{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T04:20:58Z","timestamp":1769919658106,"version":"3.49.0"},"reference-count":40,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T00:00:00Z","timestamp":1733097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFF1302501-04"],"award-info":[{"award-number":["2022YFF1302501-04"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["31770758"],"award-info":[{"award-number":["31770758"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2022YFF1302501-04"],"award-info":[{"award-number":["2022YFF1302501-04"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31770758"],"award-info":[{"award-number":["31770758"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The unique magnetothermal properties of magnetic nanoparticles enable the development of a high-precision, real-time, noninvasive temperature measurement method with significant potential in the biomedical field. Based on a low-frequency alternating magnetic field excitation model, we construct two additional magnetic field excitation models\u2014alternating current\u2013direct current superposition and dual-frequency superposition\u2014to extract harmonic amplitude components from the magnetization response. To increase the accuracy of harmonic information acquisition, the effects of the truncation error, excitation magnetic field frequency, and amplitude are thoroughly analyzed, and optimal parameter values are selected to minimize the error. A single algorithm is designed for temperature inversion, and a joint algorithm is proposed to optimize the performance of the single algorithm. Under low-frequency alternating-current magnetic field excitation, the autonomous group particle swarm optimization method achieves superior real-time performance in terms of temperature inversion and running time. Compared with the opposition learning gray wolf optimizer and particle swarm optimization\u2013gray wolf optimization, the proposed method achieves reductions of 52% and 68%, respectively. Additionally, under dual-frequency superimposed magnetic field excitation, a higher temperature inversion accuracy is achieved compared with that of the particle swarm optimization\u2013gray wolf optimization algorithm, reducing the error from 0.237 K to 0.094 K.<\/jats:p>","DOI":"10.3390\/s24237716","type":"journal-article","created":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T06:38:25Z","timestamp":1733294305000},"page":"7716","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A High-Precision Real-Time Temperature Acquisition Method Based on Magnetic Nanoparticles"],"prefix":"10.3390","volume":"24","author":[{"given":"Yuchang","family":"Zhu","sequence":"first","affiliation":[{"name":"School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Ke","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yijing","family":"Wei","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao","family":"Zheng","sequence":"additional","affiliation":[{"name":"CAS State Key Laboratory of Forest and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Chen, P.M., Pan, W.Y., Wu, C.Y., Yeh, C.Y., Korupalli, C., Luo, P.K., Chou, C.J., Chia, W.T., and Sung, H.W. 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