In traction, automotive, and some industrial processes, the operation of the induction motor is set using speed. This creates an additional control loop that is external to the current controller that inverters already possess. While the impact of the latter control loop on fault detection in induction motors has already been studied, the influence of closed-loop speed control has not been explored enough. This paper presents the findings on the impact of PID speed control on the broken rotor bar fault detection. The study reveals that the constant corrective actions of the PID controller to correct the speed cause an increase in the noise level and spectral leakage around the first harmonic in the stator current spectrum that prevents fault detection. It is concluded that it is necessary to use time-frequency analysis techniques with excellent spectral resolution, such as the Dragon Transform or the Min-Norm technique.

Rotor bar breakage in induction motors is often detected by analysing the signatures in the stator current. However, due to the alteration of the current spectrum, traditional methods may fail when inverter-fed motors operate with closed-loop control using a cascade structure to regulate the speed. In this paper, the potential of zero-sequence voltage analysis to detect this fault is investigated, and a new index to quantify the severity of the fault based on this signal is proposed. Signals from motors operating under different control strategies and signals from motors powered from the mains are considered to verify the robustness of the proposed fault severity index. As a result, in all the analysed conditions the value of the proposed index for the healthy motor is found to be approximately 0.010, while for the faulty machine it is between 0.110 and 0.252.

Electric induction motors are fundamental to industry, where reliability and continuous operation are critical. Though robust, they are prone to faults, particularly in demanding environments such as highway tunnels. Non-invasive diagnostic techniques are widely used for condition monitoring, yet most studies occur under controlled laboratory conditions, limiting their applicability in real-world scenarios. This research investigates the feasibility of applying Motor Current Signature Analysis (MCSA) for monitoring highway tunnel axial fan motors, aiming to determine its effectiveness for real-time diagnostics in industrial environments. Measurements were performed under actual operating conditions, highlighting practical challenges. Data acquisition was implemented remotely from electrical cabins feeding tunnel services, reducing installation complexity and costs compared to in-tunnel measurements. This approach enabled monitoring of all motors in a tunnel using minimal hardware (a single acquisition system equipped with Rogowski sensors) making the solution cost-effective and suitable for periodic measurements. Frequency domain analysis focused on harmonics associated with rotor bar defects and eccentricity, selected for their slow degradation and diagnostic relevance. The magnitude of these harmonics was tracked over time and compared across motors of the same model. Since most of the time the ventilators are de-energized, the periodic measurements can be seen almost as a real-time monitoring, at least for the faults considered, with much lower costs. Results were validated against maintenance reports, confirming bearing faults with eccentricity in two motors, while suspected rotor porosity remained unverified, as expected at low severity. Findings demonstrate that MCSA can provide operational insights for fault detection in tunnel environments, supporting predictive maintenance strategies. A key outcome of this study was selecting and implementing an effective measurement setup for industrial applications, while preparing the base for future machine learning integration to estimate Remaining Useful Life.

The aim of this paper is twofold. On the one hand, the applicability of the well-known diagnostic techniques, based on the motor current and stray flux signature analysis, has been experimentally tested both on small single-phase induction motors and on large on-field three-phase induction motors. On the other hand, the single phasing fault in three-phase induction motors, which has rarely been treated in the literature, has been experimentally analyzed and compared to the behavior of the single-phase motor, in order to find characteristic signatures of this fault. Time and frequency domain analyses were performed on current, axial and radial stray flux, and torque signals. The experimental study highlighted the following insights: i) classical motor current signature analysis cannot be easily applied to permanent-capacitor single-phase machines; ii) stray flux analysis reveals the presence of additional harmonic sidebands, even in healthy three-phase induction motors; iii) a rough analysis of the third harmonic in the current spectrum may be sufficient to diagnose the single phasing fault.

In this work, an investigation on permanent-capacitor single-phase induction machine, healthy three-phase and three-phase induction machine in single phasing condition is presented. The study focuses on the analysis of one-phase current signal, radial and axial stray fluxes, and also torque signal for the single phasing condition. The steady state signals are initially analyzed in the time-domain and then sidebands around the supply harmonic are studied in the frequency-domain. Firstly, new insights are presented for the permanent-capacitor motor, very rarely treated in literature. Then, the presence of a significant harmonic in stray flux signals is highlighted or all machines and conditions. An investigation over a wide frequency range is also carried out proposing a new rule of thumb to locate a supply unbalanced condition looking at third and fifth harmonics. Two Low Frequency Torque Oscillation (LFTO) conditions are considered and evaluated. Finally, the derivative of the phase current is examined, and its interaction with the stray flux signals’ variations in shape and amplitude is evaluated for several conditions. Some correlations between these signals and the current derivative are found, providing interesting diagnostic insights.

Stator faults detection under normal operation is one of the most important open problems in Induction Motors (IMs): they start as Inter-Turn Faults (ITFs) and rapidly evolve into catastrophic failures, being one of the major causes of shutdown. Hence, continuous monitoring is essential for early detection. Regarding this, line current analysis is preferred due to ease of equipment installation. In this paper, a new ITF indicator is proposed: amplitude of the homopolar Rotor Slot Harmonics (RSHs); those that form a homopolar system in a symmetrical machine. These harmonics are proven as always highly sensitive, opposite to previously used RSHs, which appear as sensitive or completely insensitive, depending on the motor analyzed. It is shown how ITF detection can be reliably solved using homopolar RSHs: they dramatically rise under early ITFs. To achieve generality, a theoretical analysis is conducted to deduce which are these RSHs as a function of the number of bars per pole pairs of the IM. Moreover, the proposed approach automatically selects and detects these harmonics, and ensures robustness against load, eccentricity and voltage unbalance variations. Efficacy of this approach is confirmed through finite element simulations of three IMs covering all cases and laboratory tests.