Fault Detection and Diagnostics for Rooftop Air Conditioners

T
T
− T
− T
W
=
W
−W
−W
m
=
m
ma ra ma ra oa
=
oa
ma
oa
If the speed of the evaporator blower is constant, f approximates the ratio of return and
outdoor air duct damper positions, which can be readily obtained from Honeywell DCV
controllers. Although, unlike the first method, the ma state can be determined for any
o
case, uncertainties will be propagated and amplified when θ is less than 90 .
In view of performance, it is still desirable to add a mixed air humidity sensor to avoid
uncertainty propagation and amplification. However, since the humidity sensor is relatively
expensive further work should be done to decide whether the extra expense is warranted
by the improved accuracy.
ma
ra
f
4.2.2 Steady-State Detector
In order to apply a steady-state model to a system, which spends considerable time in
transient operation, a steady-state detector is necessary. Thus, the error in the ability of the
model to fit the training data is added to the error introduced by the fact that the system is
almost never actually operating in steady-state. There are a number of desirable properties
of a steady-state detector method. It should be computationally efficient, require a small
amount of memory for storing values, be responsive to quick changes in operation, and be
able to distinguish between changes in measurements caused by transient operation and
measurement and system noise.
Three methods were studied by Davis (1995) through simulation for simple first-order
responses with artificial noise introduced. The three steady-state detector methods all
generate outputs which decrease as the system approaches steady-state. When the output
of the steady-state preprocessor drops below a threshold value, the system is determined to
be in steady-state. The first algorithm computes the slope of the best-fit line through a
fixed-length sliding window of recent measurements. The other two algorithms compute
the variance of recent measurements. One uses a fixed length sliding window of recent
measurements. The other method, introduced by reseachers at Landis and Gyr (Glass,
1995), recursively computes a weighted standard-deviation where more recent
measurements are weighted more heavily. Based on his analysis, Davis concluded that the
weighted standard-deviation method was the best of the three methods in terms of
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