Distribution network equipment health diagnosis method for multi-source information fusion analysis
A diagnostic method and healthy technology, applied in information technology support systems, resources, data processing applications, etc., can solve the problems that do not involve the classification technology of power distribution equipment health status, the lack of background data analysis and processing, and the single power-taking method of monitoring terminals, etc. problems, to achieve the effect of improving the reliability of the distribution network and the lean level of operation and maintenance, reducing the risk of failure and the cost of operation and maintenance
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[0031] First of all, it needs to be explained that at present, the data fusion methods of fault diagnosis can be mainly divided into: Bayesian theorem data fusion fault diagnosis method, fuzzy data fusion fault diagnosis method, D-S evidence theory data fusion fault diagnosis method, neural network data fusion fault diagnosis method, etc. Fusion fault diagnosis method. Data fusion fault diagnosis has unique advantages in improving the diagnostic accuracy, but it also has limitations. It is difficult to determine the prior probability in the Bayesian method; in fuzzy fault diagnosis, there are certain subjective factors in the selection of the influence weight of each sensor, such as improper selection will affect the accuracy of diagnosis; in the D-S evidence theory, the fault reliability function There are also human factors in the determination of the neural network data fusion, not only the difficulty of determining the value of the fault membership, but also the difficulty...
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