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4.6 MBD on the Power Supply Model-Based Fault Diagnosis
system Cable (
bool p, //input
bool q //output
) {
//declaration health variable
bool h;
attribute health(h) = true;
attribute probability(h) = h ? 0.92 : 0.08;
}
//definition behavior
h => ( q = p );
The boolean variable p is the input of the cable, and cable q is the output of the cable. Each
instantiation of a cable declares a health variable that defines a probability of 8 percent of being
false. This value, and the health probability values of the other system, are chosen to order the list
of diagnoses that the LYDIA diagnostic engine produces. The system power_supply defines the
structure of the power supply example, and by doing so, it defines the behavior of the whole power
supply example system. There are 6 variables defined as observables; the inputs and outputs to the
system. In the fault scenario described earlier, the values of these observables are:
status_Chiller = true
status_FD = true
status_TBCB = false
status_CRCB = false
status_Collimator = false
The result of inserting these values in the diagnostic engine LYDIA produces a long list of possible
diagnoses. The malfunctioning of CableB has highest probability. The second item on the produced
list is that the PDU is at false. The results of a MBD implementation can be characterized by a LUT.
The LUT is constructed by inserting all possible observations to the diagnostic engine LYDIA. Table
3.2 shows the LUT that presents the results of the model listed in Appendix C.2.1.
4.6.1 Strong Model of the Power Supply
The model listed in Appendix C.2.1 is a weak model of the power supply example. A strong model
of the power supply example is listed in Appendix C.2.2. This model specifies that a component
conducts no current if it is broken. This affects the results that the diagnostic engine LYDIA produces.
Table 4.2 shows the new LUT for single faults. The values of the observables in entry 7, 8 and 15
no longer imply that the PDU could be broken. The strong model of the PDU specifies that when PDU
malfunctions all outputs are stuck-at-zero, so none of the components could get voltage. So, the fault
scenario described above yields that CableB is at false, without any uncertainty. For fault scenarios
that have observables that map on the 15 th entry of Table 4.2 this means that the Chameleon is
broken without any uncertainty. The disadvantage of strong models is that the model is less robust.
Suppose the PDU also has fault modes that imply that only one of its outputs is stuck-at-zero. If
undefined fault modes exist, although not expected, the diagnostic engine no longer produces correct
results for certain fault scenarios.
However, the amount of multiple fault explanations for certain observable values greatly decreases.
And this way, the diagnostic engine skips states of the system that are impossible. This
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