Coal Age

MAY 2013

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coal sampling continued Figure 2: Final sample container. Figure 1: Primary cross-belt cutter bent due to impact of coal flow. In the other case, in Table 1, the statistical estimate of moisture bias was 1%. In the case of a 1% moisture bias, the economic consequence was much larger for a contract that had nearly 5 million tons committed. An additional consequence for the utility is that the opportunity for suspension or rejection may not be possible if the observed analysis and contract specification are borderline. One possible resolution for a bias is to just add or subtract as appropriate the estimate of bias to the contract specification. The flaw with that option is the assumption that a bias is linear i.e., the same amount consistently. When a known bias exists it is prudent to resolve the issue and then take away any potential problem. A moisture bias is relatively easy to resolve as the cause of a moisture bias is almost always related to the feed rate to the sampling system crusher. The element of "surprise" is a risk to the operator of a sampling system. The system operator is put in conflict with the buyer or seller if an inspection results in a finding of equipment or operational issues and the issue was unknown to the system operator. During conduct of sampling system inspections for utilities and mining Figure 3: Bags standing open. Examples of Sampling System Observations During Inspections Sampling system inspectors who use the current methods based in mathematics versus just visual observations know that when all is within ASTM and industry accepted practice the system should be operating optimally. It is not unusual to be asked which things should I do and which observations do not make a difference? Since the current design of bias testing is to take stopped-belt samples to compare with the system save sample, post bias test diagnostics are difficult. The pre-test inspection is important to enhance system readiness for the bias test. May 2013 www.coalage.com 41

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