Health monitoring of wind turbine blades in operation using three-dimensional digital image correlation. (1st September 2019)

• Record Type: Journal Article
• Authors: Wu, Rong; Zhang, Dongsheng; Yu, Qifeng; Jiang, Yuxi; Arola, Dwayne
• Is Part Of: Mechanical systems and signal processing. Volume 130(2019)
• Page Start: 470
• Page End: 483
• Publication Date: 2019-09-01
• Subjects: Digital image correlation -- Full-field measurement -- Health monitoring -- Wind turbine blade; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2019.05.031
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: A 3D-DIC method capable of determining full-field deformation with rotating structure was proposed. Full-field displacement and strain tests were performed on a 5 kw, 4 m diameter wind turbine. A fault detection method was proposed based on relative deformation of the turbine blades during operation. A diagnosis of the blade health was conducted in both the time and frequency domains. The approach can serve as an effective non-contact method for health monitoring of wind turbine blades. Abstract: Wind turbine blades are subjected to fluctuating loads during operation, which makes them vulnerable to reduced performance and mechanical failures. In addition, the maintenance of blades is time-consuming and expensive. In this paper, a novel and economic optical technique based on three-dimensional digital image correlation (3D-DIC) is described for monitoring the health of wind turbine blades. A fault detection method is proposed based on the relative deformation of the turbine blades during operation. To validate the approach, a 5 kw wind turbine with 4 m diameter was evaluated using 3D-DIC. The rotor blades were prepared with a random black-and-white pattern of dots and two digital cameras were located in front of the wind turbine to document the rotor blade deformation. The full-field dynamic parameters of displacement and strain were obtained and a diagnosis of the blade health was conducted in both the time and frequency domains. Results showed that 3D-DIC can serve as an effective non-contact method for monitoring the health of wind turbine blades during operation.