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. 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 coefficients of...

Since the neutrosophic number consists of its determinate part d and its indeterminate part eI denoted by N = d + eI, it is very suitable for dealing with real problems with indeterminacy. Therefore, this paper proposes the exponential similarity measure of neutrosophic numbers and a fault diagnosis method of steam turbine by using the exponential similarity measure of neutrosophic numbers. By ...

This paper proposes a dimension root distance and its similarity measure of single-valued neutrosophic sets (SVNSs), and then develops the fault diagnosis method of hydraulic turbine by using the dimension root similarity measure of SVNSs. By the similarity measure between the fault diagnosis patterns and a testing sample with single-valued neutrosophic information and the relation indices, we ...

According to the design procedure of fault self-diagnosis system and features of automatic transmission system, the list of relation and mapping between fault symptoms and fault causes are made in this paper. Applying the approach of fault self-diagnosis based on fuzzy neural network, fault diagnosis of the automatic transmission electronic control system is realized. The structure of fuzzy neu...

Condition monitoring and protection methods based on the analysis of the machine's current are widely used according to non-invasive characteristics of current transformers. It should be noted that, these sensors are installed by default in the machine control center. On the other hand, condition monitoring based on mathematical methods has been proposed in literature. However, they are model b...

Regarding to the complexity and diversity of analog circuit fault, a principal component analysis(PCA) and particle swarm optimization(PSO) support vector machine(SVM) analog circuit fault diagnosis method is proposed. It uses principal component analysis and data normalization as preprocessing, then reduced dimension fault feature is putted into support vector machine to diagnosis, and particl...

In order to diagnose transformer fault efficiently and accurately, a dynamic integrated fault diagnosis method based on Bayesian network is proposed in this paper. First, an integrated fault diagnosis model is established based on the causal relationship among abnormal working conditions, failure modes, and failure symptoms of transformers, aimed at obtaining the most possible failure mode. And...

Abstract— An important aspect of network management is fault management, i.e., determining, locating, isolating, and correcting faults in the network. We study modeling of communication network protocols, and their fault detection, fault identification and fault location in the discrete event systems diagnosis framework. Our approach provides a systematic way of performing fault diagnosis in ne...

To achieve fully autonomous systems, fault tolerance is often employed. Fault tolerance is the ability to continue operation in the presence of faults. Fault diagnosis is an essential component of fault tolerance, especially for autonomous robotics. It is the process of determining as much information as possible about the fault, especially the origin of the fault. However, a real time fault di...