This article presents an algorithm for reducing measurement uncertainty of one physical quantity when given oversampled measurements of two physical quantities with correlated noise. The algorithm assumes that the aleatoric measurement uncertainty in both physical quantities follows a Gaussian distribution and relies on sampling faster than it is possible for the measurand (the true value of the physical quantity that we are trying to measure) to change (due to the system thermal time constant) to calculate the parameters of the noise distribution. In contrast to the Kalman and particle filters, which respectively require state update equations and a map of one physical quality, our algorithm requires only the oversampled sensor measurements. When applied to temperature-compensated humidity sensors, it provides reduced uncertainty in humidity estimates from correlated temperature and humidity measurements. In an experimental evaluation, the algorithm achieves average uncertainty reduction of 10.3 %. The algorithm incurs an execution time overhead of 5.3 % when compared to the minimum algorithm required to measure and calculate the uncertainty. Detailed instruction-level emulation of a C-language implementation compiled to the RISC-V architecture shows that the uncertainty reduction program required 0.05 % more instructions per iteration than the minimum operations required to calculate the uncertainty.
A star type wireless sensor network based on nine-axis micro-electromechanical inertial motion sensors with the potential to include up to 254 sensor nodes is presented, and an investigation into the mechanical and structural effects of bell ringing on bell towers is presented as a possible application. This low-power and low-cost system facilitates the continual monitoring of mechanical forces exerted by swinging bells on their support and thus helps avoid structural degradation and damage. Each sensor measures bell rotation, and a novel method utilising only the instantaneous rotational angle is implemented to calculate the force caused by bell ringing. In addition, a commonly used, however, previously experimentally unconfirmed assumption that allows great simplification of force calculations was also proven to be valid by correlating predicted theoretical values with measurement data. Forces produced by ringing a 1425 kg bell in Durham Cathedral were characterised and found to agree with literature. The sensor network will form the basis of a toolkit that provides a scalable turnkey method to determine the exact mechanisms that cause excessive vibration in mechanical and architectural structures, and has the potential to find further applications in low-frequency distributed structural health monitoring.
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