scholarly journals Proportional-Type Sensor Fault Diagnosis Algorithm for DC/DC Boost Converters Based on Disturbance Observer

Energies ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1412
Author(s):  
Kyunghwan Choi ◽  
Kyung-Soo Kim ◽  
Seok-Kyoon Kim
Keyword(s):  
Fault Diagnosis ◽  
Disturbance Observer ◽  
Estimation Error ◽  
State Observer ◽  
Operating Conditions ◽  
Feedback Gain ◽  
Sensor Faults ◽  
Sensor Fault ◽  
Boost Converters ◽  
Diagnosis Algorithm

This study seeks an advanced sensor fault diagnosis algorithm for DC/DC boost converters governed by nonlinear dynamics with parameter and load uncertainties. The proposed algorithm is designed with a combination of proportional-type state observer and disturbance observer (DOB) without integral actions. The convergence, performance recovery and offset-free properties of the proposed algorithm are derived by analyzing the estimation error dynamics. An optimization process to assign the optimal feedback gain for the state observer is also provided. Finally, a fault diagnosis criteria is introduced to identify the location and type of sensor faults online using normalized residuals. The experimental results verify the effectiveness of the suggested technique under variable operating conditions and three types of sensor faults using a prototype 3 kW DC/DC boost converter.

scholarly journals Vibration Monitoring for Position Sensor Fault Diagnosis in Brushless DC Motor Drives

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2248
Author(s):  
Dimitrios A. Papathanasopoulos ◽  
Konstantinos N. Giannousakis ◽  
Evangelos S. Dermatas ◽  
Epaminondas D. Mitronikas
Keyword(s):  
Fault Diagnosis ◽  
Harmonic Component ◽  
Motor Drives ◽  
Brushless Dc Motor ◽  
Position Sensor ◽  
Sensor Faults ◽  
Sensor Fault ◽  
Brushless Dc ◽  
Non Invasive ◽  
Dc Motor Drives

A non-invasive technique for condition monitoring of brushless DC motor drives is proposed in this study for Hall-effect position sensor fault diagnosis. Position sensor faults affect rotor position feedback, resulting in faulty transitions, which in turn cause current fluctuations and mechanical oscillations, derating system performance and threatening life expectancy. The main concept of the proposed technique is to detect the faults using vibration signals, acquired by low-cost piezoelectric sensors. With this aim, the frequency spectrum of the piezoelectric sensor output signal is analyzed both under the healthy and faulty operating conditions to highlight the fault signature. Therefore, the second harmonic component of the vibration signal spectrum is evaluated as a reliable signature for the detection of misalignment faults, while the fourth harmonic component is investigated for the position sensor breakdown fault, considering both single and double sensor faults. As the fault signature is localized at these harmonic components, the Goertzel algorithm is promoted as an efficient tool for the harmonic analysis in a narrow frequency band. Simulation results of the system operation, under healthy and faulty conditions, are presented along with the experimental results, verifying the proposed technique performance in detecting the position sensor faults in a non-invasive manner.

scholarly journals Energy Analysis Method Based on Wavelet Transform for Sensor Fault Diagnosis

2011 ◽  
Vol 2-3 ◽  
pp. 117-122 ◽  
Author(s):  
Peng Peng Qian ◽  
Jin Guo Liu ◽  
Wei Zhang ◽  
Ying Zi Wei
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Wavelet Analysis ◽  
Energy Analysis ◽  
Sensor Faults ◽  
Analysis Method ◽  
Sensor Fault ◽  
Fault Type ◽  
Ideal Tool ◽  
Non Stationary Signal

Wavelet analysis with its unique features is very suitable for analyzing non-stationary signal, and it can also be used as an ideal tool for signal processing in fault diagnosis. The characteristics of the faults and the necessary information on the diagnosis can be constructed and extracted respectively by wavelet analysis. Though wavelet analysis is specialized in characteristics extraction, it can not determine the fault type. So this paper has proposed an energy analysis method based on wavelet transform. Experiment results show the method is very effective for sensor fault diagnosis, because it can not only detect the sensor faults, but also determine the fault type.

Fault Diagnosis Method for Network Control Systems Applying SVM Disturbance Compensation

2013 ◽  
Vol 427-429 ◽  
pp. 1799-1802
Author(s):  
Jiao Meng ◽  
Qi Hua Xu ◽  
Lei Han
Keyword(s):  
Fault Diagnosis ◽  
Estimation Error ◽  
State Observer ◽  
Network Control ◽  
Ideal Condition ◽  
Disturbance Compensation ◽  
Network Control Systems ◽  
Diagnosis Method ◽  
Short Time ◽  
Short Time Delay

According to a network control system--NCS with short time-delay and packet loss, an state observer is designed firstly in this paper to obtain a state estimation error equation which is equivalent to an asynchronous dynamical system having event incidence constraint. Secondly, SVM is used to identify interferences of the NCS. Finally, making the identification result as compensation term adding to the state observer can make the residual only represent fault term under ideal condition and increase the robustness of NCS for interference, which can improve the fault diagnosis precision. The simulation results prove that the designed observer can diagnose faults effective and the disturbance compensation based on SVM has attained the expected effect.

Signal reconstruction and disturbance observer-based fault-tolerant control for civil aircrafts

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xinjian Ma ◽  
Shiqian Liu ◽  
Huihui Cheng ◽  
Weizhi Lyu
Keyword(s):  
Flight Control ◽  
Disturbance Observer ◽  
Fault Tolerant ◽  
Signal Reconstruction ◽  
Angular Rate ◽  
Sensor Faults ◽  
Sensor Signal ◽  
Sensor Fault ◽  
Content Type ◽  
Civil Aircraft

Purpose This paper aims to focus on the sensor fault-tolerant control (FTC) for civil aircraft under exterior disturbance. Design/methodology/approach First, a three-step cubature Kalman filter (TSCKF) is designed to detect and isolate the sensor fault and to reconstruct the sensor signal. Meanwhile, a nonlinear disturbance observer (NDO) is designed for disturbance estimation. The NDO and the TSCKF are combined together and an NDO-TSCKF is proposed to solve the problem of sensor faults and bounded disturbances simultaneously. Furthermore, an FTC scheme is designed based on the nonlinear dynamic inversion (NDI) and the NDO-TSCKF. Findings The method is verified by a Cessna 172 aircraft model under bias gyro fault and constant angular rate disturbance. The proposed NDO-TSCKF has the ability of signal reconstruction and disturbance estimation. The proposed FTC scheme is also able to solve the sensor fault and disturbance simultaneously. Research limitations/implications NDO-TSCKF is the novel algorithm used in sensor signal reconstruction for aircraft. Then, disturbance observer-based FTC can improve the flight control system performances when the system with faults. Practical implications The NDO-TSCKF-based FTC scheme can be used to solve the sensor fault and exterior disturbance in flight control. For example, the bias gyro fault with constant angular rate disturbance of a civil aircraft is studied. Social implications Signal reconstruction for critical sensor faults and disturbance observer-based FTC for civil aircraft are useful in modern civil aircraft design and development. Originality/value This is the research paper studies on the signal reconstruction and FTC scheme for civil aircraft. The proposed NDO-TSCKF is better than the current reconstruction filter because the failed sensor signal can be reconstructed under disturbances. This control scheme has a better fault-tolerant capability for sensor faults and bounded disturbances than using regular NDI control.

Current Sensor Active Fault Tolerance Control Based on Feedback Gain Reconfiguration

2014 ◽  
Vol 511-512 ◽  
pp. 1012-1016 ◽  
Author(s):  
Zhi Qiang Wang ◽  
Xiao Long Li ◽  
Qing Zhen Wang
Keyword(s):  
Fault Tolerance ◽  
Fault Diagnosis ◽  
Control Strategy ◽  
Active Fault ◽  
State Observer ◽  
Current Sensor ◽  
Feedback Gain ◽  
Maglev Train ◽  
Tolerance Strategy ◽  
Tolerance Control

For the failure of current sensor on maglev train, an active fault tolerance control strategy based on feedback gain reconfiguration is proposed. Fault diagnosis unit based on state observer is designed to detect the output of current sensor, the diagnosis result is used to switch the control strategy. Simulation result indicates that the fault tolerance strategy meets the demands of the system.

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

2018 ◽  
Vol 8 (10) ◽  
pp. 1816 ◽  
Author(s):  
Zhimin Yang ◽  
Yi Chai ◽  
Hongpeng Yin ◽  
Songbing Tao
Keyword(s):  
Fault Diagnosis ◽  
Permanent Magnet ◽  
Synchronous Generator ◽  
Fault Estimation ◽  
Linear Matrix ◽  
Sensor Faults ◽  
Sensor Fault ◽  
Permanent Magnet Synchronous Generator ◽  
Multiple Sensor ◽  
Residual Generator

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.

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.

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