Rotor eccentricity and local demagnetization in permanent magnet synchronous motors (PMSMs) increases unbalanced magnetic pull and motor vibration resulting in accelerated aging of motor components. If the asymmetry in the rotor remains undetected, it can increase in severity, and increase the risk of stator-rotor contact, which causes forced outage of the motor and driven process. Detection of PMSM rotor asymmetry currently relies on off-line testing and on-line vibration/current spectrum analysis. However, they are inconvenient or cannot provide reliable detection as they are influenced by other mechanical non-idealities in the motor or load. In this paper, the feasibility of using the signals from analog Hall-effect field sensors for detecting eccentricity and local demagnetization is investigated. It is shown that Hall sensors present in machines for motion control can be used for measuring the variation in the flux inside the motor due to rotor magnetic asymmetry with minimal or no hardware modifications. 3-dimensional (3D) finite element analysis (FEA) and experimental results performed on an interior PMSM (IPMSM) show that the proposed method can provide sensitive and reliable detection of dynamic/mixed eccentricity and local PM demagnetization.

On-line monitoring and diagnostics of permanent magnet synchronous motors (PMSM) is becoming important with the increasing demand in PMSM applications. Most of the research effort focuses on motor current signature analysis (MCSA) as it can provide remote, on-line monitoring at low cost. However, all types of defects that produce asymmetries in the PMSM rotor or load produce identical rotor rotational frequency components. This is a serious limitation when applying MCSA since it can produce false indications and degrade the sensitivity of fault detection. The requirement of complex time-frequency analysis techniques is another limitation of MCSA for applications with speed variations. In this paper, the feasibility of using analog Hall sensor signals to complement MCSA for detection and classification of rotor and load related defects is investigated. It is shown that Hall sensors installed in machines for initial rotor position estimation can be used with minimal hardware modifications, to detect and classify signatures produced by the rotor and load for cases where MCSA fails, even during transient conditions. Experimental testing performed on an IPMSM under eccentricity, local demagnetization, and load unbalance conditions show that the reliability and sensitivity of fault detection in PMSM systems can be improved at low added cost.

There has been active research in fault diagnosis of permanent magnet synchronous motors (PMSMs) with the recent increase in reliability-critical PMSM applications. Most of the research efforts are focused on the motor current signature analysis (MCSA), as it allows remote online detection of the rotor and load defects using the current measurement available in the drive. A critical limitation of MCSA or vibration analysis is their inability to distinguish the type of rotor or load defect. It is crucial for the maintenance engineer to identify the type of defect since the course of action for continued operation differs depending on the fault. In this letter, a simple automated test method for identifying mass unbalance using vibration measurement commonly available in motor drive systems is proposed. The effectiveness of the proposed method is verified on a PMSM under emulated PM demagnetization, dynamic eccentricity, and mass unbalance conditions.

Permanent magnet synchronous machines (PMSMs) torque production capability depends on the permanent magnets (PMs) magnetization state, which can be affected by PMs temperature and of the current flowing throughout the stator windings; knowledge of the PMs temperature can be therefore of great importance both for control and monitoring purposes. PMs temperature can be measured or estimated; PM temperature measurement is not easy and is not normally implemented in commercial drives. PM temperature estimation methods can be divided into thermal models based, BEMF based and signal injection based methods. Existing HF signal injection methods estimate the PM temperature from the measured stator HF resistance. Unfortunately the resistance is also affected by magnetoresistive effect, which can limit the accuracy of the estimates. This paper proposes the use of the stator d-axis HF inductance for PM temperature estimation. This makes temperature estimation insensitive to magnetoresistive effect. In addition, it allows the use of higher frequencies, reducing the adverse impact of the injected signal on machine performance.

Online detection of rotor and load faults in permanent magnet synchronous motors (PMSM) based on spectrum analysis of current or vibration is not capable of identifying the root cause of the fault, since all faults produce identical fault signatures. The sensitivity of fault detection also depends on the motor and controller design making fault detection unreliable. In addition, operation under variable frequency and load limits the effectiveness of spectrum analysis based methods. In this article, airgap flux monitoring is investigated as an alternative for providing reliable identification of rotor and load faults in PMSMs. Based on the analysis of airgap flux under partial and uniform demagnetization, dynamic eccentricity, and load unbalance, an airgap search coil voltage based method for detection and classification of the faults is proposed. The claims made in the article are verified through experimental testing on an IPMSM under emulated fault conditions along with a comparison to vibration and current spectra-based detection. It is shown that the proposed method provides reliable online identification of the faults for cases where conventional spectrum analysis based methods fail.

Torque production capability of permanent magnet synchronous machines (PMSMs) depends on the magnetization state of the permanent magnets (PMs). Electrical stress, thermal stress, or the combined effect of both can produce demagnetization of the PMs, which eventually can result in several adverse effects including decrease in the motor torque and efficiency, and increase of the torque ripple and vibration, eventually degrading the performance and reliability of the motor and drive system. A number of approaches have been proposed for detecting PM demagnetization using model-based flux estimation, signal injection, spectrum analysis of current/back-EMF; however, all these methods show limitations in terms of invasiveness, implementation cost and/or reliability of the diagnosis. In this paper, accurate PM demagnetization detection based on measurements from hall-effect sensors is proposed. Such sensors are often mounted in commercial PMSMs, the proposed method can therefore be implemented at practically no cost.