Abstract: This article presents modeling studies of NiAl alloy
under solid-particle erosion and liquid-drop erosion. In the
solid-particle erosion simulation, attention is paid to the oxide scale
thickness variation on the alloy in high-temperature erosion
environments. The erosion damage is assumed to be deformation wear
and cutting wear mechanisms, incorporating the influence of the oxide
scale on the eroded surface; thus the instantaneous oxide thickness is
the result of synergetic effect of erosion and oxidation. For liquid-drop
erosion, special interest is in investigating the effects of drop velocity
and drop size on the damage of the target surface. The models of
impact stress wave, mean depth of penetration, and maximum depth of
erosion rate (Max DER) are employed to develop various maps for
NiAl alloy, including target thickness vs. drop size (diameter), rate of
mean depth of penetration (MDRP) vs. drop impact velocity, and
damage threshold velocity (DTV) vs. drop size.
Abstract: Oil debris signal generated from the inductive oil
debris monitor (ODM) is useful information for machine condition
monitoring but is often spoiled by background noise. To improve the
reliability in machine condition monitoring, the high-fidelity signal
has to be recovered from the noisy raw data. Considering that the noise
components with large amplitude often have higher frequency than
that of the oil debris signal, the integral transform is proposed to
enhance the detectability of the oil debris signal. To cancel out the
baseline wander resulting from the integral transform, the empirical
mode decomposition (EMD) method is employed to identify the trend
components. An optimal reconstruction strategy including both
de-trending and de-noising is presented to detect the oil debris signal
with less distortion. The proposed approach is applied to detect the oil
debris signal in the raw data collected from an experimental setup. The
result demonstrates that this approach is able to detect the weak oil
debris signal with acceptable distortion from noisy raw data.
Abstract: To improve the dynamics response of the vehicle
passive suspension, a two-terminal mass is suggested to connect in
parallel with the suspension strut. Three performance criteria, tire grip,
ride comfort and suspension deflection, are taken into consideration to
optimize the suspension parameters. However, the three criteria are
conflicting and non-commensurable. For this reason, the Chebyshev
goal programming method is applied to find the best tradeoff among
the three objectives. A simulation case is presented to describe the
multi-objective optimization procedure. For comparison, the
Chebyshev method is also employed to optimize the design of a
conventional passive suspension. The effectiveness of the proposed
design method has been clearly demonstrated by the result. It is also
shown that the suspension with a two-terminal mass in parallel has
better performance in terms of the three objectives.