Fault isolation and sensor placement are vital for monitoring and diagnosis. A sensor conveys information about a system's state that guides troubleshooting if problems arise. We are using machine learning methods to uncover behavioral patterns over snapshots of system simulations that will aid fault isolation and sensor placement, with an eye towards minimality, fault coverage, and noise tolerance
Systems health management, and in particular fault diagnosis, is important for ensuring safe, correc...
Neural networks have been employed for learning fault behavior from rocket engine simulator paramete...
A diagnostic method based on Bayesian Networks (probabilistic graphical models) is presented. Unlike...
Sensor faults continue to be a major hurdle for systems health management to reach its full potentia...
In this paper, a reinforcement learning approach is proposed to detect unexpected faults, where the ...
peer reviewedThis work develops a methodology to solve the sensor placement problem for fault detect...
peer reviewedThis work develops a methodology to solve the sensor placement problem for fault detect...
Adequate sensors are a necessary condition for fault diagnosability. Sensor placement for diagnosis ...
Wireless Sensor Network (WSN) deployment experiences show that collected data is prone to be faulty....
Sensors’ existence as a key component of Cyber-Physical Systems makes it susceptible to failures due...
This dissertation investigates the sensor placement issue in a dynamic system for fault detectabilit...
Exploiting spatial and temporal relationships in acquired datastreams is a primary ability of Cognit...
A new method of sensor failure detection, isolation, and accommodation is described using a neural n...
This paper describes the development of an intelligent sensor architecture, where signal conditionin...
Fault diagnosis is the problem of determining a set of faulty system components that explain discrep...
Systems health management, and in particular fault diagnosis, is important for ensuring safe, correc...
Neural networks have been employed for learning fault behavior from rocket engine simulator paramete...
A diagnostic method based on Bayesian Networks (probabilistic graphical models) is presented. Unlike...
Sensor faults continue to be a major hurdle for systems health management to reach its full potentia...
In this paper, a reinforcement learning approach is proposed to detect unexpected faults, where the ...
peer reviewedThis work develops a methodology to solve the sensor placement problem for fault detect...
peer reviewedThis work develops a methodology to solve the sensor placement problem for fault detect...
Adequate sensors are a necessary condition for fault diagnosability. Sensor placement for diagnosis ...
Wireless Sensor Network (WSN) deployment experiences show that collected data is prone to be faulty....
Sensors’ existence as a key component of Cyber-Physical Systems makes it susceptible to failures due...
This dissertation investigates the sensor placement issue in a dynamic system for fault detectabilit...
Exploiting spatial and temporal relationships in acquired datastreams is a primary ability of Cognit...
A new method of sensor failure detection, isolation, and accommodation is described using a neural n...
This paper describes the development of an intelligent sensor architecture, where signal conditionin...
Fault diagnosis is the problem of determining a set of faulty system components that explain discrep...
Systems health management, and in particular fault diagnosis, is important for ensuring safe, correc...
Neural networks have been employed for learning fault behavior from rocket engine simulator paramete...
A diagnostic method based on Bayesian Networks (probabilistic graphical models) is presented. Unlike...