Towards digital twin development of counterbalance valves: Modelling and experimental investigation. (1st April 2023)

• Record Type: Journal Article
• Authors: Rituraj, Rituraj; Scheidl, Rudolf
• Is Part Of: Mechanical systems and signal processing. Volume 188(2023)
• Publication Date: 2023-04-01
• Subjects: Digital twins -- Hydraulics -- Counterbalance valves -- Numerical modelling -- Parameter identification; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2022.110049
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: A model for counterbalance valves is developed that can serve as a digital twin. Model considers friction effects that significantly influence the valve behavior. Detailed experimental tests are performed to characterize the valve. Strategies for the identification of model parameters are developed. The model parameters are systematically identified and validated. Abstract: Digital twins are becoming an integral part of mechanical systems in industries due to the several advantages that they can provide such as performance analysis, predictive maintenance, and real-time monitoring. However, to allow their usage by non-experts and integration with digital twins of other interacting systems, the model behind the digital twin should be simple, physics based, and yet accurate enough to serve its purpose. This article presents such a model for counterbalance valves (CBVs) which are commonly found in a variety of hydraulic systems. The model consists of parameters that account for the internal geometry, inertia, and friction characteristics of the CBV. To illustrate the parameter identification strategy for this model, a test set up is designed, and four sets of experiments are conducted. A subset of the measured data is used in a systematic identification of the parameters. The rest of the data is used to validate the CBV model and the parameter identification strategy. The results indicate that the model is successfully able to predict the behavior of the CBV across different operating conditions, thereby, validating the model. The proposed CBV model satisfies key requirements of digital twins and thus, is a suitable candidate for the digital twin of CBVs and can easily be integrated in the digital twins of larger systems where the CBVs are installed.