## 1 Introduction  
Currently, there are more than 300 million electric motors worldwide, which account for nearly 40% of global electricity demand [1]. Their maintenance accounts for a significant percentage of production costs: in the petrochemical industry alone, it is estimated that maintenance costs represent between 15% and 40% of the total production cost [2]. More specifically, the costs associated with maintenance depend on its nature, as indicated in industrial surveys [3, 4, 5, 6], with predictive maintenance having the best cost-benefit. However, many industries still rely on preventive and corrective maintenance, considering the challenges and initial costs related to the development of technology for frequent monitoring/testing of the equipment and the creation of algorithms for early problem detection [7]. In some industries, it is often assumed that common faults can be readily detected through basic diagnostics, following a preventive maintenance strategy [8]. In contrast, many major electromagnetic and mechanical faults are not easily detectable and are triggered by earlier non-destructive phenomena [9; 10; 11]. These earlier indicators are difficult to detect using simple monitoring metrics but can be easily detected with the appropriate diagnostic technique. Moreover, several factors could influence the invisibility of faults and the lack of influence on the machine performance metrics: the type of fault, machine topology, and dimensions, among other parameters [12]. The above is particularly relevant for low-speed high-torque (LSHT) machines, which are less susceptible to excessive vibration due to their operating speed [13] and robust mechanical response. LSHT applications have been dominated by permanent magnet synchronous machines (PMSMs, shown in Figure 1a), given their high torque density, efficiency, and power factor [14; 15; 16]. Nonetheless, and emanating from rare-earth dependance concerns, increased attention has been brought to improving the performance of alternative LSHT drive systems used in industrial applications. Among them, high-pole-count induction motors (IMs, presented in Figure 1b) have been investigated, offering moderate performance [17; 18], as well as synchronous reluctance machines (SynRMs, sketched in Figure 1c) [19], providing high efficiency but a poor power factor. In these machines, the combination of low speed, high inertia, and high torque levels constitutes a critical application for advanced diagnosis techniques. In this regard, there is an opportunity to showcase the actual effects of the usual faults in the performance of LSHT machines, an area that has not been extensively addressed in the literature. In contrast, several studies have focused on modeling and analyzing the impact of faults in conventional low-pole-count PMSMs [20; 21; 22], SynRMs [23; 24; 25], and IMs [26; 27; 28; 29], while related research on LSHT machines remains limited. Some literature addresses the impact of the usual faults on LSHT machines, particularly for large wound rotor synchronous generators (WRSGs) [30; 31; 32]. However, there is limited research on other LSHT machine topologies such as PMSMs, and there is a lack of studies on LSHT IMs and SynRMs. The existing literature on LSHT PMSMs primarily focuses on the impact of eccentricity faults in high-pole-count radial flux (RF) PMSMs [33], axial flux (AF) PMSMs [34; 35], and PMSMs with tooth-coil winding (TCW) [36]. Also, partial demagnetization has been analyzed [37]. In [33], an eight-pole and a twenty-four-pole PMSM were evaluated in the presence of rotor eccentricity. The results showed little  
Figure 1: LSHT machines in 3D sketches: (**a**) example of LSHT PMSM with 14 poles; (**b**) example of LSHT SICM with 16 poles; (**c**) example of LSHT SynRM with 16 poles. The three-phase windings are highlighted in red, green, and blue for phases A, B, and C, respectively. difference in the magnitudes of the new components introduced by the static and dynamic eccentricity for the same machine.