The paper proposes a novel approach based on a current space vector derived from measured stator currents to diagnose speed and current sensor failures in the field-oriented control of induction motor drives. A comparison algorithm between the reference and measured rotor speed is used to detect the speed sensor faults. A counter is added to eliminate the influence of the encoder noise in the diagnosis method. In this approach, estimated quantities are not used in the proposed speed sensor fault diagnosis strategy, which increases the independence between the diagnosis stages in the fault-tolerant control (FTC) method. Moreover, in order to discriminate between the speed sensor faults and the current sensor faults, a new approach combining the current space vector and a delay function is proposed to reliably determine the current sensor failures. The MATLAB-Simulink software was used to verify the idea of the proposed method. Practical experiments with an induction motor drive controlled by DSP TMS320F28335 were performed to demonstrate the feasibility of this method in practice. The simulation and experimental results prove the effectiveness of the proposed diagnosis method for induction motor drives.

A novel diagnosis method based on the rotor slip is proposed in the paper to correctly detect current and speed sensor failures during the induction motor drive (IMD) operation. In order to enhance reliability and avoid confusion in the diagnosis algorithm due to the influence of measured signal quality, each fault type is determined in a priority order defined by the diagnosis method. Based on the features of the IMD applying the field-oriented control (FOC) technique, an innovative model uses the measured currents and reference speed as the input signals to estimate the rotor slip for the current sensor fault detection. After verifying the quality of the feedback of the current signals, a speed sensor fault function is continued, and performs according to relations among the reference speed, estimated speed based on the sliding mode method, and measured rotor speeds. Finally, the estimated quantities are selected to replace the wrong measured current or speed signals. The feasibility of the proposed approach is verified by simulations using Matlab-Simulink software as well as by practical experiments using an IMD prototype with a rated power of 2.2 kW and a DSC-TMS320F28335-based control system. The obtained simulation and experimental results demonstrated the feasibility, effectiveness, and reliability of the proposed diagnosis technique in detecting sensor failures and maintaining the stable operation of the IMD.

This paper proposes a fault-tolerant control (FTC) strategy using the current space vectors to diagnose sensor failures and enhance the sustained operation of a field-oriented (FO) controlled induction motor drive (IMD). Three space vectors are established for the sensor fault diagnosis technique, including one converted from the measured currents and the other two calculated from the current estimation technique, respectively, measured and with reference speeds. A mixed mathematical model using three space vectors and their components is proposed to accurately determine the fault condition of each sensor in the motor drive. After determining the operating status of each sensor, if the sensor signal is in good condition, the feedback signal to the controller will be the measured signal; otherwise, the estimated signal will be used instead of the failed signal. Failure states of the various sensors were simulated to check the effectiveness of the proposed technique in the Matlab/Simulink environment. The simulation results are positive: the IMD system applying the proposed FTC technique accurately detected the failed sensor and maintained stability during the operation.

An improved method using the phase angle shift characteristic of the sine wave is proposed to diagnose the fault states of the current sensors in an induction motor drive. The induction motor drive (IMD) system applied in this study uses the field-oriented control (FOC) loop with integrated two current sensors and a speed encoder to control the rotor speed. The space vectors created from the phase angle shift technique are compared to the estimated current for the fault diagnosis algorithm. Various types of current sensor failures are investigated by MATLAB/Simulink software to check the effectiveness of the proposed method. The simulation results have proved the performance of the proposed method in enhancing the reliability and stability of the IMD system.

This paper conducts research on sensor fault diagnosis for a three-phase induction motor drive (IMD) in steady-state operation. An improving diagnostic technique based on the integration algorithm of the sinusoidal current signal is proposed for detecting and locating faulty current sensors in the induction motor drive. The IMD integrated a proposed fault detection-isolation (FDI) system is investigated for operating characteristics when sensor failures occur. The faulty sensor needs to be accurately identified and quickly isolated from the control system. Then the estimated signal will be used to replace the fault signal to retain the IMD stability. MATLAB/Simulink software will be applied to simulate the speed-torque characteristics of the IMD system as well as sensor failures occurring during operation. The performance of the proposed method will be evaluated through the accuracy and timeliness in each fault case corresponding to each sensor.

The typical scalar control method adjusts the speed based on changes in power frequency while maintaining a constant V/f ratio corresponding to the nominal flux. The disadvantage of the typical scalar method is that the motor operating speed is always less than the reference speed by a slip value. This research proposes an improved scalar control method based on slip compensation for speed control in the induction motor drive. A virtual speed according to the rotor flux-based model reference adaptive system (RF-MRAS) technique is applied to the current model to estimate the proper compensation of the rotor slip. The suitability of the control method is verified through comparative simulations between the typical and proposed methods under various operating conditions by the MATLAB/Simulink software.