Advances in Fluid Power Systems

The main purpose of this special edition of “Advances in Fluid Power Systems” was to present new scientific work in the field of fluid power systems for the hydraulic and pneumatic control of machines and devices that are used in various industries [...]

Exhaustive Regressor Search (XRS) for Creating Models of Hydraulic Pumps and Motors

Physical models of fluid power systems rely on the validity of the principles used for creating such models. In many cases, pump and motor performance is considered a large contributor to the efficiency of a whole fluid power system and, is used to approximate the behavior of the component and the system coupled to it. Often, estimates of the power losses and efficiency of pumps and motors is limited to manufacturer test data or simplified assumptions based on first principles. However, the use of the limited test data or idealized assumptions reduces the accuracy of the models and limits the validity of the theoretical results. Moreover, the creation of accurate physical models, their numerical implementation using a computer to solve the model and the experimental validation is time consuming and costly. New advances in machine learning, statistical analysis and numerical methods can be used to reduce the time used to develop a model of a pump or motor producing similar or better results. This paper proposes the use of an autonomous and iterative algorithm to obtain linear regression coefficients necessary to characterize the flow response of a pump or motor from existing experimental data. In this study a multivariate linear model for predicting the flow output of a pump or a motor is derived from experimental data by iteratively adding data points and by iteratively and autonomously testing regressor combinations to find the best possible flow model.

Real-Time Simulation of Fluid Power Systems

System-simulations involving fluid-power structures often result in numerically stiff model equations which may require prohibitively small simulation time steps when being tackled with a fixed-step solver. This poses a challenge in situations where real-time performance is required. This paper presents a practical rule-of-thumb to estimate the maximum permissible step-size for a given fluid power system and explains the influence of the relevant physical quantities on the step size requirement in simple terms. A categorization of methods suitable to relax the step-size requirement is proposed. Many research papers have been produced about methods and examples of how to improve real-time performance of fluid power systems, or stiff systems in general. The proposed categorization can be seen as a map for the simulation engineer to understand the basic point-of-attacks for the real-time simulation problem.

A Concept of Risk Prioritization in FMEA Analysis for Fluid Power Systems

FMEA analysis is a tool of quality improvement that has been widely used for decades. Its classical version prioritizes risk of failure by risk priority number (RPN). The RPN is a product of severity (S), occurrence (O), and detection (D), where all of the factors have equal levels of significance. This assumption is one of the most commonly criticized drawbacks, as it has given unreasonable results for real-world applications. The RPN can produce equal values for combinations of risk factors with different risk implications. Another issue is that of the uncertainties and subjectivities of information employed in FMEA analysis that may arise from lack of knowledge, experience, and employed linguistic terms. Many alternatives of risk assessment methods have been proposed to overcome the weaknesses of classical FMEA risk management in which we can distinguish methods of modification of RPN numbers of employing new tools. In this study, we propose a modification of the traditional RPN number. The main difference is that severity and occurrence are valued based on subfactors. The detection number remained unchanged. Additionally, the proposed method prioritizes risk in terms of implied risk to the systems by implementing functional failures (effects of potential failures). A typical fluid power system was used to illustrate the application of this method. The method showed the correct failure classification, which meets the industrial experience and other research results of failures of fluid power systems.

IOT based Web application concept for monitoring and control of fluid power systems

This paper presents a novel concept of the WEB application for monitoring and control of fluid power systems. The proposed concept is based on the internet of things principles. WEB application is built on the Web2py framework which uses Python as the programming language. The client-side of the proposed application is based on the responsive open source AdminLTE dashboard. On the server-side Python is used for executing SQL queries sent to the database and for continuous data logging. The ModbusTCP protocol is used as the communication protocol between the server and systems. The application is tested on two experimental setups. The first one uses an industrial PLC and the second one is an Arduino PLC as a control device. Finally, experimental results are presented and a conclusion is given.

Universal Programmable Portable Measurement Device for Diagnostics and Monitoring of Industrial Fluid Power Systems

This paper presents a new universal programmable portable measuring device (PMD) as a complete, accurate, and efficient solution for monitoring and technical diagnostics of industrial fluid power systems. PMD has programmable functions designed for recording, processing, and graphical visualization of measurement results at the test stand or the place of operation of fluid power systems. PMD has a built-in WiFi communication module for transferring measurement data via Industrial Internet of Things (IIoT) technology for online remote monitoring of fluid power systems. PMD can be programmed for a variety of measuring tasks in servicing, repairing, diagnosing, and monitoring fluid power systems. For this purpose, the fluid dynamic quantity, mechanical quantity, and electrical quantity can be measured. The adjustment of the PMD to the indirect measurement of leakage flow rate in a compressed air system (CAS) is presented in detail. Measuring instruments and PMDs were connected to a branch of the pipeline. The tests used the measurement system to estimate the leakage flow rate through air small nozzles, as well as other CAS indicators.

Model-based Simulation of a Hydraulic Closed-loop Rotary Transmission with Automatic Control

Model-based simulation of a hydraulic closed-loop rotary transmission with automatic control of hydraulic pump and hydraulic motor is considered in the paper. The approach is based on multi-pole modelling and intelligent simulation. In the paper the functional scheme of the transmission is proposed and multi-pole models of components are introduced. Mathematical multi-pole models of components for steady state conditions and for dynamic transient responses are presented. A high-level graphical environment CoCoVila (compiler compiler for visual languages) is used as a tool for describing models and performing simulations. Object-oriented multi-pole models, visual programming environment, automatic program synthesis and distributed computing are as original approach in simulation of fluid power systems.

Customizing a self-healing soft pump for robot

Recent advances in soft materials enable robots to possess safer human-machine interaction ways and adaptive motions, yet there remain substantial challenges to develop universal driving power sources that can achieve performance trade-offs between actuation, speed, portability, and reliability in untethered applications. Here, we introduce a class of fully soft electronic pumps that utilize electrical energy to pump liquid through electrons and ions migration mechanism. Soft pumps combine good portability with excellent actuation performances. We develop special functional liquids that merge unique properties of electrically actuation and self-healing function, providing a direction for self-healing fluid power systems. Appearances and pumpabilities of soft pumps could be customized to meet personalized needs of diverse robots. Combined with a homemade miniature high-voltage power converter, two different soft pumps are implanted into robotic fish and vehicle to achieve their untethered motions, illustrating broad potential of soft pumps as universal power sources in untethered soft robotics.

Fault Detection and Diagnosis Methods for Fluid Power Pitch System Components—A Review

Wind turbines have become a significant part of the global power production and are still increasing in capacity. Pitch systems are an important part of modern wind turbines where they are used to apply aerodynamic braking for power regulation and emergency shutdowns. Studies have shown that the pitch system is responsible for up to 20% of the total down time of a wind turbine. Reducing the down time is an important factor for decreasing the total cost of energy of wind energy in order to make wind energy more competitive. Due to this, attention has come to condition monitoring and fault detection of such systems as an attempt to increase the reliability and availability, hereby the reducing the turbine downtime. Some methods for fault detection and condition monitoring of fluid power systems do exists, though not many are used in today’s pitch systems. This paper gives an overview of fault detection and condition monitoring methods of fluid power systems similar to fluid power pitch systems in wind turbines and discuss their applicability in relation to pitch systems. The purpose is to give an overview of which methods that exist and to find areas where new methods need to be developed or existing need to be modified. The paper goes through the most important components of a pitch system and discuss the existing methods related to each type of component. Furthermore, it is considered if existing methods can be used for fluid power pitch systems for wind turbine.