Abnormal Detection of Wind Turbine Operating Conditions Based on State Curves-Reference-Cited by-同舟云学术

Abnormal Detection of Wind Turbine Operating Conditions Based on State Curves

Published:2019-10 Issue:5 Volume:145 Page:06019001
ISSN:0733-9402
Container-title:Journal of Energy Engineering
language:en
Short-container-title:J. Energy Eng.

Author:

Sun Qunli¹,Liu Changliang²,Zhen Chenggang³

Affiliation:

1. Lecturer, Dept. of Automation, North China Electric Power Univ., Baoding 071003, China (corresponding author).

2. Professor, Dept. of Automation, North China Electric Power Univ., Baoding 071003, China.

3. Professor, Dept. of Computer, North China Electric Power Univ., Baoding 071003, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Waste Management and Disposal,Energy Engineering and Power Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29EY.1943-7897.0000612

Reference32 articles.

1. Influence of turbulence intensity on wind turbine power curves

2. Bi R. C. Zhou D. M. Hepburn and J. Rong. 2015. “A NBM based on P-N relationship forDFIG wind turbine fault detection.” In Proc. Int. Conf. Smart Grid and Clean Energy Technology 1–6. New York: IEEE. https://doi.org/10.1109/ICSGCE.2015.7454260.

3. Overview of Control Systems for the Operation of DFIGs in Wind Energy Applications

4. An experimental study on the applicability of acoustic emission for wind turbine gearbox health diagnosis

5. Automated on‐line fault prognosis for wind turbine pitch systems using supervisory control and data acquisition

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