{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T11:32:57Z","timestamp":1770895977189,"version":"3.50.1"},"reference-count":35,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2024,11,28]],"date-time":"2024-11-28T00:00:00Z","timestamp":1732752000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100005047","name":"Natural Science Foundation of Liaoning Province","doi-asserted-by":"publisher","award":["2022-BS-211"],"award-info":[{"award-number":["2022-BS-211"]}],"id":[{"id":"10.13039\/501100005047","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Basic Scientific Research Project of Liaoning Provincial Department of Education","award":["LJKMZ20220776"],"award-info":[{"award-number":["LJKMZ20220776"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Transactions of the Institute of Measurement and Control"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:p>The modern industrial process data with characteristics, such as multi-center and different structures, have challenged the traditional multivariate statistical process monitoring methods. To address this problem, a multimodal process fault detection method based on modified local gravity (MLG) is proposed in this paper. First, the method considers each data in the dataset as a particle, whose quality and gravitational constant are determined based on the distance information from the data to its nearest neighboring data, so as to obtain the partial force of the local variable. Second, the multimodal data are transformed into data that obey a single multivariate Gaussian distribution by calculating the sum of the partial forces on each local variable. Third, a principal component analysis (PCA) process monitoring model is established based on these local gravitational data. Finally, the effectiveness of the MLG-PCA method is verified with the numerical example and Tennessee Eastman process. The simulation results show that the fault detection rate of MLG-PCA is better than the rates of traditional methods.<\/jats:p>","DOI":"10.1177\/01423312241286566","type":"journal-article","created":{"date-parts":[[2024,11,28]],"date-time":"2024-11-28T04:40:56Z","timestamp":1732768856000},"page":"586-596","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Fault detection method based on modified local gravity and its application in multimodal process"],"prefix":"10.1177","volume":"48","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4424-9452","authenticated-orcid":false,"given":"Ying","family":"Xie","sequence":"first","affiliation":[{"name":"College of Information Engineering, Shenyang University of Chemical Technology, Shenyang, China"},{"name":"Liaoning Key Laboratory of Industry-Environment-Resource Collaborative Control and Optimization Technology, Shenyang University of Chemical Technology, Shenyang, China"}]},{"given":"Jinyu","family":"Lian","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Shenyang University of Chemical Technology, Shenyang, China"},{"name":"Liaoning Key Laboratory of Industry-Environment-Resource Collaborative Control and Optimization Technology, Shenyang University of Chemical Technology, Shenyang, China"}]},{"given":"Weiyue","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Shenyang University of Chemical Technology, Shenyang, China"},{"name":"Liaoning Key Laboratory of Industry-Environment-Resource Collaborative Control and Optimization Technology, Shenyang University of Chemical Technology, Shenyang, China"}]}],"member":"179","published-online":{"date-parts":[[2024,11,28]]},"reference":[{"key":"e_1_3_2_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.isatra.2017.09.015"},{"key":"e_1_3_2_3_1","doi-asserted-by":"publisher","DOI":"10.17705\/1CAIS.05229"},{"key":"e_1_3_2_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2023.3308342"},{"key":"e_1_3_2_5_1","doi-asserted-by":"publisher","DOI":"10.1002\/cem.1262"},{"key":"e_1_3_2_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/cem.2926"},{"key":"e_1_3_2_7_1","doi-asserted-by":"publisher","DOI":"10.1177\/01423312221137452"},{"key":"e_1_3_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSM.2007.907607"},{"key":"e_1_3_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2021.3054005"},{"key":"e_1_3_2_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2018.02.084"},{"key":"e_1_3_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCST.2010.2071415"},{"key":"e_1_3_2_12_1","doi-asserted-by":"publisher","DOI":"10.1021\/acs.iecr.6b01257"},{"key":"e_1_3_2_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cjche.2020.10.030"},{"key":"e_1_3_2_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2023.3253285"},{"key":"e_1_3_2_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemolab.2012.05.010"},{"key":"e_1_3_2_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemolab.2019.03.012"},{"key":"e_1_3_2_17_1","doi-asserted-by":"publisher","DOI":"10.1177\/014233129601800107"},{"key":"e_1_3_2_18_1","doi-asserted-by":"publisher","DOI":"10.3390\/pr12020251"},{"key":"e_1_3_2_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2010.12.003"},{"key":"e_1_3_2_20_1","doi-asserted-by":"publisher","DOI":"10.1021\/ie102048f"},{"key":"e_1_3_2_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2013.09.017"},{"key":"e_1_3_2_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ece.2019.09.002"},{"key":"e_1_3_2_23_1","doi-asserted-by":"publisher","DOI":"10.1002\/cem.2686"},{"key":"e_1_3_2_24_1","doi-asserted-by":"publisher","DOI":"10.1021\/ie3031983"},{"key":"e_1_3_2_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-020-04777-z"},{"key":"e_1_3_2_26_1","first-page":"1","article-title":"Robust decomposition of kernel function-based nonlinear robust multimode process monitoring","volume":"72","author":"Wang Y","year":"2023","unstructured":"Wang Y, Wan Y, Zhang H, et al. (2023) Robust decomposition of kernel function-based nonlinear robust multimode process monitoring. IEEE Transactions on Instrumentation and Measurement 72: 1\u201311.","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"key":"e_1_3_2_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2017.2695218"},{"key":"e_1_3_2_28_1","first-page":"1","article-title":"Stationary mapping based generalized monitoring scheme for industrial process with mixed operational stages","volume":"71","author":"Wang Z","year":"2021","unstructured":"Wang Z, Zheng Y, Wong DSH, et al. (2021) Stationary mapping based generalized monitoring scheme for industrial process with mixed operational stages. IEEE Transactions on Instrumentation and Measurement 71: 1\u201313.","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"key":"e_1_3_2_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/0031-3203(77)90013-9"},{"key":"e_1_3_2_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3190394"},{"key":"e_1_3_2_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2021.05.007"},{"key":"e_1_3_2_32_1","first-page":"9143727","article-title":"RFDPC: Density peaks clustering algorithm based on resultant force","volume":"2022","author":"Zhang Y","year":"2022","unstructured":"Zhang Y, Huang H, Du J, et al. (2022) RFDPC: Density peaks clustering algorithm based on resultant force. Mathematical Problems in Engineering 2022: 9143727.","journal-title":"Mathematical Problems in Engineering"},{"key":"e_1_3_2_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2022.06.011"},{"key":"e_1_3_2_34_1","doi-asserted-by":"publisher","DOI":"10.1002\/cjce.23778"},{"key":"e_1_3_2_35_1","doi-asserted-by":"publisher","DOI":"10.1002\/cjce.22651"},{"key":"e_1_3_2_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSM.2014.2374339"}],"container-title":["Transactions of the Institute of Measurement and Control"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/01423312241286566","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/01423312241286566","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/01423312241286566","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T10:48:16Z","timestamp":1770893296000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/01423312241286566"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,28]]},"references-count":35,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["10.1177\/01423312241286566"],"URL":"https:\/\/doi.org\/10.1177\/01423312241286566","relation":{},"ISSN":["0142-3312","1477-0369"],"issn-type":[{"value":"0142-3312","type":"print"},{"value":"1477-0369","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,28]]}}}