Fault diagnosis with the Aladdin transient classifier

Davide Roverso

doi:10.1117/12.488995

8 August 2003 Fault diagnosis with the Aladdin transient classifier

Davide Roverso

Proceedings Volume 5107, System Diagnosis and Prognosis: Security and Condition Monitoring Issues III; (2003) https://doi.org/10.1117/12.488995
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

The purpose of Aladdin is to assist plant operators in the early detection and diagnosis of faults and anomalies in the plant that either have an impact on the plant performance, or that could lead to a plant shutdown or component damage if allowed to go unnoticed. The kind of early fault detection and diagnosis performed by Aladdin is aimed at allowing more time for decision making, increasing the operator awareness, reducing component damage, and supporting improved plant availability and reliability. In this paper we describe in broad lines the Aladdin transient classifier, which combines techniques such as recurrent neural network ensembles, Wavelet On-Line Pre-processing (WOLP), and Autonomous Recursive Task Decomposition (ARTD), in an attempt to improve the practical applicability and scalability of this type of systems to real processes and machinery. The paper focuses then on describing an application of Aladdin to a Nuclear Power Plant (NPP) through the use of the HAMBO experimental simulator of the Forsmark 3 boiling water reactor NPP in Sweden. It should be pointed out that Aladdin is not necessarily restricted to applications in NPPs. Other types of power plants, or even other types of processes, can also benefit from the diagnostic capabilities of Aladdin.

Citation Download Citation

Davide Roverso "Fault diagnosis with the Aladdin transient classifier", Proc. SPIE 5107, System Diagnosis and Prognosis: Security and Condition Monitoring Issues III, (8 August 2003); https://doi.org/10.1117/12.488995

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available