Inductive Learning for Case-Based Diagnosis with Multiple Faults
نویسندگان
چکیده
We present adapted inductive methods for learning similarities, parameter weights and diagnostic profiles for case-based reasoning. All of these methods can be refined incrementally by applying different types of background knowledge. Diagnostic profiles are used for extending the conventional CBR to solve cases with multiple faults. The context of our work is to supplement a medical documentation and consultation system by CBR techniques, and we present an evaluation with a real-world case base.
منابع مشابه
Inductive learning for fault diagnosis
There is a steadily increasing need for autonomous systems that must be able to function with minimal human intervention to detect and isolate faults, and recover from such faults. In this paper we present a novel hybrid Model based and Data Clustering (MDC) architecture for fault monitoring and diagnosis, which is suitable for complex dynamic systems with continuous and discrete variables. The...
متن کاملFault diagnosis in a distillation column using a support vector machine based classifier
Fault diagnosis has always been an essential aspect of control system design. This is necessary due to the growing demand for increased performance and safety of industrial systems is discussed. Support vector machine classifier is a new technique based on statistical learning theory and is designed to reduce structural bias. Support vector machine classification in many applications in v...
متن کاملAN INTELLIGENT FAULT DIAGNOSIS APPROACH FOR GEARS AND BEARINGS BASED ON WAVELET TRANSFORM AS A PREPROCESSOR AND ARTIFICIAL NEURAL NETWORKS
In this paper, a fault diagnosis system based on discrete wavelet transform (DWT) and artificial neural networks (ANNs) is designed to diagnose different types of fault in gears and bearings. DWT is an advanced signal-processing technique for fault detection and identification. Five features of wavelet transform RMS, crest factor, kurtosis, standard deviation and skewness of discrete wavelet co...
متن کاملOn the development of a sliding mode observer-based fault diagnosis scheme for a wind turbine benchmark model
This paper addresses the design of an observer-based fault diagnosis scheme, which is applied to some of the sensors and actuators of a wind turbine benchmark model. The methodology is based on a modified sliding mode observer (SMO) that allows accurate reconstruction of multiple sensor or actuator faults occurring simultaneously. The faults are reconstructed using the equivalent output err...
متن کاملOn the development of a sliding mode observer-based fault diagnosis scheme for a wind turbine benchmark model
This paper addresses the design of an observer-based fault diagnosis scheme, which is applied to some of the sensors and actuators of a wind turbine benchmark model. The methodology is based on a modified sliding mode observer (SMO) that allows accurate reconstruction of multiple sensor or actuator faults occurring simultaneously. The faults are reconstructed using the equivalent output err...
متن کامل