Granted Patent B2

US 12,282,324 · App. 16/899,220 · Granted Apr 22, 2025

Inventors: Mohammad N. Elbsat (Milwaukee, WI); Michael J. Wenzel (Oak Creek, WI); Robert D. Turney (Watertown, WI)

Assignee: Tyco Fire & Security GmbH

G05B23/0283G05B19/0428G05B23/0291G06N3/08

Abstract

Claims (73)

1. A model predictive maintenance (MPM) system for building equipment, the MPM system comprising:

one or more processing circuits comprising one or more processors and memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

estimating a degradation state of the building equipment;

using a degradation impact model to generate parameters of a separate resource consumption model based on the degradation state of the building equipment, wherein the degradation impact model receives the degradation state of the building equipment as an input to the degradation impact model and provides the parameters of the resource consumption model as an output of the degradation impact model;

using the resource consumption model to predict an amount of one or more input resources that are provided as inputs to the building equipment and consumed by the building equipment to produce an amount of one or more output resources by converting the one or more input resources into the one or more output resources, wherein the resource consumption model defines a relationship between the amount of the one or more input resources consumed and the amount of the one or more output resources produced based on the parameters generated and output by the degradation impact model;

generating a maintenance schedule for the building equipment and operating decisions for the building equipment based on the amount of the one or more input resources predicted using the resource consumption model;

initiating a maintenance activity for the building equipment in accordance with the maintenance schedule; and

controlling the building equipment by generating electronic control signals based on the operating decisions for the building equipment and causing the building equipment to affect a variable state or condition in a building using the electronic control signals.

2. The MPM system of claim 1 , wherein the degradation impact model is trained using historical or simulated training data prior to using the degradation impact model to predict the amount of the one or more input resources consumed by the building equipment, wherein training the degradation impact model comprises:

generating the training data for the degradation impact model, the training data comprising a plurality of different values of the degradation state of the building equipment and corresponding values of parameters of a resource consumption model for the building equipment; and

using the training data to train the degradation impact model to predict the values of the parameters of the resource consumption model as a function of the degradation state.

3. The MPM system of claim 2 , wherein generating the training data comprises:

performing a regression process to generate the values of the parameters of the resource consumption model using data associated with a first degradation state of the building equipment; and

repeating the regression process using data associated with one or more additional degradation states of the building equipment to generate a plurality of different values of the parameters of the resource consumption model, the plurality of different values of the parameters corresponding to a plurality of different degradation states of the building equipment.

4. The MPM system of claim 1 , wherein the degradation impact model comprises a neural network model and using the degradation impact model to predict the amount of the one or more input resources consumed by the building equipment comprises:

providing the degradation state of the building equipment and an amount of the one or more output resources to be produced by the building equipment as inputs to the neural network model; and

obtaining the amount of one or more input resources consumed by the building equipment as an output of the neural network model.

5. The MPM system of claim 1 , wherein generating the maintenance schedule for the building equipment comprises:

performing an optimization of an objective function that accounts for both a cost of operating the building equipment and a cost of performing maintenance on the building equipment over a time period; and

generating a set of maintenance decisions for the building equipment as a result of performing the optimization, the set of maintenance decisions forming the maintenance schedule.

6. The MPM system of claim 1 , wherein generating the maintenance schedule for the building equipment comprises:

calculating a cost of operating the building equipment over a time period as a function of the degradation state of the building equipment at one or more times within the time period;

calculating a cost of performing maintenance on the building equipment over the time period as a function of one or more maintenance activities defined by the maintenance schedule;

adjusting the degradation state of the building equipment at one or more times following the one or more maintenance activities defined by the maintenance schedule; and

generating the maintenance schedule that results in a lowest total cost comprising the cost of operating the building equipment over the time period and the cost of performing maintenance on the building equipment over the time period.

7. The MPM system of claim 1 , wherein generating the maintenance schedule comprises determining a specific type of maintenance activity to be performed at a service time from a set of multiple different types of maintenance activities based on (1) first costs of operating the building equipment over a time period predicted to result from the multiple different types of the maintenance activities and (2) second costs of servicing the building equipment over the time period predicted to result from the multiple different types of the maintenance activities.

8. The MPM system of claim 1 , wherein the degradation state of the building equipment is an initial degradation state, the operations further comprising:

predicting one or more future degradation states of the building equipment as a function of the initial degradation state; and

using the degradation impact model to predict the amount of the one or more input resources consumed by the building equipment at one or more future times as a function of the one or more future degradation states.

9. A method for using model predictive maintenance (MPM) to generate a maintenance schedule for building equipment, the method comprising:

estimating a degradation state of the building equipment;

using a degradation impact model to generate parameters of a separate resource consumption model based on the degradation state of the building equipment, wherein the degradation impact model receives the degradation state of the building equipment as an input to the degradation impact model and provides the parameters of the resource consumption model as an output of the degradation impact model;

using the resource consumption model to predict an amount of one or more input resources that are provided as inputs to the building equipment and consumed by the building equipment to produce an amount of one or more output resources by converting the one or more input resources into the one or more output resources, wherein the resource consumption model defines a relationship between the amount of the one or more input resources consumed and the amount of the one or more output resources produced based on the parameters generated and output by the degradation impact model;

generating a maintenance schedule for the building equipment and operating decisions for the building equipment based on the amount of the one or more input resources predicted using the resource consumption model;

initiating a maintenance activity for the building equipment in accordance with the maintenance schedule; and

controlling the building equipment by generating electronic control signals based on the operating decisions for the building equipment and causing the building equipment to affect a variable state or condition in a building using the electronic control signals.

10. The method of claim 9 , wherein the degradation impact model is trained using historical or simulated training data prior to using the degradation impact model to predict the amount of the one or more input resources consumed by the building equipment, wherein training the degradation impact model comprises:

generating the training data for the degradation impact model, the training data comprising a plurality of different values of the degradation state of the building equipment and corresponding values of parameters of a resource consumption model for the building equipment; and

using the training data to train the degradation impact model to predict the values of the parameters of the resource consumption model as a function of the degradation state.

11. The method of claim 10 , wherein generating the training data comprises:

performing a regression process to generate the values of the parameters of the resource consumption model using data associated with a first degradation state of the building equipment; and

repeating the regression process using data associated with one or more additional degradation states of the building equipment to generate a plurality of different values of the parameters of the resource consumption model, the plurality of different values of the parameters corresponding to a plurality of different degradation states of the building equipment.

12. The method of claim 9 , wherein the degradation impact model comprises a neural network model and using the degradation impact model to predict the amount of the one or more input resources consumed by the building equipment comprises:

providing the degradation state of the building equipment and an amount of the one or more output resources to be produced by the building equipment as inputs to the neural network model; and

obtaining the amount of one or more input resources consumed by the building equipment as an output of the neural network model.

13. The method of claim 9 , wherein generating the maintenance schedule for the building equipment comprises:

performing an optimization of an objective function that accounts for both a cost of operating the building equipment and a cost of performing maintenance on the building equipment over a time period; and

generating a set of maintenance decisions for the building equipment as a result of performing the optimization, the set of maintenance decisions forming the maintenance schedule.

14. The method of claim 9 , wherein generating the maintenance schedule for the building equipment comprises:

calculating a cost of operating the building equipment over a time period as a function of the degradation state of the building equipment at one or more times within the time period;

calculating a cost of performing maintenance on the building equipment over the time period as a function of one or more maintenance activities defined by the maintenance schedule;

adjusting the degradation state of the building equipment at one or more times following the one or more maintenance activities defined by the maintenance schedule; and

generating the maintenance schedule that results in a lowest total cost comprising the cost of operating the building equipment over the time period and the cost of performing maintenance on the building equipment over the time period.

15. The method of claim 9 , wherein the degradation state of the building equipment is an initial degradation state, the method comprising:

predicting one or more future degradation states of the building equipment as a function of the initial degradation state; and

using the degradation impact model to predict the amount of the one or more input resources consumed by the building equipment at one or more future times as a function of the one or more future degradation states.

16. The method of claim 9 , wherein generating the maintenance schedule comprises determining a specific type of maintenance activity to be performed at a service time from a set of multiple different types of maintenance activities based on (1) first costs of operating the building equipment over a time period predicted to result from the multiple different types of the maintenance activities and (2) second costs of servicing the building equipment over the time period predicted to result from the multiple different types of the maintenance activities.

17. A model predictive maintenance (MPM) system for building equipment, the MPM system comprising:

one or more processing circuits comprising one or more processors and memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

using a degradation impact model to generate parameters of a separate resource consumption model for the building equipment based on a degradation state of the building equipment, wherein the degradation impact model receives the degradation state of the building equipment as an input to the degradation impact model and provides the parameters of the resource consumption model as an output of the degradation impact model;

using the resource consumption model to predict an amount of one or more input resources provided as inputs to the building equipment and consumed by the building equipment to produce an amount of one or more output resources by converting the one or more input resources into the one or more output resources, wherein the resource consumption model defines a relationship between the amount of the one or more input resources consumed and the amount of the one or more output resources produced based on the parameters generated and output by the degradation impact model;

using the resource consumption model to generate a maintenance schedule for the building equipment and operating decisions for the building equipment that result in a lowest total cost of operating the building equipment and performing maintenance on the building equipment over a time period;

initiating a maintenance activity for the building equipment in accordance with the maintenance schedule; and

controlling the building equipment by generating electronic control signals based on the operating decisions for the building equipment and causing the building equipment to affect a variable state or condition in a building using the electronic control signals.

18. The MPM system of claim 17 , wherein using the resource consumption model to generate the maintenance schedule comprises:

using the resource consumption model to predict an amount of one or more input resources consumed by the building equipment to produce one or more output resources as a function of the parameters of the resource consumption model; and

generating the maintenance schedule based on the amount of the one or more input resources consumed by the building equipment to produce the one or more output resources.

19. The MPM system of claim 17 , wherein the degradation impact model is trained using historical or simulated training data prior to using the degradation impact model to generate the parameters of the resource consumption model, wherein training the degradation impact model comprises:

generating the training data for the degradation impact model, the training data comprising a plurality of different values of the degradation state of the building equipment and corresponding values of the parameters of the resource consumption model; and

using the training data to train the degradation impact model to predict the values of the parameters of the resource consumption model as a function of the degradation state.

20. The MPM system of claim 19 , wherein generating the training data comprises:

performing a regression process to generate the values of the parameters of the resource consumption model using data associated with a first degradation state of the building equipment; and

repeating the regression process using data associated with one or more additional degradation states of the building equipment to generate a plurality of different values of the parameters of the resource consumption model, the plurality of different values of the parameters corresponding to a plurality of different degradation states of the building equipment.

Assignments (3)

Continuity (4)

References Cited (304)