Equipment scheduling early-warning method and system based on big data

An early warning system and big data technology, applied in the field of big data and machine learning, can solve the problems of inappropriate downtime, high operating costs, and short service life of equipment, and achieve the effect of prolonging life, reducing accident rate and preventing accidents.

Inactive Publication Date: 2017-06-20
HUATIAN ENG & TECH CORP MCC
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Problems solved by technology

[0005] The present invention proposes an early warning method based on big data and machine learning, which can effectively prevent accidents of sewage lift pumps, aiming at problems such as short service life of equipment caused by frequent start-stop a

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  • Equipment scheduling early-warning method and system based on big data
  • Equipment scheduling early-warning method and system based on big data
  • Equipment scheduling early-warning method and system based on big data

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[0019] Embodiments of the method and system for early warning of equipment scheduling based on big data according to the present invention will be described below with reference to the accompanying drawings. As those of ordinary skill in the art would realize, the described embodiments may be modified in various different ways or combinations thereof, all without departing from the spirit and scope of the present invention. Accordingly, the drawings and description are illustrative in nature and are not intended to limit the scope of protection of the claims. Furthermore, in this specification, the drawings are not drawn to scale, and the same reference numerals refer to the same parts.

[0020] Explanation of related concepts:

[0021] Machine learning: It is a multi-domain interdisciplinary subject that studies how computers simulate or realize human learning behaviors to acquire new knowledge or skills, and to reorganize existing knowledge structures to continuously improv...

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Abstract

The invention provides an equipment scheduling early-warning method and system based on big data. The equipment scheduling early-warning method includes the following steps: collecting data to form a maintenance record data set, running the record data set, and obtaining an equipment maintenance model, an equipment operating model and an equipment shutdown model after model training; verifying reliability of the models; and preparing a prediction data set, the prediction data set selecting an interval section of a linear function, applying the interval section to the above models, applying BP neural network algorithm on the basis of a weka platform to obtain a prediction result, screening an optimal maintenance period, an optimal operating duration and an optimal shutdown duration, and conducting scheduling of operation, maintenance and purchase of equipment according to the obtained data. Through big data learning, guidance data is obtained, equipment is maintained regularly, the service life of equipment is effectively prolonged, an accident rate of equipment is greatly reduced, and the operation cost is reduced.

Description

technical field [0001] The present invention relates to the field of big data and the field of machine learning, in particular to a method and system for early warning of equipment scheduling based on big data. Background technique [0002] Everything that speaks with data has become the trend of Internet development today or in the future. With the explosive growth of data volume in the industry, the important information hidden in industry big data has also attracted much attention. How to dig out useful information from massive industry big data is an important issue that enterprises must think deeply about and solve. [0003] With the advancement of my country's economic development and urbanization, the demand for urban sewage treatment is increasing. At present, although my country has made great progress in the construction of urban sewage treatment plants, most sewage treatment plants have problems such as low level of automation, underestimation of process managem...

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Application Information

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IPC IPC(8): G06Q10/06G06F17/50
CPCG06F30/20G06F2119/04G06Q10/0635
Inventor 姜岚赵贤林刘智桂峰
Owner HUATIAN ENG & TECH CORP MCC
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