Unlock instant, AI-driven research and patent intelligence for your innovation.

A wind turbine fault diagnosis system and method

A fault diagnosis system and a technology for wind turbines, applied in the field of signal filtering, can solve problems such as not satisfying the sampling theorem, large signal frequency changes, complex system algorithms, etc., achieving good anti-aliasing tracking filtering effect, small signal frequency changes, and system The effect of simple algorithm

Active Publication Date: 2017-05-03
ELECTRIC POWER RESEARCH INSTITUTE, CHINA SOUTHERN POWER GRID CO LTD +1
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] In addition, the traditional fault diagnosis system cannot accurately diagnose the faults of wind turbines, and there are still many defects in the fault diagnosis systems and methods of wind turbines on the domestic market: 1. The system algorithm is complex; 2. The spectrum obtained by sampling contains high The aliasing of the order quantity, the filtering effect is poor; 3. The signal frequency changes greatly, and the sampling upper limit frequency cannot be changed, and there is a situation that does not satisfy the sampling theorem. The sampling theorem indicates that the sampling frequency must be greater than twice the frequency of the sampled signal

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A wind turbine fault diagnosis system and method
  • A wind turbine fault diagnosis system and method
  • A wind turbine fault diagnosis system and method

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment

[0073] From image 3 It can be seen that the frequency of the fundamental frequency signal of the rotating shaft changes rapidly, which is used to simulate the speed change (rapid change) of the actual wind turbine starting and stopping and the actual speed fluctuation under the condition of constant speed control. image 3 Each from 0 - To 0 + The simulation time point is the time point when the actual shaft rotates exactly one revolution. Due to adjacent 0 - To 0 + The time interval is different (because the speed changes), therefore, the time for each rotation of the shaft also changes.

[0074] From Figure 4 It can be seen that the original simulation signal contains strong background noise and a variety of related synchronization / non-synchronization signals, coupled with the rapid change of the speed, which makes it difficult to distinguish the regularity information contained in the original signal in the time domain diagram.

[0075] Figure 5 Yes Figure 4 The signal is the...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses fault diagnosing system and method for a wind generation set. The system comprises the wind generation set, a vibration sensor, a rotating speed sensor and a signal acquiring card and computer signal processing system. The method comprises the steps of (1), generating a vibration simulating signal of the wind generation set; (2) setting initializing parameters; (3) treating a zero crossing point of a baseband signal of a rotating shaft as a key phase signal of the actual wind generation set; (4) determining whether to conduct variable upper limit type anti-aliasing filtering tracking for a composite vibration signal; (5) re-sampling the time; (6) re-sampling vibration signal amplitude; (7) calculating time domain synchronizing average value; (8) repeating steps from (4) to (7); and (9) comparing different results above. The fault diagnosing system and method for the wind generation set have the advantages that the anti-aliasing filtering tracking effect is obvious, an effective data processing method is provided for the fault diagnosing of the wind generation set, and the safe connection of the wind generation set in a grid and the safe operation of an intelligent micro-grid with the wind generation set are ensured.

Description

[0001] 【Technical Field】 [0002] The invention relates to the field of signal filtering, in particular to a wind turbine fault diagnosis system and method based on variable upper limit anti-aliasing tracking filter order analysis. [0003] 【Background technique】 [0004] In the context of the country's vigorous development of smart grids, wind power as an important part of smart grids has developed rapidly. With the increasing proportion of wind power capacity in the regional power grid, while wind power brings us many benefits, it also brings some adverse effects, including: it may seriously affect the power quality and the safe and stable operation of the power system , And may endanger conventional power generation methods, which are mainly manifested in large fluctuations in voltage and frequency. What is more serious is that when wind turbines are out of operation on a large scale due to excessive wind speed or a large instantaneous drop in grid voltage, it will cause unbearab...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/34
Inventor 李鹏杨苹郭晓斌许爱东雷金勇周少雄许志荣黄焘于力喻磊马溪原申展
Owner ELECTRIC POWER RESEARCH INSTITUTE, CHINA SOUTHERN POWER GRID CO LTD