scholarly journals A Fast Diagnosis Method for Both IGBT Faults and Current Sensor Faults in Grid-Tied Three-Phase Inverters With Two Current Sensors

2020 ◽  
Vol 35 (5) ◽  
pp. 5267-5278 ◽  
Author(s):  
Zhan Li ◽  
Pat Wheeler ◽  
Alan Watson ◽  
Alessandro Costabeber ◽  
Borong Wang ◽  
...  
Keyword(s):  
Current Sensor ◽  
Sensor Faults ◽  
Three Phase ◽  
Diagnosis Method ◽  
Current Sensors

scholarly journals Fault Diagnosis of Sensors for T-type Three-Level Inverter-fed Dual Three-Phase Permanent Magnet Synchronous Motor Drives

2019 ◽  
Vol 4 (1) ◽  
pp. 167-178
Author(s):  
Xueqing Wang ◽  
Zheng Wang ◽  
Wei Wang ◽  
Ming Cheng
Keyword(s):  
Fault Diagnosis ◽  
Permanent Magnet ◽  
Permanent Magnet Synchronous Motor ◽  
Voltage Sensor ◽  
Current Sensor ◽  
Sensor Faults ◽  
Sensor Fault ◽  
Voltage Difference ◽  
Speed Sensor ◽  
Three Phase

AbstractTo improve the reliability of motor system, this paper investigates the sensor fault diagnosis methods for T-type inverter-fed dual three-phase permanent magnet synchronous motor (PMSM) drives. Generally, a T-type three-level inverter-fed dual three-phase motor drive utilizes four phase-current sensors, two direct current (DC)-link voltage sensors and one speed sensor. A series of diagnostic methods have been comprehensively proposed for the three types of sensor faults. Both the sudden error change and gradual error change of sensor faults are considered. Firstly, the diagnosis of speed sensor fault was achieved by monitoring the error between the rotating speed of stator flux and the value from speed sensor. Secondly, the large high-frequency voltage ripple of voltage difference between the estimated voltage and the reference voltage was used to identify the voltage sensor faults, and the faulty voltage sensor was determined according to the deviation of voltage difference. Thirdly, the abnormal current amplitude on harmonic subspace was adopted to identify the current sensor faults, and the faulty current sensor was located by distinguishing the current trajectory on harmonic subspace. The experiments have been taken on a laboratory prototype to verify the effectiveness of the proposed fault diagnosis schemes.

scholarly journals A Random Forest and Current Fault Texture Feature–Based Method for Current Sensor Fault Diagnosis in Three-Phase PWM VSR

2021 ◽  
Vol 9 ◽  
Author(s):  
Lei Kou ◽  
Xiao-dong Gong ◽  
Yi Zheng ◽  
Xiu-hui Ni ◽  
Yang Li ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Random Forest ◽  
Texture Feature ◽  
Texture Features ◽  
Current Sensor ◽  
Stable Operation ◽  
Sensor Faults ◽  
Sensor Fault ◽  
Three Phase ◽  
Feature Based

Three-phase PWM voltage-source rectifier (VSR) systems have been widely used in various energy conversion systems, where current sensors are the key component for state monitoring and system control. The current sensor faults may bring hidden danger or damage to the whole system; therefore, this paper proposed a random forest (RF) and current fault texture feature–based method for current sensor fault diagnosis in three-phase PWM VSR systems. First, the three-phase alternating currents (ACs) of the three-phase PWM VSR are collected to extract the current fault texture features, and no additional hardware sensors are needed to avoid causing additional unstable factors. Then, the current fault texture features are adopted to train the random forest current sensor fault detection and diagnosis (CSFDD) classifier, which is a data-driven CSFDD classifier. Finally, the effectiveness of the proposed method is verified by simulation experiments. The result shows that the current sensor faults can be detected and located successfully and that it can effectively provide fault locations for maintenance personnel to keep the stable operation of the whole system.

scholarly journals Faults diagnosis in stator windings of high speed solid rotor induction motors using fuzzy neural network

2021 ◽  
Vol 12 (1) ◽  
pp. 597
Author(s):  
Ahmed Thamer Radhi ◽  
Wael Hussein Zayer
Keyword(s):  
Neural Network ◽  
Equivalent Circuit ◽  
High Speed ◽  
Fuzzy Neural Network ◽  
Induction Motors ◽  
Stator Winding ◽  
Three Phase ◽  
Fuzzy Neural ◽  
Diagnosis Method ◽  
Faults Diagnosis

The paper deals with faults diagnosis method proposed to detect the inter-turn and turn to earth short circuit in stator winding of three-phase high-speed solid rotor induction motors. This method based on negative sequence current of motor and fuzzy neural network algorithm. On the basis of analysis of 2-D electromagnet field in the solid rotor the rotor impedance has been derived to develop the solid rotor induction motor equivalent circuit. The motor equivalent circuit is simulated by MATLAB software to study and record the data for training and testing the proposed diagnosis method. The numerical results of proposed approach are evaluated using simulation of a three-phase high-speed solid-rotor induction motor of two-pole, 140 Hz. The results of simulation shows that the proposed diagnosis method is fast and efficient for detecting inter-turn and turn to earth faults in stator winding of high-speed solid-rotor induction motors with different faults conditions

scholarly journals Research on Mechanical Defect Detection and Diagnosis Method for GIS Equipment Based on Vibration Signal

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5507
Author(s):  
Liang He ◽  
Jie Yang ◽  
Ziwei Zhang ◽  
Zongwu Li ◽  
Dengwei Ding ◽  
...  
Keyword(s):  
Experimental Research ◽  
Detection System ◽  
Engineering Application ◽  
Vibration Signal ◽  
Signal Amplitude ◽  
Field Application ◽  
Large Current ◽  
Three Phase ◽  
Diagnosis Method ◽  
Detection And Diagnosis

Gas insulated switchgear equipment (GIS) is widely used in power system, and more attention has been paid to discharge defects than mechanical defects. However, since mechanical defects are a major cause of the failure in GIS, it is of great significance to carry out relevant research on mechanical defects. Detection and diagnosis methods of mechanical defects based on vibration signal are studied in this paper. Firstly, vibration mechanisms of GIS are analyzed. Due to structural differences between single phase insulated type GIS and three phase insulated type GIS, there are big differences in vibration mechanisms between the two types of GISs. Secondly, experimental research on mechanical defects is carried out based on a 110 kV GIS equipment and a self-developed vibration detection system; results show that mechanical defects can be diagnosed by analyzing signal amplitude, frequency spectrum and waveform distortion rate, and a large current is more beneficial for diagnosing mechanical defects. Lastly, field application has been carried out on 220 kV GIS equipment, and a poor contact defect is found, demonstrating that abnormal diagnosis can be realized by method proposed in this paper. Experimental research and field application demonstrate the feasibility and effectiveness of detection and diagnosis method for mechanical defects based on vibration signal and provide experience for subsequent engineering application.

scholarly journals The role of magnetic sensors in the hybridisation and electrification of vehicles

2019 ◽  
Author(s):  
Marc Kramb ◽  
Rolf Slatter
Keyword(s):  
Power Electronics ◽  
Causal Chain ◽  
Rogowski Coil ◽  
Magnetic Sensors ◽  
Current Sensor ◽  
Electrical Currents ◽  
Limited Bandwidth ◽  
Switching Losses ◽  
Current Sensors ◽  
Rogowski Coils

Electrical currents need to be measured in a wide variety of different applications in the field of power electronics. However, the requirements for these measurement devices are becoming steadily more demanding regarding accuracy, size and especially bandwidth. In order to increase the power density of power electronics, as particularly important in the field of electromobility, there is a clear causal chain. Soft switching leads to higher efficiency and higher frequencies, which enable smaller dimensions for a given power output. Higher switching frequencies allow the size of magnetic components to be reduced significantly, resulting in more compact and lighter designs. This trend is now being reinforced by use of new wide bandgap semiconductor materials like silicon carbide (SiC) and gallium nitride (GaN), as their low on-resistances and low parasitic capacitances reduce switching losses. Conventional current sensor solutions, e.g. hallor shunt based sensors exhibit a limited bandwidth, typically less than 250 kHz. Other current sensors, like those based on the Rogowski-Coil, are capable of highly dynamic current measurement, but are significantly more expensive, larger and hence not suitable for large series applications. Furthermore, Rogowski-Coils are only capable of measuring alternating currents (AC), which prevents their use in applications where DC currents must also be measured. In order to meet the above mentioned requirements, magnetoresistive (MR) current sensors are ideally suited due to the fact that the bandwidth of the magnetoresistive effect extends up into the GHz-range. This paper describes the principle of operation and main performance characteristics of highly integrated MR current sensors and describes their benefits compared to other types of current sensor, in particular with regard to applications in the hybridisation and electrification of vehicles.

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