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"Nondestructive Evaluation System
Reliability Assessment"

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MIL-HDBK-1823A tells how to plan an NDE experiment, design and fabricate reliability demonstration specimens, acquire the system performance data, and provides statistical methods for analyzing the data to produce POD(a) curves, 95% confidence bounds, noise analysis, and noise vs. detection trade-off curves. It presents worked-out examples using real Hit/Miss and ‚ data, and serves as a user’s manual for the mh1823 POD software.

These methods are statistical best-practices and have universal applicability – NDE of engines, airframes, ground vehicles – subject to the following limitations:

  1. The NDE systems must produce output that can be reduced to either a quantitative signal, ‚, or a binary response, hit/miss. (Images therefore will require some pre-processing to provide either ‚ or Hit/Miss as input to these analysis methods.)
  2. The specimens must have targets with measurable characteristics, like size or chemical composition. This precludes amorphous targets like corrosion unless a specific measure can be associated with it, such that other corrosion having that same measure will produce the same output from the NDE equipment.
  3. This mh1823 POD software assumes that the input data are correct. That is, if the size is X, then that is the true size. If the response is Y, then that is the true response. Situations where these conditions cannot be ensured (e.g. where target sizing is only approximate) will necessarily provide only approximate results. (The problem of accurate crack sizing is discussed in Handbook Appendix I.1 Departures from Underlying Assumptions – Crack Sizing and POD Analysis of Images.)
  4. This mh1823 POD software assumes that a POD curve goes to zero on the left, and to one on the right. Data for which min(POD) > 0 (perhaps due to signal contamination by excessive background noise), or max(POD) < 1 (resulting from random misses not related to target size) cannot be correctly represented by a model for which min(POD) = 0 and max(POD) =1. (See MIL-HDBK-1823, Appendix I-4 "Asymptotic POD Functions.")

If the input data do not meet MIL-HDBK-1823 requirements, the mh1823 POD software may still produce an answer, but it will be WRONG.

MIL-HDBK-1823 History:

R logoNOTE: The mh1823 POD algorithms use R, the most powerful statistical and graphics engine available anywhere, for all data manipulation, statistical analysis, and graphics. Because R is open-source (and free), and because all of the algorithms and methods developed here are based on modern, well documented statistical best practices described in the open literature, there is nothing proprietary in this mh1823 POD software. Since there are no restrictions on its use, the mh1823 POD software can be used as a universal standard for performing Probability of Detection (POD) analysis.

Click here to see the mh1823 POD software version history.