You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: An Overview of Fault-Diagnosis and Fault-Tolerance Techniques for Switched Reluctance Machine Systems 
Chapter Title:  3) GATE SIGNALS AUXILIARY 
1. Abstract of Cited Paper (BIB001):  A new index is introduced for eccentricity fault diagnosis in three-phase squirrel-cage induction motors. Basically, some physical quantities of the motors structure such as air gap length influence this index, while other operational factors including motor supply, control type, load level, and its fluctuation cannot affect the proposed index. The influence of various eccentricity faults upon this index is investigated and shows the segregation ability of different eccentricity types by the index. It is indicated that the change of load, speed, and saturation level can slightly change the index value. Experimental results confirm the simulation results. 
2. Abstract of Cited Paper (BIB002):  This paper proposes a new fault diagnosis method for a switched reluctance machine (SRM) drive system. The proposed fault diagnosis method is capable of detecting both open circuit and short circuit faults in the power converter switches. In addition, the position of a short fault in the asymmetric bridge converter can be detected using another proposed method. This fault occurrence can be identified in the affected motor phase. A simulation is performed with a SRM drive system, and the results are presented to verify the validity of the proposed method. 
3. Abstract of Cited Paper (BIB003):  This paper introduces new schemes for detection, isolation, and compensation of speed and current sensor (CS) faults in field oriented induction motor (IM) drives. These schemes do not use any kind of machine model and motor parameters. This is a prominent feature of the proposed approaches, which only rely on main concepts of field-oriented control (FOC)-based IM drives. Moreover, the proposed fault detection and isolation (FDI) schemes can take partial sensor failures into account. These kinds of faults that might be caused by mechanical or electrical failures, or intentional sensor tampering, are difficult to be dealt with since embedded speed and current control loops react swiftly, and inherently try to camouflage partial sensor failures. CS faults result in imbalance current flow in the motor stator phases, and speed sensor fault repudiates the orthogonally alignment of field and torque current components in field oriented IM drives. These features are cornerstones of introduced FDI methodology. Furthermore, model and parameter free compensators are proposed to recover normal operation of the machine before fault incident. After in-depth analysis, extensive simulation and experimental tests validate the proposed schemes. 
4. Abstract of Cited Paper (BIB004):  Switched reluctance motor (SRM) is a competitive solution for aircraft and automotive applications due to its fault-tolerant capabilities and robust configuration. Power converter is a key component in SRM drives, but it prone to faults. In this study, a new and fast diagnosis method for short-circuit fault of the SRM converter is proposed based on the mixed logical dynamic (MLD) model and residual generation. Effects of short-circuit fault on SRM drives are analysed in detail. The MLD model of an asymmetrical half-bridge converter of SRM drives is presented to evaluate the currents of the power converter. The short-circuit faulty switch is identified by analysing the system residual, achieved by comparing the outputs of the MLD model and the sensor measurements. In contrast to other methods, the presented method requires no additional hardware but only measured phase currents and command signals, which are available in the control system. Simulation results confirm the effectiveness of the proposed diagnosis method. It is shown that such diagnosis method can identify the faulty switch of the power converter in a few milliseconds, which is important to avoid catastrophic consequences. It is fast, reliable and easy for industrial applications due the low-computational requirement. 
5. Abstract of Cited Paper (BIB005):  This study presents a generalised fault diagnosis method for power transistors in the asymmetric half-bridge power converter of switched reluctance motor (SRM) drive. In order to extract the remarkable fault features, three current sensors are rearranged. Each phase current can be calculated by solving the equations associated with the detected values of three current sensors and three coefficients obtained based on different switching states. Different faults are preliminarily detected by monitoring the error between the estimated bus current and the actual bus current. After the identification of fault occurrence, the error will be calculated with all the combinations of three coefficients. The minimum error will be found and the corresponding coefficients are recorded. The fault types and fault power transistors are located by comparing the actual coefficients with the recorded coefficients. Being different from the existing methods, the developed diagnostic strategy can detect multiple fault types and can be used in different control modes, including voltage pulse width modulation, current chopping control and angular position control schemes. Moreover, the proposed technique is easy for online implementation without extra sensors and additional electric devices. The effectiveness of the proposed solution is validated on a three-phase 12/8 SRM drive.

Literature Review:
Gate signals are typical digital signals related to different faults. Open-and short-circuit faults in power converter and phase windings can be diagnosed quickly by making full use of gate signals. Mixed logic dynamic (MLD) model and residual generation scheme are presented in BIB005 for the diagnosis of short switch fault. The ideal chopping bus current is obtained by BIB002 . where S 1 ∼ S 6 are the gate signals of power switches in the converter, Then, the actual chopping bus current is acquired by a bus current sensor. The difference between the ideal and actual chopping bus currents is calculated for short-circuit diagnosis, and the procedure is presented in Fig. 11 . In BIB003 , the open-and short-circuit faults in power switches open-and short-circuit faults can be detected rapidly by calculating the difference of the upper-and the lower-switch signals by BIB004 . Constant pattern detection strategy is implemented to diagnose fault types quickly and determine fault locations accurately within two electrical cycles. Three coefficients A, B, and C denoted by BIB001 are used for fault identification in BIB006 . When the estimated and detected currents vary from each other, the fault location algorithm is adopted to find faults precisely. Both open-and short-circuit faults of the power switches can be easily diagnosed. where SW m (m = 1, 2, 3, 4, 5, 6) are the switching signals and SW m (m = 1, 2, 3, 4, 5, 6) are the reverse switching signals.