Modeling of Coal Mill System Used for Fault Simulation
Monitoring and diagnosis of coal mill systems are critical to the security operation of power plants. The traditional data-driven fault diagnosis methods often result in low fault recognition rate or even misjudgment due to the imbalance between fault data samples and normal data samples. In order t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/7/1784 |
| _version_ | 1797571276309528576 |
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| author | Yong Hu Boyu Ping Deliang Zeng Yuguang Niu Yaokui Gao |
| author_facet | Yong Hu Boyu Ping Deliang Zeng Yuguang Niu Yaokui Gao |
| author_sort | Yong Hu |
| collection | DOAJ |
| description | Monitoring and diagnosis of coal mill systems are critical to the security operation of power plants. The traditional data-driven fault diagnosis methods often result in low fault recognition rate or even misjudgment due to the imbalance between fault data samples and normal data samples. In order to obtain massive fault sample data effectively, based on the analysis of primary air system, grinding mechanism and energy conversion process, a dynamic model of the coal mill system which can be used for fault simulation is established. Then, according to the mechanism of various faults, three types of faults (i.e., coal interruption, coal blockage and coal self-ignition) are simulated through the modification of model parameters. The simulation shows that the dynamic characteristic of the model is consistent with the actual object, the relative error of each output variable is less than 2.53%, and the total average relative error of all outputs is about 1.2%. The model has enough accuracy and adaptability for fault simulation, and the problem of massive fault samples acquisition can be effectively solved by the proposed method. |
| first_indexed | 2024-03-10T20:37:00Z |
| format | Article |
| id | doaj.art-a417a53deede4de2a601e750df8bf703 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T20:37:00Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-a417a53deede4de2a601e750df8bf7032023-11-19T20:57:23ZengMDPI AGEnergies1996-10732020-04-01137178410.3390/en13071784Modeling of Coal Mill System Used for Fault SimulationYong Hu0Boyu Ping1Deliang Zeng2Yuguang Niu3Yaokui Gao4State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, Control and Computer Engineering College, North China Electric Power University, Beijing 102206, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, Control and Computer Engineering College, North China Electric Power University, Beijing 102206, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, Control and Computer Engineering College, North China Electric Power University, Beijing 102206, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, Control and Computer Engineering College, North China Electric Power University, Beijing 102206, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, Control and Computer Engineering College, North China Electric Power University, Beijing 102206, ChinaMonitoring and diagnosis of coal mill systems are critical to the security operation of power plants. The traditional data-driven fault diagnosis methods often result in low fault recognition rate or even misjudgment due to the imbalance between fault data samples and normal data samples. In order to obtain massive fault sample data effectively, based on the analysis of primary air system, grinding mechanism and energy conversion process, a dynamic model of the coal mill system which can be used for fault simulation is established. Then, according to the mechanism of various faults, three types of faults (i.e., coal interruption, coal blockage and coal self-ignition) are simulated through the modification of model parameters. The simulation shows that the dynamic characteristic of the model is consistent with the actual object, the relative error of each output variable is less than 2.53%, and the total average relative error of all outputs is about 1.2%. The model has enough accuracy and adaptability for fault simulation, and the problem of massive fault samples acquisition can be effectively solved by the proposed method.https://www.mdpi.com/1996-1073/13/7/1784coal milldynamic modeldata-drivenfault diagnosisfault simulation |
| spellingShingle | Yong Hu Boyu Ping Deliang Zeng Yuguang Niu Yaokui Gao Modeling of Coal Mill System Used for Fault Simulation Energies coal mill dynamic model data-driven fault diagnosis fault simulation |
| title | Modeling of Coal Mill System Used for Fault Simulation |
| title_full | Modeling of Coal Mill System Used for Fault Simulation |
| title_fullStr | Modeling of Coal Mill System Used for Fault Simulation |
| title_full_unstemmed | Modeling of Coal Mill System Used for Fault Simulation |
| title_short | Modeling of Coal Mill System Used for Fault Simulation |
| title_sort | modeling of coal mill system used for fault simulation |
| topic | coal mill dynamic model data-driven fault diagnosis fault simulation |
| url | https://www.mdpi.com/1996-1073/13/7/1784 |
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