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Photovoltaic inverter fault diagnosis method

A photovoltaic inverter and fault diagnosis technology, applied in neural learning methods, instruments, special data processing applications, etc., can solve problems such as affecting the effect of fault diagnosis, and achieve the effect of improving the effect, reducing the cost, and improving the performance.

Inactive Publication Date: 2017-08-08
HOHAI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the above methods are rarely used in the fault diagnosis of photovoltaic inverters, and these methods also have their own advantages and disadvantages, which will affect the effect of fault diagnosis

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Embodiment Construction

[0028] Below in conjunction with accompanying drawing, technical scheme of the present invention is described in further detail:

[0029] The idea of ​​the present invention is aimed at the objective fact that the application of intelligent fault diagnosis methods in the field of photovoltaic power station equipment fault diagnosis is less, and the traditional BP neural network has defects such as slow convergence speed, non-convergence of the network, and easy to fall into local minimum values. , a photovoltaic inverter fault diagnosis method based on the improved BP neural network is proposed. First, the L-M algorithm is used to improve the traditional BP neural network, and then the photovoltaic inverter fault data (ie training samples) is used for network learning to establish a photovoltaic inverter. Inverter fault diagnosis model, and finally through the test data to verify the effect of the diagnosis model, to realize the intelligence of photovoltaic inverter fault diagn...

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Abstract

The invention discloses a photovoltaic inverter fault diagnosis method. Firstly, a conventional BP neural network is improved with an L-M algorithm, photovoltaic inverter fault data (a training sample) are utilized for network learning, a photovoltaic inverter fault diagnosis model is established, and finally, the effect of the diagnosis model is verified according to test data. The BP neural network is successfully applied to the fault diagnosis field of a photovoltaic inverter, the intelligent requirements are met, besides, the BP neural network is improved, defects of conventional BP neural networks are overcome, and the accuracy and the validity of photovoltaic inverter fault diagnosis are improved.

Description

technical field [0001] The invention relates to the technical field of fault diagnosis, in particular to a photovoltaic inverter fault diagnosis method, in particular to a photovoltaic inverter fault diagnosis method based on an improved BP neural network. Background technique [0002] Fault diagnosis, as the name suggests, is to analyze, evaluate and draw conclusions about what is wrong with the system, what is the cause of the fault, how serious the fault is, and the solution to the fault. And technology, use the system to resolve redundancy, and complete the diagnostic analysis. Obviously, from the definition of fault diagnosis technology, it can be concluded that the task of fault diagnosis mainly has four aspects, namely fault detection, fault separation, fault evaluation and fault decision-making. Fault detection means that when the system is running abnormally, the fault diagnosis system can judge that the system has a fault according to various data parameters of th...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N3/08
CPCG06N3/084G06F30/20Y04S10/50
Inventor 吴学文辛嘉熙原帅秦操
Owner HOHAI UNIV