## 2 Experimental and Methodology  
### Background  
Considering the effects that external disturbances have on hydraulic systems, it is mandatory to provide solutions for the end user, i.e., workers. The end user, in many cases,  
Figure 1: Research methodology flowchart. gets confused in an unknown situation and does not know how to react, which can only be solved by engineering knowledge. In the field of hydraulic systems, previous studies have presented the approach of using numerical models based on physical laws or machine learning models combined with artificial intelligence to determine the facts about the operating conditions of the hydraulic system under study. [PERSON] et al. [36] investigated the hydraulic pump in a wide range of operating conditions and presented an energy-efficient digital pump, with adaptive operating strategies and driven by expert systems and machine learning, that outperforms conventional hydraulic pumps and achieves significant energy savings. [PERSON] et al. [37] investigated an internal leakage in hydraulic actuators and proposed an SVM classifier using pressure and boom angle displacement signals. Since the numerical models are easy to use and universally applicable to perform various scenarios with minor changes, their approximation accuracy is limited due to simplifications in the mathematical equations. Moreover, data-driven models are usually developed intentionally and offer better prediction accuracy. However, when knowledge engineering requires further investigation, the intentionally built data-driven model is not sufficient to make a correct prediction [38]. To ensure accurate predictions, rebuilding the data-driven model from scratch with additional data becomes necessary. This research utilizes data-driven models as a highly predictive method to enhance engineering knowledge and accelerate decision-making and adaptive control within the expert system. The study focuses on recognizing and addressing changes in hydraulic press behavior caused by external disturbances. Figure 2 illustrates the experimental setup and key elements of the study, highlighting the investigation of hydraulic press behavior under changed sealing and guiding characteristics, as well as the interaction between the forming process and the press as an action-reaction effect. The hydraulic press used for the experimental tests is equipped with proportional hydraulic valve MOOG D633 (nominal flow 5 L/min at pressure drop 70 bar), MOXG amplifier G122-829A (MOOG Inc., Boblingen, Germany), Programable Logical Controller (PLC) CP3718 (Beckhoff Automation, Verl, Germany), and advanced servo sealing technology hydraulic cylinder ((Hanchen, Ostfildern, Germany) rod diameter 30 mm, housing diameter 45 mm, working pressure 200 bar), which defines the initial friction characteristics. Figure 2: Investigation of a hydraulic press under external disturbances. Moreover, a diagram showcasing the friction characteristics is determined by a numerical model, provided by the hydraulic cylinder manufacturer Hanchen (Ostfildern, Germany), which is used to simulate changed friction characteristics of the components integrated into the hydraulic press [7]. Furthermore, the effects of changed friction dynamics, attributed to different sealing and guiding mechanisms integrated into hydraulic cylinders as well as wear in hydraulic press guides, are mitigated by addressing altered friction conditions with the numerical model in this research. Various sealing and guiding technologies for hydraulic cylinders influence different friction forces \(F_{D}\), represented by the Stribeck curve at different hydraulic cylinder velocities \(v_{\mathbb{C}}\)[27; 39]. At low velocities \(v_{\mathbb{C}}\), the numerical model indicates that standard sealing and guiding technologies exhibit a more pronounced stick-slip effect compared to advanced technologies, such as gap sealing technology [40].