Discrete sensor validation with multilevel flow models

Discrete Sensor Validation with Multilevel Flow Models

Improving expressional power and validation for multilevel flow models

Multilevel flow modeling (MFM) is a modeling method for complex technical systems in which the goals and functions of the system are explicitly described. MFM can be used as a basis for root cause analysis, where primary root causes are separated from consequential faults, in complex fault situations. Model representations for use in diagnostic reasoning usually describe causality, between para...

Nonlinear multilevel models, with an application to discrete response data

Nonlinear models arise in a number of circumstances, notably when modelling discrete data. In this paper we consider the multilevel nonlinear model. As in linear multilevel models, we shall consider the general case where any of the model coefficients can be random at any level, and where the random parameters may also be specified functions of the fixed parameter estimates, discussed by H. Gol...

Real-Time Root Cause Analysis with Multilevel Flow Models

A fault in a complex technical system usually leads to a large number of consequential faults. In a modern control room, most variables are measured and monitored by alarms. Therefore, a non-trivial fault usually leads to a large amount of triggered alarms, a so-called alarm cascade. Alarm cascades cause information overload and renders the alarm system useless during incidents. GoalArt has dev...

Diagnostic Algorithms Based on Multilevel Flow Models

Human error is a common source of accidents in complex plants. We believe that many human errors really are caused by lack of intelligence in the instrumentation and control systems, putting the operators in situations, which humans realistically cannot be expected to cope with. Through history, several computer-based algorithms have been proposed and used for automated sensor fault detection, ...