CN-121995023-A - Water quality analysis and detection method and system based on sponge city engineering

CN121995023ACN 121995023 ACN121995023 ACN 121995023ACN-121995023-A

Abstract

The invention relates to the technical field of data processing, in particular to a hydrological water quality analysis and detection method and a hydrological water quality analysis and detection system based on sponge urban engineering, wherein the method respectively acquires monitoring data of various hydrological monitoring indexes and water quality monitoring indexes in a preset period before the current moment at each monitoring point of the sponge urban engineering; according to the data change synchronicity of each hydrologic monitoring index between each other monitoring point and the target monitoring point and the data change association degree of each water quality monitoring index, the normal water quality data of each water quality monitoring index at the target monitoring point at the current time is predicted to obtain the final predicted value of each water quality monitoring index at the current time, and according to the difference between the actual monitoring data and the final predicted value of each water quality monitoring index at the target monitoring point at the current time, the water quality abnormality of the target monitoring point at the current time is detected, so that the accuracy of detecting the water quality abnormality of the sponge city engineering is improved.

Inventors

WANG XINLIANG
WANG QINGPENG
YANG QINGHE
ZHANG XUEGANG
DAI CHANGSHENG
WEI YINGYING
Lou Yizhang
WANG ANDONG
SUN HAO
MIN ZHENG
DONG YUEFENG

Assignees

中铁十六局集团有限公司
陕西铁路工程职业技术学院
中铁十六局集团路桥工程有限公司

Dates

Publication Date: 20260508
Application Date: 20260204

Claims (10)

1. The water quality analysis and detection method based on the sponge city engineering is characterized by comprising the following steps of: at least two monitoring points of the sponge city engineering, respectively acquiring monitoring data of each hydrologic monitoring index and each water quality monitoring index at each moment in a preset period before the current moment; Marking any monitoring point as a target monitoring point, and acquiring the water quality response degree of each water quality monitoring index at the target monitoring point according to the data change synchronicity of each hydrologic monitoring index between each other monitoring point except the target monitoring point and the target monitoring point in the preset time period and the association degree of each water quality monitoring index between each other monitoring point and the target monitoring point in the data change in the preset time period; Predicting normal water quality data of any water quality monitoring index at the target monitoring point at the current moment according to the monitoring data of any water quality monitoring index at the target monitoring point at each non-pollution moment in the preset period and the water quality response degree of any water quality monitoring index at the target monitoring point to obtain a final predicted value; According to the difference between the actual monitoring data of any water quality monitoring index at the target monitoring point at the current time and the final predicted value, the abnormal degree of any water quality monitoring index at the target monitoring point at the current time is obtained, and according to the abnormal degree of each water quality monitoring index at each monitoring point at the current time, the abnormal water quality condition of each monitoring point at the current time is detected.
2. The sponge city engineering-based water quality analyzing and detecting method as set forth in claim 1, wherein said obtaining the water quality response level of each water quality monitoring indicator at the target monitoring point comprises: aiming at any other monitoring point, according to the data change synchronicity of each hydrologic monitoring index between the any other monitoring point and the target monitoring point in the preset period, acquiring the influence degree of the any other monitoring point on the water quality condition at the target monitoring point; according to the association degree of the data change of each water quality monitoring index between any other monitoring point and the target monitoring point in the preset period, respectively acquiring the water quality contribution degree of each water quality monitoring index of the target monitoring point by any other monitoring point and the water quality influence lag time; The influence degree of each other monitoring point on the water quality condition of the target monitoring point is obtained, the water quality contribution degree and the water quality influence lag time of each other monitoring point on each water quality monitoring index of the target monitoring point are obtained, and the water quality response degree of each water quality monitoring index of the target monitoring point is obtained according to the influence degree of each other monitoring point on the water quality condition of the target monitoring point, the water quality contribution degree and the water quality influence lag time of each other monitoring point on each water quality monitoring index of the target monitoring point.
3. The sponge city engineering-based water quality analyzing and detecting method according to claim 2, wherein said obtaining the influence degree of any other monitoring point on the water quality condition at the target monitoring point according to the data change synchronicity of each hydrologic monitoring index between the any other monitoring point and the target monitoring point within the preset period comprises: According to the data change consistency degree of each hydrologic monitoring index between each other monitoring point and the target monitoring point in the preset period, acquiring the influence weight of each hydrologic monitoring index; The method comprises the steps of forming multi-dimensional hydrologic data by monitoring data of each hydrologic monitoring index of a target monitoring point at each moment in the preset period, forming a multi-dimensional data sequence by multi-dimensional hydrologic data at all moments according to time sequence, marking the multi-dimensional data sequence as a target multi-dimensional data sequence, obtaining a multi-dimensional data sequence corresponding to any other monitoring point, marking the multi-dimensional data sequence as a multi-dimensional data sequence to be analyzed, and obtaining indexes of each multi-dimensional hydrologic data according to the positions of each multi-dimensional hydrologic data in the target multi-dimensional data sequence and the multi-dimensional data sequence to be analyzed; Obtaining a preset lag data sequence, wherein the minimum value in the preset lag data sequence is 0, subtracting any lag data from the index of each multi-dimensional hydrologic data in the multi-dimensional data sequence to be analyzed according to any lag data in the lag time sequence to obtain a new index of each multi-dimensional hydrologic data in the multi-dimensional data sequence to be analyzed, calculating a weighted Euclidean distance between the multi-dimensional hydrologic data in a multi-dimensional space when each two indexes are the same and corresponding moments are non-pollution according to the influence weight of each hydrologic monitoring index, and calculating the average value of all weighted Euclidean distances to obtain the data difference degree between any other monitoring point and a target monitoring point under any lag data; And acquiring the data difference degree between any other monitoring point and the target monitoring point under each hysteresis data in the hysteresis data sequence, acquiring the minimum value of all the data difference degrees, taking the opposite number of the minimum value as an independent variable of an exponential function taking a natural constant as a base number, and acquiring the influence degree of any other monitoring point on the water quality condition at the target monitoring point.
4. The sponge city engineering-based water quality analyzing and detecting method according to claim 3, wherein said obtaining the influence weight of each hydrologic monitoring index according to the data change consistency degree of each hydrologic monitoring index between each other monitoring point and the target monitoring point in the preset time period comprises: Aiming at any hydrologic monitoring index, if a target monitoring point has a pollution moment in the preset time period, acquiring fitting data of the target monitoring point at each pollution moment of the any hydrologic monitoring index in the preset time period by using a spline interpolation method according to monitoring data of the target monitoring point at each non-pollution moment of the target monitoring point in the preset time period, forming a hydrologic data sequence by the monitoring data of the target monitoring point at each non-pollution moment of the any hydrologic monitoring index in the preset time period and the fitting data of the pollution moment, and if the target monitoring point does not have the pollution moment in the preset time period, forming a hydrologic data sequence by the monitoring data of the target monitoring point at each non-pollution moment of the any hydrologic monitoring index in the preset time period; Acquiring a hydrological data sequence of any one hydrological monitoring index at any other monitoring point in the preset period, wherein a calculation formula of the data change consistency degree of any one hydrological monitoring index between any other monitoring point and a target monitoring point is as follows: ; Wherein, the Represents any one of the hydrologic monitoring indexes, d represents any one of the other monitoring points, Representing the degree of data change consistency of any one of the hydrologic monitoring indexes between any one of the other monitoring points and the target monitoring point, Representing the number of all data in the sequence of hydrologic data, Representing the difference value of the ith data minus the ith-1 th data in the hydrological data sequence corresponding to any hydrological monitoring index at the target monitoring point, Representing the difference value of the ith data minus the ith-1 th data in the hydrologic data sequence corresponding to any one hydrologic monitoring index at any other monitoring point, The predetermined constant is indicated to be a predetermined constant, Representing a linear normalization function; Acquiring the data change consistency degree of any hydrologic monitoring index between each other monitoring point and the target monitoring point, clustering all the data change consistency degrees to obtain at least one cluster, acquiring clusters with the largest number of members, calculating the average value of all the data change consistency degrees in the clusters with the largest number of members if only one cluster with the largest number of members exists, obtaining the data expression degree of any hydrologic monitoring index, and respectively calculating the average value of all the data change consistency degrees in the clusters with the largest number of members if at least two clusters with the largest number of members exist, and selecting the maximum value as the data expression degree of any hydrologic monitoring index in the average value corresponding to the clusters with the largest number of members; respectively obtaining standard deviations of the monitoring data of any hydrologic monitoring index at each monitoring point at all non-pollution moments within the preset period, and carrying out normalization processing on the average value of all standard deviations to obtain the fluctuation degree of any hydrologic monitoring index; and calculating the product of the fluctuation degree of any one hydrologic monitoring index and the data expression degree to obtain the influence weight of any one hydrologic monitoring index.
5. The sponge city engineering-based water quality analysis and detection method according to claim 2, wherein the respectively obtaining the water quality contribution degree of each water quality monitoring index of any other monitoring point to the target monitoring point and the water quality influence lag time according to the association degree of each water quality monitoring index between the any other monitoring point and the target monitoring point in the data change within the preset period comprises the following steps: Forming multi-dimensional hydrologic data by monitoring data of each hydrologic monitoring index at any other monitoring point at each non-pollution time within the preset period, carrying out multi-dimensional clustering on all the multi-dimensional hydrologic data to obtain at least one cluster, marking the cluster at the previous time of the current time as a target cluster, marking any time in the target cluster as a target time if any time in the target cluster is a non-pollution time at the target monitoring point, acquiring all the target time in the target cluster, and forming at least two target time with continuous time sequence into a period to be analyzed; Aiming at any period to be analyzed, the monitoring data of any water quality monitoring index at a target monitoring point at each moment in the period to be analyzed is formed into a water quality data sequence, a first-order differential sequence of the water quality data sequence is obtained and is recorded as a differential sequence of the any water quality monitoring index at the target monitoring point in the period to be analyzed, and a differential sequence of the any water quality monitoring index at any other monitoring point in the period to be analyzed is obtained; mapping the differential sequences corresponding to the target monitoring point and any other monitoring point into a two-dimensional coordinate system to respectively obtain waveform diagrams corresponding to the target monitoring point and any other monitoring point, wherein the abscissa of the two-dimensional coordinate system represents time, the ordinate represents data in the differential sequence, a preset lag time sequence is obtained, the waveform diagrams corresponding to any other monitoring point are translated to any lag time in the preset lag time sequence by the any lag time in the opposite direction of the abscissa, the pearson correlation coefficient between two waveforms corresponding to overlapped parts of the abscissa in the two-dimensional coordinate system is calculated, and the correlation degree of any water quality monitoring index between any other monitoring point and the target monitoring point in any lag time is obtained; Obtaining the association degree corresponding to each lag time in the preset lag time sequence, selecting the maximum value from all association degrees as the association characteristic value of any water quality monitoring index between any other monitoring point and the target monitoring point in any period to be analyzed, and recording the lag time corresponding to the association characteristic value as the delay time of any water quality monitoring index between any other monitoring point and the target monitoring point in any period to be analyzed; And obtaining the associated characteristic value and the delay time corresponding to each period to be analyzed, calculating the average value of all the associated characteristic values to obtain the water quality contribution degree of any one of the other monitoring points to any one of the water quality monitoring indexes at the target monitoring point, and calculating the average value of all the delay times to obtain the water quality influence lag time of any one of the other monitoring points to any one of the water quality monitoring indexes at the target monitoring point.
6. The sponge city engineering-based water quality analyzing and detecting method as set forth in claim 2, wherein said obtaining the water quality response level of each water quality monitoring index at the target monitoring point based on the influence level of each other monitoring point on the water quality condition at the target monitoring point, and the water quality contribution level and the water quality influence lag time of each other monitoring point on each water quality monitoring index at the target monitoring point, comprises: Calculating the product of the water quality contribution degree of any other monitoring point to any water quality monitoring index at the target monitoring point and the influence degree of any other monitoring point to the water quality condition at the target monitoring point aiming at any water quality monitoring index to obtain the influence weight of any other monitoring point to any water quality monitoring index at the target monitoring point; Subtracting the water quality influence lag time of any other monitoring point on any water quality monitoring index at the target monitoring point from the current time according to the water quality influence lag time of any other monitoring point on any water quality monitoring index at the target monitoring point to obtain a water quality influence time, and subtracting the monitoring data of any water quality monitoring index at any other monitoring point at the time of water quality influence from the monitoring data of any water quality monitoring index at the time of water quality influence to obtain the water quality data change quantity of any water quality monitoring index at any other monitoring point at the time of water quality influence; The influence weight of each other monitoring point on any water quality monitoring index at the target monitoring point and the water quality data change quantity of any water quality monitoring index at each other monitoring point at the time of water quality influence are obtained, and the water quality data change quantity corresponding to each other monitoring point is weighted and summed according to the weight corresponding to each other monitoring point to obtain the water quality response degree of any water quality monitoring index at the target monitoring point.
7. The sponge city engineering-based water quality analysis and detection method according to claim 1, wherein predicting the normal water quality data of any water quality monitoring index at the target monitoring point at the current time according to the monitoring data of any water quality monitoring index at the target monitoring point at each non-pollution time within the preset period and the water quality response degree of any water quality monitoring index at the target monitoring point to obtain a final predicted value comprises: If the target monitoring point has pollution time in the preset time period, acquiring fitting data of any water quality monitoring index in the target monitoring point at each pollution time in the preset time period according to monitoring data of any water quality monitoring index in the target monitoring point at each non-pollution time in the preset time period by using a spline interpolation method, and forming a normal water quality data sequence of any water quality monitoring index in the target monitoring point from the monitoring data of any water quality monitoring index in the target monitoring point at each non-pollution time in the preset time period and the fitting data of the target monitoring point at the pollution time period if the target monitoring point does not have pollution time in the preset time period, and forming a normal water quality data sequence from the monitoring data of any water quality monitoring index in the target monitoring point at each time in the preset time period; According to the normal water quality data sequence, predicting normal water quality data of any water quality monitoring index at a target monitoring point at the current moment by using a preset prediction algorithm to obtain an initial predicted value; And calculating the sum of the water quality response degree of any water quality monitoring index at the target monitoring point and the initial predicted value to obtain a final predicted value.
8. The sponge city engineering-based water quality analyzing and detecting method according to claim 1, wherein said obtaining the abnormality degree of any one of the water quality monitoring indexes at the target monitoring point at the current time according to the difference between the actual monitoring data of the any one of the water quality monitoring indexes at the target monitoring point at the current time and the final predicted value comprises: And calculating the absolute value of the difference value between the actual monitoring data of any water quality monitoring index at the target monitoring point at the current time and the final predicted value to obtain the abnormality degree of any water quality monitoring index at the target monitoring point at the current time.
9. The sponge city engineering-based water quality analysis and detection method according to claim 1, wherein the detecting the abnormal condition of the water quality of each monitoring point at the current time according to the abnormal degree of each water quality monitoring index at each monitoring point at the current time comprises: And aiming at any water quality monitoring index, acquiring the historical abnormality degree of any water quality monitoring index at each monitoring point at each non-pollution time within the preset period, acquiring the normal range of any water quality monitoring index by utilizing a 3sigma principle according to all the historical abnormality degrees, and carrying out abnormality alarm on any water quality monitoring index at any monitoring point if the abnormality degree of any water quality monitoring index at any monitoring point at the current time is not in the normal range.
10. A water quality analysis and detection system based on sponge urban engineering, comprising a memory, a processor and a computer program stored in the memory and running on the processor, characterized in that the processor, when executing the computer program, realizes the steps of the water quality analysis and detection method based on sponge urban engineering according to any one of claims 1-9.

Description

Water quality analysis and detection method and system based on sponge city engineering Technical Field The invention relates to the technical field of data processing, in particular to a water quality analysis and detection method and system based on sponge urban engineering. Background The sponge city engineering is a comprehensive city water system engineering which realizes the functions of accumulating, penetrating, purifying and the like of natural rainwater through a series of ecological management means. The analysis and detection of water quality are key to guaranteeing the running state and running efficiency of the sponge city engineering, and the water quality detection mainly detects the quality and component status of water, is used for drinking water safety, pollution early warning, water treatment effect evaluation and the like, and provides data support for facility optimization and water safety management of the sponge city engineering by carrying out real-time monitoring and evaluation on the water quality condition. The existing water quality detection method mainly sets a threshold value for each piece of monitoring data, and carries out abnormal alarm for the data exceeding the threshold value. However, the actual hydrologic condition often has a great influence on water quality data, such as runoff flow increase caused by heavy rain, which often causes change of pollutant migration conditions, and the traditional detection method is difficult to distinguish the water quality data abnormality caused by hydrologic condition change and real pollution event, and ignores the pollutant migration condition, so that the false alarm rate is higher. Therefore, how to improve the accuracy of detecting abnormal water quality in sponge urban engineering is a problem to be solved. Disclosure of Invention In view of the above, the embodiment of the invention provides a water quality analysis and detection method and a system based on sponge urban engineering, which are used for solving the problem of how to improve the accuracy of detecting the abnormal condition of the water quality of the sponge urban engineering. In a first aspect, an embodiment of the present invention provides a water quality analysis and detection method based on sponge urban engineering, the method including the following steps: at least two monitoring points of the sponge city engineering, respectively acquiring monitoring data of each hydrologic monitoring index and each water quality monitoring index at each moment in a preset period before the current moment; Marking any monitoring point as a target monitoring point, and acquiring the water quality response degree of each water quality monitoring index at the target monitoring point according to the data change synchronicity of each hydrologic monitoring index between each other monitoring point except the target monitoring point and the target monitoring point in the preset time period and the association degree of each water quality monitoring index between each other monitoring point and the target monitoring point in the data change in the preset time period; Predicting normal water quality data of any water quality monitoring index at the target monitoring point at the current moment according to the monitoring data of any water quality monitoring index at the target monitoring point at each non-pollution moment in the preset period and the water quality response degree of any water quality monitoring index at the target monitoring point to obtain a final predicted value; According to the difference between the actual monitoring data of any water quality monitoring index at the target monitoring point at the current time and the final predicted value, the abnormal degree of any water quality monitoring index at the target monitoring point at the current time is obtained, and according to the abnormal degree of each water quality monitoring index at each monitoring point at the current time, the abnormal water quality condition of each monitoring point at the current time is detected. In a second aspect, an embodiment of the present invention further provides a water quality analysis and detection system based on a sponge urban engineering, including a memory, a processor, and a computer program stored in the memory and running on the processor, where the processor implements the water quality analysis and detection method based on the sponge urban engineering according to the first aspect when executing the computer program. Compared with the prior art, the embodiment of the invention has the beneficial effects that: According to the method, according to the data change synchronism of various hydrologic monitoring indexes between each other monitoring point except the target monitoring point and the target monitoring point, the circulation relation between the other monitoring points and the target monitoring point is analyzed, so that the influence degree of water q