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Modern mechanical equipment often operates under complex operating conditions and failure modes, making it difficult to extract features, construct health indicators, and predict remaining useful life. This paper presents a novel method for RUL prediction. The proposed method extracts vibration signal data from mechanical equipment and employs ensemble empirical mode decomposition (EEMD) to reconstruction and denoise the signals. Sequential Forward Selection (SFS) is then applied to filter the feature dataset, which consists of multiscale features, including monotonicity (Mon), robustness, correlation (Corr), and concavity\u2013convexity features, all of which strongly indicate the degradation process. These features are used to construct a health indicator (HI) via a Self\u2010Organizing Map (SOM), which accurately reflects the degradation state of the equipment. Following this, a bidirectional long short\u2010term memory (BLSTM) neural network is trained on the processed degradation feature dataset. The effectiveness of the model is validated on heating furnace fan data in the hot rolling. Comparative analysis with three other prediction models demonstrates superior performance of the proposed method. Compared to the Original Data\u2010BLSTM method, the proposed model reduces mean absolute error (MAE), mean squared error (MSE), and root mean square error (RMSE) by 83%, 95%, and 80%, respectively.<\/jats:p>","DOI":"10.1002\/qre.3813","type":"journal-article","created":{"date-parts":[[2025,5,21]],"date-time":"2025-05-21T14:09:50Z","timestamp":1747836590000},"page":"2427-2440","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multidimensional Feature Mining and Selection for Health Indicator Construction and Remaining Useful Life Prediction"],"prefix":"10.1002","volume":"41","author":[{"given":"Guojun","family":"Gu","sequence":"first","affiliation":[{"name":"College of Mechanical Engineering Donghua University  Shanghai P. R. China"}]},{"given":"Yuhang","family":"Yao","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering Donghua University  Shanghai P. R. China"}]},{"given":"Ershun","family":"Pan","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Management the State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University  Shanghai P. R. China"}]},{"given":"Huimin","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering Donghua University  Shanghai P. R. China"}]},{"given":"Di","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering Donghua University  Shanghai P. R. China"}]}],"member":"311","published-online":{"date-parts":[[2025,5,21]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.iotcps.2023.04.006"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2022.108705"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1115\/1.4035860"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2023.114224"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2022.112282"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/qre.3494"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compind.2023.103903"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/qre.1245"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/qre.3555"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2021.01.160"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2022.3159624"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2025.110891"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.3390\/en16093858"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijfatigue.2023.107639"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1002\/qre.2899"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.3390\/s21010182"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2022.3167778"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2021.107628"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2019.2924605"},{"key":"e_1_2_9_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.123563"},{"key":"e_1_2_9_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2024.110014"},{"key":"e_1_2_9_23_1","doi-asserted-by":"publisher","DOI":"10.1002\/qre.3023"},{"key":"e_1_2_9_24_1","doi-asserted-by":"publisher","DOI":"10.1080\/0305215X.2019.1586893"},{"key":"e_1_2_9_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.05.031"},{"key":"e_1_2_9_26_1","doi-asserted-by":"publisher","DOI":"10.1177\/1748006\u00d721990527"},{"key":"e_1_2_9_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2024.110225"},{"key":"e_1_2_9_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2018.05.017"},{"key":"e_1_2_9_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2019.06.038"},{"key":"e_1_2_9_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.2998102"},{"key":"e_1_2_9_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.isatra.2019.08.058"},{"key":"e_1_2_9_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2020.01.042"},{"key":"e_1_2_9_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.124939"},{"key":"e_1_2_9_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2013.2285318"},{"key":"e_1_2_9_35_1","doi-asserted-by":"publisher","DOI":"10.1049\/joe.2014.0303"},{"key":"e_1_2_9_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.isatra.2020.12.052"},{"key":"e_1_2_9_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2023.109753"},{"key":"e_1_2_9_38_1","doi-asserted-by":"publisher","DOI":"10.1002\/qre.3256"},{"key":"e_1_2_9_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2023.109666"},{"key":"e_1_2_9_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.02.045"},{"key":"e_1_2_9_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2023.110910"},{"issue":"1","key":"e_1_2_9_42_1","article-title":"Theory and Application of Possibility and Evidence in Reliability Analysis and Design Optimization","volume":"1","author":"Huang H. 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