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image of Choosing an Analogue to Digital Converter with Data Safety in Mind


Industry 4.0 is built upon the foundations of converting real world analogue effects into digitised binary data suitable for a computer to process. This needs to be done with care, particularly when the data is ingested by a safety critical system. A numerical study probing the limits of a typical analogue to digital converter is presented here, highlighting some potential issues that should be identified. Initially a Monte Carlo approach is used to probe the impact of digitisation on an analogue to digital converter (ADC) using traditional experimental error analysis. A constant test signal 2.5±0.01"V"  is used to understand the optimum level of digitisation. The analogue signal is assumed to have Gaussian noise which is then processed by a 5"V"  ADC. This investigation suggests an optimum digitisation level should be related to the standard error of a measured signal. The use of Bayesian inferencing using the Python package PyMC is then used to gain a better estimate of the underlying standard deviation when the signal has been digitised at the 8-bit level.


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