The limitations of the thermal, vibration, or electrical monitoring of electric machines such as false indications, low sensitivity, and difficulty of fault interpretation have recently been exposed. This has led to a shift in the direction in research toward applying new techniques for improving the reliability of condition monitoring. With the changing environment, the purpose of this article is to provide an overview of the recent trends in the industrial demand and research activity in condition monitoring technology. The new developments in insulation testing, electrical testing, flux analysis, transient analysis, and fault prognostics are summarized. The challenges and recommendations for future work for the new technologies are also explored to help support target research and development efforts according to industrial needs.

Permanent magnet synchronous machines (PMSMs) work with controllers and controller parameters affect the machine's voltages and currents and thus the diagnosis of stator winding fault. One such parameter is the current controller bandwidth that affects the harmonic content in these signals. In the literature, the 2nd harmonics in both dq-axis currents and voltages have been used for fault detection, and the main advantage is that inter-turn short-circuit (ITSC) winding fault with a few shorted turns, specially one turn, can be detected. One indicator that combines the fault information in voltages and currents is the instantaneous reactive power (IRP). However, it has been shown that IRP does not perform robustly with respect to current controller bandwidth. The main contribution of this work is that it proposes and validates a new mathematical function for ITSCs detection, Rayleigh quotient, which combines the fault information present in voltages and currents to make ITSCs detection robust to current controller bandwidth. The validations from both co-simulation and experiment show that the proposed method is robust to the bandwidth and can detect ITSC faults faster than IRP.

A significant portion of faults experienced by electrical machines are caused by degraded insulation. In order to reduce the effects of a failure, it is important to monitor the health of the insulation, preferably while the machine continues operation and without expensive equipment. In this paper, an online method to calculate the remaining useful lifetime (RUL) of stator insulation with simple equipment is proposed. Accelerated lifetime testing was performed by exposing the stator of an electric machine to high temperatures. An Extended Kalman Filter algorithm is developed to calculate the RUL. A simple analog circuit is used to show how lower sampling rates can be used to capture the necessary information for prognosis. With this circuit, the same trend used to provide a prognosis for the insulation can be measured online without using expensive or special technology.

Control of the speed as well as shaping the speed transient response of a surface-mounted permanent magnet synchronous motor (PMSM) is achieved using the method of feedback linearization and extended high-gain observer. To recover the performance of feedback linearization, an extended high-gain observer is utilized to estimate both the speed of the motor and the disturbance present in the system. The observer is designed based on a reduced model of the PMSM, which is realized through the application of singular perturbation theory. The motor parameters are assumed uncertain and we only assume knowledge of their nominal values. The external load torque is also assumed to be unknown and time-varying, but bounded. Stability analysis of the output feedback system is given. Experimental results confirm the performance and robustness of the proposed controller and compare it to the cascaded proportional integral (PI) speed controller.

Incipient interturn short-circuits (ITSCs) in permanent-magnet synchronous machines (PMSMs) develop to direct short-circuit without proper mitigation. This article proposes an ITSC mitigation control for standard three-phase interior PMSMs (IPMSMs) driven by typical three-phase inverters, named as maximum torque per circulating current (MTPCC), to constrain the circulating current (CC) due to ITSC within acceptable limits so as to delay the insulation degradation between shorted turns, and to maximize output torque to support the postfault performance. In the $dq$ current plane, it is shown that for a specific fault severity and machine speed, the operating points with the same CC form a circle, and for constant torque with ITSC is a hyperbola. ITSC is a fast-developing fault that implies the fault severity continues to increase with time, and the positions of the CC circle and torque hyperbola change with the increasing fault severity in the $dq$ current plane. The MTPCC control updates the mitigation operating point automatically, depending on the positions of the CC circle and torque hyperbola with respect to the circle of the machine's maximum current, to produce the maximum possible torque as the fault severity changes, which shows that it is adaptive to the variation of fault severity. The proposed mitigation control is validated through experiments.

This paper compares the detection methods of static eccentricity in Interior Permanent Magnet Synchronous Machines (IPMSM). Four methods are discussed: The first method uses shift in the voltages in d–q plane to detect fault. The second method uses shift in peak of the incremental inductance curve for fault detection. The third method uses the combined information of harmonics present both in current and voltage to detect the fault. This makes the detection robust with respect to current controller bandwidth. Finally, the fourth method used for detection includes measuring vibrations using accelerometers. It is shown that all four methods detected static eccentricity. These methods are compared on the basis of utility of fault detection under online or offline conditions and under saturated conditions. For all four methods the machine was tested at healthy, 25% and 50% static eccentricity levels. Two-dimensional (2-D) Finite element analysis was used for simulating machine under healthy and faulty cases. The experiments were performed by controlling the machine using Labview Real-time.