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| Summary / Description | This patent describes a method and system for monitoring the performance of process models (a mathematical or physical model that indicates relationships between inputs and outputs). Rules are used by the monitor to determine when to trigger an alarm. |
| Type of Prior Art | Issued Patents - US |
| Country | United States of America |
| Patent/Application # | 2006/0230097 |
| Kind Code | United States (US) - Patent Appl. Publ. within the ... - A1 |
| Patentee Name | Anthony J. Grichnik; Michael Seskin |
| Relevant Pages, Columns, or Lines | |
| URL | http://appft1.uspto.gov/netacgi... |
| Filing Date | April 8, 2005 |
| Additional Information | |
| Notes | |
Excerpt One aspect of the present disclosure includes a computer-implemented method for monitoring model performance. The method may include obtaining configuration information and obtaining operational information about a computational model and a system being modeled. The computational model and the system may include a plurality of input parameters and one or more output parameters. The system may generate respective actual values of the one or more output parameters, and the computational model may predict respective values of the one or more output parameters. The method may also include applying an evaluation rule from a rule set, based on the configuration information, to the operational information to determine whether the rule is satisfied. |
A method for performing multi-objective predictive modeling, monitoring, and update for an asset, comprising:
determining a status of each of at least two predictive models (104) for an asset as a result of monitoring predicted performance values, the status of each predictive model (104) including at least one of:
acceptable performance values;
validating model; and
unacceptable performance values; and
based upon the status of each predictive model (104), performing at least one of:
terminating use of the at least two predictive models (104) for the asset;
generating an alert for the asset of the status of the at least two predictive models (104); and
updating the at least two predictive models (104) based upon the status of the at least two predictive models (104).
| Relevance | The prior art provides a generalised method of monitoring a model (See claims 1, 2, 4, 6, 8, 11). The prior art uses a "rule set" to determines whether a trigger should be fired, whereas this claims three specific states that may trigger actions. The prior art provides for the following actions that are similar to claim 1: "In certain embodiments, an expiration rule may be set to disable process model being used". A "trigger may include any appropriate type of notification mechanism". A "trigger may be provided to indicate that one or more rules of rule set have been satisfied and that the performance of process model may be degraded." |
The method of claim 1, wherein the acceptable performance values are determined by comparing the predicted performance values with actual performance values of each predictive model (104), wherein the predicted performance values are considered to be acceptable if they coincide with the actual performance values.
| Relevance | See prior art claim 8 in particular. The prior art also describes a "evaluation rule" that follows the behaviour of claim 2: "Rule set may also include an evaluation rule indicating a threshold for divergence between predicted values of output parameters from process model and actual values corresponding to output parameters from a system being modeled. The divergence may be determined based on overall actual and predicted values of output parameters or based on an individual actual output parameter value and a corresponding predicted output parameter value. The threshold may be set according to particular application requirements. In the engine design example, if a predicted throttle setting deviated from an actual throttle setting value and the deviation is beyond a predetermined threshold for throttle setting, the performance of process model may be determined as degraded. When the deviation is beyond the threshold, the evaluation rule may be satisfied to indicate the degraded performance of process model. Although certain particular rules are described, it is understood that any type of rule may be included in rule set." (references omitted) |
A system for performing multi-objective predictive modeling, monitoring, and update for an asset, comprising:
at least two predictive models (104) relating to an asset;
a monitoring module (107) in communication with the at least two predictive models (104), the monitoring module (107) performing:
monitoring predictive performance values for each predictive model (104) and
determining a status of each predictive model (104) as a result of the monitoring, the status including at least one of:
acceptable performance values;
validating model; and
unacceptable performance values; and
based upon the status of each of the predictive models (104), perfonning at least one of:
terminating use of the at least two predictive models (104) for the asset;
generating an alert for the asset of the status of the at least two predictive models (104); and
updating the at least two predictive models (104) based upon the status of the at least two predictive models (104).
| Relevance | As described above for claim 1. See prior art claims 12, 13, 17. |
The system of claim 6, wherein the acceptable performance values are determined by comparing the predicted performance values with actual performance values of each predictive model (104), wherein the predictive performance values are considered to be acceptable if they coincide with the actual performance values.
| Relevance | As described above for claim 2. See prior art claim 17. |
United States