Wind driven generator CMS vibration monitoring and early warning method and system and medium
The vibration data of the wind turbine group was analyzed through the CNN-AE convolutional automatic encoder model, which solved the problem of poor timeliness of vibration data analysis in the prior art, real-time evaluation of the fan operating status and vibration warning were realized, ensuring the safe and reliable operation of the fan.
CN119641568APending Publication Date: 2025-03-18DONGFANG ELECTRIC XINNENG TECH (CHENGDU) CO LTD
Patent Information
- Application Number
- CN202510077210.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-17
- Publication Date
- 2025-03-18
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Figure CN119641568A_ABST
Abstract
The invention provides a wind driven generator CMS vibration monitoring and early warning method. The method comprises the steps of obtaining vibration data of a historical fan transmission chain health state; the vibration data are preprocessed to obtain time domain data and frequency domain data, the time domain data and the frequency domain data are input into a CNN-AE convolution automatic encoder model together with fan working condition data, a monitoring state feature space of a fan is trained, and therefore an early warning line of the fan is determined to obtain an early warning model; and inputting the vibration data and the working condition data which are acquired in real time into the trained early warning model, and completing early warning. Through the method, health state evaluation of the key rotating large component of the wind generating set can be realized, and safe and reliable operation of a fan is ensured.
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Citation Information
Cited By
Wind driven generator vibration fault analysis method, system and device and electronic equipment
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