Intelligent assembly of large-scale,complex structures using an intelligent manufacturing platform represents the future development direction for industrial manufacturing.During large-scale structural assembly proces...Intelligent assembly of large-scale,complex structures using an intelligent manufacturing platform represents the future development direction for industrial manufacturing.During large-scale structural assembly processes,several bottleneck problems occur in the existing auxiliary assembly technology.First,the traditional LiDARbased assembly technology is often limited by the openness of the manufacturing environment,in which there are blind spots,and continuous online assembly adjustment thus cannot be realized.Second,for assembly of large structures,a single-station LiDAR system cannot achieve complete coverage,which means that a multi-station combination method must be used to acquire the complete three-dimensional data;many more data errors are caused by the transfer between stations than by the measurement accuracy of a single station,which means that the overall system's measurement and adjustment errors are increased greatly.Third,because of the large numbers of structural components contained in a large assembly,the accumulated errors may lead to assembly interference,but the LiDAR-assisted assembly process does not have a feedback perception capability,and thus assembly component loss can easily be caused when assembly interference occurs.Therefore,this paper proposes to combine an optical fiber sensor network with digital twin technology,which will allow the test data from the assembly entity state in the real world to be applied to the"twin"model in the virtual world and thus solve the problems with test openness and data transfer.The problem of station and perception feedback is also addressed and represents the main innovation of this work.The system uses an optical fiber sensor network as a flexible sensing medium to monitor the strain field distribution within a complex area in real time,and then completes real-time parameter adjustment of the virtual assembly based on the distributed data.Complex areas include areas that are laser-unreachable,areas with complex contact surfaces,and areas with large-scale bending deformations.An assembly condition monitoring system is designed based on the optical fiber sensor network,and an assembly condition monitoring algorithm based on multiple physical quantities is proposed.The feasibility of use of the optical fiber sensor network as the real-state parameter acquisition module for the digital twin intelligent assembly system is discussed.The offset of any position in the test area is calculated using the convolutional neural network of a residual module to provide the compensation parameters required for the virtual model of the assembly structure.In the model optimization parameter module,a correction data table is obtained through iterative learning of the algorithm to realize state prediction from the test data.The experiment simulates a largescale structure assembly process,and performs virtual and real mapping for a variety of situations with different assembly errors to enable correction of the digital twin data stream for the assembly process through the optical fiber sensor network.In the plane strain field calibration experiment,the maximum error among the test values for this system is 0.032 mm,and the average error is 0.014 mm.The results show that use of visual calibration can correct the test error to within a very small range.This result is equally applicable to gradient curvature surfaces and freeform surfaces.Statistics show that the average measurement accuracy error for regular surfaces is better than 11.2%,and the average measurement accuracy error for irregular surfaces is better than 14.8%.During simulation of large-scale structure assembly experiments,the average position deviation accuracy is 0.043 mm,which is in line with the designed accuracy.展开更多
Optical fiber sensor networks(OFSNs)provide powerful tools for large-scale buildings or long-distance sensing,and they can realize distributed or quasi-distributed measurement of temperature,strain,and other physical ...Optical fiber sensor networks(OFSNs)provide powerful tools for large-scale buildings or long-distance sensing,and they can realize distributed or quasi-distributed measurement of temperature,strain,and other physical quantities.This article provides some optical fiber sensor network technologies based on the white light interference technology.We discuss the key issues in the fiber white light interference network,including the topology structure of white light interferometric fiber sensor network,the node connection components,and evaluation of the maximum number of sensors in the network.A final comment about further development prospects of fiber sensor network is presented.展开更多
The recent research progress in the key device and technology of the fiber optic sensor network （FOSN） is introduced in this paper. An architecture of the sensor optical passive network （SPON）, by employing hybrid...The recent research progress in the key device and technology of the fiber optic sensor network （FOSN） is introduced in this paper. An architecture of the sensor optical passive network （SPON）, by employing hybrid wavelength division multiplexing/time division multiplexing （WDM/TDM） techniques similar to the fiber communication passive optical network （PON）, is proposed. The network topology scheme of a hybrid TDM/WDM/FDM （frequency division multiplexing） three-dimension fiber optic sensing system for achieving ultra-large capacity, long distance, and high resolution sensing performance is performed and analyzed. As the most important device of the FOSN, several kinds of light source are developed, including the wideband multi-wavelength fiber laser operating at C band, switchable and tunable 2 μm multi-wavelength fiber lasers, ultra-fast mode-locked fiber laser, as well as the optical wideband chaos source, which have very good application prospects in the FOSN. Meanwhile, intelligent management techniques for the FOSN including wideband spectrum demodulation of the sensing signals and real-time fault monitoring of fiber links are presented. Moreover, several typical applications of the FOSN are also discussed, such as the fiber optic gas sensing network, fiber optic acoustic sensing network, and strain/dynamic strain sensing network.展开更多
基金supported by the National Science Foundation of China(Theoretical Model and Experimental Research on the Novel FBG Sensing System based on the Fusion Algorithm,No.61703056)the Jilin Province Science and Technology Development Plan Project(No.20190103154JH)。
文摘Intelligent assembly of large-scale,complex structures using an intelligent manufacturing platform represents the future development direction for industrial manufacturing.During large-scale structural assembly processes,several bottleneck problems occur in the existing auxiliary assembly technology.First,the traditional LiDARbased assembly technology is often limited by the openness of the manufacturing environment,in which there are blind spots,and continuous online assembly adjustment thus cannot be realized.Second,for assembly of large structures,a single-station LiDAR system cannot achieve complete coverage,which means that a multi-station combination method must be used to acquire the complete three-dimensional data;many more data errors are caused by the transfer between stations than by the measurement accuracy of a single station,which means that the overall system's measurement and adjustment errors are increased greatly.Third,because of the large numbers of structural components contained in a large assembly,the accumulated errors may lead to assembly interference,but the LiDAR-assisted assembly process does not have a feedback perception capability,and thus assembly component loss can easily be caused when assembly interference occurs.Therefore,this paper proposes to combine an optical fiber sensor network with digital twin technology,which will allow the test data from the assembly entity state in the real world to be applied to the"twin"model in the virtual world and thus solve the problems with test openness and data transfer.The problem of station and perception feedback is also addressed and represents the main innovation of this work.The system uses an optical fiber sensor network as a flexible sensing medium to monitor the strain field distribution within a complex area in real time,and then completes real-time parameter adjustment of the virtual assembly based on the distributed data.Complex areas include areas that are laser-unreachable,areas with complex contact surfaces,and areas with large-scale bending deformations.An assembly condition monitoring system is designed based on the optical fiber sensor network,and an assembly condition monitoring algorithm based on multiple physical quantities is proposed.The feasibility of use of the optical fiber sensor network as the real-state parameter acquisition module for the digital twin intelligent assembly system is discussed.The offset of any position in the test area is calculated using the convolutional neural network of a residual module to provide the compensation parameters required for the virtual model of the assembly structure.In the model optimization parameter module,a correction data table is obtained through iterative learning of the algorithm to realize state prediction from the test data.The experiment simulates a largescale structure assembly process,and performs virtual and real mapping for a variety of situations with different assembly errors to enable correction of the digital twin data stream for the assembly process through the optical fiber sensor network.In the plane strain field calibration experiment,the maximum error among the test values for this system is 0.032 mm,and the average error is 0.014 mm.The results show that use of visual calibration can correct the test error to within a very small range.This result is equally applicable to gradient curvature surfaces and freeform surfaces.Statistics show that the average measurement accuracy error for regular surfaces is better than 11.2%,and the average measurement accuracy error for irregular surfaces is better than 14.8%.During simulation of large-scale structure assembly experiments,the average position deviation accuracy is 0.043 mm,which is in line with the designed accuracy.
文摘Optical fiber sensor networks(OFSNs)provide powerful tools for large-scale buildings or long-distance sensing,and they can realize distributed or quasi-distributed measurement of temperature,strain,and other physical quantities.This article provides some optical fiber sensor network technologies based on the white light interference technology.We discuss the key issues in the fiber white light interference network,including the topology structure of white light interferometric fiber sensor network,the node connection components,and evaluation of the maximum number of sensors in the network.A final comment about further development prospects of fiber sensor network is presented.
基金These works are supported by a grant from the Sub-Project of the Major Program of the National Natural Science Foundation of China （No. 61290315）, the National Natural Science Foundation of China （No. 61275083, 61275004, and 61404056）, the National Key Foundation of Exploring Scientific Instrument of China （No. 2013YQ16048707）, and the Fundamental Research Funds for the Central Universities （HUST： No. 2014CG002, and 2014QNRC005）. Much appreciation should be given to the students, Zhinlin Xu, Yiyang Luo, Fan Ai, Wei Yang, Enci Chen, Shun Wang ,Shui Zhao, Li Liu, Hao Liao, Xin Fu, Shun Wang, Wei Yang, Wang Yang, and Mingren Su.
文摘The recent research progress in the key device and technology of the fiber optic sensor network （FOSN） is introduced in this paper. An architecture of the sensor optical passive network （SPON）, by employing hybrid wavelength division multiplexing/time division multiplexing （WDM/TDM） techniques similar to the fiber communication passive optical network （PON）, is proposed. The network topology scheme of a hybrid TDM/WDM/FDM （frequency division multiplexing） three-dimension fiber optic sensing system for achieving ultra-large capacity, long distance, and high resolution sensing performance is performed and analyzed. As the most important device of the FOSN, several kinds of light source are developed, including the wideband multi-wavelength fiber laser operating at C band, switchable and tunable 2 μm multi-wavelength fiber lasers, ultra-fast mode-locked fiber laser, as well as the optical wideband chaos source, which have very good application prospects in the FOSN. Meanwhile, intelligent management techniques for the FOSN including wideband spectrum demodulation of the sensing signals and real-time fault monitoring of fiber links are presented. Moreover, several typical applications of the FOSN are also discussed, such as the fiber optic gas sensing network, fiber optic acoustic sensing network, and strain/dynamic strain sensing network.
