PREDICTING ELECTROMECHANICAL ACTUATOR HEALTH AND REMAINING LIFE

• US 20190325663A1
• Filed: 04/23/2018
• Published: 10/24/2019
• Est. Priority Date: 04/23/2018
• Status: Active Grant

• Current Assignee: Woodward Incorporated
• Original Assignee: Woodward Incorporated
• Inventors: Brim, Miles W.
• Granted Patent: US 11,373,455 B2
• Time in Patent Office: Days
• CPC Class Codes: G01R 31/343 in operation
• 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: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G07C 3/02 Registering or indicating working or idle time only

Abstract

Methods, systems, and apparatus for predicting electromechanical actuator health and remaining life include a method storing a reliability model coupled to a controlled actuator system comprising a motive force system coupled to a driven mechanical system. The motive force system is associated with motive force parameters. The driven mechanical system is associated with driven mechanical parameters. The reliability model represents a probability of failure of the controlled actuator system over time based on motive force parameters and driven mechanical parameters. Operational parameters of the controlled actuator system, received over time from a sensor system coupled to the controlled actuator system, include one of the motive force parameters or driven mechanical parameters. The operational parameters represent a degradation of the controlled actuator system over time. The reliability model is updated to represent a revised probability of failure. A state of the controlled actuator system is determined using the updated reliability model.

Claims

1. A method comprising:

storing, on a computer system coupled to a controlled actuator system, a set of operational mode definitions, a reliability model per operational mode, the controlled actuator system comprising a motive force system coupled to and providing an operating force to a driven mechanical system, the motive force system associated with a plurality of motive force parameters, the driven mechanical system associated with a plurality of driven mechanical parameters, a reliability model representing a probability of failure of the controlled actuator system over time for each operational mode, each reliability model'"'"'s hazard rate regression model based on one or more of the plurality of motive force parameters and one or more of the plurality of driven mechanical parameters, the set of test definitions and analysis by which the plurality of driven and motive force parameters are acquired, and a plurality of statistical models that use the plurality of driven and motive force parameters to determine the probability of a system existing in an operational mode;

receiving, over time, by the computer system and from a sensor system coupled to the controlled actuator system, one or more operational parameters of the controlled actuator system, the one or more operational parameters including one of the motive force parameters or one of the driven mechanical parameters, the one or more operational parameters representing a degradation of the controlled actuator system over time;

updating, by the computer and based on the received one or more operational parameters, the reliability model according to the hazard rate regression model to represent a revised probability of failure of the controlled actuator system over time and the statistical model to represent a revised probability of existing in an operational mode;

determining, by the computer system and based on the updated reliability model, that the controlled actuator system is approaching failure; and

in response, transmitting, by the computer system, a signal indicating that the controlled actuator system is approaching failure.

2. The method of claim 1, wherein the reliability model is a first reliability model, wherein the method further comprises storing, on the computer system, a plurality of reliability models including the first reliability model, wherein each reliability model is associated with a respective category of operation of the controlled actuator system, wherein the one or more operational parameters of the controlled actuator system vary based on the category, the hazard rate regression models vary based on the category, and the statistical models that represent the probability of existing in the respective category vary based on the category, wherein each reliability model represents a respective probability of failure of the controlled actuator system over time when operated based on the one or more operational parameters associated with the respective category.

3. The method of claim 2, wherein the respective category of operation comprises at least one of:

normal operation in which the controlled actuator system is operated under a normal operational parameter range for each motive force parameter and each driven mechanical parameter,

accelerated wear operation in which the controlled actuator system is operated in a condition in which at least one motive force parameter or at least one driven mechanical parameter is operated outside a respective normal operational parameter range,

operation using non-conforming components in which a component of either the motive force system or the driven mechanical system operates outside the normal operational parameter range for the component, or

failure operation resulting from a failure inducing change to the normal operational parameter of a motive force parameter or a driven mechanical parameter.

4. The method of claim 2, further comprising:

identifying the respective category from the one or more operational parameters received from the sensor system using the statistical models that represent the probability of existing in the respective category; and

updating a reliability model associated with the identified respective category.

5. The method of claim 1, wherein the one or more operational parameters are received during an operation of the controlled actuator system.

6. The method of claim 1, wherein the one or more operational parameters are received when the controlled actuator system is off-line and operating a controlled diagnostic sequence.

7. The method of claim 1, wherein the motive force system comprises an electric motor motive force or a hydraulic actuator motive force.

8. The method of claim 7, wherein the plurality of motive force parameters includes one or more of a magnet torque constant, a rotor inertia, unbalanced rotation terms, a set of winding resistances, a set of winding inductances, a set of motor bearing and windage viscous friction, and a set of motor bearing static or dynamic Coulomb friction.

9. The method of claim 7, wherein the driven mechanical system comprises a rotary or linear actuator connected to source of motive force by one or more of a plurality of:

a direct connection, a geared connection, or a screw-drive conversion.

10. The method of claim 9, wherein the driven mechanical parameters comprise an actuator inertia and mass, a set of spring constants, a gear meshing constant, frequency, and phase, a set of screw-drive efficiencies, backlash and dead-band terms, unbalanced rotation terms, non-aligned linear motion terms, a set of actuator bearing viscous frictions, a set of bearing and shaft on seal dynamic or static Coulomb frictions, and a valve load.

11. A system comprising:

a driven mechanical system, the driven mechanical system associated with a plurality of driven mechanical parameters;

a motive force system coupled to and driven by the driven mechanical system, the motive force system associated with a plurality of motive force parameters;

a sensor system comprising a plurality of sensors, the sensor system coupled to the driven mechanical system or the motive force system, the plurality of sensors configured to sense one or more operational parameters of the controlled actuator system, the one or more operational parameters including one of the motive force parameters or one of the driven mechanical parameters, the one or more operational parameters representing a degradation of the controlled actuator system over time; and

a computer system coupled to the driven mechanical system, the motive force system, and the sensor system, the computer system comprising;

one or more processors; and

a non-transitory computer-readable medium storing instructions executable by the one or more processors to perform operations comprising;

storing a reliability model representing a probability of failure of the controlled actuator system over time for each operational mode, each reliability model'"'"'s hazard rate regression model based on one or more of the plurality of motive force parameters and one or more of the plurality of driven mechanical parameters, the set of test definitions and analysis by which the plurality of driven and motive force parameters are acquired, and a plurality of statistical models that use the plurality of driven and motive force parameters to determine the probability of a system existing in an operational mode; and

updating the reliability model to represent a revised probability of failure over time based on the received one or more operational parameters and updating the statistical model to represent the probability of existing in an operational mode.

12. The system of claim 11, wherein the operations further comprise:

determining, by the computer system and based on the updated reliability model, that either the driven mechanical system or the motive force system is approaching failure; and

in response, transmitting, by the computer system, a signal indicating that either the driven mechanical system or the motive force system is approaching failure.

13. The system of claim 11, wherein the one or more operational parameters are received during an operation of the controlled actuator system

14. The system of claim 11, wherein the one or more operational parameters are received when the controlled actuator system is off-line and operating a controlled diagnostic sequence.

15. The system of claim 11, wherein the motive force system comprises an electric motor motive force or a hydraulic actuator motive force.

16. The system of claim 15, wherein the plurality of motive force parameters includes one or more of a magnet torque constant, a rotor inertia, unbalanced rotation terms, a set of winding resistances, a set of winding inductances, a set of motor bearing and windage viscous friction, and a set of motor bearing static or dynamic Coulomb friction.

17. The system of claim 15, wherein the driven mechanical system comprises a rotary or linear actuator connected to source of motive force by one or more of a plurality of:

a direct connection, a geared connection, or a screw-drive conversion.

18. The system of claim 17, wherein the driven mechanical parameters comprise an actuator inertia and mass, a set of spring constants, a gear meshing constant, frequency, and phase, a set of screw-drive efficiencies, backlash and dead-band terms, unbalanced rotation terms, non-aligned linear motion terms, a set of actuator bearing viscous frictions, a set of bearing and shaft on seal dynamic or static Coulomb frictions, and a valve load

19. A method comprising:

identifying a plurality of driven mechanical parameters associated with a driven mechanical system;

identifying a plurality of motive force parameters associated with a motive force system coupled to and driven by the driven mechanical system;

identifying, for each driven mechanical parameter and each motive force parameter, a respective value;

determining a plurality of diagnostic sequence test and analysis definitions necessary to arrive at a respective value for the driven and motive force parameters;

determining a plurality of regression models relating the driven mechanical parameters and motive force parameters to remaining life;

determining an operational model representing an operation of the driven mechanical system driven by the motive force system based on each respective value identified for each driven mechanical parameter and each motive force parameter;

determining a plurality of statistical models representing the probability of existing in an identified operational model;

determining a plurality of reliability models representing the probability of failure of the controlled actuator system;

measuring one or more operational parameters during an off-line operation of the motive force system to drive the driven mechanical system, wherein the one or more operational parameters represent degradation of the controlled actuator system;

updating the statistical model representing the probability of existing in an identified operational model used the measured parameters;

updating the reliability model'"'"'s regression model using the measured parameters; and

identifying a set of metrics that describe the degradation of the motive force system driven by the driven mechanical system over time using a statistical method and the one or more operational parameters measured during the off-line operation.

20. The method of claim 19, wherein updating the expected behavior comprises:

developing a dynamic reliability model representing an updated expected behavior based on the set of probabilities, alpha errors and beta errors from the statistical models for each operational model and the set of updated reliability models for each operational model.