Data processing: vehicles – navigation – and relative location – Vehicle control – guidance – operation – or indication – Vehicle diagnosis or maintenance indication
Reexamination Certificate
1998-07-01
2001-04-10
Cuchlinski, Jr., William A. (Department: 3661)
Data processing: vehicles, navigation, and relative location
Vehicle control, guidance, operation, or indication
Vehicle diagnosis or maintenance indication
C701S033000, C701S099000, C702S179000, C340S438000, C340S439000
Reexamination Certificate
active
06216066
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates generally to trend performance analysis and more particularly to generating alerts for data obtained from a process through automated multi-variate data assessment.
BACKGROUND OF THE INVENTION
A trend performance analysis tool is typically used to monitor sensor data and parameter settings for a technical process. One type of technical process where a trend performance analysis tool is used is with aircraft engines. In this example, engine data are sampled from an airplane at different times of the flight and transmitted to a ground station. The data are collected and distributed to an aircraft engine expert for that particular airplane fleet. The data are preprocessed and evaluated by a trend performance analysis tool. In particular, the trend performance analysis tool monitors a multitude of engine variables. Data for each variable are compared against trending baseline data. If the data for a particular variable exceed a predetermined threshold limit and the data are not considered to be an outlier, then the trend performance analysis tool issues an alert. Typically, the predetermined alert threshold limit for each variable is set at a level that is below a limit that would generate a fault warning flag in the cockpit of the airplane. In particular, the predetermined alert threshold limit for each variable is at a level that would create an awareness of a potential problem before it turns into an event that could result in a revenue loss for the airplane. Examples of potential revenue loss situations are a grounding of an airplane, damage to an engine, departure delay, etc.
After an alert has been issued by the trend performance analysis tool, the aircraft engine expert examines trend charts for each of the variables in order to determine if an event has truly occurred which warrants further action. If the data in any of the trend charts are suspicious, then the aircraft engine expert notifies the fleet management of that particular airplane and suggests actions to further diagnose and/or actions to correct any causes for the alert. Examples of possible actions are borescoping the engine, engine washing, overhauling the engine, etc. A problem with this approach is that many alerts are generated which are false and do not warrant further diagnostic or corrective actions. There are a number of reasons for the high number of false alerts being issued. One is that the data quality varies considerably between different engines. Another reason is that predetermined alert threshold levels for a variable are preset globally and not selected for an individual airplane. Other reasons for issuing an excessive number of alerts are noise generated from poorly calibrated and deteriorating sensors, the use of faulty data acquisition systems, and slow wear of the engine which results in a constant change of normal operating conditions.
If too many alerts are generated, then the aircraft engine expert has to constantly examine the trend charts to eliminate the false alerts from the true alerts. Constantly examining the trend charts becomes a very time consuming task when there is a large number of engines to monitor as typically is the case for a large fleet of airplanes. In addition, the expert's senses may become dulled to the true alerts due to the large amount of false positive alerts. Therefore, there is a need for a system and method that produces less false positive alerts and can assist in reducing the excessive number of false alerts generated by a trend performance analysis tool.
SUMMARY OF THE INVENTION
This invention is able to generate alerts through simultaneous assessment of several engine variables and by learning changing system behavior. First, data are processed by normalization according to a set of normalization parameters. In particular, variables defined for the process are normalized individually. The normalized data for each process variable are then assessed simultaneously. In particular, multi-variate clustering is used to classify the normalized data in a multi-dimensional space defined for the process variables. The normalized data are classified into a cluster indicative of normal operating conditions and one or more alert clusters indicative of alert conditions. The clusters are of non-uniform and non-linear degrading size and shape. In particular, the boundaries between the clusters are non crisp, such that the degree of membership for a cluster is largest at the center. Data classified as being in one of the alert clusters are then verified to make sure that the data are not a false alert. Suspected alerts are verified by determining the level of vigilance for each reading. Each reading with a raised vigilance level is indicative of suspicious data. Each consecutive suspicious reading after the first suspicious reading raises the degree of vigilance. If a predetermined number of consecutive vigilance readings has been generated, then the suspected alert is considered to be a true alert and not a false alert. The cluster locations and shapes are then updated to account for slow system changes which are expected by the system, e.g., due to wear.
In accordance with one embodiment of this invention, there is provided a system and a method for generating alerts from data obtained from a process. In this embodiment, a normalizer normalizes the data. A classifier classifies the normalized data in a multi-dimensional space defined for variables in the process. The normalized data are classified into a normal cluster indicative of normal operating conditions and at least one alert cluster each indicative of alert conditions. An alert verifier verifies data classified as an alert condition.
In accordance with a second embodiment of this invention, there is provided a system and method for generating alerts from data obtained from a process. In this embodiment, a normalizer normalizes the data. A tracker tracks the normalized data for drifts that arise over time in the process. A classifier classifies the normalized data in a multi-dimensional space defined for variables in the process. The normalized data are classified into a normal cluster indicative of normal operating conditions and at least one alert cluster each indicative of alert conditions. An alert verifier verifies data classified as an alert condition.
In accordance with a third embodiment of this invention, there is provided a system and method for validating an alert generated from a trend performance analysis tool used to monitor data obtained from a process. In this embodiment, a normalizer normalizes the data monitored by the trend performance analysis tool. A classifier classifies the normalized data in a multi-dimensional space defined for variables in the process. The normalized data are classified into a normal cluster indicative of normal operating conditions and at least one alert cluster each indicative of alert conditions. An alert verifier verifies data classified as an alert condition. The verified alert condition is an indication that the alert generated from the trend performance analysis tool is valid.
REFERENCES:
patent: 4037782 (1977-07-01), Jackson
patent: 4215412 (1980-07-01), Bernier et al.
patent: 4280185 (1981-07-01), Martin
patent: 4402054 (1983-08-01), Osborne et al.
patent: 4656585 (1987-04-01), Stephenson
patent: 4660145 (1987-04-01), Hansen
patent: 5018069 (1991-05-01), Pettigrew
patent: 5263120 (1993-11-01), Bickel
patent: 5406502 (1995-04-01), Haramaty et al.
patent: 5408412 (1995-04-01), Hogg et al.
SENSA TECHNOLOGIES, INC. HOME PAGE, 1998, internet address: http://www.jenanet.com/index.thm, 28 pages.*
“Ultra High-Tech Monitoring” Software that learns By Greg Napert, Aircraft Maintenance Technology, Mar. 1998, pp. 48-52.*
“Enhancing Aircraft Engine Condition Monitoring” by M. Fernandez-Montesinos, et al, IFAC Emerging Intelligent Control Technologies, Hong Kong, 1994, pp. 161-166.*
“Novel Self-Learning Fault Detection System for Gas Turbine Engines” by VC Aptel, et al., Univ. of Sheffield, United Kingdom, ACCC Int
Doel David Lacey
Goebel Kai Frank
Arthur Gertrude
Breedlove Jill M.
Cuchlinski Jr. William A.
General Electric Company
Goldman David C.
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