Method for identifying authenticity of sewage monitoring data

Abstract

The invention relates to the technical field of identifying authenticity of sewage monitoring data. A method of mathematical statistics is comprehensively utilized, firstly, a Grabbs method is adopted for carrying out abnormal value judgment and correcting time monitoring data, the corrected time data is subjected to standard reaching screening according to the level standard required by the urban sewage treatment plant pollutant discharge standard (GB18918-2002), the data not meeting the discharge standard is removed, a t inspection method is adopted for verifying whether a spot check data sample mean is within a receiving domain of an overall sample mean or not, an X<2> inspection method is adopted for judging whether volatility of samples relative to the whole has the significant change or not, and then longitudinal comparison of the sewage monitoring data is achieved; an F inspection method and a box plot method are adopted for matching samples with similar year data dispersion degrees, and then transverse comparison of the sewage monitoring data is achieved. The authenticity of monitoring values is deeply detected layer by layer, and certain reference value is achieved for distinguishing the authenticity of the sewage monitoring data.

Description

technical field [0001] The invention relates to the technical field of identifying the authenticity of sewage monitoring data, in particular to a method for identifying the authenticity of sewage monitoring data by combining the principles of mathematical statistics. Background technique [0002] At present, some enterprises that discharge sewage, driven by economic interests, use various methods to falsify online monitoring data, such as diluting sewage at monitoring points, privately connecting dark pipes, and tampering with important parameters of monitoring instruments. These illegal acts lead to the distortion of sewage monitoring data, which brings great trouble to the work of the monitoring department. Many monitoring personnel have low professional quality and lack the ability to analyze and process data scientifically and effectively, resulting in low credibility of data and loss of evaluation significance. Due to the various types of environmental monitoring and t...

AI Technical Summary

Problems solved by technology

These illegal acts lead to the distortion of sewage monitoring data, which brings great trouble to the work of the monitoring department

Many monitoring personnel have low professional quality and lack the ability to analyze and process data scientifically and effectively, resulting in low credibility of data and loss of evaluation significance

Due to the various types of environmental monitoring and the huge amount of data, most auditors lack research on the rationality of the data and the standardization of the report, etc., and the audit is often a mere formality. The work fell into a passive state, and even caused undue losses to the monitoring station

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