ANSI IEEE C63 23-2012 American National Standard Guide for Electromagnetic Compatibility-Computations and Treatment of Measurement Uncertainty《电磁兼容性标准指南 测量不确定性的.pdf

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1、 American National Standard Guide for Electromagnetic CompatibilityComputations and Treatment of Measurement Uncertainty Sponsored by the Accredited by the American National Standards Institute IEEE 3 Park Avenue New York, NY 10016-5997 USA 13 March 2013 Sponsored by the Accredited Standards Committ

2、ee C63 Electromagnetic Compatibility ANSI C63.23-2012C63American National Standard Guide for Electromagnetic CompatibilityComputations and Treatment of Measurement Uncertainty Accredited Standards Committee C63 Electromagnetic Compatibility accredited by the American National Standards Institute Sec

3、retariat Institute of Electrical and Electronics Engineers, Inc. Approved 3 December 2012 American National Standards Institute Abstract: Methods for estimating measurement uncertainty of emissions measurement results are provided, for use in conjunction with the basic methods of ANSI C63.4. Include

4、d in this document are both Type A and Type B uncertainty evaluation methods. Keywords: ANSI C63.23, electromagnetic compatibility (EMC), emissions, immunity, measurement uncertainty, metrology, Type A evaluation, Type B evaluation The Institute of Electrical and Electronics Engineers, Inc. 3 Park A

5、venue, New York, NY 10016-5997, USA Copyright 2013 by The Institute of Electrical and Electronics Engineers, Inc. All rights reserved. Published 13 March 2013. Printed in the United States of America. IEEE is a registered trademark in the U.S. Patent (978) 750-8400. Permission to photocopy portions

6、of any individual standard for educational classroom use can also be obtained through the Copyright Clearance Center. Errata Users are encouraged to check the IEEE Errata URL (http:/standards.ieee.org/findstds/errata/index.html), and the one for ASC C63at http:/www.c63.org/explanations_interpretatio

7、ns_request.htm, for errata periodically. Interpretations Current interpretations can be accessed at the following URLs: http:/www.c63.org/explanations_ interpretations_request.htm. For more information about the committee that produced and maintains this standard, visit the ANSI Accredited Standards

8、 Committee C63web site at http:/www.c63.org. iv Copyright 2013 IEEE. All rights reserved. Notice to users Laws and regulations Users of these documents should consult all applicable laws and regulations. Compliance with the provisions of this guide does not imply compliance to any applicable regulat

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15、o check this URL for errata periodically. v Copyright 2013 IEEE. All rights reserved. Patents Attention is called to the possibility that implementation of this guide may require use of subject matter covered by patent rights. By publication of this guide, no position is taken by the IEEE with respe

16、ct to the existence or validity of any patent rights in connection therewith. If a patent holder or patent applicant has filed a statement of assurance via an Accepted Letter of Assurance, then the statement is listed on the IEEE-SA Website http:/standards.ieee.org/about/sasb/patcom/patents.html. Le

17、tters of Assurance may indicate whether the Submitter is willing or unwilling to grant licenses under patent rights without compensation or under reasonable rates, with reasonable terms and conditions that are demonstrably free of any unfair discrimination to applicants desiring to obtain such licen

18、ses. Essential Patent Claims may exist for which a Letter of Assurance has not been received. The IEEE is not responsible for identifying Essential Patent Claims for which a license may be required, for conducting inquiries into the legal validity or scope of Patents Claims, or determining whether a

19、ny licensing terms or conditions provided in connection with submission of a Letter of Assurance, if any, or in any licensing agreements are reasonable or non-discriminatory. Users of this guide are expressly advised that determination of the validity of any patent rights, and the risk of infringeme

20、nt of such rights, is entirely their own responsibility. Further information may be obtained from the IEEE Standards Association. vi Copyright 2013 IEEE. All rights reserved. Participants At the time this guide was published, Accredited Standards Committee C63Electromagnetic Compatibility had the fo

21、llowing membership: Daniel Hoolihan, Chair Jerry Ramie, Secretary Organization Represented Name of Representative AlcatelLucent Technologies . Dheena Moongilan Alliance for Telecommunications Industry Solutions (ATIS) .Mel Frerking James Turner (Alt.) American Council of Independent Laboratories (AC

22、IL) Harry Hodes . John Repella (Alt.) American Radio Relay League (ARRL) Edward F. Hare . Kermit Carlson (Alt.) Apple, Inc. . Fraidun Akhi Indrandil Sen (Alt.) AT uncertainty. NOTE 1 Measurement uncertainty includes components arising from systematic effects, such as components associated with corre

23、ctions and the assigned quantity values of measurement standards, as well as the definitional uncertainty. Sometimes estimated systematic effects are not corrected for, but instead, associated measurement uncertainty components are incorporated. NOTE 2 The parameter may be, for example, a standard d

24、eviation called standard measurement uncertainty (or a specified multiple of it), or the half-width of an interval, having a stated coverage probability. NOTE 3 Measurement uncertainty comprises, in general, many components. Some of these may be evaluated by Type A evaluation of measurement uncertai

25、nty from the statistical distribution of the quantity values from series of measurements and can be characterized by standard deviations. The other components, which may be evaluated by Type B evaluation of measurement uncertainty, can also be characterized by standard deviations, evaluated from pro

26、bability density functions based on experience or other information. NOTE 4 In general, for a given set of information, it is understood that the measurement uncertainty is associated with a stated quantity value attributed to the measurand. A modification of this value results in a modification of

27、the associated uncertainty (for example, different measurement uncertainty values for a radiated emissions measurement result may apply in different frequency ranges). ANSI C63.23-2012 American National Standard Guide for Electromagnetic CompatibilityComputations and Treatment of Measurement Uncerta

28、inty 5 Copyright 2013 IEEE. All rights reserved. NOTE 5 This definition of measurement uncertainty (i.e., as repeated from 2.26 of ISO/IEC Guide 99:2007 B17), and for situations where uncertainty components arising from sampling are not considered, corresponds to the term and definition for standard

29、s compliance uncertainty given in 3.1.16 of CISPR 16-4-1:2009 B7. 4. Basic concepts 4.1 Introduction to measurement uncertainty Measurement uncertainty is the best estimated quantity by which a measured value differs from the true value of a parameter under evaluation. Correction factors (or biases;

30、 see the definition in A.1.4) are typically used to improve correlation between measurement devices and systems and the reference quantity to which they have been calibrated. Additionally, a correction factor is always accompanied by a measurement uncertainty. The need for such factors is an indicat

31、ion that the true value cannot be directly and completely obtained from the instrumentation and with the method of measurement used. Correction factors determined during equipment calibration processes determine the bias to be applied to the measurement result, and they are subject to measurement un

32、certainty. Determining the operational characteristics of the EUT with respect to electromagnetic compatibility compliance requires both emission and immunity measurements. This guide, however, only focuses on emission measurement, which is covered in, for example, ANSI C63.4. The measurements or ev

33、aluations involve the use of various instrumentation and techniques, requiring operator interaction and decisions. The measurement (or evaluation) process produces both random and systematic effects that influence the ultimate outcome of the measurement. Examples of systematic effects are bias of th

34、e measurement result by cable loss, parallax when reading a DArsonval meter, or habits and preferences of the operator. An example of a random effect is the influence of noise contribution to the measured amplitude if the amplitude of the measurand is close to the system noise floor. Additional pape

35、rs on the treatment of uncertainty components (influence quantities) are listed in an informative bibliography (i.e., see Annex B). An evaluation of each effect included in a measurement enables the identification of influence factors (i.e., elements that contribute to the uncertainty of the measure

36、ment), and a thorough description of each effect can assist in assignment of an appropriate value and weighting factor indicating how the overall measurement uncertainty budget may be affected. Each element of the measurement process involves an uncertainty of measurement that can be assigned a valu

37、e and described by the owner of the process. The combinations of the elements of uncertainty form the basis of an uncertainty budget for a particular measurement process. 4.2 Concepts of uncertainty 4.2.1 General Measurement uncertainty is a parameter associated with the result of a measurement that

38、 characterizes the dispersion of the values that could reasonably be attributed to the true value of the measurand. It shows the spread of values above and below the measurement result within which the true value of the measurand may be expected to lie. It can be considered to be a measure of the po

39、ssible error in the value of the measurand provided by the result of a measurement; however, the true value of a measurand can never be known. Measurement uncertainty should not be confused with correction or correlation factors. Correction and correlation factors are quantities added to measurement

40、 values to create agreement between established standard values and measurement device readings (these can also be described as biases: see A.1.4). ANSI C63.23-2012 American National Standard Guide for Electromagnetic CompatibilityComputations and Treatment of Measurement Uncertainty 6 Copyright 201

41、3 IEEE. All rights reserved. Two types of evaluations are defined to determine the values for an uncertainty budget: Type A and Type B. The type of evaluation used depends on what input and reference data is available. Other electromagnetic compatibility (EMC) measurement uncertainty documents, such

42、 as CISPR 16-4-2 (an international standard) and UKAS LAB 34:2002 B21 (a UKAS guideline document), describe primarily the Type B analyses and may use Type A methods to obtain only a few contributors, whereas Clause 5 of this guide describes how to apply either method. 4.2.2 Type A evaluation Type A

43、evaluations of uncertainty are those obtained by using statistical methods where multiple observations of the same event are recorded. These observed values are used to calculate the standard deviation of the results. The standard deviation is then used to obtain the contribution of the process unde

44、r observation to the uncertainty budget. 4.2.3 Type B evaluation Type B evaluations of uncertainty are those by any method other than a statistical evaluation. Knowledge of previous performance of instruments, specifications, instrumentation reference data, and uncertainty data provided with calibra

45、tions are examples of this evaluation type. 4.2.4 Type A or Type B evaluation Either a Type A or a Type B analysis shall be carried out for each contributor to the uncertainty budget. A Type A analysis has the advantage of providing a more representative evaluation because it is based on the actual

46、test setup/equipment used during measurement and, as such, generally results in a smaller contributor value than a Type B analysis. However, a Type A analysis is more demanding in terms of time and resources because it usually involves testing or analyzing extensive amounts of data. A Type A evaluat

47、ion of a contributor is determined by following the guidance for that particular contributor (see 5.6) and finding the standard deviation for the data collected. For example, antenna factor accuracy (also called antenna factor calibration) can be determined by taking the calibration value at each fr

48、equency over the past five calibrations and determining the worst-case standard deviation over the antennas usable frequency range. This could result in a smaller contributor than the Type B contributor. If the Type B contributor for antenna factor accuracy was 0.6 dB, and the Type A analysis of the

49、 data yielded a contributor of 0.2 dB, then it would be advantageous to use the smaller contributor. 4.2.5 Measurement uncertainty budget calculation Annex A includes a detailed presentation of measurement uncertainty concepts and methods of calculation of contributors contribution to the measurement uncertainty budget based on their known or estimated probability distribution. Table 1 summarizes the formulas to be used for each type of probability distribution and provides cross-references to corresponding subclauses from Annex A. ANSI C63