Influence Of Measurement Uncertainty Research Articles

Influence of Measurement Uncertainty in the Determination of Selected Rock Parameters-A Realistic Approach.

To determine and compare the measurement uncertainty of different geological-geotechnical testing methods, numerous test locations were selected in a hard rock quarry. Measurements were carried out along two vertical measurement lines perpendicular to the mining levels of an existing exploration. Along these lines, the rock quality basically varies due to weathering (decreasing influence with increasing distance from the original ground surface), but also due to the influence of the geological-tectonic conditions on site. The mining conditions (blasting) are identical over the considered area. The rock quality was examined as follows: as field tests, the rock compressive strength was determined by means of point load test and rebound hammer, as laboratory method the Los Angeles test (standard laboratory test for the determination of the mechanical rock quality) was used to identify the impact abrasion resistance. The statistical evaluation and comparison of the results allowed conclusions to be drawn about the contribution of the individual test methods to the measurement uncertainty whereas, in practice, a priori information can be applied complementarily. It shows that the influence on the combined measurement uncertainty u of the different methods due to the geological variability in horizontal direction reaches values between 17 and 32%, whereby the rebound hammer method shows the highest values. However, the highest influences on the measurement uncertainties are a result of the vertical direction due to weathering phenomena with percentages of 55 to 70%. For the point load test, the vertical direction shows the highest significance with an influence of approximately 70%. This leads to the conclusion that a higher weathering degree of the rock mass shows an increasing effect on the measurement uncertainty which needs to be considered using a priori information in measurements.

Influence of measurement uncertainty on machine learning results demonstrated for a smart gas sensor

Abstract. Humans spend most of their lives indoors, so indoor air quality (IAQ) plays a key role in human health. Thus, human health is seriously threatened by indoor air pollution, which leads to 3.8 ×106 deaths annually, according to the World Health Organization (WHO). With the ongoing improvement in life quality, IAQ monitoring has become an important concern for researchers. However, in machine learning (ML), measurement uncertainty, which is critical in hazardous gas detection, is usually only estimated using cross-validation and is not directly addressed, and this will be the main focus of this paper. Gas concentration can be determined by using gas sensors in temperature-cycled operation (TCO) and ML on the measured logarithmic resistance of the sensor. This contribution focuses on formaldehyde as one of the most relevant carcinogenic gases indoors and on the sum of volatile organic compounds (VOCs), i.e., acetone, ethanol, formaldehyde, and toluene, measured in the data set as an indicator for IAQ. As gas concentrations are continuous quantities, regression must be used. Thus, a previously published uncertainty-aware automated ML toolbox (UA-AMLT) for classification is extended for regression by introducing an uncertainty-aware partial least squares regression (PLSR) algorithm. The uncertainty propagation of the UA-AMLT is based on the principles described in the Guide to the Expression of Uncertainty in Measurement (GUM) and its supplements. Two different use cases are considered for investigating the influence on ML results in this contribution, namely model training with raw data and with data that are manipulated by adding artificially generated white Gaussian or uniform noise to simulate increased data uncertainty, respectively. One of the benefits of this approach is to obtain a better understanding of where the overall system should be improved. This can be achieved by either improving the trained ML model or using a sensor with higher precision. Finally, an increase in robustness against random noise by training a model with noisy data is demonstrated.

Accuracy of key performance indicators in solar-assisted heating systems due to measurement uncertainties

In this paper, the influence of measurement uncertainties on the key performance indicators fsav and FSC in solar-assisted heating systems is investigated. The impact of temperature, volumetric flow rate, and irradiance sensors with different measurement accuracies is analysed with a combination of Gaussian error propagation and Monte Carlo Analysis. To identify the sensor equipment with best cost–benefit-ratio (BCBR), different sensor combinations are investigated. If fsav and FSC are to be measured, additional sensors must be installed. The resulting costs range from 250€ for an inexpensive equipment to 330€ for recommended BCBR equipment and up to 780€ for the maximum accuracy equipment. For smaller economically dimensioned systems the use of inexpensive sensors results in large uncertainties, e.g. fˆsav=(15.2±13.7)%. The uncertainties for larger systems are significantly lower, e.g. fˆsav=(56.7±6.3)%. This is true as well if better sensors are used. Regardless of the system’s size, with the BCBR sensor equipment the resulting expanded uncertainties can be reduced by 60% (relative) compared to the results with the inexpensive sensor equipment. With maximum accuracy sensor equipment the resulting expanded uncertainties can even be reduced by 77% (relative). The results show the importance of a carefully selected sensor equipment and the influence of the system’s size. Inexpensive sensors can lead to large uncertainty ranges for the important key performance indicators fsav and FSC. Thus, these key figures effectively cannot be used for assessing the performance of a solar-assisted heating system.

Axial variation in flexural stiffness of plant stem segments: measurement methods and the influence of measurement uncertainty

BackgroundFlexural three-point bending tests are useful for characterizing the mechanical properties of plant stems. These tests can be performed with minimal sample preparation, thus allowing tests to be performed relatively quickly. The best-practice for such tests involves long spans with supports and load placed at nodes. This approach typically provides only one flexural stiffness measurement per specimen. However, by combining flexural tests with analytic equations, it is possible to solve for the mechanical characteristics of individual stem segments.ResultsA method is presented for using flexural tests to obtain estimates of flexural stiffness of individual segments. This method pairs physical test data with analytic models to obtain a system of equations. The solution of this system of equations provides values of flexural stiffness for individual stalk segments. Uncertainty in the solved values for flexural stiffness were found to be strongly dependent upon measurement errors. Row-wise scaling of the system of equations reduced the influence of measurement error. Of many possible test combinations, the most advantageous set of tests for performing these measurements were identified. Relationships between measurement uncertainty and solution uncertainty were provided for two different testing methods.ConclusionsThe methods presented in this paper can be used to measure the axial variation in flexural stiffness of plant stem segments. However, care must be taken to account for the influence of measurement error as the individual segment method amplifies measurement error. An alternative method involving aggregate flexural stiffness values does not amplify measurement error, but provides lower spatial resolution.

Impact of Measurement Uncertainty on Building Modeling and Retrofitting Decisions

Retrofitting buildings is essential for improving the existing global building stock. Innovations in wireless sensor networks have provided new means for scalable and potentially low-cost solutions for evaluating optimal retrofit measures in a building. Building models are used to explore different retrofit options and to find effective combinations of retrofit measures for a building in question. This paper departs outlining a novel grey-box modeling process for building retrofit based on measurement data. However, it is unknown if the measurement data and, as a consequence, the retrofit analysis is affected by uncertainties due to measurement accuracy and other factors. Quantifying these uncertainties during the analysis process is important in the context of making effective retrofit decisions. Consequently, this work examines the influence of measurement uncertainties on the generation of the retrofit models and the suggested retrofit measures. The results illustrate that measurement uncertainty is manageable for retrofit decisions, i.e., the measurement uncertainties rarely influence the ranking of retrofit measures. However, reduced measurement uncertainties are beneficial for adequately sizing the building retrofit interventions. It is shown that measurement uncertainty of flow meter measurements and indoor temperature measurements have the biggest impact on the heat loss coefficient estimation error, which ranges overall from 3 to 26%. Further, it is shown that some retrofit measures are more sensitive to uncertainty in the input data, such as district heating and wood pellets boilers, compared to measures that include heat pumps.

Using Alternatives to Determine the Shallowest Depth for Bathymetric Charting: Case Study

Methods for gridding multibeam echo sounder (MBES) measurements to equidistant grids are proposed as alternatives to the shallowest measured depth, which is affected by outliers. The approaches considered use a combination of mean and standard deviation of soundings and the regression coefficient from the best fitted plane. These methods along with mean and shallowest depths were applied to two surveyed areas. Two issues were found to be of importance, that is, a proper distribution of soundings and low uncertainties in the depth measurements. Improper sampling excludes using the method employing regression coefficients. For flat areas, the shallowest measured depth was found to be highly influenced by measurement uncertainties, counteracted when using the mean depth. However, the mean depth underestimates the shallowest depth for areas with slopes. When correcting the mean depth for standard deviation, the effect of slopes is accounted for while the influence of measurement uncertainties is decreased compared to shallowest measured depth. Since the uncertainties are dependent on beam angle, depth, and measurement equipment, these issues need to be accounted for in survey planning.

Noise Immunity of Pulse Wave Contour Analysis

This article is devoted to analyzing the noise immunity of pulse waveform contour analysis. Different approaches to the implementation of the pulse waveform contour analysis were considered. It was demonstrated that a classical approach for the morphological analysis of the pulse wave based on using the stiffness index and the reflection index do not provide sufficient diagnostic accuracy due to the instability of detection of the reflected wave peak. The technique of contour analysis based on spectral transformation of replicated fragments of the pulse wave is proposed. As a diagnostic index the ratio of the amplitudes of the first two harmonics of the spectrum was used. The influence of measurement uncertainty of the pulse wave amplitude on determining the accuracy of the morphological analysis of the pulse wave realized by different methods was researched.

Reply to A.V. Smagin: IV. Surface diffusion or random noise?

Анализируется эксперимент проф. А.В. Смагина, из которого он получает численное значение коэффициента поверхностной диффузии газов в почве. Нами предпринята попытка оценить погрешность этого коэффициента. Обосновывается пессимистическая точка зрения: поскольку погрешность оказалась во много раз больше самого коэффициента диффузии, то не имеет смысла говорить о поверхностной диффузии – из рассмотренного эксперимента мы ничего не можем заключить о ее интенсивности, ибо статистически значимо она не отличается от нуля.

Comments on ‘Influence of measurement uncertainties on fractional solubility of iron in mineral aerosols over the oceans’ Aeolian Research 22, 85–92

Comments on ‘Influence of measurement uncertainties on fractional solubility of iron in mineral aerosols over the oceans’ Aeolian Research 22, 85–92

Influence of measurement uncertainties on fractional solubility of iron in mineral aerosols over the oceans

The atmospheric supply of mineral dust iron (Fe) plays a crucial role in the Earth’s biogeochemical cycle and is of specific importance as a micronutrient in the marine environment. Observations show several orders of magnitude variability in the fractional solubility of Fe in mineral dust aerosols, making it hard to assess the role of mineral dust in the global ocean biogeochemical Fe cycle. In this study we compare the operational solubility of mineral dust aerosol Fe associated with the flow-through leaching protocol to the results of the global 3-D chemical transport model GEOS-Chem. According to the protocol, aerosol Fe is defined as soluble by first deionized water leaching of mineral dust through a 0.45 μm pore size membrane followed by acidification and storage of the leachate over a long period of time prior to analysis. To estimate the uncertainty in soluble Fe results introduced by the flow-through leaching protocol, we prescribe an average 50% (range of 30–70%) fractional solubility to sub-0.45 μm sized mineral dust particles that may inadvertently pass the filter and end up in the acidified (at pH ∼ 1.7) leachate for a couple of month period. In the model, the fractional solubility of Fe is either explicitly calculated using a complex mineral aerosol Fe dissolution equations, or prescribed to be 1% and 4% often used by global ocean biogeochemical Fe cycle models to reproduce the broad characteristics of the presently observed ocean dissolved iron distribution. Calculations show that the fractional solubility of Fe derived through the flow-through leaching is higher compared to the model results. The largest differences (∼40%) are predicted to occur farther away from the dust source regions, over the areas where sub-0.45 μm sized mineral dust particles contribute a larger fraction of the total mineral dust mass. This study suggests that different methods used in soluble Fe measurements and inconsistences in the operational definition of filterable Fe in marine environment and soluble Fe in atmospheric aerosols are likely to contribute to the wide range of fractional solubility of aerosol Fe reported in the literature.

Study of the Influence of Measurement Uncertainty on the Sorting of Machined Parts

The basis of effective and efficient production are the measurements. Manufacturing processes should meet the accuracy requirements to produce fit products. Processes capabilities are determined (estimated) and managed by measurements and not at least the suitability of the products are also found by measurements. The measurement technique is considered as a factor associated with costs without taking part in the creation of added value. As a logical consequence is offered to reduce the measurements in order to reduce costs, according to the possibilities, but this leads to increasing of defects in production. This expensive and sometimes fatal consequences of this mentality are not reported. Processes and products are evaluated incorrectly. The number of errors and the expenses increase.

Effect of measurement uncertainties on strain-based damage diagnostics for highway bridges

Diagnostic load rating of highway bridges using distributed strain transducers is one of the more prominent strategies applied for both periodic and continuous monitoring of highway bridges. Techniques for load rating structures using experimental measurements of neutral axis locations, girder distribution factors, and dynamic increase factors have been suggested for structural health monitoring and damage detection applications. However, practical considerations related to the influence of measurement uncertainties on the reliability of these diagnostic measures in the presence of damage have only been examined recently. This paper extends uncertainty propagation formulae previously derived for neutral axis measurements to girder distribution factors. The significance of measurement uncertainties on damage-sensitive features are then explored using experimental data from a real bridge subjected to progressive, prescribed damage. The experimental results suggest that both apparent neutral axis locations and girder distribution factors exhibit sensitivity to the damage mechanisms introduced that exceeds the measurement uncertainty. In addition, girder distribution factors are found to demonstrate the ability to locate the damage. Comparisons with finite element simulations underline the challenges associated with faithfully modeling the effects of structural damage and emphasize the need for continued full-scale validation of structural health monitoring approaches on real structures.

Relationship between measurement uncertainty and verifiability of geometric specifications: the case study of drilled hole orthogonality

In mechanical design, geometrical specifications and dimensional tolerances are commonly used to avoid final product malfunction and to allow for assembly integration. Geometric specification usage, in particular, has many manufacturing and durability implications, the feasibility of their measurement and verification, however, is often neglected and the influence of measurement uncertainty in their evaluation underestimated. Often geometrical specifications are defined without considering measurement uncertainties, or measurability at all: it is not uncommon to find approved specifications prescribing unverifiable geometry, or dimension tolerances that exceed state-of-art measurements. This article explores the case study of orthogonality between a circular hole and the plane on which it is drilled, evaluated using a Coordinate Measuring Machine. Such specification is defined, according to ISO 14253, as the angle between the plane normal and cylinder axis. Uncertainty of points coordinates obtained can, however small, play a key role in the final evaluation of orthogonality: if the specified tolerance is thigh enough it is also possible to have misalignment uncertainty higher than the tolerance itself. The authors propose the results of a mathematical and numerical model, meant to help the designer to define specification to assess the relationship between cylinder-plane misalignment measurability, CMM uncertainty and features dimensions.

Influence of Measurement Uncertainties on the Thermal Environment Assessment

ISO 7726 standard describes both the measurement techniques and the related metrological performances of instruments required for the assessment of the thermal environment. Unfortunately, the calculation of required discomfort and stress indices rarely takes into account the evaluation of single measurement uncertainties and their effect on the thermal environment assessment. To assess the uncertainty in the determination of predicted mean vote and the predicted percentage of dissatisfied indices, required by ISO 7730 for the verification of the environment conformity, typical uncertainties in the measurement of both physical (the air temperature, the mean radiant temperature, the air velocity, and the relative humidity) and subjective parameters are calculated. In order to verify the conformance of comfort indices measured by means of different measurement techniques and devices, some experimental tests in three typical environments have been carried out: (i) residential, (ii) office, and (iii) industrial. To highlight both the compatibility of measurement and the suitability, tests were carried out using three special comfort-analysis data-loggers, each provided with different sensors characterized by different instrumental uncertainties.

Influence of measurement uncertainties on the determination of the Weibull distribution

Abstract The influence of measurement uncertainties (MU) on the determination of the parameters of a distribution function has been analyzed using a Monte Carlo simulation technique on the example of the Weibull distribution, which describes the strength of brittle materials. It is shown that in the parameter range which is relevant for strength testing of brittle materials (e.g. ceramics) very high precision measurements are necessary if the Weibull modulus of the parent distribution is m ≥ 20. In that case the MU should be lower than ±2% of the measured value to obtain the same confidence level compared to the ideal case (MU = 0). Otherwise a significant underestimation of m becomes very probable. However, if m ≤ 10, even relatively large MU (up to ±10%) are tolerable. In summary, the precision of the measurements is acceptable as long as the width of the error distribution be much smaller than the width of the parent distribution.

Measurement Uncertainty in Decision-Making

In this paper, the authors examine a common issue concerning the influence of measurement uncertainty on decisions. In fact, in some practical applications, it can be necessary to put in comparison measurement data with thresholds and limits. It occurs when the conformity with fixed specifications has to be verified or if warning and alert levels have to be not exceeded. In such a circumstance, to take reliable decisions in presence of uncertainty is a concrete problem. Measurement uncertainty may reasonably be the cause of unreliable decisions. In order to manage properly the uncertainty effect, the authors have developed a decision making procedure based on a methodical approach to measurement uncertainty. In detail, a fuzzy logic algorithm estimates the probability to take a wrong decision because of the uncertainty. Such information is so used in order to optimize the decisional criteria, improving the consistency of the final computing results. Risks and costs associated to the possibility to take a mistaken decision are minimized. Consequently the algorithm singles out the most reliable decision.

Development of an optical three-dimensional laser tracker using dual modulated laser diodes and a signal detector

Laser trackers are widely used in industry for tasks such as the assembly of airplanes and automobiles, contour measurement, and robot calibration. However, laser trackers are expensive, and the corresponding solution procedure is very complex. The influence of measurement uncertainties is also significant. This study proposes a three-dimensional space position measurement system which consists of two tracking modules, a zero tracking angle return subsystem, and a target quadrant photodiode (QPD). The target QPD is placed on the object being tracked. The origin locking method is used to keep the rays on the origin of the target QPD. The position of the target QPD is determined using triangulation since the two laser rays are projected onto one QPD. Modulation and demodulation are utilized to separate the coupled positional values. The experiment results show that measurement errors in the X, Y, and Z directions are less than ±0.05% when the measured object was moved by 300, 300, and 200 mm in the X, Y, and Z axes, respectively. The theoretical measurement error estimated from the measurement model is between ±0.02% and ±0.07% within the defined measurable range. The proposed system can be applied to the measurements of machine tools and robot arms.

Measurement uncertainty in vibromonitoring systems and diagnostics reliability evaluation

This paper analyses the influence of measurement uncertainty to the decision-making model, where possible values are distributed normally and are limited by predefined limit values. While analysing evaluation of uncertainty in vibration monitoring systems, the latter due to the features and nature of the measurement process are distinguished into two main types: permanently installed systems and periodical vibration monitoring systems. The uncertainty model for these two different monitoring systems is also provided.

The influence of measurement uncertainties on the evaluation of the distribution volume ratio and binding potential in rat studies on a microPET® R4: a phantom study

In small animal positron emission tomography (PET) imaging, the injectable radiotracer dose is often limited by the tracer mass which, together with the tracer kinetics and scanner sensitivity, dictates the statistical quality of the time activity curves (TACs) used to extract biological parameters. We investigated the effect of measurement uncertainty on the determination of the distribution volume ratio (DVR) and binding potential (BP) as estimated using the tissue input Logan (DVRL, BPL) and the ratio (DVRr, BPr) methods for two tracers, with the Concorde microPET® R4 camera. Parameters' coefficients of variation (COV) were estimated from a combination of rat and phantom data. For 11C-dihydrotetrabenazine, the COV was 11% for the BPL and 13.4% for the BPr when using TACs obtained from individual regions of interest (ROIs) and segmented attenuation correction. The COVs were reduced to 7.5% (BPL) and 8.6% (BPr) when the striatal and cerebellar TACs were estimated as averages of 3 and 2 ROIs respectively. Results obtained for 11C-methylphenidate (MP) yielded approximately 30% higher COVs. With measured attenuation correction, the COVs were on average 100% higher. The presented method can be used to examine the contribution of a variety of imaging conditions to the uncertainty of biologically meaningful parameters.

Reflection ellipsometry for in‐situ determination of complex permittivity and thickness of a single‐layer material at several angles of incidence and frequencies

AbstractSeveral experimental results on common single‐layer samples have been obtained in the microwave domain using the reflection ellipsometry technique and two different data analysis procedures. They lead to estimations of complex permittivity as a function of the angle of incidence, frequency, and thickness. The influence of measurement uncertainties is discussed. © 2003 Wiley Periodicals, Inc. Microwave Opt Technol Lett 36: 243–248, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.10733