Electro-Hydraulic System Monitoring and Control Using Multivariate Latent Methods

With the rapid development of technology of hydraulic automation systems is observed in our current era, an ongoing effort to introduce engineering technology, automated solutions in everyday life with an emphasis on the field of hydraulic automation systems. The systems sector develops increasingly their fields of application, whether simple or hydraulic circuits for modern hydraulic automation circuits. This paper outlines the use of a statistical multivariate technique called Principal Component Analysis (PCA) and applies it to the monitoring and control of electro-hydraulic servo systems. The experiments were conducted using on-off and PID approaches to control the position of a hydraulic cylinder under different speeds and different PID coefficients. This approach was implemented using data from position sensors with programmable logic controllers (PLC) with the aid of supervisory control and data acquisition system (SCADA) to control the system and make online monitoring for the behavior of the hydraulic cylinder. The SCADA concept was developed to be a universal means of remote access to a variety of local control modules, which could be from different manufacturers and allow access through standard automation protocols. in practice, large SCADA systems have grown to become very similar to distributed control systems in function while using multiple means of interfacing with the plant. They can control large-scale processes that can include multiple sites, and work over large distances as well as small distances. It is one of the most commonly used types of industrial control systems, both large and small systems can be built using the SCADA concept, these systems can range from just tens to thousands of control loops depending on the application. PCA was used to detect the best speed and coefficient of the process. The proposed technique can be used for electro-hydraulic servo system monitoring in a real-time environment