In this paper, the vehicle faults are estimated and diagnosed by introducing wavelet transform, based on the state-space method. It monitors the state of railway vehicle suspension system, establishes a vertical dynamic state-space model of railway-vehicle system to identify the parameters of vehicle suspension system. The simulation results show that, in the circumstances of the change of the ...

Forest fires are amongst the significant causes threatening our environment degradation nowadays. Current fire detection systems lack the capability of fire triggering detection from its early stages. Wireless sensor networks (WSN) as a solution letting to gather sensory data measurements, such as humidity and temperature, from all points of forest continuously, and, provide reliable and depend...

Abstract Analog ICs in general have many performance metrics that depends on multitude of device parameters. Parametric yield loss is often a problem in analog IC designs, where a significant portion of ICs manufactured fail specification test due to variation in process parameters. Parametric faults are mainly caused by statistical fluctuations in the manufacturing process. It causes the analo...

This paper presents a model adjustment and a multi-model based fault diagnosis approach. Both methods are based on the same idea. A physical model of the process is altered such that it mimics the behavior of the process in the presence of certain faults. A number of these modified models, each governing a different fault condition, are evaluated and the model with the smallest output error is ...

to meet increasing demand for higher reliability in power electronics converters applicable in electric vehicles, fault detection (FD) is an important part of the control algorithm. In this paper, a model based open transistor fault diagnosis method is presented for a voltage-source inverter (VSI) supplying a five-phase PM motor drive. To realize this goal, a model based observer is designed to...

This paper presents a new approach for fault detection and classification in transmission line using Decision Tree (DT). The DT based fault detection algorithm uses 1/4th cycle data of fault currents from fault inception, to generate the optimal decision tree for fault detection. Similarly, the DT based classification algorithm takes half cycle data from fault inception of three phase currents ...

This paper analyses two different approaches of fault distance location in a double circuit transmission lines, using artificial neural networks. The single and modular artificial neural networks were developed for determining the fault distance location under varying types of faults in both the circuits. The proposed method uses the voltages and currents signals available at only the local end...

As the component parameters of analog circuits are influenced by tolerance, a soft fault-concept diagnosis model in this paper, which is based on the qualitative concepts of cloud model theory, is proposed to achieve the complete description of fault states and the fast diagnosis. The diagnosis model uses the cloud transform method to represent the conceptual soft classification of the multiple...

The fault diagnosis of rotating machinery has attracted considerable research attention in recent years because such components as bearings and gears frequently suffer failure, resulting in unexpected machine breakdowns. Signal processing-based condition monitoring and fault diagnosis methods have proved effective in fault identification, but the revelation of faults from the resulting signals ...

We scale the various parameters deening a 3D fault model (i.e. characteristic distance and time of a state friction law, size and aspect ratio of the fault, medium impedance) and derive two dimensionless parameters governing the typical dynamics of the fault through single or multiple ruptures. The diier-ent faulting regimes are illustrated by a series of numerical simulations. As the parameter...