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2011 | Buch

Large-Scale Dimensional Metrology: The New Paradigm of Distributed Systems Kapitel lesen Erstes Kapitel lesen

Distributed Large-Scale Dimensional Metrology

New Insights

verfasst von: Fiorenzo Franceschini, Maurizio Galetto, Domenico Maisano, Luca Mastrogiacomo, Barbara Pralio

Verlag: Springer London

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

The field of large-scale dimensional metrology (LSM) deals with objects that have linear dimensions ranging from tens to hundreds of meters. It has recently attracted a great deal of interest in many areas of production, including the automotive, railway, and shipbuilding sectors.

Distributed Large-Scale Dimensional Metrology introduces a new paradigm in this field that reverses the classical metrological approach: measuring systems that are portable and can be easily moved around the location of the measured object, which is preferable to moving the object itself.

Distributed Large-Scale Dimensional Metrology combines the concepts of distributed systems and large scale metrology at the application level. It focuses on the latest insights and challenges of this new generation of systems from the perspective of the designers and developers. The main topics are:

coverage of measuring area,sensors calibration,on-line diagnostics,probe management, andanalysis of metrological performance.

The general descriptions of each topic are further enriched by specific examples concerning the use of commercially available systems or the development of new prototypes. This will be particularly useful for professional practitioners such as quality engineers, manufacturing and development engineers, and procurement specialists, but Distributed Large-Scale Dimensional Metrology also has a wealth of information for interested academics.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Large-Scale Dimensional Metrology: The New Paradigm of Distributed Systems
Abstract
Besides classical centralized metrology instruments in which a stand-alone unit works independently to provide geometrical features of the object to be measured, recent approaches to Large-Scale Dimensional Metrology seem to turn their attention towards distributed metrology systems made of multiple components with small dimensions spread around the measuring volume. In general this network of sensors allows rapid dimensional measurements to be performed in relation to large-sized objects, with typical dimensions of several decametres. Distributed metrology systems introduce a new paradigm in the field of Large-Scale Dimensional Metrology, reversing the classical approach to dimensional metrology. Due to their nature, they are portable and can be easily transferred around the volume where the measurand is, instead of moving the measurand to the measuring machine. Compared to centralized systems, distributed systems may cover larger measuring volumes, with no need to reposition the instrumentation devices around the measured object. Portability, reconfigurability and ease of installation make these systems attractive for many industries that manufacture large-scale products.
Fiorenzo Franceschini, Maurizio Galetto, Domenico Maisano, Luca Mastrogiacomo, Barbara Pralio
Chapter 2. Indoor GPS (iGPS™)
Abstract
Indoor GPS is a recent laser-based distributed measurement system for dimensional measurements of large-size objects. The performance of iGPS™ depends both on the characteristics of the system components and their physical configuration. Hence, it is important to characterise its real capabilities and point out how they can be influenced by the system configuration and calibration. This chapter presents the system architecture, its hardware and software working principles and provides an exploratory evaluation of the system’s metrological performance, both in static and dynamic conditions.
Fiorenzo Franceschini, Maurizio Galetto, Domenico Maisano, Luca Mastrogiacomo, Barbara Pralio
Chapter 3. The Mobile Spatial Coordinate Measuring System
Abstract
The Mobile Spatial coordinate Measuring System (MScMS) has been recently designed to make dimensional measurements of large-sized objects. This system, based on modular architecture, consists of three basic parts: a network of sensing devices, distributed around the working area, a portable probe to measure the coordinate points of a reference object, and a data processing unit to store measurement data and process them by means of ad hoc application software. Within the MScMS framework, two systems based on different technologies have been developed at the Industrial Metrology and Quality Engineering Laboratory of Politecnico di Torino—DISPEA. The first (MScMS-I) is based on ultrasound technology whereas the second (MSCMS-II) is based on infrared photogrammetry. In this chapter, we discuss the system architecture and working principles. Furthermore, hardware/software implementation details and metrological performance of two prototypes of these systems are presented. Next, the MScMS is compared with well-tested and widespread instruments, such as classical Coordinate Measuring Machines, and with the iGPS™, described in Chap.​ 2.
Fiorenzo Franceschini, Maurizio Galetto, Domenico Maisano, Luca Mastrogiacomo, Barbara Pralio
Chapter 4. Positioning and Coverage of Distributed Devices
Abstract
As it strongly affects system performance in measuring 3D point coordinates, sensor positioning represents a challenging issue in Large-Scale Dimensional Metrology applications based on wireless sensor networks. In this chapter the wide variety of existing placement approaches are discussed according to two main categorization criteria, sensor mobility capabilities and deployment schemes. The main network design challenges—sensing and communication models, working environment geometry, operating conditions, physical constraints, measurement procedures, measurement tasks, and localisation techniques—are presented. A practical case study of sensor placement, applied within the framework of the MScMS, is discussed. An optimisation strategy for designing a stationary network is applied, involving working environment constraints, system functional characteristics, measurand geometry, and measurement task definition within the 3-dimensional network design. The network configurations resulting from a regular-grid based strategy and a genetic algorithms-based approach are compared in terms of overall costs, sensor availability and measurement precision.
Fiorenzo Franceschini, Maurizio Galetto, Domenico Maisano, Luca Mastrogiacomo, Barbara Pralio
Chapter 5. System Calibration calibration
Abstract
In order to properly work, every distributed system need to know several parameters about local metrological devices. Some of these parameters may change because of environmental factors such as vibrations, thermal change or other accidental reasons. For this reason, a careful calibration activity is needed to achieve the best accuracy. During this phase, which can be automated to some extent, the system calculates information like network device positions and bearings, local temperature, humidity, pressure and so on. All this information is used during the measurement phase. Errors during the calibration phase adversely affect the accuracy of the measurements.
Fiorenzo Franceschini, Maurizio Galetto, Domenico Maisano, Luca Mastrogiacomo, Barbara Pralio
Chapter 6. Self-Diagnostic Tools
Abstract
In order to prevent external and internal causes of error, distributed systems can implement some tests for on-line diagnostics. These tests verify the reliability of the measurements according to several acceptance criteria defined on the basis of empirical observations. After introducing the concept of “self-diagnostics” and “measurement reliability”, this chapter describes three diagnostic tests that were specifically developed for distributed metrology systems.
Fiorenzo Franceschini, Maurizio Galetto, Domenico Maisano, Luca Mastrogiacomo, Barbara Pralio
Chapter 7. Methodologies for Performance Enhancing
Abstract
Measurements can be affected by errors related to many sources, such as technological features of the measuring instrument, measurement procedure and conditions, and operator’s skill. Metrological performance of an instrument can be significantly enhanced by developing a correction model, able to compensate for recognized systematic errors. After an introduction to the concept of error correction, the core of this chapter is the presentation of a methodology aimed at identifying and correcting some of the most influential systematic errors. In particular, the case of MScMS-I is analysed in detail. Finally, some general ideas about the construction of homologous models for other large-scale metrology distributed systems (i.e., the MScMS-II and the iGPS™) are given.
Fiorenzo Franceschini, Maurizio Galetto, Domenico Maisano, Luca Mastrogiacomo, Barbara Pralio
Chapter 8. Evaluation of Measurement Uncertainty
Abstract
Precision and accuracy are of prime interest when analyzing quality in a measurement procedure. Precision provides information about the dispersion of the measured values with respect to the true value of the measurand. It describes an internal quality of the measurement process. In general, it is expressed by means of the uncertainty, which is a non-negative parameter characterizing the dispersion of the quantity values being attributed to the measurand. On the other hand, the term accuracy may only be used in comparison to reference values of the same measurand. Accuracy is a term relating the mean of the measurements to the reference value, while precision is representative of the spread of these measurements. Perfection in measurement can never be achieved since even a precise and accurate measurement will have some remaining uncertainty. It is best to use the term accuracy only as a quantitative term, or for broad comparisons between methods, and use the term uncertainty as the qualitative assessment. When the uncertainty of measurement is evaluated and stated, then the fitness of purpose for a particular application can be properly understood. In the present Chapter the discussion is focused on the principal techniques for uncertainty estimation in Large-Scale Dimensional Metrology applications. Practical examples referring to MScMS-I and MScMS-II are presented and discussed as well.
Fiorenzo Franceschini, Maurizio Galetto, Domenico Maisano, Luca Mastrogiacomo, Barbara Pralio
Backmatter
Metadaten
Titel
Distributed Large-Scale Dimensional Metrology
verfasst von
Fiorenzo Franceschini
Maurizio Galetto
Domenico Maisano
Luca Mastrogiacomo
Barbara Pralio
Copyright-Jahr
2011
Verlag
Springer London
Electronic ISBN
978-0-85729-543-9
Print ISBN
978-0-85729-542-2
DOI
https://doi.org/10.1007/978-0-85729-543-9

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