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Measurement and Control Transactions of the Institute of DOI: 10.1191/0142331203tm093oa 2003; 25; 335 Transactions of the Institute of Measurement and Control Xiaochun George Wang and Wei Liu for the lumber-drying process A singular pencil model and neural network cascade fault diagnosis strategy /cgi/content/abstract/25/4/335 The online version of this article can be found at: Published by: On behalf of: The Institute of Measurement and Control found at: can beTransactions of the Institute of Measurement and Control Additional services and information for /cgi/alerts Email Alerts: /subscriptions Subscriptions: /journalsReprints.navReprints: /journalsPermissions.navPermissions: ? 2003 SAGE Publications. All rights reserved. Not for commercial use or unauthorized distribution. at PENNSYLVANIA STATE UNIV on April 17, 2008 Downloaded from Transactions of the Institute of Measurement and Control 25,4 (2003) pp. 335–351 A singular pencil model and neural network cascade fault diagnosis strategy for the lumber-drying process Xiaochun George Wang and Wei Liu Innovation Centre, National Research Council of Canada 3250 East Mall, Vancouver, B.C., Canada V6T 1W5 This paper presents some results that were obtained in fault diagnosis for a wood-drying pro- cess. It is dif?cult to detect and diagnose faults or failure in the drying process due to complex dynamic nonlinearity, coupling effects among key variables, and process disturbances caused by the variation of lumber sizes, species and environmental factors. In this paper, a real-time fault diagnosis algorithm is developed based on a singular pencil model and neural network classi?er. Inputs of the network are the process I/O data, such as moisture and temperature, and estimated parameters and states, while outputs of the network are process fault situations. A wood-drying kiln is studied as a test case, which is with two actuators and 23 sensors, six estimated parameters and states, and 11 fault situati