Abstract
In order to improve the fault detection capability of large and medium-sized pump stations, the abnormal feature diagnosis of the fault data is required, and the intelligent diagnosis algorithm of the fault data of the large and medium-sized pump station under the information-based evaluation system is put forward. The fault data sensing information acquisition node distribution model of the large and medium-sized pump station is constructed, the multi-sensor fusion sampling method is adopted to sample the fault data of the large and medium-sized pump station, and the statistical feature quantity of the fault data of the large and medium-sized pump station is extracted. The fault data set of large and medium-sized pump station is used to detect and optimize the abnormal working condition of the fault data set of the large and medium-sized pump station, and the fault diagnosis of the large and medium-sized pump station is realized according to the detection result. The simulation results show that the accuracy of the fault data set of large and medium pump station is high, and the real-time and self-adaptability of the fault detection are better.
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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Liu, Yh., Chen, Yh. (2020). Research on Intelligent Diagnosis of Fault Data of Large and Medium-Sized Pumping Stations Under Information Evaluation System. In: Zhang, YD., Wang, SH., Liu, S. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-030-51100-5_9
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DOI: https://doi.org/10.1007/978-3-030-51100-5_9
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