Wind turbine converter fault diagnosis method based on wavelet transformation and DBN

A technology of wavelet transform and fault diagnosis, applied in the field of power system, can solve problems such as application limitations of model methods, difficulty in establishing mathematical models of systems, and complex systems

Inactive Publication Date: 2018-01-26
CHONGQING UNIV
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Problems solved by technology

With the development of technology, the system becomes more and more complex, and it becomes more and more diff...

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  • Wind turbine converter fault diagnosis method based on wavelet transformation and DBN
  • Wind turbine converter fault diagnosis method based on wavelet transformation and DBN

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Embodiment Construction

[0010] In order to achieve the above object, the present invention provides the following technical solutions: The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0011] Step 1, run the model under different faults such as figure 1 As shown, the current of the three-phase power on the machine side is measured.

[0012] Step 2, using wavelet transform to decompose the current signal of the three-phase electricity at each scale to obtain the corresponding energy coefficients at each scale.

[0013] By properly choosing the scale factor and translation factor, a scalable window can be obtained, and the proper choice of basic wavelet can make the wavelet transform have the ability to characterize the local characteristics of the signal in both the time domain and the frequency domain. According to this feature, the multi-resolution feature can be applied to the extraction of power spectrum features ...

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Abstract

The present invention relates to a wind turbine converter fault diagnosis method based on wavelet transformation and a DBN and belongs to the field of wind turbine converter fault diagnosis based on wavelet transformation and DBNs and provides a wind turbine converter fault diagnosis method based on wavelet transformation and a DBN. As the installed capacity of wind turbines increases, the wind turbines occupy an increasingly high portion in a power grid, and thus, fast identification of the locations of wind turbine faults is pivotal to the stable operation of the wind turbines and the powergrid. According to the method, multi-scale analysis is performed on signals through using wavelet transformation; fault signal feature vectors are extracted; and the DBN performs supervised learning on the feature vectors, so that a fault identification model can be obtained. The method can excellently identify converter faults.

Description

technical field [0001] The invention belongs to the field of electric power systems, and relates to a fault diagnosis method for a fan converter based on wavelet transform and DBN. Background technique: [0002] In recent years, with the rapid development of human society, people's demand for energy has risen rapidly. The rapid and massive consumption of traditional fossil energy has led to increasingly serious problems such as environmental pollution and the greenhouse effect in the world. At the same time, due to the non-renewable characteristics of fossil energy itself, green and renewable wind energy will definitely become the priority development choice of various countries. Facts have also proved that wind energy has become the fastest growing renewable energy in the world today. [0003] With the rapid increase of the installed capacity of the wind power generation system, the failure rate of the wind power generation system is also increasing. Due to working under...

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Application Information

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IPC IPC(8): G01R31/34
Inventor 柴毅魏善碧刘延兴何昊阳孙秀玲何馨
Owner CHONGQING UNIV
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