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Research on equipment health of distributed energy power station based on improved Mahalanobis distance
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Ziyang CHEN, Daogang PENG, Chunmei XU, Huirong ZHAO
Thermal Power Generation | 2023, 52(8) : 188 - 196
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Thermal Power Generation | 2023, 52(8): 188-196
• Power generation technology forum •
Research on equipment health of distributed energy power station based on improved Mahalanobis distance
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Ziyang CHEN, Daogang PENG, Chunmei XU, Huirong ZHAO
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  • College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Published: 2023-08-25 doi: 10.19666/j.rlfd.202212198
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Distributed energy power stations are developing rapidly because of their cleanliness, environmental protection, economy and high efficiency. However, there are few data used for fault diagnosis of plant equipment, so a method to predict the health state and aging degree of equipment is urgently needed. Based on this, a prediction model which can analyze the running state of equipment and obtain the deterioration trend of equipment is proposed. Firstly, multi-dimensional data of the equipment is preprocessed, and an improved Mahalanobis distance based equipment health model of distributed energy power station is constructed quantitatively by combining the analytic hierarchy process (AHP) with Gaussian mixture distribution. Then, the combined prediction model based on the improved sparrow algorithm and short and long time memory neural network is established to predict the trend and correlation analysis of the deterioration of distributed energy power plant equipment. The experimental results show that the proposed fusion health model can predict equipment anomalies in the case of insufficient actual fault data of distributed energy power stations.

device health  /  improved Mahalanobis distance  /  Gaussian mixture distribution  /  sparrow search algorithm  /  long short-term memory neural network
Ziyang CHEN, Daogang PENG, Chunmei XU, Huirong ZHAO. Research on equipment health of distributed energy power station based on improved Mahalanobis distance[J]. Thermal Power Generation, 2023 , 52 (8) : 188 -196 . DOI: 10.19666/j.rlfd.202212198
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Year 2023 volume 52 Issue 8
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Article Info
doi: 10.19666/j.rlfd.202212198
  • Receive Date：2022-12-06
  • Online Date：2026-01-26
  • Published：2023-08-25
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  • Received：2022-12-06
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Affiliations
    College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China
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多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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