The Prediction of the Motor State of the Shore Bridge Based on the Generative Resistance Network GAN
| Publication Date: |
2018-11-06
|
|---|---|
| Publisher: |
Institute of Physics (IOP)
|
| Print ISSN: |
1757-8981
|
| Electronic ISSN: |
1757-899X
|
| Topics: |
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
|
| Published by: |
| _version_ | 1836399080593424384 |
|---|---|
| autor | C Shi, G Tang, Y Li and X Hu |
| beschreibung | In order to forecast the trend and the vibration characteristic parameters of the shore bridge driving system and find the internal faults. This paper analyze the trend by using a large number of bridge lifting motor historical data based on the theory of generative information against network GAN, introduce the base theory of the generative theory against network in detail, establish a prediction model based on GAN and use the model to predict crane driving system performance parameters. The experimental results show that the prediction model based on GAN can achieve satisfactory results in the prediction and realize the accurate prediction of the change trend of the bridge driving system. |
| citation_standardnr | 6353084 |
| datenlieferant | ipn_articles |
| feed_id | 123476 |
| feed_publisher | Institute of Physics (IOP) |
| feed_publisher_url | http://www.iop.org/ |
| insertion_date | 2018-11-06 |
| journaleissn | 1757-899X |
| journalissn | 1757-8981 |
| publikationsjahr_anzeige | 2018 |
| publikationsjahr_facette | 2018 |
| publikationsjahr_intervall | 7984:2015-2019 |
| publikationsjahr_sort | 2018 |
| publisher | Institute of Physics (IOP) |
| quelle | IOP Conference Series: Materials Science and Engineering |
| relation | http://iopscience.iop.org/1757-899X/435/1/012010 |
| search_space | articles |
| shingle_author_1 | C Shi, G Tang, Y Li and X Hu |
| shingle_author_2 | C Shi, G Tang, Y Li and X Hu |
| shingle_author_3 | C Shi, G Tang, Y Li and X Hu |
| shingle_author_4 | C Shi, G Tang, Y Li and X Hu |
| shingle_catch_all_1 | The Prediction of the Motor State of the Shore Bridge Based on the Generative Resistance Network GAN In order to forecast the trend and the vibration characteristic parameters of the shore bridge driving system and find the internal faults. This paper analyze the trend by using a large number of bridge lifting motor historical data based on the theory of generative information against network GAN, introduce the base theory of the generative theory against network in detail, establish a prediction model based on GAN and use the model to predict crane driving system performance parameters. The experimental results show that the prediction model based on GAN can achieve satisfactory results in the prediction and realize the accurate prediction of the change trend of the bridge driving system. C Shi, G Tang, Y Li and X Hu Institute of Physics (IOP) 1757-8981 17578981 1757-899X 1757899X |
| shingle_catch_all_2 | The Prediction of the Motor State of the Shore Bridge Based on the Generative Resistance Network GAN In order to forecast the trend and the vibration characteristic parameters of the shore bridge driving system and find the internal faults. This paper analyze the trend by using a large number of bridge lifting motor historical data based on the theory of generative information against network GAN, introduce the base theory of the generative theory against network in detail, establish a prediction model based on GAN and use the model to predict crane driving system performance parameters. The experimental results show that the prediction model based on GAN can achieve satisfactory results in the prediction and realize the accurate prediction of the change trend of the bridge driving system. C Shi, G Tang, Y Li and X Hu Institute of Physics (IOP) 1757-8981 17578981 1757-899X 1757899X |
| shingle_catch_all_3 | The Prediction of the Motor State of the Shore Bridge Based on the Generative Resistance Network GAN In order to forecast the trend and the vibration characteristic parameters of the shore bridge driving system and find the internal faults. This paper analyze the trend by using a large number of bridge lifting motor historical data based on the theory of generative information against network GAN, introduce the base theory of the generative theory against network in detail, establish a prediction model based on GAN and use the model to predict crane driving system performance parameters. The experimental results show that the prediction model based on GAN can achieve satisfactory results in the prediction and realize the accurate prediction of the change trend of the bridge driving system. C Shi, G Tang, Y Li and X Hu Institute of Physics (IOP) 1757-8981 17578981 1757-899X 1757899X |
| shingle_catch_all_4 | The Prediction of the Motor State of the Shore Bridge Based on the Generative Resistance Network GAN In order to forecast the trend and the vibration characteristic parameters of the shore bridge driving system and find the internal faults. This paper analyze the trend by using a large number of bridge lifting motor historical data based on the theory of generative information against network GAN, introduce the base theory of the generative theory against network in detail, establish a prediction model based on GAN and use the model to predict crane driving system performance parameters. The experimental results show that the prediction model based on GAN can achieve satisfactory results in the prediction and realize the accurate prediction of the change trend of the bridge driving system. C Shi, G Tang, Y Li and X Hu Institute of Physics (IOP) 1757-8981 17578981 1757-899X 1757899X |
| shingle_title_1 | The Prediction of the Motor State of the Shore Bridge Based on the Generative Resistance Network GAN |
| shingle_title_2 | The Prediction of the Motor State of the Shore Bridge Based on the Generative Resistance Network GAN |
| shingle_title_3 | The Prediction of the Motor State of the Shore Bridge Based on the Generative Resistance Network GAN |
| shingle_title_4 | The Prediction of the Motor State of the Shore Bridge Based on the Generative Resistance Network GAN |
| timestamp | 2025-06-30T23:37:17.660Z |
| titel | The Prediction of the Motor State of the Shore Bridge Based on the Generative Resistance Network GAN |
| titel_suche | The Prediction of the Motor State of the Shore Bridge Based on the Generative Resistance Network GAN |
| topic | ZL |
| uid | ipn_articles_6353084 |