{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T14:49:39Z","timestamp":1774536579855,"version":"3.50.1"},"reference-count":41,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2015,11,13]],"date-time":"2015-11-13T00:00:00Z","timestamp":1447372800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Basic Research Program of China: Key Fundamental Research on the Unmanned Mining Equipment in Deep Dangerous Coal Bed","award":["2014CB046301"],"award-info":[{"award-number":["2014CB046301"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51475454"],"award-info":[{"award-number":["51475454"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National High Technology Research and Development Program of China","award":["2013AA06A411"],"award-info":[{"award-number":["2013AA06A411"]}]},{"name":"Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In order to efficiently and accurately identify the cutting condition of a shearer, this paper proposed an intelligent multi-sensor data fusion identification method using the parallel quasi-Newton neural network (PQN-NN) and the Dempster-Shafer (DS) theory. The vibration acceleration signals and current signal of six cutting conditions were collected from a self-designed experimental system and some special state features were extracted from the intrinsic mode functions (IMFs) based on the ensemble empirical mode decomposition (EEMD). In the experiment, three classifiers were trained and tested by the selected features of the measured data, and the DS theory was used to combine the identification results of three single classifiers. Furthermore, some comparisons with other methods were carried out. The experimental results indicate that the proposed method performs with higher detection accuracy and credibility than the competing algorithms. Finally, an industrial application example in the fully mechanized coal mining face was demonstrated to specify the effect of the proposed system.<\/jats:p>","DOI":"10.3390\/s151128772","type":"journal-article","created":{"date-parts":[[2015,11,13]],"date-time":"2015-11-13T03:52:35Z","timestamp":1447386755000},"page":"28772-28795","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Multi-Sensor Data Fusion Identification for Shearer Cutting Conditions Based on Parallel Quasi-Newton Neural Networks and the Dempster-Shafer Theory"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4087-9430","authenticated-orcid":false,"given":"Lei","family":"Si","sequence":"first","affiliation":[{"name":"School of Mechatronic Engineering, China University of Mining &amp; Technology, Xuzhou 221116, China"},{"name":"School of Information and Electrical Engineering, China University of Mining &amp; Technology, Xuzhou 221116, China"}]},{"given":"Zhongbin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering, China University of Mining &amp; Technology, Xuzhou 221116, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8632-6532","authenticated-orcid":false,"given":"Xinhua","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering, China University of Mining &amp; Technology, Xuzhou 221116, China"}]},{"given":"Chao","family":"Tan","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering, China University of Mining &amp; Technology, Xuzhou 221116, China"}]},{"given":"Jing","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering, China University of Mining &amp; Technology, Xuzhou 221116, China"}]},{"given":"Kehong","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering, China University of Mining &amp; Technology, Xuzhou 221116, China"}]}],"member":"1968","published-online":{"date-parts":[[2015,11,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2014\/948796","article-title":"A novel approach for shearer cutting load identification through integration of improved particle swarm optimization and wavelet neural network","volume":"6","author":"Wang","year":"2014","journal-title":"Adv. Mech. Eng."},{"key":"ref_2","first-page":"3224","article-title":"Wavelet multi-resolution analysis of weak reflected wave from the interfaces of coal seam and strata","volume":"24","author":"Yu","year":"2005","journal-title":"China J. Rock Mech. Eng."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Sun, J.P., and Su, B. (2012). Coal-Rock Interface Detection Using Digital Image Analysis Technique, Springer London.","DOI":"10.1007\/978-1-4471-2467-2_144"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"586","DOI":"10.1016\/j.jmoldx.2012.06.005","article-title":"Coal-rock interface recognition method based on EMD and neural network","volume":"34","author":"Wang","year":"2012","journal-title":"J. Vib. Meas. Diagn."},{"key":"ref_5","first-page":"513","article-title":"Establishment of a theoretical model of sensor for identification of coal rock interface by natural ray and underground trials","volume":"21","author":"Qin","year":"1996","journal-title":"J. China Coal Soc."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Sahoo, R., and Mazid, A.M. (2009, January 10\u201313). Application of Opto-Tactile Sensor in Shearer Machine Design to Recognize Rock Surfaces in Underground Coal Mining. Proceedings of IEEE International Conference on Industrial Technology, Churchill, Australia.","DOI":"10.1109\/ICIT.2009.4939645"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Bausov, I.Y., Stolarczyk, G.L., Stolarczyk, L.G., and Koppenjan, S.D.S. (2007, January 27\u201329). Look-Ahead Radar and Horizon Sensing for Coal Cutting Drums. Proceedings of 4th International Workshop on Advanced Ground Penetrating Radar, Naples, Italy.","DOI":"10.1109\/AGPR.2007.386553"},{"key":"ref_8","first-page":"12","article-title":"Back to the basics of the rotating machinery vibration analysis","volume":"29","author":"Taylor","year":"1995","journal-title":"Sound Vib."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.jsv.2015.07.034","article-title":"A wavelet-based method for the forced vibration analysis of piecewise linear single- and multi-DOF systems with application to cracked beam dynamics","volume":"358","author":"Joglekar","year":"2015","journal-title":"J. Sound Vib."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Lian, J.J., Zhang, Y., Liu, F., and Zhao, Q.H. (2015). Analysis of the ground vibration induced by high dam flood discharge using the cross wavelet transform method. J. Renew. Sustain. Energ., 7.","DOI":"10.1063\/1.4928520"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Awrejcewicz, J., Krysko, A.V., Kutepov, I.E., Zagniboroda, N.A., Zhigalov, M.V., and Krysko, V.A. (2013). Analysis of Chaotic Vibrations of Flexible Plates Using Fast Fourier Transforms and Wavelets. Int. J. Struct. Stab. Dy., 13.","DOI":"10.1142\/S0219455413400051"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.net.2014.12.010","article-title":"Vibration signal analysis of main coolant pump flywheel based on Hilbert-Huang transform","volume":"47","author":"Liu","year":"2015","journal-title":"Nucl. Eng. Technol."},{"key":"ref_13","first-page":"689","article-title":"Vibration analysis on the mechanisms for hydropower unit rotors based on empirical mode decomposition","volume":"16","author":"Fu","year":"2014","journal-title":"J. Optoelectron. Adv. M."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.apacoust.2014.08.016","article-title":"Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals","volume":"89","author":"Ali","year":"2015","journal-title":"Appl. Acoust."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"980","DOI":"10.1109\/TSG.2014.2386305","article-title":"An artificial neural network approach for early fault detection of gearbox bearings","volume":"6","author":"Bangalore","year":"2015","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.mechmachtheory.2015.03.013","article-title":"Gear fault diagnosis based on support vector machine optimized by artificial bee colony algorithm","volume":"90","author":"Yang","year":"2015","journal-title":"Mech. Mach. Theory"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1134\/S0005117913020094","article-title":"Creating a model of passive electronic components using a neural network approach","volume":"74","author":"Belkov","year":"2013","journal-title":"Autom. Remote Control"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"11665","DOI":"10.3390\/s150511665","article-title":"Classifying sources Influencing Indoor Air Quality (IAQ) Using Artificial Neural Network (ANN)","volume":"15","author":"Saad","year":"2015","journal-title":"Sensors"},{"key":"ref_19","unstructured":"Watrous, R.L. (1987, January 21\u201324). Learning Algorithms for Connectionist Networks: Applied Gradient Methods of Nonlinear Optimization. Proceedings of the IEEE First International Conference on Neural Networks, San Diego, CA, USA."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1203","DOI":"10.1134\/S0005117914070030","article-title":"A neural network algorithm for servicing jobs with sequential and parallel machines","volume":"75","author":"Gholami","year":"2014","journal-title":"Autom. Remote Control"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1007\/s10766-013-0245-x","article-title":"Parallel training of an improved neural network for text categorization","volume":"42","author":"Li","year":"2014","journal-title":"Int. J. Parallel Program."},{"key":"ref_22","first-page":"515","article-title":"Cryptanalysis and improvement on a parallel keyed hash function based on chaotic neural network","volume":"52","author":"Wang","year":"2013","journal-title":"Telecommun. Syst."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"21857","DOI":"10.3390\/s150921857","article-title":"Multi-sensor data fusion using a relevance vector machine based on an ant colony for gearbox fault detection","volume":"15","author":"Liu","year":"2015","journal-title":"Sensors"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.inffus.2013.10.002","article-title":"Using multi-sensor data fusion for vibration fault diagnosis of rolling element bearings by accelerometer and load cell","volume":"18","author":"Safizadeh","year":"2014","journal-title":"Inf. Fusion"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1007\/s12555-014-0251-9","article-title":"High-speed train navigation system based on multi-sensor data fusion and map matching algorithm","volume":"13","author":"Kim","year":"2015","journal-title":"Int. J. Control Autom."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"7049","DOI":"10.3390\/s140407049","article-title":"Novel Paradigm for Constructing Masses in Dempster-Shafer Evidence Theory for Wireless Sensor Network\u2019s Multisource Data Fusion","volume":"14","author":"Zhang","year":"2014","journal-title":"Sensors"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.measurement.2014.04.015","article-title":"A novel approach for coal seam terrain prediction through information fusion of improved D-S evidence theory and neural network","volume":"54","author":"Si","year":"2014","journal-title":"Measurement"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1016\/j.asoc.2015.06.057","article-title":"Structural damage detection based on posteriori probability support vector machine and Dempster-Shafer evidence theory","volume":"36","author":"Zhou","year":"2015","journal-title":"Appl. Soft Comput."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.pmcj.2014.10.009","article-title":"Multi-sensor data fusion methods for indoor activity recognition using temporal evidence theory","volume":"21","author":"Kushwah","year":"2015","journal-title":"Pervasive Mob. Comput."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1460","DOI":"10.1109\/TNN.2003.820670","article-title":"Parallel nonlinear optimization techniques for training neural networks","volume":"14","author":"Phua","year":"2003","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Tan, G.Z., Shi, H.M., Wang, F., and Deng, C. (2009, January 11\u201312). Short-Term Traffic Flow Prediction Based on Parallel Quasi-Newton Neural Network. Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation, Zhangjiajie, China.","DOI":"10.1109\/ICMTMA.2009.249"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1214\/aoms\/1177698950","article-title":"Upper and lower probabilities induced by multivalued mappings","volume":"38","author":"Dempster","year":"1967","journal-title":"Ann. Math. Stat."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"957","DOI":"10.1214\/aoms\/1177698328","article-title":"Upper and lower probabilities generated by a random closed interval","volume":"39","author":"Dempster","year":"1968","journal-title":"Ann. Math. Stat."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Shafer, G. (1976). A Mathematical Theory of Evidence, Princeton University Press.","DOI":"10.1515\/9780691214696"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1109\/34.55104","article-title":"The combination of evidence in the transferable belief model","volume":"12","author":"Smets","year":"1990","journal-title":"IEEE Trans. Pattern Anal."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/0004-3702(94)90026-4","article-title":"The transferable belief model","volume":"66","author":"Smets","year":"1994","journal-title":"Artif. Intell."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"804","DOI":"10.1109\/21.376493","article-title":"A k-Nearest neighbor classification rule based on Dempster-Shafer theory","volume":"25","author":"Denoeux","year":"1995","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/S0165-0114(00)00086-5","article-title":"Handling possibilistic labels in pattern classification using evidential reasoning","volume":"122","author":"Denoeux","year":"2001","journal-title":"Fuzzy Set. Syst."},{"key":"ref_39","first-page":"223","article-title":"Signal denoising based on EEMD for non-stationary signals and its application in fault diagnosis","volume":"47","author":"Jian","year":"2011","journal-title":"Comput. Eng. Appl."},{"key":"ref_40","unstructured":"Chaari, F., Zimroz, R., Bartelmus, W., and Haddar, M. (2014, January 15\u201317). Advances in Condition Monitoring of Machinery in Non-Stationary Operations. Proceedings of the Fourth International Conference on Condition Monitoring of Machinery in Non-Stationary Operations, Lyon, France."},{"key":"ref_41","first-page":"1","article-title":"A fault diagnosis methodology for gear pump based on EEMD and Bayesian network","volume":"10","author":"Liu","year":"2015","journal-title":"PLoS ONE"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/11\/28772\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:52:02Z","timestamp":1760215922000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/11\/28772"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,11,13]]},"references-count":41,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2015,11]]}},"alternative-id":["s151128772"],"URL":"https:\/\/doi.org\/10.3390\/s151128772","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,11,13]]}}}