Data-Based Flow Rate Prediction Models for Independent Metering Hydraulic Valve
Accurate valve flow rate prediction is essential for the flow control process of independent metering (IM) hydraulic valve. Traditional estimation methods are difficult to meet the high-precision requirements under the restricted space of the valve. Thus data-based flow rate prediction method for IM...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/20/7699 |
| _version_ | 1797473592566349824 |
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| author | Wenbin Su Wei Ren Hui Sun Canjie Liu Xuhao Lu Yingli Hua Hongbo Wei Han Jia |
| author_facet | Wenbin Su Wei Ren Hui Sun Canjie Liu Xuhao Lu Yingli Hua Hongbo Wei Han Jia |
| author_sort | Wenbin Su |
| collection | DOAJ |
| description | Accurate valve flow rate prediction is essential for the flow control process of independent metering (IM) hydraulic valve. Traditional estimation methods are difficult to meet the high-precision requirements under the restricted space of the valve. Thus data-based flow rate prediction method for IM valve has been proposed in this study. We took the four-spool IM valve as the research object, and carried out the IM valve experiments to generate labeled data. Picking up the post-valve pressure and valve opening as input, we developed and compared eight different data-based estimation models, including machine learning and deep learning. The results indicated that the SVR and DNN with three hidden layers performed better than others on the whole dataset in the trade-off of overfitting and precision. And MAPE of these two models was close to 4%. This study provides further guidelines on high-precision flow rate prediction of hydraulic valves, and has definite application value for development of digital and intelligent hydraulic systems in construction machinery. |
| first_indexed | 2024-03-09T20:16:44Z |
| format | Article |
| id | doaj.art-a5782018e7854e29a6d63eab6c8e725a |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T20:16:44Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-a5782018e7854e29a6d63eab6c8e725a2023-11-23T23:59:09ZengMDPI AGEnergies1996-10732022-10-011520769910.3390/en15207699Data-Based Flow Rate Prediction Models for Independent Metering Hydraulic ValveWenbin Su0Wei Ren1Hui Sun2Canjie Liu3Xuhao Lu4Yingli Hua5Hongbo Wei6Han Jia7State Key Laboratory for Manufacturing System Engineering, School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710000, ChinaState Key Laboratory for Manufacturing System Engineering, School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710000, ChinaJiangsu Advanced Construction Machinery Innovation Center Ltd., Xuzhou 221000, ChinaJiangsu Advanced Construction Machinery Innovation Center Ltd., Xuzhou 221000, ChinaState Key Laboratory for Manufacturing System Engineering, School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710000, ChinaState Key Laboratory for Manufacturing System Engineering, School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710000, ChinaState Key Laboratory for Manufacturing System Engineering, School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710000, ChinaState Key Laboratory for Manufacturing System Engineering, School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710000, ChinaAccurate valve flow rate prediction is essential for the flow control process of independent metering (IM) hydraulic valve. Traditional estimation methods are difficult to meet the high-precision requirements under the restricted space of the valve. Thus data-based flow rate prediction method for IM valve has been proposed in this study. We took the four-spool IM valve as the research object, and carried out the IM valve experiments to generate labeled data. Picking up the post-valve pressure and valve opening as input, we developed and compared eight different data-based estimation models, including machine learning and deep learning. The results indicated that the SVR and DNN with three hidden layers performed better than others on the whole dataset in the trade-off of overfitting and precision. And MAPE of these two models was close to 4%. This study provides further guidelines on high-precision flow rate prediction of hydraulic valves, and has definite application value for development of digital and intelligent hydraulic systems in construction machinery.https://www.mdpi.com/1996-1073/15/20/7699independent metering hydraulic valvevalve flow rate predictionmachine learningdeep learning |
| spellingShingle | Wenbin Su Wei Ren Hui Sun Canjie Liu Xuhao Lu Yingli Hua Hongbo Wei Han Jia Data-Based Flow Rate Prediction Models for Independent Metering Hydraulic Valve Energies independent metering hydraulic valve valve flow rate prediction machine learning deep learning |
| title | Data-Based Flow Rate Prediction Models for Independent Metering Hydraulic Valve |
| title_full | Data-Based Flow Rate Prediction Models for Independent Metering Hydraulic Valve |
| title_fullStr | Data-Based Flow Rate Prediction Models for Independent Metering Hydraulic Valve |
| title_full_unstemmed | Data-Based Flow Rate Prediction Models for Independent Metering Hydraulic Valve |
| title_short | Data-Based Flow Rate Prediction Models for Independent Metering Hydraulic Valve |
| title_sort | data based flow rate prediction models for independent metering hydraulic valve |
| topic | independent metering hydraulic valve valve flow rate prediction machine learning deep learning |
| url | https://www.mdpi.com/1996-1073/15/20/7699 |
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