{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T15:41:01Z","timestamp":1783438861277,"version":"3.54.6"},"reference-count":33,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2023,11,13]],"date-time":"2023-11-13T00:00:00Z","timestamp":1699833600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fujian Science and Technology Projects","award":["2021H0020"],"award-info":[{"award-number":["2021H0020"]}]},{"name":"Fujian Science and Technology Projects","award":["2020H0018"],"award-info":[{"award-number":["2020H0018"]}]},{"name":"Fujian Science and Technology Projects","award":["2022J01808"],"award-info":[{"award-number":["2022J01808"]}]},{"name":"Fujian Natural Science Foundation Projects","award":["2021H0020"],"award-info":[{"award-number":["2021H0020"]}]},{"name":"Fujian Natural Science Foundation Projects","award":["2020H0018"],"award-info":[{"award-number":["2020H0018"]}]},{"name":"Fujian Natural Science Foundation Projects","award":["2022J01808"],"award-info":[{"award-number":["2022J01808"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, a quadratic convolution neural network (QCNN) using both audio and vibration signals is utilized for bearing fault diagnosis. Specifically, to make use of multi-modal information for bearing fault diagnosis, the audio and vibration signals are first fused together using a 1 \u00d7 1 convolution. Then, a quadratic convolution neural network is applied for the fusion feature extraction. Finally, a decision module is designed for fault classification. The proposed method utilizes the complementary information of audio and vibration signals, and is insensitive to noise. The experimental results show that the accuracy of the proposed method can achieve high accuracies for both single and multiple bearing fault diagnosis in the noisy situations. Moreover, the combination of two-modal data helps improve the performance under all conditions.<\/jats:p>","DOI":"10.3390\/s23229155","type":"journal-article","created":{"date-parts":[[2023,11,14]],"date-time":"2023-11-14T09:46:13Z","timestamp":1699955173000},"page":"9155","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Fusion of Audio and Vibration Signals for Bearing Fault Diagnosis Based on a Quadratic Convolution Neural Network"],"prefix":"10.3390","volume":"23","author":[{"given":"Jin","family":"Yan","sequence":"first","affiliation":[{"name":"School of Marine Engineering, Jimei University, Xiamen 361021, China"},{"name":"Fujian Engineering Research Center of Marine Engine Detecting and Remanufacturing, Xiamen 361021, China"},{"name":"Provincial Key Laboratory of Naval Architecture and Ocean Engineering, Xiamen 361021, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian-bin","family":"Liao","sequence":"additional","affiliation":[{"name":"School of Marine Engineering, Jimei University, Xiamen 361021, China"},{"name":"Fujian Engineering Research Center of Marine Engine Detecting and Remanufacturing, Xiamen 361021, China"},{"name":"Provincial Key Laboratory of Naval Architecture and Ocean Engineering, Xiamen 361021, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6448-4743","authenticated-orcid":false,"given":"Jin-yi","family":"Gao","sequence":"additional","affiliation":[{"name":"Information Science and Technology College, Dalian Maritime University, Dalian 116026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei-wei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Information Science and Technology College, Dalian Maritime University, Dalian 116026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chao-ming","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Marine Engineering, Jimei University, Xiamen 361021, China"},{"name":"Fujian Engineering Research Center of Marine Engine Detecting and Remanufacturing, Xiamen 361021, China"},{"name":"Provincial Key Laboratory of Naval Architecture and Ocean Engineering, Xiamen 361021, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong-liang","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Marine Engineering, Jimei University, Xiamen 361021, China"},{"name":"Fujian Engineering Research Center of Marine Engine Detecting and Remanufacturing, Xiamen 361021, China"},{"name":"Provincial Key Laboratory of Naval Architecture and Ocean Engineering, Xiamen 361021, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"108105","DOI":"10.1016\/j.ymssp.2021.108105","article-title":"An explainable artificial intelligence approach for unsupervised fault detection and diagnosis in rotating machinery","volume":"163","author":"Brito","year":"2022","journal-title":"Mech. 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