Combining multiple Large Volume Metrology systems: Competitive versus cooperative data fusion

Large Volume Metrology (LVM) tasks can require the concurrent use of several measuring systems. These systems generally consist of set of sensors measuring the distances and/or angles with respect to a point of interest so as to determine its 3D position. When combining different measuring systems, characterized by sensors of different nature, competitive or cooperative methods can be adopted for fusing data. Competitive methods, which are by far the most diffused in LVM, basically perform a weighted mean of the 3D positions determined by the individual measuring systems. On the other hand, for cooperative methods, distance and/or angular measurements by sensors of different systems are combined together in order to determine a unique 3D position of the point of interest.This paper proposes a novel cooperative approach which takes account of the measurement uncertainty in distance and angular measurements of sensors of different nature. The proposed approach is compared with classical competitive approaches from the viewpoint of the metrological performance. The main advantages of the cooperative approach, with respect to the competitive one, are: (i) it is the only option when the individual LVM systems are not able to provide autonomous position measurements (e.g., laser interferometers or single cameras), (ii) it is the only option when only some of the sensors of autonomous systems work correctly (for instance, a laser tracker in which only distance – not angular – measurements are performed), (iii) when using systems with redundant sensors (i.e. photogrammetric systems with a large number of distributed cameras), point localization tends to be better than that using the competitive fusion approach.     

Experimental characterization of consensus protocol for decentralized smart grid metering

The availability of intelligence at substation level, combined with the adoption of pervasive communication networks, offers technologies and opportunities to decentralized smart grid metering and control. In this domain self-organizing sensor networks equipped by distributed consensus protocols have been recognized as an effective enabling paradigm.The performance of these protocols is usually evaluated in simulation environments without considering the effects of real measurement transducers, data acquisition systems and communication systems. Attention is rarely paid to the influence of factors such as: the measurement uncertainty of the transducers, the effect of the limited bandwidth available on real radio systems, and the change of performance when real nodes enter and exit from the network during or among consensus procedure. The large scale deployment of this paradigm asks for comprehensive analysis aimed at assessing the impact of the non-idealities characterizing the real power system environment on the cooperative protocols performance. Armed with such a vision this paper aims at characterizing the performance of distributed consensus protocols in presence of uncertainty and non-ideality of the measurement instruments, of the measurement process and of the communication channel in a smart grid environment. Results obtained in simulation and real scenarios might be helpful hints in the implementation and use of this protocol in real networks.     

Validation and verification methodology of GSM network call duration measurement system

The article deals with the validation and verification methodology of the GSM network measurement system, as these systems performing call duration measurements fall within the scope of legal metrology. Because the number of calls in the GSM networks is very large, the test call sample size determination algorithm proposed in the paper. Correctly chosen sample size allows to take statistically significant decision about communication network call duration measurement system measurement error with chosen confidence level. The sample representativity issue is also discussed in the paper. The proposed methodology was tested experimentally.     

New criterion for evaluating the aptitude of measurement systems in process capability determination

In practice, carrying out statistical process control of manufacturing processes requires the use of measurement systems. These systems are not totally reliable because they are subject to inherent variability. This paper investigates the influence of measurement uncertainty on the analysis of manufacturing process capability. A new methodology is described that helps overcome the effect of measurement uncertainty in order to obtain a more accurate assessment of the capability of the production processes. This methodology presents a solution that ensures the metrological confirmation of the measurement processes, and it was developed for manufacturing processes centred at a nominal value and for off-centred processes. Moreover, an improved capability index integrated into the statistical process control is proposed for evaluating measurement systems. The index helps identify manufacturing process quality risks associated with uncertainty in measurement systems.     

Bayes filter for dynamic coordinate measurements – Accuracy improvment,data fusion and measurement uncertainty evaluation

This paper presents a novel methodology to improve the measurement accuracy of dynamic measurements. This is achieved by deducing an online Bayes optimal estimate of the true measurand given uncertain, noisy or incomplete measurements within the framework of sequential Monte Carlo methods. The estimation problem is formulated as a general Bayesian inference problem for nonlinear dynamic systems. The optimal estimate is represented by probability density functions, which enable an online, probabilistic data fusion as well as a Bayesian measurement uncertainty evaluation corresponding to the “Guide to the expression of uncertainty in measurement“. The efficiency and performance of the proposed methodology is verified and shown by dynamic coordinate measurements.     

Determination of thermal plume thickness using thermocouple cross correlation coefficient decay

A methodology to measure the thickness of a thermal boundary layer by cross correlating the signal from thermocouples is presented. It is shown that measurement of temperature, velocity, and boundary layer thickness is achievable using a single sensor utilizing three thermocouples rather than the typical two thermocouples used in the cross correlation velocimetry technique discussed in literature. The methodology is validated using experiments performed in two laboratory scale devices: a heated turbulent jet and a variable diameter natural gas burner. Experimental measurements are compared with theoretical calculations, and uncertainty in the measurement is discussed.     

Hydraulic modelling of control devices in loop equations of water distribution networks

The simulation of hydraulic behaviour of water distribution networks (WDN) needs to develop and implement a mathematical model that is able to consider a wide range of control devices of complex systems. A literature overview is primarily provided for the solution procedures of steady state simulation of nonlinear pipe network hydraulics. Typical elements of pressure regulating valves are conceptually described and differentiated into their functional characteristics to incorporate their hydraulics in the simulation model. They are explored by considering their possible topological positions and operating states. A novel efficient methodology using an unknown head-loss function is initially presented for the hydraulic simulation of network flow problems containing static and/or dynamic closed pipes. Closed pipes can be mainly obtained in the distribution networks either by turning off the isolation valves at a pipe segment or as a result of the operating state of unidirectional control devices depending on the pressure distribution in the pipe network. Thereupon, this approach is extended to integrate the control elements of pipe networks such as check valves, pressure reducing (PRV) and safety valves as well as booster/pumping stations. An iterative numerical algorithm is applied to solve the loop equations using the Newton-Raphson method for the linearised energy equation, where Hardy-Cross technique is locally used to correct flow rates of loops containing closed pipes in the iteration procedure. The developed hybrid approach demonstrated robust and very fast converging behaviour for real-world pipe network applications. Moreover, it can consider a variety of combinations of control devices in different network configurations. Several empirical head loss formulas can be additionally used in combination with the commonly known equations such as Hazen-Williams and Colebrook-White head loss formulas. The application of the algorithm will be briefly demonstrated by discussing some simulation results from example and real world large scale WDN.     

Uncertainty estimation for multiposition form error metrology

We analyze a general multiposition comparator measurement procedure that leads to partial removal of artifact error for a class of problems including roundness metrology, measurement of radial error motions of precision spindles, and figure error metrology of high-accuracy optical components. Using spindle radial error motion as an explicit example, we present a detailed analysis of a complete test with N orientations of a test ball with respect to the spindle. In particular, we show that (1) all components of the ball roundness error average to zero except those with frequencies of kN cycles/revolution, where k is a positive integer; and (2) the combined standard uncertainty of the measurement is proportional to 1/√N. We then show how a complete set of measurements for an N-position test can be synthesized from only two measurements, and we derive a general expression for the combined standard uncertainty as a function of the number of positions n (2 ≤ n ≤ N) actually measured in an N-position test. This uncertainty can serve as a useful guide to measurement design, involving trade-offs between multiple setup cost and complexity and required levels of angular harmonic resolution and combined standard measurement uncertainty.     

A neural network developed in a Foundation Fieldbus environment to calculate flow rates for compressible fluid

This paper proposes the development of an artificial neural network multilayer perceptron, implemented in a Foundation Fieldbus environment, to calculate the flow rate of natural gas by using an orifice plate in a closed pipe. The principal benefit of using neural networks lies in their low computational cost and simplicity of implementation, which allows just standard blocks to be used, making the technology independent of the Foundation Fieldbus system manufacturer. To perform the calculation, the proposed methodology relies on static pressure, temperature and differential pressure measurements, which are typically available in industrial plants. The developed methodology generates highly accurate results, and this approach can be implemented at a relatively low cost for Foundation Fieldbus system users.     

信标冗余网络

本文描述了用于EtherNet/IP的一个协议,可以在网络基础架构和终端设备网络接口上提供多重容错功能.这种协议称为信标冗余协议或者BRP.基于BRP协议的网络可称为BRP网络.BRP网络基于ISO/IEC 8802-3(以太网)和IEEE 802.1标准以及冗余基础架构.在BRP网络中,网络切换由终端设备自己决定.B...     

Network localization procedures for experimental evaluation of mobile spatial coordinate measuring system (MScMS)

Large scale metrology refers to dimensional measurement of objects or features of perhaps a ten of meters or more in size. Alternatively, large scale metrology could be said to apply to any dimensional measurement where the metrology instrument has to be brought to the object rather than vice versa. Recent approaches seem to turn their attention towards distributed metrology systems made of multiple components with small dimensions spread around the measuring area. In general, these components are able to form a wireless network of sensors that allows rapid dimensional measurements to be performed in relation to large-size objects, with typical dimensions of several decametres. The portability, flexibility, and ease of installation of wireless sensor networks (WSNs) make these systems attractive for many industries manufacturing large scale products. This paper proposes different WSN localization procedures designed for the mobile spatial coordinate measuring system, a distributed metrology system developed at the industrial metrology and quality laboratory of DISPEA—Politecnico di Torino.     

Automated dimensional inspection planning using the combination of laser scanner and tactile probe

Combining multiple sensors on CMMs (Coordinate Measuring Machines) is useful to fulfil the increasing requirements on both complexity and accuracy in dimensional metrology. Yet, the methodology to plan measurement strategies for systems combining different types of sensors is still a major challenge. Such planning is commonly done in an interactive way. This paper presents a methodology which can create inspection plans automatically for CMM inspection combining a touch trigger probe and a laser scanner. The inspection features are specified based on the extracted geometry features and the associated PMI (Product and Manufacturing Information) items from a CAD model. A knowledge based sensor selection method is applied to choose the suited sensor for each inspection feature. For touch trigger measurements, the sampling strategy considers the measurement uncertainty calculated by simulation. A geometry-guide method is developed for collision-free probing path generation. For laser scan measurements, the required view angles and positions of the laser scanner are determined iteratively, based on which the scan path is generated automatically. The proposed methodology is tested for several cases and validated by measurement experiments. The methodology provides suited planning results and can be used for automated dimensional inspection, i.e. Computer Aided Quality Control (CAQC).     

An integrated manufacturing network management framework by using mobile agent

The growth in the development of distributed manufacturing systems necessitates increases in efficient technologies in order to facilitate management of the networked resources. Systems such as manufacturing automation protocol (MAP) already exist which were specifically designed for managing networked manufacturing devices. However, MAP has been criticised for being over-complex and expensive for small–medium sized enterprises. The simple network management protocol (SNMP) was designed for managing TCP/IP networks, and we argue that it can also be used for managing networked manufacturing devices. However, SNMP, like MAP, is based upon a client/server architecture, and both have scalability issues. We also investigate the use of mobile agent (MA) technology as a means of managing a domain of manufacturing devices. An integrated network management framework based on MA technology is developed to direct the research into the investigation of aligning network management paradigm to the strategic management decision.     

An experiment in distributed manufacturing control

Local area networks are used in industrial control applications that require the digital interconnection of low-level devices such as transducers, actuators and simple controllers. It is possible to use such interconnections solely as a wiring alternative to the traditional star-connected computer controllers and to leave the control of the application with one ‘central’ computer. However, using a local area network to connect intelligent low-level devices opens up the possibility of applying a distributed control methodology to the application. This paper describes the application of a distributed control approach to a work cell previously based around a single, large programmable logic controller. Comparisons of the two approaches are made in an attempt to quantify the effect of this new approach on the metrics of the work cell.     

The estimation of measurement uncertainty of small circular features measured by coordinate measuring machines

This paper examines the measurement uncertainty of small circular features as a function of the sampling strategy; i.e., the number and distribution of measurement points. Specifically, we examine measuring a circular feature using a three-point sampling strategy in which the angular distance between the points varies from widely spaced, 120°, to closely grouped, a few degrees. Both theoretical and experimental results show that the measurement uncertainty is a strong function of the sampling strategy. The uncertainty is shown to vary by four orders of magnitude as a function of the angular distribution of the measurement points. A conceptual framework for theoretically estimating the measuring uncertainty is described, and good agreement with experiments is obtained when the measurements are consistent with the assumptions of the theoretical model. This paper is an expansion of a previous internal report1 with additional material on analog probes and probe lobing models.     

分布式电驱动车辆状态感知与控制研究综述

分布式电驱动车辆转矩响应快、全轮独立可控、制动能量可回收且可大幅度提升整车能效,对增强车辆安全性、操纵稳定性和运行节能性具有重要的意义。但须研究解决过驱动系统复杂性、非线性耦合、轮路接触非线性和不确定性等核心问题,这依赖于研究先进的状态感知和控制方法。从控制和状态感知的角度,基于功能目标对现有研究进行分类,综述分布式电驱动车辆的最新研究进展。状态感知为控制系统提供准确、可靠、快速的运动状态反馈信号,但面临车速估计难、传统检测方法带宽受限、复杂未知路面影响等挑战。控制系统首要目标是车辆安全稳定性,进而提升整车能效,并可通过多目标优化拓展其他复合功能,但面临多目标耦合干涉、异构多尺度执行系统同步协调、附着条件未知不确定、在线实时计算与全工况测试等关键挑战。充分利用分布式电驱动系统机电信号测量准确、简便、带宽高的优势,协同利用智能车体系的多源异构传感信息,是状态感知技术发展的重要思路;进一步挖掘分布式电驱动转矩响应快、全轮电制动能量回馈等优势,突破复杂、全工况、不确定条件下的多目标优化控制方法,是解决控制系统所面临挑战的重要思路。     

A study on mutative scale straightness measurement based on uncertainty analysis

Mutative Scale Measurement is often used to measure the characteristics of mechanical and electrical equipments/components in manufacturing industry. A typical case is the straightness measurement of large-scale rails. Due to the uncertainty of surface error distribution, and difference in the size and the locations of sample points, the evaluated value has a certain degree of uncertainty, which reduces the accuracy of the measurement. Since the decrease of uncertainty is at the expense of higher measurement cost, optimization of measurement cost for an acceptable uncertainty becomes a significant issue. This paper describes the composition of the uncertainty that caused by the measuring process and analyzes the uncertainty caused by sample size insufficiency. On the basis of these arguments, a model has been proposed to calculate the minimum sample size which meets the requirement of measurement uncertainty. Case studies are carried out to demonstrate the application of the derived methodology on sampling strategy.     

Uncertainty study of fiscal orifice meter used in a gas Algerian field

Uncertainty variation of a fiscal orifice measurement system used in an Algerian natural gas exportation station is studied using data from a natural gas production field known as Gas Tin Fouye Tabankort (GTFT) located in the south-east of Algeria. The expected results are uncertainty calculus over a range of temperature and pressure variation and to the customs authorities’ allocation.In fact, each quantity of measured fluid flow has certain uncertainty and then the fiscal measurement station is very important for gas exportation, which means the income. Therefore, the pursuit of flow metering device uncertainty and its influence on the measured quantities in the transmission networks is very important.For that, the uncertainty caused by flowmeter in the measurement station causing economical revenue fluctuations is studied. The work was done to justify why there is a production decrease of hydrocarbons without identifying reasons during summer. The difference between the mass flow rate quantity produced and the transmitted value was important that is why our work is done to clarify exactly from where the problem can come.The measurements setting with two operating conditions (gas temperature and pressure) show that the uncertainty is dominated by seasonal temperatures and pressures variations which induce fluctuation in gas and pipe temperatures and influence the metrological performance of the transmitters. Indeed, the metrological measurement chain performance is affected also by these two operating conditions.The present work is done according to the ONML (National Legal Metrological Office) instructions regarding differences between the measured and the seller values represented by the mass flow rate.In natural gas transmission network, the important problem in the management and control of the network is represented by the unaccounted for gas, a quantity of measuring error which is to be considered in the equation of network balancing. One of the unaccounted for gas sources are the environmental conditions and systematic measurement errors.In this work, the calculation of the combined uncertainty of the mass flow rate measured by an Orifice fiscal gas metering plant is done. From the results founded, the authors confirm that the uncertainty in the measurement system causing by the climatic conditions generates unaccounted for gas.     

Optimal inspection strategy planning for geometric tolerance verification

Two features characterize a good inspection system: it is accurate, and compared to the manufacturing cost, it is not expensive. Unfortunately, few measuring systems posses both these characteristics, i.e. low uncertainty comes with a cost. But also high uncertainty comes with a cost, because measuring systems with high uncertainty tend to generate more inspection errors, which come with a cost.     

基于信息融合技术的加工过程监测系统研究

加工过程状态的监测与控制是提高机床智能化的重要研究内容,为实现加工过程的智能化监测与控制必须以多传感器及多传感器信息融合技术为基础.提出了一种基于粗糙集理论和神经网络的多传感器智能信息融合方法,该方法将粗糙集理论作为实现多传感器数据融合的方法,同时针对粗糙集理论只能处理离散数据的问题.提出了使用自组织特征映射网络对传感器采集数据进行离散化及聚类处理的方法,针对粗糙集理论在决策融合处理方面的不足,提出了使用BP神经网络来实现决策规则的有效融合,分析了该方法的原理、关键技术及实现方法,为后期的进一步的研究和应用打下基础.