Low-cost smart embedded sensor for single throw mechanical equipment

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.