{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T14:19:11Z","timestamp":1771337951420,"version":"3.50.1"},"reference-count":17,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2018,4,9]],"date-time":"2018-04-09T00:00:00Z","timestamp":1523232000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>The paper describes a novel method for the detection of damage in carbon composites as used in drone frames. When damage is detected a further novel corrective response is initiated in the quadcopter flight controller to switch from a four-arm control system to a three-arm control system. This is made possible as a symmetrical frame is utilized, which allows for a balanced weight distribution between both the undamaged quadcopter and the fallback tri-copter layout. The resulting work allows for continued flight where this was not previously possible. Further developing work includes improved flight stability with the aid of an underslung load model. This is beneficial to the quadcopter as a damaged arm attached to the main body by the motor wires behaves as an underslung load. The underslung load works are also transferable in a dual master and slave drone system where the master drone transports a smaller slave drone by a tether, which acts as an underslung load.<\/jats:p>","DOI":"10.3390\/computers7020023","type":"journal-article","created":{"date-parts":[[2018,4,10]],"date-time":"2018-04-10T13:06:08Z","timestamp":1523365568000},"page":"23","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Failure Detection of Composites with Control System Corrective Response in Drone System Applications"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4873-1000","authenticated-orcid":false,"given":"Mark","family":"Bowkett","sequence":"first","affiliation":[{"name":"Faculty of Computing, Engineering &amp; Sciences, University of South Wales, Pontypridd CF37 1DL, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6398-4340","authenticated-orcid":false,"given":"Kary","family":"Thanapalan","sequence":"additional","affiliation":[{"name":"Faculty of Computing, Engineering &amp; Sciences, University of South Wales, Pontypridd CF37 1DL, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ewen","family":"Constant","sequence":"additional","affiliation":[{"name":"Faculty of Computing, Engineering &amp; Sciences, University of South Wales, Pontypridd CF37 1DL, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,4,9]]},"reference":[{"key":"ref_1","unstructured":"Ning, W. (2015). Structural Health Condition Monitoring of Carbon Fiber Based Composite Materials Using Acoustic Emission Techniques. [Master\u2019s Thesis, College of Engineering and Physical Sciences, University of Birmingham]."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1080\/21642583.2017.1311240","article-title":"Comparative analysis of failure detection methods of composites materials systems","volume":"5","author":"Bowkett","year":"2017","journal-title":"Syst. Sci. Control Eng."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.neunet.2016.01.001","article-title":"State estimation for a class of artificial neural networks with stochastically corrupted measurements under round-robin protocol","volume":"77","author":"Luo","year":"2016","journal-title":"Neural Netw."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Bowkett, M., Thanapalan, K., and Constant, E. (2017, January 20\u201322). 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Eng."},{"key":"ref_17","unstructured":"Fabian, N., Daniel, H., and Julio, C. (2016, January 24\u201327). Resolution improvement of accelerometers measurement for drones in agricultural applications. 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