CN113159130B - Construction sewage treatment method - Google Patents
Construction sewage treatment method Download PDFInfo
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- CN113159130B CN113159130B CN202110318743.3A CN202110318743A CN113159130B CN 113159130 B CN113159130 B CN 113159130B CN 202110318743 A CN202110318743 A CN 202110318743A CN 113159130 B CN113159130 B CN 113159130B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F1/00—Treatment of water, waste water, or sewage
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Abstract
The invention discloses a construction sewage treatment method, which comprises the steps of obtaining the position information of a pollution source and the types of pollutants contained in the position information of the pollution source; integrating the pollution to display that the pollution coefficient meets the value condition; according to distribution condition conditions required to be met by displaying the distribution condition of the pollution coefficient, converting the displayed pollution coefficient to obtain real-time pollution source position information; training a pollution source detection network model based on a training sample set reconstructed based on the integrated pollution source position information and the real-time pollution source position information and the types of the included pollutants; and inputting the position information of the pollution source to be predicted and the reference pollutant information marked with the type of the pollutant into the pollution source detection network model based on the trained pollution source detection network model, and determining the type of the pollutant. The pollution source and the corresponding pollutants can be detected in real time, so that timely treatment can be realized, and the pollution range is effectively prevented from being enlarged.
Description
Technical Field
The invention relates to the technical field of timely detection of pollution sources, in particular to a construction sewage treatment method.
Background
Numerous projects are located in mountainous area and hilly areas, some projects even comprise drinking water source areas or drinking water source conservation areas, and the projects mostly belong to serious disaster areas with water and soil loss in China, the ecological environment is very fragile, and if a large amount of sewage generated in the project construction process cannot be properly treated and is discharged, the pollution to the mountainous area environment, particularly the water environment, is certainly caused, so that the problem of construction sewage is highly emphasized, and the relationship between the construction and the original ecological environment resource is coordinated.
The sewage sources in the construction process mainly include the following: the method comprises the following steps of water burst generated when the tunnel passes through a bad geological unit, sewage generated by construction machinery, sewage generated after blasting in drilling and blasting construction and used for dust fall, sewage generated by concrete spraying and grouting, bedrock fracture water and the like. According to past construction experience, the discharged sewage flow has large change from several cubes per hour to hundreds of cubes per hour, and is mainly influenced by many factors such as unfavorable geology, construction progress and the like.
"high turbidity water" refers to a source of river water or river water with a high sand content or turbidity. The design criteria of the high-turbidity water supply water are as follows: the high-turbidity water refers to a sand-containing water body with higher turbidity and clear crowded and subsided interface, and the sand content of the water body is 10kg/m 3 -100kg/m 3 . In the construction process, sudden disasters such as collapse, faults, water burst and the like are easy to occur under the action of penetrating through a fold development section, passing through a fault fracture zone and blasting vibration force.
The main pollution characteristic of the sudden disaster is high turbidity pollution, and SS of produced sewage is more than or equal to 20000mg/L. The most effective method for removing turbidity is chemical coagulation sedimentation method, but the conventional coagulation sedimentation method is not satisfactory in the face of high-turbidity water pollution caused by sudden disasters. The limitations of conventional coagulation treatment of high turbidity water are mainly shown in:
(1) The treatment cost is high. The high-turbidity water treatment has higher requirement on the turbidity removal rate, the traditional coagulating sedimentation treatment efficiency is limited, and researches show that the addition amount of a coagulant has a direct relation on the removal of pollutants, and the turbidity removal rate is generally improved by improving the amount of the coagulant in the high-turbidity water treatment, so that the treatment cost is increased.
(2) The quality of the effluent is poor. The coagulant dosage is too high, which can cause the destabilized colloid system to be re-stabilized, the turbidity to be increased and the effluent quality not to be guaranteed; on the other hand, the content of the wrong salt in the effluent is increased, and the water quality safety does not meet the requirement.
(3) The occupied area of the equipment is large. The hydraulic power charge on the surface of the conventional coagulating sedimentation tank is generally about 1m < 3 >/(m < 2 >. H), namely when the treatment capacity of equipment is 10m < 3 >/h, the area of the sedimentation tank needs 10m < 2 >, the occupied area of the equipment is large, the transportation is inconvenient in sudden disasters, the sedimentation time of a coagulating sedimentation tank for frequent scars is not less than 30min, and the sedimentation time is too long, so that the coagulating sedimentation tank is not suitable for emergency water treatment.
Therefore, the traditional chemical coagulation sedimentation technology for treating high-turbidity sewage can not meet the requirement of water outlet, and the converter unit length and the medicine consumption are high during the conventional coagulation sedimentation, the equipment floor area is large, and the traditional chemical coagulation sedimentation technology is not suitable for being used in the field of high-turbidity construction sewage caused by sudden disasters.
Disclosure of Invention
The technical problem to be solved by the invention is the technical problem of the background technology, and the invention aims to provide a construction sewage treatment method, which solves the problem of timely detection of a pollution source on a construction site.
The invention is realized by the following technical scheme:
a method of construction sewage treatment, the method comprising:
obtaining contamination source location information and a type of a contaminant included in the contamination source location information;
integrating the display pollution coefficient of the pollution source position information to meet a value taking condition;
according to the distribution condition which needs to be met by the distribution condition of the display pollution coefficients, the display pollution coefficients of the pollution source position information are transformed to obtain real-time pollution source position information;
training a pollution source detection network model based on a training sample set reconstructed by the integrated pollution source position information and the real-time pollution source position information and the types of the included pollution substances;
based on the trained pollution source detection network model, inputting the position information of the pollution source to be predicted and the reference pollutant information marked with the type of the pollutant into the pollution source detection network model, and determining the type of the pollutant included in the position information of the pollution source to be predicted, wherein the type of the pollutant includes: metal pollution, chemical pollution, building slag pollution and sewage pollution, and is used for assisting in identifying the characteristics of different degrees of environmental pollution of pollutants.
Further, the integrating the display pollution coefficient of the pollution source position information satisfies a value condition, including:
detecting a contaminated region of a contaminant included in the contaminant source location information;
and integrating the position of the pollution source position information until the position of a pollution area of the pollutant included in the pollution source position information is consistent.
Further, the integrating the display pollution coefficient of the pollution source position information satisfies a value condition, including:
and carrying out pollution enhancement treatment on each color channel of the pollution source position information based on the pollution identification degree required to be met by the pollution source position information.
Further, the integrating the display pollution coefficient of the pollution source position information satisfies a value condition, including:
removing uncontaminated areas of corresponding pollutants in the position information of the pollution sources;
and integrating the position information of the removed pollution source to accord with a preset position.
Further, the transforming the display pollution coefficient of the pollution source location information according to the distribution of the display pollution coefficient and the distribution condition that needs to be satisfied according to the distribution condition of the display pollution coefficient to obtain the real-time pollution source location information includes:
determining a display pollution coefficient which is defective according to the display pollution coefficient of the pollution source position information compared with the distribution condition according to a value space where the display pollution coefficient of at least one type of the pollution source position information is located and the distribution condition satisfied by the value space;
and transforming the display pollution coefficient of the pollution source position information to the display pollution coefficient of the defect to obtain real-time pollution source position information.
Further, the training pollution source detection network model includes:
initializing a pollution source detection network model;
initializing a distance calculation layer, a full connection layer and a classification layer which are sequentially connected with the pollution source detection network model to obtain a combined pollution source detection network model for classifying the position information of the pollution source to be predicted, and inputting the pollution and the corresponding types included in the training sample set into the pollution source detection network model for iterative calculation until the loss function of the pollution source detection network model meets the convergence condition.
Further, the step of inputting, based on the trained pollution source detection network model, the pollution source location information to be predicted and reference pollutant information labeled with the type of the pollutant into the pollution source detection network model, and determining the type of the pollutant included in the pollution source location information to be predicted includes:
in a combined pollution source detection network model, extracting pollution characteristics of pollution source position information to be predicted and pollution characteristics of reference pollutant information marked with the types of pollutants by using the combined pollution source detection network model, wherein the reference pollutant information is the concentrated pollution of the training sample;
determining the pollution characteristics of the position information of the pollution source to be predicted and the error vector of the pollution characteristics of the reference pollutant information, and performing down-sampling processing on the error vector;
and mapping the error vector after the down-sampling processing to a specific value space to obtain the probability that the position information of the pollutant source to be predicted belongs to the type of the pollutant marked by the reference pollutant information.
Further, before the training a pollution source detection network model based on the reconstructed training sample set of the integrated pollution source location information and the real-time pollution source location information and the types of the included pollutants, the method further includes:
and reconstructing a training sample set based on the integrated pollution source position information and the real-time pollution source position information in pairs.
Compared with the prior art, the invention has the following advantages and beneficial effects:
the invention relates to a construction sewage treatment method, which comprises the steps of obtaining the position information of a pollution source and the types of pollutants contained in the position information of the pollution source; integrating the display pollution coefficient of the pollution source position information to meet a value taking condition; according to distribution condition conditions required to be met by displaying the distribution condition of the pollution coefficient, converting the displayed pollution coefficient of the pollution source position information to obtain real-time pollution source position information; training a pollution source detection network model based on a training sample set reconstructed based on the integrated pollution source position information and the real-time pollution source position information and the types of the included pollutants; based on the trained pollution source detection network model, inputting the position information of the pollution source to be predicted and the reference pollutant information marked with the type of the pollutant into the pollution source detection network model, and determining the type of the pollutant included in the position information of the pollution source to be predicted. The pollution source and the corresponding pollutants can be detected in real time, so that the pollution source and the corresponding pollutants can be treated in time, and the pollution range is effectively prevented from being enlarged.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is a flow chart of a method for treating construction wastewater according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. The following description refers to the accompanying drawings in which the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the application, as detailed in the appended claims.
On the basis of the above, please refer to fig. 1, which is a schematic flow chart of a method for treating construction wastewater according to an embodiment of the present invention, and the method for treating construction wastewater specifically includes the following steps S21 to S25.
Step S21, obtaining contamination source location information and a type of a contaminant included in the contamination source location information.
And S22, integrating the display pollution coefficient of the pollution source position information to meet a value taking condition.
And S23, transforming the display pollution coefficients of the pollution source position information according to distribution condition conditions required to be met by the distribution condition of the display pollution coefficients to obtain real-time pollution source position information.
And S24, training a pollution source detection network model based on the reconstructed training sample set of the integrated pollution source position information and the real-time pollution source position information and the types of the included pollutants.
Step S25, based on the trained pollution source detection network model, inputting the position information of the pollution source to be predicted and the reference pollutant information marked with the type of the pollutant into the pollution source detection network model, and determining the type of the pollutant included in the position information of the pollution source to be predicted, wherein the type of the pollutant includes: metal pollution, chemical pollution, building slag pollution and sewage pollution, and is used for assisting in identifying the characteristics of different degrees of environmental pollution of pollutants
It is understood that, in executing the contents described in the above-described steps S21 to S25, the contamination source location information and the kind of the contaminant included in the contamination source location information are obtained; integrating the display pollution coefficient of the pollution source position information to meet a value taking condition; according to distribution condition conditions required to be met by displaying the distribution condition of the pollution coefficient, converting the displayed pollution coefficient of the pollution source position information to obtain real-time pollution source position information; training a pollution source detection network model based on a training sample set reconstructed based on the integrated pollution source position information and the real-time pollution source position information and the types of the included pollutants; based on the trained pollution source detection network model, inputting the position information of the pollution source to be predicted and the reference pollutant information marked with the type of the pollutant into the pollution source detection network model, and determining the type of the pollutant included in the position information of the pollution source to be predicted. The pollution source and the corresponding pollutants can be detected in real time, so that timely treatment can be carried out, the expansion of the pollution range is effectively avoided, the construction environment is better, the health of related technicians is protected, the condition that the related technicians leave a doctor is effectively reduced, and the cost is effectively saved.
In an actual operation process, the inventor finds that, when the display pollution coefficient integrating the pollution source location information meets the value taking condition, there is a technical problem that the display pollution coefficient is inaccurate, so that it is difficult to accurately obtain the meeting value taking condition, and in order to improve the technical problem, the step of integrating the display pollution coefficient of the pollution source location information meeting the value taking condition described in step S22 may specifically include the contents described in step S221 and step S222 below.
Step S221 of detecting a contaminated region of the contaminant included in the contamination source location information.
Step S222, integrating the position of the contamination source position information until the position of the contamination area of the contaminant included in the contamination source position information is consistent.
It can be understood that, when the contents described in the above steps S221 and S222 are executed, and the display pollution coefficient integrating the pollution source location information satisfies the value taking condition, the technical problem that the display pollution coefficient is not accurate is avoided, so that the value taking condition can be accurately satisfied.
In an actual operation process, the inventor finds that when the display pollution coefficient integrating the pollution source location information meets a value condition, there is a technical problem that the pollution source location information cannot be accurately determined, so that it is difficult to accurately obtain the value condition, and in order to improve the technical problem, the step of integrating the display pollution coefficient integrating the pollution source location information and meeting the value condition described in step S22 may specifically include the content described in the following step q 1.
And q1, performing pollution enhancement treatment on each color channel of the pollution source position information based on the pollution identification degree required to be met by the pollution source position information.
It can be understood that, when the content described in step q1 is executed and the display pollution coefficient integrating the pollution source location information satisfies the value taking condition, the technical problem that the pollution source location information cannot be accurately determined is avoided, so that the value taking condition can be accurately satisfied.
In an actual operation process, the inventor finds that when the display pollution coefficient integrating the pollution source location information meets a value taking condition, there is a technical problem that a pollution location is inaccurate, so that an uncontaminated area is brought into calculation, and thus, a workload of a data processing terminal is increased.
And r1, removing uncontaminated areas of the corresponding pollutants in the position information of the pollution sources.
And r2, integrating the position information of the removed pollution source to accord with a preset position.
It can be understood that, when the contents described in the above steps r1 and r2 are executed and the display pollution coefficient integrating the pollution source location information satisfies the value taking condition, the technical problem of inaccurate pollution location is avoided, so that the non-polluted area is eliminated, and the workload of the data processing terminal is reduced.
In an actual operation process, the inventor finds that, when the display pollution coefficient of the pollution source location information is transformed according to the distribution condition that needs to be satisfied by displaying the distribution condition of the pollution coefficient, there is a technical problem that the transformation is inaccurate, so that it is difficult to accurately obtain the real-time pollution source location information, and in order to improve the technical problem, the step of transforming the display pollution coefficient of the pollution source location information according to the distribution condition that needs to be satisfied by displaying the distribution condition of the pollution coefficient, which is described in step S23, to obtain the real-time pollution source location information, may specifically include the contents described in the following step S231 and step S232.
Step S231, determining a display pollution coefficient that is defective according to the display pollution coefficient of the pollution source location information compared with the distribution condition, according to a value space in which the display pollution coefficient of the at least one type of the pollution source location information is located and the distribution condition satisfied by the value space.
Step S232, converting the display pollution coefficient of the pollution source position information to the display pollution coefficient of the defect to obtain real-time pollution source position information.
It can be understood that, when the contents described in step S231 and step S232 are executed, and the distribution condition that needs to be satisfied according to the distribution condition of the pollution source location information is used to transform the pollution source location information, the technical problem of inaccurate conversion is avoided, so that the real-time pollution source location information can be accurately obtained.
In an actual operation process, the inventor finds that, when the pollutant source position information to be predicted and the reference pollutant information labeled with the type of the pollutant are input into the pollution source detection network model based on the trained pollution source detection network model, there is a technical problem of model calculation error, so that it is difficult to accurately determine the type of the pollutant included in the pollutant source position information to be predicted, and in order to improve the technical problem, step S25 describes that, the step of inputting the pollutant source position information to be predicted and the reference pollutant information labeled with the type of the pollutant into the pollution source detection network model based on the trained pollution source detection network model, and determining the type of the pollutant included in the pollutant source position information to be predicted may specifically include the contents described in the following steps S251 to S253.
Step S251, in the combined pollution source detection network model, extracting the pollution characteristics of the position information of the pollution source to be predicted and the pollution characteristics of the reference pollutant information marked with the type of the pollutant by using the combined pollution source detection network model, wherein the reference pollutant information is the concentrated pollution of the training sample.
Step S252, determining the pollution feature of the to-be-predicted pollution source location information and the error vector of the pollution feature of the reference pollutant information, and performing down-sampling processing on the error vector.
Step S253 of mapping the error vector after the down-sampling processing to a specific value space, to obtain a probability that the pollutant source location information to be predicted belongs to the type of the pollutant marked by the reference pollutant information.
It can be understood that, when the contents described in steps S251 to S253 are executed, when the pollution source detection network model based on training is used to input the pollution source location information to be predicted and the reference pollutant information labeled with the type of the pollutant into the pollution source detection network model, the technical problem of model calculation error is avoided, so that the type of the pollutant included in the pollution source location information to be predicted can be accurately determined.
Based on the above, before the training sample set reconstructed based on the integrated pollution source location information and the real-time pollution source location information and the types of the included pollutants, the method further includes the following steps described in p 1.
And step p1, reconstructing a training sample set based on the integrated pollution source position information and the real-time pollution source position information in pairs.
It can be understood that, when the content described in the above step p1 is executed, the pollution position can be accurately calculated, which effectively reduces the work task of the data processing terminal and makes the data processing faster.
The above-mentioned embodiments, objects, technical solutions and advantages of the present invention are further described in detail, it should be understood that the above-mentioned embodiments are only examples of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (5)
1. A method for treating construction sewage, which is characterized by comprising the following steps:
obtaining contamination source location information and a type of a contaminant included in the contamination source location information;
integrating the display pollution coefficient of the pollution source position information to meet a value taking condition;
according to the distribution condition which needs to be met by the distribution condition of the display pollution coefficients, the display pollution coefficients of the pollution source position information are transformed to obtain real-time pollution source position information;
training a pollution source detection network model based on a training sample set reconstructed by the integrated pollution source position information and the real-time pollution source position information and the types of the included pollution substances;
based on the trained pollution source detection network model, inputting the position information of the pollution source to be predicted and the reference pollutant information marked with the type of the pollutant into the pollution source detection network model, and determining the type of the pollutant included in the position information of the pollution source to be predicted, wherein the type of the pollutant includes: metal pollution, chemical pollution, slag building pollution and sewage pollution are used for assisting in identifying the characteristics of different degrees of environmental pollution of pollutants;
the method for transforming the display pollution coefficients of the pollution source position information according to the distribution condition required to be met by displaying the distribution condition of the pollution coefficients to obtain the real-time pollution source position information comprises the following steps:
determining a display pollution coefficient which is defective according to the display pollution coefficient of the pollution source position information compared with the distribution condition according to a value space where the display pollution coefficient of at least one type of the pollution source position information is located and the distribution condition satisfied by the value space;
converting the display pollution coefficient of the pollution source position information into the display pollution coefficient of the defect to obtain real-time pollution source position information;
the training pollution source detection network model comprises:
initializing a pollution source detection network model;
initializing a distance calculation layer, a full connection layer and a classification layer which are sequentially connected with the pollution source detection network model to obtain a combined pollution source detection network model for classifying the information of the position of the pollution source to be predicted, and inputting the pollution and the corresponding types included in the training sample set into the pollution source detection network model for iterative computation until the loss function of the pollution source detection network model meets the convergence condition;
the method includes the steps of inputting position information of a pollution source to be predicted and reference pollutant information marked with the type of the pollutant into the pollution source detection network model based on the trained pollution source detection network model, and determining the type of the pollutant included in the position information of the pollution source to be predicted, and the method includes the following steps:
in a combined pollution source detection network model, extracting pollution characteristics of pollution source position information to be predicted and pollution characteristics of reference pollutant information marked with the types of pollutants by using the combined pollution source detection network model, wherein the reference pollutant information is the concentrated pollution of the training sample;
determining an error vector of the pollution characteristics of the to-be-predicted pollution source position information and the pollution characteristics of the reference pollutant information, and performing down-sampling processing on the error vector;
and mapping the error vector after the down-sampling processing to a specific value space to obtain the probability that the position information of the pollutant source to be predicted belongs to the type of the pollutant marked by the reference pollutant information.
2. The method for treating construction sewage according to claim 1, wherein the integrating of the display pollution coefficient of the pollution source location information satisfies a value condition, comprising:
detecting a contaminated region of a contaminant included in the contaminant source location information;
and integrating the position of the pollution source position information until the position of a pollution area of the pollutant included in the pollution source position information is consistent.
3. The method for treating construction sewage according to claim 1, wherein the integrating of the display pollution coefficient of the pollution source location information satisfies a value condition, comprising:
and carrying out pollution enhancement treatment on each color channel of the pollution source position information based on the pollution identification degree which needs to be met by the pollution source position information.
4. The method for treating construction sewage according to claim 1, wherein the integrating of the display pollution coefficient of the pollution source location information satisfies a value condition, comprising:
removing uncontaminated areas of corresponding pollutants in the position information of the pollution sources;
and integrating the position information of the removed pollution source to accord with a preset position.
5. The method of claim 1, wherein before training the pollution source detection network model, the method further comprises, based on the integrated pollution source location information and the real-time pollution source location information, reconstructing a training sample set and the types of included pollutants, the method further comprising:
and reconstructing a training sample set based on the integrated pollution source position information and the real-time pollution source position information in pairs.
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