Monitoring the Condition of a Valve and Linear Actuator in Hydraulic Systems

Abstract

The topic of condition monitoring has been a growing area of research in both academia and industry for much of the last two decades. Condition monitoring of fluid power equipment has been no exception to this trend. Much of the research work associated with monitoring the condition of fluid power equipment has centered on pump and motor components due to their relatively high cost and complexity. The work in this paper focuses on the lesser expensive, but more common components of valves and linear actuators. The primary focus of the work presented here pertains to assessing the independent component condition of a valve-controlled linear actuator circuit. The paper first presents simulation studies to establish techniques for proper data collection, neural network training and output interpretation. The neural network approach is then applied to a valve and linear actuator of a John Deere 410E Backhoe Loader. The results indicate that the concept can be applied to a commercial system and is feasible for implementation.

Identification of the Nonlinear Friction Characteristics in a Hydraulic Actuator Using the Extended Kalman Filter

“…However, condition monitoring strategies are not restricted to state/parameter estimation techniques. Other methods such as oil pressure, flow and temperature monitoring, oil contamination monitoring, spectral analysis and vibration analysis of hydraulic components, neural networks and expert systems are commonly used, especially due to progress in the field of sensor technology and computers [3][4][5][6].…”

Equation-based domain knowledge utilization into neural network structure and learning

“…25 Traditional NN has been explored for process modeling in the domain of fluid power and hydraulics. 26 But, to the best of our knowledge, the work reported in this article is the first attempt to combine hydraulic DK into the structure of NN.…”

Intelligent controls for electro-hydraulic poppet valves

“…The output of a residual generator is near zero when no failure is present and significantly different from zero otherwise (Massoumnia et al, 1989). According to Hindman, Burton, and Schoenau (2006), the fluid power industry greatly benefits from having smart components with condition monitoring capabilities since this helps improve machine reliability and ''uptime''. Monitoring and detecting the slow degradation in performance of hydraulic components can reduce maintenance costs and improve productivity.…”

“…This is because otherwise unnoticed faulty components could then be detected and serviced during regularly scheduled maintenance before failing completely and causing unscheduled downtime (Laitinen, Kauranne, & Pietola, 2004). As such, more attention has been given to monitoring the condition of hydraulic pumps and motors due to their complexity and cost (Hindman et al, 2006). In regards to valves, the amount of internal leakage for a proportional closed-center spool valve was monitored in Hindman et al (2006) since this relates to the amount of wear present in the component.…”

“…As such, more attention has been given to monitoring the condition of hydraulic pumps and motors due to their complexity and cost (Hindman et al, 2006). In regards to valves, the amount of internal leakage for a proportional closed-center spool valve was monitored in Hindman et al (2006) since this relates to the amount of wear present in the component.…”