为加快实现“创新激光技术，服务转型升级，做强激光装备，助力高端制造”的目标，高端激光制造装备省部共建协同创新中心兹定于2019年10月23-24日在浙江杭州举办“光学元件与激光制造”第七届协同创新论坛。论坛邀请了五位海外专家在光学元件与激光制造相关领域进行系列报告。报告信息如下：
报告一：Interferometric Synthetic Aperture Microscopy: replacing lenses with computers in OCT
报告人：P. Scott Carney
报告时间：2019年10月23日上午10:00
报告地点：机械楼D526
报告摘要：Optical elements may be thought of as effecting a linear transformation of the optical field. Given access to the field, those same transformations, and many more, may be performed with a computer and so hardware may be replaced with software. I will mainly discuss the application of this idea in optical coherence tomography (OCT) where we have replaced complicated hardware with physics-based algorithms to produce a high-resolution 3-d imaging system with infinite depth of field in a compact form factor. I will give examples of the method in use in biological systems and results from a recent clinical trial in breast cancer.
报告人简介：P. Scott Carney has served as the Director of The Institute of Optics, since July 2017. He holds a PhD in Physics (1999) from the University of Rochester and a bachelors degree in Engineering Physics (1994) from the University of Illinois Urbana-Champaign. He was faculty at ECE Illinois 2001-2017. He is active in the optics community primarily through the OSA as a journal editor and meeting organizer. He is an entrepreneur and cofounder of Diagnostic Photonics, Inc. His research interests include computed imaging, spectroscopy, and coherence theory.
报告二：Design of Multi-Channel Nozzles for Laser Cladding
报告人：Mykola Anyakin
报告时间：2019年10月24日下午2:00
报告地点：机械楼D526
报告摘要：Gas-powder laser cladding technology is widely used nowadays either to restore surface of tools and parts or to modify part’s properties (wear resistance, corrosion resistance etc).Application of multichannel nozzles for the delivery of gas-powder streams into laser processing zone boosts the range of technological applications. This research is focused on simultaneous introduction of different powder into the processing zone. Another scope of interest is the control of powder distribution on the surface of workpiece and manipulation of powder concentration distribution on the go. Two different laser types were used – fiber and High-Power Diode lasers.Research activities included numerical simulation of gas-powder stream propagation inside the nozzle and into the ambient atmosphere, printing of prototypes with STL technology and their experimental validation. The performance of prototypes was evaluated and the most promising ones were selected for manufacturing.Original nozzles for the delivery of gas-powder mixtures with controllable distribution of powder concentration were designed and manufactured. Single clads were made using these nozzles and clad characteristics were compared. It was found that the outcome of laser cladding process significantly depends on the distribution of powder concentration, geometrical characteristics of nozzle inner cavity, powder and carrier gas flowrate. Manufacturing of parts with complex shapes is one of the most promising applications for the designed nozzles.
报告人简介：Dr. M.Anyakin is Vice Director, Senior Researcher in Laser Technology Research Institute of National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”. He received the degree of DSc on 2010 from National Technical University of Ukraine. He won the Ministry of Higher Education Prize for Best Student Research in 1980, Prize for Young scientists "Excellent Research" in 1984 and People’s Government of Zhejiang Province “West Lake Award” in 2014. So far, more than 81 papers and 34 inventions have been published.
报告三：PCA data reduction for increasing AM experiment controllability
报告人：Dmytro Dosyn
报告时间：2019年10月24日下午2:30
报告地点：机械楼D526
报告摘要：In the report it is proposed to investigate data reduction techniques for the purpose of further possible increasing of AM process dimensional, geometric accuracy and productivity applying modern approaches. AM techniques are widely used for manufacturing of the complex objects. The use of artificial intelligence, in particular artificial neural networks show the current trends of improvement in AM. This makes the process more precise, less time-consuming and allows to increase the production efficiency. AM process features array includes redundant and uninformative features. So, more time is required for error sources estimation and classification. Therefore, it is necessary during data analysis to reduce the input feature set. The following methods are used for feature reduction: complete search, depth-first search, breadth-first search, branch-and-bound, group method of data handling, feature ranking, feature clustering, evolutionary search, etc. The principal component method is proposed to be used for reduction of input characteristics.
The main advantage of using quantitative characteristics for the purpose of error sources classification is the lack of a subjective human factor. Therefore, an urgent problem is evaluation of the quantitative characteristics of geometric accuracy like RMSE, circularity error for cylindrical objects, their reduction and data classification using modern classifiers to improve AM precision.
报告人简介：Ph.D., Associate Professor at the Information systems and networks Department, Institute of Computer Science and Information Technology at Lviv Polytechnic National University, Lviv, Ukraine. He had published 49 scientific papers, 4 monographs. In 1998 he defended a candidate thesis (Ph.D.) “The method of the interferometry data adaptive correction using ionosphere monitoring data”. The main scientific interest includes intelligent agents behavior and agent motivation modelling, text mining for knowledge discovery, ontology learning, text document pertinency estimation and intelligent information search using EVPI.
报告四：Analysis and modeling of inclusions in laser modified layer of aluminium alloys
报告人：Iryna Ivasenko
报告时间：2019年10月24日下午3:00
报告地点：机械楼D526
报告摘要：Laser melt injection of SiC particles into aluminum alloys increases their functional properties. It is proposed to use image processing methods to analyse the distribution of solid inclusions of SiC in the surface layer of the laser-modified aluminum alloy. A 3-D modelling of surface layer with SiC particles was fulfilled. It allows making preliminary estimation of functional properties of surface layers for different size of particles and different percentage by the volume.
报告人简介：Dr. Iryna Ivasenko graduated from Lviv State University in 1995, and he received a Ph.D. degree from Karpenko Physico-mechanical Institute of National academy of sciences of Ukraine in 2000. Dr. Iryna Ivasenko is currently a Senior Researcher in Karpenko Physico-mechanical Institute of National academy of sciences of Ukraine. He participated 2 funded research projects and 6 selected state budget research grants of NAS of Ukraine. He served as West Ukraine Chapter Chair of IEEE MTT/ED/AP/CPMT/SSC and he now is a Ukraine Section Secretary of IEEE. So far, more than 14 journal papers have been published.
报告五：Acoustic emission method in prediction problemsof residual resource of structural elements
报告人：Iryna Dolinska
报告时间：2019年10月24日下午3:30
报告地点：机械楼D526
报告摘要：Methods of prediction of residual resource of structural elements using acoustic emission have been developed. These methods are based on the author's previously developed energy approach to the investigation of cracks subcritical growth in materials and on the known from the literature correlation between the new-formed defects area and acoustic emission parameters. The method application is demonstrated on the example of the residual resource determination of the structural elements operating under long-term static load and high temperature. With the help of this method an effective methodology was developed for kinetic diagrams constructing of high-temperature creep cracks growth in metallic materials. Method was applied to the prediction of residual resource of the oil hydrocracking reactor wall.
报告人简介：Dr Iryna Dolinska received a master's degree from The Ivan Franko National University of Lviv in 2009. She received her PhD degree in solid mechanics on 2012 and DSc in Engineering on 2018 from the Karpenko Physico-mechanical Institute of National academy of sciences of Ukraine, respectively. Dr Iryna Dolinska is currently a senior researcher at Karpenko Institute of Physical Machinery, National Academy of Sciences, Ukraine. Dr Iryna Dolinska won the Presidential Young Scientist Award in 2015. And he was Laureate of the Presidium of the National Academy of Sciences of Ukraine for Young Scientists in 2012. Dr Iryna Dolinska served twice as the President of Ukraine Scholarship for Young Scientists. He was the president for one research project and participates in two research projects. So far, more than 27 journal papers, 2 Research monographs and 1 Textbook have been published.
高端激光制造装备省部共建协同创新中心
2019年10月21日