This research builds on the work carried out in the area of developing a smart sensor for Single Throw Mechanical Equipment
(STME). Limits sensors are the best candidate for observing throw trajectories although their limitation to detect a continuous
change in residuals, restricts their usage to discrete applications. Thus research and academia maintains focus on continuous
sensors, while industry keeps the limit switches as their key sensor. The paper attempts to bridge the gulf and formally presents a
framework for deploying optimal number of limit switches to capture the process dynamics with increased degree of freedom
and use them as model based multi sensor residual generator. The energy distribution of Residual Spectra generated by such
Model Based Parity Space relationship results in drifts in the form of Eigen value. The Eigen vector in such a multi-dimensional
Residual Space is used to maintain the degree and polarity of drift. This paper presents investigations into the issues related to
such Eigen analysis. It was found that normalized residuals from multiple sources and parity space relations are neutralized in
the form of unified representation of energy that can be used to form a generic framework for fault detection and isolation. It is
being investigated, how the proper modeling of quantitative entities as energy, could lead to unified and neutral residual space
while keeping the implementation cost reasonably low. Higher degree of freedom allows robust model based self diagnostics to
cater for sensor, actuators and system failures isolation model based self diagnostics. An FPGA based implementation of the
algorithm is underway based on MEMS to ensure compact very high degree freedom of sensor within financial constraints for
Embedded STMEs embedded fault Diagnostics system.
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