Current Differential Signal Extraction Algorithm via Fast-TD and Its Application in Open-Circuit Fault Diagnosis of Magnetic Bearings

Open-circuit faults in power switching elements are primary failures of active magnetic bearing (AMB) system. However, the characteristics of current signals of switching elements have not been fully used in the diagnosis of open-circuit faults in magnetic bearings. This article proposes a tracking differentiator (TD) algorithm, referred as Fast-TD, to extract differential information from the current signal, which is applied to the fault diagnosis of open-circuit failures in magnetic bearings. Especially, the rigorous convergence proof of the Fast-TD algorithm is presented. First, when a switching element of the three-phase full-bridge in AMB system is open-circuited, theoretical analysis demonstrates the feasibility of diagnosing the open-circuit faults in power switching elements in real time by analyzing the differential signals from the current sensor. Then, the Fast-TD algorithm for extracting the differential information of current sensor is proposed and its convergence is proven by demonstrating the convergence trajectories of the states within different regions. Next, the current differential extraction method via Fast-TD is applied to the fault diagnosis and fault-tolerant control (FTC) of a magnetic system. The case studies, which include comparison simulations with two other differentiators, verify the effectiveness of the proposed Fast-TD algorithm.