{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T18:05:47Z","timestamp":1780596347116,"version":"3.54.1"},"reference-count":51,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T00:00:00Z","timestamp":1780531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2024CDJYXTD-004"],"award-info":[{"award-number":["2024CDJYXTD-004"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Chongqing Water Environment Holding Group Co., Ltd.","award":["2022-06"],"award-info":[{"award-number":["2022-06"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Rotor imbalance and abnormal vibration are classical operating conditions in rotating machinery and can often be identified by conventional vibration analysis. However, the development of low-power, self-powered, and distributed sensing nodes remains important for long-term condition monitoring, particularly in scenarios where external power supply, wiring, and maintenance are constrained. Existing vibration sensors, including piezoelectric and capacitive types, are constrained by power consumption and degraded performance under low-frequency and weak excitation. To address this issue, a magnetically repulsive cushion triboelectric nanogenerator (MRCT) is proposed to enable self-powered vibration sensing. The magnetic-repulsion cushion allows the upper friction layer to undergo stable contact\u2013separation motion under a non-contact restoring force, while the microstructured strip electrode array (MSEA) enhances the triboelectric output and signal stability. A hybrid convolutional neural network\u2013gated recurrent unit (CNN-GRU) deep-learning model is employed to extract time-domain and frequency-domain features from the collected signals, enabling real-time identification of rotor vibration amplitude, frequency, and imbalance weight. Experimental results show that the MRCT provides stable output, a high signal-to-noise ratio, and an identification accuracy above 98% for predefined rotor imbalance-weight states under laboratory conditions. In addition, a shaft-misalignment-related abnormal vibration condition was examined on the motor platform. The corresponding time-domain and frequency-domain analyses show that the MRCT voltage signal exhibits distinguishable signal variations under normal and misalignment-related conditions, including spectral changes around the 2\u00d7 rotational frequency. A laboratory-scale AIoT-oriented demonstration further verifies the feasibility of integrating MRCT signal acquisition, CNN-GRU inference, wireless transmission, and GUI-based visualization. It should be noted that the present work mainly focuses on imbalance-state recognition, while the misalignment-related experiment provides an additional sensor-response verification. Broader validation involving mechanical looseness, bearing defects, variable-speed operation, cross-machine testing, and long-term industrial conditions remains necessary.<\/jats:p>","DOI":"10.3390\/s26113587","type":"journal-article","created":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T17:11:04Z","timestamp":1780593064000},"page":"3587","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Magnetically Repulsive Cushion Triboelectric Nanogenerator for Rotating Machinery Structural Health Monitoring"],"prefix":"10.3390","volume":"26","author":[{"given":"Haojie","family":"Peng","sequence":"first","affiliation":[{"name":"College of Physics and Optoelectronic Engineering, Chongqing Normal University, Chongqing 401331, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yufen","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Physics and Optoelectronic Engineering, Chongqing Normal University, Chongqing 401331, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanling","family":"Li","sequence":"additional","affiliation":[{"name":"College of Optoelectronic Engineering, Chongqing University, Chongqing 400044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingjie","family":"He","sequence":"additional","affiliation":[{"name":"College of Physics and Optoelectronic Engineering, Chongqing Normal University, Chongqing 401331, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changke","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Physics and Optoelectronic Engineering, Chongqing Normal University, Chongqing 401331, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Na","sequence":"additional","affiliation":[{"name":"Chongqing Municipal Water Supply Co., Ltd., Chongqing 400060, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Tan","sequence":"additional","affiliation":[{"name":"Chongqing Municipal Water Supply Co., Ltd., Chongqing 400060, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Qiu","sequence":"additional","affiliation":[{"name":"Chongqing Municipal Water Supply Co., Ltd., Chongqing 400060, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaohong","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Physics and Optoelectronic Engineering, Chongqing Normal University, Chongqing 401331, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"117297","DOI":"10.1016\/j.eswa.2022.117297","article-title":"Construction of health indicators for condition monitoring of rotating machinery: A review of the research","volume":"203","author":"Zhou","year":"2022","journal-title":"Expert Syst. 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