2021 IEEE International Conference on Mechatronics (ICM) 2021
DOI: 10.1109/icm46511.2021.9385663
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Diagnosis of Sensor Faults in PMSM and Drive System Based on Structural Analysis

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Cited by 3 publications
(4 citation statements)
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“…Following this step, the diagnosis of the related faults in a sy by mining the set of analytically redundant relations in the system is carried out [23 Zhang J. et al studied the joint diagnosis problem for eight sensor faults in the perma magnet drive system of electric vehicles, including inverter output three-phase volt motor output three-phase current, a motor position sensor, and a vehicle speed sensor Ebrahimi S. H. et al realized the joint diagnosis of the position sensor and the motor The diagnosis of 10 sensor signals was investigated, including inverter input DC vol inverter output three-phase voltage, motor three-phase current, motor speed, motor p tion, and load torque, based on the inverter output three-phase voltage, the motor ou three-phase current, and the motor position sensor signals in a permanent magnet d system [25]. The above multi-sensor joint diagnosis methods based on structural ana [23][24][25] have added many redundant sensors (e.g., hardware redundancy among th phase voltage sensors, redundancy between motor speed and position sensors, etc Fruitful research results have been achieved for the sensor fault diagnosis of PMTDSs [6]. According to the type of diagnostic objects, these methods can be divided into two categories: single-sensor fault diagnosis and joint fault diagnosis of multiple types of sensors.…”
Section: Introductionmentioning
confidence: 99%
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“…Following this step, the diagnosis of the related faults in a sy by mining the set of analytically redundant relations in the system is carried out [23 Zhang J. et al studied the joint diagnosis problem for eight sensor faults in the perma magnet drive system of electric vehicles, including inverter output three-phase volt motor output three-phase current, a motor position sensor, and a vehicle speed sensor Ebrahimi S. H. et al realized the joint diagnosis of the position sensor and the motor The diagnosis of 10 sensor signals was investigated, including inverter input DC vol inverter output three-phase voltage, motor three-phase current, motor speed, motor p tion, and load torque, based on the inverter output three-phase voltage, the motor ou three-phase current, and the motor position sensor signals in a permanent magnet d system [25]. The above multi-sensor joint diagnosis methods based on structural ana [23][24][25] have added many redundant sensors (e.g., hardware redundancy among th phase voltage sensors, redundancy between motor speed and position sensors, etc Fruitful research results have been achieved for the sensor fault diagnosis of PMTDSs [6]. According to the type of diagnostic objects, these methods can be divided into two categories: single-sensor fault diagnosis and joint fault diagnosis of multiple types of sensors.…”
Section: Introductionmentioning
confidence: 99%
“…Ebrahimi S. H. et al realized the joint diagnosis of the position sensor and the motor [24]. The diagnosis of 10 sensor signals was investigated, including inverter input DC voltage, inverter output three-phase voltage, motor three-phase current, motor speed, motor position, and load torque, based on the inverter output three-phase voltage, the motor output three-phase current, and the motor position sensor signals in a permanent magnet drive system [25]. The above multi-sensor joint diagnosis methods based on structural analysis [23][24][25] have added many redundant sensors (e.g., hardware redundancy among three-phase voltage sensors, redundancy between motor speed and position sensors, etc.)…”
Section: Introductionmentioning
confidence: 99%
“…In Ref. [ 8 ], a structural analysis method is applied to diagnose the sensor faults; the Dulmage Mendelsohn decomposition technique is used in the diagnosis model, according to the dynamic model in the matrix form. The authors in [ 9 ] present an FTC technique based on electrical torque to reduce the IMD system’s current sensor noise.…”
Section: Introductionmentioning
confidence: 99%
“…The structural analysis approach has been able to successfully detect faults in automotive engines [26][27][28], hybrid vehicle [29], and battery systems [30]. In [31,32]. The algorithm has successfully been applied on PMSM electric drive systems to detect sensor faults such as voltage, current, encoder, and torque sensors.…”
Section: Introductionmentioning
confidence: 99%