Electric Heating Cable Fault Testing System Based on Wavelet Packet and RBF Neural Network
A new method for testing of the electric heating cable fault was proposed,which was based on the wavelet packet and RBF (radial basis function) neural network. The principle used for testing the short-circuit fault of the electric heating cable was described. The flow chart of the detecting system was given. Experimental results showed that the method, which combined the wavelet packet and RBF neural network, could be used to improve the effectiveness of locating the electric heating cable fault.
The Application of Wavelet Transform in Electrical Heating Cable Trouble-shooting Testing
A new trouble-shooting testing method for electrical heating cable based on dyadic wavelet transform is proposed. The paper analyzes the wavelet transform theory used in trouble-shooting testing method. The feature of dyadic wavelet transform is analyzed .The process of denoising and fault location is introduced in detail. The experimental result is analyzed. This method can be used to find the trouble-shooting of the cable rapidly and accurately. It is very important to trouble-shooting testing for electrical heating cable.
Research of Cable Fault Detection with Wavelet Transform
The methods of cable fault location,fault recognition,system modeling,and information fusion are researched deeply based on the theories of wavelet.Wavelet transform has the merits of time-frequency localization,especially adapted to detect singular signal.The properties of the wavelet transform and the discrete dyadic wavelet transform are discussed,and a fast wavelet algorithm for one-dimensional signals is described.Some applications of wavelet transform in the diagnosis of mechanical equipment are given.When fault exits in high voltage transmission line,how to examine the cable fault fleetly and accurately becomes an important research task in automatic system,so a new method is put forward,by which fault phase detection is accomplished through distinguishing the fault features of modulus maximum of wavelet transform of current traveling waves.Wavelet analysis overcomes the defect that the Fourier transformation cannot analyze time-frequency localization of signal simultaneously, also it has ability of distilling signal characteristic,especially having advantages in processing transient signals or faint signals.Results of analysis through EMTP prove this method has high precision.