CN-122010285-A - Intelligent algae monitoring method and system based on floating bed process

CN122010285ACN 122010285 ACN122010285 ACN 122010285ACN-122010285-A

Abstract

The invention discloses an alga intelligent monitoring method and system based on a floating bed process, comprising the steps of constructing a floating bed regional map model; the method comprises the steps of collecting multidimensional algae and environmental parameters before and after floating bed regulation, carrying out linear regression prediction on the serialization parameters to form new parameter data, vectorizing the parameters to obtain algae and environmental characteristic vectors, introducing hierarchical clustering algorithm to evaluate regional characteristic similarity, analyzing algae propagation migration direction and environment matching region, comparing and analyzing algae migration trend and environment change before and after regulation, evaluating floating bed regulation effectiveness and optimizing a floating bed setting scheme. The invention realizes intelligent monitoring of algae and prediction of water ecology multipoint trend, accurately identifies algae migration rules, scientifically evaluates the effectiveness of floating bed arrangement, effectively relieves water deterioration, improves water ecology regulation and control efficiency, and reduces early warning hysteresis.

Inventors

HONG CHANGHONG
YANG FENGJUAN
LIU DA
LIU SHUAI
Xiao Gengfeng
Mai Yingwen

Assignees

广东省水利水电科学研究院

Dates

Publication Date: 20260512
Application Date: 20260413

Claims (10)

1. An intelligent algae monitoring method based on a floating bed process is characterized by comprising the following steps: s11, constructing a map model according to the ecological floating bed area; S12, collecting multidimensional algae parameters and ecological environment parameters of the floating bed area and the adjacent area through a monitoring unit in a period before ecological regulation; S13, carrying out time dimension serialization on the multidimensional algae parameters and the ecological environment parameters, carrying out data prediction on the algae parameters and the environment parameters for a preset period of time through a linear regression prediction model, inserting predicted values into the algae parameters and the ecological environment parameters, and carrying out vectorization on the multidimensional parameters to form algae change feature vectors and environment change feature vectors; s14, introducing a hierarchical clustering algorithm, carrying out floating bed multi-region feature similarity evaluation according to the algae change feature vector and the environment change feature vector as input, and analyzing an algae propagation migration direction and environment matching region based on the floating bed region through a clustering result; And S15, collecting multidimensional parameters of the floating bed area and the adjacent area through a monitoring unit, analyzing the algae propagation migration direction and the environment matching area in a period after the ecological regulation, carrying out algae propagation migration trend evaluation and environment state change analysis in a period before the ecological regulation, carrying out effectiveness evaluation based on the ecological regulation on the floating bed, and optimizing a floating bed setting scheme.
2. The intelligent monitoring method of algae based on the floating bed process of claim 1, wherein the step S11 is specifically: carrying out three-dimensional map construction according to the shape and the area of the ecological floating bed area, the arrangement of monitoring points and the floating bed setting scheme information to form a visual map model; in the map model, each monitoring point corresponds to at least one monitoring unit and comprises a floating bed setting area; at least one floating bed and a water body purifying device are included in the floating bed setting area.
3. The intelligent monitoring method of algae based on the floating bed process of claim 1, wherein S12 specifically comprises: setting a plurality of monitoring time points in a period before ecological regulation, and collecting multidimensional algae parameters and ecological environment parameters of a floating bed area and an adjacent area through a monitoring unit; The algae parameters are monitored through water sampling, and the algae parameters comprise preset algae biomass, algae species number and preset algae duty ratio; The ecological environment parameters comprise dissolved oxygen, water temperature, pH value, total nitrogen and total phosphorus parameters.
4. The intelligent monitoring method of algae based on the floating bed process of claim 1, wherein S13 specifically comprises: selecting one parameter from multidimensional algae parameters or ecological environment parameters for serialization, and obtaining a first sequence; introducing a linear regression prediction model, carrying out sequence prediction on the first sequence, taking sequence points as dependent variables, taking time as independent variables, and carrying out prediction based on a preset step length to obtain a plurality of predicted values; inserting a plurality of predicted values into the end section of the first sequence by using an intermediate interpolation method, and obtaining a second sequence; Performing linear fitting on the second sequence based on linear regression, and taking a fitting coefficient as a parameter regression variation value; And calculating parameter regression variation values of the multidimensional algae parameters and the ecological environment parameters, and forming algae variation feature vectors and environment variation feature vectors based on algae and environment dimensions respectively.
5. The intelligent monitoring method of algae based on the floating bed process of claim 1, wherein S14 specifically comprises: Calculating and obtaining algae change characteristic vectors and environment change characteristic vectors corresponding to the floating bed area and the adjacent area; The algae change feature vector and the environment change feature vector of each area are used as two clustering inputs, and the algae and the environment change feature cluster analysis of the areas is carried out in a bottom-up mode through a hierarchical clustering algorithm; In the clustering process, a merging rule is set, wherein the merging rule is to judge whether the similarity of the change feature vectors corresponding to the two areas is in a preset range, judge whether the two areas are adjacent areas, introduce Euclidean distance calculation into the similarity, if the two judgments are yes, merge the two areas to be used as a cluster, and meanwhile, the change feature vectors corresponding to the floating bed area can be clustered and merged for multiple times; Carrying out cyclic data merging on clustering input until the preset iteration times or the number of clustering areas is larger than a preset value, and obtaining a first clustering result and a second clustering result; In the first clustering result, analyzing a cluster in which the floating bed area is positioned, calculating the directions of central points of the floating bed area and the rest adjacent areas in the cluster, and taking the directions as the propagation and migration directions of algae; And in the second clustering result, analyzing a cluster where the floating bed area is located, and marking the adjacent area in the cluster as an environment matching area.
6. The intelligent monitoring method of algae based on the floating bed process of claim 1, wherein the step S15 is specifically: In a period after ecological regulation, collecting multidimensional algae parameters and environment parameters of a floating bed area and an adjacent area through a monitoring unit, and analyzing an algae propagation migration direction and environment matching area; Before and after ecological regulation, analyzing and calculating the change rate of the propagation and migration direction of algae and analyzing the descending trend of the matching areas according to the number of the environment matching areas; carrying out effectiveness evaluation of ecological regulation according to the change rate of the migration direction and the descending trend of the matching area; And optimizing the floating bed setting scheme according to the evaluation result.
7. The method of intelligent monitoring of algae based on a floating bed process of claim 6, comprising sending the evaluation result and the floating bed setting scheme to a preset terminal.
8. The method of intelligent monitoring of algae based on a floating bed process of claim 1, wherein the vicinity comprises a plurality of.
9. The intelligent algae monitoring system based on the floating bed process is characterized by comprising a memory, a central processing unit and a data interface, wherein the memory comprises an intelligent algae monitoring program based on the floating bed process, and the intelligent algae monitoring program based on the floating bed process is executed by the central processing unit to realize the following steps: s11, constructing a map model according to the ecological floating bed area; S12, collecting multidimensional algae parameters and ecological environment parameters of the floating bed area and the adjacent area through a monitoring unit in a period before ecological regulation; S13, carrying out time dimension serialization on the multidimensional algae parameters and the ecological environment parameters, carrying out data prediction on the algae parameters and the environment parameters for a preset period of time through a linear regression prediction model, inserting predicted values into the algae parameters and the ecological environment parameters, and carrying out vectorization on the multidimensional parameters to form algae change feature vectors and environment change feature vectors; s14, introducing a hierarchical clustering algorithm, carrying out floating bed multi-region feature similarity evaluation according to the algae change feature vector and the environment change feature vector as input, and analyzing an algae propagation migration direction and environment matching region based on the floating bed region through a clustering result; And S15, collecting multidimensional parameters of the floating bed area and the adjacent area through a monitoring unit, analyzing the algae propagation migration direction and the environment matching area in a period after the ecological regulation, carrying out algae propagation migration trend evaluation and environment state change analysis in a period before the ecological regulation, carrying out effectiveness evaluation based on the ecological regulation on the floating bed, and optimizing a floating bed setting scheme.
10. A computer readable storage medium, wherein the computer readable storage medium includes an intelligent algae monitoring program based on a floating bed process, and the intelligent algae monitoring program based on the floating bed process realizes the steps of the intelligent algae monitoring method based on the floating bed process according to any one of claims 1 to 8 when being executed by a central processor.

Description

Intelligent algae monitoring method and system based on floating bed process Technical Field The invention relates to the field of floating bed technology and ecological monitoring, in particular to an intelligent algae monitoring method and system based on the floating bed technology. Background The drinking water source reservoir is a core guarantee for urban and rural water supply, and the water quality safety of the drinking water source reservoir is directly related to public health. At present, the floating bed technology has become one of key technologies of reservoir eutrophication, pollution control and ecological regulation because of being ecological-friendly, stable in algae control effect and strong in ecological regulation capability, but the application of the existing floating bed has obvious short plates. The existing floating bed technology only focuses on the condition that aquatic plants absorb and purify certain pollutants, lacks the condition of comprehensively evaluating ecological pollution such as algae propagation by combining multiple dimensions, is influenced by factors such as ecological competition, pollutant migration at the upstream and downstream, different space settings of a floating bed and the like, changes of the pollutants are complicated and diversified, so that the algae growth under the application of the ecological floating bed is difficult to evaluate trend, the traditional technology is often based on fixed-point timing sampling analysis, early warning lag often occurs, and complex influencing factors of the algae growth are difficult to comprehensively reflect by a predictive analysis means, so that intelligent ecological monitoring and water body tracking regulation are difficult to realize. Disclosure of Invention The invention overcomes the defects of the prior art and provides an intelligent algae monitoring method and system based on a floating bed process. The first aspect of the invention provides an intelligent algae monitoring method based on a floating bed process, which comprises the following steps: s11, constructing a map model according to the ecological floating bed area; S12, collecting multidimensional algae parameters and ecological environment parameters of the floating bed area and the adjacent area through a monitoring unit in a period before ecological regulation; S13, carrying out time dimension serialization on the multidimensional algae parameters and the ecological environment parameters, carrying out data prediction on the algae parameters and the environment parameters for a preset period of time through a linear regression prediction model, inserting predicted values into the algae parameters and the ecological environment parameters, and carrying out vectorization on the multidimensional parameters to form algae change feature vectors and environment change feature vectors; s14, introducing a hierarchical clustering algorithm, carrying out floating bed multi-region feature similarity evaluation according to the algae change feature vector and the environment change feature vector as input, and analyzing an algae propagation migration direction and environment matching region based on the floating bed region through a clustering result; And S15, collecting multidimensional parameters of the floating bed area and the adjacent area through a monitoring unit, analyzing the algae propagation migration direction and the environment matching area in a period after the ecological regulation, carrying out algae propagation migration trend evaluation and environment state change analysis in a period before the ecological regulation, carrying out effectiveness evaluation based on the ecological regulation on the floating bed, and optimizing a floating bed setting scheme. In this scheme, S11 specifically is: carrying out three-dimensional map construction according to the shape and the area of the ecological floating bed area, the arrangement of monitoring points and the floating bed setting scheme information to form a visual map model; in the map model, each monitoring point corresponds to at least one monitoring unit and comprises a floating bed setting area; at least one floating bed and a water body purifying device are included in the floating bed setting area. In this scheme, the S12 specifically is: setting a plurality of monitoring time points in a period before ecological regulation, and collecting multidimensional algae parameters and ecological environment parameters of a floating bed area and an adjacent area through a monitoring unit; The algae parameters are monitored through water sampling, and the algae parameters comprise preset algae biomass, algae species number and preset algae duty ratio; The ecological environment parameters comprise dissolved oxygen, water temperature, pH value, total nitrogen and total phosphorus parameters. In this scheme, the S13 specifically is: selecting one parameter from multidimensional algae par