Speed and Current Sensor Fault Detection and Isolation Based on Adaptive Observers for IM Drives

Yu, Yong Chang; Wang, Ziyuan; Xü, Dianguo; Zhou, Tao; Xu, Riwei

doi:10.6113/jpe.2014.14.5.967

Cited by 36 publications

(24 citation statements)

References 23 publications

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“…There are three main kinds of faults in induction motor drive systems: electrical faults, mechanical faults, and sensor faults [8]. On the controller side, sensor faults are one of the most common problems in industrial applications [9].…”

Section: Speed Sensor Faultmentioning

confidence: 99%

Comparative study between propulsion control system failures of an electrical vehicle piloted by FOC and by DTC using dual-induction-motors structure

Cherif¹,

Benoudjit²,

Naït-Saïd³

et al. 2020

Diagnostyka

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This paper deals with a comparative study using numerical simulations between the failures effect caused by the speed sensor faults for a propulsion control system (PCS) of an electrical vehicle (EV) using dualinduction motors structure. The PCS strategies are achieved on two types of controls where the first one is done from a flux-oriented control (FOC) and the second one is conducted from a direct torque control (DTC). For an electric vehicle, we will often guarantee service continuity, in spite of the occurred faults such as an offset fault in speed sensor and a zero-feedback sensor speed fault which both are essentially needed in the structure of the PCS-EV. The occurred fault cited above might influence one of the dual induction motors which could be conducted an unbalance in the dual used motors and from which the control of the vehicle might be also lost. The results of the realized numerical simulations on the EV conducted by the PCS demonstrate clearly the impact of the so-called-fault. Thereafter, we can also appreciate the robustness using each used control propulsion system in despite of the occurred speed sensor fault.

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Section: Speed Sensor Faultmentioning

confidence: 99%

Comparative study between propulsion control system failures of an electrical vehicle piloted by FOC and by DTC using dual-induction-motors structure

Cherif¹,

Benoudjit²,

Naït-Saïd³

et al. 2020

Diagnostyka

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show abstract

“…These schemes are proposed for an IM system [8,[28][29][30], DFIG system [9,10] and PMSG system [2,31]. The schemes in [28][29][30] are presented to isolate single sensor fault. In these approaches, a bank of observers is established to monitor each sensor fault on the basis of the rest sensors are health.…”

Section: Multiple Fault Detection and Isolationmentioning

confidence: 99%

LPV Model Based Sensor Fault Diagnosis and Isolation for Permanent Magnet Synchronous Generator in Wind Energy Conversion Systems

et al. 2018

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This paper deals with the current sensor fault diagnosis and isolation (FDI) problem for a permanent magnet synchronous generator (PMSG) based wind system. An observer based scheme is presented to detect and isolate both additive and multiplicative faults in current sensors, under varying torque and speed. This scheme includes a robust residual generator and a fault estimation based isolator. First, the PMSG system model is reformulated as a linear parameter varying (LPV) model by incorporating the electromechanical dynamics into the current dynamics. Then, polytopic decomposition is introduced for H ∞ design of an LPV residual generator and fault estimator in the form of linear matrix inequalities (LMIs). The proposed gain-scheduled FDI is capable of online monitoring three-phase currents and isolating multiple sensor faults by comparing the diagnosis variables with the predefined thresholds. Finally, a MATLAB/SIMULINK model of wind conversion system is established to illustrate FDI performance of the proposed method. The results show that multiple sensor faults are isolated simultaneously with varying input torque and mechanical power.

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“…The fault detect method can isolate the incipient fault of a speed sensor and current sensors in real-time, but the performance of the state observer is degraded at very low speed. In reference [ 43 ], three Luenberger observers are used to realize a fault diagnosis of the current sensors, as shown in Figure 7 . The proposed three paralleled adaptive observers are capable of current sensor fault detection and localization.…”

Section: Sensor Fault Diagnosismentioning

confidence: 99%

Review on the Traction System Sensor Technology of a Rail Transit Train

Feng

Liao

et al. 2017

Sensors

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The development of high-speed intelligent rail transit has increased the number of sensors applied on trains. These play an important role in train state control and monitoring. These sensors generally work in a severe environment, so the key problem for sensor data acquisition is to ensure data accuracy and reliability. In this paper, we follow the sequence of sensor signal flow, present sensor signal sensing technology, sensor data acquisition, and processing technology, as well as sensor fault diagnosis technology based on the voltage, current, speed, and temperature sensors which are commonly used in train traction systems. Finally, intelligent sensors and future research directions of rail transit train sensors are discussed.

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Speed and Current Sensor Fault Detection and Isolation Based on Adaptive Observers for IM Drives

Cited by 36 publications

References 23 publications

Comparative study between propulsion control system failures of an electrical vehicle piloted by FOC and by DTC using dual-induction-motors structure

Comparative study between propulsion control system failures of an electrical vehicle piloted by FOC and by DTC using dual-induction-motors structure

LPV Model Based Sensor Fault Diagnosis and Isolation for Permanent Magnet Synchronous Generator in Wind Energy Conversion Systems

Review on the Traction System Sensor Technology of a Rail Transit Train

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