## 1 Introduction  
Electromechanical systems are hybrid systems that are made up of mechanical and electrical elements, and due to their functionality, they have a wide application in modern industries, such as the electrical industry, manufacturing, process consumption, and automotive processes, among others [1, 2]. The main elements involved in an electromechanical system may include pulleys, belts, shafts, and mechanical couplings, among others. However, induction motors (IMs) and gearboxes (GBs) remain the most common elements in model industrial electromechanical system configurations since they allow electrical energy to be transformed into mechanical energy and, in turn, also allow the torque to increase or decrease in power transmissions [3]. Another important point, because IM and GB are widely used, is their low cost, robust mechanical construction, which can adapt to variable load conditions, versatility, low maintenance, efficiency, and ability to operate in severe environments [4]. However, unexpected faults may occur during the useful life of the elements that make up an electromechanical system, causing unscheduled downtimes for all the associated components, mainly in the IM and GB. Typical faults in IM may be due to electrical and mechanical stress. Electrical stresses are associated with hitches in the power supply and cause stator faults like short circuits in the stator winding. Mechanical stresses are caused by overloads that can produce bearing defects, broken rotor bars, unbalance, and misalignment [5]. The GB is usually affected by severe faults like broken or chipped gear teeth and non-severe failures that also influence their proper operation, such as pitting, tearing, and wear [6]. Consequently, the presence of failures in IM or GB can cause undesirable breakdowns in the electromechanical system, causing machinery stoppages, with the associated economic consequences in terms of loss of production [2]. Therefore, the development and implementation of new strategies to perform continuous condition monitoring can ensure the correct operation and optimal conditions of industrial processes. Continuous condition monitoring has become a technique used by engineers and scientists, and it has been commonly performed by measuring different physical magnitudes that commonly describe the behavior of electromechanical systems; moreover, using techniques for signal processing and other advanced methodologies, it is possible to indicate the presence of a fault [3]. Techniques based on vibrations, acoustic emissions, electric current, stray flux, and thermal factors, among others, are the most used for monitoring conditions in IM and GB [7; 8; 9]. It is worth noting that most of these techniques are of the invasive type, in addition to using signal processing techniques to decompose the measured signals into their fundamental components to identify how the signal changes in the presence of a fault in the system. Methodologies based on the use of Wavelet Transform (WT), Fast Fourier Transform (FFT), Empirical Mode Decomposition (EMD), Variational Mode Decomposition (VMD), and Motor Current Signature Analysis (MCSA), among others, are often used when dealing with the signals of electric currents, vibration, sound, and stray flux [10; 11; 12]. Although these methodologies are often effective and used, a specialist with prior knowledge is required to achieve the correct interpretation of the obtained results; then, the identification of the actual condition of IM and GB is given. Since there is usually an error of interpretation in the results, there could also be restrictions when the design of automatic fault diagnosis approaches is required. In recent years, infrared thermography (IRT) has been implemented as a non-invasive and non-destructive technology with a wide range of monitoring capabilities and is a technique that, if correctly implemented, can lead to an adequate solution for methodologies in automatically detecting failures on electromechanical systems [13].