# Magnetic Levitation: An Academic Prototype
## 6 Experimental Results  
In the developed model, the proximity sensors have the following electronic characteristics: sensing side diameter: 18 mm; sensing distance: 15 mm; setting distance: 0 to 10.5 mm; and maximum current consumption: 15 mA. On the other hand, the mechanical components have a shaft housing inner diameter of 2.2 mm and a shaft diameter of 1.5 mm. These specifications indicate that the sensors are able to detect objects within a specific range (up to 15 mm) with a setting distance that allows for adjustments within 0 to 10.5 mm. The prototype design indicates that the sensors are well suited for applications that demand precise detection in confined spaces. Their low current consumption of 15 mA contributes to energy efficiency, which is essential to reducing the overall power requirements of the system. There is no change in the motor voltage when controlling shaft vibrations. In fact, the motor speed remains constant at 990 rpm at 24 V, regardless of the shaft vibration. As is well known, a capacitive sensor detects changes in the capacitance between the sensing object, a shaft in our case, and the sensor. The amount of capacitance varies depending on the distance of the sensing object. This change in the dielectric constant causes a change in capacitance. The sensor detects this change and converts it into an electrical signal that can be used to activate a switch, send a signal to a microcontroller, or perform some other control function. In our experiment, shaft vibration corresponds to the distances between the shaft and the shaft housing, although it can be interpreted as a vertical type of vibration as shown in Figure 4. These distances are measured indirectly, at all times, by proximity sensors that emit a signal in volts. This signal indicates the input voltage when the sensor detects an object in its field of action and 0 V if it detects nothing. The vibration control of the shaft is carried out by means of electromagnets, which are controlled by the microcontroller based on the information emitted by the proximity sensors, and they perform the task of attracting the metal shaft to keep it levitating. After assembling the components of our mechanism based on the parameters discussed above, the mechanism was put into operation to check how the vibration controller that had been designed and programmed behaved. The signal data were captured using a PicoScope data acquisition card. The vertical axis Y of the resulting graph displays a scale ranging between \(\pm\)3.3 V. The controller was activated at 5 s, 15 s, and 30 s, approximately, and deactivated at around 0 s, 10 s, and 20 s, given on the X axis. The data clearly indicate that when the controller is activated, the voltage oscillation significantly narrows to within \(\pm\)0.2 V. In contrast, when the controller is deactivated, the voltage oscillation widens, reaching approximately \(\pm\)1.5 V, demonstrating a substantial reduction in stability. In Figure 23, it can be clearly seen how the vibrations are significantly reduced when the electromagnets act. This outcome confirms that the model designed and constructed according to the specified guidelines effectively reduces the vibration amplitude of the shaft. The reduction in voltage oscillation can be directly correlated to a decrease in physical vibration, with the voltage scale corresponding to a specific vibration amplitude, which can be measured in millimeters, if necessary. This relationship allows us to translate the observed voltage changes into tangible reductions in vibration, illustrating the effectiveness of the controller in stabilizing the system. Although failures may occur during the operation of any mechanism, requiring rapid detection and severity estimation to ensure proper functioning, this aspect was not considered in the scope of this work. We would like to emphasize that the digital control design presented in this paper, along with the accompanying prototype experiment, is primarily an academic system.