Tailings safety monitoring method based on evolved neural network

A neural network and safety monitoring technology, applied in the field of tailings safety monitoring based on evolutionary neural network, can solve the problems of unfavorable elimination of danger, short emergency treatment time, etc., and achieve the effect of improving early warning and safety guarantee

Inactive Publication Date: 2014-07-23
HUNAN WUZHOU INSPECTION TECH
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Problems solved by technology

[0003] The present invention provides a tailings safety monitoring method based on evolutionary neural network, the purpose of which is to overcome the short time left for emergency treatment when the safety alarm of tailings is issued in the prior art, which is not conducive to timely elimination of danger

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  • Tailings safety monitoring method based on evolved neural network
  • Tailings safety monitoring method based on evolved neural network
  • Tailings safety monitoring method based on evolved neural network

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Embodiment Construction

[0037] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0038] Such as figure 1 As shown, a tailings safety monitoring method based on evolutionary neural network includes the following steps:

[0039] Step 1: Obtain historical data and construct a tailings curve model according to the principle of curve modeling;

[0040] The historical data refers to the air temperature, water level, water temperature, slope displacement, dry beach displacement, groundwater seepage pressure, concrete stress and tailings dry beach curve area, volume and shape;

[0041] The tailings curve model refers to x is the abscissa of any point on the dry beach curve, and y is the length of the dry beach corresponding to point x on the dry beach curve; aj is the coefficient obtained by polynomial fitting, the value of j is an integer from 0 to m; the tailings dry beach curve is integrated to obtain the dry beach area;

[0042] St...

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Abstract

The invention discloses a tailings safety monitoring method based on an evolved neural network. The tailings safety monitoring method includes the following steps that (1), historical data are obtained, and meanwhile a tailings curve model is constructed according to the curve modeling principle; (2), a neural network prediction model is built and evolved by using the historical data; (3), an evolution individual is determined and optimized by adopting a high-dimensional optimization evolutionary algorithm to obtain a mature prediction model; (4), data are collected in real time to serve as node data of an input layer of the mature prediction model obtained in the step (3), and tailings parameters after the interval time delta t are predicted; (5), if an output value of the tailings curve model exceeds a set warning value, an early-warning signal is sent out. According to the tailings safety monitoring method, the data measured in advance and the data measured in real time are synthesized, the development trend of the main safety parameters of a tailings pond is effectively predicted, and therefore early-warning is brought forward greatly.

Description

technical field [0001] The invention relates to a tailings safety monitoring method based on an evolutionary neural network. Background technique [0002] With the development of my country's economic construction, various large-scale civil engineering projects such as roadbeds, bridges, tunnels, dams, mine tailings, slopes, and high-rise buildings have sprung up like mushrooms after rain. How to prevent the potential safety hazards in these civil buildings for a long time has become an important link to ensure people's lives, property and public safety. Effective detection methods are conducive to timely detection of problems, and reliable monitoring modes are the "sentinels" to ensure that civil and engineering buildings are in a safe state for a long time. At present, the domestic tailings safety detection mechanism generally adopts sensors to collect monitoring data in real time, and sets the safety threshold in advance according to experience to form a "sensor + trigge...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08B21/10G06N3/02
Inventor 肖赤心罗世武
Owner HUNAN WUZHOU INSPECTION TECH
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