Dynamic Error Compensation for Ball Screw Feed Drive Systems Based on Prediction Model
The dynamic error is the dominant factor affecting multi-axis CNC machining accuracy. Predicting and compensating for dynamic errors is vital in high-speed machining. This paper proposes a novel prediction-model-based approach to predict and compensate for the ball screw feed system’s dynamic error....
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Machines |
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| Online Access: | https://www.mdpi.com/2075-1702/13/5/433 |
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| _version_ | 1850257909362982912 |
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| author | Hongda Liu Yonghao Guo Jiaming Liu Wentie Niu |
| author_facet | Hongda Liu Yonghao Guo Jiaming Liu Wentie Niu |
| author_sort | Hongda Liu |
| collection | DOAJ |
| description | The dynamic error is the dominant factor affecting multi-axis CNC machining accuracy. Predicting and compensating for dynamic errors is vital in high-speed machining. This paper proposes a novel prediction-model-based approach to predict and compensate for the ball screw feed system’s dynamic error. Based on the lumped and distributed mass methods, this method constructs a parameterized dynamic model relying on the moving component’s position for electromechanical coupling modeling. Using Latin Hypercube Sampling and numerical simulation, a sample set containing the input and output of one control cycle is obtained, which is used to train a Cascade-Forward Neural Network to predict dynamic errors. Finally, a feedforward compensation strategy based on the prediction model is proposed to improve tracking performance. The proposed method is applied to a ball screw feed system. Tracking error simulations and experiments are conducted and compared with the transfer function feedforward compensation. Typical trajectories are designed to validate the effectiveness of the electromechanical coupling model, the dynamic error prediction model, and the feedforward compensation strategy. The results show that the prediction model exhibits a maximum prediction deviation of 1.8% for the maximum tracking error and 13% for the average tracking error. The proposed compensation method with friction compensation achieves a maximum reduction rate of 76.7% for the maximum tracking error and 63.7% for the average tracking error. |
| format | Article |
| id | doaj-art-b813d594a28e42e398b2adb5459c0d42 |
| institution | OA Journals |
| issn | 2075-1702 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj-art-b813d594a28e42e398b2adb5459c0d422025-08-20T01:56:17ZengMDPI AGMachines2075-17022025-05-0113543310.3390/machines13050433Dynamic Error Compensation for Ball Screw Feed Drive Systems Based on Prediction ModelHongda Liu0Yonghao Guo1Jiaming Liu2Wentie Niu3Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin 300350, ChinaKey Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin 300350, ChinaKey Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin 300350, ChinaKey Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin 300350, ChinaThe dynamic error is the dominant factor affecting multi-axis CNC machining accuracy. Predicting and compensating for dynamic errors is vital in high-speed machining. This paper proposes a novel prediction-model-based approach to predict and compensate for the ball screw feed system’s dynamic error. Based on the lumped and distributed mass methods, this method constructs a parameterized dynamic model relying on the moving component’s position for electromechanical coupling modeling. Using Latin Hypercube Sampling and numerical simulation, a sample set containing the input and output of one control cycle is obtained, which is used to train a Cascade-Forward Neural Network to predict dynamic errors. Finally, a feedforward compensation strategy based on the prediction model is proposed to improve tracking performance. The proposed method is applied to a ball screw feed system. Tracking error simulations and experiments are conducted and compared with the transfer function feedforward compensation. Typical trajectories are designed to validate the effectiveness of the electromechanical coupling model, the dynamic error prediction model, and the feedforward compensation strategy. The results show that the prediction model exhibits a maximum prediction deviation of 1.8% for the maximum tracking error and 13% for the average tracking error. The proposed compensation method with friction compensation achieves a maximum reduction rate of 76.7% for the maximum tracking error and 63.7% for the average tracking error.https://www.mdpi.com/2075-1702/13/5/433ball screw feed systemprediction modeldynamic errorfeedforward compensationdynamic accuracy |
| spellingShingle | Hongda Liu Yonghao Guo Jiaming Liu Wentie Niu Dynamic Error Compensation for Ball Screw Feed Drive Systems Based on Prediction Model Machines ball screw feed system prediction model dynamic error feedforward compensation dynamic accuracy |
| title | Dynamic Error Compensation for Ball Screw Feed Drive Systems Based on Prediction Model |
| title_full | Dynamic Error Compensation for Ball Screw Feed Drive Systems Based on Prediction Model |
| title_fullStr | Dynamic Error Compensation for Ball Screw Feed Drive Systems Based on Prediction Model |
| title_full_unstemmed | Dynamic Error Compensation for Ball Screw Feed Drive Systems Based on Prediction Model |
| title_short | Dynamic Error Compensation for Ball Screw Feed Drive Systems Based on Prediction Model |
| title_sort | dynamic error compensation for ball screw feed drive systems based on prediction model |
| topic | ball screw feed system prediction model dynamic error feedforward compensation dynamic accuracy |
| url | https://www.mdpi.com/2075-1702/13/5/433 |
| work_keys_str_mv | AT hongdaliu dynamicerrorcompensationforballscrewfeeddrivesystemsbasedonpredictionmodel AT yonghaoguo dynamicerrorcompensationforballscrewfeeddrivesystemsbasedonpredictionmodel AT jiamingliu dynamicerrorcompensationforballscrewfeeddrivesystemsbasedonpredictionmodel AT wentieniu dynamicerrorcompensationforballscrewfeeddrivesystemsbasedonpredictionmodel |