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Industrial enterprise large user water consumption abnormity monitoring and early warning method

A technology for abnormal monitoring and large users, applied in the field of enterprise water monitoring, it can solve problems such as troubled water management personnel and false alarms, and achieve the effect of solving the uncertainty of water use, improving accuracy, and improving abnormal monitoring methods.

Active Publication Date: 2020-06-09
HANGZHOU DIANZI UNIV
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AI Technical Summary

Problems solved by technology

This flat line method can indeed detect some abnormal situations sensitively, but there are a large number of false alarms, which seriously trouble the management personnel of the water department. See literature [3]

Method used

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  • Industrial enterprise large user water consumption abnormity monitoring and early warning method
  • Industrial enterprise large user water consumption abnormity monitoring and early warning method
  • Industrial enterprise large user water consumption abnormity monitoring and early warning method

Examples

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Embodiment

[0041]Example: A certain enterprise is a foreign trade manufacturer, organizes production according to the order, and arranges shifts according to the busyness of the task. There are 1 to 3 shifts per day, no periodicity, and a single water inlet pipe with a diameter of 100mm. The water department has collected and recorded its trade table data since 2018 (Table 1), and the sampling period is 15 minutes. In 2018, the flat line alarm method was adopted for the enterprise. Specifically, the alarm was issued when the inlet flow exceeded the limit (20 tons / h) for 4 consecutive times within one hour. There were more than 20 alarms throughout the year. It was proved that they were all false alarms, which greatly troubled the water supply. Division staff on duty.

[0042] Table 1 The measured data of X enterprise trade table Unit: m 3

[0043] time Accumulated readings 15 minute interval water volume 2018-01-01 00:00:00 132910.2 0.7 2018-01-01 00:15:00 1329...

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Abstract

The invention discloses an industrial enterprise large user water consumption abnormity monitoring and early warning method. The method comprises the steps of firstly, establishing an industrial enterprise water consumption monitoring database; secondly, calculating dynamic 24-hour water consumption in a historical stable period, performing normal distribution verification on a 24-hour water consumption sequence by adopting KS (Karst Square) examination, and calculating upper and lower limit parameters of the box line diagram when the normal distribution is skewed distribution; and when the distribution is normal distribution, calculating the parameters of the SPC control chart. Finally, SCADA actual measurement data are obtained, 24-hour water consumption is calculated in a rolling mode at each sampling moment and compared with an upper limit threshold value and a lower limit threshold value, and over-limit judgment and early warning are conducted. The upper and lower bound thresholdsof the dynamic 24-hour water consumption of the industrial enterprise are determined through data mining; according to the method and the system, the normal or skewed distribution condition is considered, the practical problems of uncertainty of water consumption of large users of industrial enterprises and difficulty in water company supervision are well solved, the accuracy of automatic monitoring and early warning of water consumption abnormity of the industrial enterprises is improved, and a three-level DMA abnormity monitoring means of water companies is perfected.

Description

technical field [0001] The invention belongs to the technical field of enterprise water monitoring, in particular to an abnormal monitoring and early warning method for large users of industrial enterprises. Background technique [0002] With the maturity of the large meter remote transmission technology and the establishment of the leakage measurement and monitoring platform of the water department, the automatic collection and transmission of data from the unit trade large meter and the water inlet assessment form of the community is gradually realized, and the water department implements water flow supervision. For residential quarters or institutions / schools / hospitals / shopping malls, using the DMA minimum night flow (MNF) method for leakage supervision is an effective method, see literature [1]. Literature [2] determines the MNF threshold through data mining, and draws on the advantages of the conventional SPC method to detect gradient anomalies, perfects the means of ce...

Claims

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Application Information

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IPC IPC(8): G06F17/18
CPCG06F17/18Y02P90/02
Inventor 徐哲陈晖何必仕江永伟
Owner HANGZHOU DIANZI UNIV
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