Displacement sensors play a key role in the control of dynamic processes. Such sensors can be endowed with self-diagnostic capabilities to identify both the degradation of their conditions and the possible process anomalies that caused them, thus allowing researchers to monitor the process efficiency and therefore its sustainability. Within this scope, a self-diagnostic method is proposed to infer the conditions of a resistive displacement sensor by estimating its model parameters online during operation. Experimental results confirm the effectiveness of the presented method.
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Mazzoli et al. (2024) studied this question.
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