Control of an electrochemical device with integrated diagnostics, prognostics and lifetime management
US11239481B2 (en) 2014-10-17 2022-02-01 Stiftelsen Sintef Control of an electrochemical device with integrated diagnostics, prognostics and lifetime management

Also Published As

Publication number Publication date
US10126209B2 (en) 2018-11-13
US20150346065A1 (en) 2015-12-03
CN104854747B (en) 2017-09-26
JP2016511450A (en) 2016-04-14
EP2954580A4 (en) 2016-10-05
KR20150095876A (en) 2015-08-21
EP2954580B1 (en) 2019-11-20
CN104854747A (en) 2015-08-19
JP6197047B2 (en) 2017-09-13
KR101978018B1 (en) 2019-05-13
EP2954580A1 (en) 2015-12-16

Similar Documents

Publication Publication Date Title
US11275124B2 (en) Abnormality cause identifying method, abnormality cause identifying device, power converter and power conversion system
US9793753B2 (en) Power quality detector
CN105324900B (en) The method and apparatus of the early warning of the defects of for power equipment
GB2470465A (en) Abnormality detection of air conditioner
CN108885199B (en) Sensor signal processing apparatus
US20150241304A1 (en) Method for the computer-assisted monitoring of the operation of a technical system, particularly of an electrical energy-generating installation
JP2015518619A (en) System and method for detecting overheating of power plant equipment in real time with multiple parallel detection and analysis parameters
CN116703252B (en) Intelligent building information management method based on SaaS
KR20220083284A (en) Method for predecting power generation and remaining useful life per system and system for performing the same
US10126209B2 (en) Limit based threshold estimation for prognostics and health management
CN106652393B (en) False alarm determination method and device
JPWO2018154845A1 (en) Management device, management method, and program
KR20180075889A (en) alarm occurring method for using big data of nuclear power plant
EP3312844B1 (en) Abnormality indication monitoring system
CN117037454A (en) Early warning protection system, control method and device of electrical cabinet, medium and electrical cabinet
US20230296690A1 (en) Battery System and Detection Method
CN115632486B (en) Power consumption safety management method and system based on Internet of things
US9435672B2 (en) Measurement transducer for process instrumentation, and method for monitoring the state of its sensor
CN115876357A (en) Temperature sensor self-checking fault method and system
CN113659175B (en) Self-diagnosis method and device for fuel cell stack and electronic equipment
US20220316134A1 (en) Health assessment of a mechanical system
KR102280208B1 (en) Summing card detecting abnormal state of load cell and operation method thereof
CN112579665A (en) Energy equipment control method and device and energy equipment
CN110190305B (en) Degradation detection device for fuel cell stack, fuel cell system, and management method therefor
KR101598535B1 (en) Apparatus and method for analyzing electric power equipment

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 12890240

Country of ref document: EP

Kind code of ref document: A1

WWE Wipo information: entry into national phase

Ref document number: 14651181

Country of ref document: US

WWE Wipo information: entry into national phase

Ref document number: 2012890240

Country of ref document: EP

ENP Entry into the national phase

Ref document number: 2015549324

Country of ref document: JP

Kind code of ref document: A

NENP Non-entry into the national phase

Ref country code: DE

ENP Entry into the national phase

Ref document number: 20157018979

Country of ref document: KR

Kind code of ref document: A