Error sources, calibration

Method Time Uncertaintya Altitudeb Sources Calibration Error Sources... 

Calibration Error Sources with Recommended Action for Error Reduction... 

In those cases where concentrations are not measured directly, the problem of calibration of the in-situ technique becomes apparent. An assurance must be made that no additional effects are registered as systematic errors. Thus, for an isothermal reaction, calorimetry as a tool for kinetic analysis, heat of mixing and/or heat of phase transfer can systematically falsify the measurement. A detailed discussion of the method and possible error sources can be found in [34]. 

What are the main error sources in PAC experiments One of them may result from the calibration procedure. As happens with any comparative technique, the conditions of the calibration and experiment must be exactly the same or, more realistically, as similar as possible. As mentioned before, the calibration constant depends on the design of the calorimeter (its geometry and the operational parameters of its instruments) and on the thermoelastic properties of the solution, as shown by equation 13.5. The design of the calorimeter will normally remain constant between experiments. Regarding the adiabatic expansion coefficient (/), in most cases the solutions used are very dilute, so the thermoelastic properties of the solution will barely be affected by the small amount of solute present in both the calibration and experiment. The relevant thermoelastic properties will thus be those of the solvent. There are, however, a number of important applications where higher concentrations of one or more solutes have to be used. This happens, for instance, in studies of substituted phenol compounds, where one solute is a photoreactive radical precursor and the other is the phenolic substrate [297]. To meet the time constraint imposed by the transducer, the phenolic... 

If an outlier is identified statistically, the error source has to be found and elim inated. Than the complete calibration has to be repeated. 

This means for improvement concerns the experimental procedures that are used to collect and analyze the calibration samples. In PAC, sample collection can involve either a highly automated sampling system, or a manual sampling process that requires manual sample extraction, preparation, and introduction. Even for an automated data collection system, errors due to fast process dynamics, analyzer sampling system dynamics, non-representative sample extraction, or sample instability can contribute large errors to the calibration data. For manual data collection, there are even more error sources to be considered, such as non-reproducibility of sample preparation and sample introduction to the analyzer. 

Many workers have previously devoted attention to the contribution of errors in measurements to the problem of building trees from distances, as summarized in the contribution by Marshall.25 By contrast, we have not been concerned with this relatively minor source of error. Instead, our concern has been with a bigger source of error, the calibration error, which reflects the uncertainty in the relationship of distance measured with an indirect method to that measured with a more direct method. This aspect has not been addressed by previous workers. To illustrate the magnitude that this problem can assume, we note that DNA hybridization led to an estimate of 3.3% sequence divergence between the mitochondrial DNAs of two flies (Drosophila yakuba and D. teissieri).26 Restriction analysis done on the whole mitochondrial genome, in contrast, led to an estimate of 0.22%.27 Sequencing of one-seventh of these fly mitochondrial DNAs produced an estimate of 0.3%,27 similar to the latter indirect estimate but in dramatic contrast to the estimate from hybridization. 

Calibration is the largest source of error in the measurements. N0a permeation rates were determined by the rate of weight loss. Neighing errors amount to + 2%. The uncertainty in the NO/Oa titration method used to check the weight loss method is about 5%. Additional calibration errors of + 2% are caused by temperature variations of the permeation devices. 

CIE Publication 53-1982 (Methods of characterizing the performance of radiometers and photometers) and CIE Publication 69-1987 (Methods of characterizing illuminance meters and luminance meters Performance, characteristics and specifications) provide detailed information on this error source and much more. CIE Division 2 TC 2-40 is currently working on an updated revision of these publications. Presently no radiometric applications have reached this level of standardization. However, both the European Thematic Network for UV Measurements (6) and the CIE TC 2-47 (Characterization and calibration methods of UV radiometers), established around 1998, (To prepare a CIE recommendation on methods of... 

The use of a commercially available software package (QUANT) is described in the analysis of copolymer films by computer assisted infrared spectroscopy. Important features of the software are illustrated by the example of analysis of vinyl acetate/vinyl chloride copolymers. Critical aspects of method development are explained and error sources are examined. Calibration is reported with a correlation coefficient of 0.9998. 

It is notable that such kinds of error sources are fairly treated using the concept of measurement uncertainty which makes no difference between random and systematic . When simulated samples with known analyte content can be prepared, the effect of the matrix is a matter of direct investigation in respect of its chemical composition as well as physical properties that influence the result and may be at different levels for analytical samples and a calibration standard. It has long since been suggested in examination of matrix effects [26, 27] that the influence of matrix factors be varied (at least) at two levels corresponding to their upper and lower limits in accordance with an appropriate experimental design. The results from such an experiment enable the main effects of the factors and also interaction effects to be estimated as coefficients in a polynomial regression model, with the variance of matrix-induced error found by statistical analysis. This variance is simply the (squared) standard uncertainty we seek for the matrix effects. 

The determination of boron is as yet not fully in control in many laboratories, which is an indication that the interest in this element has increased only recently in most environmental laboratories. This situation was reflected in the spread of the results, which nevertheless seemed to correspond to the state of the art at the moment. Some sources of errors detected were e.g. high limits of detection for INAA, memory effects in ICP-MS and calibration error. ICP-AES is a widely used technique to determine boron however, the technique must be applied with great care. Typical problems encountered in such a matrix are iron interferences at the most suited boron-line and ashing procedure causing a high and irreproducible blank. 

Sources of errors that were detected were mainly due to calibration errors, high blanks explaining high results and uncontrolled interferences (e.g. in ICPMS). 

The most common sources of systematic errors that were detected during the technical discussions were contamination problems, calibration errors or uncontrolled matrix effects. Results obtained by TXRF could not be retained for certification since this... 

Errors in DEPT editing may arise from a number of sources. The most likely is incorrect setting of the proton pulses, especially the 0 pulse used for editing, which may often be traced to poor tuning of the proton channel. Even small errors in 0 can lead to the appearance of small unexpected peaks in the DEPT-90 if 0 is too small it approaches DEPT-45 whilst too big and it approaches DEPT-135. Usually, because of their low intensity, these spurious signals are easily recognised and should cause no problems. Even with correct pulse calibrations, errors can arise when the setting for the delay period is very far from that demanded by Uch [35] and in particular CH3 resonances... 

TCs typically have a repeatability of 1°C, whereas RTDs have a repeatability of 0.1°C. Accuracy is a much more complex issue. Errors in the temperature reading can result from heat loss along the length of the thermowell, electronic error, sensor error, error from nonlinearity, calibration errors, and other sources. ... 

Instrumental Errors. Instrumental errors are caused by nonideal instrument behavior, by faulty calibrations, or by use under inappropriate conditions. Typical sources of instrumental errors include drift in electronic circuits leakage in vacuum systems temperature effects on detectors currents induced in circuits from llO- power lines decreases in voltages of batteries with use and calibration errors in meters, weights, and volumetric equipment. 

Sources of error detected in the technical discussion were mainly due to calibration errors or lack of quality control. 

The Cathode Radiant Sensitivity" is the current of the photocathode divided by the power of the incident light at a given wavelength. Measuring the Cathode Radiant Sensitivity requires a lamp, a monochromator and a reference detector, e.g. a calibrated photodiode. The setup is difficult to calibrate due to the various error sources. 

Even for a very precise IMU the azimuth error caused by the gyro drift increases to a considerable extent. Of course we have to remark that in high precision applications the inertial sensors are very carefully calibrated, and the sensor output is compensated for the main error sources. Thus in the alignment only the error caused by tum-on repeatability of the sensor biases has to be considered. 

The great number of error sources together with a lack of norms that could provide a standard trazability procedure are generating this situation. In fact, only a few recommendations [4,7] regarding test procedure and calibration of the equipment could be found in the norms. There is neither certified laboratories to calibrate the testers nor a national master which could assure the measurements trazability [2],... 

Volumetric procedures incorporate several important sources of systematic error. Chief amongst these are the drainage errors in the use of volumetric glassware, calibration errors in the glassware, and indicator errors. Perhaps the commonest error in routine volumetric analysis is to fail to allow enough time for a pipette to drain properly, or a meniscus level in a burette to stabilize. Pipette drainage errors have a systematic as well as a random effect the volume delivered is invariably less than it should be. The temperature at which an experiment is performed has two effects. Volumetric equipment is conventionally calibrated at 20°C, but the temperature in... 

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