Induction Infrared Thermography and Thermal-Wave-Radar Analysis for Imaging Inspection and Diagnosis of Blade Composites
| Autor: | Ruizhen Yang, Nichen Wang, Yunze He, Xuan Wu, Shoudao Huang, Andreas Mandelis |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Turbine blade
Infrared Machine vision Computer science Acoustics Carbon fibers 02 engineering and technology law.invention law Nondestructive testing Radar imaging 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Radar business.industry 020208 electrical & electronic engineering Delamination Condition monitoring Photothermal therapy 021001 nanoscience & nanotechnology Thermal conduction Computer Science Applications Electromagnetic induction Visual inspection Control and Systems Engineering visual_art Thermography visual_art.visual_art_medium 0210 nano-technology business Information Systems |
| Zdroj: | IEEE Transactions on Industrial Informatics. 14:5637-5647 |
| ISSN: | 1941-0050 1551-3203 |
| DOI: | 10.1109/tii.2018.2834462 |
| Popis: | Condition monitoring, nondestructive testing, and fault diagnosis are currently considered crucial processes for on-condition maintenance (OCM) to increase the reliability and availability of wind turbines and reduce the wind energy generation cost. Carbon fiber reinforced plastics (CFRPs) have been increasingly used to fabricate wind turbine blades. Delamination-type damage is inevitable during manufacture or in-service of a CFRP blade. This inner (subsurface) flaw, usually difficult to be detected by artificial visual inspection or machine vision based on CCD or CMOS, severely degrades the load-bearing capacity of a blade. Induction infrared thermography (IIT) is an emerging infrared machine vision inspection technology, which has the capability of insight to CFRP based on electromagnetic induction and heat conduction. This paper introduces photothermal thermal-wave radar (TWR) nondestructive imaging (NDI) to IIT, based on cross-correlation (CC) pulse compression and matched filtering and applies TWR principles to CFRP imaging inspection and diagnosis. The experimental studies carried out under the transmission mode have shown that TWR B-scan and phasegram can be used to inspect and diagnose subsurface delaminations in CFRP with improved signal-to-noise ratio (SNR) and shape identification. As a new machine vision inspection method, TWRI will play an important role in the OCM of the wind turbine blade. |
| Databáze: | OpenAIRE |
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