Supervised learning method, like support vector machine (SVM), has been widely applied in diagnosing known faults, however this kind of method fails to work correctly when new or unknown fault occurs. Traditional unsupervised kernel clustering can be used for unknown fault diagnosis, but it could not make use of the historical classification information to improve diagnosis accuracy. In this pa...

The soft fault diagnosis of nonlinear analog circuits is an important guarantee of the stable and reliable operation of electronic products. In view of the low accuracy and heavy computation load of current soft fault diagnosis methods for nonlinear analog circuits, this paper presents a soft fault diagnosis method for nonlinear analog circuits based on fractal theory. Analyzing the single-frac...

Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is a crucial task. In this paper a novel machinery fault diagnosis approach based on a statistical lo...

Ocean economy plays a crucial role in the strengthening maritime safety industry and in the welfare of human beings. Electric Submersible Pumps (ESP) have been widely used in floating platforms on the sea to provide oil for machines. However, the ESP fault may lead to ocean environment pollution, on the other hand, a timely fault diagnosis of ESP can improve the ocean economy. In order to meet ...

This paper studies a fault tolerant control strategy for a four wheel skid steering mobile robot (SSMR). Through this work the fault diagnosis procedure is accomplished using structural analysis technique while fault accommodation is based on a Recursive Least Squares (RLS) approximation. The goal is to detect faults as early as possible and recalculate command inputs in order to achieve fault ...

A novel thruster fault diagnosis and accommodation method for open-frame underwater vehicles is presented in the paper. The proposed system consists of two units: a fault diagnosis unit and a fault accommodation unit. In the fault diagnosis unit an ICMAC (Improved Credit Assignment Cerebellar Model Articulation Controllers) neural network information fusion model is used to realize the fault id...

We propose a StochAstic Fault diagnosis AlgoRIthm, called Safari, which trades off guarantees of computing minimal diagnoses for computational efficiency. We empirically demonstrate, using the 74XXX and ISCAS85 suites of benchmark combinatorial circuits, that Safari achieves several orders-of-magnitude speedup over two well-known deterministic algorithms, CDA∗ and HA∗, for multiple-fault diagno...

Aiming at the problem of diagnosis difficulty caused by too many factors of woodworking machinery system, a kind of diagnosing method based on fault phenomenon was presented. The research on woodworking machinery system fault phenomenon space arrived at conclusion that the emergency of each fault phenomenon subject to 0-1 distribution. Therefore, phenomenon vector corresponding to each fault fo...

According to intelligent complementary ideas, a new transformer fault diagnosis method is proposed based on rough set (RS) and Bayesian optimal classifier in this paper. Through RS reduction, the diagnostic decision table is simplified and fault symptoms information is compressed, and the minimal decision rules can be obtained. In light of the minimal decision rules, the complexity of Bayesian ...

A reliable and accurate diagnosis of inter-turn short circuit faults is a challenging problem in the area of fault diagnosis of electrical machines. The purpose of this challenge is to be more efficient in fault detection and to provide a reliable method with low-cost sensors and simple numerical algorithms which not only detect the occurrence of the fault, but also locate its position in the w...