## 2 Materials and Methods
### The Smart Bearing Technology and Its Application to Rolling Process  
The goal of smart bearing is to detect any abnormal operation of the rolling mill (\"out-monitoring\") as well as early identification of any inner faults (\"in-monitoring\"). In the steelmaking process, the risk of catastrophic events motivates equipping all the machinery with an effective condition monitoring system. This is carried out, for instance, for the electric arc furnace [15]. In rotating machinery, statistics demonstrate that several faults rise up in bearings, and effective condition monitoring can detect their immediate consequences and evidence. A fault there nucleated affects the rotor shaft dynamics and its stability [16; 17; 18]. Therefore, monitoring bearings allows for assessing the overall system health and reliability. The smart bearing needs to be power supplied, either autonomously or through a light and flexible wire connection, and suitably miniaturized to be embedded into the machine [19]. Embedding sensors in some systems is rather difficult, but providing a condition monitoring of the rolling mill promotes the automation of steel production through some mechatronic manufacturing systems [20; 21; 22]. Some obstacles to wireless telecommunication in the rolling mill actually exist. Therefore, a deep research activity promotes the development of effective sensor technologies.  
Since the beginning of this millennium [23], several solutions have been proposed. [PERSON] [24] exploits a wireless and temperature-sensitive capacitor sensor (up to 220 \({}^{\circ}\)C), being more effective than thermocouples. [PERSON] [25] introduces an autonomous smart bearing suitable for harsh environments being able to operate up to 300 \({}^{\circ}\)C and harvest thermal energy from the environment through a thermoelectric generator (TEG), even used in some other applications [26]. It exploits wireless communication to send data. In the work of [9], a multi-tasking smart bearing is proposed, including two piezoelectric vibration sensors, two magneto-electric speed sensors, and two thermocouples. In the work of [27], the whole sensing unit is designed. A sensor based on a microprocessor monitors the bearing duty cycles and dynamics. Vibration data in two directions are collected and preliminarily analyzed. This system sends the monitoring system directly the evidence of fault detection, in either the shaft or bearings, resorting to the wavelet energy spectrum technique. In the work of [28], a small strain gauge, for high spatial resolution and low response time, is applied to rolling contact in the axial roller bearing. A comprehensive review of the state of the art of the smart bearing technologies and the structure of integrated sensors and of the parameters to be monitored for the aircraft engine is depicted in the work of [29]. [PERSON] introduces [30] a cost-effective triboelectric sensor embedded into a roller bearing based on the triboelectric effect. [PERSON] [31] proposes a review of the most recent smart bearing layouts and focuses on some key issues such as signal detection, power supply, read-out circuits, and bearing arrangement. [PERSON] [32] presents an integrated and self-powered wireless system for high-temperature (above 125 \({}^{\circ}\)C) environments powered by a thermoelectric generator for bearing condition monitoring in aircraft application, where the TEG allows collecting data every 46 s and transmitting every 260 s. [PERSON] [19] designed an autonomous configuration based on a vibration energy harvester. The energy conversion exploits vibration of a flexible structure, with surface-bonded piezoelectric layers, being excited by some permanent magnets during their rotation. All the above-mentioned solutions exploit quite suitable access to the monitored system. The ratio between the size of the sensor and of the machine element is never too low, and environmental conditions are only seldom critical. In case of the rolling mill, those benefits are very often absent, and a specific strategy is required.