T-NT Confidence Bounds

This subchapter includes the following topics:

Approximate Confidence Bounds for the T-NT Exponential

Confidence Bounds on the Mean Life

The mean life for the T-NT model is given by Eqn. ( 1) by setting m = L(V). The upper mU and lower mL bounds on the mean life (ML estimate of the mean life) are estimated by:

10.11.13.gif(13)

10.11.14.gif(14)

where Kα is defined by:

10.11.1.gif

If delta.gif is the confidence level, then α = 1delta2.gif for the two-sided bounds and α =1- delta.gif for the one-sided bounds. The variance of mhat.gif is given by:

10.11.2.gif

or:

10.11.3.gif

The variances and covariance of B, C and n are estimated from the local Fisher Matrix (evaluated at bhat.gif, chat.gif, nhat.gif) as follows:

10.11.4.gif

where:

10.11.5.gif

Confidence Bounds on Reliability

The bounds on reliability at a given time, T, are estimated by:

10.12.1.gif

where mU and mL are estimated using Eqns. ( 13) and ( 14).

Confidence Bounds in Time

The bounds on time for a given reliability (ML estimate of time) are estimated by first solving the reliability function with respect to time:

10.13.1.gif

The corresponding confidence bounds are estimated from:

10.13.2.gif

where mU and mL are estimated using Eqns. ( 13) and ( 14).

Approximate Confidence Bounds for the T-NT Weibull

Bounds on the Parameters

Using the same approach as previously discussed (betahat.gif and chat.gif positive parameters):

10.21.1.gif

and:

10.21.2.gif

The variances and covariances of β, B, C and n are estimated from the Fisher Matrix (evaluated at betahat.gif, bhat.gif, chat.gif, nhat.gif) as follows:

10.21.3.gif

where:

10.21.4.gif

Confidence Bounds on Reliability

The reliability function (ML estimate) for the T-NT Weibull model is given by:

10.22.1.gif

or:

10.22.2.gif

Setting:

10.22.3.gif

or:

10.22.4.gif

The reliability function now becomes:

10.22.5.gif

The next step is to find the upper and lower bounds on u:

10.22.15.gif(15)

10.22.16.gif(16)

where:

10.22.6.gif

or:

10.22.7.gif

The upper and lower bounds on reliability are:

10.22.8.gif

where uU and uL are estimated using Eqns. (15) and (16).

Confidence Bounds on Time

The bounds on time (ML estimate of time) for a given reliability are estimated by first solving the reliability function with respect to time as follows:

10.23.1.gif

or:

10.23.2.gif

where uhat2.gif = lnthat.gif.

The upper and lower bounds on u are estimated from:

10.23.17.gif(17)

10.23.18.gif(18)

where:

10.23.3.gif

or:

10.23.4.gif

The upper and lower bounds on time are then found by:

10.23.5.gif

where uU and uL are estimated using Eqns. (17) and (18).

Approximate Confidence Bounds for the T-NT Lognormal

Bounds on the Parameters

Since the standard deviation, otdash2.gif and chat.gif are positive parameters, ln (otdash2.gif) and ln (chat.gif) are treated as normally distributed and the bounds are estimated from:

10.31.1.gif (upper bound)

10.31.01.gif (lower bound)

and

10.31.2.gif (upper bound)

10.31.02.gif (lower bound)

The lower and upper bounds on B and n, are estimated from:

10.31.3.gif (upper bound)

10.31.03.gif (lower bound)

and

10.31.4.gif (upper bound)

10.31.04.gif (lower bound)

The variances and covariances of B, C, n and otdash.gif are estimated from the local Fisher Matrix (evaluated at bhat.gif, chat.gif, nhat.gif, otdash2.gif) as follows:

10.31.5.gif

where:

10.31.6.gif

Bounds on Reliability

The reliability of the lognormal distribution is given by:

10.32.1.gif

Let zhat2.gif (t, U, V; B, C, n, OT.gif) = Eqn. 10.gif,

then dzdt.gif.

For t = Tdash2.gif, zhat2.gif = Eqn. 11.gif and for t = oo.gif, zhat2.gif = oo.gif. The above equation then becomes:

10.32.2.gif

The bounds on z are estimated from:

10.32.3.gif

where:

10.32.4.gif

or:

10.32.5.gif

The upper and lower bounds on reliability are:

10.32.6.gif (upper bound)

10.32.06.gif (lower bound)

Confidence Bounds on Time

The bounds around time, for a given lognormal percentile (unreliability), are estimated by first solving the reliability equation with respect to time, as follows:

10.33.1.gif

where:

10.33.2.gif

and:

10.33.3.gif

The next step is to calculate the variance of Tdash2.gif(U, V; bhat.gif, chat.gif, nhat.gif, otdash2.gif):

10.33.4.gif

or:

10.33.5.gif

The upper and lower bounds are then found by:

10.33.6.gif

Solving for TU and TL yields:

10.33.7.gif

See Also:
Temperature-NonThermal Relationship


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