The presence of an open-circuit fault subjects a three-phase induction motor to severely unbalanced voltages that may damage the stator windings consecutively causing total shutdown of systems. Unplanned downtime is very costly. Therefore, fault diagnosis is essential for making a predictive plan for maintenance and saving the required time and cost. This paper presents a model-based diagnosis technique for diagnosing an open-circuit fault in any phase of a three-phase induction motor. The proposed strategy requires only current signals from the faulty machine to compare them with the healthy currents from an induction motor model. Then the errors of comparison are used as an objective function for a genetic algorithm that estimates the parameters of a healthy model, which they employed to identify and localize the fault. The simulation results illustrate the behaviours of basic parameters (stator and rotor resistances, self-inductances, and mutual inductance) and the number of stator winding turn parameters with respect to the location of an open-circuit fault. The results confirm that the number of stator winding turns are the useful parameters and can be utilized as an identifier for an open-circuit fault. The originality of this work is in extracting fault diagnosis features from the variations of the number of stator winding turns.
Multilevel inverters have been widely used in various occasions due to their advantages such as low harmonic content of the output waveform. However, because multilevel inverters use a large number of devices, the possibility of circuit failure is also higher than that of traditional inverters. A T-type three-level inverter is taken as the research object, anda diagnostic study is performed on the open-circuit fault of insulated gate bipolar transistor (IGBT) devices in the inverter. Firstly, the change of the current path in the inverter when anopen-circuit fault of the device occurred, and the effect on the circuit switching states andthe bridge voltages were analyzed. Then comprehensively considered the bridge voltages,and proposed a fault diagnosis method for a T-type three-level inverter based on specificfault diagnosis signals. Finally, the simulation verification was performed. The simulation results prove that the proposed method can accurately locate the open-circuit fault of theinverter device, and has the advantage of being easy to implement.
DC-DC converters have become essential components in various industrial applications, including aerospace, electric vehicles, and renewable energy systems. However, ensuring enhanced reliability remains a critical challenge for these converters. Fault diagnosis and reliability analysis are crucial for preventing damage and minimizing maintenance costs. This study focuses on investigating the operational behavior of DC-DC boost converters under normal and faulty conditions, precisely targeting open-circuit and short-circuit faults in converter switches. To achieve this, an adaptive threshold approach is introduced for effective fault detection. The adaptive threshold value is calculated based on measured voltage and current signals, along with their corresponding reference signals from the primary control system. The research is structured into two parts: the first part addresses sliding mode control aspects, ensuring regulated output voltages, output currents, and capacitor voltage for sustained converter operation. The second part investigates fault diagnosis, analyzing the impact of defective DC-DC converters on the overall electrical system functionality. The proposed algorithm's performance is evaluated and validated through simulations in MATLAB/Simulink environment. Furthermore, based on the results’ comparison, the proposed approach of the sliding mode controller and adaptive threshold contributes to enhancing the reliability of DC-DC converters and enables effective fault detection and isolation.
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