Geometric optimization of magnetorheological damper for prosthetic ankles using artificial neural networks

IF 3.1 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Mechatronics Pub Date : 2023-12-26 DOI:10.1016/j.mechatronics.2023.103108

Sachin Kumar, Sujatha Chandramohan, S. Sujatha

{"title":"Geometric optimization of magnetorheological damper for prosthetic ankles using artificial neural networks","authors":"Sachin Kumar, Sujatha Chandramohan, S. Sujatha","doi":"10.1016/j.mechatronics.2023.103108","DOIUrl":null,"url":null,"abstract":"<div><p><span>In this work, the primary design constraints of a magnetorheological (MR) actuator and its stroke dimension have been found based on biomechanical requirements and anthropometric constraints of the ankle in a transtibial prosthesis. Based on the inverted slider-crank mechanism models, the force controller parameters of the MR damper are identified. Parameters of the MR dampers are evaluated through optimization that minimises the error between the prosthetic ankle moment and the desired ankle moment for normal level ground walking from experimental data. Furthermore, an </span>artificial neural network<span> (ANN) framework for the MR valve is developed where a three-layered ANN model has been utilised to forecast the magnetic flux density<span> (MFD) across different regions of the MR valve. The data have been generated from an ANSYS-APDL software package using finite element magnetostatic analysis (FEMS). The ANN model outcomes match the FEMS results reasonably well. Finally, the ANN model is employed to find MFD and is used to optimize the MR valve. Optimal solutions are obtained that satisfy the goal function of maximising the damper force and minimising the energy consumption and weight of the MR damper. Subsequently, the optimized MR damper has been fabricated and tested experimentally and it has been found to produce enough force to act as an actuator in a prosthetic ankle.</span></span></p></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"98 ","pages":"Article 103108"},"PeriodicalIF":3.1000,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mechatronics","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0957415823001642","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}

引用次数: 0

Abstract

In this work, the primary design constraints of a magnetorheological (MR) actuator and its stroke dimension have been found based on biomechanical requirements and anthropometric constraints of the ankle in a transtibial prosthesis. Based on the inverted slider-crank mechanism models, the force controller parameters of the MR damper are identified. Parameters of the MR dampers are evaluated through optimization that minimises the error between the prosthetic ankle moment and the desired ankle moment for normal level ground walking from experimental data. Furthermore, an artificial neural network (ANN) framework for the MR valve is developed where a three-layered ANN model has been utilised to forecast the magnetic flux density (MFD) across different regions of the MR valve. The data have been generated from an ANSYS-APDL software package using finite element magnetostatic analysis (FEMS). The ANN model outcomes match the FEMS results reasonably well. Finally, the ANN model is employed to find MFD and is used to optimize the MR valve. Optimal solutions are obtained that satisfy the goal function of maximising the damper force and minimising the energy consumption and weight of the MR damper. Subsequently, the optimized MR damper has been fabricated and tested experimentally and it has been found to produce enough force to act as an actuator in a prosthetic ankle.

查看原文本刊更多论文

利用人工神经网络优化假肢脚踝磁流变阻尼器的几何结构

在这项工作中，根据经胫假肢中踝关节的生物力学要求和人体测量限制，找到了磁流变（MR）致动器的主要设计限制及其行程尺寸。根据倒置滑块-曲柄机构模型，确定了磁流变阻尼器的力控制器参数。通过优化评估磁共振阻尼器的参数，使假肢踝关节力矩与正常水平地面行走时理想踝关节力矩之间的误差最小化。此外，还为磁共振瓣膜开发了一个人工神经网络（ANN）框架，利用三层人工神经网络模型预测磁共振瓣膜不同区域的磁通密度（MFD）。数据由 ANSYS-APDL 软件包通过有限元磁静力分析 (FEMS) 生成。ANN 模型的结果与 FEMS 的结果相当吻合。最后，ANN 模型被用来寻找 MFD，并用于优化磁共振阀门。所获得的最优解能够满足阻尼力最大化、能耗最小化和 MR 阻尼器重量最小化的目标功能。随后，对优化后的磁共振阻尼器进行了制造和实验测试，发现其产生的力足以充当假肢踝关节的致动器。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Mechatronics 工程技术-工程：电子与电气

CiteScore

5.90

自引率

9.10%

发文量

审稿时长

109 days

期刊介绍： Mechatronics is the synergistic combination of precision mechanical engineering, electronic control and systems thinking in the design of products and manufacturing processes. It relates to the design of systems, devices and products aimed at achieving an optimal balance between basic mechanical structure and its overall control. The purpose of this journal is to provide rapid publication of topical papers featuring practical developments in mechatronics. It will cover a wide range of application areas including consumer product design, instrumentation, manufacturing methods, computer integration and process and device control, and will attract a readership from across the industrial and academic research spectrum. Particular importance will be attached to aspects of innovation in mechatronics design philosophy which illustrate the benefits obtainable by an a priori integration of functionality with embedded microprocessor control. A major item will be the design of machines, devices and systems possessing a degree of computer based intelligence. The journal seeks to publish research progress in this field with an emphasis on the applied rather than the theoretical. It will also serve the dual role of bringing greater recognition to this important area of engineering.