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
Pending Publication Date: 2022-01-28
国网河北省电力有限公司雄安新区供电公司 +2
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However, the existing systems often have the following problems: (1) The monitoring terminal has a single way of taking power; (2) It is difficult to collect data and transmit; (3) The product integration is poor; (4) Lack of background data analysis and processing
However, none of the technical solutions disclosed above involve the classification technology of power distribution equipment health status, and do not involve technical details such as diagnosis of distribution network equipment health information obtained through the process of multi-source information fusion analysis.
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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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The invention provides a distribution network equipment health diagnosis method for multi-source information fusion analysis, which is used for obtaining the health state level of distribution equipment in a distribution cable health diagnosis system, and comprises the following steps: obtaining signals of each influence factor dimension of the distribution network equipment through a sensing layer; the signals of the influence factor dimensions comprise terahertz time domain signals, partial discharge signals and temperature signals; transmitting the signal of each influence factor dimension to a data layer through a transmission layer; completing feature extraction of the signal of each influence factor dimension in the data layer to obtain an influence factor vector of each dimension; and using a fuzzy evaluation method to obtain a comprehensive evaluation result taking the distribution network equipment as an evaluated object. A fuzzy data fusion method is adopted to evaluate the health state of the system, and a high-quality diagnosis system can be obtained during practical application of multi-source information fusion analysis.
Description
technical field [0001] The invention belongs to the technical field of digital active distribution network, and in particular relates to a computer processing method for a distribution cable health diagnosis system. Background technique [0002] In the digital active distribution network with power cables as the main body, power distribution equipment such as power cables are mainly distributed in the underground comprehensive utility gallery and the ground operating environment. Due to the uneven level of cable installation technology and the complex operating conditions of power equipment, the risk of urban distribution network failures continues to increase. If the power equipment fails, such as insulation breakdown, it will affect the reliability of power supply and power quality of the distribution network. [0003] Traditional distribution network operation and maintenance focus on equipment status detection for overdue service or abnormal working conditions. However...
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IPC IPC(8): G06Q10/06G06Q50/06G06F17/16G06K9/00G06K9/62G06V10/80G01R31/08G01R31/12
CPCG06Q10/06393G06Q50/06G06F17/16G01R31/083G01R31/086G01R31/088G01R31/1272G06F2218/08G06F18/253Y04S10/52
Inventor 池威威刘海峰路鹏程钟成贾志辉李志雷
Owner 国网河北省电力有限公司雄安新区供电公司
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