{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T21:06:06Z","timestamp":1761599166552,"version":"build-2065373602"},"reference-count":51,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2018,1,29]],"date-time":"2018-01-29T00:00:00Z","timestamp":1517184000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1510117","51605477"],"award-info":[{"award-number":["U1510117","51605477"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key Basic Research Program of China","award":["2014CB046301"],"award-info":[{"award-number":["2014CB046301"]}]},{"name":"Postgraduate Scientific Research and Innovation Project of Jiangsu Province","award":["KYZZ16_0212"],"award-info":[{"award-number":["KYZZ16_0212"]}]},{"name":"Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>As a sound signal has the advantages of non-contacted measurement, compact structure, and low power consumption, it has resulted in much attention in many fields. In this paper, the sound signal of the coal mining shearer is analyzed to realize the accurate online cutting pattern identification and guarantee the safety quality of the working face. The original acoustic signal is first collected through an industrial microphone and decomposed by adaptive ensemble empirical mode decomposition (EEMD). A 13-dimensional set composed by the normalized energy of each level is extracted as the feature vector in the next step. Then, a swarm intelligence optimization algorithm inspired by bat foraging behavior is applied to determine key parameters of the traditional variable translation wavelet neural network (VTWNN). Moreover, a disturbance coefficient is introduced into the basic bat algorithm (BA) to overcome the disadvantage of easily falling into local extremum and limited exploration ability. The VTWNN optimized by the modified BA (VTWNN-MBA) is used as the cutting pattern recognizer. Finally, a simulation example, with an accuracy of 95.25%, and a series of comparisons are conducted to prove the effectiveness and superiority of the proposed method.<\/jats:p>","DOI":"10.3390\/s18020382","type":"journal-article","created":{"date-parts":[[2018,1,29]],"date-time":"2018-01-29T07:46:20Z","timestamp":1517211980000},"page":"382","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Cutting Pattern Identification for Coal Mining Shearer through a Swarm Intelligence\u2013Based Variable Translation Wavelet Neural Network"],"prefix":"10.3390","volume":"18","author":[{"given":"Jing","family":"Xu","sequence":"first","affiliation":[{"name":"School of Mechatronic Engineering, China University of Mining and Technology, No.1 Daxue Road, Xuzhou 221116, China"}]},{"given":"Zhongbin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering, China University of Mining and Technology, No.1 Daxue Road, Xuzhou 221116, China"}]},{"given":"Chao","family":"Tan","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering, China University of Mining and Technology, No.1 Daxue Road, Xuzhou 221116, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4087-9430","authenticated-orcid":false,"given":"Lei","family":"Si","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering, China University of Mining and Technology, No.1 Daxue Road, Xuzhou 221116, China"}]},{"given":"Xinhua","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering, China University of Mining and Technology, No.1 Daxue Road, Xuzhou 221116, China"},{"name":"Institute of Sound and Vibration Research, University of Southampton, Highfield, Southampton SO17 1BJ, UK"}]}],"member":"1968","published-online":{"date-parts":[[2018,1,29]]},"reference":[{"key":"ref_1","first-page":"191","article-title":"Coal-rock interface recognition based on MFCC and neural network","volume":"6","author":"Xu","year":"2013","journal-title":"Int. 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