{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T00:36:37Z","timestamp":1783730197799,"version":"3.55.0"},"reference-count":20,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2022,9,7]],"date-time":"2022-09-07T00:00:00Z","timestamp":1662508800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62071328"],"award-info":[{"award-number":["62071328"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Transmitter-receiver (T-R) probes are widely used in the eddy-current testing of carbon fibre reinforced plastics (CFRP). However, T-R probes have the disadvantage of being highly sensitive to lift-off. On this basis, lift-off interference can be eliminated by differential structure. However, due to the electrical anisotropy of CFRP, the detection sensitivity of the side-by-side T-R probe and traditional R-T-R differential probe are greatly affected by the scanning angle, and the probe often needs to scan the sample along a specific path to achieve the ideal required detection effect. To solve these problems, a symmetrical dual-transmit-dual-receive (TR-TR) differential probe is designed in this paper. The detection performance of the TR-TR probe was verified by simulation and experiments. Results show that the TR-TR probe is less affected by the scanning angle and lift-off when used in CFRP defect detection, and has high detection sensitivity. However, the imaging results of the TR-TR probe do not show the defect characteristics straightforwardly. To solve this problem, a defect feature extraction algorithm is proposed in this paper. The results show that the defect feature extraction algorithm can locate and size the defect more accurately and improve the signal-to-noise ratio.<\/jats:p>","DOI":"10.3390\/s22186761","type":"journal-article","created":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T04:18:32Z","timestamp":1662610712000},"page":"6761","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Non-Destructive Testing of Carbon Fibre Reinforced Plastics (CFRP) Using a Dual Transmitter-Receiver Differential Eddy Current Test Probe"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5977-1713","authenticated-orcid":false,"given":"Ronghua","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Tiangong University, Tianjin 300387, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junyu","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Control Science and Engineering, Tiangong University, Tianjin 300387, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiyu","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Control Science and Engineering, Tiangong University, Tianjin 300387, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9796-7119","authenticated-orcid":false,"given":"Ming","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Life Sciences, Tiangong University, Tianjin 300387, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongying","family":"Fang","sequence":"additional","affiliation":[{"name":"School of Control Science and Engineering, Tiangong University, Tianjin 300387, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junhua","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Tiangong University, Tianjin 300387, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Danqi","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Tiangong University, Tianjin 300387, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ahmad, F., Awadh, M.A., Abas, M., Noor, S., and Hameed, A. 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