Measurement Uncertainty Analysis of the Rotary-scan Method for the Measurable Dimension of Cylindrical Workpieces

The measurement uncertainty analysis is carried out to investigate the measurable dimensions of cylindrical workpieces by the rotary-scan method in this paper.Due to the difficult alignment of the workpiece with a diameter of less than 3 mm by the rotary scan method,the measurement uncertainty of the cylindrical workpiece with a diameter of 3 mm and length of 50 mm which is measured by a roundness measuring machine,is evaluated according to GUM(Guide to the Expression of Uncertainty in Measurement)as an example.Since the uncertainty caused by the eccentricity of the measured workpiece is different with the dimension changing,the measurement uncertainty of cylindrical workpieces with other dimensions can be evaluated the same as the diameter of 3 mm but with different eccentricity.Measurement uncertainty caused by different eccentricities concerning the dimension of the measured cylindrical workpiece is set to simulate the evaluations.Compared to the target value of the measurement uncertainty of 0.1μm,the measurable dimensions of the cylindrical workpiece can be obtained.Experiments and analysis are presented to quantitatively evaluate the reliability of the rotary-scan method for the roundness measurement of cylindrical workpieces.

Measurement Uncertainty Evaluation of Conicity Error Inspected on CMM

The cone is widely used in mechanical design for rotation, centering and fixing. Whether the conicity error can be measured and evaluated accurately will directly influence its assembly accuracy and working performance. According to the new generation geometrical product specification（GPS）, the error and its measurement uncertainty should be evaluated together. The mathematical model of the minimum zone conicity error is established and an improved immune evolutionary algorithm（IlEA） is proposed to search for the conicity error. In the IIEA, initial antibodies are firstly generated by using quasi-random sequences and two kinds of affinities are calculated. Then, each antibody clone is generated and they are self-adaptively mutated so as to maintain diversity. Similar antibody is suppressed and new random antibody is generated. Because the mathematical model of conicity error is strongly nonlinear and the input quantities are not independent, it is difficult to use Guide to the expression of uncertainty in the measurement（GUM） method to evaluate measurement uncertainty. Adaptive Monte Carlo method（AMCM） is proposed to estimate measurement uncertainty in which the number of Monte Carlo trials is selected adaptively and the quality of the numerical results is directly controlled. The cone parts was machined on lathe CK6140 and measured on Miracle NC 454 Coordinate Measuring Machine（CMM）. The experiment results confirm that the proposed method not only can search for the approximate solution of the minimum zone conicity error（MZCE） rapidly and precisely, but also can evaluate measurement uncertainty and give control variables with an expected numerical tolerance. The conicity errors computed by the proposed method are 20%-40% less than those computed by NC454 CMM software and the evaluation accuracy improves significantly.

Measurement uncertainty in pharmaceutical analysis and its application

The measurement uncertainty provides complete information about an analytical result. This is very important because several decisions of compliance or non-compliance are based on analytical results in pharmaceutical industries. The aim of this work was to evaluate and discuss the estimation of uncertainty in pharmaceutical analysis. The uncertainty is a useful tool in the assessment of compliance or non-compliance of in-process and final pharmaceutical products as well as in the assessment of pharmaceutical equivalence and stability study of drug products.

Adaptive cubature Kalman filter based on variational Bayesian inference under measurement uncertainty

A novel variational Bayesian inference based on adaptive cubature Kalman filter(VBACKF)algorithm is proposed for the problem of state estimation in a target tracking system with time-varying measurement noise and random measurement losses.Firstly,the Inverse-Wishart(IW)distribution is chosen to model the covariance matrix of time-varying measurement noise in the cubature Kalman filter framework.Secondly,the Bernoulli random variable is introduced as the judgement factor of the measurement losses,and the Beta distribution is selected as the conjugate prior distribution of measurement loss probability to ensure that the posterior distribution and prior distribution have the same function form.Finally,the joint posterior probability density function of the estimated variables is approximately decoupled by the variational Bayesian inference,and the fixed-point iteration approach is used to update the estimated variables.The simulation results show that the proposed VBACKF algorithm considers the comprehensive effects of system nonlinearity,time-varying measurement noise and unknown measurement loss probability,moreover,effectively improves the accuracy of target state estimation in complex scene.

Bernoulli particle flter with observer altitude for maritime radiation source tracking in the presence of measurement uncertainty

For maritime radiation source target tracking in particular electronic counter measures（ECM）environment,there exists two main problems which can deteriorate the tracking performance of traditional approaches.The frst problem is the poor observability of the radiation source.The second one is the measurement uncertainty which includes the uncertainty of the target appearing/disappearing and the detection uncertainty（false and missed detections）.A novel approach is proposed in this paper for tracking maritime radiation source in the presence of measurement uncertainty.To solve the poor observability of maritime radiation source target,using the radiation source motion restriction,the observer altitude information is incorporated into the bearings-only tracking（BOT）method to obtain the unique target localization.Then the two uncertainties in the ECM environment are modeled by the random fnite set（RFS）theory and the Bernoulli fltering method with the observer altitude is adopted to solve the tracking problem of maritime radiation source in such context.Simulation experiments verify the validity of the proposed approach for tracking maritime radiation source,and also demonstrate the superiority of the method compared with the traditional integrated probabilistic data association（IPDA）method.The tracking performance under different conditions,particularly those involving different duration of radiation source opening and switching-off,indicates that the method to solve our problem is robust and effective.

A Possibilistic Approach for Uncertainty Representation and Propagation in Similarity-Based Prognostic Health Management Solutions

In this paper, a data-driven prognostic model capable to deal with different sources of uncertainty is proposed. The main novelty factor is the application of a mathematical framework, namely a Random Fuzzy Variable (RFV) approach, for the representation and propagation of the different uncertainty sources affecting Prognostic Health Management (PHM) applications: measurement, future and model uncertainty. In this way, it is possible to deal not only with measurement noise and model parameters uncertainty due to the stochastic nature of the degradation process, but also with systematic effects, such as systematic errors in the measurement process, incomplete knowledge of the degradation process, subjective belief about model parameters. Furthermore, the low analytical complexity of the employed prognostic model allows to easily propagate the measurement and parameters uncertainty into the RUL forecast, with no need of extensive Monte Carlo loops, so that low requirements in terms of computation power are needed. The model has been applied to two real application cases, showing high accuracy output, resulting in a potentially effective tool for predictive maintenance in different industrial sectors.

Evaluation of Uncertainty in the Determination of Ozone Concentration in the Air by Sodium Indigo Disulfonate Spectrophotometry

The uncertainty of the determination of ozone concentration in the air at a workplace by sodium indigo disulfonate spectrophotometry was evaluated.The results show that the expanded uncertainty of ozone concentration U was 0.016 mg/m^(3),and the main factor affecting the measurement uncertainty of ozone concentration was the uncertainty introduced during sample collection.

Rotation Measurement Using Speckle Photography with LiNbO3 Crystal: Theoretical and Experimental Analysis

Photorefractive crystals present varied features charming presence, such as high resolution, and normal handling. Depending on the portability of erasing images, photorefractive crystals are convenient for read-write implementations and hence find potential use in speckle photography, speckle interferometry, image processing and holography. A two-beam coupling arrangement using a LiNbO3 crystal as a recording medium for real-time rotation measurement using the coherent and low-power laser source is presented in this paper. A speckle photography technique is advanced for the measurement of a small rotation of a transmitted glass slide sample. New theoretical analysis is formulated for a general case of a slide rotation. Experimental studies are carried out to verify the outcome of the theoretical predictions and accuracy of measurement. Uncertainty of rotation measurement is studied and quantified. The proposed technique is a simple, attractive and alternative method for fringe analysis. The method promises a high degree of accuracy and increased range for rotation measurement in real-time.

Determination of Heavy Metals in Tobacco by ICP-MS and Analysis of Uncertainty

The research aims to set up the determination method of heavy metals in tobacco by ICP-MS and analyze its uncertainty. Microwave digest technique is used for decomposition of the tobacco samples. Bi,Sc,Ge and In are employed as internal standards to eliminate the interference of the matrix. A method is developed for simultaneous determination of Cr,Cu,As,Cd,Hg and Pb in tobacco from Yunnan Province by ICP-MS,and the measurement uncertainty is evaluated by metrological method. The test results indicate that in the content range of0- 1. 0 g / ml,the linearly dependent coefficient of six elements is 1. 0000,and the RSD achieves 1. 5%- 11%( n = 8). The elemental content in tobacco is as follows: Cr( 2. 92,0. 24) mg / kg,Cu( 3. 64,0. 24) mg / kg,As( 0. 467,0. 025) mg / kg,Cd( 3. 12,0. 15) mg / kg,Hg( 0. 035,0. 006) mg/kg,Pb( 4. 62,0. 36) mg/kg. The uncertainty of sample size,the constant volume of the sample solution can be neglected. It is concluded that the method is accurate,simple,sensitive and rapid.

Modified robust finite-horizon filter for discrete-time systems with parameter uncertainties and missing measurements

A robust finite-horizon Kalman filter is designed for linear discrete-time systems subject to norm-bounded uncertainties in the modeling parameters and missing measurements.The missing measurements were described by a binary switching sequence satisfying a conditional probability distribution,the commonest cases in engineering,such that the expectation of the measurements could be utilized during the iteration process.To consider the uncertainties in the system model,an upperbound for the estimation error covariance was obtained since its real value was unaccessible.Our filter scheme is on the basis of minimizing the obtained upper bound where we refer to the deduction of a classic Kalman filter thus calculation of the derivatives are avoided.Simulations are presented to illustrate the effectiveness of the proposed approach.

Adaptive Fault Estimation for Dynamics of High Speed Train Based on Robust UKF Algorithm

This paper proposes an adaptive unscented Kalman filter algorithm(ARUKF)to implement fault estimation for the dynamics of high⁃speed train(HST)with measurement uncertainty and time⁃varying noise with unknown statistics.Firstly,regarding the actuator and sensor fault as the auxiliary variables of the dynamics of HST,an augmented system is established,and the fault estimation problem for dynamics of HST is formulated as the state estimation of the augmented system.Then,considering the measurement uncertainties,a robust lower bound is proposed to modify the update of the UKF to decrease the influence of measurement uncertainty on the filtering accuracy.Further,considering the unknown time⁃varying noise of the dynamics of HST,an adaptive UKF algorithm based on moving window is proposed to estimate the time⁃varying noise so that accurate concurrent actuator and sensor fault estimations of dynamics of HST is implemented.Finally,a five-car model of HST is given to show the effectiveness of this method.

Optimization of the cavity beam-position monitor system for the Shanghai soft X-ray free-electron laser user facility

To achieve high-efficiency operation of the highgain free-electron laser(FEL),the electron beams and radiated photon beams need to be overlapped precisely and pass through the entire undulator section.Therefore,a high-resolution beam-position monitor(BPM)is required.A cavity BPM(CBPM)with a resonant cavity structure was developed and used in the Shanghai Soft X-ray FEL(SXFEL)test facility and can achieve a position resolution of<1μm.The construction and operation of the SXFEL user facility also bring about higher requirements for beamposition measurement.In this case,the factors that affect the performance of the CBPM system were further analyzed.These included the amplitude and phase stability of the local oscillator,stability of the trigger signal,performance of the radio frequency front-end,signal processing electronics,and signal processing algorithms.Based on the upgrade and optimization of the system,a beam test platform was built at the end of the linear acceleration section of the SXFEL,and the experimental results show that the position resolution of the system can reach 177 nm at a bunch charge of 500 pC,and the dynamic range is controlled within±300μm,and the relative measurement uncertainty of the bunch charge can reach 0.021%,which are significant improvements compared to the attributes of the previous system.

Establishment of a Real-time Fluorescent Quantitative PCR Assay for Detection of Genetically Modified Maize Line MON88017

In order to improve the standardized technical systems of quantitative analyses for genetically modified organisms （GMOs） and products, ensure bio-safety and reduce ecological risk in China, a real-time fluorescent quantitative PCR assay was established for detection of genetically modified maize line MON88017. The established method was evaluated based on the specificity, sensitivity, accuracy and measurement uncertainty. The results showed that the established method had strong specificity in detection of genetically modified maize line MON88017. 1.50% MON88017 sample was detected with 29 replica- tions. The average measured value （ 1. 541% ） was close to the actual value （ 1.50% ） and the relative deviation was 2.70%. The variation coefficient of the measured value was 0.110 g ; the recovery was 100.00% and the measurement uncertainty was 0. 096. The limit of detection for genetically modified maize line MON88017 with the established method was 5 copies at the 97.5% confidence level. Thus, the real-time fluorescent quantitative PCR assay established in this study exhibited high specificity, accuracy and sensitivity, which could provide technical support for the safety supervision of genetically modified organ- isms and products in China.

Processing and Unification of Environmental Noise Data from Road Traffic with Spatial Dimension Collected through Mobile Phones

Noise measurement using mobile phones is now developed very well. While there are some good applications for the measurement of noise from road traffic, thus on processing of measured data is only paid a very little attention. The data, however, are burdened by specific errors and for further work with them it is necessary to adjust and determine their uncertainty. One of the biggest problems is inaccuracy in position versus the noise source and the shortest length of measurement that can be regarded as representative. Imprecision in terms of location can be determined by calculating the variance of possible distance from the noise source, which for measurement of traffic noise requires a map-matching data points both transverse to the street (sidewalk) network and in the longwise direction. During typical urban measurements, this error can even reach 7 - 10 dB. Three basic types of algorithms for the calculation of uncertainty and positional correction based on the type of input and output data (raster, vector, vector-oriented) were tested. Uncertainty in the variability of the measurement data is necessary to determine from the number of passing vehicles per time unit. The presented solutions are implemented in the Mobile Noise system.

Comparative Study of Zamzam, Bottled Drinking and Distilled Waters by a Novel Computer Simulation Speckle Photography Method Using Fourier Transform

The refractive index of a liquid medium is an important optical parameter since it exhibits the optical properties of the liquid. Its values are often required to interpret various types of spectroscopic data. The intensity distribution and contrast of image speckle patterns obtained for Zamzam, bottled drinking and distilled waters are investigated on a computer as a function of six discrete wavelengths across the visible spectrum. The present novel computer simulation speckle photography using Fourier transform study and the new theoretical background have been confirmed with previous experimental results. Uncertainty of refractive index measurements was studied on a wide range of discrete wavelengths using the computer simulation and the new theoretical formulae.

Research on Consistency Judgement of Indication Error for Calibration Result of Humidity Sensor in Meteorology

In order to solve the lack of relevant evaluation research on the accuracy of HMP155A humidity sensor calibration results in the past, this paper designs the corresponding experimental scheme, and obtains the corresponding calibration results according to the experimental scheme;Then the measurement uncertainty of the indication error in the calibration results is evaluated by GUM, and the corresponding extended uncertainty U95 is obtained. Finally, according to the requirements of JJF1094-2016 characteristic evaluation of measuring instruments, combined with the calibration results and the actual situation of U95, the conformity of the indication error of calibration is determined. The result is that each calibration point of the sensor meets the requirements of conformity determination and is within the qualified range. This research effectively makes up for the blank of the previous research on the conformity determination of the indication error of the calibration results and has strong theoretical and practical significance.

Data processing of small samples based on grey distance information approach

Data processing of small samples is an important and valuable research problem in the electronic equipment test. Because it is difficult and complex to determine the probability distribution of small samples, it is difficult to use the traditional probability theory to process the samples and assess the degree of uncertainty. Using the grey relational theory and the norm theory, the grey distance information approach, which is based on the grey distance information quantity of a sample and the average grey distance information quantity of the samples, is proposed in this article. The definitions of the grey distance information quantity of a sample and the average grey distance information quantity of the samples, with their characteristics and algorithms, are introduced. The correlative problems, including the algorithm of estimated value, the standard deviation, and the acceptance and rejection criteria of the samples and estimated results, are also proposed. Moreover, the information whitening ratio is introduced to select the weight algorithm and to compare the different samples. Several examples are given to demonstrate the application of the proposed approach. The examples show that the proposed approach, which has no demand for the probability distribution of small samples, is feasible and effective.

Research on uncertainty in measurement assisted alignment in aircraft assembly

Operations in assembling and joining large size aircraft components are changed to novel digital and flexible ways by digital measurement assisted alignment.Positions and orientations（P＆O）of aligned components are critical characters which assure geometrical positions and relationships of those components.Therefore,evaluating the P＆O of a component is considered necessary and critical for ensuring accuracy in aircraft assembly.Uncertainty of position and orientation（U-P＆O）,as a part of the evaluating result of P＆O,needs to be given for ensuring the integrity and credibility of the result;furthermore,U-P＆O is necessary for error tracing and quality evaluating of measurement assisted aircraft assembly.However,current research mainly focuses on the process integration of measurement with assembly,and usually ignores the uncertainty of measured result and its influence on quality evaluation.This paper focuses on the expression,analysis,and application of U-P＆O in measurement assisted alignment.The geometrical and algebraical connotations of U-P＆O are presented.Then,an analytical algorithm for evaluating the multi-dimensional U-P＆O is given,and the effect factors and characteristics of U-P＆O are discussed.Finally,U-P＆O is used to evaluate alignment in aircraft assembly for quality evaluating and improving.Cases are introduced with the methodology.

A New Approach to the Theory of Turbulence

On the basis of the fact that physical world possesses hierarchical structure and the concepts of nonstandard mathematics, a new description of turbulence was presented. Fundamental equations of turbulent flows were also given. It is natural in this nonstandard picture of turbulence that the closure methods are obtained and seem to be precise.

Possibilistic entropy-based measure of importance in fault tree analysis

With respect to the subjective factors and nonlinear characteristics inherent in the important identification of fault tree analysis （FTA）, a new important measure of FTA is proposed based on possibilistic information entropy. After investigating possibilistic information semantics, measure-theoretic terms, and entropy-like models, a two-dimensional framework has been constructed by combining both the set theory and the measure theory. By adopting the possibilistic assumption in place of the probabilistic one, an axiomatic index of importance is defined in the possibility space and then the modelling principles are presented. An example of the fault tree is thus provided, along with the concordance analysis and other discussions. The more conservative numerical results of importance rankings, which involve the more choices can be viewed as “soft” fault identification under a certain expected value. In the end, extension to evidence space and further research perspectives are discussed.