Method of signal singularity identification and correction in road surface measurement data

2010 ◽  
Vol 24 (9) ◽  
pp. 878-884
Author(s):  
Ying Ma ◽  
Huming Duan ◽  
Fei Xie ◽  
Kaibin Zhang
Keyword(s):  
Measurement Data ◽  
Road Surface ◽  
Surface Measurement

scholarly journals Data-Driven Intelligent 3D Surface Measurement in Smart Manufacturing: Review and Outlook

Machines ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 13
Author(s):  
Yuhang Yang ◽  
Zhiqiao Dong ◽  
Yuquan Meng ◽  
Chenhui Shao
Keyword(s):  
High Resolution ◽  
High Performance ◽  
Sampling Design ◽  
Three Dimensional ◽  
Measurement Data ◽  
Data Driven ◽  
Surface Measurement ◽  
Smart Manufacturing ◽  
Future Research ◽  
3D Surface

High-fidelity characterization and effective monitoring of spatial and spatiotemporal processes are crucial for high-performance quality control of many manufacturing processes and systems in the era of smart manufacturing. Although the recent development in measurement technologies has made it possible to acquire high-resolution three-dimensional (3D) surface measurement data, it is generally expensive and time-consuming to use such technologies in real-world production settings. Data-driven approaches that stem from statistics and machine learning can potentially enable intelligent, cost-effective surface measurement and thus allow manufacturers to use high-resolution surface data for better decision-making without introducing substantial production cost induced by data acquisition. Among these methods, spatial and spatiotemporal interpolation techniques can draw inferences about unmeasured locations on a surface using the measurement of other locations, thus decreasing the measurement cost and time. However, interpolation methods are very sensitive to the availability of measurement data, and their performances largely depend on the measurement scheme or the sampling design, i.e., how to allocate measurement efforts. As such, sampling design is considered to be another important field that enables intelligent surface measurement. This paper reviews and summarizes the state-of-the-art research in interpolation and sampling design for surface measurement in varied manufacturing applications. Research gaps and future research directions are also identified and can serve as a fundamental guideline to industrial practitioners and researchers for future studies in these areas.

Study on the symmetrical laser displacement sensor for the road surface measurement

2010 ◽  
Author(s):  
Hongxun Song ◽  
Ronggui Ma ◽  
Yi Zhang ◽  
Hui Ding ◽  
Ning Zhang
Keyword(s):  
Road Surface ◽  
Displacement Sensor ◽  
Surface Measurement ◽  
Laser Displacement Sensor ◽  
The Road

Surface Variation Modeling by Fusing Surface Measurement Data With Multiple Manufacturing Process Variables

2016 ◽  
Author(s):  
Jie Ren ◽  
Hui Wang
Keyword(s):  
High Precision ◽  
Spatial Data ◽  
Measurement Data ◽  
Cost Effective ◽  
Surface Shape ◽  
Surface Measurement ◽  
Process Variables ◽  
Process Information ◽  
Surface Variation ◽  
Sampled Measurements

Controlling surface shape variations plays a key role in high-precision manufacturing. Most manufacturing plants rely on a number of multi-resolution measurements on manufactured surfaces to evaluate surface shapes and resultant quality. Conventional research on surface shape modeling focused on interpolation and extrapolation of spatial data using sampled measurements based on presumed spatial relationship over entire surface locations. However, the prediction accuracy is heavily restricted by the density of sampled measurements, preventing cost-effective evaluation of surface shape in high precision. New opportunities emerge for cost-effective high-precision surface manufacturing when the industry begins to extensively collect in-plant process information. This paper explores the opportunity by investigating strategies for fusing surface measurement data with multiple process variables. The fusion is achieved by characterizing the relationships between surface height and process variables using (1) linear regression based co-Kriging and (2) fuzzy if-then rules as well as considering spatial correlations. Under (3) Bayesian sequential updating frameworks, a generic surface variation model is updated sequentially using different process information. Case studies are conducted for comparisons and demonstrate the advantages of the fuzzy inference based spatial model.

scholarly journals Review on the Surface Heat Transfer Coefficients of Radiant Systems

2019 ◽  
Vol 111 ◽  
pp. 01075 ◽  
Author(s):  
Jun Shinoda ◽  
Ongun B. Kazanci ◽  
Shin-ichi Tanabe ◽  
Bjarne W. Olesen
Keyword(s):  
Heat Transfer ◽  
Heated Surface ◽  
Measurement Data ◽  
Radiant Heat ◽  
Surface Measurement ◽  
Radiant Heat Transfer ◽  
Extensive Literature ◽  
Prediction Errors ◽  
Transfer Coefficients ◽  
Heat Transfer Coefficients

Heat transfer coefficients are often used to describe the thermal behaviour of radiant systems and how it transfers heat between the cooled/heated surface and the room. In addition to current standards, numerous studies have been conducted to obtain the heat transfer coefficients through experiments and simulations. However, inconsistency is evident in the values or expressions suggested. Thus, this study investigated possible sources of discrepancy through an extensive literature review on articles and standards that focused on the heat transfer coefficients at the cooled/heated surface. Measurement data provided by different authors were extracted to compare both the amount of heat transfer and the actual heat transfer coefficients. Consequently, suggested values and expressions were used to predict the measurement data in other articles to examine their accuracy. Comparison of the results showed that the radiant heat transfer coefficients had a consistent value throughout the literature and had prediction error within ±20%. However, larger deviations and prediction errors were seen in the total and convective heat transfer. It was suggested that some of the sources of error may have been the calculation procedure of each heat transfer mechanism, choice of reference temperature and its measurement height/position, and room dimensions.

ANALYSIS OF THE MATERIAL REMOVAL RATE IN MAGNETIC ABRASIVE FINISHING OF THIN FILM COATED PYREX GLASS

2017 ◽  
Vol 24 (Supp01) ◽  
pp. 1850004
Author(s):  
HEE HWAN LEE ◽  
SEOUNG HWAN LEE
Keyword(s):  
Process Monitoring ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Measurement Data ◽  
Surface Measurement ◽  
Time Interval ◽  
Magnetic Abrasive Finishing ◽  
Afm Indentation ◽  
Abrasive Finishing

The material removal rate (MRR) during precision finishing/polishing is a key factor, which dictates the process performance. Moreover, the MRR or wear rate is closely related to the material/part reliability. For nanoscale patterning and/or planarization on nano-order thickness coatings, the prediction and in-process monitoring of the MRR is necessary, because the process is not characterizable due to size effects and material property/process condition variations as a result of the coating/substrate interactions. The purpose of this research was to develop a practical methodology for the prediction and in-process monitoring of MRR during nanoscale finishing of coated surfaces. Using a specially designed magnetic abrasive finishing (MAF) and acoustic emission (AE) monitoring setup, experiments were carried out on indium-zinc-oxide (IZO) coated Pyrex glasses. After a given polishing time interval, AFM indentation was conducted for each workpiece sample to measure the adhesion force variations of the coating layers (IZO), which are directly related to the MRR changes. The force variation and AE monitoring data were compared to the MRR calculated form the surface measurement (Nanoview) results. The experimental results demonstrate strong correlations between AFM indentation and MRR measurement data. In addition, the monitored AE signals show sensitivity of the material structure variations of the coating layer, as the polishing progresses.

scholarly journals Metrology Data-Based Simulation of Freeform Optics

2018 ◽  
Vol 8 (12) ◽  
pp. 2338 ◽  
Author(s):  
Ingo Sieber ◽  
Allen Yi ◽  
Ulrich Gengenbach
Keyword(s):  
Performance Prediction ◽  
Simulation Analysis ◽  
Measurement Data ◽  
Surface Measurement ◽  
Measurement Tool ◽  
Freeform Surfaces ◽  
Microinjection Molding ◽  
Surface Data ◽  
Freeform Optics ◽  
Accurate Performance

This paper describes the approach to use measurement data to enhance the simulation model for designing freeform optics. Design for manufacturing of freeform optics is still challenging, since the classical tolerancing procedures cannot be applied. In the case of spherical optics manufacturing, tolerances are more or less isotropic, and this relationship is lost in case of freeform surfaces. Hence, an accurate performance prediction of the manufactured optics cannot be made. To make the modeling approach as accurate as possible, integration of measured surface data of fabricated freeform optics in the modeling environment is proposed. This approach enables performance prediction of the real manufactured freeform surfaces as well as optimization of the manufacturing process. In our case study this approach is used on the design of an Alvarez-optics manufactured using a microinjection molding (µIM) process. The parameters of the µIM process are optimized on the basis of simulation analysis resulting in optics, with a performance very close to the nominal design. Measurement of the freeform surfaces is conducted using a tactile surface measurement tool.

scholarly journals Analysis of a novel tool path generation method for corrective machining in ultra-precision diamond turning based on point clouds

2021 ◽  
Author(s):  
Marco Buhmann ◽  
Erich Carelli ◽  
Christian Egger ◽  
Klaus Frick
Keyword(s):  
Point Cloud ◽  
Tool Path ◽  
Cutting Tool ◽  
Measurement Data ◽  
Tool Path Generation ◽  
Diamond Turning ◽  
Surface Measurement ◽  
Computation Method ◽  
Path Generation ◽  
Ultra Precision

Abstract The increasing demand for machining non-rotational optical surfaces requires capable and flexible cutting tool path generation methods for ultra-precision diamond turning. Furthermore, the recent interest in on-machine metrology and corrective machining require efficient as well as accurate algorithms capable to handle point cloud based surface data. In the present work, a new computation method for the tool path generation is proposed that focuses on three-axes corrective machining. Therefore, it is based on the principle of defining the surface to be machined by a point cloud of certain density, since surface measurement data is usually available as point cloud. Numeric approximation techniques are used to compute the surface normal vectors and calculate the resulting positions of the cutting tool path preserving a uniform radial axis motion for face turning. Investigations are performed in order to quantify the error between the calculated tool path and the exact analytical solution. The error dependencies are analyzed regarding the local surface slope and numerical parameters. Error values below 1nm are achieved. In addition, form deviation results prove the method’s capability for corrective diamond turn machining.

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