A probabilistic time variant sensor accuracy model and GUI in aerospace applications

In this work, we proposed a unique model and Graphic User Interface (GUI) to measure the sensor accuracy with different accuracy regions for aerospace applications. Sometimes the measurement region for the sensor is a wide range, and the sensor might have higher accuracy in different regions. In other words, the accuracy values are not uniform for the entire range. In this work we developed a Matlab model and GUI that estimate the accuracy of the overall performance of the sensor when there are multiple accuracy regions of differing tolerances. This model and GUI use probability distribution parameters as a feedback input and the error distribution of the sensor to estimate the accuracy during each flight/ground phase/time interval which makes it a time variant model. The proposed GUI can be used to display multiple sensor error functions for different user inputted probabilistic parameters from estimated measurement distributions. This model and GUI can be used to determine what sensors to be selected, where the sensors can be used, and guide a machine or a user for a more productive decision making process. The current model and GUI exist in Matlab and return error curves for different probabilistic parameters to display the effect of changing your parameters due to expected distribution of measurements. It introduces a high fidelity model that could meet challenging program accuracy requirements, reduce the cost of man power, and processing time. Moreover, the proposed tool can be used to estimate the error generated by the resistance of the cable in a two-wire Resistance Temperature Detectors (RTDs) and predicts the behavior of error for different lengths of cable. This can help us use two-wire RTDs instead of three-wired RTDs where the probability distribution of measurements is outside the sensitive region in the extreme cold (cryogenic) region due to the delta resistance between temperature measurements being very small. This reduces the mass which significantly reduces the cost and installation time as well.