{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T19:03:08Z","timestamp":1770231788347,"version":"3.49.0"},"reference-count":23,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2019,7,15]],"date-time":"2019-07-15T00:00:00Z","timestamp":1563148800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Sichuan Province Science Support Program of China","award":["No. 2018GZ0008"],"award-info":[{"award-number":["No. 2018GZ0008"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Considering the lack of precision in transforming measured micro-electro-mechanical system (MEMS) accelerometer output signals into elevation signals, this paper proposes a bridge dynamic displacement reconstruction method based on the combination of ensemble empirical mode decomposition (EEMD) and time domain integration, according to the vibration signal traits of a bridge. Through simulating bridge analog signals and verifying a vibration test bench, four bridge dynamic displacement monitoring methods were analyzed and compared. The proposed method can effectively eliminate the influence of low-frequency integral drift and high-frequency ambient noise on the integration process. Furthermore, this algorithm has better adaptability and robustness. The effectiveness of the method was verified by field experiments on highway elevated bridges.<\/jats:p>","DOI":"10.3390\/s19143125","type":"journal-article","created":{"date-parts":[[2019,7,16]],"date-time":"2019-07-16T02:23:16Z","timestamp":1563243796000},"page":"3125","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Refactoring and Optimization of Bridge Dynamic Displacement Based on Ensemble Empirical Mode Decomposition"],"prefix":"10.3390","volume":"19","author":[{"given":"Yingquan","family":"Zou","sequence":"first","affiliation":[{"name":"School of Information Science and Technology, Southwest Jiaotong University of China, Chengdu 611756, China"},{"name":"State key Laboratory of Rail Transit Engineering Informatization, China Railway First Survey and Design Institute Group, Xi\u2019an 710043, China"}]},{"given":"Yunpeng","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Southwest Jiaotong University of China, Chengdu 611756, China"}]},{"given":"Peng","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Southwest Jiaotong University of China, Chengdu 611756, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zhu, X., Cao, M., Ostachowicz, W., and Xu, W. (2019). Damage identification in bridges by processing dynamic responses to moving loads: Features and evaluation. Sensors, 19.","DOI":"10.3390\/s19030463"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Yunus, M.Z.M., Ibrahim, N., and Ahmad, F.S. (2017, January 23\u201324). A review on bridge dynamic displacement monitoring using global positioning system and accelerometer. Proceedings of the International Conference on Engineering and Technology (InCET 2017), Putrajava, Malaysia.","DOI":"10.1063\/1.5022933"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Hidehiko, S., Kentaro, K., and Chitoshi, M. (2016). Technique for determining bridge displacement response using MEMS Accelerometers. Sensors, 16.","DOI":"10.3390\/s16020257"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1080\/15732479.2016.1198393","article-title":"After-fracture redundancy analysis of an aged truss bridge in Japan","volume":"13","author":"Lin","year":"2017","journal-title":"Struct. Infrastruct. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"62","DOI":"10.11648\/j.ijtet.20170304.13","article-title":"Linear variable differential transducer (LVDT) & its applications in civil engineering","volume":"3","author":"Joshi","year":"2017","journal-title":"Int. J. Transp. Eng. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2018\/9385171","article-title":"The feasibility of using laser doppler vibrometer measurements from a passing vehicle for bridge damage detection","volume":"2018","author":"Malekjafarlan","year":"2018","journal-title":"Shock Vibr."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.jsv.2017.06.008","article-title":"Identification of structural stiffness and excitation forces in time domain using noncont-act vision-based displacement measurement","volume":"406","author":"Feng","year":"2017","journal-title":"J. Sound Vib."},{"key":"ref_8","first-page":"111","article-title":"Plane and vertical precision of GPS control survey in engineering survey","volume":"1","author":"Feng","year":"2017","journal-title":"Constr. Des. Project"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/j.measurement.2018.07.090","article-title":"Structural displacement estimation through multi-rate fusion of accelerometer and RTK-GPS displacement and velocity measurements","volume":"130","author":"Kim","year":"2018","journal-title":"Measurement"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"393","DOI":"10.3390\/s130100393","article-title":"The role of advanced sensing in smart cities","volume":"13","author":"Hancke","year":"2013","journal-title":"Sensors"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Guo, R., Ye, S., and Ji, Y. (2018, January 2). Optimization acceleration integral method based on power spectrum estimation. Proceedings of the 6th International Forum on Industrial Design, Luoyang, China.","DOI":"10.1051\/matecconf\/201817603012"},{"key":"ref_12","first-page":"48","article-title":"Research on performance comparison of high cost and low cost MEMS accelerometers","volume":"37","author":"Du","year":"2018","journal-title":"Transducer Microsys. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Majumder, S., Mondal, T., and Deen, M. (2017). Wearable sensors for remote health monitoring. Sensors, 17.","DOI":"10.3390\/s17010130"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Kandula, V., DeBrunner, L., DeBrunner, V., and Ranmbo, R. (2012, January 4\u20137). Field testing of indirect displacement estimation using accelerometers. Proceedings of the 2012 Conference Record of the Forty Sixth Asilomar Conferen-ce on Signals, Pacific Grove, CA, USA.","DOI":"10.1109\/ACSSC.2012.6489361"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"602","DOI":"10.1360\/N092015-00282","article-title":"Novel integration method of measured acceleration to velocity and displacement based on zero initial condition","volume":"46","author":"Lin","year":"2016","journal-title":"Sci. Sin. Technol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"356","DOI":"10.7763\/IJCEE.2013.V5.731","article-title":"Performance analysis of fft filter to measure displacement signal in road roughness profiler","volume":"5","author":"Do","year":"2013","journal-title":"Int. J. Comput. Electr. Eng."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2072","DOI":"10.4028\/www.scientific.net\/AMR.591-593.2072","article-title":"Application of EMD to integrated signal trend extraction","volume":"591\u2013593","author":"Chen","year":"2012","journal-title":"Adv. Mater. Res."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1089","DOI":"10.4028\/www.scientific.net\/AMM.239-240.1089","article-title":"Study on measured data processing method of model test for relative motions between two side-by-side replenishment ships in waves","volume":"239\u2013240","author":"Shi","year":"2012","journal-title":"Appl. Mech. Mater."},{"key":"ref_19","first-page":"429","article-title":"HHT and fuzzy C-means clustering-based fault recognition for axial piston pump","volume":"45","author":"Jiang","year":"2015","journal-title":"J Jilin Univ. (Eng. Technol. Ed.)"},{"key":"ref_20","first-page":"49","article-title":"Modal parameter identification of bridge structure based on improved EEMD algorithm","volume":"35","author":"Chen","year":"2018","journal-title":"J. Highway Transp. Res. Dev."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1142\/S1793536909000047","article-title":"Ensemble Empirical Mode Decomposi-tion: A noise-assisted data analysis method","volume":"1","author":"Wu","year":"2009","journal-title":"Adv. Adapt. Data Anal."},{"key":"ref_22","unstructured":"Huang, N.E., and Shen, S.P. (2017). Hilbert-Huang Transform and Its Applications, National Defense Industry Press. [2nd ed.]."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"04017102","DOI":"10.1061\/(ASCE)BE.1943-5592.0001137","article-title":"Fatigue stress spectra and reliability evaluation of short-to medium-span bridges under stochastic and dynamic traffic loads","volume":"22","author":"Yan","year":"2017","journal-title":"J. Bridge Eng."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/14\/3125\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:05:56Z","timestamp":1760187956000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/14\/3125"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,15]]},"references-count":23,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2019,7]]}},"alternative-id":["s19143125"],"URL":"https:\/\/doi.org\/10.3390\/s19143125","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,15]]}}}