This paper develops the intelligent fault diagnosis system of reciprocating pump. The system takes fault diagnosis system as the core, using the Visual c++ as the software language. The software controls the data acquisition of pressure, position and flow signal synchronously. The different fault types corresponding signal curve is also different, so the main fault signal is pressure signal, fl...

Anomalous propagation echo belongs to representative non-precipitation echoes which have very similar characteristics of precipitation echoes. It occurs due to superrefraction or ducting phenomenon of radar beam by temperature or humidity. There are a lot of ongoing researches about detecting and removing the anomalous propagation echo in radar data in order to improve accuracy of data analysis...

In this paper a new method for adaptive synthesis of a smooth orthogonal wavelet, using fast neural network and genetic algorithm, is introduced. Orthogonal lattice structure is presented. A new method of supervised training of fast neural network is introduced to synthesize a wavelet with desired energy distribution between output signals from low–pass and high–pass filters on subsequent level...

In this paper, a wavelet-based neural network classifier for recognizing power quality disturbances is implemented and tested under various transient events. The discrete wavelet transform (DWT) technique is integrated with the probabilistic neural network (PNN) model to construct the classifier. First, the multi-resolution analysis (MRA) technique of DWT and the Parseval’s theorem are employed...

In this paper, a wavelet-based neural network (WNN) classifier for recognizing EEG signals is implemented and tested under three sets EEG signals (healthy subjects, patients with epilepsy and patients with epileptic syndrome during the seizure). First, the Discrete Wavelet Transform (DWT) with the Multi-Resolution Analysis (MRA) is applied to decompose EEG signal at resolution levels of the com...

Wavelet neural network (WNN) is a combination of wavelet analysis and neural network and has the strong fault tolerance, the strong anti-jamming and the strong adaptive ability. However, WNN is likely to trap local minimum and premature convergence. According to these shortcomings, particle swarm optimization (PSO) algorithm is applied to wavelet neural network (WNN) and has good effect. This p...

The processing of spatial information by the visual system shows a number of similarities to the wavelet transforms that have become popular in applied mathematics. Over the last decade, a range of studies has focused on the question of ‘why’ the visual system would evolve this strategy of coding spatial information. One such approach has focused on the relationship between the visual code and ...

A technology for technical diagnostics based on the multivariate analysis of system status is under consideration. It combines the capabilities of wavelet transforms and relaxation neural networks. Important practical advantages of the proposed technique include the capability to recognise damage using only a few training patterns and the possibility to apply the method for non-stationary input...