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Fault management is a key research part in the field of distributed applications management. Fault Management based on active probing is divided into two phases: fault detection and fault diagnosis, considering probe costs in these two phases, this paper proposes two algorithms: PSFD and PSFL. Finally, MATLAB is used as the experiment platform and BNT toolkit is adopted. Simulations show the effectiveness...
High-voltage circuit breaker is the most important control and protection equipment. Doing fault diagnosis to high-voltage is very important to realize the power system stable and reliable running. The improved BP neural network momentum gradient descent algorithm was used in high-voltage fault diagnosis comparing with traditional BP neural network in this paper. The simulation indicated that this...
In this paper, 6 degrees of freedom vibration model of hoist cage excited by steelwork faults was established first. Then horizontal and vertical vibration characteristics under local faults and whole faults were simulated through MATLAB, based on which a wavelet singularity method was proposed to process the vibration to determine the position and seriousness of the steelwork faults. Finally, simulation...
High-voltage circuit breakers are important electrical equipments which play the role of protection and control in the power network. In order to make the power system operate in a stable and reliable way, it is of great significance to make online fault diagnosis of High-voltage circuit breakers. In this paper, the improved D-S evidence theory for data fusion method was studied and used in high-voltage...
The dynamic part is failure-prone and sensitive areas in aerospace system. Based on structural stratum analysis of aerospace dynamic system, this paper analysis the traversal algorithm for tree structure using analytic hierarchy process. The fault diagnosis algorithm called GZSS-1 is put forward. Then the algorithm called GGZSS-1 is put forward based on study and ameliorate the GZSS-1. Actual application...
The paper utilizes ensemble empirical mode decomposition (EEMD) and Hilbert marginal spectrum for the fault diagnosis of the reciprocating compressor on the offshore platform of WZ12-1, aiming at the non-stationary and nonlinear characteristics of vibration signals collected from the faulty compressor. First, the EEMD algorithm self-adaptively anti-aliasing decomposes the vibration signal into a set...
There is much difficulty in fault diagnosis because of lacking of system fault samples. So this paper presents a mixed strategy of combining differential evolution algorithm with local enhanced operator with the optimization of the parameters of support vector machine. For the diesel engine valve clearance fault diagnosis, the measured diesel engine valve vibration signals data after wavelet transform...
Fault Diagnosis for radar's transmitter is very crucial, yet very difficult. Transmitter is complex electrical equipment whose units are full of uncertain factors and information. The paper puts forward a new fault diagnosis method based on Bayesian network for the transmitter. The cause-result graph of transmitter is gained by analyzing its structure firstly, and then the fault model based on Bayesian...
This paper presents fault diagnosis method in aluminum electrolysis based on Modified Elman Neural Network. According to the mechanism of fault occurring in aluminum electrolysis, time and type of fault is determined by neural network. Simulation results show that the fault diagnosis method based on Modified Elman Neural Network can predict fault during aluminum electrolysis rapidly and accurately...
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