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Electronics
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Fault Diagnosis and Intelligent Control Applications in Fluid Power System
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Fault Diagnosis and Intelligent Control Applications in Fluid Power System

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 5810

Special Issue Editors

Prof. Dr. Yan Shi

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Guest Editor
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Interests: mechatronic engineering; hydraulic transmission and control; precision detection technique
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Qing Guo

E-Mail Website
Guest Editor
School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: electrohydraulics; exoskeleton
Special Issues, Collections and Topics in MDPI journals
Dr. Changhui Wang

E-Mail Website
Guest Editor
School of Electromechanical and Automotive Engineering, Yantai University, Yantai 264005, China
Interests: fuzzy control; controller design; control theory
Prof. Dr. Fei Liu

E-Mail Website
Guest Editor
College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China
Interests: robust and adaptive controls; electrohydraulic; exoskeleton; rehabilitation robots

Special Issue Information

Dear Colleagues,

Fluid power systems (FPSs) have both typical hydraulic and pneumatic driving systems, which represent fluid power generation, control, and transmission. FPSs are widely used in different fields, such as engineering machinery, energy development, robotics, aircraft, and other advanced manufacturing and interdisciplinary fields. With the development of advanced design and manufacturing technology, more requirements and challenges have been put forward to FPSs. To improve system reliability, security, and performance, some focused problems should be addressed, such as element diagnosis, uncertainty, external load, disturbance, and noise in FPSs. Hence, many technologies are presented to solve these problems, including but not limited to fault diagnosis, intelligent control, advanced detection technique, energy saving, environmental protection, and advanced applications.

This Special Issue focuses on new developments of fault diagnosis and intelligent control applications in FPSs. This is a worldwide platform to share the latest achievements and valuable ideas. The potential topics include but are not limited to:

  • Advanced signal processing for FPSs
  • System modeling of FPSs
  • Intelligent control for FPSs
  • Smart components and sensors
  • Advanced detection technique
  • Safety and reliability of FPSs
  • Fault diagnosis and prognostics
  • Adaptive controller design in FPSs
  • Artificial intelligence application in FPSs
  • Fluid power hybrid
  • Energy saving and environmental protection in fluid power
  • Advanced applications of FPSs

Prof. Dr. Yan Shi
Prof. Dr. Qing Guo
Dr. Changhui Wang
Prof. Dr. Fei Liu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (4 papers)

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Research

24 pages, 7895 KiB  
Article
Leakage Fault Diagnosis of Two Parallel Cylinders in Pneumatic System with a Minimal Number of Sensors
by Hongwei Zhu, Zhiwen Wang, Hu Wang, Zecheng Zhao and Wei Xiong
Electronics 2023, 12(15), 3261; https://doi.org/10.3390/electronics12153261 - 29 Jul 2023
Viewed by 1051
Abstract
The low investment cost is one of the core competitiveness advantages of pneumatic power systems. With increasingly pressing intelligent manufacturing, it is meaningful to investigate the feasibility of implementing fault diagnoses of pneumatic systems with a minimal number of low-cost sensors. In this [...] Read more.
The low investment cost is one of the core competitiveness advantages of pneumatic power systems. With increasingly pressing intelligent manufacturing, it is meaningful to investigate the feasibility of implementing fault diagnoses of pneumatic systems with a minimal number of low-cost sensors. In this study, a typical pneumatic circuit with two parallel-installed cylinders is taken as an example. The pressure, flow rate, and exergy data collected from upstream sensors are used for diagnosing the leakage faults in two downstream cylinders with the help of different machine learning methods. The features of data are extracted with stacked auto-encoders. Gaussian process classifier, support vector machine, and k-nearest neighbor are used for classifying faults. The results show that it is feasible to detect and diagnose downstream multi-faults with one or two upstream sensors. In terms of the working conditions presented in this study, the average accuracy of diagnosis with exergy data is the highest, followed by flow-rate data and pressure data. The support vector machine performs the best among the three machine learning methods. Full article
(This article belongs to the Special Issue Fault Diagnosis and Intelligent Control Applications in Fluid Power System)
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12 pages, 1984 KiB  
Article
Modeling and Analysis of the Soil Vapor Extraction Equipment for Soil Remediation
by Yan Shi, Shijian Zhao, Zhuo Diao, Yuan Ye, Qiansuo Wang and Yixuan Wang
Electronics 2023, 12(1), 151; https://doi.org/10.3390/electronics12010151 - 29 Dec 2022
Cited by 2 | Viewed by 1302
Abstract
Soil vapor extraction (SVE) is one of the most commonly used technologies for soil remediation of contaminated sites, and the use of models to accurately predict and evaluate the operational effectiveness of SVE is a necessary part of site contamination treatment projects. A [...] Read more.
Soil vapor extraction (SVE) is one of the most commonly used technologies for soil remediation of contaminated sites, and the use of models to accurately predict and evaluate the operational effectiveness of SVE is a necessary part of site contamination treatment projects. A pneumatic model-based equipment model is proposed to comprehensively describe the SVE operation process. Though the numerical simulation, the influence of fan frequency, air valve opening, pressure, and total flow was analyzed, and an optimal extraction strategy was validated. Then, field experiments were carried out to verify the validity of the model. The proposed model and experimental results can provide a theoretical basis for the design and duration evaluation of SVE. Full article
(This article belongs to the Special Issue Fault Diagnosis and Intelligent Control Applications in Fluid Power System)
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23 pages, 5779 KiB  
Article
Simulation Study on Variable Pressure Margin Energy Recovery of Electric Loader Actuator
by Hongyun Mu, Yanlei Luo, Yu Luo and Lunjun Chen
Electronics 2022, 11(24), 4215; https://doi.org/10.3390/electronics11244215 - 16 Dec 2022
Cited by 2 | Viewed by 1463
Abstract
The conventional electric loader uses a motor instead of an engine, which aligns with the current energy-saving and emission-reduction trend. However, the motor’s speed control performance and overload capacity are under-utilized, and the actuator suffers from the potential energy waste problem of the [...] Read more.
The conventional electric loader uses a motor instead of an engine, which aligns with the current energy-saving and emission-reduction trend. However, the motor’s speed control performance and overload capacity are under-utilized, and the actuator suffers from the potential energy waste problem of the boom arm. This study proposes a variable pressure margin energy recovery system for the electric loader actuator. It uses a combination of a permanent magnet synchronous motor (PMSM) and a quantitative pump. It can achieve variable pressure margin control and energy recovery through the pressure feedback closed-loop control. AMESim is used to build the simulation model based on the system control strategy, actuator, supercapacitor, and PMSM mathematical mode. Under typical working conditions, the simulation study is conducted on a 50-type wheel loader to obtain cylinder displacement, system energy recovery, and energy-saving performance. The simulation results show that the system is feasible and can effectively reduce energy consumption. Its energy recovery efficiency is 65.4%. The PMSM energy supply is reduced by 28.6% with the variable pressure margin control. It has high energy-saving performance, and the energy-saving efficiency is 38.5%. It provides a reference for research on energy-saving systems for electric construction machinery. Full article
(This article belongs to the Special Issue Fault Diagnosis and Intelligent Control Applications in Fluid Power System)
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16 pages, 994 KiB  
Article
Control Synchronization Design of a Multiple Electrohydraulic Actuator System with Linearization Dynamics and an External Disturbance Observer
by Jun Qi, Qing Guo, Hualong Ren, Zhenlei Chen, Yao Yan and Dan Jiang
Electronics 2022, 11(23), 3925; https://doi.org/10.3390/electronics11233925 - 27 Nov 2022
Viewed by 1343
Abstract
The control synchronization of multiple electrohydraulic actuators (MEHAs) is initially discussed to ensure the consensus of every electrohydraulic actuator (EHA) with three-order isomorphic dynamics. First, the EHA model is linearized using the Lie derivative method to obtain the state-space model of MEHAs. Then, [...] Read more.
The control synchronization of multiple electrohydraulic actuators (MEHAs) is initially discussed to ensure the consensus of every electrohydraulic actuator (EHA) with three-order isomorphic dynamics. First, the EHA model is linearized using the Lie derivative method to obtain the state-space model of MEHAs. Then, the disturbance observer is used to estimate and compensate for the unknown external load caused by the driving force of a motion plant. Via the Lyapunov technique, this protocol asymptotically achieves consensus to a zero neighborhood with the ultimate boundaries of the MEHAs’ state errors. The effectiveness of the synchronous control protocol is verified by both simulation and experimental benches with two-node EHAs. Full article
(This article belongs to the Special Issue Fault Diagnosis and Intelligent Control Applications in Fluid Power System)
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