Please use this identifier to cite or link to this item: http://archive.nnl.gov.np:8080/handle/123456789/310
Title: Novel error Outlier Method and FBG sensor based real-time low velocity impact monitoring of composite wing structure
Authors: Shrestha, Pratik
Keywords: CompositeWing
FBG sensors
Impact localization
Structural health monitoring
Error Outlier
Issue Date: 20-Dec-2018
Abstract: Real-time structural health monitoring system (SHM) to monitor low velocity impact on composite structure, which can cause barely visible impact damage, can ensure the safety and structural integrity of civil/military aircraft structure. In this dissertation, a novel error outlier method for localizing impact was proposed and several algorithms using this concept were developed. Impact localization study using 1D array fiber Bragg grating (FBG) sensor configuration were performed on a full scale composite wing of Jabiru UL-D aircraft. Impact signals were sampled using a high speed FBG interrogator at a frequency of 100 kHz. Furthermore, soft and hard-impact classification technique was developed and validated by localizing impacts delivered using trained and non-trained hammer with varying impactor hardness. The proposed method successfully classified and localized the trained hard-impacts with average error of 18.5 mm and maximum error of 41.5 mm, and the trained soft-impacts were localized with average error of 48.5 mm and maximum error of 111.0 mm. Whereas, the various non-trained impact cases were localized with average error of 80.7 mm and the maximum error ranged from 217.2 mm to 303.1 mm. The present study demonstrates the suitability of the proposed novel error outlier method based low velocity impact monitoring of trained or non-trained impact cases.
Description: A dissertation submitted to the faculty of Korea Advanced Institute of Science and Technology in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Aerospace Engineering, 2016.
URI: http://103.69.125.248:8080/xmlui/handle/123456789/310
Appears in Collections:500 Natural sciences and mathematics

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