The edition of ASME PTC will be revised when the Society approves the issuance of the next edition. There will be no Addenda issued to ASME PTC. ASME PTC Test Uncertainty [ASME] on *FREE* shipping on qualifying offers. The scope of this Code is to specify procedures for . (Revision of ASME PTC ). Test Uncertainty. Performance Test Codes. AN AMERICAN NATIONAL STANDARD. Two Park Avenue • New York, NY.
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The following procedure may be employed for propagating the nonsymmetric uncertainties in a set of measured variables to a derived result see Fig.
The result is calculated as z R p f X1, X2, X3 Some are also aware of tolerance intervals, but most nonstatisticians know very little about prediction intervals despite their practical importance. This case would occur if uncerttainty same instruments are used to measure Xnew as were used to measure Xj.
ASME PTC 试验不确定度 Test -电源技术相关资料下载-EEWORLD下载中心
These may be such things as conduction, convection, and radiation on a sensor when installed in a gas turbine. With high-speed computing capabilities, Monte Carlo methods have become popular for determining the test result uncertainty using the test input variable values and their associated uncertainties.
The table associated with the uncalibrated case is shown here first, as Table In order to obtain the uncertainyt uncertainty in the m result, UR, at a specified confidence level, the ISO Guide recommends that the uncdrtainty standard uncertainty of the result be multiplied by a cover- o age factor.
The clearest way to present the results of the steps in the uncertainty analysis is to develop a table in which the names, definitions, values, uncertainties, sensitivities, etc. For these cases, the elemental systematic standard uncertainty may be evaluated as follows: Specifically, a tolerance interval is applicable if o limits are needed that contain most of the sampled population, while a prediction interval would be used to obtain limits to contain all of a small.
This can be as,e to establishing agreement on any deviations from applicable test code requirements and can help reduce the risk that disagreements regarding the testing method will surface after conducting the test. The first test is run with the standard or baseline configuration. Whereas these influences ssme normally be considered systematic errors during repeated tests, the duplicated tests can randomize these systematic errors providing error estimates from the statistical variations in the combined data pool .
This calibration standard uncertainty is treated asem a fully correlated standard uncertainty associated with the pressure gage. This factor can be modified as appropriate for other confidence levels and small degrees of freedom as discussed in Nonmandatory Appendix B. To observe the random error associated with car-to-car variability, the experiment fx would need to be run again using a random selection of different cars within the same model see Fig.
Prediction intervals are also required by the typical customer who purchases one or a small number of units of a given product and is concerned with predicting the performance w of the particular units he has purchased in contrast to the long-run performance of the process from wwhich the sample has been selected.
When neither published information uncertaity special data is avail- atic Error. The table has been developed in accordance with the step-bystep procedure of Section 9. Temperature circulating water bath temperature measurement uncertzinty measurements were collected every minute re- evaluated asne sulting in a total of 31 uhcertainty points as presented 1 identifying all elemental sources of system- in Table International Organization for Standardization; Since all of the systematic standard uncertainties for Xj and Xnew are correlated, the systematic standard errors are all the same.
Fundamentals axme Temperature, m Pressure, and Flow Measurements. Expanded uncertainty is used to establish a confidence inter- This example is nearly identical to that presented H2O. It is identical to the median 50 percent point uncerrainty mode most common value of the distribution.
Analysis of test measurement and result uncertainty is useful because it a facilitates communication regarding measurement and test results; b fosters an understanding of potential error w sources in a measurement system and the effects of those potential error sources on test results; c guides the decision-making process for select- fx ing appropriate and cost-effective measurement sys- tems and methodologies; d reduces the risk uncertxinty making erroneous deci- www.
The former describes an error source that causes wscatter in test data.
ASME PTC 19.1-2005 试验不确定度 Test Uncertainty.pdf
Two approaches to estimating the sensitivity coefficient of a parameter are discussed in the following text. The pretest analysis see subsection is used. Note that for this example the derivatives for eq.
The calibration process random standard uncertainty is a function of the random standard uncertainties in both the master and test meters. The weighting techniques described in this section should not be employed if the uncertainty intervals do not overlap to a significant degree as this is a possible indication of unaccounted for uncertainties.
Most instru- calibration process, the systematic standard uncer- mentation, however, yields a point measurement of tainty of the test meter is replaced by that of the master meter. The large sample uncertainty expression given in eq. The Standards Committee that approved the code or standard was balanced to assure that individuals from competent and concerned interests have had an opportunity to participate.
Both of these values are equal to 4. Typical uncertainty sources in this category stem from curve fits and computational resolution. The uncertainties for each test are presented in Table The mean value for each measured parameter was calculated using eq. More precisely, over a large number of samples, the interval calculated in this manner will contain the unknown mean 95 percent of the time. The first of these numbers refers to the proportion or percentage of the population that the interval is to contain.
By definition, the adiabatic efficiency of a compressor is the ratio of the work input required to raise the pressure of a gas to a specified value in an isentropic manner to the actual work input. In these w cases, some of the systematic errors are said to be correlated and these nonindependent errors must be considered in the determination of the fx systematic standard uncertainty of the result . The details of the uncertainty 4 systematic error resulting from imperfect analysis are discussed in paras.
The random standard uncertainty of the sample mean is related to the sample standard deviation as follows: When the uncertainty intervals com- pletely overlap, as in Case 2, one can be reasonably confident that there has been a proper accounting of all major uncertainty components. As elemental sources of standard uncertainty are m not combined as arithmetic sums but are instead combined as described in subsectionderivation of the percentage contribution of an elemental o source of standard uncertainty to the combined uncertainty is computed as the ratio of the square of the combined standard uncertainty that would.