Hidden Markov models for fault detection in dynamic systems

Hidden Markov Models for Fault Detection in Dynamic Systems

A. S. Willsky, " A Survey of design methods for failure detection in dynamic systems, " Automatica, pp. 601-61 1, 1976. Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy-a survey and some new results ". 1571 ABSTRACT The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention...

Hidden Markov models for fault detection in dynamic system

Fault Detection in Process Systems using Hidden Markov Disturbance Models

Fault detection and diagnosis is critical for maintaining the health of process systems. Common fault signals include process and disturbance parameter changes, as well as sensor and actuator malfunctions (such as persistent drifts and biases). These may be characterized by the existence of latent ‘fault’ states. This work examines the effectiveness of a Hidden Markov Model framework for modeli...

Hidden Markov models and dynamic systems

Order online: www.siam.org/catalog • Use your credit card (AMEX, MasterCard, or VISA): Call SIAM Customer Service at +1-215-382-9800 worldwide or toll free at 800-447-SIAM in USA and Canada; Fax: +1-215-386-7999; E-mail: [email protected] • Send check or money order to: SIAM, Dept. BKNO08, 3600 Market Street, 6th Floor, Philadelphia, PA 19104-2688. SOCIETY FOR INDUSTRIAL AND APPLIED MATHEMATIC...

Hidden Markov Models for Software Piracy Detection

In this paper, we analyze a method for detecting software piracy. A metamorphic generator is used to create morphed copies of a base piece of software. A hidden Markov model is trained on the opcode sequences extracted from these morphed copies and the resulting trained model is used to score suspect software to determine its similarity to the base software. A high score indicates that the susp...