It has been lately shown that, traditional diagnostic approaches for rotor electrical faults detection in induction motors can be dangerously misleading. That is due to many different fault cases that mask the fault signatures thus leading to false negative alarms, or a plethora of harmless conditions that generate signatures similar to the faulty ones leading to false positive alarms. Aiming for reliable fault detection, a new trend has appeared, that of the analysis of the stator current at start-up of the motor. This method proves to be reliable in many cases however there are still cases where it can lead to false positive alarms especially when applied on motors by diagnostic engineers for the first time. Aiming for a more reliable approach, a new method is proposed in this paper. The proposed novel method consists of the analysis of the zero-sequence current under transient motor operation and specifically the start-up. The paper's findings demonstrate the method's reliability and superiority over the analysis of a single current.

This paper presents the study of magnetic bearings regarding a linear model. Initially, the advantages of magnetic bearings are referenced, in relation to the existing technology. Subsequently, the linearized model of the system is presented and the need for closed loop and control of the system is clarified. This need leads to further analysis of linear controllers like P, I, D, PI, PD, and PID. For each of them, the stability of closed loop system is studied, using the characteristic equation of the system and the Routh-Hurwitz criterion. To this end, the boundary conditions for the existence of the stability of each of them are found and presented. After finding the controllers’ characteristic parameters which could provide stability to the system, simulation tests with existence of white noise follow. Finally, the proposed PID controller performance is examined, based on existing laboratory data, and results concerning the stability of this controller are presented.

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.

Electric propulsion systems are today widely applied in modern ships, including transport ships and warships. The ship of the future will be fully electric, and not only its propulsion system but also all the other services will depend on electric power. The robust and reliable operation of the ship’s power system is essential. In this work, a review on the mechanical and electrical faults of electric machines that are used in electric ships is presented.

Conventional diagnostic methods applied to industrial induction motors, such as the Motor Current Signature Analysis, may lead to false-negative diagnostic outcomes in several cases. Such a case consists of the non-adjacent rotor breakages occurrence. Various alternatives with advanced digital signal processing algorithms have been proposed that concern the monitoring and analysis of the stator current, or the stray magnetic flux, of the motor during the transient start-up. Those methods work efficiently in most cases; however, the real issue is that most large industrial motors have very few start-ups during their long operating life time. In that sense, it is not feasible to implement the transient analysis-based methods. This paper addresses an alternative methodology that solves this issue for induction motors at steady state. The method relies on a two-stage signal processing technique for frequency information tracking and extraction, where the higher harmonic index of the motors torque around the sixth harmonic is evaluated during each stage. By the results of the method, it is evident that the fault and its severity level can be reliably detected at the steady state. The methods efficacy is proven valid even for challenging cases of large industrial motors, where the likelihood of a false diagnostic decision is increased during the signature screening.

A new method for detecting demagnetization faults in axial flux permanent magnet synchronous wind generators is presented in this study. Demagnetization faults occur in the case of total or partial loss of the magnetic properties of one or more permanent magnets of the machine. Fault signatures appearing in the current or voltage signal due to a demagnetization fault can often be confused with those produced by eccentricity faults, making the discrimination between the two types of faults difficult. The proposed methodology is based on the analysis of the instant power spectrum of the generator, combined with an estimator to derive the permanent magnet flux, based on the machine equations. Short-Time Fourier Transform is proposed as the means for spectrum analysis to ensure performance during variations of the generator speed. Results derived from the experimental tests are presented, which show that the proposed methodology is capable of detecting demagnetization faults and distinguishing them from eccentricity ones under a wide variety of operating conditions.