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    BS ISO 13292-2006 Copper lead zinc and nickel concentrates - Experimental methods for checking the bias of sampling《铜、铅、锌和镍精矿 取样偏差检验用实验方法 n n n n n》.pdf

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    BS ISO 13292-2006 Copper lead zinc and nickel concentrates - Experimental methods for checking the bias of sampling《铜、铅、锌和镍精矿 取样偏差检验用实验方法 n n n n n》.pdf

    1、BRITISH STANDARDBS ISO 13292:2006Copper, lead, zinc and nickel concentrates Experimental methods for checking the bias of samplingICS 73.060.99g49g50g3g38g50g51g60g44g49g42g3g58g44g55g43g50g56g55g3g37g54g44g3g51g40g53g48g44g54g54g44g50g49g3g40g59g38g40g51g55g3g36g54g3g51g40g53g48g44g55g55g40g39g3g37

    2、g60g3g38g50g51g60g53g44g42g43g55g3g47g36g58BS ISO 13292:2006This British Standard was published under the authority of the Standards Policy and Strategy Committee on 30 April 2008 BSI 2008ISBN 978 0 580 55515 2National forewordThis British Standard is the UK implementation of ISO 13292:2006.The UK p

    3、articipation in its preparation was entrusted to Technical Committee NFE/36, Copper, lead and zinc ores and concentrates.A list of organizations represented on this committee can be obtained on request to its secretary.This publication does not purport to include all the necessary provisions of a co

    4、ntract. Users are responsible for its correct application.Compliance with a British Standard cannot confer immunity from legal obligations.Amendments/corrigenda issued since publicationDate CommentsReference numberISO 13292:2006(E)INTERNATIONAL STANDARD ISO13292Second edition2006-03-15Copper, lead,

    5、zinc and nickel concentrates Experimental methods for checking the bias of sampling Concentrs de cuivre, de plomb, de zinc et de nickel Mthodes exprimentales de contrle de lerreur systmatique dchantillonnage BS ISO 13292:2006ii iiiSommaire Page Foreword iv 1 Scope . 1 2 Normative references . 1 3 Ge

    6、neral requirements and recommendations . 1 4 Sampling and sample processing methods 2 4.1 Sampling 2 4.1.1 General. 2 4.1.2 Checking bias in mechanical sampling 3 4.1.3 Checking difference between sampling at different locations 3 4.2 Sample processing and analysis 3 5 Analysis of experimental data

    7、. 3 5.1 Statistical basis. 3 5.2 Determination of the mean difference and its standard deviation 4 5.3 Determination of the required number of data sets 4 5.4 Statistical test 6 Annex A (informative) Numerical examples of determining the bias of sampling 7 Bibliography . 11 BS ISO 13292:2006iv Forew

    8、ord ISO (the International Organization for Standardization) is a worldwide federation of national standards bodies (ISO member bodies). The work of preparing International Standards is normally carried out through ISO technical committees. Each member body interested in a subject for which a techni

    9、cal committee has been established has the right to be represented on that committee. International organizations, governmental and non-governmental, in liaison with ISO, also take part in the work. ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of e

    10、lectrotechnical standardization. International Standards are drafted in accordance with the rules given in the ISO/IEC Directives, Part 2. The main task of technical committees is to prepare International Standards. Draft International Standards adopted by the technical committees are circulated to

    11、the member bodies for voting. Publication as an International Standard requires approval by at least 75 % of the member bodies casting a vote. Attention is drawn to the possibility that some of the elements of this document may be the subject of patent rights. ISO shall not be held responsible for i

    12、dentifying any or all such patent rights. ISO 13292 was prepared by Technical Committee ISO/TC 183, Copper, lead, zinc and nickel ores and concentrates. This second edition cancels and replaces the first edition (ISO 13292:1997), which has been technically revised. BS ISO 13292:20061Copper, lead, zi

    13、nc and nickel concentrates Experimental methods for checking the bias of sampling WARNING This International Standard may involve hazardous materials, operations and equipment. It is the responsibility of the user of this International Standard to establish appropriate health and safety practices an

    14、d determine the applicability of regulatory limitations prior to use. 1 Scope This International Standard specifies methods for checking whether there is any bias in the sampling of copper, lead, zinc and nickel concentrates, where the sampling is carried out in accordance with the methods specified

    15、 in ISO 12743. These methods can also be used for comparing alternative sampling regimes, checking whether there is any bias in sample processing and for checking possible significant differences in sampling at different places, e.g. at loading and discharge points, or the analysis of exchange sampl

    16、es. Numerical examples are given in Annex A. 2 Normative references The following referenced documents are indispensable for the application of this document. For dated references, only the edition cited applies. For undated references, the latest edition of the referenced document (including any am

    17、endments) applies. ISO 12743, Copper, lead, zinc and nickel concentrates Sampling procedures for determination of metal and moisture content 3 General requirements and recommendations The procedures specified in this International Standard are applicable to paired data only. The results obtained fro

    18、m the method to be checked for bias (referred to as Method B) are compared with the results for a reference method (referred to as Method A), which is considered to produce unbiased results from technical and empirical viewpoints. If there is no significant difference between the results obtained us

    19、ing Method B and Method A, then Method B may be adopted as a routine method. While the procedures specified in Clause 5 are principally designed for checking bias against a reference method, separate measurements of quality characteristics, e.g. using different sampling regimes, sampling at loading

    20、(Method A) and discharge (Method B), or analyses of exchange samples, may also be compared to check whether there is a statistically significant difference between the results. Mechanical sampling systems, or manual sampling methods, are tested for bias by comparing the test results for final system

    21、 or manually collected samples (Method B) with the test results for reference increments collected from a stopped conveyor belt (Method A). Analytical methods or test procedures are checked against certified reference materials. The standard method of taking reference increments from a stopped conve

    22、yor belt presents operational difficulties, even if the handling system is capable of being restarted with a fully loaded belt. The main problems are losses in production tonnage and the difficulty experienced in the sequence of starting the handling system. During a ships loading or unloading opera

    23、tion, this can cause delays in the turnaround time of the ship. BS ISO 13292:20062 Alternative reference methods, which are also expensive, divert the ore flow onto a transfer conveyor belt to produce a material bed section identical to that from the main belt on which the mechanical primary sampler

    24、 (Method B) is installed. Stopped-belt sampling is then carried out on the transfer belt to collect reference increments (Method A). The transfer conveyor belt should be of sufficient length to allow the establishment of a material bed section that is not influenced by any longitudinal segregation i

    25、ntroduced by the diversion plate. The primary sampler and the point of diversion to the transfer belt should be as close as possible. Sampling and sample processing procedures are more prone to bias than analytical techniques and test methods. As system samples and reference increments are progressi

    26、vely reduced in mass and particle size, lot samples, subsamples and test samples become increasingly vulnerable to sample loss and contamination. Therefore, systematic errors occur more frequently during sample processing than during sampling, so different stages of the sample processing procedure m

    27、ay require testing for bias. Where testing for bias, the number of paired sets of measurements (data sets) shall be not less than 20. The number of data sets required depends on the variance of the differences between the two methods and on the value of the bias, , to be detected. Any chemical or ph

    28、ysical characteristic may be used to check whether any bias is present, e.g. copper, lead, zinc, nickel or moisture content. Bias may not always be present for just one parameter. Therefore, several parameters to reduce the effect of short-term variations in quality, preferably including all those t

    29、hat are likely to be of interest, should be examined to determine whether bias exists. Characteristics to be tested for the presence of bias need to be decided before the test work begins. If the purpose of the bias check is to assess the performance of the sampling equipment, it is recommended that

    30、 increments for Method A and Method B be taken from closely adjacent portions of the concentrate to reduce the effect of short-term variations in quality, and that sample processing and analysis be carried out on each increment individually. This is likely to reduce the number of data sets required

    31、to detect a given bias in the sampling equipment. On the other hand, if the purpose of the bias check is to determine whether the selected sampling regime is biased, e.g. due to the presence of periodic variations in quality, it is recommended that increments for Method A and Method B be taken compl

    32、etely independently. Even after a bias check has been conducted, further checks should be carried out at regular intervals. Bias checks should also be carried out when sampling equipment is changed. 4 Sampling and sample processing methods 4.1 Sampling 4.1.1 General The method to be checked (Method

    33、B) shall be compared with a designated reference method (Method A) using the same type of concentrate. Method A may also be an alternative method that is being compared with Method B. As specified in Clause 3, at least 20 pairs of samples shall be collected following the procedures detailed in ISO 1

    34、2743. BS ISO 13292:200634.1.2 Checking bias in mechanical sampling Method A: Reference increments are taken by stopped-belt sampling. Method B: System increments are taken from a moving stream with a mechanical sampler. 4.1.3 Checking difference between sampling at different locations Method A: Incr

    35、ements are taken from a moving stream with a mechanical sampler at a loading location. Method B: Increments are taken from a moving stream with a mechanical sampler at a discharge location. 4.2 Sample processing and analysis The procedure for constituting pairs of samples and carrying out the subseq

    36、uent sample processing and analysis shall be as follows. a) Constitute two samples (sample A and sample B), consisting of one or a number of individual increments obtained in accordance with Method A and Method B. b) Subject sample A and sample B to similar sample processing and analysis procedures,

    37、 as specified in ISO 12743 and other relevant International Standards, to obtain sets of measurements for the characteristics of interest. It is recommended that analyses of paired samples be carried out under repeatability conditions, to decrease the analytical variance. 5 Analysis of experimental

    38、data 5.1 Statistical basis It is helpful at this point to review the definitions of Type I and Type II risks in bias testing. Consider the null hypothesis, H0, that there is no positive or negative bias in Method B compared with Method A. The alternative hypothesis, H1, is that there is either posit

    39、ive or negative bias. A Type I error occurs if H0is rejected on the basis of the sample data falling into the critical region of a statistical test when, in reality, H0is true. A Type II error occurs if H0is accepted on the basis of the statistical test on the sample data when, in reality, H1is true

    40、. In this International Standard, the statistical test for accepting H0is that the absolute value of the difference between the mean of the quality characteristics for the reference (or alternative) set of increments (Method A) and the mean for the corresponding set of system increments (Method B) i

    41、s smaller than a specified bias detection limit, BDL. A bias can be either positive or negative, so for a positive bias: ( ) ( )BABDLxx+ (1) while for a negative bias: ( ) ( )BABDLxx , calculate the standardized difference, D, and the required number of data sets, nr, corresponding to this value of

    42、D using Equations 8 and 9 below. These equations are based on the strategy of adjusting the number of data sets in Equation 7 until BDL = , while avoiding the rigour of adjusting the corresponding degrees of freedom in the t-tests: Ds=d(8) ()kkttnD+=20,05; 1 0,10; 1r2(9Calculated values of nrfor k =

    43、 20 and different values of the standardized difference D are given in Table 2. e) Collect an additional (nr- k) data sets and repeat steps b) to d) until the number of data sets exceeds nr. Table 1 Values of t at 5 % and 10 % levels of significance (two-sided test) Number of data sets, k t0,05;k 1t

    44、0,10;k 120 21 22 23 24 25 26 27 28 29 30 31 41 61 121 2,093 2,086 2,080 2,074 2,069 2,064 2,060 2,056 2,052 2,048 2,045 2,042 2,021 2,000 1,980 1,960 1,729 1,725 1,721 1,717 1,714 1,711 1,708 1,706 1,703 1,701 1,699 1,697 1,684 1,671 1,658 1,645 BS ISO 13292:20066 Table 2 Required number of data set

    45、s determined from the initial 20 measurements for given standardized differences D and = 0,05 and = 0,10 Standardized difference D Required number of data sets nr0,35 0,40 0,45 0,50 0,55 0,60 0,65 0,70 0,75 0,80 0,85 119 91 72 58 48 41 35 30 26 23 20 NOTE The required number of data sets in this tab

    46、le is calculated using Equation 9 with t0,05;19= 2,093 and t0,10;19= 1,729 (from Table 1). 5.4 Statistical test Calculate the value of a parameter t0(which is assumed to have a t-distribution with 1k degrees of freedom) using the following equation: dkts=0d(10) If the absolute value of t0is smaller

    47、than the value of t0,05;k 1given in Table 1 for k data sets ( 1k degrees of freedom), the difference between Method A and Method B is not larger than d, the value of the bias (or difference) to be detected. Therefore, Method A and Method B can be considered equivalent and hence Method B could be ado

    48、pted as a routine method, if Method A is a designated reference method. However, if the absolute value of t0is larger than the value of t0,05;k1in Table 1, there is a significant difference between Method A and Method B, and hence a significant bias in Method B, if Method A is a designated reference

    49、 method. Action should be taken to eliminate this bias . BS ISO 13292:20067Annex A (informative) Numerical examples of determining the bias of sampling A.1 Example 1 ( = 0,2 % copper) The numerical example shown in Table A.1 is the result of an experiment comparing stopped-belt sampling with a mechanical sampler carried out in accordance with 4.1. The magnitude of bias to be detected is 0,2 % copper (m/m). Table A.1 Numerical example 1 (copper concentrate) Copper content, % (m/m) Data set xBixAidi= xBi- xAidi21 2 3 4 5 6 7 8 9 10 11 12 13 14


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