Health status detection for motor drive systems includes detecting the working status of the motor and diagnosing open-circuit (OC) faults in the inverter. This paper proposes a ...generalized-layer-added principle component analysis (GPCA) to determine the load-up/load-shedding status of a motor and diagnose faults in its inverter. Most current methods for detecting OC faults are constrained by changes in the current amplitude and frequency, potentially leading to misjudgments during load-up/load-shedding transient states. The proposed method addresses this issue. Initially, this paper employs a homogenization method to process current data, eliminating the impact of transient processes during motor load-up/load-shedding states on inverter fault diagnosis. Subsequently, the fast Fourier transform (FFT) is used to extract the frequency domain characteristics of the data. If the PCA method is trained with a singular matrix, this can lead to an unreliable result. This paper introduces a generalization layer based on the PCA method, leading to the GPCA method, which enables training with singular matrices. The GPCA method is then developed to compute data features. By presetting thresholds and utilizing the prediction error value and contribution rate index of the GPCA method, the relevant state of the motor drive system can be determined. Finally, through simulations and experiments, it has been demonstrated that the method, using data from the stable working state, can effectively detect the working status of a motor and diagnose OC faults in its inverter, with a diagnostic time of 0.05 current cycles.
This paper proposes a power switch open-circuit (OC) fault diagnosis method for a motor drive inverter system. This method utilizes adjacent trend lines to extract fault features from the current ...vector trajectory, enabling rapid fault diagnosis and localization. Firstly, the current vector trajectory is obtained by applying the Clark transformation to the three-phase currents, and trend line slopes are calculated using equidistant current signal nodes. Subsequently, the method determines fault by calculating changes in adjacent trend line slopes and quickly locates the faulty power switch by considering the average slope of adjacent trend lines and the beta-axis current direction in the alpha–beta coordinate system. Accurate OC fault localization can be achieved with just a few trend line data points calculated in each current cycle, reducing the extra hardware and computational burden. This method is not only suitable for load variations but also applicable to the diagnosis of both single-switch and multiple-switch faults. Finally, simulation and experimental results validate the effectiveness and robustness of the method.
Voltage source converters have been used in high voltage direction current systems, which provides various advantages such as reduction in installation cost and space, easy connectivity with ...renewable energy sources and enhanced power quality. One of the most important issues is how to ride through the grid faults to ensure the stability operation of voltage source converters. In practice, however, there are practical considerations of physical restrictions such as the linear stability operating boundary, beyond which the current would be distorted, even the system would be instable. In this paper, a quantitative analysis and evaluation of the linear stability operating boundary is presented for operating the voltage source converter under grid faults. The proposed method indicates that the operating boundary mainly depends on the circuit parameters and control strategies. Simulation results have provided to verify the proposed quantitative analysis and control strategy. It is expected to provide a useful guidance for designing and controlling the voltage source converter within the linear stability operating boundary, which enhances the system and increased the reliability of the system.
The conventional Si-based semiconductors suffer from low switching frequency, high conduction loss and low efficiency. These shortcomings hinder the improvement of power electronic power converter ...performance. An attractive solution is to replace Si-based semiconductor devices with the wide-bandgap semiconductors based on gallium-nitride material. In terms of the step-down converters which are used for hydrogen energy systems, it is difficult for the traditional buck circuit to eliminate the output current ripple and achieve fault-tolerant operation. Therefore, topologies of the step-down power converter also need improvement. In this paper, a GaN-based step-down power converter and control strategy for hydrogen energy systems is presented. Firstly, the mathematical analysis of the conventional buck converter is done to clarify why it has limitations regarding the reliability and current ripple. Another alternative solution is discussed but still suffers from ripples. In order to eliminate the current ripple and enhance the fault-tolerant ability, a novel GaN-based solution is given and both analysis and design are provided. The current ripple can be perfectly cancelled and fault-tolerant operation can be fully achieved. The comparison is carried out with the existing solutions. The time-domain simulation tests are carried out. And the experimental prototype is established based on the enhancement mode GaN transistor. The experimental results verify the effectiveness of proposed design regarding the current ripple cancellation and dynamic performance.
Industrial data is usually nonlinear and corrupted by noise and outliers, which brings great challenges to fault detection and modeling in industrial data. To this end, L21-norm-based kernel ...principal component analysis is incorporated into the self-paced learning framework (L21-KPCA-SPL) in this study. It is innovative in sense that: (1) L21-KPCA is proposed, which can solve the nonlinear problem of data and increase the robustness of the algorithm; (2) self-paced learning (SPL) framework can avoid the local optimal solution problem caused by non-convex optimization; (3) based on the process monitoring of L21-KPCA-SPL, the pixel cumulative contribution of monitoring statistics is proposed. Compared with traditional PCA-like methods, the proposed algorithm is more robust. Compared with other robust methods, the proposed algorithm is more suitable for dealing with nonlinear data. Extensive experiments have been conducted on image classification datasets to demonstrate that the proposed method is more effective than other state-of-the-art methods. Furthermore, the proposed algorithm is used to detect ore blockage fault at the turn of conveyor belt. The experimental results further verify the effectiveness of the proposed method, which can replace the traditional manual detection and meet the requirements of real-time detection of ore blockage.
•The L21-KPCA method is proposed to solve the nonlinear problem of the data and improve the robustness of the algorithm.•L21-KPCA is incorporated into the SPL framework to avoid the local optimal solution problem caused by non-convex optimization.•Based on the process monitoring of the L21-KPCA-SPL method, the variable cumulative contribution of monitoring statistics is proposed.
In order to effectively eliminate the overlap-time effect introduced by the addition of the overlap time in the space vector modulation (SVM), an overlap-time effect elimination SVM method based on ...vector bridge extension is proposed for current source converter (CSC). This article first selects the current vector as the bridge vector according to the ac side voltage relationships, and then uses the bridge vector to add the overlap time to the other two current vectors by bridge extension method, which make the dwell time of active vector the same as the ideal dwell time and the overlap-time effect can be directly eliminated without any compensation. In addition, by rearranging the order of the vectors, the number of switching times is reduced. Thus, this method sets the overlap time within the modulation, which is different from the traditional SVMs. The output current is the same as that of the ideal SVM, which can improve the harmonic performance of currents. Finally, the simulation and experimental results show that the proposed method can effectively eliminate the overlap-time effect.
In this article, an enhanced short-horizon integration actual voltage reconstruction method based on nonlinear error inverse-compensation (NEIC-SHIVR) is proposed for voltage source inverters. The ...NEIC-SHIVR method takes into account not only the influence of nonlinear errors in modulation such as dead time addition and narrow pulses elimination on voltage reconstruction but also considers the influence of nonlinear errors in PWM transfer links such as power switch delay and switch voltage drop on voltage reconstruction. First, the real-state driving signal is computed by the output driving signal and the power switch delay time. The auxiliary driving signal is reconstructed to get the auxiliary switching state according to the phase current direction. Second, referring to the auxiliary switching states and the phase-current directions, the instantaneous equivalent bus voltage within each clock pulse is computed by the dc-bus voltage and the switch voltage drop. Finally, the output voltage within each switching period is integrated by the reconstructed instantaneous equivalent bus voltage in each clock pulse. Compared with SHIVR, NEIC-SHIVR provides a more accurate reconstructed voltage. Compared with other methods, NEIC-SHIVR inherits many advantages of SHIVR. For example, it can apply to any PWM method and does not use high-cost high-frequency voltage sensors, which improves system reliability and reduces system complexity. Simulations and experiments verify the effectiveness of the proposed method.
Unbalanced loads are general in uninterruptible power supply (UPS), standalone power generation applications and the failure mode of three-phase inverters. Three-phase four-leg inverters are a ...well-known solution to handle neutral currents caused by unbalanced loads. In four-leg inverters, three-dimensional space vector modulation (3DSVM) is widely used. However, the 3DSVM of four-leg current source inverter (CSI) has not been systematically studied so far. To fill this gap, this paper proposes a 3DSVM for CSI. The definition of the current vector, the identification of the position of reference vector and the sequence of switches are introduced. Under unbalance loads, the symmetrical load voltage can be realized, which complies with IEEE Std. 1159-2019. The output current can comply with IEEE Std. 519-2014. The proposed 3DSVM has the potential to extend the advanced modulation strategies that have been implemented/ proposed on three-leg CSI.
In order to decrease the switching loss of the auxiliary circuit of the resonant DC link (RDCL) inverter and improve the voltage utilization and system efficiency, this paper presents a new space ...vector pulse width modulation (SVPWM) method based on the zero-voltage notch of the resonant DC link inverter. This resonant DC link inverter reduces the current stress in the main circuit by paralleling auxiliary switch. And this method makes the operation of the auxiliary resonant circuit (ARC) less frequent, thus reducing the losses of the ARC and therefore improving the system efficiency. At the same time, this method analyzes and compensates for the missing voltage vectors based on the ideal output voltage, so that the inverter output voltage vector under this modulation is the same as the ideal SVPWM output voltage vector. Compared with the original modulation of RDCL inverter, this method does not change the switching sequence, the switching times, and the action time of the vector, while reducing the switching ripple. The effectiveness and feasibility of the modulation strategy is verified in the paper through theoretical analysis as well as experiments.
Industrial data are in general corrupted by noises and outliers, which do not meet the application assumptions in feature extraction. Many existing feature extraction algorithms are not robust, ...overly consider the less important features of the data, and cannot capture the key features of the data. To this end, the two-level feature extraction method (TFEM) based on l 21 -norm is proposed in this study. Compared with single-projection feature extraction algorithms, TFEM consists of two projections: the nonreduced and reduced dimensionality projections. The nonreduced dimensionality projection can remove the parts of less important features that are unrelated to the key features of the data. The reduced dimensionality projection can reduce the dimensionality of the data and further extract the features of the data. In addition, l 21 -norm is used to make the algorithm more robust. Finally, the convergence of the proposed algorithm is analyzed. Extensive experiments have been conducted on the Tennessee Eastman and Penicillin Fermentation processes to demonstrate that the proposed method is more effective than other state-of-the-art fault detection methods.
