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Health management and fault early warning method for wind turbine generator

A technology of health management and fault early warning, applied in the direction of wind turbines, wind turbine monitoring, engines, etc., can solve the problems that affect the efficiency of wind turbine power generation and the profitability of wind farms

Inactive Publication Date: 2021-04-30
THERMAL POWER TECH RES INST OF CHINA DATANG CORP SCI & TECH RES INST
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  • Claims
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Problems solved by technology

Seriously affect the power generation efficiency of wind turbines and the profitability of the entire wind farm

Method used

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  • Health management and fault early warning method for wind turbine generator
  • Health management and fault early warning method for wind turbine generator
  • Health management and fault early warning method for wind turbine generator

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Embodiment Construction

[0027] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0028] This embodiment provides a wind turbine health management and fault early warning method, including:

[0029] The health feature extraction of the complete wind turbine:

[0030] Based on the power, wind speed, main shaft speed and pitch angle parameters in the SCADA operating parameters, the health characteristics of the whole wind turbine are extracted to characterize the health status of the wind turbine;

[0031] Feature extraction for fan-specific faults:

[0032] Based on the generator bearing temperature, torque speed, hydraulic oil temperature, yaw position and other parameters in the SCADA operating parameters and the vibration, speed, and acoustic emissi...

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Abstract

The invention relates to a health management and fault early warning method for a wind turbine generator. The method comprises the steps: extracting health features of a whole fan; extracting features of specific faults of the fan; monitoring the overall health state of the fan; diagnosing a fault mode; and predicting a fan fault trend: predicting the fault development trend of the fan by adopting a Bayesian network, a multiple regression analysis method or a neural network according to different fault types, and timely arranging maintenance at the early stage of the fault so as to avoid shutdown caused by serious fault. Based on data mining, machine learning and other means, the operation mode of the fan is automatically recognized, and the health condition and the working performance of the fan are diagnosed in real time. Meanwhile, the fan fault mode is determined from historical data, defects and hidden dangers of key components are found and recognized in time, a basis is provided for efficiently arranging maintenance resources in a wind field, then health management and reliability maintenance of wind power equipment are achieved, and the service life of the components is prolonged.

Description

technical field [0001] The invention belongs to the technical field of wind power generation, and in particular relates to a health management and fault early warning method of a wind turbine. Background technique [0002] In recent years, the development speed of the wind power industry has slowed down significantly, and facing the status quo of "the same price for wind and fire", how to improve the level of wind power operation and how to reduce operation and maintenance costs have become the primary issues facing the entire industry. The reliability of large wind turbine components has a significant impact on the performance and safety of the unit, especially blades, main shafts, generators, gearboxes, frequency converters, etc., which have a high failure rate, long downtime, and relatively high failure recovery costs. cause large economic losses. For example, the maintenance cost of a gear box failure is close to 1 million yuan, which is more than 60% of the annual powe...

Claims

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Application Information

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IPC IPC(8): F03D17/00
CPCF03D17/00
Inventor 叶翔阴晓艳王然宋寅武永鑫
Owner THERMAL POWER TECH RES INST OF CHINA DATANG CORP SCI & TECH RES INST
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