High-resistance Connection Fault Research Articles

High-Resistance Connection Fault Diagnosis in Ship Electric Propulsion System Using Res-CBDNN

The fault detection and diagnosis of a ship’s electric propulsion system is of great significance to the reliability and safety of large modern ships. The traditional fault diagnosis method based on mathematical models and expert knowledge is limited by the difficulty of establishing an accurate model of the complex system, and it is easy to cause false alarms. Data-driven methods, such as deep learning, can automatically learn from the mass of data, extract and analyze fault characteristics, and create a more objective distinction system state. A deep learning fault diagnosis model based on ResNet feature extraction capability and bidirectional long-term memory network timing processing capability is proposed to realize fault diagnosis of high resistance connections in ship electric propulsion systems. The results show that the res-convolutional BiLSTM deep neural network (Res-CBDNN) can fully integrate the advantages of the two networks, efficiently process fault current data, and achieve high-performance fault diagnosis. The accuracy of Res-CBDNN can be kept above 85% in a noisy environment, and it can effectively monitor the high resistance connection fault of ship electric propulsion systems.

High-Resistance Connection Fault Diagnosis of SRM Based on Multisensor Calibrated Transformer With Shifted Windows

High-Resistance Connection Fault Diagnosis of SRM Based on Multisensor Calibrated Transformer With Shifted Windows

High-Resistance Connection Diagnosis of Doubly Fed Induction Generators

The high resistance connection fault of the stator is a common fault in doubly fed induction generators, which causes a three-phase imbalance in the stator circuit. Since the stator winding is directly connected to the power grid, interference from the asymmetric power grid must be eliminated in order to achieve the accurate diagnosis of stator resistance imbalance faults. Therefore, a new diagnosis method based on filter shunt capacitor banks is proposed in this paper. By introducing shunt capacitor banks, an artificial neutral point is constructed to replace the neutral point of the power grid. Then, the neutral point voltage of the stator winding relative to the artificial neutral point is selected as a fault characteristic signal. In this paper, the change in three-phase stator currents after a high-resistance connection fault is analyzed in detail, and by comparing the fault characteristic signal with three-phase stator currents, the fault phase location and fault severity of high-resistance connection can be accurately obtained. Finally, simulations are carried out via the field-circuit coupling method to validate the effectiveness of the proposed method.

Deadbeat Fault-Tolerant Control Scheme for Dual Three-Phase PMSG With High-Resistance Connection Fault

This article proposes a current deadbeat-based fault-tolerant control scheme for a dual three-phase permanent magnet synchronous generator with a high-resistance connection (HRC) fault. First, the voltage deviation caused by the HRC fault is deduced, and the postfault prediction model is established. Then, the instantaneous active power and reactive power are analyzed considering the negative-sequence voltage and current. To eliminate the fluctuation components and improve the steady-state performance, the fault-tolerant current references are designed under the condition of HRC fault. The deadbeat principle is employed to track the periodic <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> current references accurately. The two targets of eliminating output power fluctuations and stabilizing electromagnetic torque are achieved. Finally, the virtual voltage vectors are synthesized to generate the reference voltage and suppress the harmonic current. The proposed method effectively restrains the fluctuations of active power, reactive power, dc-link voltage, and electromagnetic torque. The experimental results verify the effectiveness of the proposed method.

An Inequality Indicator for High-Resistance Connection Fault Diagnosis in Marine Current Turbine

Marine current energy is an abundant renewable energy resource. Marine current turbines (MCTs) can convert the kinetic energy of marine currents into electrical energy. However, the variations in the marine currents are violent and complex. These characteristics will be reflected in the variation in the operating condition of MCTs, thus interfering with normal diagnosis for the high-resistance connection (HRC). The HRC can be caused by damaged connections between device components that are easily made due to the harsh marine environment. To diagnose HRC in MCT, an inequality indicator is proposed to quantify the current imbalance caused by HRC. The inequality indicator is defined based on the arithmetic–geometric mean inequality and can identify slight current imbalances in the early stages of HRC. The inequality indicator is robust to the variable operating conditions of the permanent magnet synchronous machine (PMSM) in the MCT. Experimental results show that the inequality indicator can be used to effectively diagnose HRC in the MCT with 100% accuracy. This research will help maintain the health condition of the MCTs and provide some ideas for diagnosis in MCTs. Moreover, the inequality indicator may provide a different approach to the analysis for other faults that can lead to a current imbalance.

Detection and Discrimination of Interturn Fault and High-Resistance Connection Fault in PMSM Based on Deviation Angle of Zero Sequence Voltage

Detection and Discrimination of Interturn Fault and High-Resistance Connection Fault in PMSM Based on Deviation Angle of Zero Sequence Voltage

Mitigation of high-resistance connection in surface-mounted PMSM drive system based on model predictive current control

High-resistance connection fault can result in the increasing of power loss and the rise of heat, so the electric machine drive system possibly can be damaged. Therefore, to reduce the copper loss caused by high-resistance connection in surface mounted permanent magnet synchronous machine drive system, a method to minimize the copper loss based on the model predictive current control is shown in this paper. First, the permanent magnet synchronous machine model is deduced under high-resistance connection fault condition. Then, the direct axis current is deduced to minimize the copper loss. Next, the predictive model of permanent magnet synchronous machine is deduced under fault condition, and the cost function is defined to select the optimal voltage vector. Finally, the proposed model predictive current control strategy is realized to minimize the copper loss. And the effectiveness of this method is verified through the simulation and experiment. According to the results of the simulation and experiment, the proposed model predictive current control method has the same performance as the traditional model predictive current control method, as well as can reduce the copper loss effectively.

High-Resistance Connection Diagnosis in Five-Phase PMSMs Based on the Method of Magnetic Field Pendulous Oscillation and Symmetrical Components

An online approach for diagnosing high-resistance connection (HRC) faults in five-phase permanent magnet synchronous motor drives is presented in this article. The development of this approach is based on a so-called “magnetic field pendulous oscillation (MFPO)” technique and symmetrical components method. Under HRC fault condition, a “swing-like” MFPO phenomenon is observed compared to the healthy condition. Furthermore, with the extracted current features in symmetrical components domain, different HRC fault types are successfully identified and distinguished. These fault types include single-phase faults, e.g., HRC fault in phase-A; two-phase nonadjacent faults, e.g., HRC fault in phase-A&C; and two-phase adjacent faults, e.g., HRC fault in phase-A&B. Meanwhile, the localization of the faulty phase/phases is also accomplished, and the fault severity is estimated. In this approach, only sensing of the phase currents is needed. Hence, the implementation cost is very low since the sensory data of the currents are typically already available in the closed-loop vector-controlled drives for control purpose and no additional sensors or related signal conditioning circuits are required. The effectiveness of the presented diagnostic approach is verified by simulations and experimental results.

Fault-Tolerant Control Strategy for Five-Phase PMSM Drive System With High-Resistance Connection

High-resistance connection (HRC) fault can result in increased copper loss, thus possibly causing damage to the electric machine drive system. Therefore, a fault-tolerant control strategy is proposed for a five-phase permanent magnet synchronous machine drive system with HRC to minimize the copper loss. The fault-tolerant control strategy is realized based on the magnetomotive force invariance principle and copper loss minimization principle. The simulation and experiment are carried out to quantitatively validate the effectiveness of the proposed fault-tolerant control strategy. Both the simulation and experimental results show that the proposed strategy can effectively reduce the copper loss caused by the HRC fault.

High-Frequency Voltage Injection Based Stator Interturn Fault Detection in Permanent Magnet Machines

An interturn short-circuit fault in the stator winding of an electric machine, denoted as turn fault, has been recognized as one of the most severe faults in permanent magnet machines, which require a swift and reliable detection, in order to implement appropriate mitigations. The asymmetry brought by a turn fault is widely used for fault detection. However, similar features also emerge in a less severe high-resistance connection (HRC) fault, which may lead to an incorrect fault identification. In this article, a more exclusive turn fault detection method with the ability to differentiate from the HRC fault is proposed. It injects high-frequency square-wave voltage signals and makes use of the difference in the high-frequency impedance under the two fault conditions. The sensitivity to the HRC fault is largely reduced. The proposed turn fault indicator is independent of the operating conditions and robust with respect to state transients. This method is validated in a fault-tolerant permanent magnet assisted synchronous reluctance machine drive.

A Two-Step Strategy for Online Fault Detection of High-Resistance Connection in BLDC Motor

High-resistance connection (HRC) is one of the common stator faults in motors. The HRC fault detection method for brushless direct current motors (BLDCMs) has not been reported yet. This study proposes a two-step strategy for the detection, localization, and evaluation of HRC fault in a BLDCM. In the first step, the zero sequence voltage component (ZSVC) of the motor is acquired and analyzed, and the HRC fault can be detected from the amplitude of the fundamental frequency component of the ZSVC spectrum. In the second step, once the HRC fault has been detected, three indicators are calculated from the ZSVC and three-phase currents to localize the fault phase. The resistance value of the HRC is then calculated. Theoretical, simulated, and experimental analyses have been performed, and the results of them are consistent with one another, thereby validating the effectiveness of the proposed strategy. Both the HRC fault detection algorithm and the motor control algorithm are implemented on a single microcontroller unit in real time, which makes the proposed strategy efficient and flexible in industrial applications.

A DC-Flux-Injection Method for Fault Diagnosis of High-Resistance Connection in Direct-Torque-Controlled PMSM Drive System

This paper proposes a dc-flux-injection method for fault diagnosis of high-resistance connection (HRC) in a direct-torque-controlled permanent magnet synchronous machine (PMSM) drive system. In this method, the flux linkage bias is superimposed in the flux control loop of the direct torque control system, and then the dc current offset is excited in the stator windings. By superimposing two different pairs of flux linkage biases, a binary linear equation group about the resistance deviations can be established based on the stator currents and zero-sequence voltage component. By solving the equation group, the resistance deviations can be calculated for the HRC fault detection, faulty phase location, and fault severity estimation. Both the simulation and experimental results validate the effectiveness of the proposed method. In addition, the proposed method is immune to the symmetrical variations of stator resistance and interturn fault of the PMSM.

Detection and Classification of Turn Fault and High Resistance Connection Fault in Permanent Magnet Machines Based on Zero Sequence Voltage

Health monitoring and fault detection are becoming more and more important in electrical machine systems due to the increasing demand for reliability. Winding turn fault is a common fault in permanent magnet (PM) machines, which can cause severe damages and requires prompt detection and mitigation. High resistance connection fault, which results in phase asymmetry may also occur but does not require immediate shutdown. Thus, apart from the fault detection, the classification between the two faults is also required. In this paper, a new technique for detecting and classifying turn fault and HRC fault by utilizing both the high and low frequency components of the zero sequence voltage is proposed with the enhanced sensitivity. The dependence on the operating conditions is minimized with the proposed fault indicators. The effectiveness of fault detection and classification has been verified by extensive experimental tests on a triple redundant fault tolerant PM assisted synchronous reluctance machine. The robustness of the turn fault detection in transient states and under no load conditions has also been demonstrated.

Detection and classification of turn fault and high‐resistance connection fault in inverter‐fed permanent magnet machines based on high‐frequency signals

Winding turn fault and high-resistance connection (HRC) fault will lead to different consequences and require different mitigation actions. In this study, the differentiating features between a turn fault and HRC fault are analysed and compared in a three-phase surface-mounted permanent magnet machine fed by the inverter with pulse-width-modulation voltages. The resultant high-frequency components in both voltages and currents are utilised for the fault detection and classification based on the high-frequency impedance and ripple current, without requiring modifications to the machine or interface design. Extensive simulations show that this method is capable of fault detection and classification in both transient and steady-state operations.

Research on Vector Control Strategy of Surface-mounted Permanent Magnet Synchronous Machine Drive System with High-Resistance Connection

High-resistance connection (HRC) is a common electrical fault for the electric machine drive system. This fault can lead to the increased power loss and heat, thus possibly causing the damage of the electric machine drive system due to the excessive temperature. Hence, this paper first proposes a vector control strategy of the surface-mounted permanent magnet synchronous machine (PMSM) drive system with the HRC fault to minimize the copper loss. The mathematical model of the PMSM with the HRC is presented in abc stationary frame. The function relationship between the copper loss and the direct axis current, quadrature axis current, stator resistance, and the additional resistance due to the HRC is established and analyzed. The expression of the direct axis current, which minimizes the copper loss, is deduced under the condition of the HRC in one phase and two phases. Consequently, the proposed vector control strategy for the surface-mounted PMSM driving system is achieved. Both the simulation and experimental results show that the proposed method not only preserves the performance of the conventional vector control method, but also can effectively reduce the copper loss, thus protecting the PMSM from the damage due to the increased temperature possibly caused by the HRC fault.

Quantitative Fault Severity Estimation for High-Resistance Connection in PMSM Drive System

In this paper, a fault severity estimation method is presented for high-resistance connection (HRC) in a permanent magnet synchronous machine drive system, being dependent upon the zero sequence voltage component (ZSVC) and stator currents. According to the relationship between the stator current, ZSVC and resistance deviations, a bivariate quadratic equation group is established with regard to the resistance deviations caused by HRC. The resistance deviations are obtained by solving the equation group. Based on the obtained resistance deviations, not only the fault is diagnosed and the faulty phase is identified, but also the HRC fault severity is estimated. Both the simulation and experiment are studied to validate the fault severity estimation method. The results verify the effectiveness and robustness of the proposed fault severity estimation method.

Fault Diagnosis of High-Resistance Connection in a Nine-Phase Flux-Switching Permanent-Magnet Machine Considering the Neutral-Point Connection Model

This paper presents a fault diagnosis technique for high-resistance connection (HRC) in a nine-phase flux-switching permanent-magnet (FSPM) machine based on zero-sequence voltage components (ZSVC), where the neutral-point connection mode is considered. A nine-phase FSPM machine topology is first introduced and no-load back electromotive force waveforms are analyzed. Moreover, the topologies of the nine-phase FSPM drive with different neutral-point connection modes are studied. Then, the mathematical model of a nine-phase FSPM machine with HRC is established with the consideration of the neutral-point connection mode and then the influence of the HRC on the ZSVC is analyzed based on the established model. It is shown that the HRC may be diagnosed by monitoring the change of the spectral contents of the ZSVC. Furthermore, this paper focuses on the situation of the nine-phase FSPM machine with one neutral point. In this case, to remove the influence of the FSPM machine operating point, an effective fault indicator is defined and used for HRC fault detection. Finally, the simulation and the experiment are carried out to validate the proposed method. Both the results show that the proposed method can be applied for the HRC fault diagnosis in a nine-phase FSPM machine.