Pub Date : 2023-01-01DOI: 10.1504/ijhm.2023.10057302
Luis Miguel Gómez Paez, Lei Liu, Chenwei Pu, De-yuan Meng, Pengfei Qian
{"title":"Methods to improve motion servo control accuracy of pneumatic cylinders - review and prospect","authors":"Luis Miguel Gómez Paez, Lei Liu, Chenwei Pu, De-yuan Meng, Pengfei Qian","doi":"10.1504/ijhm.2023.10057302","DOIUrl":"https://doi.org/10.1504/ijhm.2023.10057302","url":null,"abstract":"","PeriodicalId":29937,"journal":{"name":"International Journal of Hydromechatronics","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66895750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijhm.2023.10059853
Xuqu Hu, Yunce Zhang, Tao Wang
{"title":"Robust active disturbance rejection control for modular fluidic soft actuators","authors":"Xuqu Hu, Yunce Zhang, Tao Wang","doi":"10.1504/ijhm.2023.10059853","DOIUrl":"https://doi.org/10.1504/ijhm.2023.10059853","url":null,"abstract":"","PeriodicalId":29937,"journal":{"name":"International Journal of Hydromechatronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136368219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijhm.2023.134339
M. Sellam, K. Kannan, S. Natarajan
Computation of the curvature is an essential task during the simulation of processes such as bio-film growth and two-phase fluid flow wherein the interfacial forces play a crucial role in the determination of the state of stress. Existing methods for computing the curvature at the interface are not very accurate and exhibit unwanted numerical oscillations. In this work, a novel method is proposed to compute the mean curvature of the interface accurately. As opposed to Bruchon method which has only one stabilising term that can bias the results, the proposed method includes a pair of counteracting stabilising terms that remove any such bias. A comparative investigation of the proposed method with other existing techniques is also presented to demonstrate the superior performance. The paper also illustrates the application of the proposed curvature computation method for the flow through pipe problem in the last section.
{"title":"A new stabilised curvature computation method using the level set function","authors":"M. Sellam, K. Kannan, S. Natarajan","doi":"10.1504/ijhm.2023.134339","DOIUrl":"https://doi.org/10.1504/ijhm.2023.134339","url":null,"abstract":"Computation of the curvature is an essential task during the simulation of processes such as bio-film growth and two-phase fluid flow wherein the interfacial forces play a crucial role in the determination of the state of stress. Existing methods for computing the curvature at the interface are not very accurate and exhibit unwanted numerical oscillations. In this work, a novel method is proposed to compute the mean curvature of the interface accurately. As opposed to Bruchon method which has only one stabilising term that can bias the results, the proposed method includes a pair of counteracting stabilising terms that remove any such bias. A comparative investigation of the proposed method with other existing techniques is also presented to demonstrate the superior performance. The paper also illustrates the application of the proposed curvature computation method for the flow through pipe problem in the last section.","PeriodicalId":29937,"journal":{"name":"International Journal of Hydromechatronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135051920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijhm.2023.130520
Changsheng Xi, Jie Yang, Xiaoxia Liang, Rahizar Bin Ramli, Shaoning Tian, Guojin Feng, Dong Zhen
To improve the ability of the deep learning model to handle imbalanced data, a fault diagnosis method based on improved gated convolutional neural network (IGCNN) is proposed. Firstly, an improved gated convolution layer is proposed for feature extraction, with the batch normalisation (BN) layer applied to adjust the data distribution and enhance the generalisation performance of the model. Then, the feature learned by multiple gated convolution layers and pooling layers is fed to the fully connected layer for fault type identification. Finally, the label-distribution-aware margin (LDAM) loss function is employed to adjust the model being more sensitive to the minority class and mitigate the influence of imbalanced data on the model. Experimental validation is conducted using two bearing datasets. Results show that the proposed method is more robust than other fault diagnosis methods, with higher recognition accuracy in severely imbalanced dataset.
{"title":"An improved gated convolutional neural network for rolling bearing fault diagnosis with imbalanced data","authors":"Changsheng Xi, Jie Yang, Xiaoxia Liang, Rahizar Bin Ramli, Shaoning Tian, Guojin Feng, Dong Zhen","doi":"10.1504/ijhm.2023.130520","DOIUrl":"https://doi.org/10.1504/ijhm.2023.130520","url":null,"abstract":"To improve the ability of the deep learning model to handle imbalanced data, a fault diagnosis method based on improved gated convolutional neural network (IGCNN) is proposed. Firstly, an improved gated convolution layer is proposed for feature extraction, with the batch normalisation (BN) layer applied to adjust the data distribution and enhance the generalisation performance of the model. Then, the feature learned by multiple gated convolution layers and pooling layers is fed to the fully connected layer for fault type identification. Finally, the label-distribution-aware margin (LDAM) loss function is employed to adjust the model being more sensitive to the minority class and mitigate the influence of imbalanced data on the model. Experimental validation is conducted using two bearing datasets. Results show that the proposed method is more robust than other fault diagnosis methods, with higher recognition accuracy in severely imbalanced dataset.","PeriodicalId":29937,"journal":{"name":"International Journal of Hydromechatronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136092813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijhm.2023.10055033
M. Balasubramani, R. Venkatakrishnaiah, K. Raju
{"title":"A mayfly optimisation method to predict load settlement of reinforced railway tracks on soft subgrade with multi-layer geogrid","authors":"M. Balasubramani, R. Venkatakrishnaiah, K. Raju","doi":"10.1504/ijhm.2023.10055033","DOIUrl":"https://doi.org/10.1504/ijhm.2023.10055033","url":null,"abstract":"","PeriodicalId":29937,"journal":{"name":"International Journal of Hydromechatronics","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66895137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijhm.2023.10056146
Sun Yongjun, C. Gerada, Liu Yiwei, Cui Shipeng
{"title":"Model adaptive collision detection for flexible joint manipulator based on state observer","authors":"Sun Yongjun, C. Gerada, Liu Yiwei, Cui Shipeng","doi":"10.1504/ijhm.2023.10056146","DOIUrl":"https://doi.org/10.1504/ijhm.2023.10056146","url":null,"abstract":"","PeriodicalId":29937,"journal":{"name":"International Journal of Hydromechatronics","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66895476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijhm.2023.10058581
S. Natarajan, K. Kannan, M. Sellam
{"title":"A new stabilized curvature computation method using the level set function","authors":"S. Natarajan, K. Kannan, M. Sellam","doi":"10.1504/ijhm.2023.10058581","DOIUrl":"https://doi.org/10.1504/ijhm.2023.10058581","url":null,"abstract":"","PeriodicalId":29937,"journal":{"name":"International Journal of Hydromechatronics","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66896043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1504/ijhm.2023.129126
Hongwei Ning, Shizhi Qian, Teng Zhou
Tracking of free interfaces in two-phase and multi-phase fluids is a critical step in computational fluid dynamics. Among the many methods, because of no need for parameterisation of curves and an excellent solution to the problem of evolutionary curve topology change, the level set method (LSM) is widely used in the field and has achieved good results. The paper reviews applications of LSM in the tracking of free interfaces, including theory fundamental, solving the basic partial differential equation used to represent fluids in LSM, free interfaces tracking of two-phase fluids, interfaces evolutions of multi-phase fluids, and coupling with other methods to increase tracking performance. Based on the summaries, we confirm the level set method has achieved excellent results in fluid interface tracking either alone or coupled with other algorithms. Of course, the level set method requires further optimisation in terms of initialisation and mass conservation.
{"title":"Applications of level set method in computational fluid dynamics: a review","authors":"Hongwei Ning, Shizhi Qian, Teng Zhou","doi":"10.1504/ijhm.2023.129126","DOIUrl":"https://doi.org/10.1504/ijhm.2023.129126","url":null,"abstract":"Tracking of free interfaces in two-phase and multi-phase fluids is a critical step in computational fluid dynamics. Among the many methods, because of no need for parameterisation of curves and an excellent solution to the problem of evolutionary curve topology change, the level set method (LSM) is widely used in the field and has achieved good results. The paper reviews applications of LSM in the tracking of free interfaces, including theory fundamental, solving the basic partial differential equation used to represent fluids in LSM, free interfaces tracking of two-phase fluids, interfaces evolutions of multi-phase fluids, and coupling with other methods to increase tracking performance. Based on the summaries, we confirm the level set method has achieved excellent results in fluid interface tracking either alone or coupled with other algorithms. Of course, the level set method requires further optimisation in terms of initialisation and mass conservation.","PeriodicalId":29937,"journal":{"name":"International Journal of Hydromechatronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135534457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Axial piston pumps are key components in hydraulic systems and their performance significantly affects the efficiency and reliability of hydraulic systems. Many data-driven approaches have been applied to the fault diagnosis of axial piston pumps. However, few studies focus on the performance degradation assessment that plays an important role in the predictive maintenance for axial piston pumps. This paper proposes a hybrid model-driven and data-driven approach to assess the health status of axial piston pumps. A physical flow loss model is established to solve for the flow loss coefficients of the axial piston pump under different operating conditions. The flow loss coefficients act as feature vectors to train a support vector data description (SVDD) model. A health indicator based on SVDD is put forward to quantitatively assess the pump health status. Experimental results under different pump health conditions confirm the effectiveness of the proposed method.
{"title":"Hybrid model-driven and data-driven approach for the health assessment of axial piston pumps","authors":"Qun Chao, Zi Xu, Yuechen Shao, Jianfeng Tao, Chengliang Liu, Shuo Ding","doi":"10.1504/ijhm.2023.129123","DOIUrl":"https://doi.org/10.1504/ijhm.2023.129123","url":null,"abstract":"Axial piston pumps are key components in hydraulic systems and their performance significantly affects the efficiency and reliability of hydraulic systems. Many data-driven approaches have been applied to the fault diagnosis of axial piston pumps. However, few studies focus on the performance degradation assessment that plays an important role in the predictive maintenance for axial piston pumps. This paper proposes a hybrid model-driven and data-driven approach to assess the health status of axial piston pumps. A physical flow loss model is established to solve for the flow loss coefficients of the axial piston pump under different operating conditions. The flow loss coefficients act as feature vectors to train a support vector data description (SVDD) model. A health indicator based on SVDD is put forward to quantitatively assess the pump health status. Experimental results under different pump health conditions confirm the effectiveness of the proposed method.","PeriodicalId":29937,"journal":{"name":"International Journal of Hydromechatronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135914219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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