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 Improving Machined Surface Shape Prediction by Integrating Multi-Task Learning With Cutting Force Variation Modeling

2016 ◽  
Vol 139 (1) ◽  
Author(s):  
Chenhui Shao ◽  
Jie Ren ◽  
Hui Wang ◽  
Jionghua (Judy) Jin ◽  
S. Jack Hu
Keyword(s):  
Cutting Force ◽  
Spatial Data ◽  
Critical Role ◽  
Measurement Data ◽  
Multitask Learning ◽  
Surface Shape ◽  
Surface Model ◽  
Model Parameters ◽  
Shape Prediction ◽  
Force Variation

The shapes of machined surfaces play a critical role affecting powertrain performance, and therefore, it is necessary to characterize the shapes with high resolution. State-of-the-art approaches for surface shape characterization are mostly data-driven by interpolating and extrapolating the spatial data but its precision is limited by the density of measurements. This paper explores the new opportunity of improving surface shape prediction through considering the similarity of multiple similar manufacturing processes. It is a common scenario when the process of interest lacks sufficient data whereas rich data could be available from other similar-but-not-identical processes. It is reasonable to transfer the insights gained from other relevant processes into the surface shape prediction. This paper develops an engineering-guided multitask learning (EG-MTL) surface model by fusing surface cutting physics in engineering processes and the spatial data from a number of similar-but-not-identical processes. An iterative multitask Gaussian process learning algorithm is developed to learn the model parameters. Compared with the conventional multitask learning, the proposed method has the advantages in incorporating the insights on cutting force variation during machining and is potentially able to improve the prediction performance given limited measurement data. The methodology is demonstrated based on the data from real-world machining processes in an engine plant.

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.

Autocorrelation Phase Measurement of Spread Spectrum Signal for High Precision Indoor Microwave Positioning

2015 ◽  
Vol 734 ◽  
pp. 31-39
Author(s):  
Wen Yang Cai ◽  
Gao Yong Luo
Keyword(s):  
High Precision ◽  
Spread Spectrum ◽  
Phase Measurement ◽  
Wide Band ◽  
Cost Effective ◽  
Local Area ◽  
Indoor Positioning ◽  
60 Ghz ◽  
Positioning Method ◽  
Increasing Demand

The increasing demand for high precision indoor positioning in many public services has urged research to implement cost-effective systems for a rising number of applications. However, current systems with either short-range positioning technology based on wireless local area networks (WLAN) and ZigBee achieving meter-level accuracy, or ultra-wide band (UWB) and 60 GHz communication technology achieving high precision but with high cost required, could not meet the need of indoor wireless positioning. This paper presents a new method of high precision indoor positioning by autocorrelation phase measurement of spread spectrum signal utilizing carrier frequency lower than 1 GHz, thereby decreasing power emission and hardware cost. The phase measurement is more sensitive to the distance of microwave transmission than timing, thus achieving higher positioning accuracy. Simulation results demonstrate that the proposed positioning method can achieve high precision of less than 1 centimeter decreasing when various noise and interference added.

scholarly journals The Swiss joint information platform for natural hazards

2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Philipp Angehrn ◽  
Sabina Steiner ◽  
Christophe Lienert
Keyword(s):  
Natural Hazards ◽  
Spatial Data ◽  
Natural Hazard ◽  
Regional Scale ◽  
Measurement Data ◽  
User Feedback ◽  
Acceptance Testing ◽  
Spatial Density ◽  
Data Sets ◽  
Information Platform

<p><strong>Abstract.</strong> The Swiss Joint Information Platform for Natural Hazards (GIN) has been realized from 2008 to 2010 as part of the Swiss federal government’s OWARNA project, which aimed at optimizing warning and alerting procedures against natural hazard. The first online-version of the platform went productive in 2011 with the primary goal of providing measured and forecast natural hazard data in form of processed cartographic, graphic and other multimedia products to professional users &amp;ndash; before, during and after natural hazard events. In Switzerland water-, weather-, snow- and earthquake-related hazards are the most relevant ones.</p><p>In 2013, an online survey showed that the platform does not fully meet user expectations, particularly as to user experience and usability of its cartographic, web-based user interface. Revaluation and redesign of the overall platform were necessary in order to improve map legibility, caused by the complexity of data, large data amounts, and high spatial density of online, real-time measurement data locations. A new web design and user interaction concept have been developed in 2014 and eventually put online in June 2017. User acceptance testing by means of surveys and direct user feedback sessions were key factors in this perennial redesign process. The GIN platform now features important novel technical and graphical elements: The starting page is based on a dashboard containing virtual dossiers (Fig. 1), with which users configure their desired information, data, and map bundles individually, or use predefined adaptable views on various existing data sets. In addition, there is a new overall spatial search function to query data parameters. A responsive approach further improves the usability of the platform. The focus of these new features is on multi-views involving maps, diagrams, tables, text products, as well as selected geographical areas on maps, and fast data queries (Fig. 2). Current user feedback suggests that the new GIN platform design is well received, and that it is moving closer to its very goal: online monitoring and management of natural hazard events by enhanced usability, more targeted and higher personalization.</p><p>Several Swiss Cantons (i.e., the political entities in Switzerland below the federation) actively participated, and still participate, in the conceptual GIN platform development process through advisory board meetings and consultations. On the operational level, Cantons actively provide and contribute further natural hazard information and measurement data from their own natural hazard monitoring networks. These additional Cantonal regional-scale data sets help to fill spatial data gaps, where no Federal data is available. GIN thusly integrates natural hazard data from Federal and Cantonal levels (and partly even private level), which adds value to all stakeholders on various political levels involved in natural hazard management (Federal, Cantonal, Regional, Communal crisis committees). Stakeholders not only use GIN’s ample database and cartographic product portfolio to accomplish their early warning and crisis management tasks, but also benefit from seamless, secure and reliable IT-services, provided by the Swiss Federal Government. With the new GIN platform, Switzerland has a powerful, integrative, and comprehensive tool for monitoring and responding to natural hazard events.</p>

scholarly journals Estimation of Building Heights and DEM Accuracy Assessment Using ICESat-2 Data Products

2021 ◽  
Vol 10 (1) ◽  
pp. 37
Author(s):  
Goddu Pavan Sai Goud ◽  
Ashutosh Bhardwaj
Keyword(s):  
Spatial Data ◽  
Rural Areas ◽  
Urban Areas ◽  
Accuracy Assessment ◽  
Urban Expansion ◽  
Population Expansion ◽  
Cost Effective ◽  
Absolute Error ◽  
Google Earth ◽  
Surface Geometry

The use of remote sensing for urban monitoring is a very reliable and cost-effective method for studying urban expansion in horizontal and vertical dimensions. The advantage of multi-temporal spatial data and high data accuracy is useful in mapping urban vertical aspects like the compactness of urban areas, population expansion, and urban surface geometry. This study makes use of the ‘Ice, cloud, and land elevation satellite-2′ (ICESat-2) ATL 03 photon data for building height estimation using a sample of 30 buildings in three experimental sites. A comparison of computed heights with the heights of the respective buildings from google image and google earth pro was done to assess the accuracy and the result of 2.04 m RMSE was obtained. Another popularly used method by planners and policymakers to map the vertical dimension of urban terrain is the Digital Elevation Model (DEM). An assessment of the openly available DEM products—TanDEM-X and Cartosat-1 has been done over Urban and Rural areas. TanDEM-X is a German earth observation satellite that uses InSAR (Synthetic Aperture Radar Interferometry) technique to acquire DEM while Cartosat-1 is an optical stereo acquisition satellite launched by the Indian Space Research Organization (ISRO) that uses photogrammetric techniques for DEM acquisition. Both the DEMs have been compared with ICESat-2 (ATL-08) Elevation data as the reference and the accuracy has been evaluated using Mean error (ME), Mean absolute error (MAE) and Root mean square error (RMSE). In the case of Greater Hyderabad Municipal Corporation (GHMC), RMSE values 5.29 m and 7.48 m were noted for TanDEM-X 90 and CartoDEM V3 R1 respectively. While the second site of Bellampalli Mandal rural area observed 5.15 and 5.48 RMSE values for the same respectively. Therefore, it was concluded that TanDEM-X has better accuracy as compared to the CartoDEM V3 R1.

MULTI-TONE WAVEFORM MEASUREMENT SYSTEM ENABLING CHARACTERIZATION OF MICROWAVE DEVICES

2014 ◽  
Vol 23 (10) ◽  
pp. 1450141
Author(s):  
MUHAMMAD AKMAL CHAUDHARY ◽  
JONATHAN LEES ◽  
JOHANNES BENEDIKT ◽  
PAUL TASKER
Keyword(s):  
Measurement System ◽  
Measurement Data ◽  
Quality Measurement ◽  
Cost Effective ◽  
Operating Conditions ◽  
Efficient Manner ◽  
Vector Error Correction ◽  
Sampling Oscilloscope ◽  
Rf Components ◽  
Vector Error

This paper presents a fully automated time domain, waveform measurement system, capable of measuring multi-tone waveforms up to a frequency of 14 GHz. Multi-tone waveform measurement capabilities will prove useful in enhancing the understanding of the response of devices under realistic operating conditions, and allow for detailed investigation into device problems leading to memory effects. The system, which is based around a standard sampling oscilloscope, is capable of measuring all four traveling waves simultaneously. It is a cost effective solution, capable of capturing high quality measurement data, it consists of two test sets one to measure RF components of the signal and one to measure IF components, which are then recombined before being measured by the sampling oscilloscope. Vector error correction is applied to the measured data to fully calibrate the system to the device plane, ensuring any dispersion in the connecting hardware is removed. A multi-tone waveform sampling method is employed, ensuring the waveforms are captured in the most efficient manner. Device results are presented showing the multi-tone voltage and current waveforms at the device plane. Some useful applications of the system are demonstrated and explained.

Research on the High Precision Laser Line Scanning Measuring System

2007 ◽  
Vol 339 ◽  
pp. 131-135 ◽  
Author(s):  
Jian Jun Ding ◽  
Zhuang De Jiang ◽  
Bing Li ◽  
Jun Jie Guo
Keyword(s):  
High Precision ◽  
Laser Scanning ◽  
Laser Line ◽  
Measuring System ◽  
Surface Measurement ◽  
Iteration Algorithm ◽  
Reconstruction Method ◽  
Loop Feedback ◽  
Axis Position ◽  
Line Scanning

Rapid reverse technology is one of the key technologies with which the enterprises develop new product and occupy the market rapidly. How to realize the reverse measurement and CAD geometry reconstruction rapidly and accurately is always the most important focus for the researchers. Based on the laser scanning technology, the realization principle of the laser line scanning measuring system is presented and the approaches to improve the precision are also analysed in the paper. The self-adaptation adjustment of the probe position can move the light knife image to the optimal imaging area of the CCD according to the calibration result, which will ensure the measurement precision of the CCD image. With the inner velocity loop and outer position loop feedback control, the simple axis position precision of the mechanical system can be controlled within 5um. In order to pick up the points of the light knife centre rationally and exactly, the reconstruction-disperse iteration algorithm is put forward. After processed by different iteration times, the optimal points can be obtained. The reconstruction method of curve and surface based on NURBS is also given. The paper presents the application and realization of the system at last, which realizes the curve and surface measurement with high precision.

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