Academic literature on the topic 'Roughness class measuring system'
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Journal articles on the topic "Roughness class measuring system"
Agoyan, Marion, Gary Fourneau, Guy Cheymol, Ayoub Ladaci, Hicham Maskrot, Christophe Destouches, Damien Fourmentel, et al. "Confocal chromatic sensor for displacement monitoring in research reactor." EPJ Web of Conferences 253 (2021): 04021. http://dx.doi.org/10.1051/epjconf/202125304021.
Full textPatel, Rikesh, Matthias Hirsch, Paul Dryburgh, Don Pieris, Samuel Achamfuo-Yeboah, Richard Smith, Roger Light, Steve Sharples, Adam Clare, and Matt Clark. "Imaging Material Texture of As-Deposited Selective Laser Melted Parts Using Spatially Resolved Acoustic Spectroscopy." Applied Sciences 8, no. 10 (October 19, 2018): 1991. http://dx.doi.org/10.3390/app8101991.
Full textCao, Wei, Zhanchuan Cai, and Ben Ye. "Measuring Multiresolution Surface Roughness Using V-System." IEEE Transactions on Geoscience and Remote Sensing 56, no. 3 (March 2018): 1497–506. http://dx.doi.org/10.1109/tgrs.2017.2764519.
Full textПрохорец, Ольга, Olga Prokhorets, Владимир Давыдов, Vladimir Davydov, Вячеслав Языков, and Vyacheslav Yazykov. "Measuring system for 3d measurement of surface roughness." Bulletin of Bryansk state technical university 2015, no. 2 (June 30, 2015): 104–9. http://dx.doi.org/10.12737/22854.
Full textLiu, Zhen, Wei Yang, Minzan Li, Peng Zhou, Xiangqian Yao, Yuqing Chen, and Ziyuan Hao. "Soil Roughness Measuring System Combined With Image Processing." IFAC-PapersOnLine 51, no. 17 (2018): 689–94. http://dx.doi.org/10.1016/j.ifacol.2018.08.116.
Full textDodda Mallappa, Shivanna, Kiran Mysore Bhaskar, Venkatesh Gude Subbaraya, and Kavitha Shimoga Divakar. "Process Capability Assessment Using Vision System." International Journal of Modern Manufacturing Technologies 13, no. 2 (December 20, 2021): 96–102. http://dx.doi.org/10.54684/ijmmt.2021.13.2.96.
Full textMazule, L., S. Liukaityte, R. C. Eckardt, A. Melninkaitis, O. Balachninaite, and V. Sirutkaitis. "A system for measuring surface roughness by total integrated scattering." Journal of Physics D: Applied Physics 44, no. 50 (December 2, 2011): 505103. http://dx.doi.org/10.1088/0022-3727/44/50/505103.
Full textZhu, Ming, Qi Yong Zeng, Kai Wu, Tao Hong, and Xiao Feng Zheng. "Surface Roughness Measuring System Design for Cutting Workpiece Based on Machine Vision Technology." Applied Mechanics and Materials 128-129 (October 2011): 434–38. http://dx.doi.org/10.4028/www.scientific.net/amm.128-129.434.
Full textGarcía Plaza, Eustaquio, Pedro Jose Núñez López, Francisco Mata, and A. Sanz. "Machining Control of Surface Roughness by Measuring Cutting Forces." Advanced Materials Research 498 (April 2012): 157–62. http://dx.doi.org/10.4028/www.scientific.net/amr.498.157.
Full textZhao, Yan Ling, Si Hai Cui, Liang Zhu, and Feng Ling Wu. "Design and Realization of Roughness Measurement System Based on DM642." Applied Mechanics and Materials 16-19 (October 2009): 1025–29. http://dx.doi.org/10.4028/www.scientific.net/amm.16-19.1025.
Full textDissertations / Theses on the topic "Roughness class measuring system"
Тимко, Олександр Олександрович. "Оптико-електронна вимірювальна система класу шорсткості поверхні оптичних об’єктів." Bachelor's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/34787.
Full textThesis project on "Optical-electronic measuring system of the surface roughness class of optical objects" consists of an explanatory note of 64 pages, 14 figures, 8 tables, 17 references. The technical task for the diploma project was to design an opto-electronic measuring system so that the user could automatically determine the class of surface roughness using software and measuring system. In the diploma the analytical research of methods of definition of a class of roughness was carried out. Namely, the raster method, the method of light and shadow glow, the microinterference method and the logarithmic method. It should be noted that most methods for determining the roughness of an object are based on optical microscopy. Therefore, to build a measuring system for determining the class of surface roughness, we chose the optical method as a basis. The analytical review of devices and systems of analogues for determination of surface roughness is carried out in the work. Namely, we considered a device for measuring optically transparent objects, a device for determining roughness, a station for monitoring the roughness and contour of the surface Homm el Tester T8000 and a surface roughness meter MicroProf 200. We considered the advantages and disadvantages of each system or device analogues and determined , which we choose as a basis for designing our own measuring system. We started designing our own system by building a block diagram of the measuring system and determining the components. The following components were selected and substantiated: CCD array cameras, optical system or device, light filters, power supply, lighting source, video capture program. On the basis of these units the laboratory stand of the optoelectronic measuring system of a class of roughness of a surface is designed. Before the start of the measurement, we performed experimental studies of the characteristics of the measuring stand (optoelectronic system), namely, the study of light signal characteristics and spectral characteristics. In the diploma project the analysis of requirements for accuracy of measurement by optoelectronic measuring system is carried out. The calculation of the energy illuminance of the surface of the object of study, ie the surface for which we determine the roughness class. The illuminance of the surface of the object of measurement was experimentally studied in two different ways (using a photometer and using a luxmeter). We designed and assembled the photometer ourselves, but we chose the luxmeter ready for measurement. Then we compared the experimental results of the illumination of the surface of the object of study. In the bachelor’s thesis, we selected and substantiated the objects that we will use as tests. We noted that to ensure proper operation and confirmation of this fact, we have chosen a reference test object of micrometric size, namely the dashed measure according to GOST. On the designed laboratory version of the optoelectronic measuring system, we conducted a series of studies with a sample (glass with a rough surface). We prescribed the method of research and determination of the class of floor roughness, which was done experimentally and presented the results of these studies in the thesis and work. A package of drawings was made for the diploma project in accordance with the technical task of the bachelor’s diploma project.
Hu, Fengxuan. "Development and evaluation of an inertial based pavement roughness measuring system." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001641.
Full textHe, Zaiqian. "Investigation of a multi-purpose optical measurement system /." View abstract or full-text, 2005. http://library.ust.hk/cgi/db/thesis.pl?IEEM%202005%20HE.
Full textMarchiori, Marcelo Mennet. "Estudo de um sistema de medição a laser na análise da textura da superfície gerada por torneamento." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2013. http://hdl.handle.net/10183/79829.
Full textThe determination of the roughness is a key for a good classification of a surface. Thereby, the work was started with a study about the roughness measurements methods. Due to the great adaptability and speed of laser methods, the studies were directed to these kinds of measurement techniques. It was observed in the literature that these laser devices were linked to systems where the reflected laser was analyzed by systems with CCD detectors, where the reflected image was entirely analyzed. Hence, the bibliography brought inspiration to measure the surface roughness generated by axial turning from the intensity of the reflected laser. It was proposed then a measurement method exclusively based on the intensity of the signal that was reflected by the surface under study, because the authors noted that as the roughness of surface became bigger as the signal reflected is became smaller. The proposed system has been assembled and ability to distinguish different roughness was tested successfully. Then samples were produced with different roughness in order to obtain a function that would correlate the laser signal with its roughness (this measurement is made by tactile measurement instrument). The transfer function obtained was tested on different samples that generated in order to prove its efficacy. Samples produced with different cutting tools were also produced and subjected to the same procedure. The transfer functions reached a successful prediction of the roughness maximum for 16.6% of the points assuming a margin of error of 20%. So, looking up the reasons that could have caused this percentage we think the possibility as the occurrence of some optical effects that can cause interference due to irregularities on the surface. These optical effects can degenerate the reflected signal. The proof that the signal could possibly be corrupted was made by the bibliographic references and some images obtained by scanning electron microscopy in which they could observe the existence of structures on the sample surfaces that would can be a reason for these effects individually or together.
CHEN, YING-CHIAO, and 陳映喬. "Development of a Portable Non-contact Measuring System for Surface Roughness and Surface Profile." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/b5mz8k.
Full text國立臺灣科技大學
機械工程系
107
The purpose of this study is to develop a portable non-contact surface measurement system that can be used to evaluate the surface profile and roughness after polishing. The laser beam, passing through the collimating lens and by changing the grating mask, one to three parallel beams can be generated. The beams projected on the object and then reflected on the imaging screen. Then, the image on the screen were captured by the CCD industrial camera for further analysis. In this study, LabVIEW is used as the main programming tool. With the help of the NI Vision Assistant software, the captured image can be filtered in the first stage and the generated code can be written in LabVIEW with graphical program. This study is divided into two parts: surface roughness measurement and surface contour measurement. The surface roughness of a test object is measured by using the reflected light intensity method, the suitable threshold value, which was used to evaluate the roughness of the test piece, has been found by analyzing the relationship between the roughness value and the reflection image. The measurement system is attempted to be integrated with the robot arm for the possible in-process measurement after the surface finishing processing has been achieved. Regarding the surface contour measurement, different curved surfaces will reflect the laser light fringes at different positions on the screen. A relationship equation between the position of light spots, which reflect from the curved surface and the surface parameter, and then the height, the X-axis and the Y-axis rotation angle of the object, has been verify by the derived relational equations, respectively. According to the experimental results, the threshold value of the roughness measurement for our system was 90, the test piece with the surface roughness of 0.02μm-0.2μm can be measured. With regard to the surface profile measurement, the result was verified by the relational equation. The actual measurement of the cylindrical profile of a test object is consistent with the data obtained by the contact measurement system.
Yang, Ching-Kun, and 楊景焜. "A study of non-contact surface roughness measuring system for the steel with good surface finishing." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/54002551212158649186.
Full text國立臺灣科技大學
機械工程系
89
The Objective of this study is to develop a non-contact surface roughness measuring system for the steel with good surface finishing (Ra=0.04~0.8µm). The system consists of four major parts, namely the line projector, a X-Y stage to move the specimen, CCD camera, and image analysis software. The measuring principle of the developed system based on the scattering characteristics of the laser beam projected on a workpiece surface with homogenous surface roughness. The larger the surface roughness value the larger the correspondent line width. The line width of the image was determined by the so-called edge detection method through calculating the first derivative of the smoothed image filtered by average filter and then finding the maximum slope position. A back propagation neural network was also developed in this study to predict the unknown surface roughness of the specimen via the measured line width by training the experimental surface roughness and line width data. According to the experimental results, the predicted surface roughness through back propagation neural network method was more accurate than that of the second order, third order, and fourth order polynomial curve fitting of the experimental surface roughness and line width data.
Kao, Hsiang-Lun, and 高祥倫. "Development of a Non-Contact and Optical Measuring Automation System for the Surface Roughness of Disk Cams." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/y2627w.
Full text國立臺灣海洋大學
機械與機電工程學系
105
Disk cam mechanisms are still applied in a wide variety of machinery, and disk cams are their essential parts. Disk cams are contact-type transmission elements, so the surface roughness of their profiles must be well to avoid excessive vibration and noise occurring at high-speed operations of the machinery. In order to make disk cams achieve excellent performance, the roughness surfaces of machined cam profiles must be inspected for quality control. This thesis aims at developing a non-contact and optical measuring automation system for measuring the surface roughness of disk cams. Technologies of precision machinery, motion control, logic control, optical measurement, machine vision, image processing, and data acquisition must be integrated into one system to realize the automated optical measurement of the surface roughness of disk cams. Firstly, by applying the laser scattering phenomena occurred when a laser beam illuminates the surface of an object, a non-contact measuring method called the speckle-spot area method was proposed in this study for measuring of the surface roughness of the cam profile. The speckle-spot area method is based on the use of a laser displacement meter (a laser point light source) to illuminate the cam profile surface, and to capture the speckle images by using a camera. The speckle images are then dealt with by image processing to obtain the areas of the speckles, and the surface roughness values of the cam profile to be measured are calculated through using a correlation curve. Numerous data of speckle images were obtained through experiments in this study, and the correlation curve between the speckle area and the surface roughness value was obtained by using regression analysis. Secondly, in order construct an optical measuring automation system to realize the proposed method, a measuring machine for examining the profile accuracy of disk cams developed in previous study was improved by adding a rotary motion stage and a roughness-measuring vision module, and the necessary system integration and the development of an automated measuring procedure were carried out. Finally, practical experiments were conducted. The experimental results showed that the developed system could achieve a repeatability range of ±0.15 μm when considering the mean roughness values and the extreme roughness values of the contour points on individual cam samples. Also, by considering the total mean values of the mean roughness values and of the extreme roughness values obtained by the developed system and by a traditional contact-type roughness measuring system, respectively, relative measuring errors between the two systems could achieve a range of ±0.03 μm. Therefore, the proposed speckle-spot area method in combined with the developed non-contact and optical measuring automation system indeed can realize the surface roughness measurement of disk cams with high precision and high accuracy.
Book chapters on the topic "Roughness class measuring system"
Santagata, E., and S. Sciamanna. "Development of a new response-type road roughness measuring system." In Sustainability, Eco-efficiency, and Conservation in Transportation Infrastructure Asset Management, 711–18. CRC Press, 2014. http://dx.doi.org/10.1201/b16730-104.
Full textAkhtar, Imtisal, Malik Abdul Rehman, and Yongho Seo. "Measuring the Blind Holes: Three-Dimensional Imaging of through Silicon via Using High Aspect Ratio AFM Probe." In 21st Century Surface Science - a Handbook. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.92739.
Full textKhimicheva, Ganna, and Oleksii Dziuba. "BACKGROUND FOR DEVELOPING THE PARAMETER CONTROL SYSTEM OF THE COMFORT ZONE OF OFFICE PREMISES." In Development of scientific, technological and innovation space in Ukraine and EU countries. Publishing House “Baltija Publishing”, 2021. http://dx.doi.org/10.30525/978-9934-26-151-0-35.
Full textReid, Samuel, and Travis West. "Measuring the Frequency of Critical Thinking in a Second Language Academic Discussion Course." In Development of Innovative Pedagogical Practices for a Modern Learning Experience, 237–68. CSMFL Publications, 2021. http://dx.doi.org/10.46679/978819484836309.
Full textPetryshyn, Igor, and Olexandr Bas. "NATURAL GAS HEAT COMBUSTION DETERMINATION ON MEASURING SYSTEMS WITH DUPLICATE GAS UNITS." In Integration of traditional and innovative scientific researches: global trends and regional aspect. Publishing House “Baltija Publishing”, 2020. http://dx.doi.org/10.30525/978-9934-26-001-8-2-8.
Full textLarson, Richard S., and Alexandre Chigaev. "Applications of Flow Cytometry to Cell Adhesion Biology: From Aggregates to Drug Discovery." In Flow Cytometry for Biotechnology. Oxford University Press, 2005. http://dx.doi.org/10.1093/oso/9780195183146.003.0023.
Full textConference papers on the topic "Roughness class measuring system"
Na, Xiao-Feng, Zhaobang Pu, and Xiu-Mei Wen. "High- precision measuring system of surface roughness." In Measurement Technology and Intelligent Instruments, edited by Li Zhu. SPIE, 1993. http://dx.doi.org/10.1117/12.156507.
Full textHan, Jinhong, Yunkai Wang, and Xianfeng Zhang. "A measuring system for surface roughness parameters." In Third International Symposium on Precision Mechanical Measurements. SPIE, 2006. http://dx.doi.org/10.1117/12.716176.
Full textIsakson, Marcia J., Paul Abkowitz, Michael Rukavina, Zel Hurwitz, and Isaac Metcalf. "Measuring seafloor roughness using an ROV mounted laser profiling system." In OCEANS 2016 MTS/IEEE Monterey. IEEE, 2016. http://dx.doi.org/10.1109/oceans.2016.7761135.
Full textHaiping, Lu, Xu Chunliang, Jia Mingquan, and Chen Yan. "A New Type and Facile Measuring System of Soil Roughness." In 2008 International Workshop on Geoscience and Remote Sensing (ETT and GRS). IEEE, 2008. http://dx.doi.org/10.1109/ettandgrs.2008.116.
Full textAn, Deok-Soon, Jeong-Hee Nam, and Soo-Ahn Kwon. "Calibration of Roughness Measuring Instrument for Adopting the Performance Warranty System." In GeoHunan International Conference 2009. Reston, VA: American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/41047(354)9.
Full textKumar, Lohith, Teja Tallam, Naveen Kumar ChikkaKrishna, Muppa Karunakar Reddy, and S. Pradeep Reddy. "Response Type Road Roughness Measuring System from a Vehicle Mounted Android Smartphone." In 2022 IEEE Delhi Section Conference (DELCON). IEEE, 2022. http://dx.doi.org/10.1109/delcon54057.2022.9753508.
Full textDeng, Zhicong, and Masanori Kurita. "Development of an optical system for measuring the roughness of blasted surfaces." In International Conference on Sensors and Control Techniques (ICSC2000), edited by Desheng Jiang and Anbo Wang. SPIE, 2000. http://dx.doi.org/10.1117/12.385553.
Full textMa, Jing, and Kun Ma. "Simultaneous Stabilization for a Class of Generalized Linear System." In 2009 International Conference on Measuring Technology and Mechatronics Automation. IEEE, 2009. http://dx.doi.org/10.1109/icmtma.2009.404.
Full textSnezhko, Yury. "Mathematical modeling of amplitude-phase measuring system for a precision surface-roughness registration." In San Diego '92, edited by Katherine Creath and John E. Greivenkamp. SPIE, 1992. http://dx.doi.org/10.1117/12.139241.
Full textLi, Zhanhong, and Jianxin Liu. "The In-process and Real-Time Roughness Measuring System Design for Free-Form Surface." In 2010 International Conference on Computational and Information Sciences (ICCIS). IEEE, 2010. http://dx.doi.org/10.1109/iccis.2010.205.
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